Report No. 68447-RU Russian Federation Export Diversiï¬?cation through Competition and Innovation: A Policy Agenda April 2013 Private and Financial Sectors Development Unit Europe and Central Asia Region Document of the World Bank Acronyms BEEPS Business Environment and Enterprise Performance Survey BCPS Brazilian Competition Policy System BRIC Brazil, Russia, India, and China ECA Europe and Central Asia EM Extensive Margin EU European Union FAS Federal Antimonopoly Service FDI Foreign Direct Investments GDLN Global Development Learning Network GDP Gross Domestic Product GRP Gross Regional Product ICT Information and Communication Technology IM Intensive Margin IP Intellectual Property IT Information Technology OECD Organization for Economic Co-operation and Development PCMs Price-Cost Margins RAS Russian Academy of Sciences R&D Research and Development RCA Revealed Comparative Advantage RPA Revealed Patent Advantage RVC Russian Venture Company RZD Russian Railways SDE Secretariat of Economic Law of the Ministry of Justice SMEs Small and medium enterprises SOEs State-Owned Enterprises TFP Total Factor Productivity TTOs Technology Transfer Offices UKF Unity through Knowledge Fund UNESCO United Nations Educational, Scientific and Cultural Organization VAT Value Added Tax VEB Vneshecombank WTO World Trade Organization Vice President: Philippe H. Le Houerou Country Director: Michal Rutkowski Sector Director: Gerardo Corrochano Sector Manager Paloma Anos Casero Task Team Leaders: Paulo Correa and Donato De Rosa Foreword and Acknowledgments This study builds on three technical notes: Analysis of Selected Trade Outcomes in the Russian Federation, Competition and Competition Policy in the Russian Federation, and Commercializing Public Research in Russia: Scaling up the Emergence of Spinoff Companies—and a background paper “Econometric Analysis of the Russian Investment Climate.â€? The study was cofunded by the Trust Fund Grant from the multidonor Diagnostic Facility for Shared Growth. Key findings have been shared and discussed with the Russian government in three Global Development Learning Network (GDLN) workshops focusing on each technical note. The study was prepared by a World Bank team led by Paulo Correa and Donato De Rosa, and including Guillermo Arenas, Carolina Austria, Sylvie Bossoutrot, Paul Conway, Jose Luis Guasch, Juan Julio Gutierrez, Mariana Iootty, Martha Licetti, Dragana Pajovic, Jorge Peña, Ljudmila Poznanskaya, Igor Pilipenko, Jose Guilherme Reis, Jose-Daniel Reyes, Alina Tourkova, and Yana Ukhaneva. The study was prepared under the guidance of Pedro Alba (Country Director, ECCU1), Gerardo Corrochano (Director, ECSPF) and Sophie Sirtaine (Sector Manager, ECSF2). Frank Sader and David Rosenblatt (World Bank), Geoff Barnard (OECD), and Natalia Volchkova (CEFIR) were peer reviewers for the study. Valuable comments were provided by Zeljko Bogetic, Matthias Grueninger, William Liefert, Tatyana Ponomareva, Jean-Luis Racine, Natalya Shagaida, and Stepan Titov. The team is also grateful for the input from the participants in the three GDLN workshops at the Ministry of Economic Development of the Russian Federation, particularly Alexandr Pirozhenko, Director, Department of Competition Promotion, and Natalia Larionova, Director, Department of SME Development. We would also like to thank the other workshop participants: Russian regional representatives and participating speakers Elena Boutrimova, Miguel Camacho, Jorge Duarte de Oliveira, Carlos Gutierrez, Ann Penistan, Russell Pittman, Elizabete Serodio, and Mariana Tavares. The GDLN activities were coordinated by Francois Nankobogo, with contributions from Mikhail Bunchuk. iii Contents Foreword and Acknowledgments ............................................................................................................. iii Main Findings and Policy Recommendations .......................................................................................... x Russia’s trade performance has a narrow product base and untapped trade potential ............................................ x Productivity, innovation, and competition are core factors explaining Russia’s narrow export base and limited use of its export potential ......................................................................................................................................xi Productivity is affected by about 20 investment climate factors, including innovation and competition............ xii Russia’s highly restrictive product market regulations hamper productivity and export diversification............. xii Lack of entrepreneurship and low commercialization of public research limit the emergence of new products with export potential ........................................................................................................................................... xiii A strategy for export diversification in Russia should incorporate the conditions for the emergence of productive and innovative firms ..........................................................................................................................xiv Continued reform of the innovation system will increase firm-level R&D and commercialization of public research, possibly unleashing entrepreneurship.................................................................................................... xv Reducing the remaining anti-export bias of Russia’s trade policy and aligning export promotion strategies with international best practices will further enable export diversification .................................................................. xv Overview ...................................................................................................................................................... 1 Trade Performance of the Russian Federation ........................................................................................................ 2 Binding Constraints to Export Diversification – Firm-Level Evidence ................................................................. 6 Competition and Competition Policy ................................................................................................................... 13 Entrepreneurship, Innovation, and Research Commercialization ......................................................................... 18 Policy Implications ............................................................................................................................................... 22 References ............................................................................................................................................................ 33 Chapter 1: Analysis of Selected Trade Outcomes in the Russian Federation .................................... 36 Orientation and Growth of Trade ......................................................................................................................... 37 Diversification ...................................................................................................................................................... 44 Quality .................................................................................................................................................................. 49 Survival ................................................................................................................................................................ 53 Policy Options for Export Diversification in Russia ............................................................................................ 55 References ............................................................................................................................................................ 71 Chapter 2: Competition and Competition Policy in the Russian Federation ..................................... 74 Performance and Competition of the Russian Federation: How does Russia compare with other economies in the region? ............................................................................................................................................................ 77 Factors Affecting Competition in Russia ............................................................................................................. 82 Characteristics of Competition and Regulatory Conditions in Selected Russian Sectors................................... 102 References .......................................................................................................................................................... 113 Chapter 3: Commercializing Public Research in Russia: Scaling up the Emergence of Spinoff Companies ............................................................................................................................................... 114 Russia’s Innovation System and Commercialization Efforts ............................................................................. 114 Challenges in Russia’s Innovation System ......................................................................................................... 120 Human Capital .................................................................................................................................................... 124 Russia’s Intellectual Property Legal Framework................................................................................................ 128 Early-stage Financing ......................................................................................................................................... 136 References .......................................................................................................................................................... 139 Annex A: The World Bank Enterprise Survey – Data and Methodology ......................................... 141 Annex B: The Agricultural Sector in the Russian Federation ............................................................ 143 Annex 1A: A Note on the Gravity Model .............................................................................................. 151 Annex 1B: An Extended Version of the Product-space Analysis........................................................ 154 iv Annex 1C: A Note on Regional Performance of Exports .................................................................... 160 Annex 2A: Price-cost Margin Calculations .......................................................................................... 163 Annex 3A: List of Persons Interviewed during the Mission, October–November 2010 ................... 169 Annex 3B: Revealed Technological Advantage and Nanotechnology in Russia ............................... 170 Annex 3C: Patent filings of Russian applicants by federal district, 2009 .......................................... 172 Annex 3D: Start-ups related to the Federal Law 217, dated August 2, 2009 .................................... 175 v Figures Figure 1 Decomposition of export growth, 2000–08 .................................................................................... 3 Figure 2 Comparative advantage and the product space in the BRICs, 2006–08 ......................................... 4 Figure 3 Russia’s unexplored markets .......................................................................................................... 5 Figure 4 BRIC export relationships .............................................................................................................. 5 Figure 5 Exports relative to endowment, 1993 ............................................................................................. 6 Figure 6 Exports relative to endowment, 2003 ............................................................................................. 6 Figure 7 Contributions of measured variables to export propensity (%) ...................................................... 7 Figure 8 Percentage absolute contributions of TFP to the probability of exporting ..................................... 8 Figure 9 Contributions of measured variables to aggregate logTFP (%) .................................................... 11 Figure 10 Contributions of measured variables to the propensity of investing in R&D (%) ...................... 13 Figure 11 Overall product market regulations indicator, Russia and comparator economies, 2008 .......... 14 Figure 12: Subindicator: Barriers to Trade and Investment and State Control, Russia and comparator economies, 2008 ......................................................................................................................................... 14 Figure 13: Distribution of observed price-cost margins in manufacturing (Russia and selected ECA countries) .................................................................................................................................................... 15 Figure 14 Concentration levels in selected Russian industries, by region (Herfindahl-Hirschman Index) 15 Figure 15 Total entrepreneurship activity, 2006 ......................................................................................... 19 Figure 16 R&D patents granted versus GDP per capita, 2008 ................................................................... 20 Figure 17 Science and engineering journal articles per researcher in Russia ............................................. 20 Figure 18 Characteristics of Russian TTOs, 2010 ...................................................................................... 22 Figure 1.1 Openness to trade, 1996–98....................................................................................................... 38 Figure 1.2 Openness to trade, 2006–08....................................................................................................... 38 Figure 1.3 Compound average growth rate, BRICs, 1998–2008 ................................................................ 39 Figure 1.4 Change in dependence of oil and gas ........................................................................................ 40 Figure 1.5 Russia’s export and import of services (% of GDP).................................................................. 41 Figure 1.6 Trade in services, BRICs (1994=1) ........................................................................................... 41 Figure 1.7 Russia’s nonoil export destinations, 2000 ................................................................................. 42 Figure 1.8 Russia’s nonoil export destinations, 2009 ................................................................................. 42 Figure 1.9 Russia’s oil and gas export destinations, 2000 .......................................................................... 43 Figure 1.10 Russia’s oil and gas export destinations, 2009 ........................................................................ 43 Figure 1.11 Total exports, Russia, 2006–08 ............................................................................................... 43 Figure 1.12 Nonoil exports, Russia, 2006–08 ............................................................................................. 43 Figure 1.13 RCA, BRICs, 1996–98 and 2006–08 ...................................................................................... 44 Figure 1.14 Herfindahl-Hirschman Index for products, BRICs, 1998 and 2008 ........................................ 45 Figure 1.15 Herfindahl-Hirschman Index for markets, BRICs, 1998 and 2008 ......................................... 45 Figure 1.16 Growth orientation of markets ................................................................................................. 46 Figure 1.17 Growth orientations of products .............................................................................................. 46 Figure 1.18 Export destinations by product, 2000 ...................................................................................... 47 Figure 1.19 Export destinations by product, 2008 ...................................................................................... 47 Figure 1.20 Intensive and extensive margin in products, BRICs, 1998–2008 ............................................ 48 Figure 1.21 Intensive and extensive margin in markets, BRICs, 1998–2008 ............................................. 48 Figure 1.22 Russia’s decomposition of export growth, 2000–08 ............................................................... 48 Figure 1.23 Change in export sophistication, BRICs.................................................................................. 49 Figure 1.24 Comparative advantage and the product space, BRICs, 2006–08 ........................................... 52 Figure 1.25 Export relationships, BRICs, 1999–2008 ................................................................................ 53 Figure 1.26 Exports relative to endowment, 1993 ...................................................................................... 54 Figure 1.27 Exports relative to endowment, 2003 ...................................................................................... 54 Figure 1.28 Death of exports, 2003............................................................................................................. 54 Figure 1.29 New exports, 2003 ................................................................................................................... 54 vi Figure 1.30 Relative importance of TFP, international connectivity (exports and FDI), innovation, competition, and the investment climate in explaining firms’ behavior in Russia (%) .............................. 59 Figure 1.31 Percentage absolute contributions of TFP to the probability of exporting, by country ........... 60 Figure 1.32 Percentage absolute contributions of quality and innovation to the probability of exporting . 61 Figure 1.33 Tariffs in the BRICs ................................................................................................................ 63 Figure 1.34 Overall Trade Restrictiveness Index among the BRICs .......................................................... 64 Figure 1.35 Average full-time permanent employees by country, various years ....................................... 66 Figure 2.1 Competition indicators, 2010 .................................................................................................... 77 Figure 2.2 Indicators of Product Market Regulation, selected European countries, 2008 .......................... 78 Figure 2.3 Trade Restrictiveness Index, 2008............................................................................................. 79 Figure 2.4 Distribution of observed PCM in manufacturing, Russia and selected ECA countries............. 80 Figure 2.5 Mean PCM across countries by sector – index number ............................................................ 81 Figure 2.6 Regional price levels, adjusted for GRP per capita, distance, and time and product fixed effects .................................................................................................................................................................... 83 Figure 2.7 Price variation among regions for selected products, adjusted for GRP per capita, distance to district center, average household consumption, and time fixed effects ..................................................... 83 Figure 2.8 Number of dominant firms in regional markets ........................................................................ 90 Figure 2.9 Concentration levels in selected Russian product markets, Herfindahl-Hirschman Index ........ 91 Figure 2.10 Concentration levels in selected Russian industries, by region – Herfindahl-Hirschman Index .................................................................................................................................................................... 92 Figure 2.11 State participation in selected industries (% of shareholding) ................................................. 94 Figure 2.12 State aid applications and GRP per capita by region, 2009 ..................................................... 96 Figure 2.13 State aid applications by region, 2009 ..................................................................................... 97 Figure 2.14 Number of property state aid applications approved, 2009 ..................................................... 98 Figure 2.15 Distribution of tax arrears by region as a share of tax revenues (%) ....................................... 98 Figure 2.16 Tax arrears in selected regions as a share of tax revenues, 2010 (%)...................................... 98 Figure 2.17 Competition cases 2009 – anticompetitive actions of government vs. anticompetitive practices .................................................................................................................................................................. 100 Figure 2.18 Procurement complaints and violations, 2008–09 ................................................................ 101 Figure 2.19 Violations by type, 2008–09 .................................................................................................. 101 Figure 2.20 Number of transport segments with SOEs............................................................................. 103 Figure 2.21 Share of assets of foreign-owned banks ................................................................................ 107 Figure 2.22 Change in number of business entities in sectors in Russia, 2008 to 2009 (%) .................... 109 Figure 2.23 Dealing with construction permits ......................................................................................... 111 Figure 3.1 Cost of patenting and gross R&D expenditures, 2008 ............................................................ 115 Figure 3.2 Science and engineering journal articles per researcher .......................................................... 115 Figure 3.3 Total researchers per thousand total employment ................................................................... 116 Figure 3.4 Evolution of R&D investments and number of researchers, 1996–2008 ................................ 117 Figure 3.5 Russia’s RTA, 2002–07 ........................................................................................................... 118 Figure 3.6 R&D expenditures for selected countries by source of funds, 2009 ....................................... 120 Figure 3.7 Russian R&D by character of work, 2000–09 ......................................................................... 123 Figure 3.8 Share of all new university degrees awarded in science or engineering, 2007........................ 125 Figure 3.9 TTO personnel payment system, 2010 .................................................................................... 134 Figure 3.10 Sources of TTO income, 2010 ............................................................................................... 134 Figure 3.11 Additional services provided by TTO or parent institution, 2010 ......................................... 134 Figure B.1 Structure of agricultural land in 2009 (%) .............................................................................. 143 Figure B.3 Sectoral composition of value added (percent of GDP).......................................................... 144 Figure B.4 Employment distribution (percent) ......................................................................................... 144 Figure B.5 Total crops produced (million tons) ........................................................................................ 144 Figure B6 Main wheat exporters ............................................................................................................... 146 Figure B7 Wheat production and price ..................................................................................................... 146 vii Figure B.8 Cost and output of wheat, Russia and Canada ........................................................................ 146 Figure 1A.1 Russian exports to China, 2006–08 ...................................................................................... 152 Figure 1A.2 Total exports Figure 1A.3 Nonoil and nongas exports .................................................... 153 Figure 1B.1 Comparative advantage and the product space, Russia, 2006–08 ........................................ 154 Figure 1B.2 Russia’s competitive products, 1992/94–2006/08 ................................................................ 156 Figure 1B.3 Russia’s emerging products, 1992/94–2006/08 .................................................................... 157 Figure 1B.4 Russia’s marginal products, 1992/94–2006/08 ..................................................................... 158 Figure 1B.5 Russia’s declining products, 1992/94–2006/08 .................................................................... 159 Figure 1C.1 Regional share of total exports, 2006 and 2009 (%) ............................................................. 160 Figure 1C.2 Regional share of nonoil exports, 2006 and 2009 (%) .......................................................... 160 Figure 1C.3 Regional share of nonoil export growth, between 2006 and 2009 (%) ................................. 160 Figure 1C.4 Sector RCA in the Central Region, 2006 and 2009 .............................................................. 161 Figure 1C.5 Sector RCA in the Central-Chernozem Region, 2006 and 2009 .......................................... 161 Figure 1C.6 EU share in total exports, 2006 and 2009 (%) ...................................................................... 161 Figure 1C.7 United States share in total exports, 2006 and 2009 (%) ...................................................... 161 Figure 1C.8 Herfindahl-Hirschman Index for markets, by region, 2006 and 2009 .................................. 162 Figure 1C.9 Number of markets with exports of at least US$1 million, 2009.......................................... 162 Figure 2A.1 Price analysis in Russian regions by product, all products analyzed (%) ............................. 165 Figure 2A.1 Price analysis in Russian regions by product, all products analyzed (%) (cont’d.) .............. 166 Figure 2A.1 Price analysis in Russian regions by product, all products analyzed (%) (cont’d.) .............. 167 Figure 2A.1 Price analysis in Russian regions by product, all products analyzed (%) (cont’d.) .............. 168 Table Table 1 Age of researchers by educational attainment ............................................................................... 21 Table 1.1 Russian exports, 2000–09 ........................................................................................................... 38 Table 1.2 Russian crude oil exports, 2000–09 ............................................................................................ 39 Table 1.3 A.T. Kearney offshoring rankings, BRICs, 2007 ....................................................................... 41 Table 1.4 A.T. Kearney offshoring rankings, Central and Eastern European countries, 2007 ................... 42 Table 1.5 Correlations between market destinations (product) shares and world demand (slopes), BRICs .................................................................................................................................................................... 46 Table 1.6 Top 10 nonextractive export products, 2008 .............................................................................. 50 Table 1.7 Markets served by top 10 nonextractive export products, 2000–08 ........................................... 51 Table 1.8 Diversification drivers in a panel dataset, 87 countries, 1990–2004, ......................................... 56 Table 1.9 Structure of the effectively applied tariff, Russia ....................................................................... 63 Table 1.10 Effectively applied tariff (simple means).................................................................................. 64 Table 1.11 Producers’ export participation (% of firms that export) .......................................................... 66 Table 1.12 Minimum productivity threshold to export (Solow residual), selected countries ..................... 67 Table 1.13 Minimum productivity threshold to export (revenue-based labor productivity), selected countries ...................................................................................................................................................... 67 Table 1.14 Share of exporters by size ......................................................................................................... 68 Table 1.15 Probability of inspection by tax officials .................................................................................. 69 Summary of policy options ......................................................................................................................... 76 Table 2.1 Price comparisons analysis – Russia vs. Commonwealth of Independent States countries ....... 80 Table 2.2 Mean values for selected variables in Russia and the other ECA countries, by sector ............... 86 Table 2.2 Mean values for selected variables in Russia and the other ECA countries, by sector (cont’d.) 87 Table 2.3 Cross-sector variation in mark-up differential between Russia and the ECA region ................. 88 Table 2.4 Breakdown of manufacturing sectors according to market structure characteristics in Russia .. 89 Table 2.5 Presence of SOEs ........................................................................................................................ 93 Table 2.6 Government participation in selected sectors ............................................................................. 93 Table 2.7 Price controls in air transport, 2011 .......................................................................................... 103 Table 2.8 Regulation in air transport, 2011 .............................................................................................. 104 viii Table 2.9 Price controls in maritime transport services, 2011 .................................................................. 105 Table 2.10 Regulations in road transport, 2011 ........................................................................................ 105 Table 2.11 Bank assets and ownership of the 10 largest banks in Russia, 2008....................................... 107 Table 2.12 H-statistics and Lerner indices for BRICs .............................................................................. 108 Table 2.13 Factors restricting business activities of construction companies (% of respondents) ........... 109 Table 3.1 Gross domestic expenditure on R&D in priority areas of science, technology, and engineering by source of funding, 2007 (thousand US$) ............................................................................................. 119 Table 3.2 R&D by funding source and performer, 2007 .......................................................................... 121 Table 3.3 Number of institutions, personnel by performing sector .......................................................... 122 Table 3.4 Age of researchers by educational attainment .......................................................................... 125 Table 3.5 Foreign science and engineering PhD recipients in the United States and share staying there 126 Table 3.6 R&D personnel by educational attainment and field of science, 2007 ..................................... 126 Table 3.8 Enterprises created by academic departments and RDIs related to the Federal Law 217, August 2, 2009 ..................................................................................................................................................... 130 Table 3.9 Registration of license contracts and patent assignment contracts ........................................... 131 Table A.1 Structure of equations system .................................................................................................. 141 Table A.2 Contribution of the investment climate (explanatory variables) to the dependent variables of the equation ..................................................................................................................................................... 142 Table B.1 Area under crops in Russia (percent) ....................................................................................... 143 Table B.2 Top 10 production, 2008 (thousands of tons)........................................................................... 145 Table B.3 Top 10 exports, 2008 (thousands of tons) ................................................................................ 145 Table B.4 Structure of agricultural output, current prices ........................................................................ 146 (%of total) ................................................................................................................................................. 146 Table 2A.1 Price analysis in Russian regions (complete list) ................................................................... 164 Table 3A.1 Russian patent specialization and patent applications by field of technology, 2002–06 ....... 171 Boxes Box 1 The investment climate and the intensity of exports ........................................................................ 10 Box 2 Price controls and other government interventions in Russian agriculture ...................................... 17 Box 3 The case of soybean exports in Brazil .............................................................................................. 25 Box 4 Competition policy in action: the Australian experience ................................................................. 29 Box 1.1 Measuring export sophistication ................................................................................................... 50 Box 2.1 State aid in the news ...................................................................................................................... 95 Box 2.2 Reasons for rejection of state aid applications ............................................................................ 100 Box 2.3 Procurement and competition policy in Brazil ............................................................................ 102 Box 2.4 Rail transport anticompetition cases............................................................................................ 104 Box 2.5 Restrictions of professional associations ..................................................................................... 106 Box 2.6 Anticompetitive behavior of regional authorities in construction markets ................................. 110 Box 3.1 Croatia’s Unity through Knowledge Fund .................................................................................. 128 Box 3.2 Commercializing the discoveries of Russian weapons scientists ................................................ 135 Box 3.3 The Russian Venture Company ................................................................................................... 137 Box B.1 Evolution of Russia’s tariffs quotas (TRQs) for meat ................................................................ 148 ix Main Findings and Policy Recommendations Russia’s trade performance has a narrow product base and untapped trade potential x Petroleum and natural gas dominated Russia’s exports over the last decade, with the sector experiencing double-digit annual export growth and accounting for almost 65 percent of Russia’s export value in 2009 – an outcome of higher commodity prices and export volumes. Export growth rates of the nonoil and gas sector were also notable. Such industries as machinery, electronics, transportation equipment, and chemicals reached a combined growth rate in export value of 10 percent. This more positive comparison, however, hides important structural limitations in Russia’s trade performance. x A closer look at Russia’s trade composition indicates a narrow product base and a lack of diversification toward new markets and products. Decomposition of export growth from 2000 to 2008 highlights how flows of existing products to old trading partners accounted for 88.4 percent of the growth in Russian exports. This was offset by declining exports to existing markets (–4.3 percent) and by the extinction of exports of existing products in existing markets (–3.2 percent). Exports of old products to new markets increased over the decade (19.0 percent). These figures hint at Russia’s inability to expand its export base to new markets and products. x Moreover, Russia’s revealed comparative advantage seems concentrated in the “peripheryâ€? of the product-space map, which may limit its potential for export diversification.i The product space includes among its 97 products such industries as raw materials (26 products) and forestry (11 products). (At the center of the product space are industries such as metallurgy, vehicles, and machinery, in which Russia does not show comparative advantages.) Such specialization is sometimes considered problematic because the capabilities developed in those sectors are not easily redeployed to other industries, hindering economic diversification. Yet several resource-rich countries have managed to expand their comparative advantages beyond their traditional, natural resource–intensive products. x Russian firms are, on average, larger than the average firm in the Europe and Central Asia (ECA) region, but too few firms export. Only a minority of firms in an economy export. Yet, according to the World Bank’s 2009 Enterprise Survey, the share of exporting firms in Russia in 2009 (6.9 percent) was far lower than in India in 2006 (12.5 percent), Brazil in 2009 (18.1 percent), and China in 2003 (24.5 percent). The comparison with India and Brazil is especially striking because both are continental economies with only moderate trade integration. This low export-participation ratio runs across industries and is still an issue when comparing Russia with more developed economies. x Exporters face difficulties not only entering foreign markets but also sustaining their presence in them. Analysis of over 40,000 export relationships (country-product pairs with at least one year of exports with a value of at least US$1,000) in 1999–2009 reveals that only 57 percent of export events in Russia survived more than two years. In China the export survival rate was more than 70 i Product-space analysis is based on the tools pioneered by Hidalgo and others (2007). The position of a product on the product-space map determines the products to which companies in that economy may be able to produce related products, based on the existing set of capabilities available and the location of corresponding products on the map. The process of accumulating specific capabilities therefore results in diversification and economic development. x percent. Brazil and India also performed better than Russia (but worse than China). Some export “mortalityâ€? is common internationally, but the comparatively low export survival rates in Russia provide further evidence of the lack of international competitiveness in the nonoil and gas sector. x As a result, Russia is not fully tapping into its existing trade potential (trade opportunities given the country’s current structural conditions). An analysis based on a gravity model that includes 130 of Russia’s trading partners indicates that Russia undertrades with China and India, as well as with several G-8 countries, including the United States, Italy, and Germany. More interestingly, the number of countries with which Russia seems to be undertrading rises when the oil and gas industries are excluded from the model. Indeed, despite China’s increase in its share of global trade, its share in Russia’s total exports remained at around 4–5 percent over 1998–2008. x While macroeconomic variables such as the exchange rate play a central role in determining export performance, this report focuses on the microeconomic, firm-level factors reducing the propensity of Russian firms to export. Internationally, the entry of new exporters has been a driving force behind several export booms. In Chile, for instance, 64 percent of the increase in exports over 1990–2007 was accounted for by the entry of new exporters, rather than by an increase in exports by existing exporters (export intensity). Microeconomic factors related to the business environment affect firms’ profitability and – given that firms differ in productivity – their ability to export. These factors may be preventing Russia from expanding its export base and from tapping into existing trade opportunities. Productivity, innovation, and competition are core factors explaining Russia’s narrow export base and limited use of its export potential x Our exploratory study of Russia’s investment climate finds that firms’ productivity levels, firms’ innovation performance, and the level of domestic competition are the main microeconomic determinants of the country’s export propensity. Total factor productivity is a less important determinant of export intensity, while domestic competition and firm-level research and development (R&D) remain significant, along with red tape, corruption, and labor skills. This is consistent with the notion that higher productivity is crucial for helping firms cover the fixed costs associated with entering new markets but less important for expanding existing export relationships. Preliminary findings from our trade analysis show that fixed costs to export are on average higher in Russia than in comparator countries (though variable export costs are at the same level). x Beyond productivity, innovation, and competition, other obstacles to higher export propensity should also be considered. For instance, firms with a higher number of power outages per month or with higher shares of electricity coming from a generator are less likely to enter foreign markets. Businesses spending more time dealing with bureaucratic issues show lower export propensity, indicating the relevance of the regulatory environment. Moreover, firms that purchase a higher share of their input on credit (after delivery) – which we interpret as evidence of cash-constrained companies – are less likely to export. x The importance of productivity, innovation, and competition to export propensity is not unique to Russia. Productivity is shown to be significant and most important for export propensity in a xi sample of 19 countries, including Brazil, South Africa, and Turkey. A number of studies relate higher R&D expenditures and product innovation to higher export performance – as in small, nonexporting firms in Germany and Spain, for example. And our results on the important contribution of competition are consistent with the argument that strong rivalry in domestic markets strengthens the capacity of local firms to compete abroad. This argument is corroborated by the experience of Chile, India, Indonesia, and Japan. In Russia, the combined (absolute) contribution of competition variables amounts to more than 15 percent of the probability of exporting – with price increases in domestic markets (a sign of monopoly power) making firms less likely to export. Yet firms’ productivity and innovative performance depend on overall investment climate conditions. Productivity is affected by about 20 investment climate factors, including innovation and competition x About 20 different factors, rather than 15 for export propensity, are relevant to firm productivity, including technological capacity and entrepreneurship. Technological upgrades – the proportion of staff with access to a computer, import activity, and quality certification (an indication of technical conformity) – appear to be among the most important investment climate factors. Consistent with the complementary relationship between skills and technology, the supply of training by firms appears to be another key strategy for increasing business productivity. Of particular relevance is the experience of the manager, which we interpret as evidence of the role of business-related skills for firm productivity in Russia. Moreover, firms developing new products or services show higher productivity levels. x Intensity of domestic competition is important for productivity. Firms subject to informal competition (the gray market) show lower productivity. Public subsidies, too, seem to be associated with lower productivity – an apparent contradiction, in principle, with the goals of state aid. All these factors tend to distort competition and have an adverse impact on productivity. In fact, the Olley and Pakes decomposition of Russia’s productivity shows that the current contribution of the allocative efficiency component (how much of the output is commanded by the more productive firms) to aggregate productivity in the country (about 20 percent) corresponds to half the value for Brazil in the early 2000s. By creating a more level playing field, competition policy in Russia could help increase productivity and thus export diversification. Russia’s highly restrictive product market regulations hamper productivity and export diversification x State ownership is twice as high in Russia as in 10 countries in the European Union, with state-owned enterprises accounting for about 17 percent of employment. Data indicate that national, state, or provincial government controls at least one firm in 16 of 19 sectors – a figure much higher than the averages for the Organisation for Economic Co-operation and Development (OECD), where the typical member economy registers government participation in only 9 of the same sectors. The Transition Indicators from the European Bank for Reconstruction and Development also show that enterprise restructuring in Russia is lagging behind that of Poland, Turkey, and the average in the ECA region. xii x State aid seems to favor larger, less productive incumbent companies over smaller, more efficient firms. State aid (as loans, subsidies, or tax cuts, for example) is often applied unevenly across regions, sectors, and firms. According to the World Bank Trade Restrictiveness Index, incumbent firms in Russia are more insulated from international competition, especially through nontariff barriers in the form of technical regulations and quantitative restrictions, than in most comparable countries. Actions of regional governments also influence competition conditions in domestic markets. x Analysis of market structure in Russia at the geographic and product market levels also reveals a high degree of concentration, with significant variations across regions and sectors. A related problem is market fragmentation: the 2009 World Bank Enterprise Survey shows that 50 percent of Russian firms considered local markets their main sales destination – a large number, even compared with large economies such as Brazil (35 percent). Despite the size of the Russian economy, isolation from global markets may induce companies to choose less modern technology and operate at suboptimal scales. x One implication of limited import competition in Russia is market dominance. Price-cost margins for inputs of exportable goods in Russia tend to be larger than those of their international peers, reducing the incentive of local exports. Russian firms register larger price-cost margins than the average for the region in every manufacturing sector except food, garments, and chemicals. A more detailed analysis reveals that firms in sectors where Russia registers higher price-cost margins than its regional counterparts tend to be older and larger, are less likely to export and invest in R&D, and are more likely to operate in local markets. Lack of entrepreneurship and low commercialization of public research limit the emergence of new products with export potential x Despite its importance to export propensity, business R&D has been declining in recent years. Russia’s business R&D expenditures slipped from a high of 0.88 percent of GDP in 2003 to 0.65 percent in 2008. The equivalent figure for OECD countries increased from 1.49 percent to 1.63 percent over the same period. As shown by our econometric results, the propensity of Russian firms to engage in R&D depends on a number of investment climate factors that are only partly affected by innovation policies. For instance, firm productivity levels, investments in information and communications technologies, skills, and the manager’s experience – proxies for entrepreneurship and business knowledge – are all important. x More broadly, entrepreneurship in Russia is below that expected for the country’s development level. Limited entrepreneurship is closely related to poor governance and weak institutional regimes in a society that favors the allocation of talent to rent seeking rather than productive activities. About a quarter of management time in Russia is spent on regulation requirements, compared with 7 percent in India, which illustrates how a deficient governance regime leads to misallocation of talent. Yet Russia’s talent pool is large, as indicated by an internationally comparable level of graduates in engineering and science. x The commercialization of public research – potentially another source of innovation – is hampered by various factors. Researchers’ productivity has been declining, and public measures to xiii promote innovation have focused on universities, even though they receive a much smaller share of public R&D investments than research institutes, thus shrinking the research pool from which patents can be obtained and licensed, and spinoff companies created. Funding allocation on a per-head basis, as opposed to performance-based allocation, along with a declining number of middle-career researchers – who are more likely to publish and commercialize research – does not favor research productivity. Discoveries in the defense sector, which could potentially be a major source of civilian innovation, remain inaccessible to the private sector. x Overall conditions for large-scale commercialization processes are gradually improving, but important limitations remain. Despite recent advances in intellectual property legislation, loopholes and uncertainties over the full ownership of discoveries financed by public funding hinder private investments and full development of the commercialization process. Licenses are mostly granted on a nonexclusivity basis, which raises doubts about firms’ capacity to raise capital and carry on with the necessary investments. A gap between the Foundation for Assistance to Small Innovative Enterprises programs and venture capital funding continues to threaten the survival of Russian start-ups, despite recent initiatives to improve early-stage financing in the country. A strategy for export diversification in Russia should incorporate the conditions for the emergence of productive and innovative firms x Our analysis suggests the need to take a broader view of the diversification challenge in Russia, incorporating the conditions for allowing productive and innovative firms to emerge and for achieving a higher probability of firm survival in foreign markets. Raising the share of nonresource exports in Russia has so far proved difficult, reflecting similar difficult experiences elsewhere. There is no magic wand to promote export diversification. Uncovering a strategy that could induce export diversification, given Russia’s institutional and political economy constraints, is therefore likely to be a gradual, interlinked process of recurrent assessments, government learning, consistency with the country’s comparative advantages, and policy attention in each area, rather than a single-shot type of intervention. x Policymakers can help raise the potential of export diversification in Russia by adopting selected innovation and competition policies, alongside productivity-oriented reforms. Export diversification depends on a raft of macro- and microeconomic conditions, including a competitive exchange rate and solid governance system. Yet the government, by boosting competition, improving innovation, and facilitating trade, can enable economic renewal and the capacity of firms to enter international markets. This in turn could trigger a positive cycle of productivity, innovation, and trade integration through feedback effects. Russia’s competition policy should level the playing field, reducing rents in domestic markets and favoring the emergence of more efficient firms. x Leveling the playing field, facilitating entry of more efficient firms, and encouraging orderly exit of less efficient ones would contribute to higher productivity and export propensity. At its core, the policy should promote reduction of state ownership; more uniform, transparent, and results-oriented enforcement of state aid regulations; simplification of the business environment in which firms operate; xiv and competition in service and network industries. As in Australia and the European Union, such a policy could help Russia increase productivity and consolidate its domestic market, enabling the country’s firms to benefit from additional trade gains. Specific measures should include: advancing government reforms of public enterprises, minimizing their distortive impact on the marketplace; broadening the mandate on state aid regulation to diminish firm- and sector-specific state aid; aligning state aid regulation with international best practices; and eliminating preferential treatment to state- or municipality-owned corporations. Sector-specific policies in key service industries (such as transport, construction, and professional services) would further increase competition, promote entry, and reduce the prices of services. Continued reform of the innovation system will increase firm-level R&D and commercialization of public research, possibly unleashing entrepreneurship x The government’s current initiatives to foster innovation could be strengthened through improvements in the innovation system, human capital, and the legal framework for intellectual property. More specific policy options include: results-based management of public research organizations; performance-based career development; strengthened cooperation with Russian researchers abroad; and transfer of ownership rights of intellectual property to research organizations. Funding gaps should be addressed through provision of finance for early-stage development of technologies, matching grants, and differentiated tax breaks for small and medium enterprises. Over the longer term, the government should expand commercialization efforts to new areas with innovative potential, including the Russian Academy of Sciences, the defense sector, and agricultural research; continue to reform the investment climate, focusing on skills and technology adoption and favoring business investments in R&D; and continue to improve the governance of the overall economy to decrease incentives for rent seeking and to incentivize the allocation of talent, entrepreneurship, and innovation. Reducing the remaining anti-export bias of Russia’s trade policy and aligning export promotion strategies with international best practices will further enable export diversification x Efforts to liberalize trade have been one of the highlights of Russia’s economic reform for the past two decades. Parallel to efforts to lower tariffs, reduce quotas, and diminish import subsidies, the country completed its negotiations for accessing the World Trade Organization (WTO), with bilateral market access negotiation completed with interested WTO members, including the United States, and became a member in August 2012. Yet hurdles remain for Russia’s full integration with the rules-based trading system, including increased tariffs (in light of the global economic crisis) in industries such as processed foods, light manufacturing, the automotive sector, and some construction equipment. Adopting a low and uniform tariff structure could benefit an economy that seeks to enhance export diversification through innovation. Moreover, based on our findings of high fixed costs to export in Russia, reducing such costs could provide opportunities to encourage firms to export and to establish new export relationships. Advancing the development of regional coordinating centers would help create new exports and sustain current trade partnerships. xv Overview 1. Economic modernization and export diversification are priorities in the Russian economic policy agenda, with several measures undertaken in recent years to promote growth in the nonoil and gas sector. Yet why some firms succeed in breaking into foreign markets while others do not is far from fully understood. In this chapter, we try to identify the binding constraints to export diversification in Russia. Using firm-level data, we identify which investment climate factors are affecting Russian firms’ propensity to engage in export activities. Results show that lack of competition and entrepreneurial innovation are obstacles to the emergence of new, potentially exportable products. We then discuss what enhanced trade, competition, and innovation policy measures could contribute to export diversification. 2. Russia’s export base has narrowed substantially over the past decade. Oil and natural gas constituted less than half of total exports in 2000. Ten years later, this figure had grown to two-thirds of total exports, with an additional 15 percent coming from other extractive commodities and only 9 percent from high-tech exports, mainly in the defense industry. At the same time, and in contrast to the other BRIC countries,1 Russia currently exhibits revealed comparative advantage (RCA)2 in only two sectors (extractive industries and iron and steel).3 While in part a result of higher commodity prices, this also indicates a loss of export competitiveness of Russia’s nonresource sectors. 3. Lack of diversification cannot be pinned down to a single cause. 4 In addition to the macroeconomic imbalances resulting from the alteration of relative prices between resource and nonresource sectors, poor governance, administrative complexity (red tape), inadequate labor and managerial skills, and difficult access to finance all contribute to hindering the emergence of exporters in nonresource sectors. According to the 2009 Enterprise Survey, for instance, only 12 percent of Russian firms do not identify skills and education of the workforce as a constraint, compared with 40 percent in 2005. At the same time, a mere 30 percent of firms have access to a line of credit or a loan from financial institutions (versus, for example, 65 percent in Brazil).5 4. Competition and innovation are examined in this study as key drivers of export diversification. We propose an interpretation of the challenges of export diversification in Russia in which the lack of competition and entrepreneurial innovation are presented as obstacles to the emergence of new, potentially exportable products, and thereby export diversification. We do this by complementing assessments of trade, competition, and innovation in Russia with the analysis of firm-level data from the 2009 Enterprise Survey, analysis that can be found in chapters 1–3 and a background study on the Russian business environment.  This chapter was prepared by Paulo Correa, Lead Economist, Donato De Rosa, Senior Economist, and Dragana Pajovic, Analyst (all Private and Financial Sector Development, ECA Region, World Bank). 1 BRIC is Brazil, Russia, India, and China. 2 RCA is an empirical indicator of trade specialization. The index is used to calculate the relative advantage or disadvantage of a certain country in a certain class of goods or services as evidenced by trade flows. RCA of exports by sector in Russia and the BRICs is computed using the two- digit HS classification system. Defining Xi and Mi as, respectively, exports and imports, RCA is computed, for each sector i, as: § Xi Mi · RCA i ¨ ¸ ¨ ¦ X k  ¦ M k ¸˜100 © ¹ 3 Brazil, by comparison, shows comparative advantage in the same sectors with the addition of agricultural products and food and beverages. 4 Several recent studies examine the challenge of economic diversification from different perspectives. See, for example, World Bank (2007, 2009, 2011a, 2011b); Bogetic and others (2010); and OECD (2009b). 5 See www.emterprisesurveys.org for data of enterprise surveys conducted worldwide by the World Bank. The 2009 survey for the Europe and Central Asia Region – the Business Environment and Enterprise Performance Survey – was conducted in cooperation with the European Bank for Reconstruction and Development and is used widely in this study. 1 5. After presenting our findings we identify some key trade policy measures that could help firms enter foreign markets and sustain current trade relationships. Preliminary findings from our trade analysis show that in Russia fixed costs and the minimum average productivity level required to export are higher than in most other comparator economies. Reducing such fixed export costs could provide opportunities to encourage firm exports and to facilitate enterprises in establishing new export relationships. In addition, adopting a low and uniform tariff structure could benefit an economy that seeks to enhance export diversification through lowered obstacles to innovation. Finally, there should be a continued effort to promote exports through the regional coordinating centers that support and promote export-oriented small and medium enterprises (SMEs), serving as a single window for trade and investment issues. 6. A comprehensive competition policy would help establish a level playing field, facilitate entry of more efficient firms, and encourage orderly exit of less efficient firms, thereby contributing to increased productivity and export propensity. Specific measures should include: broadening the mandate on state aid regulation to diminish firm- and sector-specific state aid; creating an inventory of state aid; aligning state aid regulation with international best practices; and eliminating preferential treatment to state- or municipality-owned corporations. Sector-specific policies in key service industries (such as transport, construction, and professional services) would further increase competition and incentives for entry and reduce prices of services. 7. The government’s current initiatives to foster innovation could be strengthened through a number of specific measures focusing on commercialization of public R&D and adequate research funding. More specific policy options include results-based management of public research organizations; performance-based career development; transfer of intellectual property rights to research organizations; provision of finance for early-stage development of technologies; matching grants; and differentiated tax breaks for SMEs. The Russian Academy of Sciences, the defense sector, and agricultural research could also be explored as areas with innovation potential. 8. This study is organized as follows. Section II scrutinizes various dimensions of Russia’s trade performance, including export diversification, sophistication, and survival. A detailed analysis of the role of exports, innovation, productivity, and competition on firm performance is presented in Section III. Section IV analyzes the competition environment in Russia, by presenting analyses of price-cost margins, state ownership, and regional and sectoral characteristics of competition, while Section V provides an overview of Russia’s innovation system and proposes measures to increase the impact of R&D on the economy. Section VI concludes and presents policy options. Trade Performance of the Russian Federation 9. Decomposition of export growth shows that Russia has been struggling to diversify its export base to new markets and products. Such decomposition into the margins of trade is informative for identifying the source of export dynamism.6 When examining export growth in Russia from 2000 to 6 Export growth can take place at the intensive margin (selling existing products to existing markets) or at the extensive margin (selling existing products to new markets, new products to new markets, and new products to existing markets). Growth along the intensive margin is a source of export diversification if it is obtained through the increase of the share of nontraditional exports in total exports. There are multiple definitions of the intensive and extensive margins. In this chapter, the concepts are invoked in the context of diversification as well as survival of exports. In the former, the attempt is to explore to what extent Russia has been able to add new products and new markets – that are economically significant – 2 2008, flows of existing products to existing export destinations accounted for 88.4 percent of total export growth (figure 1). This increase was offset by falling exports to existing markets (–4.3 percent) and by the extinction of exports of existing products in existing markets (–3.2 percent). The only significant variation at the extensive margin is the increase of old products in new markets (19.0 percent). While export growth of more developed countries is expected to be concentrated in the intensive margin, this analysis hints at Russia’s deficiency to diversify its export base to new markets and products. Figure 1 Decomposition of export growth, 2000–08 Intensive margins Extensive margins 120.0 100.0 Percent growth 80.0 60.0 88.4 40.0 19.0 20.0 -4.3 -3.2 0.0 0.0 0.0 Increase of Decrease of Extinction of Increase of Increase of Increase of old products old products exports of new products new products old products -20.0 in old in old existing in new in old in new markets markets products to markets markets markets existing markets Components of export growth Source: Authors’ calculations 10. Exports are concentrated in markets that are not growing strongly. How a country’s industry is faring in international competition can be gauged by its share in strategic markets, such as those that are growing (and importing) rapidly. Generally, Russia’s top export partners are not among those that have seen the highest rates of import growth between 2000 and 2008. In fact, Russia shows the lowest correlation between (log) product share and annual world import growth among the BRICs. 11. Russia reveals a comparative advantage mainly in products that have few connections – or potential spillover effects – with other sectors. Computed at the four-digit Standard International Trade Classification level, figure 2 shows the products in which Russia has RCA in 2006–08 (black dots) on the product-space map, alongside the other BRICs.7 to its portfolio. When the two margins are discussed in the context of export survival, the attempt is to decompose export growth into constituents capturing growth of old products in old markets versus the rest. 7 The product-space analysis is based on the tools pioneered by Hidalgo, Klinger, Barabasi, and Hausmann (2007). The position of a product in the product space determines the products to which companies in that economy may be able to produce related products, based on the existing set of capabilities available and the location of corresponding products on the map. The process of accumulating specific capabilities therefore results in diversification and economic development. Revealed comparative advantage of Russia’s product space is here computed at the four-digit Standard International Trade Classification level. 3 Figure 2 Comparative advantage and the product space in the BRICs, 2006–08 Russia Brazil China India Source: Authors’ calculations 12. The product-space analysis of Russia’s export basket reveals three points. x First, Russia’s product-space map has a fairly healthy number of products (97) in which the country has achieved RCA. x Second, the products in which Russia has developed RCA are mostly in the periphery of the product-space map, meaning that they have few connections to other sectors. This implies that gaining comparative advantage in other sectors is more difficult, since the capabilities needed to produce the current export basket are not easily redeployed to other sectors. All the other BRICs have, on the other hand, been somewhat successful in penetrating the core of the product space (especially China), implying that future structural transformation of the export basket could be easier. x Third, new products in which Russia has developed RCA are in the same or very similar sectors as its “classicâ€? exports. These are mainly resource-based commodities like raw materials, forestry products, cereals, and oil and gas, indicating that over the last 15 years Russia has been largely stuck in the same export sectors (figure 3). However, the country also developed comparative advantage in some nonresource industries like capital-intensive goods and chemicals. 4 Figure 3 Russia’s po markets unexplored ed cted ctua ts 20 Log of Predicted Exports, 2006-2008 CHN DEU IND USA ITA JPN 15 BRA 10 5 8 10 12 14 16 18 Log of Actual Exports, 2006-2008 Source: Authors’ calculations 13. There may be untapped potential to increase exports within the existing product space. Analysis of Russia’s total exports, based on a gravity model of Russia and over 130 of its trading partners, indicates that Russia undertrades with India, China, and several G-8 countries, including the United States, Italy, and Germany (located above the 45-degree line in figure 3). 8 The number of countries rises significantly when the oil and gas industries are excluded from the model. This result suggests that there is scope for exploring other opportunities for export diversification in Russia. 14. Russia’s exports also seem to suffer from premature “death.â€? The probability of Russian export relationships surviving until the second year is about 0.57 (on a scale of 0–1) and of maintaining a relationship for five years is 0.22 (figure 4). In comparison, the survival rates of the export relationships of the other BRICs are much higher, particularly in China, where the survival rate is roughly 0.70 for the first two years. This result suggests that export diversification strategies in Russia should pay particular attention to the factors affecting the survival of new exports (export discoveries). Figure 4 BRIC export relationships Survival Rate 1999-2008 1 .8 probability .4 .6 .2 0 0 5 10 Analysis Time Russia Brazil China India Source: Author’s calculations 15. This may indicate a mismatch between current exports and the country’s factor endowments. To explain why a country’s exports cannot be sustained, one of several areas to investigate is whether the exports that die represent attempts to produce goods that require a mix of factor 8 For a detailed discussion on the gravity model and the results of this exercise, see chapter 1. 5 endowments different from that supported by the economy. With few exceptions, Russia’s most significant exports in 1993 were in line with the average factor endowment in upper middle-income countries, with some embodying capital greater than the average (figure 5). By 2003, the endowment of both physical and human capital had increased slightly, and Russia produced many exports with higher factor requirements. The major exports, however, remained close to the endowment point, with one major output below (figure 6). A majority of exports that existed in 1993, but not a decade later, required a fairly high level of physical and human capital. At the same time, a majority of “newâ€? exports active in 2003, but not a decade earlier, are also moderately capital intensive. It can be hypothesized that, all else equal, ambitious ventures that defy a country’s comparative advantage have a higher rate of failure. Figure 5 Exports relative to endowment, 1993 Figure 6 Exports relative to endowment, 2003 Russia: Exports Relative to Endowment 1993 Russia: Exports Relative to Endowment 2003 15 15 Revealed Human Capital Index Revealed Human Capital Index 10 10 5 5 0 0 0 50000 100000 150000 0 50000 100000 150000 200000 Revealed Physical Capital Index Revealed Physical Capital Index Source:Authors’ calculations Source: Authors’ calculations Binding Constraints to Export Diversification – Firm-Level Evidence 16. Empirical analysis of the investment climate factors and their effects on firm performance help identify the binding constraints to nonresource exports in Russia. This result is based on more than 250 variables provided by the 2009 World Bank Enterprise Survey that are related to the Russian investment climate. The topics in the survey include the obstacles to doing business, infrastructure, finance, labor, corruption and regulation, law and order, innovation and technology, trade, and firm productivity. Out of these numerous variables, we identify a smaller set (about 20) that are statistically significant (at 5 percent at least) to explain each aspect of firm performance: the economy’s export propensity and intensity (probability of exporting and the share of exports in total sales); total factor productivity (TFP);9 and innovation ability. 17. We apply micro-econometric techniques to estimate the correlations between dependent and independent variables. In addition to the above dependent variables, the equations measure a number of independent (or explanatory) variables’ impact on firm performance, including competition, a group of other investment climate variables, and other control variables (including industry, region, and firm size). A system of equations is used to model the interrelations among the dependent and independent variables. A summary of the methodology used is in annex A. While we interpret the results with a “grain of salt,â€? we believe they represent a good first screening of Russia’s binding constraints to firm growth. The remainder of the section summarizes the results of the background paper by Pena (2010)  This section is based on Peña (2010). 9 TFP is the portion of output not explained by the amount of inputs used in production. As such, its level is determined by how efficiently and intensely the inputs are used in production. 6 describing key investment climate factors affecting firm productivity (TFP), exports (propensity), and innovation. Investment Climate and Propensity to Export 18. The results of this analysis show that the main contributors to firm export propensity in Russia are the firm’s productivity level, its innovation performance, and the competition environment it faces. Factors related to infrastructure, regulatory environment, and access to finance, though still playing a role in the propensity of Russian firms to export, exhibit lower (absolute) contributions. The relative contributions of individual variables to firms’ export propensity (the effect that can be associated with the investment climate) are in figure 7. Our primary focus on export propensity follows recent findings of research that show entry as the driving force in several export booms. In Chile, for instance, 64 percent of the increase in exports during 1990–2007 came from new exporters, rather than from an increase (export intensity) in incumbent exporters. The contribution of the investment climate on Russian firms’ export intensity is discussed in box 1. Figure 7 Contributions of measured variables to export propensity (%) TFP Innovation, quality & skills Competition Infrastructure Regulatory env. Finance Other 70 control variables 58.37 60 50 40 32.71 % Contributions 30 20 7.61 6.07 10 3.82 4.74 1.44 2.22 2.42 0 -0.27 -4.45 -3.76 -1.08 -10 -4.56 -5.29 1 2.1 2.2 2.3 3.1 3.2 3.3 3.4 4.1 4.2 5.1 5.2 5.3 6.1 7.1 1 TFP (log) 3.1 Domestic competition 5.1 Informal payments in tax inspections 2.1 Dummy for R&D 3.2 Dummy for informal competitors 5.2 Manager's time spent in bur. issues 2.2 Dummy for new product 3.3 Dummy for more than 5 competitors 5.3 Dummy for gifts to receive certificates 2.3 Dummy for quality certification 3.4 Dummy for increased prices 6.1 Purchases paid for after delivery 4.1 Power outages 7.1 Dummy for sales decreased 4.2 Electricity from own generator Source: Authors’ calculations 19. Productivity levels exhibit the largest contribution by far: a 1 percent increase in TFP is associated with an increase in export propensity of up to 11 percent. Also, evaluation of the importance of TFP, relative to other variables, in explaining the propensity of firms to export shows that TFP accounts for 42.1 percent of the determinants of exporting for firms in Russia (relative to other variables; figure 8). Such importance of productivity in a firm’s propensity to export is consistent with recent studies on trade with heterogeneous firms. These studies argue that high-productivity firms are 7 more likely to export because they are able to pay the substantial sunk (fixed) costs incurred in entering foreign markets.10 Figure 8 Percentage absolute contributions of TFP to the probability of exporting 50 40.7 42.1 42.9 40 30.3 30 24.1 24.2 24.4 25.1 20.7 21.7 22.0 18.2 19.6 19.6 20 14.0 15.7 15.7 9.0 9.1 10.6 10 0 Source: Staff calculations based on Peña (2010) and Escribano, Peña, and Reis (2010). 20. The relevance of firm productivity to the probability of exporting is not unique to Russia. While significant in its own right, it is important to give a cross-country perspective to understand to what extent the contribution of productivity to export propensity is specific to the Russian context. Figure 8 shows the percentage relative contributions of TFP to the probability of exporting (exporting propensity) in 19 countries. The results show that, regardless of the country, TFP is always significant and most important for international engagement. However, the results also show that, with Turkey and South Africa, Russia stands out as a country where the association between productivity and exporting is particularly strong. 21. The underlying costs to export may be higher in Russia than in other countries. The heterogeneous firm literature on international trade has established that export participation is mostly determined by variable export costs (such as transport costs and tariffs) and fixed export costs (such as market entry costs). This combination affects firm profitability and – given that firms differ in productivity – their ability to engage in exports. As a result, the firms that can overcome the trade costs to export are usually the largest and most productive within a country. There is, therefore, a direct relationship between the level of trade costs and the minimum productivity threshold required to export. A simple way to infer differences in exporting costs across countries is to look at some measure of the minimum productivity required to export in each country.11 Our results indicate that the minimum average productivity required to export in Russia is higher than in almost all comparator economies.12 22. Further analysis suggests that fixed costs to export are the key impediment to Russian businesses. To gauge the impact of variable costs for exports, we look at the Market Access Tariff Trade Restrictiveness Index,13 which is below the average for the Europe and Central Asia (ECA) region – 10 Yet the role of productivity in shaping aggregate export responses should not be overstated, and most of the literature identifies exchange rates and foreign income growth as more important determinants. See, for instance, Bernard (2006). 11 We compute two measures of productivity in each country. The first is the “Solow residualâ€? estimated from an ordinary least squares regression of a log Cobb-Douglas production function. Specifically, we regress total sales on total employment, total stock of capital, and cost of materials (all in logs). The second is the standard revenue-based labor productivity computed as the ratio of total sales over total employment at the establishment level. 12 For a detailed discussion of these results, see chapter 1. 13 This index calculates the equivalent uniform tariff of trading partners that would keep their level of imports constant. It is weighted by import values and import demand elasticities of trading partners. 8 indicating that variable export costs in Russia are slightly more favorable than for the countries in comparator regions. This suggests that the fixed costs of exporting are the key factors impeding export participation in Russia. These preliminary findings are in line with firm-level evidence provided by Volchkova (2010), which links firm-level information with customs data to find that Russian enterprises face higher fixed exporting costs than French firms. This analysis could suggest that Russia faces unexploited trade potential in the form of firms that are willing, yet unable, to venture abroad because of too high fixed costs to export. 23. The tax code may further limit the willingness to export, especially for smaller firms.14 In Russia, exporting firms are entitled to receive a value-added tax refund which, according to anecdotal evidence, increases the probability of being inspected by tax officials. Firms may therefore prefer not to export at all rather than face tough tax controls and potential charges. We investigated this issue using firm-level information from the 2009 Enterprise Survey, and our preliminary findings indicate that the probability of being audited is around 20 percent higher for exporters than for nonexporters in Russia. 24. Firms introducing a new product and investing in R&D and those facing competition from domestic firms are more likely to export. By encouraging innovation and enterprise R&D, innovation policies could, in principle, increase the probability of a firm to export and thus contribute to export diversification. This conclusion holds regardless of the sector of the firm performing R&D. Similarly, firms subject to strong domestic competition have a higher probability of exporting. Results are consistent with the argument that strong rivalry in domestic markets strengthens the capacity of local firms to compete abroad. 15 By affecting the competition environment, the Russian government can affect the export propensity of domestic firms. 25. Another factor impeding the propensity of exporting is the red tape faced by Russian enterprises. Figure 7 illustrated that firms where senior managers spend more time dealing with requirements of government regulations have a lower probability of exporting. Indeed, Enterprise Survey data show that managers in Russian enterprises spend on average 19.9 percent of their time trying to meet regulatory requirements – a higher proportion than in many other emerging economies, such as Romania, Ukraine, or Brazil (ranging from 9.2 to 18.7 percent) and significantly higher than the OECD average of 1.2 percent. 26. Limitations in infrastructure as well as delays in payments are also impediments, with adverse effects on a firm’s probability of exporting. Establishments that purchase a higher share of their input on credit (after delivery) seem to have a lower probability of exporting. Similarly, infrastructure seems to impose a strain on exporters. Businesses experiencing a higher number of power outages per month are less likely to enter foreign markets, as are firms with a higher share of electricity coming from a generator. 14 Tax rates are perceived by businesses in general as a major obstacle to growth (Plekhanov and Isakova 2011). 15 See, for instance, Porter and Sakakibara (2004) in reference to the Japanese experience. 9 Box 1 The investment climate and the intensity of exports A secondary issue to export propensity is the intensity of exports – here, other investment climate conditions prove to be the main determinants, with domestic competition and innovation also playing a role. As a second step to export propensity, we try to say something on the determinants of the volume of exports – that is, once a firm self-selects into export markets, why do some firms export more than others? We construct a standard probit model for export volume, measured as percentage of total annual sales, with the objective of getting consistent estimators of the effects of TFP, innovation, competition, and investment climate variables on the exporting intensity of firms.1 Results show small relative contributions of domestic competition and innovation – both around 3 percent – to higher export intensity. This can probably be explained by the low proportion of firms engaging in research and development and facing intense domestic competition. On the other hand, other investment climate variables as a whole contribute almost 50 percent to the mean of exporting intensity, while the remaining 43 percent is explained by other control variables (industry, region, size effects, and the like). Within the 50 percent contribution of the investment climate, the role of regulatory factors, labor skills, and other control variables (mainly number of competitors), as well as additional competition variables (mainly facing more than five competitors) stand out (right panel in the figure). Absolute contributions of R&D, competition, and control variables to export intensity Regulatory environment 18.1% Finance Otherinv. Othercontrol 5.1% variables climate variables Quality 43.3% Laborskills 0.9% 12.1% Other (competition) 13.3% Domestic competition R&Dinvestment 3.5% 3.2% Note: 1. We here consider a self-selection problem, as we only observe the volume of exports for those firms exporting. Thus the equation encounters an endogenous sample selection problem. To model the probability of firms exporting, we use probability of exporting equation estimated with a standard probit model. For more details on the methodology, see Peña (2010). Investment Climate and Total Factor Productivity 27. Productivity is a multidimensional variable, but investment climate factors are able to explain a significant part of it. Because productivity plays a major role in a firm’s decision to export and invest in R&D, we also investigated which investment climate factors contribute more to the TFP levels of Russian firms. Results indicate that the investment climate explains up to 36 percent of aggregate log TFP.16 Details on the role of the investment climate are in figure 9, where the individual investment climate contributions to aggregate log TFP are included. There are 20 statistically significant variables, out of which 17 are exclusively investment climate variables. 16 In addition to the investment climate, other factors explaining aggregate logTFP include the equation’s explanatory variables (exports, foreign direct investment, innovation, employment), as well as industry/region/size effects and the constant technical efficiency (constant term of the TFP equation). 10 Figure 9 Contributions of measured variables to aggregate logTFP (%) Trade & FDI Innovation, quality and skills Competition Infrastructure Reg. Finance and Other control 30 & logistics env. corporate governance variables 25.96 25 20 14.18 15 11.40 12.17 10.78 8.69 8.88 10 7.30 % contributions 5.59 6.10 2.45 3.39 5 1.34 0.55 0 -5 -1.22 -1.42 -0.54 -2.13 -3.68 -10 -9.79 -15 1.1 1.2 1.3 2.1 2.2 2.3 2.4 2.5 3.1 3.2 4.1 4.2 5.1 6.1 6.2 6.3 6.4 6.5 7.1 7.2 1.1 Dummy for FDI 1.2 Dummy for exports 3.1 Domestic competition 6.1 Dummy for loan 1.3 Dummy for imports 3.2 Dummy for informal competition 6.2 Sales paid after delivery 2.1 Dummy for new product 4.1 Shipment losses in exports 6.3 New fixed assets financed by internal funds 2.2 Dummy for quality certification 4.2 Days to clear customs in exports (interac.) 6.4 New fixed assets financed by equity 2.3 Staff with computer 6.5 Dummy for subsides 5.1 Dummy for gifts in tax inspections 2.4 Dummy for training 7.1 Dummy for incorporated company 2.5 Experience of the manager 7.2 Dummy for decreased sales Source:Authors’ calculations. 28. Results indicate that innovation, labor skills, and exporting and importing activities, among others, are associated with higher TFP. Technological upgrades – defined as the share of staff with access to a computer, import activity, and quality certification (an indication of technical conformity) – appear among the most relevant investment climate factors. Of particular relevance, according to our results, is the manager’s experience. The positive contribution of the dummy for incorporated companies can be seen as evidence of the importance of strict corporate governance rules. 29. Firms subject to informal competition (gray market) and businesses receiving subsidies have lower productivity. Public subsidies seem to be associated with lower productivity – in apparent contradiction, in principle, to the goals of state aid. All these factors tend to distort competition and have an adverse impact on productivity. In fact, the Olley and Pakes decomposition of Russia’s productivity shows that the current contribution of the allocative component (how much of the output is commanded by the more productive firms) to aggregate productivity in the country (about 20 percent) corresponds to half the value for Brazil in the early 2000s. By creating a more level playing field, competition policy in Russia may contribute to increased productivity and thus export diversification. 30. Data support the hypotheses of domestic competition spurring TFP and exports. To evaluate how competition is related to the endogenous variables of the system, four variables approximating four measures of competition were defined: domestic, foreign, customer, and informal. Analysis suggests that the more competition a firm faces from domestic firms, the higher the TFP and probability of exporting. Facing informal competition exerts a statistically significant negative influence on TFP, employment, and investment in R&D. 31. In summary, analysis indicates a strong correlation between productivity, innovation, and domestic competition and firms’ propensity to export. The analysis shows that innovation-related variables (investing in R&D, introducing a new product, and holding a quality certification) contribute to roughly 46 percent of the total effect of investment climate variables on firms’ export propensity. Results also indicate significant differences in productivity levels – firms facing domestic competition have an 11 estimated 19 percent higher productivity than firms that do not face such competition. At the same time, firms are 8 percent more likely to export when facing domestic competition. There are also large productivity gains to be expected from a hypothetical increase in Russia’s domestic competition to the levels of the top performer in the ECA region. These results support our emphasis on domestic competition and innovation as two crucial axes to promote the emergence of internationally competitive exports. 32. Yet, as the analysis has illustrated, these are not the only variables relevant to export propensity. Several other key investment climate factors contribute to higher propensity to export by Russian firms, including bureaucracy, finance, and infrastructure. Several of these issues have already been studied extensively by the World Bank and other international and Russian organizations, providing a menu of policy options. The following sections (after the next subsection) therefore focus on competition and innovation – topics that have received less attention but where there is strong demand from the Russian government for World Bank support – and how these areas could contribute to increased export diversification. Investment Climate and Propensity to Invest in R&D 33. To better understand the factors affecting a firm’s R&D decision, we studied the effects of the investment climate on the probability of R&D investments by Russian firms – with results indicating that firms with higher TFP are more likely to invest in R&D (figure 10). 17 Higher productivity may enable investments in R&D by increasing the internal funds available to the firm. Internal funding is often preferred as a source of innovation financing because of lower costs or simple unavailability of credit (rationing). 34. Results indicate the importance of information and communications technologies, tertiary education, and training, as well as the experience of the manager – proxies for entrepreneurship and business knowledge. Being a limited liability company also increases the probability of a firm’s investment in R&D. By reducing monitoring costs and downside risks for shareholders, limited liability companies enable managers to take on riskier investments that hold out a promise of greater returns and potentially represent an overall more productive investment strategy for the firm. 35. Firms introducing a new product are more likely to invest in R&D. Our analysis indicates a positive effect of introducing a new product, pointing to synergies between R&D investment and new products. One way to interpret this result is that R&D and technological modernization are complementary inputs to the innovation process, as technologically outdated firms are less likely to spend on R&D. However, it seems that firms are more likely to invest in R&D when capacity use is lower. This latter result, though apparently puzzling, follows the less conventional view that business R&D may be countercyclical (that is, it increases during downturns). For its part, the result of outsourcing is interpreted as evidence of gains from specialization – productivity enhancements derived from division of labor, which in turn is limited by the size of the market. By affecting the size of the market through product market regulations, governments may affect firms’ specialization and thus productivity levels. 17 Firms were asked what amount they spent in fiscal year 2007 on R&D activities, either in-house or contracted with other companies (outsourced). 12 Figure 10 Contributions of measured variables to the propensity of investing in R&D (%) TFP Trade Comp. Innovation, quality & skills Infras. Regulatory Other control variables 30 27.62 environment 27.83 25 20 15 12.79 7.37 8.13 10 5.92 5.63 4.28 4.93 4.35 4.44 % Contributions 5 1.42 0.80 0.44 0 -5 -0.86 -2.76 -10 -10.32 -15 1 2 3 4.1 4.2 4.3 4.4 4.5 4.6 4.7 5 6.1 6.2 6.3 7.1 7.2 7.3 4.1 Dummy for new product 6.1 Manager's time spent in bur. issues 1 TFP (log) 4.2 Dummy for outsourcing 6.2 Dummy for gifts to get construction permits 4.3 Dummy for webpage 6.3 Dummy for external auditory 2 Dummy for exports 4.4 Staff - skilled workers 4.5 Staff - university education 7.1 Dummy for incorporated company 3 Dummy for informal competitors 4.6 Dummy for training 7.2 Dummy for limited company 4.7 Experience of the manager 7.3 Capacity utilization 5 Dummy for own generator Source:Authors’ calculations Competition and Competition Policy 36. Effective competition and competition policy can play a key role in fostering economic diversification. The entry conditions faced by new (innovative) firms and the exit of obsolete ones, which would raise the productivity of surviving firms, is the main process through which growth prospects of the firms in the nonextractive industries would be strengthened. In particular, regulations that promote competition may increase the incentive – and lower the costs – to invest and innovate by incorporating new technologies into the production process, thus stimulating productivity growth. A similar point to that of the Olley and Pakes decomposition (referred to earlier) is raised by Bakatina and others (2009): “This paradox (that the presence of struggling productive players despite relatively high competition is primarily explained by the fact that the government, through unequal regulations and/or enforcement, is distorting the playing field) is the main explanation for the lack of productivity and investment growth in eight out of the ten selected sectors.â€? 37. Asymmetric application of existing regulations or access to state aid favor larger, less productive incumbent companies to the detriment of smaller and more efficient firms and potential entrants. These market distortions are sector specific and take many forms. For example, cheap energy is provided to nonviable steel and cement plants, and wholesale markets are subject to one-eighth of the tax liabilities of new forms of retail organizations, such as hypermarkets and discount stores. This asymmetry is particularly acute at the regional level and is a source of regional variability in the broad competition regime. In procurement rules, for example, municipal and regional authorities have adopted different approaches to using single-source procurement bids and to practices, which may facilitate collusion, even though a federal legal framework has been established (a factor that normally has an important effect in the construction sector).18 According to the same Bakatina and others (2009) study, “in nine out of the ten 18 The Certificate of Independent Bid Determination has been discussed as a mechanism to deter collusive behavior, but it has not been implemented because it will require changes in the procurement law. It is expected that the launch of electronic bids will increase competition and outcomes in this area. 13 selected sectors, the non-level playing field is the key explanation for the lack of restructuring of the old assets and/or investments by best practice companies.â€? 38. Contrary to the experience of earlier reformers in Eastern Europe, firm dynamics (entry and exit) in Russia have not contributed significantly to productivity growth. Most of the country’s productivity gains in the last decade have come from the use of excess capacity, while specialization and technological updates were the main factors in the productivity gains of Eastern Europe’s earlier reformers. Entry rates were particularly low in Russia19 – even though entrants showed labor productivity rates 10 percent higher on average than incumbents in the entry year. In addition, exit rates, though difficult to estimate, are probably much lower than in most transition economies, if one considers that enterprise restructuring in Russia lags behind Poland, Turkey, and the average of countries in the ECA region, according to the Transition Indicators from the European Bank for Reconstruction and Development. Moreover, Russia has some of the most pervasive product market regulations among developed economies (figure 11), with particularly poor results in the subindicator Barriers to Trade and Investment and State Control (figure 12). Figure 11 Overall product market regulations Figure 12: Subindicator: Barriers to Trade and indicator, Russia and comparator economies, 2008 Investment and State Control, Russia and comparator economies, 2008 3.5 6 3.0 Russia (3.09) 5 Russia (4.64) 2.5 4 2.0 3 1.5 2 1.0 1 0.5 0 0.0 Note: Strictness of regulations on a scale of 0–6; higher values indicate more restrictive policies on competition. Source: OECD PMR 2009. 39. The sweeping scope of the public enterprise sector and extent to which the state directly controls strategic decisions of public enterprises is a strong factor in Russia’s comparatively poor performance. Indeed, the lack of enterprise restructuring is especially challenging for the competitiveness and growth of Russia's “monotownsâ€? (the 460 company towns that depend heavily on a single industry). 40. Russian incumbent firms seem more isolated from international competition than their counterparts in countries at similar development levels and to have variations in firm qualities in sectors with higher price-cost margins. According to the World Bank Trade Restrictiveness Index, international trade policy – especially nontariff barriers in the form of technical regulations and quantitative restrictions – seems more protectionist in Russia than in several OECD countries. Overall trade restrictiveness in Russia is 16 percent, against 6–10 percent in the United States, Japan, and China. One implication of limited import competition is market dominance: price-cost margins for inputs of 19 World Bank 2008. 14 exportable goods tend to be larger than those of their international peers (figure 13), reducing the incentive for local exports.20 Moreover, Russian firms register larger price-cost margins than the average of the region in every manufacturing sector except food, garments, and chemicals. A more Figure 13: Distribution of observed price-cost margins detailed analysis in selected sectors reveals that in manufacturing (Russia and selected ECA countries) firms in sectors where Russia registers higher price-cost margins than its regional counterparts tend to be older; have more employees; are less likely to export and invest in R&D; are more likely to operate in local markets; and, in some cases, are less likely to operate in a competitive market structure. The analysis of Russia’s market structure at the geographic and product market level also reveals high concentration, with significant variations across regions and Russia=1, Selected ECA countries=0 sectors (figure 14). Figure 14 Concentration levels in selected Russian industries, by region (Herfindahl-Hirschman Index) Textiles Electronics PlasticandRubber Karelia Irkutskoblast Karelia Tomskoblast Tatarstan Tatarstan Moderately Irkutskoblast Highly Highly concentrated: concentr Tveroblast Rostovoblast Tatarstan concentrate 1500Ͳ2500 ated: Tomskoblast d: Voronezhoblast Voronezhoblast PermKrai Tveroblast Rostovoblast Moderately concentrated: Tomskoblast PermKrai Voronezhoblast Moderatelyconcentrated: 1500Ͳ2500 Irkutskoblast Tveroblast Rostovoblast 1500Ͳ2500 Unconcentrated: PermKrai SaintͲPetersburg Unconcentrated: SaintͲPetersburg <1500 SaintͲPetersburg <1500 Unconcentrated:<1500 Moscow Moscow Moscow 0 2000 4000 6000 8000 10000 0 2000 4000 6000 8000 10000 0 2000 4000 6000 8000 10000 Source: SPARK Database. [cite as author-date and add to references] 41. A related problem is market fragmentation: the 2009 World Bank Enterprise Survey shows that 50 percent of Russian firms considered local markets their main sales destination – a high rate, even compared with large economies like Brazil (about 35 percent). Despite the size of the Russian economy, such isolation from global markets may induce companies to choose less modern technology and operate at suboptimal scales. In Russia, two factors could explain market fragmentation and less competitive markets: transportation costs (related to limited transport infrastructure and long distances) and barriers created by the interventions of regional governments that hinder the entry of firms from outside the region. 42. Enforcement of regulations and anticompetitive actions of regional authorities differs extensively in several policy areas, contributing to market fragmentation. Analysis suggests that the application of state aid regimes in Russia, enforcement of competition rules related to tendering and specific anticompetitive practices, and government actions all distort the playing field, with the use of aid by regional authorities varying widely. In addition, the level of tax arrears as a share of total tax revenues 20 According to the World Economic Forum, for instance, market dominance in Russia is much higher than in the EU and the average OECD country. 15 fluctuates broadly across regions, with 68 of 83 regions presenting tax arrears of 30 percent or more. Regional authorities were the most active providers of state support in 2007–08.21 Market dynamics and rates of government involvement also differ widely across key economic sectors, and the stage of development of competition and the regulation of infrastructure, manufacturing, and services vary substantially across industries. 43. Even though privatization of state-run companies is on the government’s agenda, the state still controls the largest producers in many key sectors, including electricity, banking, oil, and railways. State ownership in Russia appears to be twice as large as in 10 countries of the European Union (EU-10), and state-owned enterprises account for about 17 percent of employment. These companies usually occupy dominant market positions in their areas of activity, with scope for private participation – including that by foreign investors – tightly controlled. (In 2007, the share of foreign participation was 2.7 percent in the average Russian company but 7.5 percent in the EU-10 countries.) Tariffs have progressively replaced nontariff barriers as the principal instrument for regulating foreign trade, but average tariff rates and tariff dispersion were still higher in Russia than in all OECD countries by the mid- 2000s, providing some degree of isolation from international competition. 44. Entry regulations are still pervasive, with access to land of particular concern, especially its regional variability. Data from Doing Business 2011 show that it takes 42 days to register property in Russia, against a 38-day average for the ECA region. Doing Business 2011 also ranks Russia as 182 out of 183 economies in “dealing with construction permits.â€? It takes 540 days to build a warehouse, versus 250 days on average in the ECA region (the corresponding cost is 4,141 percent of Russia’s income per capita). A subregional Doing Business analysis from 2009 showed that, by region, Moscow imposes the most difficulties for those dealing with construction permits, the Rostov-on-Don region the fewest.22 For bankruptcy procedures, it takes on average 3.8 years to close a business, with Russia ranking 103 out of 183 economies. The government has also established a number of state corporations that have the special legal status of a noncommercial organization and that are not subject to the Bankruptcy Law. 45. The stages of development of competition, as well as regulation of infrastructure and service sectors, varies greatly across industries in Russia. x Within transport, a state-owned enterprise dominates the railway market, and road freight intermodal competition is extremely limited. Regional laws govern the road transport sector (freight and passengers) within a region, while interregional truck transport is governed by federal laws. Trucks and new vehicles are subject to high import duties, which discourage entry, and regional and municipal authorities often provide preferential treatment to municipally owned enterprises, particularly in passenger services. x The government also has substantial ownership of firms in the banking sector, with an active role in the market through the state-owned commercial banks and the state investment vehicle Vneshekombank. Contestability of the financial sector is obstructed by differences in supervisory practices across institutions and an unclear – and not entirely credible – exit process. x Competition constraints have also been identified in the Russian construction market, in particular related to the uneven playing field between incumbents and new entrants. Construction 21 Kuznetsov and others 2010. 22 See www.doingbusiness.org. 16 markets have characteristics prone to collusive and cartel-like behavior. Licensing schemes for operation in each segment of the supply chain remain cumbersome. x In telecommunications, fixed operators are dominant, but there are many players in the mobile sector, even at the regional level. Some regulations to improve or stimulate competition, such as mobile termination charges, are not yet in place. x The government has introduced various export restrictions and price controls in agriculture (box 2). Unsurprisingly, arable land in Russia is underused, and the agricultural productivity gap is significant.23 Box 2 Price controls and other government interventions in Russian agriculture Since its transition to an open economy in the early 1990s, Russia has emerged as a major agricultural exporter of grains (mainly wheat and barley).1 The government has sharply raised investment in agriculture over the past five years, with the budget of the State Program for Development of Agriculture 2008–2012 aimed mainly at financial stability for the sector through interest rate subsidies. The government took several other measures in response to the high inflation of 2007–08: x Price freezes. The government reached a voluntary price restraint agreement with major food producers and retailers to control retail prices on “socially importantâ€? food products, including bread, eggs, milk, and sunflower oil. The agreement lasted from October 2007 to April 2008. x Direct input subsidies. To mitigate higher energy prices, farms are provided subsidies for fuel costs for sowing. They also receive subsidies for mineral fertilizer, chemicals, and high-quality seed purchases, and for transporting seeds. Pig meat and poultry farmers receive per-ton subsidies. x Grain commodity interventions. These were put through in October 2007–June 2008, via large releases of grains (nearly 85 percent of total intervention stocks), mainly in industrial centers and regions with high grain imports. This pattern was reversed as a result of a large grain harvest in 2008, and the government initiated grain purchase interventions in late 2008. As prices started to rise in summer 2010, the government again started to sell grain from the state intervention fund. x Trade-oriented measures. Import duties on key foodstuffs were temporarily reduced to combat high inflation, including tariff cuts for dairy products, vegetables, and vegetable oil. Duties on poultry and eggs imported for breeding were removed. Export-restriction measures were imposed in late 2007 through duties on wheat, meslin, and barley exports. As a way to prevent wheat and meslin outflows through the Russia–Belarus–Kazakhstan customs union, exports of these grains to Belarus and Kazakhstan were temporarily banned. These duties were removed in mid-2008, in response to large grain harvests. However, as a result of severe drought and wildfires in the summer of 2010, the government reimposed bans on grain exports, expected to last until end-2011. Source: Liefert, Liefert, and Serova 2009; OECD 2009b; USDA Foreign Agricultural Service 2010; Bloomberg Businessweek 2010. 1. Since integrating with world markets in the early 1990s, privatizing its agriculture, and diminishing subsidies and price controls in livestock, Russia’s earlier high meat production fell considerably and has been replaced by high meat imports. Rather than facing strong domestic demand for grains to feed a large livestock industry, Russia is today exporting the grain produced at home, helping increase exports. Meat production, 10.1 billion tons in 1990, averaged 4.8 million tons a year over 1996–2005, climbing to 6.7 million tons in 2009 as a result of government initiatives to increase self-sufficiency. 23 For more information on agriculture in the Russian Federation, see annex II. 17 Entrepreneurship, Innovation, and Research Commercialization 46. Our empirical analysis provides support to the importance of firm-level innovation in export propensity and productivity levels of Russian businesses. As discussed in Section III, investing in R&D and, even more so, engaging in product development, increases the probability of Russian firms entering foreign markets, thus potentially contributing to export diversification. The analysis shows that innovation variables contribute to 46 percent of the investment climate effect on firms’ export propensity. In addition, several innovation and labor-skills variables are positively (and significantly) associated with higher firm productivity. 47. Private R&D investments in Russia are average relative to the country’s level of development, but a declining trend in recent years is worrisome. Russia’s business R&D expenditures declined from a high of 0.88 percent of GDP in 2003 to 0.65 percent in 2008. In the same period, OECD countries increased their equivalent expenditures from 1.49 percent to 1.63 percent. Other advanced emerging economies, such as Mexico and China, with per capita GDP lower than or similar to Russia, had higher business R&D expenditures as a share of GDP (1.8 percent and 1.1 percent of GDP, respectively), while other advanced Eastern European economies, such as the Czech Republic and Slovenia, were also ahead (0.91 and 1.07 percent, respectively). Russia has room to improve its business R&D spending. 48. The R&D activities of foreign firms in Russia have also decreased over the last decade. The changing landscape of global R&D can be seen in the growth of R&D sourced from abroad (through private business, public institutions, or international organizations). These sources are quite important in funding business R&D. In most countries, such financing from abroad primarily comes from other businesses, notably multinational enterprises. The share of Russian business R&D financed from abroad decreased, from a fairly high 11 percent in 1998 to 7.2 percent in 2008, compared with around 9 percent among EU-27 countries in 2007. Among emerging economies, the Slovak Republic and Hungary reported the largest increases in 1998–2008 (17 and 6 percentage points, respectively), while the share of Sweden, for instance, grew by more than 7 percentage points. 49. Entrepreneurship in Russia is lower than expected for the country’s development level. Internationally, the amount of entrepreneurial activity generally declines with development (measured by per capita income) up to a point, after which a positive relationship seems to emerge (figure 15). This may be interpreted as evidence that entrepreneurship could present declining returns – as the catch-up process evolves – possibly reflecting declining opportunities for imitation, learning by doing, and the like. The subsequent ascending section of the graph may reflect that innovation becomes a more active entrepreneurial factor as richer countries tend to focus more on R&D-related activities. 18 Figure 15 Total entrepreneurship activity, 2006 Russia Note: 2006 is latest available data. Source: Global Entrepreneurship Monitor and World Bank. 50. Limited entrepreneurship is closely related to poor governance and weak institutional regimes, as they affect the allocation of talent in society to rent seeking rather than productive activities. In Russia, the share of firms considering corruption a top obstacle for business (11 percent) is about five times that in Brazil (2 percent), according to the World Bank 2009 Enterprise Survey. About a quarter of management time in Russia is spent on regulation requirements, compared with 7 percent in India, which illustrates how a deficient governance regime leads to misallocation of talent. Foreign and domestic investors in Russia face potentially hazardous conditions, since the regulatory framework provides only limited protection from the risk of expropriation, as indicated by a weak scoring in the Protecting Investors indicator in Doing Business (5.0 index points on a scale of 0–10). 51. The commercialization of public research – potentially another source of innovation – has only recently become a focus of government innovation policy. According to the Ministry of Education and Science, more than 950 start-ups have been created to date. The great majority (97 percent) stem from university research and only 3 percent from research institutes. This corresponds to an average of 5.1 firms per university and 1.2 firms per institute, even though the institutes concentrate a majority of both capital and human resources in R&D. In addition, the number of patents granted to Russian researchers – often a first step to commercializing research – remains stagnant. Patents granted as a share of patent applications to the U.S. Patent and Trademark Office fell sharply over 1998–2008, from 71 percent to 32 percent. Russia has in recent years been surpassed by Poland and China in the number of patents granted by that office. The aggregate effect is a fairly inefficient innovation system that requires much more investment in R&D per patent than countries with similar levels of R&D: while Russia and Hungary spend similar shares of GDP on R&D (about 1 percent in 2008), Hungary generates nearly twice as many patents per unit of R&D spent (figure 16). 19 Figure 16 R&D patents granted versus GDP per capita, 2008 8.5 LogGERD/PatentsgrantedintheU.S. Turkey Romania Russia Portugal 8.0 CzechRep. China Poland Slovenia Slovakia Spain Croatia 7.5 Hungary Luxembourg Norway Austria Ireland Iceland Italy Belgium France Sweden 7.0 UK Denmark Finland Netherlands Germany Israel Switzerland Canada Korea U.S. Japan 6.5 Ͳ0.4 Ͳ0.2 0.0 0.2 0.4 0.6 0.8 LogGERD/GDP Source: OECD; UNESCO; U.S. Patent and Trademark Office; World Bank 2011. 52. This persistently negative trend in scientific performance undermines Russia’s research pool, limiting the options for commercialization. Some aspects of scientific production in Russia have been relatively lower than in other countries. Figure 17 Science and engineering journal articles per Apart from the high-level performance of R&D in researcher in Russia government research institutions, academic 0.035 productivity was relatively poorer and has fallen 0.034 further in recent years, despite the higher R&D 0.033 investment as a proportion of R&D (figure 17). 0.032 Equally, the number of researchers in Russia 0.031 decreased 15 percent over 1996–2008, resulting 0.030 in fewer researchers as a proportion of 0.029 employment relative to the averages for the EU- 0.028 15, EU-27, and OECD – but this was an area in which Russia outperformed its industrialized Source: Staff elaboration based on World Bank (2011c). neighbors only a decade ago. 53. One of the reasons for declining research productivity in Russia is the way public funding is distributed. The government allocates a budget to public research organizations and higher education institutions in amounts it regards sufficient to cover anticipated costs, regardless of the performance of the institute or the researcher. A small proportion of research institutions’ budgets is allocated competitively (about 15 percent in 2009, compared with roughly 30 percent in Israel), a mechanism that usually results in a tighter link between research funding and scientific output. Most of the budget for research institutions, including universities, is allocated based on personnel headcount, but again without any link to the performance of the research organization. Such headcount budgeting creates, in addition to low scientific outputs, a system that inflates costs, as research organizations have an incentive to keep the number of researchers high. 20 54. Another obstacle for a more efficient R&D system is the declining number of middle-career researchers. Such researchers (30–49 years old) tend to publish and commercialize research results more. In Russia, this age group fell from 37.7 percent Table 1 Age of researchers by educational attainment of the total in 2002 to 32.2 percent in 2006 Year Age category (years) (table 1). This in part stemmed from limited 2002 2004 2006 Researchers renewal of the research pool, as indicated by the 70 and older 3.8 4.6 5.9 50–69 44.9 45.2 45 large share of science and engineering graduates 30–49 37.7 34.9 32.1 studying oversees and not returning. (By 2007, Under 30 13.5 15.4 17 less than a quarter of science and engineering 70 and older 20.3 22.2 24.7 50–69 64.2 63.7 62.3 PhDs graduates receiving PhDs in the United States in 30–49 15.5 13.9 13.1 2002 had returned to Russia.) A lack of Under 30 0.2 0.1 0.1 opportunities for career advancement in Russia, 70 and older 5.9 7.4 9.7 Candidates of science 50–69 54.9 54 52.8 made worse by wages that are not 30–49 35.6 34.4 33.1 internationally competitive, is the basis for this Under 30 3.5 4.1 4.5 negative trend. Source: Ministry of Education and Science of the Russian Federation 2009; ROSSTAT 2010; The Higher School of Economics. 55. Although the legal framework for intellectual property has improved, it is still uncertain, discouraging both patenting and licensing. Two major pieces of legislation govern intellectual property in Russia. Part IV of the Civil Code (2008) provides a foundation for dealing with intellectual property generated by public funding (63 percent of R&D expenditure). Federal Law 217 (2009) deals exclusively with the use of intellectual property generated from public funds for start-up companies by universities and research institutes linked to the Russian Academy of Sciences. However, the start-ups do not own the patent that supports the company, with intellectual property rights not exclusively granted to companies. In addition, while discoveries in the defense sector could potentially be a major source of civilian innovation, their application remains limited because, on the one hand, most of these discoveries are inaccessible to the private sector and, on the other, much of the technology developed falls into the category of know-how as opposed to patents, making commercialization difficult. Finally, the absence of a patent court implies that a lack of jurisprudence makes it hard to arbitrate disputes, while the issue of assigning intellectual property to discoveries before the Civil Code (2008) remains unresolved. 56. Several initiatives to overcome the financial gap have been put in place in recent years, yet there seems to be a lack of funding instruments for specific firm segments. Most innovators interviewed during the identification mission mentioned the lack of funding for the innovation cycle between the third round of investment from the Foundation for Assistance to Small Innovative Enterprises and the venture capital funding that includes early-stage matching grants – often referred to as the “valley of death.â€? This gap is not even addressed by the recently created seed capital fund of the Russian Venture Company, which was set up by the government to stimulate creation of a venture investment industry, increase the funds of such venture foundations, and move Russian science-intensive technological products and services to world markets. Most Russian venture capital continues to be attracted to mature companies operating in mature markets rather than the early stage financing of Russian firms. Essentially, there seems to be a lack of investment projects that fit venture capital investment criteria. 21 57. Many technology transfer offices (TTOs) in Russia have been created by the Ministry of Education and Science. International experience lends some support to the notion that TTOs, as organizations specialized in managing intellectual property, can play a central role in commercializing public research more quickly. A World Bank/Ministry of Education and Science survey of 112 TTOs conducted in January–May 2011 indicates that Russian TTOs share most of the characteristics of similar institutions in the United States and Europe, including number of employees and formal background; the use of pay scales and incentives, bonuses, and success fees; and engagement in a broader field of innovation-related activities that goes beyond simple technology transfer (figure 18). Yet the simple existence of TTOs will not lead to any huge process of research commercialization unless the appropriate incentive regime for disclosure of discoveries is in place. Figure 18 Characteristics of Russian TTOs, 2010 Sources of income Personnel payment system Additional services provided by TTO or parent institution 8% 20.4 21% 39.5 20% 13% 51% 18.4 54% 18% 15% 0.4 9.9 7.3 0.5 3.6 from parent institution univ. pay scale and bonus incubator and prototyping services licenses royalties in 2010 equity in new companies only univ. pay scale only incubator ss broker for research rent of space only bonus only prototyping ss rent of equipment consulting fees none additional ss other payment system other Source: World Bank/MOES survey 2009 . http://www.enterprisesurveys.org/nada/index.php/catalog/553 Policy Implications 58. We argue that improving the investment climate factors that contribute most to explaining firms’ export propensity – relaxing some of the binding constraints – would enable more firms to break into new foreign markets and contribute to export diversification. In Russia, this essentially means raising productivity, strengthening competition, and promoting innovation and R&D. Enhancing managerial and technical skills and accelerating technology adoption would help raise productivity further, as would improvements in access to better trade logistics. In a nutshell, by reforming the investment climate, Russia’s policymakers could contribute to a more bottom-up approach to export diversification. 22 59. Competition and innovation are sources of economic renewal that in turn are at the core of the long-term development process. Reforms to relax critical binding constraints would also contribute to raised productivity and a greater propensity to export among Russian firms. Over the longer term, the interplay of higher productivity, competition, and innovation would expand the number of exported products and thus raise the density of Russia’s product space. These bottom-up initiatives could then complement the mostly top-down approaches to export diversification currently in use. A stable macroeconomic framework and a governance regime that rewards productive investments rather than rent seeking are also among the critically important underlying factors. 60. Yet traditional export diversification strategies often involve government interventions – industrial policies – that increase economic returns on investments in specific industries. Industrial policies aim to shift economic resources toward industries producing sophisticated, high-tech products. The rationale is to provide temporary conditions for firms to learn by doing and eventually reach international levels of competitiveness. The goal is to achieve faster growth by rapidly increasing productivity or expanding global demand for those products (or both). In addition, export Figure 19 Export diversification: A schematic approach promotion policies are often used to help productive firms overcome market and policy failures specific to the export cycle and exploit export opportunities.24 (These failures are often related to uncertainties in undertaking new activities in foreign markets, especially costs and sunk-entry costs.) Export promotion policies encompass a variety of “softâ€? measures, such as commercial diplomacy and intelligence about foreign markets. In a simplified way, one could map industrial policy and export promotion through two stages of the production-exporting cycle – creating new products and breaking into new markets, but not enabling the emergence of Source: Staff elaboration. productive firms or the survival of new exporters. 61. The contribution of industrial policies to successful export diversification is hard to assess. The popular view that industrial policies have driven export diversification in East Asia becomes controversial when other factors affecting export diversification are taken into account. The Republic of Korea and Taiwan, China, for instance, had large rates of physical and human capital accumulation that shifted their comparative advantage toward capital-intensive goods during the 1960s and 1970s, making it difficult to isolate the effect of industrial policies at that time. In the late 1980s, for example, Korean business expenditures in R&D reached 80 percent of total R&D expenditure. In that period, students with internationally acquired, government-funded PhDs were required to return to Korea and encouraged to work in emerging enterprises. Additionally, the adoption of measures to neutralize the antiexport bias of 24 Newfarmer and others 2009. 23 industrial policies enabled firms to break into foreign markets, achieve efficient sizes, and adopt modern technologies – mitigating any antiexport bias inherent in other measures. 62. Targeting high-tech sectors typically has limited benefit for export diversification. Learning by doing in these sectors is much more challenging, given the rapid technological change relative to that of mature industries with more stable technologies. Developing countries often succeed in mastering the technology of mature products in the high-tech sector, breaking into markets for technological commodities, such as standard computer chips. But they keep up with the frontier less often. The size of the spillover effects of high-tech production is often overestimated. As the U.S. experience of the last two decades suggests, productivity gains are driven mostly by information and communication technology (ICT) in the service sector – not by the expansion of output of ICT industries. ICT and other R&D- intensive sectors generated spillovers and contributed to the U.S. technological leadership during that period, but it is the diffusion of ICT use in services, such as retail, that explains most of the productivity gains of the 1990s. 63. Often-cited instances of new products breaking into foreign markets have limited value as viable models. Internationally competitive high-tech sectors will inevitably command a small share of output and employment in developing countries, given the limited and expensive supply of inputs. Thus the likelihood of generating relevant spillover benefits or greatly improving the country’s labor productivity is bound to be small. For example, the share of Brazil’s output of, and employment from, mid-range Embraer jet manufacturers is less than 1 percent, but as the country develops, the share of services in both output and employment inevitably grows. Other experiences in export diversification, perhaps more relevant to the purpose of this chapter – such as cultivation of asparagus in Peru, cut- flowers in Kenya, or clothing manufacture in Mauritius – failed to generate a continual, dynamic process of export diversification. Generating a process of permanent product upgrading, productivity growth, and innovation is important. 64. A broader view of export diversification, however, gives weight to the emergence of productive firms as well as entry and survival in foreign markets. Such emergence is closely related to the strength of the process of firm entry and exit. Healthy firm dynamics shift output toward more efficient plants, raising average productivity and increasing the likelihood of productive firms introducing incremental innovations (better products and lower costs). 25 Strong business R&D and the massive commercialization of public research are an important source of new ideas to be introduced into the market by entrepreneurial researchers or businesspeople – when the existing governance regime does not shift talent away from productive activities.26 By lowering costs, improving quality, and creating new goods, firms are more likely to break into new markets and sustain their exports for longer. But exports are unlikely to survive and grow if the supply of internationally competitive inputs (the backbone services for exports) is insufficiently elastic to accommodate eventual demand pressures and unforeseen changes in the business environment, such as unpredictable delays in customs, unanticipated power outages, and rent seeking by government officials. 25 See, for instance, Nickell (1996); Blundell and others (1999); and Aghion and others (2005); and Aghion, Braun, and Fedderke 2008. 26 The importance of the scientific community to entrepreneurship has been documented by a growing body of economic research. See, for instance, Rosenberg (2009) in Acs and others (2009). The entrepreneurial pool of a society may engage in productive, unproductive, or destructive activities, depending on the relative pay-offs embedded in the society’s governance regime. Poor governance and weak institutional regimes shift talent from productive activities – innovation, productivity, and starting new firms – toward rent seeking, expropriation of property rights, and crime. See Baumol (1990). 24 65. Open markets and business-oriented technology policies are often ingredients common to the most successful cases of diversification. Chile managed to diversify from its copper-intensive industry to wine, salmon, and fruit by combining unilateral trade liberalization and business-oriented technology policies. Brazil provides another example. The country transformed itself from being highly dependent on coffee exports to becoming a diversified exporter – including the world’s largest food exporter – in the space of roughly one generation. Brazil’s success in the soybean market, for instance, was due to determined trade orientation, entrepreneurship, business-friendly technology policies, and a workable land market (box 3). In addition, a large privatization program helped transform moribund state- owned companies – Compania Vale do Rio Doce (iron ore and other metals) and Compania Siderurgica Nacional (steel) – into global players whose products add to the diversification of Brazilian exports. Worth noting in both cases is how consistency in policy on latent comparative advantages enabled Chilean and Brazilian exporters not only to break into foreign markets but also – thanks to the availability of inputs at competitive prices – to sustain and eventually expand their export volumes.27 Box 3 The case of soybean exports in Brazil Trade orientation, entrepreneurship, and technology policy were the key factors in Brazil’s transformation from a net importer into the world’s second-largest exporter of soybeans in the space of about 30 years. In the early 1970s, the Brazilian government encouraged the cultivation of soybeans in the southern region, where a temperate climate and fertile soil seemed to provide adequate conditions. By the mid- 1980s, however, fertile land in that area had become scarce and rental prices had risen. Agricultural entrepreneurs began looking for alternatives in the then cheap and virtually unexplored “Cerradoâ€? – the Brazilian prairies – an area about the size of France but with completely different soil and climatic conditions. At that time, Embrapa, a government agricultural research institute, was instrumental in rebalancing soil acidity and cultivating crops suited to the country’s tropical climate, thereby expanding the area effectively available for cultivation for soybeans. Embrapa now grows more than 200 varieties of soybeans to suit the country’s diverse soil and climatic conditions. High agricultural productivity and the effective use of land enabled entrepreneurs to explore new export opportunities. Access to better and cheaper agricultural inputs, stemming from broad trade liberalization, were also pivotal in raising agricultural productivity, and soybean exports in particular, after the 1990s. 66. Tailoring export diversification strategy to the country’s characteristics is essential. Export diversification strategies seem more likely to generate broad, sustainable results when they: x Take account of all stages of the production–export cycle – in particular, conditions for the emergence of productive and innovative firms and firm survival in foreign markets. x Are consistent with the country’s comparative advantages (fairly abundant supply of inputs) and allow successful new entrants to foreign markets to sustain and expand their exports. x Adopt industrial policy strategies aimed at increasing the share of international trade in GDP, strengthening firm dynamism, and fostering innovation.28 x Do not distort incentives to attracting talent through unproductive activities, such as rent seeking. 67. There is no universal cookbook for diversification, just some policy lessons and examples of international experience. This implies that a successful policy framework for diversification will inevitably be broad, employing a menu of approaches. This does not mean that everything will need to be 27 See, for instance, Chandra (2006). 28 See, for instance, Harrison and Rodríguez-Clare (2009). 25 done at once or at the same speed, but it does imply that a single approach is unlikely to succeed and that policy attention in each area (and awareness of interlinks) will be needed for long-term success. In the following subsections, we propose a menu of policy options for trade, competition, and innovation, with recommendations summarized in the matrix at the end of the section. To capture the importance of sequencing, the actions are grouped into short- and medium-term priorities. Trade Policy in the Russian Federation 68. Efforts to liberalize trade have been one of the highlights of Russia’s economic reform for the past two decades. Russian authorities have to a large extent adopted the view that growth would be spurred with greater integration with the world marketplace, and as a result tariffs have been lowered, quotas reduced, and import subsidies diminished. At the same time, the country began negotiating accession to the WTO in the early 1990s, with bilateral market access negotiation finalized with interested WTO members, including the United States, and accession completed in August 2012. 69. Yet some hurdles remain for Russia’s full integration with the rules-based trading system. The global economic crisis had an impact on the pace of trade liberalization and the finalization of Russia’s WTO accession process. Although Russia reduced tariffs in 2007 and 2008, the prevailing trend in 2009 was to increase them on medium-tech products in response to the crisis. The government increased tariffs on processed foods, light manufacturing, the automotive sector, and some construction equipment and indicated that it would continue to review its tariff policy in light of overall economic conditions. Tariff data show that Russia uses relatively few tariff policy measures to restrain import competition. Nonetheless, among the BRICs, the Overall Trade Restrictiveness Index in Russia is higher than in India and China and only slightly lower than in Brazil. 70. No single entity is in charge of export promotion in Russia. At the federal level, the function of export support and promotion is divided between the Ministry of Industry and Trade and the Ministry of Economic Development, with the Ministry of Agriculture dealing with export promotion of agricultural products. At the regional level, every ministry/department that deals with economic development and enterprise support has a section that deals with export promotion. Internationally, the private sector also supports related activities, as illustrated by the case of the Moscow Investment and Export Promotion Agency. Recent evidence suggests that export promotion agencies generally have a significant positive effect on exports, though with decreasing returns to scale in resources devoted to export promotion.29 Export promotion agencies with larger shares of private sector representation but with more public funding are associated with larger national export. Yet, although funding is a crucial issue for firms when deciding whether to export, many other factors, as international practices have shown, play an important part in creating successful export promotion agencies, such as firm leadership, skilled agency staff, and strong international market presence. 71. To encourage the participation of SMEs in exports, the government has adopted a resolution with additional measures to support SMEs that export industrial products. The program, started in October 2010 and totaling US$2 billion, will subsidize costs associated with loan interest, with SME-related payments of certification, firm registration, or other forms of conformity assessment, with exhibitions and fairs abroad, and other costs. The program will support the creation and maintenance of regional coordinating centers to support export-oriented SMEs. A key principle for the organization and 29 Lederman and others 2010. 26 operation of these centers is that they should carry out their activities in close cooperation with the Ministry of Economic Development, Russian trade missions to foreign countries, and other relevant authorities of the Russian Federation. There will also be a need for qualified personnel capable of implementing the basic functions of export and investment promotion to support exports and attract investment to the region. The idea is for these centers to act as a “single windowâ€? for export-oriented SMEs and to attract investment. 72. Our analysis has shown that licensing policies and country-specific tariff rate quotas are limiting the ability of Russian firms to benefit from competition, in turn creating obstacles to the innovation process. For instance, import licenses are necessary for importing certain products, including alcoholic beverages, pharmaceuticals, hazardous wastes, and some food products. These licensing policies, with tariff rate quotas, are the most binding nontariff measures limiting the ability of Russian firms to benefit from competition, creating obstacles to innovation. Adopting a low, uniform tariff structure could benefit an economy that seeks to enhance export diversification through innovation. Recent literature has shown that lower tariffs levels are associated with quality upgrading for products close to the world quality frontier,30 while discouraging quality upgrading for products distant from that frontier. Tarr (2000) has provided a compelling case for Russia to favor tariff uniformity over differentiated tariff protection, based on political economy considerations, administrative convenience, and reduction of smuggling and corruption in customs. 73. Findings further support the notion that fixed costs to export are higher in Russia than in some peer countries. We explored this issue by examining the role of the current tax code on the probability of being tax audited (one source of fixed costs for exporters). Preliminary analysis suggests that the probability of being audited is around 20 percent higher for exporters than for nonexporters in Russia. This finding is in line with the explanation that the value-added tax refund may encourage tax inspections, but this issue should be explored further. Nonetheless, reducing such fixed export costs could provide opportunities to encourage firm exports and to facilitate enterprises in establishing new export relationships. 74. Based on these findings, we summarize the policy options in trade policy and diversification as follows: Short-term policy options x Develop further the program for regional coordinating centers, while ensuring private involvement and access to qualified, skilled personnel. x Commit to a long-term process involving monitoring and evaluation, government learning, and policy adjustment. Medium-term policy options x Create a low, uniform tariff structure, thus encouraging innovation close to the world quality frontier. x Encourage firms to enter new markets by lowering fixed (sunk) costs to export, such as tax audits when exporting versus operating in the local market. 30 See, for instance, Amiti and Khandelwal (2009). 27 Competition Policy in the Russian Federation 75. A comprehensive competition policy would establish a level playing field and facilitate entry and encourage orderly exit of less efficient firms, contributing to increased productivity and export propensity. The creation of a European single market is an example where setting up an active competition policy went beyond business behavior and covered control of state aid. This policy helped ensure fair competition and contributed to the convergence of Europe with U.S. productivity levels and to higher competitiveness, both for the region as a whole and for individual member economies. Another example of an economy that successfully transformed its national competition policy is Australia, with its National Competition Policy. The country opened its market to international competition, eliminated barriers to trade among its states, and became a world leader in procompetitive product market regulation in more recent years. The new competition policy was implemented through an incentive scheme in which the national government financially rewarded achievements of negotiated milestones (or punished a lack of achievement; box 4). 76. A comprehensive competition policy in Russia would need to address issues remaining from the transition agenda and new challenges related to introducing procompetitive regulations in product markets. The main issues are state ownership, price control, and trade policy; regulation of entry and exit; asymmetric application of existing rules and access to state aid; and regulation of service sectors (including infrastructure). Several of these factors may have significant regional variance and may contribute to mitigating (or accentuating) geographic factors such as lack of infrastructure, thereby generating unequal opportunities for growth among regions. 77. A series of policy interventions fostering competition in Russia could level the playing field and facilitate entry of new businesses. Such policies could help increase productivity and consolidate Russia’s domestic market, enabling domestic firms to benefit from additional gains from trade. Short-term policy options x Advance government reforms of public enterprises, ensuring alignment with market forces. x Broaden the mandate on state aid regulation in order to diminish sector- and firm-specific state aid. x Align state aid regulation and enforcement with international best practice (focus on horizontal objectives and include balancing tests that analyze the effects of state aid on competition). x Introduce certificates of independent bidding determination and prohibitions to contract and participate in public procurement if a firm has participated in a cartel. x Create an inventory of state aid by beneficiary and evaluate distortions of competition of state aid (including tax arrears). x In transport, eliminate price controls and government involvement. x In construction, provide a unified database of land plots with complete information about ownership and usage status in the construction industry. x In professional services, provide specific prohibitions toward self-regulation that facilitate price- fixing and limits entry. Medium-term policy options x Eliminate preferential treatment to state- or municipality-owned corporations. 28 x In transport, reduce direct participation of the state in the provision of goods. x In construction, streamline the processes for registration, construction permits, and licensing schemes. Box 4 Competition policy in action: the Australian experience The extensive competition policy reforms in Australia gained broad consensus at the highest political levels, through preparation of the parliamentary Hilmer Report in the early 1990s and through the key role held by parliament in monitoring the implementation of the main policy recommendations. After continuing pressure from business sectors exposed to international competition, such as agriculture and large enterprises, to reform nationwide infrastructure (including energy and ports), and after recognizing the importance of national competition to productivity growth and increased living standards, policymakers in Australia agreed in 1992 to the development of a national competition policy and a 10-year reform agenda. The establishment of a formal Council of Australian Governments and continual meetings with representatives of federal, state, and local governments in special Premiers’ Conferences led to the creation of a formal institutional setting for cooperation on the reform agenda. Subsequently, an Inquiry Committee, chaired by Professor Frederick Hilmer, was set up to undertake an independent inquiry into a National Competition Policy (NCP), resulting in a report presented to the Council in August 1993 with the outcome that the broad scope of the Hilmer proposals were endorsed. Australia’s competition-oriented reforms happened in three waves, first through increased exposure to international markets in the early 1990s, next with the development and implementation of the NCP in the mid-1990s, and then with regular updates from the late 1990s. Comprehensive reforms, coordinated across all levels of government, aimed to reform all legislation restricting competition; implement a culture of “continuous improvementâ€? in regulatory quality; implement competitive neutrality for all public businesses; and provide third-party access to significant infrastructure facilities. The NCP was implemented through an incentive scheme in which the national government financially rewarded achievements of negotiated milestones (or punished a lack of achievement). A system of “competition payments,â€? defined as the state’s share of additional revenue arising from the NCP, was introduced. Payments were made from federal governments to state governments that implemented specific reforms, and pecuniary penalties were imposed on slow reformers, in the form of reduced or delayed budget transfers from the central government. Although a majority of reform goals in competition policy were met on time in the 10-year period, some cases of pecuniary penalties for slow reformers exist. For instance, Western Australia’s uncompleted plans for water systems led to a 5 percent suspension penalty of its 2005–06 competition payments. When reform goals were finally met in 2007, suspended payments were then disbursed. Similarly, Queensland’s failure to address anticompetitive restrictions in liquor licensing resulted in a 5 percent permanent deduction penalty of the state’s 2003–04 competition payments (see table). The Australian experience is considered one of the most successful examples in recent years. The NCP helped make Australia one of the top performing OECD economies and has enhanced economic flexibility and adaptability to change, showing the quickest recovery from the global crisis among OECD countries. The reforms have reduced barriers to entry and exit, have improved competition, and are estimated to have increased GDP by 2.5 percent (excluding dynamic effects). National competition payments, 2002–03 to 2005–06 (US$ million) 29 Source: Corden 2009; Kain 1995; Hilmer 1993. Innovation and Commercialization Policies in the Russian Federation 78. The main challenge for commercializing public research is how to balance the interests of researchers and research organizations vis-à-vis this objective. Commercialization often requires an additional engagement from the researcher that is inconsistent with his or her career objectives. Universities also do not have a natural incentive for managing intellectual property that may emerge from publicly funded research – costs are high and to a large extent sunk, and transaction costs are abundant. Returns, on the other hand, are often uncertain. In the United States, for instance, the insignificant commercialization of research by universities motivated the adoption of the Bayh-Dole Act in 1980. The act transfers to the universities the intellectual property rights resulting from publicly funded research, establishes a minimum amount of royalties to be shared with the researcher, and greatly simplifies the process of intellectual property management (which previously had been subject to more than 20 different pieces of legislation). These changes enabled more universities to afford the investments required to effectively monitor, protect, and market intellectual property and encouraged academic researchers to engage in the related activities. Similar versions of this act have been adopted in about 20 OECD countries. 79. A number of policy measures have been launched in recent years to foster innovation in Russia – with particular emphasis on emulating the experience of Silicon Valley. One example is the development of Rusnano (a state-owned fund for venture capital financing) and Skolkovo (planned as a science city). In addition, Russia has recently created more than 950 companies based on publicly funded research discoveries, which shows how Russian innovation policy, if scaled up, could raise the productivity of SMEs and contribute to a more diversified economy. This success is a consequence of the Russian government’s efforts to provide sound innovation policies, improve the legal framework, and create supporting services for innovation. Yet a larger process of spinoffs would not necessarily emerge from the current conditions, since current innovation policies still need fine-tuning and improvements. Challenges include increasing the volume of high-quality research; improving the management of intellectual property emerging from public research; increasing the availability of public funding in all operational stages; strengthening governance and reducing the fragmentation of public R&D programs; 30 and targeting availability of support organizations (TTOs, incubation services, and science parks) beyond supply of physical infrastructure. 80. Despite the government’s strengthened focus on increasing competitiveness of Russian enterprises through modernization and improved innovation capacity, the country still lags in commercializing its research base. We suggest several policy measures for Russia’s innovation system, human capital, and intellectual property legal framework, which could help foster commercialization. Short-term policy options x Strengthen the results-based management of public research organizations, with allocation of public funding based on scientific output and acknowledgment of commercialization efforts. x Develop performance-based career development for researchers, with support for young scientists a priority. x Facilitate research collaboration with Russian researchers based abroad. x Transfer full ownership (not only use) of the intellectual property to public research organizations through amendments to Civil Code Section IV and Federal Law 217. x Provide funds for early-stage development of technologies to address the financial gap between the Foundation for Assistance to Small Innovative Enterprises and the venture capital funding that includes early-stage matching grants. x Enhance the supply of financing for innovative start-ups through early-stage matching grants, differentiated tax breaks for SMEs, and integration of business development services in one agency. Medium-term policy options x Expand commercialization efforts to include areas with potential for new ideas, such as the Russian Academy of Sciences, the defense sector, and agricultural research. x Continue to reform the investment climate, focusing on skills and technology adoption, favoring business investments in R&D. x Continue improving the governance of the overall economy to decrease incentives for rent seeking and to incentivize the allocation of talent, entrepreneurship, and innovation. 31 Policy Options Matrix Strategic Goal: To broaden Russia’s export base through enhanced competition and innovation policies. Objective Short-term policy options Medium-term policy options ή Develop further the initiated program for regional ή Create a low, uniform tariff structure, thus coordinating centers to support and promote export- encouraging innovation close to the world quality Facilitate oriented SMEs, serving as “one-stop-shops,â€? while frontier. and ensuring private sector involvement and access to qualified, skilled personnel. ή Encourage firms to enter new markets by promote trade ή Commit to a long-term process involving monitoring and lowering fixed (“sunkâ€?) costs to export (facing evaluation, government learning, and policy adjustment.. tax audits when exporting versus operating in the local market). ή Advance government reforms of public enterprises, ή Eliminate preferential treatment to state- or ensuring alignment with market forces. municipality-owned corporations. ή Broaden the mandate on state aid regulation in order to ή In the transport sector, reduce direct participation diminish state aid to particular firms and sectors. of the state in the provision of goods ή Align state aid regulation and enforcement with ή In the construction industry, streamline the international best practice (focus on horizontal objectives, processes for registration, construction permits, and include balancing tests and the effects of state aid on and licensing schemes for each segment of the competition). supply chain. ή Introduce Certificates of Independent Bidding Determination and prohibitions to contract and participate Enhance in public procurement if a firm has participated in a cartel. competition ή Create an inventory of state aid by beneficiary and evaluate distortions of competition of state aid (including tax arrears). In the transport sector, eliminate price controls and government involvement ή In the construction industry, provide a unified database of land plots with complete information on ownership and usage status. ή In professional services, provide specific prohibitions toward self-regulation that facilitates price-fixing and limits entry. x Strengthen the results-based management of public x Expand commercialization efforts to include areas research organizations, with allocation of public funding with potential for new ideas (for example, the based on scientific output and acknowledgment of Russian Academy of Sciences, the defense sector, commercialization efforts. agricultural research). x Develop performance-based career development for x Continue to reform the investment climate, researchers, with support for young scientists as a priority. focusing on skills and technology adoption and x Facilitate research collaboration with Russian researchers favoring business investments in R&D. based abroad. x Continue to improve the governance of the overall x Transfer full ownership (not only use) to public research economy to decrease incentives for rent seeking Accelerate organizations through amendments of Civil Code Section and incentivize the allocation of talent, innovation IV and the Federal Law 217. entrepreneurship, and innovation. x Provide funds for early stage development of technologies to address the financial gap between the Foundation for Assistance to Small Innovative Enterprises and the venture capital funding that includes early-stage matching grants. x Enhance the supply of financing for innovative start-ups through early stage matching grants, differentiated tax breaks for SMEs, and integration of business development services in a single agency. 32 References Aghion, Philippe, Nicholas Bloom, Richard Blundell, Rachel Griffith, and Peter Howitt. 2005. “Competition and Innovation: An Inverted-U Relationship.â€? 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GAIN Report RS1012. http://gain.fas.usda.gov/Recent%20GAIN%20Publications/Agricultural%20Budget%20in%202010_Moscow_Russi an%20Federation_3-9-2010.pdf. Volchkova, Natalya. 2010. “Dissecting Russian Export: Firm, Industries, and Destinations.â€? Centre for Economic and Financial Research Presentation at the New Economic School Conference, November 13, Moscow. World Bank. 2006. “Enhancing the Impact of Public Support to Agriculture and Rural Sectors.â€? Report 39213. Washington, DC. ———. 2007. Energy Efficiency in Russia: Untapped Reserves. Washington, DC: World Bank and International Finance Corporation. ———. 2008. Unleashing Prosperity: Productivity Growth in Eastern Europe and Former Soviet Union. Washington, DC. ———. 2009. “Russian Federation—Regional Development and Growth Agglomerations: Longer-Term Challenges of Economic Transition in the Russian Federation.â€? Country Economic Memorandum Report 45486. Washington, DC. ———. 2011a. “Russian Economic Report 25: Securing Stability and Growth.â€? Moscow and Washington, DC. ———. 2011b. Russia: Reshaping Economic Geography. Washington, DC. ———. 2011c. World Development Indicators 2011. Washington, DC. 35 Chapter 1: Analysis of Selected Trade Outcomes  in the Russian Federation x Russia’s oil and gas exports grew in the decade from slightly less than half to about two- thirds of the country’s total exports in 2008, giving Russia the highest level of product concentration among the BRICs. The problem encompasses not only merchandise trade but also trade in services – a potential alternative for export diversification. A gravity model applied to nonoil exports in conjunction with an assessment of the pattern of trade at the regional level indicates the existence of untapped potential of export diversification within established bilateral trade relationships. These results back the idea of regional export promotion agencies supporting mainly small and medium enterprises to engage in exports. x There are problems of quality/sophistication of Russia’s export basket. The sophistication of Russia’s export basket has almost continuously decreased over time while China’s and India’s have increased. By 2008, China had overcome Russia as the BRIC country with the highest export sophistication. Russia’s short-run opportunities to move to new products are few and the country has limited scope for quality upgrading. Econometric analysis supports the notion that quality and innovation significantly affect the probability of exporting at the firm level: a 1 percent increase in quality and innovation increases the export propensity of Russian firms by 32.9 percent. These findings set the stage for innovation-driven economic growth, in line with the government’s 2008 Long Term Strategy for Socio-Economic Development. The challenge remains how to translate the created research base into commercial innovation and to incentivize firms to start adopting this knowledge in the production processes. x Analyses indicate low rates of survival of export relationships in Russia. The probability of an export relationship surviving until the second year is about 0.57, and maintaining a relationship for five years is 0.22, both much lower than in Brazil, China, or India. This result is even more striking when coupled with the fact that, as expected given its development level, most of the export growth in Russia takes place at the intensive margin, with increases of old products in old markets. These results highlight the importance of policies that focus on sustaining current trade relations and on encouraging new durable trade relationships at the firm level. These types of policies may, for instance, be implemented by the recently reinforced regional export promotion agencies. x The results presented in this chapter suggest taking a broader view of the diversification challenge in Russia, encouraging the emergence of productive and innovative firms, and achieving a higher rate of firm survival in foreign markets. Raising the share of non-resource exports in Russia has so far proved difficult – similar to what has been seen in other countries. Experience also shows that there is no magic recipe to promote export diversification. Discovering a strategy that could induce export diversification within Russia’s institutional, political, and economic constraints is instead likely to be a gradual process involving recurrent assessments, government learning, and policy adjustment.  This chapter was prepared by Jose Guilherme Reis, José-Daniel Reyes, and Guillermo Arenas, at the World Bank International Trade Department. 36 x Licensing policies and country-specific tariff rate quotas are the two binding nontariff measures limiting the ability of Russian firms to benefit from competition. This in turn creates obstacles to the innovation process. Adopting a low and uniform tariff structure could bring benefits for an economy that seeks to enhance export diversification through innovation. Recent literature has shown that lower tariffs are associated with quality upgrading for products close to the world quality frontier, but discourage quality upgrading for products distant from the frontier. Tarr (1999) has provided a compelling case for Russia to favor tariff uniformity over differentiated tariff protection, based on political economy considerations, administrative convenience, and reduction of smuggling and corruption in customs. x Analysis supports the view that the fixed costs to export are higher in Russia than in some peer countries. We explore this issue by examining the role of the current tax code on the probability of being tax audited, as one source of fixed costs for exporters. Preliminary analysis suggests that the probability of being audited is around 20 percent higher for exporters than for nonexporters. This finding is in line with the explanation that the value-added tax refund may encourage tax inspections, but this issue deserves to be explored further. Orientation and Growth of Trade 1.1. In the last decade, Russian exports have become increasingly concentrated in natural resources. Russia’s government is consciously attempting to reduce the risk associated with overreliance on a narrow range of natural resource–based sectors, by exploring policy options to increase economic and export diversification. In what follows, we review recent trends of trade in Russia. Given data availability, the analysis focuses more on merchandise trade, but some results for the services sector are also incorporated.32 Openness to Trade 1.2. The trade-to-GDP ratio is one of the most basic indicators of openness to foreign trade and economic integration. It weighs the combined importance of exports and imports of goods and services in an economy. The ratio gives an indication of the dependence of domestic producers on foreign demand and of domestic consumers and producers on foreign supply. There is a concave relationship between trade openness and per capita income: countries tend to trade more as incomes rise, but at a falling rate. Russia’s position below the predicted line indicates that it undertrades relative to countries at comparable levels of per capita income. A decade ago (1996–98) Russia had the highest openness to trade among the BRICs (figure 1.1) but, in contrast to its peers, trade has remained at around 50 percent of GDP. China and India doubled their average trade-to-GDP ratio. Now (2006–08), China has overcome Russia, and India is approaching Russia’s level of openness to trade (figure 1.2). Even Brazil, which has a low trade- to-GDP ratio, became more open over this period, with an increase in the ratio from 15 percent to 26 percent. 32 All econometric and graphical analysis and presentations draw on the authors’ calculations using UN Comtrade data unless stated otherwise. Export information is obtained from mirror data. 37 Figure 1.1 Openness to trade, 1996–98 Figure 1.2 Openness to trade, 2006–08 Openness to Trade 9698 Openness to Trade 0608 250 250 MYS 200 200 MYS Trade to GDP (%), 0608 Trade to GDP (%), 9698 VNM HUN 150 150 BGR CZE HUN CZE 100 100 BGR LVA LVA VNM CHN RUS RUS 50 50 IND CHN IND BRA BRA 0 0 6 7 8 9 10 11 6 7 8 9 10 11 Log of GDP per capita (PPP, av. 9698) Log of GDP per capita (PPP, av. 0608) Source: UN Comrade Source: UN Comrade 1.3. Another indicator is a country’s share in world exports over time. In 2002, Russian exports constituted 1.6 percent of world exports compared with China’s 4.6 percent and with the United States’ 12.2 percent. In 2008, Russia’s share had risen to 2.7 percent while that of China had risen to 8.1 percent and that of the United States’ had fallen to 9.4 percent. Russia’s ability to increase its export share is mainly due to the reliance on extractive industries. Table 1.1 Russian exports, 2000–09 2000 2009 CAGR(%) product/sector Exports(US$'000) %of total Exports(US$'000) %of total 00Ͳ 09 Petroleumoils 31,628,491 34.8 140,231,624 54.5 18.0 (HS270900,HS271000) Natual GasIngaseousstate  6,592,387 7.2 23,723,226 9.2 15.3 (HS271121) Ironsteel andothermetals 19,161,171 21.1 29,372,322 11.4 4.9 (HS26,72Ͳ 83) OtherExtractive Industries 10,836,901 11.9 19,168,232 7.4 6.5 (HS25Ͳ 27,68Ͳ 71) Chemicals,plastic,rubber 7,994,370 8.8 17,836,354 6.9 9.3 (HS28Ͳ 36,38Ͳ 40) Foodbeverages,tobacco,wood,paper 5,530,597 6.1 11,056,567 4.3 8.0 (HS11,15Ͳ 24,44Ͳ 48) Machinery,electronics,transportequipment 3,696,972 4.1 7,755,943 3.0 8.6 (HS84Ͳ 89) Agriculture,meatanddairy,seafood 3,501,033 3.8 6,341,190 2.5 6.8 (HS1Ͳ 10,12Ͳ 14) Textiles,apparel,leather,footwear 1,247,702 1.4 596,894 0.2 Ͳ 7.9 (HS41Ͳ 42,50Ͳ 65) OtherIndustries 749,941 0.8 1,450,394 0.6 7.6 (HS37,43,49,66Ͳ 67,90Ͳ 97) Total 90,939,565 100 257,532,746 100 16.0 Source:Comtrade Composition of Exports 1.4. Russia’s exports are dominated by petroleum and natural gas. These two products experienced double-digit annual export growth in the last decade, representing almost 65 percent of Russia’s exports by value in 2009 (table 1.1, above). The combined share of the more sophisticated industries including machinery, electronics, transportation equipment, and chemicals was about 10 percent in 2009. Although these sectors experienced annual growth rate of almost 10 percent during the last decade, their share in the overall export basket decreased due to the outstanding export  The sectoral classification follows Hanson (2010). Export values reflect mirror data in Comtrade, with possible underreporting. 38 performance of oil and gas. Russia’s exports of high-tech products are low, considering what an industrial powerhouse the Soviet Union used to be. 1.5. The remarkable oil export performance in nominal values is the product of high prices and high export volumes. While the average nominal price of a barrel of oil more than doubled between 2000 and 2009, Russian oil exports by volume went from 144.4 million tons to 247.5 million tons over the period (table 1.2). The change in relative prices – in favor of oil, gas, and metals – and the real appreciation of the ruble may also have depressed the growth of non-resource tradables and contributed to the failure to diversify. Table 1.2 Russian crude oil exports, 2000–09 Russia:CrudeOilExports,2000Ͳ2009 Total GrowthRates(%) Volume Value Volume Value Averagepriceofexport mln.Tons mlnof USD USD/Barrel 2000 144.4 25271.9 23.9 2001 164.5 24990.3 13.9 Ͳ 1.1 20.8 2002 189.5 29113.1 15.2 16.5 21.0 2003 228.0 39679.0 20.3 36.3 23.8 2004 260.3 59044.8 14.2 48.8 31.0 2005 252.5 83438.0 Ͳ3.0 41.3 45.2 2006 248.4 102282.9 Ͳ1.6 22.6 56.3 2007 258.6 121502.8 4.1 18.8 64.3 2008 243.1 161147.0 Ͳ6.0 32.6 90.7 2009 247.5 100593.2 1.8 Ͳ 37.6 55.6 Source:Bankof Russia. http://www.cbr.ru/eng/statistics/print.aspx?file=credit_statistics/crude_oil_e.htm 1.6. Exports from non-resource-based industries in Russia have grown at a slower pace than the average in the other BRICs (figure 1.3). Extractive industries bucked this trend, indicating that the country is concentrating in resource-based industries. Figure 1.3 Compound average growth rate, BRICs, 1998–2008 30.0 20.0 10.0 0.0 Foodbeverages, Ironsteelandother  Chemicals,plastic, Textiles,apparel, Extractive Industries Agriculture,meat anddaity, seafood TransportEquipm tobacco,wood, leather,footwear Machinery, Electronics, Ͳ10.0 paper rubber metals Rusia Brazil China India Average* * Average doesnotinclude Russia Source: UN Comrade 39 1.7. As historical evidence suggests, diversifying away from oil and gas (especially, as in Russia’s case, when reserves are abundant) can be slow. Among the few exceptions are Indonesia and Egypt (figure 1.4). Figure 1.4 Change in dependence of oil and gas Share in Merchandise Exports 100 BRN NGAIRQ Share of Oil and Gas exports, 2006-2008 DZA KWT QAT VEN SAU IRN 80 ARE GAB TTO SYR 60 RUS ECU BHR EGY 20 40 IDN IND BRA CHN 0 0 20 40 60 80 100 Share of Oil and Gas exports, 1993-1995 Source: UN Comrade 1.8. Russia’s agricultural exports fell to a mere 2.5 percent in 2009, from 3.8 percent in 2000. Although not usually identified as such, agriculture is an important alternative for diversification for a country like Russia, given availability of agricultural land. Trade in commodities, shunned a couple of decades ago, offers new opportunities to countries. New dynamics in global commodity markets have emerged and will prove particularly important in the post-crisis environment. First, commodities are experiencing strong and sustained demand from developing countries – especially China. Second, commodity markets are now more than ever linked to energy markets, because of the increasingly important role played by biofuels. As a result, price prospects are strong in oil and agriculture markets alike. Although this is good news for commodity exporters, stronger governance and efficient regulation will be necessary to manage commodity wealth, and avoid some of the negative impacts that have accompanied previous instances of high prices, such as Dutch disease. For agricultural commodity importers, food insecurity will have severe implications for people, particularly the poor. 1.9. Brazil is a good example. The country transformed from being highly dependent on coffee exports to becoming a diversified exporter – and the world’s largest food exporter – in roughly one generation. Brazil’s success in soybean markets, for instance, was due to trade orientation, entrepreneurship, business-friendly technology policies, and a workable land market. In addition, a large privatization program helped transform moribund state-owned companies – Compania Vale do Rio Doce (iron ore and other metals), and Compania Siderurgica Nacional (steel) – into global players whose products help diversify Brazilian exports. Consistency with latent comparative advantages enabled Brazilian exporters not only to break into foreign market but – thanks to the availability of inputs at competitive prices – sustain and eventually expand their export volumes. 1.10. The importance of trade in services (as a percentage of GDP) in Russia dropped continuously from 2002. Both exports and imports declined (figure 1.5). This trend is particularly worrisome relative to China and India (figure 1.6). By sector, transportation (29 percent) and travel (23 percent) services accounted for the bulk of Russia’s exports in 2008. By annual growth, business 40 (37 percent) and construction services (38 percent) were among the most dynamic sectors in Russia, while travel (19 percent) and transportation (18 percent) had the slowest growth over the period. Figure 1.5 Russia’s export and import of Figure 1.6 Trade in services, BRICs (1994=1) services (% of GDP) 16 14 12 Brazil China 10 India Russia 8 6 4 2 0 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Source: UN Comrade Source: UN Comrade 1.11. The limited dynamism of services exports in Russia is a concern, given the objective to diversify exports. Trade in services, particularly business services, has become a dynamic component of trade as well as an alternative for export diversification in developing and developed countries. During 2000–07, trade in services grew as fast as trade in goods, at an average 12 percent a year. A large number of developing countries have successfully exported services, both within their own regions and to high- income countries. India’s success is well known: exports of software and business process services account for around 33 percent of India’s total exports. 1.12. According to the A.T. Kearney Global Services Location Index 2007, Russia is not considered an attractive location for offshoring business, ranking 37 of 50 countries. Versus the other BRICs, Russia is at a clear disadvantage given that India and China are the most attractive offshoring destinations and Brazil rounds out the top five (table 1.3). Russia is not well positioned even among Central and Eastern European countries (table 1.4). Despite having competitive wages, a large population, and strong technical skills, very weak business environment scores leave Russia at the bottom of the regional rankings (ahead only of Ukraine). As the A.T. Kearney report (2007) highlights, eroding low wage–based competitiveness around the world means that the key to maintaining and enhancing long-term competitiveness in services offshoring lies in developing skills, investing in infrastructure, and strengthening the regulatory environment. Russia needs to improve its weak business environment if it intends to reap the benefits of offshoring services. Table 1.3 A.T. Kearney offshoring rankings, BRICs, 2007 Financial People and skills Business Rank Country Total score attractiveness availability environment 1 India 3.22 2.34 1.44 7.00 2 China 2.93 2.25 1.38 6.56 5 Brazil 2.64 1.78 1.47 5.89 37 Russia 2.61 1.38 1.16 5.14 Source:AT Kearney, 2007 41 Table 1.4 A.T. Kearney offshoring rankings, Central and Eastern European countries, 2007 Financial People and skills Business Rank Country Total score attractiveness availability environment 9 Bulgaria 3.2 1.0 1.6 5.75 12 Slovak Republic 2.8 1.0 1.8 5.62 15 Estonia 2.4 1.0 2.2 5.60 16 Czech Republic 2.4 1.1 2.1 5.57 17 Latvia 2.6 0.9 2.0 5.56 18 Poland 2.6 1.2 1.8 5.54 24 Hungary 2.5 1.0 2.0 5.47 28 Lithuania 2.6 0.8 2.0 5.42 33 Romania 2.9 0.9 1.5 5.28 37 Russia 2.6 1.4 1.2 5.14 47 Ukraine 2.8 1.0 1.1 4.83 Source: AT Kearney, 2007 Trading Partners 1.13. Russia’s nonoil exports are concentrated in five regions. In 2000, the European Union (EU), the United States, post-Soviet countries, China, and Japan took roughly 75 percent of Russia’s nonoil exports (figure 1.7). This picture changed little by 2009 (figure 1.8), except that Turkey became the fourth export market and Japan lost importance. The composition of the top markets also changed: China and the post-Soviet markets gained relevance, while the United States lost more than half its share. Figure 1.7 Russia’s nonoil export destinations, 2000 Figure 1.8 Russia’s nonoil export destinations, 2009 24.7 33.7 24.7 28.6 8.5 5.5 6.5 8.9 13.5 20.8 10.8 13.9 EuropeͲ27 UnitedStates PostSoviet Countries EuropeͲ27 PostSoviet Countries China China Japan Other Turkey UnitedStates Other Source: UN Comrade 1.14. During the last decade, Russia has had a major role in the European energy sector as the largest exporter of oil and natural gas to the EU (figures 1.9 and 1.10). Other important markets are the post-Soviet countries, the United States, and China. 42 Figure 1.9 Russia’s oil and gas export destinations, Figure 1.10 Russia’s oil and gas export destinations, 2000 2009 p ( ) 2.0  2.3  7.2  14.6  5.0  7.7  8.4  59.0  12.9  80.9  EuropeͲ27 PostSoviet Countries EuropeͲ27 PostSoviet Countries UnitedStates China UnitedStates China Other Other Source: UN Comrade How “Naturalâ€? are these Trading Partners? 1.15. One of the most successful empirical relationships in economics is the gravity equation, which relates the value of trade between countries to their size and the economic distance between them. The model provides a framework to evaluate the observed bilateral trade relative to the trade predicted by the model. Given the overreliance of Russia on its oil and gas exports, it is instructive to do this exercise with and without hydrocarbons. 1.16. We ran a cross-country regression on Russia’s exports in 2008 (using mirror data) on various bilateral characteristics with trading partners. With these steps and those detailed in annex 1A, the gravity results of whether a country overtrades or undertrades with particular partners are better grounded in trade theory. 1.17. Considering Russia’s total export value, it is apparent that the country undertrades with China and India as well as with several G-8 countries (figure 1.11) including the United States, Italy, and Germany (located above the 45-degree line). But Russia slightly overtrades with Brazil and Japan. Not considering oil and gas, Russia undertrades with many countries (figure 1.12). In this setup, exports to China are approximately what the model predicts indicating that around 14 percent of nonoil exports are directed to China in this period. This analysis suggests the existence of untapped potential of export diversification at the industry/product level within established bilateral trade relationships. Figure 1.11 Total exports, Russia, 2006–08 Figure 1.12 Nonoil exports, Russia, 2006–08 Predicted v Actual Exports Predicted v Actual Exports 20 Log of Predicted Exports, 2006-2008 Log of Predicted Exports, 2006-2008 18 CHN DEU IND USA ITA DEU IND USA ITA CHN JPN 16 15 JPN BRA BRA 14 12 10 10 8 5 8 10 12 14 16 18 8 10 12 14 16 18 Log of Actual Exports, 2006-2008 Log of Actual Exports, 2006-2008 Source: UN Comtrade Source: UN Comtrade 43 Revealed Comparative Advantage 1.18. The revealed comparative advantage (RCA) is an index used in international economics for calculating the relative advantage or disadvantage of a certain country in a certain class of goods or services as evidenced by trade flows. Due to the concentration of its export products around extractive industries, Russia exhibits RCA in only two sectors: extractive industries and iron and steel. This is somewhat different from the experience of the other BRICs (figure 1.13). For instance, Brazil, in addition to having RCA in the same sectors as Russia also has it in agriculture products, and foods and beverages, while India also has comparative advantage in chemicals, agriculture, and apparel. Finally, China shows RCA in iron, machinery, other industries, and apparel. Figure 1.13 RCA, BRICs, 1996–98 and 2006–08 Russia Brazil .8 2.4 Agriculture, meat and diary, seafood .6 Agriculture, meat and diary, seafood 4 .8 .7 Chemicals, plastics, rubber .5 Chemicals, plastics, rubber .6 4 1 Extractive industries 3.3 Extractive industries 1.2 .7 3.3 Food, beverages, tobacco, wood, paper .7 Food, beverages, tobacco, wood, paper 3 3.3 1.7 Iron, steel, and other metals 1.7 Iron, steel, and other metals 1.2 .1 .5 Machinery, electronics, transportation equip. .1 Machinery, electronics, transportation equip. .5 .2 .3 Other industries .1 Other industries .2 .2 .8 Textiles, apparel, leather, footwear .1 Textiles, apparel, leather, footwear .7 0 1 2 3 4 0 1 2 3 4 rca9698 rca0608 rca9698 rca0608 China India .7 2.4 Agriculture, meat and diary, seafood .4 Agriculture, meat and diary, seafood 1.5 .5 .8 Chemicals, plastics, rubber .5 Chemicals, plastics, rubber 1 .4 1.8 Extractive industries .2 Extractive industries 1.7 .5 .7 Food, beverages, tobacco, wood, paper .5 Food, beverages, tobacco, wood, paper .6 .7 .9 Iron, steel, and other metals 1 Iron, steel, and other metals 1.2 .7 .2 Machinery, electronics, transportation equip. 1.3 Machinery, electronics, transportation equip. .3 2.5 .4 Other industries 2.1 Other industries .4 3.7 3.9 Textiles, apparel, leather, footwear 3.1 Textiles, apparel, leather, footwear 3.2 0 1 2 3 4 0 1 2 3 4 rca9698 rca0608 rca9698 rca0608 Source: UN Comrade Diversification 1.19. Russia is consciously attempting to lessen the risks and vulnerabilities from overreliance on a narrow range of natural resource–based sectors. This section assesses how concentrated Russia’s exports and the markets they serve are; the degree to which the export portfolio is aligned with products and import markets that are growing in the world economy; and how the market reach of specific exports (successful or unsuccessful) has evolved over the past decade. 1.20. The main argument for diversifying exports is to lessen risks and vulnerabilities from relying on too much income from a narrow range of products. Such vulnerabilities can occur through volatility in international prices and external shocks beyond an exporter’s control. Recently, diversification and “discoveryâ€? of new exports have also been shown to contribute positive externalities 44 and facilitate higher productivity, leading to improved long-term growth prospects. Diversification is important for developing countries because it allows them to develop competence over a broader range of manufactured goods. Countries develop by learning to make new things, and through entrepreneurial dynamism and growth, not only relying on what they have traditionally done well. 1.21. In manufacturing, Easterly, Reshef, and Schwenkenberg (2009) show that for every country they assessed, exports are dominated by a few “big hits.â€? They find that success in exports and specialization is driven by a narrow range of specific exports to specific markets. While this appears to undercut the argument for export diversification, Imbs and Wacziarg (2003) find that economies tend to diversify over most of their development path. Only after reaching a higher threshold of income is further growth associated with specialization. Klinger and Lederman (2004) find a similar inverted-U relationship between income and export activity. Concentration Index 1.22. The Herfindahl-Hirschman Index measures the concentration of export share held by a particular product (destination) in a given country export profile. It varies from 0 (no concentration) to 1 (full concentration). This index confirms that Russia’s main issue is the concentration of its export basket around few products rather than around few market destinations. This pattern has been accentuated in the last decade as Russia has become a major exporter of oil and natural gas. Compared with the other BRICs, Russia has the highest concentration measure in products (figure 1.14) but the lowest concentration in markets (figure 1.15). Despite the importance of oil and gas in its export basket, Russia’s export partners are not heavily concentrated. The top five export partners accounted for roughly 25 percent of Russia’s exports in 2006–08, similar to 10 years before. The country’s nonoil exports also follow a similar pattern, with the top seven export destinations accounting for less than 50 percent of Russia’s exports. Figure 1.14 Herfindahl-Hirschman Index for Figure 1.15 Herfindahl-Hirschman Index for products, BRICs, 1998 and 2008 markets, BRICs, 1998 and 2008 Herfindahl Index - Products (HS6) 0.014 BRA 0.031 0.005 CHN 0.006 0.025 IND 0.028 0.051 RUS 0.187 0.026 ZAF 0.024 0 .05 .1 .15 .2 1998 2008 Source: Authors’ calculations Source: Authors’ calculations Growth Orientation of Export Products and Markets 1.23. How a country’s industry is faring in international competition can be gauged by its share in strategic markets, such as those growing (and importing) rapidly. Russia’s top export partners are not generally among those that have seen the highest rates of import growth between 2000 and 2008. Figure 1.16 shows a weak, positive correlation between Russia’s top exports and their rate of growth in 45 the world market. For Russia’s exports to be “pulledâ€? by the world growth of products that it exports, the relationship needs to be stronger (figure 1.17). In fact, Russia shows the lowest correlation between (log) product share and annual world import growth among the BRICs (table 1.5). When all exports of the extractive industries that draw on subsoil resources are dropped (Harmonized System classification 25–27 and 68–71), the general positive orientation still holds (not shown). Figure 1.16 Growth orientation of markets Figure 1.17 Growth orientations of products Compound annual import growth rate of products 2000-08 (% ) Compound annual import growth rate of markets 2000-08 (%) Russia: Growth Orientation of Markets Russia: Growth Orientation of Products 40 30 30 25 20 20 10 10 15 -10 0 5 -3 -2 -1 0 1 2 -4 -2 0 2 4 Log destination share in total exports 2008 Log product share in total exports (HS6) 2008 Source: UN Comrade Table 1.5 Correlations between market destinations (product) shares and world demand (slopes), BRICs Orientation Market Product Brazil –0.33 0.16 Russia –0.01 0.08 India –0.44 0.13 China –0.39 0.15 Source: UN Comrade Value and Reach of Exports 1.24. Over 2000–08, Russia expanded the number of export markets that at least one of its products (at the six-digit Harmonized System level) serves from around 80 to more than 100. The most prolific products are vodka and oil. The total value of its existing products (colored green in figures 1.18 and 1.19) in the newly expanded or existing markets has also increased. The black dots indicate products that were exported in 2000, but not in 2008, possibly indicating death or suspension. But the orange dots indicate products that were not exported in 2000 but were in 2008, which proxy for new discoveries. In general the products that disappeared did not constitute large export amounts, whereas only a few “newâ€? exports in 2008 reached around 25 markets. 46 Figure 1.18 Export destinations by product, Figure 1.19 Export destinations by product, 2000 2008 Number of Export Destinations by Product 2000 Number of Export Destinations by Product 2008 20 15 15 Value of Exports (HS6), in log Value of Exports (HS6), in log 10 10 5 5 0 0 -5 -5 0 20 40 60 80 0 20 40 60 80 100 Number of Markets Number of Markets Source: Authors’ calculations based on UN Comrade Intensive and Extensive Margins of Exports 1.25. Export growth can take place at the intensive margin (selling existing products to existing markets) or at the extensive margin (selling existing products to new markets, new products to new markets, and new products to existing markets).33 There are multiple definitions of the intensive and extensive margins. In this chapter, the concepts are invoked in the context of diversification as well as survival of exports. In the former, the attempt is to explore to what extent Russia has been able to add new products and new markets – that are economically significant – to its portfolio. When the two margins are discussed in the context of export survival, the attempt is to decompose export growth into constituents capturing growth of old products in old markets versus the rest. 1.26. How has Russia performed on the intensive margin (IM) and the extensive margin (EM) of exports between 1998 and 2008? Using the method of Hummels and Klenow (2005), its IM and EM are plotted jointly on an IM–EM space, with those of the other BRICs. Russia’s share of exports in all products that the rest of the world also exports (IM) rose slightly over the 10 years (figure 1.20). The IM as measured here indicates how big Russia is in what it exports, and the EM measures how globally important is what it exports. This can be characterized as a move from being a “big fish in a small pondâ€? to being a “small fish in a big pond.â€? Countries like India and China (though not Brazil) have managed to increase their share of export in goods that the rest of the world produces (IM) as well as the breadth of their export portfolio relative to all exportable products (EM). 1.27. Extending this to analyze destinations, however, Russian export share in countries it currently exports to IM has increased, but its reach to markets that cumulatively are larger relative to the world in 2008 than in 1998 (EM) has fallen (figure 1.21). By contrast, China and Brazil have both increased their existing share of exports to existing markets, and added new markets to their portfolio of destinations. 33 Growth along the intensive margin – of products already established as exports – is a source of export diversification if it is obtained through the increase of the share of nontraditional exports in total exports. 47 Figure 1.20 Intensive and extensive margin in Figure 1.21 Intensive and extensive margin in products, BRICs, 1998–2008 markets, BRICs, 1998–2008 Intensive and Extensive Margin in Products, 1998-08 Intensive and Extensive Mar gin in Markets, 1998-08 China China 10 10 Intensive Margin Intensive Margin China 5 China 5 Russia Russia Brazil Brazil Russia India Russia India India India Br azil Brazil 0 0 98 98.5 99 99.5 100 97 98 99 100 Extensive Margin Extensive Margin 1998 2008 1998 2008 1.28. Decomposing export growth into the margins of trade is also informative to see the source of export dynamism. For 2000–2008, existing flows to existing countries accounted for 88.4 percent of the growth (figure 1.22). This export growth was offset by exports that fell to existing markets (– 4.3 percent) and by the extinction of exports of existing products in existing markets (–3.2 percent). The only significant variation at the extensive margin is the increase of old products in new markets (19.0 percent). While export growth of more developed countries is expected to be concentrated in the intensive margin, this analysis hints at Russia’s deficiency to diversify its export base to new markets/products. Figure 1.22 Russia’s decomposition of export growth, 2000–08 Source: Authors’ calculations 48 Quality 1.29. What countries produce, and how they produce them, matters for export-led growth. All else equal, goods that embody greater value addition through ingenuity, skills, and technology fetch higher prices in world markets. Countries that produce goods more sophisticated than what their income would suggest tend to see higher rates of future economic growth. Upgrading product quality, therefore, can be a secure source of both export and economic growth. This section assesses the “incomeâ€? and “factorâ€? contents of exports to see if what Russia produces are sophisticated and high value, as well as the product space maps to analyze the evolution of RCA in Russia’s nonoil/nongas sectors. It briefly explores possibilities for upgrading in manufacturing. Sophistication of Exports 1.30. Hausmann, Hwang, and Rodrik (2006) show that the sophistication of products is important for economic growth. Countries with a more sophisticated export basket, proxied by a measure named EXPY (box 1.1), enjoy accelerated subsequent growth, while those with less sophisticated export baskets tend to lag behind – in essence, countries become what they export. Given the overreliance of Russia on its oil and gas exports, any comparison of the sophistication of their overall export basket would reflect mainly the sophistication of the hydrocarbon sector.34 Figure 1.23 shows the evolution of the sophistication of nonoil exports for Russia and the other BRICs. The sophistication of Russia’s export basket has almost constantly fallen over time, while China’s and India’s have risen. In 2002, Russia showed the highest EXPY, but was overtaken by China in 2008. Figure 1.23 Change in export sophistication, BRICs Source: UN Comrade 34 Oil and gas are lucrative export earners, but in relative sophistication measured by PRODY, they are of low sophistication compared with portfolios of countries with more diversified manufacturing products. This is because there are many low income exporters of oil and gas. 49 Box 1.1 Measuring export sophistication Hausmann, Hwang, and Rodrik (2006) proposes a measure of export sophistication, denoted by EXPY, which is computed in a two-stage process. The first stage is to measure the income associated with each product in the world, termed PRODY. The PRODY of a particular product is the GDP per capita of the typical country that exports that good. Typical GDP is calculated by weighting the GDP per capita of all countries exporting the good. The weight given to each country is based on revealed comparative advantage, defined as the share of its exports that comes from that good relative to the “averageâ€? country. The PRODY for a single product is calculated by weighting the GDP per capita of all countries exporting that product. Therefore, a product that typically makes up a large percentage of a poor country’s export basket will have stronger weights toward poor countries’ GDP per capita. This will be less the case for a product that makes up a small percentage of a poor country’s exports but is a significant component of many rich countries’ export baskets. The second stage is to measure the income associated with a country’s export basket as a whole; this is its EXPY. From the first stage, each product that a country exports will have a PRODY. The EXPY is calculated by weighting these PRODY by the share that each good contributes to total exports. If butter makes up 15 percent of a country’s exports, its PRODY will be given a weight of 0.15. Countries whose export baskets are made up of “rich-country goodsâ€? will have a higher EXPY, while export baskets made up of “poor-country goodsâ€? will have a lower EXPY. § x jk · ¨ ¨X ¸ ¸ § xik · © j ¹Y PRODYk ¦ x jk j and EXPYi ¦¨ X ¸PRODYk © i¹ j ¦X j k j Unit Values 1.31. When supply is competitive, higher prices are generally associated with higher quality and greater product differentiation. One way a country can increase the absolute amount of exports per capita is to augment the quality of exports and thus the value of exports per unit. One of Russia’s main challenges is the lack of product diversification and its low capacity to increase the quality of existing exporting products. Table 1.6 shows a list of the top 10 products exported in 2008 outside extractive industries (Harmonized System classification 25–27 and 68–71).35 Table 1.6 Top 10 non-extractive export products, 2008 Product Name 760110 Aluminium,notalloyed 310420 Potassiumchloride 720712 Semi Ͳfinishedproductsof ironornonͲ alloysteel:Other,ofrectangular(otherthansquare) crosssection 750210 Nickel,notalloyed 720449 Ferrouswasteandscrap;remeltingscrapingotsof ironorsteel:Other 720110 Nonalloypigironcontainingbyweight0.5%orlessof phosphorus 440320 Woodinthe rough,whetherornotstrippedof barkorsapwood,orroughlysquared.:Other,coniferous 720711 Semi Ͳfinishedproductsof ironornonͲ alloysteel.:Of rectangular(includingsquare) crosssection,the widthmeasuring 760120 Aluminiumalloys 440710 Woodsawnorchippedlengthwise:coniferos Note:Sortbyimportance in2008'sexportbasket.Some namesare truncatedtoreduceclutter Source: Contrade 35 We also take out uranium (284420) since its price multiplied by a factor of 10 between 2000 and 2008. This price-effect artificially increases unit values and obscures the analysis of the quality content. In 2000, Russia’s exports of uranium accounted for 1.3 percent of the total export basket. 50 1.32. Outside extractive sectors, Russia exports mainly metals, wood, and chemicals. Apart from wood, potassium, and some semifinished products of iron, these products are largely homogeneous where the scope for quality upgrading is limited. The lack of quality differentiation across markets is indicated by the low standard deviation of unit values. The average number of markets that these products serve did not change dramatically between 2000 and 2008 (table 1.7). Table 1.7 Markets served by top 10 non-extractive export products, 2000–08 2000 2008 UVCAGR(%) Unit Product %ofExp MeanUV* #markets UVSD* %of Exp MeanUV* #markets UV SD* 00Ͳ08 kg 760110 4.9% 1.6 46 0.2  1.4% 3.1  47 1.3  8.4  kg 310420 0.8% 0.2 43  0.3 1.2% 28.8 47 189.0 87.2 kg 720712 0.7% 0.2 23  0.1 1.2% 163.4 26 828.8 125.0 kg 750210 1.6% 8.7 42  2.3 0.9% 22.1 38 5.5  12.3 kg 720449 0.7% 0.1 30 0.2  0.8% 0.5  37 0.3  18.9 kg 720110 0.4% 0.2 35 0.0  0.7% 0.6  45 0.2  19.8 M3 440320 1.4% 98.6 37 80.3 0.7% 198.8 31 159.6 9.2  kg 720711 0.8% 0.3 39 0.4  0.5% 0.9  32 0.4  15.0 kg 760120 1.4% 1.4 39 0.2  0.5% 3.3  45 2.8  11.0 M3 440710 0.8% 148.7 63 65.0 0.5% 281.1 64 130.2 8.3  Totalexp 13.5% 8.5% *USDollars Source: Contrade Product-space Analysis 1.33. Exploring the network of relatedness between products, product-space analysis indicates what merchandise goods a country exports competitively, which goods are closer to the ones currently produced, and whether the country has undergone a structural transformation over time. An analysis of Russia’s export composition using the tools pioneered by Hidalgo and others (2007) reveals that the transformation of Russia’s export basket has been slow – that is, Russia has relied on the same products as the base of its comparative advantage over the last 15 years. 1.34. The product-space analysis of Russia’s export basket reveals three things (see annex 1B). First, Russia’s product space map shows 97 products in which the country has achieved RCA. Second, the products in which Russia has developed RCA are mostly in the periphery of the product space map and have few connections to other sectors, which imply that gaining comparative advantage in other sectors is more difficult since the capabilities needed to produce its export basket are not easily redeployed to other sectors.36 Third, the products in which Russia has developed RCA are mainly resource-based: raw materials (26 products), forestry (11 products), cereals (9 products), and oil and gas (3 products), though the country also developed comparative advantage in nonresource-based industries like capital-intensive goods (13 products) and chemicals (14 products).37 1.35. Further, the direction of Russia’s export basket transformation has been very simple. New products in which Russia has developed RCA are in the same or very similar sectors as its “classicâ€? 36 The center of the product space, for example, is quite dense with better connectedness among industries related to metallurgy, vehicles, machinery, and the like. To the bottom right of the product space lie the more sophisticated electronics and chemical industries. The scattered industries on the upper half are largely agricultural and resource-based. 37 The RCA presented here is computed from a different classification from the one presented in the composition of export by sectors. The former is calculated at the four-digit Standard International Trade Classification level whereas the latter is computed at the two-digit Harmonized System classification. The more granular level of disaggregation of the Standard International Trade Classification allows picking some products that were not identified as having a competitive edge before. 51 exports – mainly resource-based commodities like raw materials, forestry, cereals, and oil and gas – which indicates that over the last 15 years Russia has been mainly stuck in the same export sectors. Unlike the other BRICs, Russia has developed RCA in very few products at the core of the product space (figure 1.24). All the other BRICs have had some success in penetrating the core of the product space (especially China), which means that future structural transformation will be easier. Also, when the other BRICs develop RCA in products in the periphery, these products are sometimes outside the countries’ traditional export sectors – something that does not happen in Russia. 1.36. The conclusion is clear: the relatively few products in which Russia has gained RCA is a result of a slow pace of structural transformation in the country over the last 15 years. Further, the direction of this change has also been less favorable than in the other BRICs. The products in which Russia has developed RCA are generally outside the core of the product space – a remarkable finding that does not hold for any other BRIC country. Figure 1.24 Comparative advantage and the product space, BRICs, 2006–08 China India Brazil Russia Source: Authors’ calculations 52 1.37. The Transition Report 2008 of the European Bank for Reconstruction and Development reached similar conclusions and highlights the fact that countries like Russia with unsophisticated and highly unconnected export baskets have few opportunities to move to new products or upgrade quality in existing sectors. 38 The report shows evidence that Central European and South Eastern European countries have upgraded their export structure and sophistication by virtue of increasing trade relations with the EU-15. By contrast, the Commonwealth of Independent States as a whole, and Russia in particular, has become increasingly reliant on the export of petroleum and raw materials, with virtually no increase in the sophistication of the export basket and no significant emergence of new export industries. Survival Probability of Export Death 1.38. Russia’s exports at the four-digit Standard International Trade Classification level to all (reporting) countries from 1999 to 2009 are analyzed for their survival rates.39 During the 11-year period, each product is exported to a particular country mostly in spurts. There are 40,506 country- product pairs with at least one year of exports valued at least at US$1,000. For many of these pairs, trade takes place just once, or a single spurt of consecutive years. Some die and are then revived. The total number of spells is, therefore, 62,978. 1.39. About 7,127 of the 62,978 spells last the full 11 years, but the median duration of spell is only two years. Figure 1.25 (Kaplan-Meier survival function) shows that the probability of a Russian export relationship surviving until the second year is about 0.57, and maintaining a relationship for five years is 0.22. The survival rate of China’s export relationships is much higher. Brazil and India performed better than Russia but, as expected, lag behind China. Figure 1.25 Export relationships, p p 1999–2008 BRICs, Survival Rate 1999-2008 1 .8 probability .4 .2 0 .6 0 5 10 Analysis Time Russia Brazil China India Source: Authors’ calculations Exports Relative to Comparative Advantage 1.40. To explain why a country’s exports cannot be sustained, one of several areas to investigate is whether the exports that die represent attempts to produce goods that require a different mix of 38 EBRD 2008. 39 A detailed measurement of entry and survival in exports requires access to time-series data about individual firms. Unfortunately, accessing this kind of data is often difficult. We focus here on survival of export relationships, a limited proxy for survival of firms. 53 factor endowments than supported by the economy. If a nation’s endowment point is represented by the intersection of its average stock of physical and human capital, we can see how far or close to the endowment point are factor intensities of exports. 1.41. With few exceptions, the most significant exports of Russia in 1993 were in line with the average factor endowment in upper middle-income countries, with some embodying capital greater than the average (figure 1.26). By 2003, the endowment of both physical and human capital had increased slightly, and Russia produced many exports with higher factor requirements (figure 1.27). The major exports, however, remained close to the endowment point, with one major output below. Most exports that existed in 1993, but not a decade later, were those requiring a higher level of physical and human capital (figure 1.28). At the same time, most “newâ€? exports that were active in 2003, but not a decade earlier, are also moderately capital intensive (figure 1.29). It can be hypothesized that, all else equal, ambitious ventures that defy a country’s comparative advantage have a higher rate of failure. However, success of exports depends on an array of factors, including accumulated national capabilities, search and information costs related to the business of exporting, and exchange rate volatility.40 Figure 1.26 Exports relative to endowment, 1993 Figure 1.27 Exports relative to endowment, 2003 Russia: Exports Relative to Endowment 1993 Russia: Exports Relative to Endowment 2003 15 15 Revealed Human Capital Index Revealed Human Capital Index 10 10 5 5 0 0 0 50000 100000 150000 0 50000 100000 150000 200000 Revealed Physical Capital Index Revealed Physical Capital Index Figure 1.28 Death of exports, 2003 Figure 1.29 New exports, 2003 Russia: Death of Exports 2003 Russia: New Exports 2003 12 12 10 Revealed Human Capital Index Revealed Human Capital Index 10 8 8 6 6 4 4 2 2 0 50000 100000 150000 200000 0 50000 100000 150000 Revealed Physical Capital Index Revealed Physical Capital Index Source: Authors’ calculations 40 Easterly, Reshef, and Schwenkenberg (2009) discuss the role of fortuity in a random product being a “hitâ€? in a certain destination leading to substantial growth, imitation, and concentration of a few successful export items at a given time. 54 Summary of key findings – trade performance assessment Intensive margin Extensive margin Orientation and Diversification Quality Survival growth “Increasing export value of “Maintaining export “Increasing unit existing products across relationships, and “Increasing export value from new Policy objective values of existing markets, and to specific minimizing loss of markets and new productsâ€? export flowsâ€? markets across productsâ€? export valueâ€? Extremely high Low rates of new firm Increasing dependence on oil/gas concentration of entry and Low survival of exports. No progress on diversification Major hydrocarbon exports. experimentation with export relationships. into services. Limited diversification new products. High % of fall in challenges in Despite the importance of oil and gas on even across High physical/ human export value among trade its export basket, Russia’s export nonhydrocarbon exports; capital endowments old products in old competitiveness partners are not heavily concentrated. lack of sustained product not reflected in the markets Limited, undiversified presence in high- competitiveness (RCA) capital content of growth products and export destinations exports Policy Options for Export Diversification in Russia 1.42. Export diversification – products and markets – is strongly associated with economic growth.41 This positive link between diversity and long-run growth accrues from reduced volatility in output that would otherwise result from the impact of external shocks on a concentrated export basket, as well as from the increased potential for generating spillovers. 42 Although much of the focus on diversification, especially in low-income countries, is on concerns over a “natural resources curse,â€? there is increasing evidence that it is not natural resources in themselves that are the problem but rather concentration of exports.43 1.43. Recent interest in export diversification has been accompanied by several attempts to explain its determinants. The bulk of empirical evidence is concentrated on the income determinants, and several papers study the impact of income on export diversification by putting a measure of diversification on the left-hand side of the equation and income on the right-hand side. Klinger and Lederman (2004) found a U-shaped relationship between export concentration and GDP per capita by regressing the former on the latter, providing evidence of a nonlinear effect of income on export diversification. 1.44. Carrère, Strauss-Khan, and Cadot (forthcoming) propose a quantitative assessment of the main determinants of export diversification. Specifically, they regress the overall Theil index, the within-groups Theil, the between-groups Theil, and the number of exported products on 10 variables using a panel dataset of 87 countries for 1990–2004. Country and year fixed effects control for unobservable characteristics in all regressions (table 1.8). 41 Hesse 2009; Lederman and Maloney 2009. 42 Haddad, Lim, and Saborowski 2010. 43 Lederman and Maloney 2007. 55 Table 1.8 Diversification drivers in a panel dataset, 87 countries, 1990–2004, Note: Robust standard errors in italics, with * meaning that the correspondent coefficient is significantly different from zero at 10%; ** significant at 5%; *** significant at 1%. Source: Carrère, Strauss-Khan, and Cadot forthcoming. 1.45. Results confirm the U-shaped tendency of income on export diversification. The results also show that, once per capita GDP is controlled for, infrastructure appears as an important driver of diversification: a 10 percent rise in the infrastructure index reduces the Theil index by about 0.7 percent. Remoteness also has the expected sign: the more remote the country, the lower its export diversification—that is, the higher the Theil—essentially in terms of the extensive margin and number of products. The analysis thus confirms that high distance to importers increases the export fixed cost and thus drastically reduces export diversification. Preferential market access is clearly an important factor of diversification at both margins. By contrast, net inflows of foreign direct investment (FDI; as a share of GDP) seem to concentrate export value in some products, thus increasing concentration at the intensive margin. This result may be expected as multinational companies specialize in specific products that they produce in high volumes. The analysis also finds a significant impact of education on export diversification. A 10 percent increase in the years of schooling reduces the Theil index by 1.1 percent and increases the number of exported products by 6.2 percent. Similarly, institutional quality appears clearly significant with a positive impact on diversification. Finally, as expected, the larger the population, the more diversified the economy. 1.46. As noted by Carrère, Strauss-Khan, and Cadot, these results should be treated with caution. The regressions are informative of the factors with a significant impact on diversification and of the sign of this impact, once other factors are controlled for. It is difficult, however, to rank these factors and clearly isolate single impacts because of potential multicolinearity issues between these variables. 1.47. Overall, Carrère, Strauss-Khan, and Cadot suggest that poor countries have, on average, undiversified exports. As they grow, they diversify, and then reconcentrate at high incomes. The extensive margin (new products) dominates the action in terms of diversification, but the intensive margin (higher volumes) dominates the action in terms of export growth. Thus, if governments are ultimately interested in exports (and employment) growth, the intensive margin appears to be a better bet. The 56 reason is that there is enormous churning, so that many of today’s new products are tomorrow’s failed products. The Role of Industrial Policy and Information Asymmetries 1.48. Traditional export diversification strategies have often been based on government interventions that increase economic returns of investments on specific industries. These industrial policies aim to shift economic resources toward industries producing sophisticated, high-tech products. The rationale is to provide temporary conditions for firms to learn by doing and eventually to reach international levels of competitiveness. The goal is to achieve faster growth by rapid productivity increases or expansion of global demand for those products (or both). 1.49. The contribution of industrial policies to the successful examples of export diversification is, however, difficult to assess. Evidence supporting the popular view that industrial policies have driven export diversification in East Asian countries becomes controversial when other factors affecting export diversification are taken into account.44 The Republic of Korea and Taiwan, China, for instance, had large rates of physical and human capital accumulation that shifted their comparative advantage toward capital- intensive goods during 1960–80, making it hard to isolate the effect of industrial policies at that time. The adoption of measures to neutralize the antiexport bias of industrial policies, in addition, induced an export-orientation that enabled firms to achieve efficient sizes and adopt modern technologies, mitigating the risks inherent in protectionist measures. In the late 1980s, for example, Korean business expenditures on research and development (R&D) reached 80 percent of total R&D expenditure. In that period, students with internationally acquired, government-funded PhDs were required to return to Korea and encouraged to work in emerging enterprises. 1.50. Some of the recent theories on exports and competitiveness suggest that productivity (competitiveness) gains are achieved primarily through interindustry spillovers, and that these are more likely to be achieved in certain product groups than in others – in the product-space language, in denser parts of the forest where there are greater opportunities for cross-product linkages.45 Interindustry spillovers are also identified empirically by Shakurova (2010) who estimates how the probability of exporting a good depends on previous experience in exporting either similar goods (“horizontalâ€? spillovers) or upstream ones (“verticalâ€? spillovers). Cross-country regressions at the industry level show that the size of those spillovers varies across industries but is in most cases statistically significant. But others caution that there is no firm link between diversification and productivity and that if it is easy to move from one industry to another, the rents achievable in these industries occupying the dense part of the forest should be eroded.46 1.51. In addition, governments put in place measures to help productive firms overcome market and policy failures specific to the export cycle – often related to uncertainties in undertaking new activities in foreign markets (especially with regard to costs) and sunk-entry costs – and exploit export opportunities. These export promotion policies encompass a variety of “softâ€? measures, as for instance commercial diplomacy or intelligence about foreign markets. 44 Noland and Pack 2004. 45 Hidalgo and others 2007. 46 Harrison and Rodríguez-Clare 2009. 57 1.52. Empirical evidence on the impact of export promotion has an uneven record. After reviewing the mixed evidence so far, Lederman, Payton, and Olarreaga (2006, 2009) find, on the basis of cross-country evidence, extremely high rates of return on public money invested in export promotion agencies. Some conditions, however, must be fulfilled, including private sector involvement in agency management. They also find strongly diminishing returns – that is, a little bit of money does a lot of good, but a lot of money does not. 1.53. Other aspects emphasized in the literature are strong leadership, skilled staff, and international presence.47 This last point has been further explored by Bergeik (2010), who believes that having embassies and consulates in recipient countries is more important than having export promotion agencies. 1.54. Finally, a recent impact evaluation of Tunisia’s export-promotion agency sheds some light on whether the agency promotes growth at the intensive or extensive margin.48 Compared with a control group of firms that did not benefit from export promotion, beneficiary firms expanded at the extensive margin in terms of products and markets. However, their export sales grew faster than those of control-group firms only the year of the treatment. After one year, they were back on a parallel trajectory. Thus export promotion seems to foster diversification, but might in the end lead firms to spread themselves too thin. Evidence for Russia 1.55. What can we say about determinants of export diversification in Russia? Without firm-level customs data, we summarize the empirical evidence on the investment climate determinants of firms’ internationalization in Russia.49 The key objective is to analyze the role of total factor productivity (TFP), degree of international integration (through exports and FDI inflows), innovation, competition, and other investment climate variables on firms’ economic behavior, in particular, firms’ propensity to export in Russia. To provide some benchmarking for the results obtained, we compare the results obtained with results for 19 other developing countries. To do this, we combine an analysis carried out by Pena (2010) with an analysis done for 19 countries using the same methodology.50 1.56. The analysis for Russia is conducted at the firm level using the 2009 World Bank Enterprise Survey in a simultaneous equation model to identify the determinants of the export propensity of Russian firms. The model selects about 15 statistically significant variables of a total of more than 250, 47 Hogan 1991. 48 Gourdon and others 2011. 49 The Research Department of the World Bank is assembling a customs transaction database, covering many countries and many years. The database includes measures of export growth and dynamics at the country, industry, and market levels, which will be made available to policymakers and the public in general. This database will help monitor the evolution of exports and will improve the understanding of exporters’ behavior. There is still no information available for Russia. 50 Escribano, Peña, and Reis 2010. The countries are Turkey, Egypt, Colombia, Mexico, Pakistan, Guatemala, Honduras, Nicaragua, Costa Rica, Peru, Chile, India, Kenya, Uganda, Senegal, Brazil, Malaysia, Morocco, and South Africa. Unfortunately, endogeneity is still an unsettled issue in this kind of analysis. Implementation of those techniques that allow obtaining causal interpretations, like those derived from the concept of contemporaneous Granger causality or experimental or quasi-experimental methods, are unfeasible to implement in the context of surveys with cross-sectional datasets or with incomplete panels with a very short time dimension. Although the two papers propose solutions to reduce the degree of endogeneity and eliminate spurious correlations of variables, they do not allow us to always give causal interpretations for the results obtained. Rather, the results should be interpreted as empirical regularities relating alternative measures of firms’ expected economic performance with investment climate variables. 58 aiming at maximizing its explanatory power. 51 To mitigate estimation issues, Pena (2010) uses the investment climate variables to control for the usually unobservable firm-level fixed effects. He also uses an instrumental variable estimator for TFP to alleviate the endogeneity coming from the simultaneity bias. After obtaining a consistent estimation of the parameters of the system of equations (relations among the variables), he evaluates the relative importance of each variable on the sample means of the dependent variable. 1.57. It turns out that TFP is the key variable explaining why firms can compete in export markets, receive FDI, and engage in R&D in Russia (figure 1.30). Exports and FDI (measured here together as international integration) have a positive effect on TFP, employment, and R&D, but the size compared with other variables of the effect is very low. Innovation, evaluated by looking at R&D investment, the introduction of new products, and the upgrade of existing products, exerts a positive and fairly strong influence on TFP, exports, and R&D. But TFP is influenced by a number of investment climate variables, including labor and management skills, innovation and quality, competition, international integration, red tape, and finance. Figure 1.30 Relative importance of TFP, international connectivity (exports and FDI), innovation, competition, and the investment climate in explaining firms’ behavior in Russia (%) 100% 4.0 Othercontrolvariables 8.8 4.4 12.2 17.5 9.0 3.8 2.5 Laborskills 6.6 2.2 80% 36.2 10.2 2.9 Qualityandotherinnovation 3.8 18.7 6.3 variables 32.0 Financeandcorporategovernance 60% 9.9 29.1 7.8 0.8 0.6 16.6 Redtape,informalityandothers 6.3 20.9 8.0 Infrastructure 40% 15.3 4.0 2.2 0.3 Competition 14.0 56.6 10.0 20% 42.1 1.1 1.5 Innovation 4.5 33.4 10.3 21.6 Internationalintegration 5.0 0% TFP Aggregate AveragelogͲ Propensityof Propensityof Propensityof logTFP employment firmsexporting firmsreceiving firmsengagedin Realwages FDI R&D Source: UN Comtrade 1.58. In the specific case of the propensity to export, Pena’s (2010) analysis corroborates the relevance of firms’ productivity in Russia, estimating that a 1 percent increase in TFP is associated with an increase in the probability of exporting of about 11 percent. Evaluation of the importance of TFP, relative to other variables, in explaining propensity of firms of exporting shows that TFP explains up to 42.1 percent of why firms export in Russia (relative to other variables). Firms investing in R&D and upgrading existing products are also more likely to export. 1.59. The relative impact of competition from domestic, foreign, and informal firms, as well as competition from customers, is also relevant. This can be gauged by the positive influence of the number of competitors and the negative influence of the dummy for increased prices, another measure of competition. There are indirect effects as well, as those firms facing intense competitive pressure from 51 Peña 2010. 59 domestic firms are 18.8 percent more productive on average.52 A larger degree of domestic competition and smaller degree of informal competition could lead to important TFP gains and in the number of firms exporting and innovating. 1.60. While significant in their own right, it is important to give a cross-country perspective, to understand to what extent these results are specific to Russia. Escribano, Pena, and Reis (2010) applied the same methodology to 19 countries. Although the countries were selected for data availability reasons, heterogeneity is observed in them at different dimensions (country, region, and so on). The heterogeneity stems from two main factors: geographic, as we have countries with different extensions from different regions (Latin America, Africa, and Asia), and economic, the sample includes low- and middle-income countries. 1.61. Figure 1.31 shows the percentage absolute contributions of TFP to the probability of exporting (exporting propensity) in the 19 countries. 53 Regardless of the country in focus, TFP is always significant and relatively the most important positive covariate for international engagement. With Turkey and South Africa, Russia stands out as a country where this association is particularly strong. Figure 1.31 Percentage absolute contributions of TFP to the probability of exporting, by country 50.0 42.9 45.0 40.7 42.1 40.0 35.0 30.3 30.0 24.1 24.2 24.4 25.1 25.0 20.7 21.7 22.0 18.2 19.6 19.6 20.0 15.7 15.7 14.0 15.0 9.0 9.1 10.6 10.0 5.0 0.0 Kenya Morocco Turkey Peru Egypt Brazil Mexico SouthAfrica Russia Phillippines Chile Senegal India Colombia Uganda CostaRica Guatemala Malaysia Tanzania Pakistan Source: Authors’ calculations based on Pena (2010) and Escribano, Pena, and Reis (2010). 1.62. The same pattern is observed when the results for quality and innovation are considered. The first observation is that the contributions of this group are lower than those of the blocks analyzed so far. For exports, only in Chile and Russia is the contribution of this group outstanding, at 30.6 percent and 32.9 percent (figure 1.32). Turkey and Egypt also show relatively large contributions, at 22.2 percent and 16.2 percent. In the other countries, the contributions are below 10 percent.54 But the important point is that, again, in Russia the correlation between innovation variables and propensity to export is particularly strong. 52 Peña 2010. 53 Escribano, Peña, and Reis 2010. 54 Escribano, Peña, and Reis 2010. 60 Figure 1.32 Percentage absolute contributions of quality and innovation to the probability of exporting 35.0 32.9 30.6 30.0 25.0 22.2 20.0 16.2 15.0 9.5 9.7 10.0 8.2 6.5 7.0 7.0 7.0 5.3 3.2 4.0 5.0 2.1 2.4 2.7 3.0 0.7 1.4 0.0 Peru SouthAfrica Mexico Phillippines Senegal India Kenya Morocco Colombia CostaRica Turkey Uganda Malaysia Tanzania Egypt Russia Brazil Pakistan Chile Guatemala Source: Authors’ calculations based on Pena (2010) and Escribano, Pena, and Reis (2010). 1.63. In sum, results show that productivity- and innovation-related variables contribute to more than 70 percent of the total effect of investment climate variables on firms’ export propensity in Russia. A comparison with other 19 countries using the same econometric approach shows that TFP and innovation have a stronger association with the propensity to export in Russia than in most of the other countries (Turkey being the exception for TFP, Chile for innovation). 1.64. Taking into account the difficulty to imply causality from a cross-section exercise, what these results seem to suggest is that, from a policy point of view, addressing the main determinants of firm productivity is an essential step to help promote export diversification in Russia. Productivity’s determinants are many, but it seems clear that the government needs to make the country a better place for doing business, as well as a better place for locating some parts of global value chains. Russian rankings in the World Bank Doing Business Indicators and Enterprise Surveys are below the averages of peer countries in almost all respects and they have not shown major improvements in recent years. While other middle-income economies with large domestic markets show similar rankings – Brazil and India perform marginally worse than Russia – the fact is that Russia lags behind competitors China, Japan, Mexico, and Singapore, not to mention the more developed European countries.55 Russia also falls behind its major competitors in trade costs and trade logistics, ranked only 94 of 150 countries evaluated by the international Logistics Performance Index. The performance in customs is especially negative, where Russia obtains its lowest score in the ranking, behind China and Brazil. 1.65. Access to imported inputs is a key element of the business environment and can play a key role in successful export diversification,56 a point explored in the next section. 55 According to the Doing Business Indicators, in 2010 the Russian Federation ranked 123 of 183 economies for the ease of doing business. 56 Amiti and Khandelwal 2009. 61 Trade Policies 1.66. Although preferential trade liberalization has received considerable attention in the empirical literature as a driver of product diversification,57 unilateral trade reforms have not. Yet the link between import diversification and TFP is strongly established at the firm level. Thus import liberalization can be taken as a positive shock on TFP which should, according to the Melitz (2003), raise the number of industries with an upper tail of firms capable of exporting – and thus overall export diversification. Indeed, arguments running roughly along this line can be found in Bernard, Jensen, and Schott (2006) and Broda, Greenfield, and Weinstein (2006), for example. As shown in the previous section, this topic is particularly important in Russia – TFP is strongly correlated with the propensity to export in the Russian case, the association stronger in Russia than in the vast majority of countries where the same econometric model was applied. 1.67. Efforts to liberalize trade have been one of the highlights of Russia’s economic reform since 1992. Following the breakup of the Soviet Union, authorities adopted the view that growth would be spurred on with greater integration with the world marketplace. The result is that tariffs have been greatly lowered, quotas reduced, and import subsidies diminished. The country also began the process of negotiating accession to the World Trade Organization (WTO) hoping to join the organization before the end of the decade. However, a lack of commitment during the early years and the financial crisis in 1998 led the entire process to run out of steam. Active negotiations and discussions started again only after President Putin declared WTO accession, one of the goals of his presidency. Russia has now completed bilateral market access negotiations with interested WTO members, including the United States, and is having multilateral discussions with WTO members. Having finalized accession to the rule-based trading system is critical for locking in hard-won economic reforms and engendering new ones. 1.68. The global economic crisis has had an impact on the pace of trade liberalization. Although Russia did reduce tariffs in 2007 and 2008, the prevailing trend in 2009 was to increase tariff rates in medium-tech products in response to the crisis. Russia’s government raised tariffs on processed foods, light manufacturing, the automotive sector, and some construction equipment and indicated that it would continue to review its tariff policy in light of overall economic conditions. While initially announced as temporary measures for nine months, many of these have been renewed and many of them incorporated in the common external tariff of the Russia–Belarus–Kazakhstan customs union. 58 Yet despite these increments, the overall dispersion of the applied rates indicated by its overall standard deviation and the coefficient of variation has remained unchanged since 2007 (table 1.9).59 57 See, for example, Amurgo-Pachego (2008), Feenstra and Kee (2007), and Dutt, Mihov, and Van Zandt (2009). 58 On November 27, 2009, the presidents of Russia, Belarus, and Kazakhstan signed the agreements creating the custom union, including a harmonized table of tariffs and tariff-rate quotas, as well as a harmonized customs code. The common external trade tariff was implemented from January 1, 2010, with the majority of the tariff rates established at Russia’s current applied rates. 59 Customs duties for high-tech equipment fell between 2008 and 2009. 62 Table 1.9 Structure of the effectively applied tariff, Russia Russia:Structure ofthe EffectivelyAppliedtariff 1996 2001 2005 2007 2008 2009 NumberofTariffsLines(6Ͳ digitsHarmonizedsystem) 4,731 4,324 4,321 4,536 4,529 4,524 Simple average appliedrate 9.9 9.4 8.8 6.3 6.2 6.3 HighTechProducts 8.5 9.4 8.6 5.8 5.8 5.7 MediumTechProducts 11.5 9.3 8.3 6.3 6.0 6.3 LowTechProducts 11.9 11.2 11.2 7.6 7.8 7.7 PrimaryandResource Ͳ basedProducts 8.1 8.6 8.9 5.9 5.7 5.7 a Domestictariff "peaks"(%of all tariff lines) 0.4 0.0 0.0 0.0 0.0 0.0 International tariff "peaks"(%of all tariff lines) b 23.4 9.3 8.1 7.0 7.1 7.3 Overall standarddeviationof tariff rates 7.5 5.3 5.2 5.7 5.7 5.7 Coefficientof variationof tariff rates 0.8 0.5 0.6 0.8 0.8 0.8 Dutyfree tariff lines(%of all tariff lines) 12.4 0.7 1.1 16.9 17.9 18.5 Nuisance appliedrates(%of all tariff lines) c 0.0 0.0 0.0 0.0 0.0 0.0 a.Domestictariff peaksare definedasthose exceedingthree timesthe overall simple average appliedrate. b.International tariff peaksare definedasthose exceeding15%. c.Nuisance ratesare those greaterthanzero,butlessthanorequal to2%. Note:Simple meanappliedtariff isthe unweightedaverage of effectivelyappliedratesforall productssubjecttotariffs calculatedforall tradedgoods.Dataare classifiedusingthe HarmonizedSystemof trade atthe six Ͳ digitlevel.Tariff line  datawere matchedtoStandardInternational Trade Classification(SITC) revision2codestodefine commoditygroups. Effectivelyappliedtariff ratesatthe six Ͳdigitproductlevel are averagedforproductsineachcommoditygroup. Source:WITSͲ TRAINS 1.69. Unlike the other BRICs, Russia uses a limited number of tariff policy measures to restrain import competition. Russia’s tariff structure is comparable with Brazil’s, while China and India have much higher levels of traditional protection (figure 1.33). Both Brazil and Russia levy lower import duties for its agricultural sector (primary and resource-based products) than for the nonagricultural sector (table 1.10). Figure 1.33 Tariffs in the BRICs High Tech Low Tech 0 20 40 60 80 100 Percentage Brazil China India Russia Brazil China India Russia Medium Tech Primary and Resource-based Products 0 20 40 60 80100 Brazil China India Russia Brazil China India Russia Source: TRAINS-WITS 63 Table 1.10 Effectively applied tariff (simple means) EffectivelyAppliedTariffRate (simplemeans) Primaryandresource Ͳ LowTech MediumTech HighTech basedProducts Products Products Products 1996 2001 2005 2009 1996 2001 2005 2009 1996 2001 2005 2009 1996 2001 2005 2009 Brazil 8.3 10.4 6.8 6.6 16.6 18.7 15.0 18.1 16.1 13.2 12.3 12.5 12.5 11.9 9.6 8.8 China 24.0 18.2 9.5 9.3 30.8 18.3 11.8 10.4 20.4 15.0 9.0 7.5 17.9 13.3 6.8 5.8 India 27.9 33.8 24.7 17.4 34.4 32.3 14.9 9.3 27.7 30.9 15.8 9.4 26.1 27.2 15.2 11.2 Russia 8.1 8.6 8.9 5.7 11.9 11.2 11.2 7.7 11.5 9.3 8.3 6.3 8.5 9.4 8.6 5.7 Average 17.1 17.8 12.5 9.8 23.4 20.1 13.2 11.4 18.9 17.1 11.4 8.9 16.3 15.5 10.1 7.9 Source:WITSͲ TRAINS 1.70. Comparing simple tariff averages across groups can be misleading if there is significant variation of the underlying rates at the tariff lines. A convenient way of graphically depicting groups of numerical data is the box-and-whisker diagram.60 Constructing this measure for applied tariffs across different types of products and across the BRICs, we confirm that Russia has one of the lowest average tariffs and that the dispersion of its rates is relatively low.61 Primary and resource-based products in Brazil and Russia have, on average, a low tariff rate and low dispersion compared with China and India. This picture also reveals India’s high level of protection in the agricultural sector. 1.71. Russia also uses country-specific tariff-rate quotas to protect its agricultural sector from excessive import competition. Including nontariff measures, the level of protection for the agricultural sector is higher than for the nonagricultural sector. On the Overall Trade Restrictiveness Index, Russia exhibits the second-highest level of total protection, only after Brazil (figure 1.34).62 The tariff equivalent of its trade policy is higher than the corresponding average in the other BRICs and in the Europe and Central Asia (ECA) region. Figure 1.34 Overall Trade Restrictiveness Index among ( the BRICs ) 50 ALL 40 Agricultural NonͲAgricultural Percentage 30 20 10 Ͳ Brazil Russian India ECA China Federation Average Source:WorldTrade Indicators(2010) 1.72. Russia’s current system of import and activity licenses to engage in wholesaling and manufacturing also undermines import competition and restrains innovation upgrading. Import licenses are necessary for importing certain products, including alcoholic beverages, pharmaceuticals, products with encryption technology, explosive substances, nuclear substances, hazardous wastes, and 60 The box-and-whisker diagram characterizes the distribution of the data through their five-number summaries: the smallest observation, lower quartile, median, upper quartile, and the largest observation. The length of the box indicates the degree of dispersion. 61 This picture remains unchanged if we look at years before 2009. 62 This index (applied tariffs including preferences) calculates the uniform equivalent tariff of a country's tariff schedule and nontariff measures that would maintain domestic import levels, including preferential tariffs. 64 some food products (such as unprocessed products of animal origin). Licensing requirements are applied to the processing, transportation, storage, and sale of oil and gas. 1.73. All importers of alcohol products must have an activity license to produce or distribute and store such products, placing a burden on importers that should be applied to distributors. Importers must also obtain an import license for each type of alcoholic product under a burdensome and time- consuming process. 1.74. Any product containing encryption technology must be tested and approved by Russia’s Federal Security Services before it can be imported, which can take six months or longer. This system impedes imports, delays the creation of an innovative and knowledge-based economy, and hampers the ability of Russian firms to acquire foreign technology that increases their ability to innovate and compete in the world market. 1.75. Russia also levies export duties on some raw products to stimulate the development of downstream processing products and to encourage their export. For example, a variety of agricultural products are subject to export tariffs, such as certain fish products, oilseeds, fertilizers, and wood products. In preparation for WTO accession, Russia indicated that it will gradually eliminate most of these duties, except for products deemed strategic, such as hydrocarbons and scrap metals. 1.76. In sum, licensing policies and tariff-rate quotas are the two most binding nontariff measures that limit the ability of Russian firms to benefit from competition, creating obstacles to the innovation process. Import licensing requirements hamper the ability of Russian firms to import high-tech products that could help them innovate. But tariff-rate quotas distort competition and could preclude imports when the quota is met. 1.77. Finally, it is important to emphasize the benefits that a low and uniform tariff structure entails for an economy seeking to enhance export diversification through innovation. The most recent evidence on the gains from a low tariff schedule is provided by Amiti and Khandelwal (2009), who show that lower tariffs are associated with quality upgrading for products close to the world quality frontier, but discourage it for products distant from the frontier. Tarr (1999) provides a compelling case for Russia to favor tariff uniformity (rather than differentiated tariff protection) based on political economy considerations, administrative convenience, and reduction of smuggling and corruption in customs. Firms’ Participation in International Trade 1.78. The heterogeneous firm literature in international trade has established that export participation is largely determined by variable export costs, such as transport costs and tariffs, and by fixed export costs, such as market entry costs. This combination affects firm profitability and, given that firms differ in productivity, also affects their ability to engage in exports. Thus the firms that can overcome the trade costs to export are usually the biggest and most productive firms in a country. There is, then, a direct relationship between the level of trade costs and the minimum productivity threshold required to export. By looking at some imperfect measures of the minimum productivity thresholds to export, this section sheds light on how Russia compares with some comparator countries, and on which trade costs seem most binding to impede export participation. 65 1.79. Russian firms are, on average, bigger than those in the ECA region (figure 1.35). Despite having a large number of employees, often concentrated in hydrocarbons, too few firms export. This low participation ratio is seen across industries and remains an issue when one compares Russia with developed economies such as France and the United States (table 1.11). Figure 1.35 Average full-time permanent employees by country, various years Table 1.11 Producers’ export participation (% of firms that export) ProducersExportParticipation Percentage ofestablishmentsthatexport Industry Russia(09) Chile (06) S.Africa(07) Turkey(08) Brazil (09) France (86) USA(87) Textilesandapparel 3.3  12.4 12.3 48.4 12.5 25.2 11.6 Food 8.0  18.8  8.8 27.8 13.0 5.5  13.1 Metalsandmachinery 19.7 21.2 27.6 41.9 22.3 32.1 19.0 Electronics Ͳ 31.8 70.0 18.8 Ͳ 30.2 34.6 Chemicalsandpharmaceuticals 20.8 20.3 22.9 34.8 23.4 55.4 30.3 NonͲmetallicandplasticmaterials Ͳ 25.0 23.3 38.8 35.3 16.4 Othermanufacturing 12.2 16.7 8.7  36.8 12.7 20.6 20.6 Manufacturing 13.3 17.1 16.5 40.0 16.1 17.4 14.6 Source:PRMTRcomputationusingenterprisesurveys,standardizeddata2006Ͳ 2010. Note:FranceandUSAdataare derivedfromEatonet.al.(2004). 1.80. We use the 2006–10 standardized version of the Enterprise Survey data to compare some characteristics of Russian firms with Brazil, Chile, South Africa, and Turkey. These countries were chosen both to identify relevant peer countries in their economic characteristics and because of the availability of firm-level data in the standardized version of the Enterprise Survey. Although Russia’s natural comparators are the other BRICs, the lack of comparable data makes that exercise unfeasible. 1.81. A simple way to infer differences on exporting costs across countries is to look at some measure of the minimum productivity level required to export in each country. If the productivity threshold to export is higher in Russia than in the peer country group, we can conjecture that the underlying trade costs to export in the former are higher than in the latter. We compute two measures of productivity in each country. The first one is the “Solow residualâ€? estimated from an OLS regression of a log Cobb-Douglas production function. Specifically, we regress total sales on total employment, total stock of capital, and cost of materials (all in logs). 63 The second is standard revenue-based labor 63 The regressions include industry fixed effects to control for observable and unobservable characteristics that change across industries but not across establishments within industries. 66 productivity, computed as the ratio of total sales to total employment at the establishment level. Tables 1.12 and 1.13 present the average productivity of the first quartile of exporters in each cell,64 and show that the minimum average productivity required to export in Russia is higher than in the peer countries. 65 This result is robust across our two productivity measures. In metals and machinery and chemicals and pharmaceuticals, the Russian productivity threshold is lower than in the peer countries, suggesting lower trade costs in those sectors. Overall, these results indicate that the underlying costs to export are on average higher in Russia than in benchmark countries. Table 1.12 Minimum productivity threshold to export (Solow residual), selected countries MinimumProductivityThresholdtoExport LTFPͲSolow'sResidual Industry Russia(09) Chile (06) SouthAfrica(07) Turkey(08) Brazil (09) Textilesandapparel 0.00 Ͳ0.47 Ͳ0.22 Ͳ1.16 Ͳ1.39 Food Ͳ0.50 Ͳ1.41 Ͳ0.82 Ͳ1.06 Ͳ2.37 Metalsandmachinery Ͳ0.52 Ͳ0.51 Ͳ0.45 Ͳ0.77 Ͳ1.36 Electronics Ͳ0.05 Ͳ0.20 Ͳ0.82 Chemicalsandpharmaceuticals Ͳ0.98 Ͳ0.28 Ͳ0.33 Ͳ0.70 Ͳ1.80 NonͲmetallicandplasticmaterials 0.00 Ͳ0.27 Ͳ0.48 Ͳ0.83 Othermanufacturing Ͳ0.08 Ͳ0.49 Ͳ0.32 Ͳ1.70 Ͳ0.41 Manufacturing Ͳ0.98 Ͳ1.41 Ͳ0.82 Ͳ1.70 Ͳ2.37 Source:PRMTRcomputationusingenterprise surveys,standardizeddata2006Ͳ2010. Note:Valuesrepresentthe minimumproductivitylevel withinexportersineachcell.Productivityiscomputedasthe  Solowresidual fromthe OLSestimationofalogCobbͲDouglasproductionfunction.Specifically,foreachcountrywe  regresstotal salesontotal employment,total stockofcapital,andcostofmaterials.The regressionsinclude industry fixedeffectstocontrol forunobservable characteristicsthatchange acrossindustriesbutnotacrossestablishments withinindustries.See EscribanoandGuasch(2004). Table 1.13 Minimum productivity threshold to export (revenue-based labor productivity), selected countries MinimumProductivityThresholdtoExport RevenueͲ basedLaborProductivity Industry Russia(09) Chile (06) SouthAfrica(07) Turkey(08) Brazil (09) Textilesandapparel 13.32 16.43 11.57 8.8 10.26 Food 12.43 15.24 10.43 10.46 11.38 Metalsandmachinery 12.56 16.54 11.25 8.7 10.76 Electronics 12.02 Ͳ 12.25 11.21 Ͳ Chemicalsandpharmaceuticals 12.91 16.45 11.68 10.7 11.74 NonͲ metallicandplasticmaterials 13.38 17.91 10.6 9.31 Ͳ Othermanufacturing 12.77 11.79 11.39 8.48 10.82 Manufacturing 12.02 11.79 10.43 8.48 10.26 Source:PRMTRcomputationusingenterprise surveys,standardizeddata2006Ͳ 2010. Note:Valuesrepresentthe minimumproductivitylevel withinexportersineachcell.Laborproductivityiscomputedastotal  salesovertotal employmentatthe establishmentlevel. 1.82. Identifying which of the underlying export costs is the most binding constraint for export participation is more difficult as it would require detailed firm-level information about the type of costs that exporting firms face and market-specific information about the exporting countries.66 An alternative way to gauge the impact of variable costs is to look at the Market Access Tariff Trade Restrictiveness Index, which calculates the equivalent uniform tariff of trading partners that would keep their level of imports constant.67 This index (including preferences) for Russia is 2.0 percent, below the average for the ECA region (2.6 percent) and the average for the upper middle-income group 64 A cell is an industry-country group. 65 Apart from South Africa in the Cobb-Douglas case. 66 This information is currently unavailable in the Enterprise Survey data. 67 It is weighted by import values and import demand elasticities of trading partners. 67 (2.3 percent). This indicates that variable export costs in Russia are slightly more favorable than for countries in the comparator regions, suggesting that the fixed costs to export are the key factor impeding export participation in Russia. 1.83. A direct implication of this analysis is that Russia has much unexploited trade potential in the form of firms that are willing, yet unable, to venture abroad because the fixed costs to export are too high. Reducing these fixed export costs provides rich opportunities to encourage firms to export as well as to facilitate firms in establishing new export relationships. These impacts go beyond traditional trade policies like reducing tariffs and quotas, which are more suitable to deepen existing trade relationships. These preliminary findings are in line with firm-level evidence provided by Volchkova (2010), who links firm-level information with customs data to find that Russian enterprises face a higher fixed exporting cost than French firms. 1.84. A particular concern over obstacles hampering Russian firms from exporting is the impact that the tax code has on small firms’ willingness to engage in exports.68 In Russia, exporting firms are entitled to receive a value-added tax (VAT) refund that, according to anecdotal evidence, increases the probability of being inspected by tax officials. Firms may therefore prefer not to export at all than to face tough tax controls and potential charges. We try to look at this issue using the establishment information from the Russia 2009 Enterprise Survey. On average there are fewer Russian exporters than in the comparator countries for each size category (table 1.14). Table 1.14 Share of exporters by size Shareofexportersbysize Size Russia(09) Chile (06) SouthAfrica(07) Turkey(08) Brazil (09) small(<20) 2.47 3.76 3.6 15.82 1.47 medium(20Ͳ99) 8.11 10.5 10.11 34.07 6.40 large(100andover) 16.62 33.08 36 23.26 54.91  Manufacturing 13.3 17.1 16.5 40.0 16.1 Source:PRMTRcomputationusingenterprise surveys,standardizeddata2006Ͳ2010. Note:Size categoriesare definedaccordingtototal employmentthresholdsindicatesinparenthesis. 1.85. To see if being an exporter increases the probability of being inspected by tax officials and, if so, to determine whether this impact is more important for small and medium enterprises (SMEs), we take advantage of the business-government relationships section in the 2009 Enterprise Survey. In particular, establishments were asked whether they were visited or inspected by tax officials. We are interested in estimating the correlation of this binary outcome with the export status of the establishment and its size. 1.86. A preliminary, albeit informative, way to achieve this goal is to estimate the impact of being an exporter on the probability that the establishment is visited by tax officials via a logistic regression. The dependent variable is the probability of being inspected defined as a dummy variable equal to 1 if the establishment was visited by tax officials. Table 1.15 presents the results. In specification 1, we observe that being an exporter increases the probability of being inspected, this effect is statistically significant at 1 percent and robust across specifications. In specification 2, we add sales as an indicator of the economic dimension of the plant and we observe the impact on the probability of being audited is very 68 Tax rates are perceived by businesses in general as a major obstacle to growth (Plekhanov and Isakova 2011). 68 low, albeit significant. In specification 3, we add a dummy variable, which is equal to 1 is the establishment has fewer than 100 full-time employees and we observe that this characteristic reduces the probability of being audited indicating that bigger firms are more likely to be inspected than other firms. In specification 4, we add an interaction term between the small establishment dummy variable and the exporter dummy variable to check whether the response of high probability of tax auditing for exporters varies across firm size. This interaction variable is not significant, thus small exporting firms do not face higher probabilities of being audited than other exporters in Russia. Table 1.15 Probability of inspection by tax officials Regressor Spec1 Spec2 Spec3 Spec4 Exporter 0.19 0.20 0.19 0.19 [0.04]*** [0.04]*** [0.05]*** [0.05]*** sales 0.00 0.00 0.00 (0.00)** [0.00]* [0.00]* Small Establishment Ͳ 0.15 Ͳ 0.15 [0.06]*** [0.06]*** ExporterXsmall 0.01 [0.02] IndustryFixedeffects yes yes yes yes Observations 526 526 526 526 Loglikelihood Ͳ 444.0 Ͳ 320.5 Ͳ 316.8 Ͳ 316.8 Note:Marginal effectsevaluate atthe meansof the  independientvariables.*p<0.1;**p<0.05;***p<0.01 1.87. In conclusion, this preliminary analysis indicates that Russian exporters face a higher probability of tax inspection than nonexporting firms, of around 20 percent. This finding is in line with the explanation that the VAT refund may encourage tax inspections, but we cannot test this with the available data. We did not find a significant difference in the probability of being inspected across different sizes of exporters. Policy Options 1.88. This chapter has analyzed different dimensions of Russia’s trade performance. While lack of export diversification is a well-known problem facing the Russian economy, this chapter goes beyond it by exploring other dimensions, such as the sophistication and quality of its export basket and the survival rate of its export relationships. We use these analyses to shed light on the most binding constraints to export diversification. 1.89. The overall results indicate that quality and innovation are key determinants in encouraging firms’ participation in international trade and, thus, export diversification. We also find preliminary evidence of the role of fixed costs in exporting as an additional factor limiting export diversification. In particular, we find evidence that Russian exporters face a higher probability of tax inspection than nonexporting firms, which may diminish their willingness to export. This may be especially important for SMEs. 1.90. Russia’s oil and gas sector grew in the decade from slightly less than half to about two- thirds of the country’s exports in 2008. As a result Russia shows the highest level of product concentration within the BRICs. The problem encompasses not only merchandise trade, as trade in services – a potential alternative for export diversification – also showed limited dynamics. The 69 concentration problem is limited to products, though – compared with the other BRICs, Russia has the lowest concentration index for markets. Still, a gravity model applied to nonoil exports in conjunction with an assessment of the pattern of trade at the regional level indicates the existence of untapped potential of export diversification within established bilateral trade relationships. These results back the idea of regional export promotion agencies supporting mainly SMEs to engage in exports. 1.91. The analysis also shows that there are problems of quality/sophistication in the export basket of the country. The sophistication of Russia’s export basket has almost continuously decreased over time, while China’s and India’s have increased. While in 2002 Russia showed the highest EXPY (a measure of sophistication of the export basket), in 2008 China overtook Russia. In addition, the analysis confirmed that Russia seems to have few short-run opportunities to move to new products and limited scope for quality upgrading. In addition, we found robust evidence that quality and innovation are key determinants affecting the probability of exporting at the firm level: a 1 percent increase in quality and innovation increases the probability of a Russian firm starting to export by 32.9 percent. These findings set the stage for innovation-driven economic growth that aims to reduce the reliance on resource-based products, which is in line with the government’s 2008 Long Term Strategy for Socio-Economic Development. The main challenge now is to translate the research base that this program has created into commercial innovation and generate the right incentives for firms to start adopting this knowledge into their production processes. 1.92. Another finding relates to the low rates of survival of export relationships in Russia. The probability of a Russian export relationship surviving until the second year is about 0.57, and maintaining a relationship for five years is 0.22, both much lower than the survival rate of China’s export relationships and even those for Brazil and India. This result is even more striking when coupled with the fact that, as expected given its development level, most of the export growth in Russia takes place at the intensive margin, with increases of old products in old markets. These results highlight the importance of policies that focus on sustaining current trade relations and on encouraging new, durable trade relationships at the firm level. These types of policies may be implemented by the recently strengthened regional export promotion agencies, for example. 1.93. For trade policies, we have shown that licensing policies and tariff-rate quotas are the two most binding nontariff measures that limit the ability of Russian firms to benefit from competition, creating obstacles to the innovation process. Adopting a low and uniform tariff structure could bring benefits for an economy that seeks to enhance export diversification through innovation. 1.94. 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"The weight of economic and commercial diplomacy," ISS Working Papers - General Series1765018715, International Institute of Social Studies of Erasmus University (ISS), The Hague. 73 Chapter 2: Competition and Competition Policy  in the Russian Federation x Effective competition and competition policies can play a key role in fostering economic diversification. The entry conditions facing new (innovative) firms and the exit of obsolete ones, which would raise the productivity of surviving firms, are the main process through which the growth prospects of the firms in the non-extractive industries would be strengthened. In particular, regulations that promote competition may increase the incentive – and lower the cost – to invest and innovate by incorporating new technologies in the production process, thus stimulating productivity growth. In Australia, estimates suggest that the economy experienced wide gains from the effects of competition policies on productivity improvements and price changes in key infrastructure areas during the 1990s, which boosted GDP by 2.5 percent (around US$20 billion).69 And this is a conservative estimate because it does not consider the effects of dynamic efficiency gains from more competitive markets. x However, Russia’s regulatory framework is one of the most restrictive for competition among developed and leading developing economies. Between 2001 and 2007, the share of highly concentrated markets in Russia rose from 43 percent to 47 percent, a high incidence of concentrated sectors compared with most developed economies.70 Contrary to the experience of earlier reformers in Eastern Europe, firm dynamics (entry and exit) in Russia have not significantly contributed to productivity growth. Entry rates have been very low. And exit rates, though difficult to estimate, are probably much lower than in most transition economies, if one considers that enterprise restructuring in Russia lags behind that in Poland, Turkey, and the average of countries in the Europe and Central Asia (ECA) region. x But competition conditions in Russia can still be improved. Empirical analysis reveals that domestic competition is relatively important for increasing Russian firms’ productivity. According to an analysis of data from the Business Environment and Enterprise Performance Survey (BEEPS) for 2008, those firms facing intense competitive pressure from domestic firms are on average 18.8 percent more productive and have a 7.9 percent higher probability of exporting than other firms. However, Russian markets are still dominated by a few incumbent players, with some regions registering more than 200 dominant firms. Russian prices for selected consumers markets are 20 percent higher than in other economies of the ECA region. Regional price dispersion among key sectors in Russia (pharmaceuticals, communication services, and retail gasoline) is present even after controlling for factors affecting price variation such as distance and the level of regional economic activity. Finally, aggregate and sector- specific price-cost margins reveal that Russian firms tend to have margins consistent with less competitive markets than other countries in the region. A more detailed analysis of price-cost margins in  This chapter was prepared by Martha Martinez Licetti, Investment Climate Advisory Services, Strategy & Analysis Unit, The World Bank and Mariana Iootty, ECSPF, The World Bank. Carolina Austria, Alina Tourkova, and Yana Ukhaneva provided research assistance. The authors would like to thank the technical departments of the Federal Antimonopoly Service, in particular Ms. Olesya Minaeva, Head of International Projects Division, for providing detailed information and statistics on the status of competition in the Russian Federation. 69 Productivity Commission 2005; Crawford 2009. 70 Concentration ratios are calculated using the Herfindahl-Hirschman Index and the three-bank concentration ratio methodologies. A highly concentrated industry is defined as one in which the Herfindahl-Hirschman Index is greater than 2,000. For a detailed methodology, see Conway, Lysenko, and Barnard (2009). 74 selected sectors reveals that firms in sectors where Russia registers higher price-cost margins than regional counterparts tend to be older and larger, have smaller export orientation and research and development intensity, are more likely to operate in local markets, and, in some cases, are less likely to operate in a competitive market structure. x Competition levels are also affected by remaining market fragmentation. Based on the 2009 BEEPS, about 50 percent of Russian firms consider local (regional) markets their main sales destination – a large number, even compared with similar economies such as Brazil (about 3 percent). Despite the size of the Russian economy, such isolation from global markets may induce companies to choose less modern technology and operate at suboptimal scales, thus reducing productivity levels. In the particular case of Russia, two factors could potentially explain market fragmentation and less competitive markets: transport costs (related to limited transport infrastructure and long distances), and barriers created by the interventions of regional governments that hamper the entry of firms from outside the region. x Among regional authorities, enforcement of regulations and anticompetitive actions differ extensively in several policy areas, contributing to market fragmentation. The application of state aid regimes, enforcement of competition rules related to tendering, and specific anticompetitive practices, as well as actions conducted by government, affect competition among regions and distort the playing field. Market dynamics and government involvement also vary widely across key economic sectors. The stage of development of competition and the regulation of infrastructure, manufacturing, and services vary greatly among industries. Finally, competition constraints are felt in transport, construction, and banking through extensive state control, self-regulation, and regulatory barriers to new market participants. x Interventions that could help foster competition and increase the effectiveness of the competition policy framework are summarized below. 75 Summary of policy options Economywide interventions Topic Recommendations Expected impact State aid and preferential Broaden the mandate on state aid regulation to diminish state Level the playing field, reduce treatment aid to particular firms and sectors favoritism, and increase transparency Eliminate preferential treatment to state or municipality-owned corporations Create an inventory of state aid by beneficiary and evaluate distortions of competition of state aid (including tax arrears) Align state aid regulation and enforcement with international best practice (focusing on horizontal objectives, including balancing tests and effects on competition) Potential collusive Guarantee open and efficient tender processes Reduce possibilities of collusion behavior and discretion and corruption in tender process Reduce possibilities of collusion by introducing certificates of independent bidding determination and introducing prohibitions Reduce the cost of doing to contract and take part in public procurement if a firm has business in public procurement participated in a cartel Spillover effect – construction Sector-specific interventions Topic Recommendations Expected impact Self-regulation of Provide specific prohibitions on self-regulation that facilitates Increase entry and reduce prices business associations price-fixing and limits entry of services Transport Eliminate price controls and government involvement in Increase competition competitive sectors Reduce direct participation of the state in provision of goods Construction Provide a unified database of land plots with complete Limit the benefits of informal information about ownership and use status or potential relationships with local officials restrictions on future use that certain construction firms possess Streamline the processes for registration, obtaining construction permits, and licensing schemes for each segment of the supply Increase incentives for entry as chain well as the number of participants Review the impact on competition of the requirement that certain construction firms must have prior experience for similar, large projects before they can bid for a new contract 76 Performance and Competition of the Russian Federation: How does Russia compare with other economies in the region? 2.1. Even though significant progress has been made in the last few years, Russia still lags behind economies in the ECA region in the intensity of market competition. Russia ranks in the third- lowest decile (30 percentile) in the intensity of local market competition and the extent of market dominance for economies in the region (figure 2.1). Figure 2.1 Competition indicators, 2010 Intensity of local market competition Extent of market dominance Germany Germany Belgium Switzerland Sweden Belgium Austria Netherlands UnitedKingdom Austria UnitedKingdom Netherlands Denmark CzechRep. CzechRepublic Turkey Italy France Norway Denmark Sweden Spain France Norway Finland Estonia Luxembourg SlovakRep. Cyprus Poland Spain Switzerland SlovakRepublic Hungary Ireland Slovenia Estonia Portugal Poland Turkey Ireland Malta Finland Montenegro Greece Slovenia Lithuania Romania Romania Hungary Italy Albania Latvia Greece Bulgaria Latvia Macedonia, FYR Macedonia Macedonia,FYR Moldova Bulgaria Kazakhstan RussianFederation Albania Kazakhstan Croatia Portugal RussianFed. Lithuania Tajikistan Ukraine Moldova Montenegro Azerbaijan Tajikistan Iceland Georgia Georgia KyrgyzRep. Israel Serbia Croatia Bos&Herz KyrgyzRepublic Azerbaijan Ukraine Armenia Armenia 0 1 2 3 4 5 6 0 1 2 3 4 5 6 Note: Left panel is based on answers to the question “How would you assess the intensity of competition in the local markets in your country? (1=limited in most industries; 7= intense in most industries).â€? Right panel is based on answers to the question “How would you assess the extent of market dominance in your country? (1=few players; 7= competition).â€? Source: World Economic Forum, Global Competitiveness Report, 2010–2011 77 2.2. The regulatory environment in Russia is restrictive. State control is extensive and there are high barriers to trade and investment. Based on the Organisation for Economic Co-operation and Development’s (OECD) Indicators of Product Market Regulation, Russia is one of the most restrictive European countries (figure 2.2). Figure 2.2 Indicators of Product Market Regulation, selected European countries, 2008 Productmarketregulation Statecontrol 3.5 5 3.094 4.39 4.5 3 4 2.5 3.5 Mean= Mean= 3 2 2.5 2.41 1.54 1.5 2 1.5 1 1 0.5 0.5 0 Turkey Germany Hungary Norway Greece Portugal Netherlands Slovenia RussianFederation Poland Belgium Sweden Switzerland France Austria Spain Denmark Luxembourg CzechRepublic Italy Finland SlovakRepublic Estonia 0 Barrierstoentrepreneurship Barrierstotradeandinvestment 3 3.5 3.11 2.5 3 1.78 2.5 2 Mean=1.43 2 1.5 1.5 1 Mean=0.77 1 0.5 0.5 0 0 Note: Index is on a scale of 0–6 from least to most restrictive. Source: Indicators of Product Market Regulation, OECD (2008). 2.3. The World Bank’s Trade Restrictiveness Index also ranks Russia’s trade policies as highly restrictive. Russian tariffs and other nontariff barriers on all imports are higher than those of other countries, especially through nontariff barriers in the form of technical regulations and quantitative restrictions (figure 2.3). 78 Figure 2.3 Trade Restrictiveness Index, 2008 OverallTradeRestrictivenessIndex AgriTradeRestrictivenessIndex Mfg.TradeRestrictivenessIndex 0.20 0.70 0.25 0.18 0.16 0.60 0.16 0.20 0.14 0.50 0.15 0.12 0.15 0.40 0.10 Mean= 0.30 0.25 0.10 0.08 .06 Mean= Mean= 0.06 0.20 .16 .05 0.05 0.04 0.10 0.02 Ͳ Armenia Georgia Ukraine Moldova Kazakhstan KyrgyzRep Turkey Russia Chile Macedonia Norway Azerbaijan Ͳ Ͳ Ukraine Kazakhstan KyrgyzRep Kazakhstan Ukraine KyrgyzRep Armenia Turkey Georgia Armenia Norway Norway Turkey Georgia Russia Moldova Chile Macedonia Russia Chile Macedonia Moldova Azerbaijan Azerbaijan Note: The Trade Restrictiveness Index captures the trade distortions that each country imposes on its import bundle. Index is on a scale of 0–1 from least to most restrictive. Source: World Bank 2008. 2.4. Russian prices for selected consumer products71 are higher than comparable prices in other countries within the region,72 controlling for per capita GDP, time effects, and trade costs.73 Using monthly information for 2005–10, table 2.1 presents the regression results with and without variables that control for factors that may affect prices. The Russia dummy variable captures price levels in Russia relative to other countries after adjusting for GDP per capita, cost of imports, and product and time control variables. For January 2005–July 2010, empirical results indicate that, on average, prices in Russia are around 20 percent higher than in Commonwealth of Independent States counterparts. Differences in GDP per capita and import costs do not capture the difference in prices. In addition, countries with larger GDP per capita and higher import costs are associated with higher prices in the economy for the products under analysis. 71 Prices for the following food products are in the sample: beef (excluding boneless meat); butter; fresh milk (2.5–3.2 percent fat content); hen’s eggs; macaroni from wheat flour of highest category; rye bread; sugar (granulated); sunflower seed oil; and white bread of high quality flour. 72 Sample countries are Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic, Moldova, Russia, Tajikistan, and Ukraine. 73 The baseline empirical specification for the price comparison analysis follows the equation: Log ( price ijt ) E 1 Russia  E 2 Log ( Xjt )  K i  G t  H it Where: i product , j country , t month , year Log ( Xjt ) G DP per capita, cost of imports - as control variables K i product fixed effects G t time fixed effects (month, year, and monthly * year) The empirical specification also controls for robust standard errors. 79 Table 2.1 Price comparisons analysis – Russia vs. Commonwealth of Independent States countries Variable Baseline regression Regression with controls Regression with controls- 2 Coeff t-stat Coeff t-stat Coeff t-stat Russia dummy 0.2680 (**) 6.53 0.1864 (**) 2.56 0.1845 (**) 2.34 Log (GDPpc) 0.0594 (*) 1.85 0.0776 (**) 2.40 Log (cost of import) 0.1509 1.70 Specification includes Year fixed effects X X X Monthly fixed effects X X X Product fixed effects X X X Year * Month fixed effects X X X Note: (**) significant at 95%, (*) significant at 90%. 2.5. Russian firms exhibit higher price-cost margins (PCMs) than manufacturing firms elsewhere in the region. Using firm-level data from the Enterprise Surveys conducted in several regional economies, PCMs – one of the indicators Figure 2.4 Distribution of observed PCM in manufacturing, used to measure competition in a market – Russia and selected ECA countries are calculated for Russia and comparator countries. 74 Figure 2.4 presents the distribution of estimated PCM values for Russia and the selected set of ECA countries in manufacturing. 75 For Russia and the comparator group, the figure shows a right-skewed distribution, which indicates that the bulk of the values lie to the left of the mean. This result, which is consistent with theory, means that a larger part of firms have lower than average margins and a smaller proportion of firms Note: Russia=1, selected ECA countries=0. extract a very high PCM. Source: Authors’’ calculations 2.6. Russian firms register larger PCMs than the regional average in every manufacturing sector except food, garments, and chemicals. Figure 2.5 compare the index values of average PCM across the selected countries in the ECA region, assuming that the country with the smallest PCM has an index equal to 100. However, the value for Russia is statistically and significantly higher only for the other manufacturing, textiles, and electronics sectors.76 74 Annex 2A summarizes the empirical specification and data used to calculate price cost margins. 75 Using BEEPS sample weights. 76 For these sectors, the difference between the mean value for Russia and that for the set of comparator countries was significantly different from zero, at the 1 percent level. Results are available on request. 80 Figure 2.5 Mean PCM across countries by sector – index number Othermanufacturing Food 250.0 300.0 250.0 200.0 175.5 200.0 Average 175.4 150.0 Average 150.0 100.0 100.0 100.0 100.0 50.0 50.0 0.0 0.0 500.0 Textiles Garments 500.0 450.0 450.0 Average 400.0 350.0 400.0 300.0 Average 264.4 350.0 300.0 272.0 250.0 200.0 158.9 250.0 150.0 200.0 100.0 150.0 50.0 100.0 0.0 50.0 Serbia Belarus Turkey Latvia Estonia Romania Russia Bulgaria Bosnia Slovakia Lithuania Poland FYROM Hungary 0.0 CzechRepublic Kazakhstan Chemicals PlasticandRubber 900.0 600.0 800.0 500.0 700.0 600.0 Average 400.0 Average 495.5 500.0 282.0 300.0 400.0 300.0 200.0 200.0 100.0 100.0 100.0 100.0 0.0 0.0 Nonmetallicmineralproducts BasicMetals 700.0 7000.0 600.0 6000.0 500.0 Average 432.0 5000.0 400.0 4000.0 Average 3089.3 300.0 3000.0 200.0 100.0 2000.0 100.0 1000.0 100.0 0.0 0.0 250.0 Fabricatedmetalproducts Machineryandequipment 400.0 350.0 200.0 Average 179.6 300.0 Average 238.6 250.0 150.0 200.0 100.0 100.0 150.0 100.0 100.0 50.0 50.0 0.0 0.0 81 Electronics 1400.0 1200.0 1000.0 899.8 800.0 Average 600.0 400.0 200.0 100.0 0.0 Source: Authors’ calculations 2.7. Different indicators generally show that competition in Russia is relatively weak compared with economies in the region: the intensity of local competition is low, product market and trade regulations are highly restrictive, and market outcomes such as prices and PCMs are higher than in counterparts. Factors Affecting Competition in Russia 2.8. Local markets are characterized by fragmentation in the presence of transport and information costs as well as entry barriers. Empirical and econometric analysis suggests that prices among Russian regions vary significantly even after controlling for factors that may affect price differences, such as the level of income, distance to markets, population, and time and product fixed effects. Previous research on price dispersion among regions for the period before 2000 finds that large differences in interregional prices could not be explained by distance and attributed the reason for price dispersion to the behavior and attitude of regions toward markets.77 More recent studies suggest that only 36 percent of Russian regions were integrated with the national market during 1994–2000, 44 percent were in the process of integrating, and the rest were not integrated nor intended to integrate. For some regions, market frictions prevented prices from being close to national prices.78 2.9. Using ROSSTAT data for 2003–10, regression analysis on selected products confirms that price levels still register significant variation across Russian regions after controlling for variables that account for differences in market demand, access to markets, and time trends (see annex 2A).79 The level of gross regional product (GRP) per capita is associated with higher prices. The results also show that prices increase with distance, showing that transport costs still influence prices regionally. However, significant variation still persists after these factors are taken into account, revealing that specific conditions within regions and potential barriers to competition are still preventing arbitrage. 2.10. Compared with Moscow city, price variations across Russian regions are substantial, after controlling for both GRP per capita and distance. For example, some regions such as Mordovia and Volgograd register prices 35 percent and 39 percent below those in Moscow, while Sakhalin and Magadan show price levels only 7 percent and 11 percent below Moscow’s (figure 2.6). Chukotka registers prices 34 percent higher than in Moscow while the overall price level in Bryansk is 55 percent lower. 77 Berkowitz and De Jong (2002). “Integration: An Empirical Assessment of Russia,â€? William Davidson Working Paper Number 488. 78 ““Russia’s common market takes shape: Price convergence and market integration among Russian regions,â€? Konstantin Gluschenko. BOFIT- Institute for Economies in Transition -Bank of Finland. BOFIT Discussion Papers 7/ 2006. 79 Sample includes prices for amoxicillin, beef, economy flight, gasoline, Internet charges, and local mobile connection. 82 Figure 2.6 Regional price levels, adjusted for GRP per capita, distance, and time and product fixed effects 130% 110% 90% 70% 50% 30% MoscowCity Tver Astrakhan Ryazan Saratov Belgorod Bryansk JAR Khabarovsk Murmansk Arkhangelsk Krasnoyarsk Yamalo Perm Kursk Kabardino Kalmykia Ulyanovsk Karachay StPetersburg Karelia Irkutsk Tula Khakassia Altai Khanty Samara Mordovia Udmurt Vladimir Sakha Ingushetia AltaiRep Rostov Kurgan MariEl Vologda Voronezh Sakhalin Central Far North Northwes South Caucasus Siberia Ural Volga Eastern tern ern Source: Authors’ calculations based on regression analysis. 2.11. However, price variation is actually product specific and varies among regions. This suggests that local conditions beyond the level of GRP per capita, population, and distance from main markets influence prices (figure 2.7). For example, beef prices in the most expensive regional market (Koryak Region) are more than twice as high as in the least expensive market (Tuva Region). Likewise for cement, prices in Chukotka are nearly five times as high as in Karachay, even after adjusting for factors that affect price dispersion. Figure 2.7 Price variation among regions for selected products, adjusted for GRP per capita, distance to district center, average household consumption, and time fixed effects Product:Beef Product:Cement Sector:Food Sector:Nonmetalmineralproductionand construction 180% 400% 160% 350% 140% 300% 120% 250% 100% 200% 80% 150% 100% 60% 50% 40% 0% 20% Murmansk Kalmykia Sverdlovsk Krasnoyarsk FarEast Primorsky Novosibirsk Karachay Amur Vladimir Tyumen Kurgan Kabardino Kamchatka Voronezh Kostroma Kursk Tatarstan Chukotka Khanty Samara Vologda 0% Koryak Murmansk Omsk Kalmykia Nenets Tomsk UstOrda Sakha Evenki Khakassia Yaroslavl Stavropol Lipetsk Saratov Ryazan Vladimir Rostov Kurgan Vologda Voronezh Tatarstan Chuvash 83 Product:Gasoline Product:Mobileconnectionfees Sector:Other Sector:Communication 250% 160% 140% 200% 120% 150% 100% 80% 100% 60% 50% 40% 20% 0% 0% Adygea Adygea Penza Tuva Primorsky Orenburg Penza Orenburg Nenets Yamalo Rostov Bashkortostan Saratov Bashkortostan Arkhangelsk Ivanovo Bryansk Vladimir JAR Ryazan Magadan Kursk Magadan Ivanovo Belgorod Novgorod Irkutsk Kamchatka Chukotka Voronezh Tomsk Kaliningrad Pskov Tula StPetersburg Mordovia Ingushetia Sakhalin Stavropol Kaliningrad MariEl Vologda Note: A complete list of products analyzed is presented in annex 2A. Source: Authors’ calculations. 2.12. Variation in the competitive environment (market structure, degree of state control, regulatory barriers, and anticompetitive practices) as well as lack of integration across markets and regions are potential factors causing such large differences across geographic and product markets in both the level of prices and in the PCMs analyzed below. Market Structure and Firm Characteristics 2.13. A more detailed analysis of PCMs in selected sectors reveals that firms in sectors where Russia registers higher PCMs than regional counterparts tend to be older, larger, have smaller export orientation and research and development (R&D) intensity, are more likely to operate in local markets, and, in some cases, are less likely to operate in a competitive market structure. When assessing the average level of PCM that prevails in a certain sector in Russia and how it compares with other countries, it is worth examining, for each sector, the main characteristics that are frequently used in the empirical industrial organization literature to explain the mark-up level, like establishment size, concentration, product differentiation, competitive pressure, and barriers to entry. 2.14. Data from BEEPSs allow us to consider some of these firm-level characteristics. Size, measured by number of full-time employees, is used as a standard technologically based parameter and is a proxy for size advantages, such as scale economies at the firm level. Product differentiation is proxied by R&D intensity (defined as the R&D spending divided by sales), though the data from BEEPS do not allow for a distinction between product and process innovation. Age, measured in years, is employed as a way to reflect the ability of an incumbent firm to deal with competitive pressure from entry and exit in the sector. Competitive pressure is proxied by two alternative indicators at firm level. First, as the BEEPS dataset does not allow the computation of a sector’s concentration ratios, the competitive pressure is reflected, by the number of competitors a firm has in its local/national market, and then by the firm’s export orientation, as it reflects the firm’s exposure to international markets. Second, to reflect the barriers that a firm faces to operate in the market, we consider the frequency of firms that perceive business licensing and permits as an obstacle. 2.15. Data show that the sectors where the average PCM in Russia is significantly higher than the other countries’ average (in other manufacturing, electronics, and textiles) have some similarities 84 (table 2.2). Compared with the regional average for the same sector, firms in the other manufacturing sector tend to be older, be larger, have smaller export orientation and R&D intensity, are less likely to consider business licensing and permits as a barrier, and are more likely to operate in a local/national market structure. Firms in electronics seem to have a similar profile, except for the fact that their average R&D intensity is equal to the regional average for the sector, they are more likely to perceive licensing and permits as an obstacle, and are less likely to operate in a competitive market structure. Firms in Russia’s textiles sector have some similarities with other manufacturing and electronics firms in the country, particularly relating to size and export orientation, as they also tend to be older and less export oriented than the regional average. However, they differ in R&D intensity as theirs is higher than the average of the textiles sector in the region. 2.16. Regression analysis also suggests that as an incumbent firm gets older, larger, and is less likely to invest in R&D, it extracts higher PCM than the average for other countries for the same sector. An alternative way to examine variation in mark-up differential between Russia and the selected set of ECA countries across all the sectors is to estimate a “mark-up price differential equationâ€? with size, age, export-orientation, perception about the barriers to entry set by government, main market where the firm operates, and number of competitors as explanatory variables. 2.17. The following equation tries to explain the cross-sector variation in mark-up differential between Russia and the ECA region by sector using these characteristics as explanatory variables. The equation for firm i in sector j in Russia is: തതതതതതതതതതത ܲ‫ܯܥ‬௜à¯? െ ܲ‫ܯܥ‬ ఫா஼஺ ቆ ቇ ൌ ߚ଴ ൅ ߚଵ ܵ݅‫Ý?ݖ‬௜à¯? ൅ ߚଶ ‫Ý?݃ܣ‬௜à¯? ൅ ߚଷ ‫݌ݔܧ‬௜à¯? ൅ ߚସ ܴƬ‫Ý?݊݅ܦ‬௜à¯? ൅ ߚହ ‫Ý?Ý?݇ݎܽܯ‬௜à¯? ൅ ߚ଺ ‫݌݋݊݋ܯ‬௜à¯? ൅ ߚ଻ ‫݉ݎÝ?ܲ݊Ý?ܿ݅ܮ‬௜à¯? ൅ ܲ‫ܯܥ‬à¯?ா஼஺ തതതതതതതതതതതതത ௉஼ெ೔ೕ ି௉஼ெ where ൬ ௉஼ெೕಶ಴ಲ ണಶ಴ಲ ൰ is the relative difference of ܲ‫ܯܥ‬௜à¯? (the PCM level for firm i in sector j in ఫா஼஺ (the PCM average in sector j for the other ECA countries). ܵ݅‫Ý?ݖ‬௜à¯? is a dummy for തതതതതതതതതതത Russia) and ܲ‫ܯܥ‬ size (small, medium, and large). ‫Ý?݃ܣ‬௜à¯? is the age of firm in years. ‫݌ݔܧ‬௜à¯? is a dummy controlling for exporting status. ܴƬ‫Ý?݊݅ܦ‬௜à¯? is the R&D intensity of the firm. ‫Ý?Ý?݇ݎܽܯ‬௜à¯? is a categorical variable that identifies the main market of the firm (local, national or international). ‫݌݋݊݋ܯ‬௜à¯? is a dummy for a firm that has no competitor in its local/national market. ‫݉ݎÝ?ܲ݊Ý?ܿ݅ܮ‬௜à¯? is a dummy distinguishing the firm that consider business license and permit as a very severe obstacle. Finally, ܵÝ?ܿ‫ݎ݋Ý?‬௜ is a dummy controlling for sector fixed effects. We use unweighted OLS estimation and compute clustered standard errors to allow for possible correlations in PCM across firms in the same sector. Table 2.3 summarizes the results. 85 Table 2.2 Mean values for selected variables in Russia and the other ECA countries, by sector Other Other Other Other Other Russia countries Russia countries Russia countries Russia countries Russia countries Firm size Business licensing /permit (no. of full-time Export orientation R&D intensity as a barrier employees)a Age (years) (% of firms) (% of sales) (% of firms)b Other manufacturing 134.9 55.2 16.94 15.9 13.4 34.0 0.3 0.6 2.2 4.1 Food 139.4 49.9 15.48 18.8 8.8 17.3 0.5 0.5 17.5 9.8 Textiles 22 107 53.04 16.4 10.0 54.6 0.5 0.3 0.0 4.2 Garments 70.33 82.9 15.38 14.6 1.9 56.5 0.5 0.3 27.2 8.0 Chemicals 97.76 112 16.41 17.8 13.7 61.4 4.3 1.4 15.7 3.2 Plastics and rubber 53.49 37.4 16.92 14.7 23.3 32.2 1.8 0.4 0.0 14.7 Nonmetallic mineral products 231.8 67.5 27.06 19 13.9 31.4 0.5 0.6 0.0 5.9 Basic metals 1073 198 19.86 17 49.6 64.3 0.4 0.7 12.7 0.7 Fabricated metal products 60.72 36.4 13.17 12.8 11.2 34.3 1.9 0.4 0.7 7.1 Machinery and equipment 151.2 38.3 15.39 19.6 11.1 45.7 3.4 1.3 6.3 3.7 Electronics 226.2 112 49.95 18 10.9 41.2 1.5 1.5 22.4 1.4 86 Table 2.2 Mean values for selected variables in Russia and the other ECA countries, by sector (cont’d.) Russia Other countries Russia Other countries Market structure (in local/national Market structure (in local/national Main market Main market market) market) (% of firms) (% of firms) (% of firms) (% of firms) More More Local National International Local National International Monopoly Duopoly 3 to 6 than 6 Monopoly Duopoly 3 to 6 than 6 Other manufacturing 50.1 41.8 8.1 28.8 51.2 20.0 4.5 0.0 18.7 76.8 8.1 2.9 31.0 57.9 Food 71.0 29.0 0.0 49.2 45.9 5.0 4.7 3.1 29.4 62.8 3.7 2.3 20.2 73.8 Textiles 100.0 0.0 0.0 23.3 51.4 25.3 0.0 0.0 100.0 0.0 5.3 2.7 19.2 72.8 Garments 58.9 41.1 0.0 21.0 44.3 34.7 3.1 2.5 17.3 77.1 1.8 0.9 28.4 68.9 Chemicals 34.0 62.9 3.1 7.7 50.3 42.0 5.5 4.8 35.6 54.1 3.1 2.2 25.6 69.2 Plastics and rubber 69.2 30.8 0.0 33.4 57.0 9.6 0.0 0.0 30.8 69.2 0.2 10.9 25.7 63.1 Nonmetallic mineral products 34.8 65.2 0.0 20.6 64.9 14.4 0.0 0.0 9.7 90.3 5.1 5.8 32.0 57.1 Basic metals 11.0 89.0 0.0 13.3 53.1 33.6 0.0 0.0 38.7 61.3 5.3 10.0 57.5 27.2 Fabricated metal products 50.8 45.3 3.9 28.3 54.6 17.1 6.4 6.8 43.2 43.6 4.0 5.2 34.6 56.2 Machinery and equipment 38.9 57.9 3.1 12.6 61.6 25.8 6.6 6.6 53.9 33.0 0.7 2.5 35.1 61.7 Electronics 24.5 75.5 0.0 31.3 50.4 18.3 0.0 0.0 68.9 31.1 3.6 7.3 14.3 74.7 a. Firm size is measured by number of permanent full-time employees plus the number of full-time seasonal employees. b. Business licensing and permits as a government barrier is measured by the average proportion of firms that perceive business licensing and permit as a very severe obstacle. 87 Table 2.3 Cross-sector variation in mark-up differential between Russia and the ECA region (1) (2) (3) (4) (5) (6) (7) Age 0.002** 0.002 0.002 0.001 0.001 0.000 0.001 (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Medium -0.027 -0.027 -0.030 0.008 0.018 0.026 (0.043) (0.045) (0.046) (0.050) (0.053) (0.083) Large 0.070 0.071 0.071 0.157** 0.190*** 0.170*** (0.044) (0.050) (0.049) (0.050) (0.055) (0.052) Export-oriented -0.008 -0.007 -0.054 -0.059 -0.092 (0.062) (0.064) (0.104) (0.101) (0.102) R&D intensity -0.005** -0.004* -0.005* -0.005* (0.002) (0.002) (0.002) (0.002) National market -0.045 -0.044 -0.024 (0.052) (0.047) (0.049) International market 0.037 0.000 0.000 (0.204) (0.000) (0.000) Monopolist -0.020 0.103 (0.113) (0.062) Licensing/permit as a barrier 0.022 (0.052) _cons -0.036* -0.047** -0.047** -0.042* -0.164*** -0.132*** -0.072 (0.019) (0.018) (0.018) (0.019) (0.029) (0.027) (0.045) Sector control Yes Yes Yes Yes Yes Yes Yes N.obs 532 532 532 532 437 414 379 *** p<0.01, ** p<0.05, * p<0.1 Note: Clustered standard errors by sector are in parentheses. 2.18. Due to the absence of a proper structural model, these results have limited analytical power and must be interpreted only in their statistical sense. However, the results can provide further clues on the main firm characteristics that affect the mark-up differential in Russia compared with a selected set of ECA countries. In this regard, the results suggest – for four of seven specifications tested – that as an incumbent firm gets older in Russia it extracts higher PCM than the average for the other countries in the same sector. There is also evidence that the larger a firm in Russia, the higher its PCM compared with the regional average in the same sector. Finally, data also suggest that the higher the R&D intensity of a Russian firm, the smaller its PCM compared with the average PCM. 2.19. To identify the type of competition and ultimately relate it to the sector mark-up estimates in Russia, taxonomy of market structure is established, which reveals that sectors with larger product differentiation and smaller fragmentation register higher PCMs. Following the approach used in Oliveira Martins, Scarpetta, and Pilat (1996), a starting point is the observation that differences in market power across manufacturing industries are at least partly due to differences in entry conditions for each sector, which in turn have been related, among other factors, to technological conditions such as economies of scale and product differentiation. Two variables are then used: firm size, as a proxy for the existence of size advantages such as scale economies at the firm level; and R&D intensity, as a proxy of product differentiation. Sectors where average establishment size is smaller than the average of manufacturing industry in Russia is termed fragmented, while a sector with larger average size is classified as segmented. In fragmented sectors, the number of firms typically grows in line with the size of the market, while segmented sectors are characterized by the presence of large establishments, and firm concentration remains relatively stable.80 Based on the second indicator – R&D intensity – a sector is 80 Oliveira Martins, Scarpetta, and Pilat 1996. 88 classified as low differentiated if its average R&D intensity is inferior to the country’s average, or high differentiated when average R&D intensity is larger than the country’s average. 2.20. Table 2.4 provides a breakdown of manufacturing sectors based on the combination of size and R&D intensity. Table 2.4 Breakdown of manufacturing sectors according to market structure characteristics in Russia Average R&D intensityb a Average PCM Average size (%) Fragmented 0.46 High differentiated 0.50 Chemicals 0.38 Plastics and rubber 0.52 53.5 1.8 Fabricated metal products 0.48 60.7 1.9 Low differentiated 0.40 Textiles 0.46 22.0 0.5 Garments 0.35 70.3 0.5 Segmented 0.48 High differentiated 0.49 Machinery and equipment 0.44 151.2 3.4 Electronics 0.59 226.2 1.5 Low differentiated 0.48 Other manufacturing 0.48 134.9 0.3 Food 0.42 139.4 0.5 Nonmetallic mineral products 0.50 231.8 0.5 Basic metals 0.49 1,072.9 0.4 a. Average size for manufacturing industry was estimated as 131.9 full-time employees. b. Average R&D intensity for manufacturing industry was estimated as 1.11%. 2.21. While providing a simplifying device, table 2.4 also provides some explanation for the observed PCM. There is evidence that PCM levels in the country are substantially lower for fragmented sectors, when compared with segmented industries, which suggests that product market competition tends to be higher for the former group of sectors than among the remaining manufacturing sectors in the country. 2.22. When considering fragmented and segmented sectors, the distinction between low- and high-differentiated sectors also appears to contribute somewhat to the explanation of observed PCM levels. First, as expected, fragmented low-differentiated sectors have the lowest average mark-ups, which confirm that these industries may indeed have the least potential to exercise market power. Second, the fact that mark-ups are higher in fragmented high-differentiated industries might partly be taken as a sign of innovation rents. Data also show that PCM levels are higher in segmented industries partly because of the performance of segmented high-differentiated sectors (especially the electronics sector), where the market structure is expected to have many oligopolistic features. 2.23. The analysis of market structure in Russia at the geographic and product market level also reveals high concentration. Figure 2.8 illustrates that, at the regional level, the number of firms with large market shares varies significantly by geographic market, which is confirmed by the level of concentration in selected product markets (figure 2.9). 89 Figure 2.8 Number of dominant firms in regional markets Nizhni Kaliningrad Samara Volgograd Ivanovo Kursk Primorsky Ryazan Khabarovsk Penza Bashkortostan Astrakhan Leningrad Perm Stavropol Yamalo Murmansk Tver Mordovia Rostov Pskov Khanty MoscowRegion Yaroslavl Orenburg Smolensk Tula Sakhalin Kirov Magadan Tatarstan Vladimir Krasnoyarsk Altai Kostroma Udmurt Ossetia Belgorod Tyumen Tomsk Sverdlovsk Chelyabinsk Voronezh Karelia Kamchatka Novgorod MariEl Bryansk Omsk Arkhangelsk Orel Novosibirsk Amur Irkutsk Chuvash Saratov Komi Adygea Kaluga Karachay Khakassia Kemerovo Lipetsk Sakha Vologda Kabardino Tambov StPetersburg Buryat AltaiRep Kurgan Ulyanovsk Chukotka MoscowCity JAR Dagestan Nenets TransBaikal Krasnodar Kalmykia Tuva Ingushetia 0 100 200 300 400 500 600 700 Source: Federal Antimonopoly Service (FAS). 90 Figure 2.9 Concentration levels in selected Russian product markets, Herfindahl-Hirschman Index Vitamin preparations ChildrenCannedFruit Sulfur Tea Highlyconcentrated>2500 Potashfertilizers Validol Gascombustible  natural Diesel Newsprint Cars Trucks Tyresfor trucks,busesand trolleybuses Electric motors Buses Synthetic detergents Moderatelyconcentrated Printingpaper Coal 1500 Ͳ2500 Phosphate fertilizers05) Hydrochloric acid Mainline freight Toiletsoap CastironandblastͲfurnace  ferroalloys Vegetable Oils Ironore  Ferrousmetal alloys Unconcentrated<1500 Roofingmaterial DrugsCardiovascular Milksweetenedcondensed Antibiotics Cannedfish natural Analgesic,antipyretic  andantiͲinflammatory drugs Wines Cannedmeat 0 2000 4000 6000 8000 10000 HHI Source: Federal Antimonopoly Service. 91 2.24. The concentration level in Russia also varies by regions and sectors. Figure 2.10 shows that the share of firms with larger market shares varies significantly by region. For instance, the textiles and electronics sectors present high concentration in many Russian regions, whereas businesses in the plastics and rubber sector is, at the most, moderately concentrated in the regions examined. Figure 2.10 Concentration levels in selected Russian industries, by region – Herfindahl-Hirschman Index Textiles Electronics Karelia Irkutskoblast Tomskoblast Tatarstan Irkutskoblast Highly Highly concentrated: Tveroblast Tatarstan concentrated: Voronezhoblast 1,500Ͳ2,500 Tomskoblast 1,500Ͳ2,500 Rostovoblast PermKrai Moderatelyconcentrated: PermKrai 1,500Ͳ2,500 Voronezhoblast Moderatelyconcentrated: Tveroblast Rostovoblast 1,500Ͳ2,500 SaintͲPetersburg Unconcentrated:<1,500 SaintͲPetersburg Moscow Unconcentrated:<1,500 Moscow 0 2,000 4,000 6,000 8,000 10,000 0 2,000 4,000 6,000 8,000 10,000 Plasticandrubber Karelia Tatarstan Moderatelyconcentrated: 1,500Ͳ2,500 Rostovoblast Voronezhoblast Tveroblast Tomskoblast Irkutskoblast PermKrai Unconcentrated:<1,500 SaintͲPetersburg Moscow 0 2,000 4,000 6,000 8,000 10,000 Source: SPARK Database. State Control and Government Participation 2.25. State ownership in Russia appears to be twice as large as in the EU-10 countries, and state- owned enterprises (SOEs) account for about 17 percent of employment. These companies usually occupy dominant market positions in their areas of activity, with scope for private participation – including by foreign investors – tightly controlled. (The share of foreign participation in the average Russian company was 2.7 percent in 2007 compared with 7.5 percent in the EU-10 countries.) Tariffs have progressively replaced nontariff barriers as the principal instrument for regulating foreign trade, but average tariff rates and tariff dispersion were still higher in Russia than in all OECD countries in the mid- 2000s, providing some degree of isolation from international competition. 2.26. National, state, or provincial government controls at least one firm in 16 economic sectors. This figure is relatively high compared with the typical OECD economy which registers government participation in only nine of the same sectors (table 2.5). 92 Table 2.5 Presence of SOEs National, state, or provincial government controls at least one firm Yes No Manufacture of refined petroleum products X Manufacture of basic metals X Manufacture of fabricated metal products, machinery and equipment X Electricity generation/import, electricity transmission, electricity distribution, electricity supply X Gas generation/import, gas transmission, gas distribution, gas supply X Wholesale trade including motor vehicles X Restaurants and hotels X Railway passenger transport, transport via railways, freight transport, operation of transport X Other urban, suburban, and interurban passenger transport X Freight transport by road X Operation of road infrastructure X Water transport X Air transport X Operation of air transport infrastructure X Telecommunications fixed line service, fixed line services X Water transport operation of water transport infrastructure X Financial institutions (not central banks) X Insurance X Motion picture distribution and projection X Total 16 3 Source: OECD 2008. 2.27. State ownership is pronounced in infrastructure/network industries. The government has 100 percent market share in rail transport and postal services and more than 50 percent in gas, electricity, air transport, and telecommunications (table 2.6). Table 2.6 Government participation in selected sectors Sector Market share No public Less than Equal to or more than 100% ownership 50% 50%, and less than 100% Gas industry Production/import sector X Gas transmission X Gas distribution X Electricity industry X Generation of electricity X Transmission of electricity X Distribution X Supply segments X Rail transport Operation of infrastructure X Operation of passenger transport X Air transport Domestic and international traffic combined X Telecommunication X Postal services X Source: OECD 2008. 2.28. Even though privatization of state-run companies is on the government’s agenda, the state still controls the largest producers in many key sectors. The state’s shareholding is above 85 percent in key sectors for economic growth such as oil, banking, rail, and electricity): oil production (Rosneft), the 93 pipeline monopoly (Transneft); leading banks Sberbank and Vneshtorgbank (VTB); and the rail and shipping giants Russian Railways (RZD) and Sovkomflot (figure 2.11). Figure 2.11 State participation in selected industries (% of shareholding) 100 90 stateshareholding(%) 80 70 60 50 100 100 100 100 100 40 79.11 75.16 75.5 30 58 57.6 20 10 0 Sivkomflot Rosneft Rosselkhozbank RusHydro Transneft Sberbank RussianRailways HousingMort.CreditAg. FederalFridCompany Vneshtorgbank Railways Shipping Mortgage Electricity(transmission Oil(transitandproduction) Banking lending andpowegeneration) Source: Company web pages and www.vedomosti.ru (accessed June 2011). 2.29. The government’s dominance in these industries is likely to continue given the barriers to trade and investment. There are statutory or other legal limits on the number or proportion of shares that can be acquired by foreign investors in the electricity and gas generation, transmission, distribution, and supply sectors; railways, air, and water transport; and railways, air, and water infrastructure operation. Government Actions Limiting Competition Regionally State Aid and Preferences 2.30. The Law on Protection of Competition states that state preferences can be granted on the basis of the legal acts of the federal executive bodies, authorities of the constituent territories of the Russian Federation, municipal authorities, and other agencies exclusively for the following purposes: 1. Securing vital activities of the population residing in areas of the extreme north and other regions with similar conditions. 2. Advancing education and science. 3. Research. 4. Protecting the environment. 5. Preserving, using, and protecting the cultural heritage of the Russian Federation. 6. Developing art and culture and preserving cultural values. 7. Developing sports. 8. Ensuring national defense and state security. 9. Supporting agriculture. 10. Providing social security. 11. Protecting labor. 94 12. Protecting citizens’ health. 13. Supporting small and medium businesses. 14. Other purposes determined by other federal laws, normative legal acts of the President of the Russian Federation, and normative legal acts of the government of the Russian Federation. 2.31. The Law on Protection of Competition specifically uses the term “state or municipal preferencesâ€? and not “state or municipal aidâ€? to ensure that provision of property advantages is considered as granting of state or municipal preferences (for example, tax, property, or rent relief).81 2.32. Previous analyses indicate that incumbent firms received preferential treatment from federal and regional governmental authorities in various forms including tax breaks, investment credits, direct subsidies, guaranteed loans, access to state property, and the creation of special economic zones on the sites of specific enterprises (box 2.1).82 Regional authorities still grant special tax or credit preferences to build local business champions. According to Bakatina and others (2009), “in nine out of the ten selected sectors, the non-level playing field is the key explanation for the lack of restructuring of the old assets and/or investments by best practice companies.â€? Box 2.1 State aid in the news 1. The Wall Street Journal reported in November 2008 that the Russian government has announced its willingness to keep using its reserves, the third largest in the world at the time, to boost liquidity and bail out troubled industries. The government pledged US$200 billion in loans, tax cuts, and other measures. 2. In February 2009, United Company Rusal, an aluminum business, requested state aid in the form of a convertible bond from Vneshekonombank to refinance billions of dollars of debt. 3. In May 2009, Russia’s leading petrochemical holding company, Sibur, received approval for a loan from Vneshekonombank to finance a major polypropylene project. Sibur reportedly requested approximately US$2.1 billion to finance a polypropylene plant in Tobolsk and a PVC plant in Nizhny Novgorod region. 4. In November 2009, the government announced a state plan for the Russian Corporation of Nanotechnologies. The plan allocated the following amounts for investment projects: 2010 (€1.2 billion), 2011 (€1.42 billion), 2012 (€1.52 billion), 2013 (€0.73 billion), 2014 (€0.4 billion), and 2015 (€0.24 billion). Source: Various newswire reports. 2.33. An analysis of state aid and preferences data indicates that the use of aid by regional authorities varies widely across Russian regions. Regions with similar levels of wealth exhibit a dissimilar number of state aid applications (figure 2.12). In practice, even though Russia’s competition law framework is extensive to state and municipal aid – a regulating advantage that is given under more favorable conditions in comparison with the other market participants – its enforcement is partial compared with the EU. In particular, the scope and the purpose of the state aid regulation as well as the criteria for identifying state aid could be improved. The Russian legal framework does not seem to 81 State or municipal preference is defined as the provision by a state or municipal body or by a body or organization exercising its functions of advantages to specific economic entities which provides them with better conditions for their activity by means of the transfer of state or municipal property or objects of civil-law rights or by means of the provision of privileges having a property or monetary value. 82 Desai and Goldberg 2008. 95 explicitly include all the types of state aid instruments (grants, tax exemptions, capital injections). Likewise, the notification procedure and enforcement mechanism need to guarantee that a balancing test that analyzes the impact of state aid on market competition is a key criteria for granting state aid. It must also adopt the primary principle that aid must be necessary and proportionate to achieve objectives of common interest. In addition, there is no centralized inventory of state aid by regional and local authorities or an assessment on whether the state aid granted has distorted competition in local markets. Figure 2.12 State aid applications and GRP per capita by region, 2009 Source: Federal Antimonopoly Service; ROSSTAT. 2.34. In practical terms, the granting of state aid and preferences is region specific. From the 29 regions with data, only four regions register a large number of accepted state aid applications relative to the total number of applications notified to the Federal Antimonopoly Service (FAS; above 50 percent) while 15 regions have rejection rates above 80 percent (figure 2.13). 96 Figure 2.13 State aid applications by region, 2009 Murmansk Yaroslavl Kemerov cityofMoscow Ulianovsk KhantyͲMansiisk Sverdlovsk Mordovia NorthOssetiaͲAlania Karelia Tatarstan Irkutsk Khabarovsk YamaloͲNenetsk Stavropol Rejected Voronezh Acepted Tver Kaluga Tomsk Moscow Volgograd Samara Kaliningrad Sakha(Yakutia) Rostov Omsk Penza Perm St.Petersburg 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Source: Federal Antimonopoly Service. 2.35. Data on applications granted to state aid for property transfers show a wide variation among regions (figure 2.14).83 In Tyumen, only 9 of 55 applications were approved unconditionally; in Chelyabinsk, all 41 state aid applications were approved without conditions. In Tula, all nine approved applications were subject to conditions, while in Bashkortostan only 1 of 55 applications was approved, albeit without conditions. 2.36. Similarly, tax arrears vary widely by region. Of 83 regions, 68 had tax arrears of 30 percent or more (figures 2.15 and 2.16). For instance, tax arrears in Tomsk or Tatarstan are only about 20 percent of what is seen in Stavropol, Mordovia, or Kemerovo oblast. 83 Property transfers include state transfer of buildings, land, equipment, cash, and other assets. 97 Figure 2.14 Number of property state aid applications approved, 2009 60 50 Approved ConditionalApproval 40 30 20 10 0 Source: Federal Antimonopoly Service. Figure 2.15 Distribution of tax arrears by Figure 2.16 Tax arrears in selected regions as a region as a share of tax revenues (%) share of tax revenues, 2010 (%) 35 NorthCaucasian StavropolKrai District 30 RepublicofMordovia UlyanovskOblast PenzaOblast 25 SamaraOblast Numberofregions PermKrai VolgaDistrict 20 RepublicofTatarstan KemerovoOblast 15 NovosibirskOblast 29 IrkutskOblast OmskOblast 10 TomskOblast SiberianDistrict 15 VoronezhOblast 5 10 MoscowOblast 7 6 6 TverOblast 5 5 YaroslavlOblast 0 CentralDistrict Moscow 10% 20% 30% 40% 50% 60% 70% More KalugaOblast MurmanskOblast RepublicofKarelia KaliningradOblast NorthWestern SaintPetersburg District LeningradOblast RostovOblast VolgogradOblast SouthDistrict KhabarovskKrai SakhaRepublic FarEast District SverdlovskOblast YamaloͲNenetsAutonomous… UralDistrict KhantyͲMansiAutonomousOkrug 0% 20% 40% 60% 80% 100% Source: Federal Tax Services. 2.37. Recent research sheds some light in understanding the decisions behind the state aid granted, based on a survey conducted with firms that have received state aid.84 Termed “insiders,â€? these are companies that have already entered the regional markets and have developed relations with 84 Kuznetsov and others 2010. 98 authorities. The survey indicated that in 2007–08, regional authorities were the most active providers of state support: 26 percent of the firms surveyed received support from the regional government, 19 percent received administrative support,85 and 14 percent financial support. The survey also showed that regional and local levels provided administrative support more frequently, while the federal level focused on financial support. 2.38. Various factors determined government support. The survey classified these factors in three groups. Structural features include the enterprise’s sector, size, years of existence, owners, and the investment potential of the host region. Social responsibility indicators include the employment- generating ability of the enterprise and its participation in business associations. Membership in business associations was deemed important because they provide the communication channel between the government and the private sector. Modernization performance indicators include export performance, major investments made in 2005–08, and innovations. 2.39. Government support is more often provided to firms in regions with low to medium investment potential and to old firms dating back to the Soviet regime. In addition, government support at the federal level may be different from the other levels where government-owned firms can obtain preferential benefits only at the federal level. Federal support focuses on firms that preserve jobs. An enterprise’s participation in business associations is a significant factor for getting regional and local government support. Finally, modernization indicators are important at the regional and municipal, but not federal, levels. 2.40. Such nonuniform interpretation of state aid rules across regions could distort the market. Granting state aid based on a firm’s participation in business associations and ties to the Soviet era does little to encourage new entrants, and rewards inefficient incumbents. 2.41. The presence of state or municipality-owned corporations endowed with some preferential treatment (such as exclusive rights or exemptions that disadvantage private firms, as well as state functions) is an important challenge. The FAS has proposed that these effects could be alleviated by some measures such as increasing competition oversight, stripping such corporations of their state functions, an equal competition environment, and privatization. Anticompetitive Actions of Governments 2.42. Actions of government bodies at the regional level also influence competition in domestic markets. More than 50 percent of anticompetitive practices were conducted by government bodies, including participation in horizontal and cartel agreements (according to 2009 data). The relative importance of anticompetitive government actions varies greatly among regions, from 90 percent in Irkutsk to 10 percent in Tyva (figure 2.17). Typical anticompetitive actions include imposing bans or restrictions on the free movement of goods or preventing firms from exercising specific economic activities (box 2.2).86 85 Administrative support was interpreted as anything other than financial support, including assistance in developing contacts with Russian/foreign partners and other government authorities, and in attracting investors. 86 The Russian competition authority may file suits against statutory legal acts or nonnormative acts of public authorities such as federal executive authorities in case they contradict the competition act with the possibility for partial or total invalidity of the relevant act. 99 Box 2.2 Reasons for rejection of state aid applications There are varying reasons why state aid applications were rejected. A few examples are as follows: x In September 2010, an entrepreneur in the Republic of Udmurtia was denied preference in leasing a state property. The Federal Antimonopoly Service (FAS) ruled that the Law on Protection of Competition does not provide for state preference to be granted to individuals for temporary use of state-owned property. x In March 2011, the FAS office in Penza rejected the application for municipal preference of Trud LLC for lack of documents. x The Federal Department for Execution of Punishment requested government-support measures, including tax exemption of RUB8 million a year. This request was denied as it was deemed a violation of the Competition Law. Source: FAS. Figure 2.17 Competition cases 2009 – anticompetitive actions of government vs. anticompetitive practices 100% 90% 80% 70% 60% Government actionsͲ averageRF:51% 50% 40% 30% 20% 10% 0% Totalcases:ActionsGov TotalCases:AbuseandPrivateAgreements Note: Private cases include cases initiated under articles 10 and 11. Government cases include cases initiated under articles 15 and 16. Source: Federal Antimonopoly Service. 2.43. In the case of procurement and tender processes, the FAS found that 60 percent of violations in 2008–09 were at regional and municipal levels (figure 2.18). 87 The Competition 87 Article 17. Antimonopoly Requirements to Tenders 1. The actions that lead can lead to prevention, restriction or elimination of competition in the course of tender are prohibited, including: 1) coordination of activities of the participants of tenders by the tenders’ organizers or customers; 2) creation of preferential conditions for participation in the tender to one or several participants, including by means of access to information, unless otherwise is determined by the Federal Law; 3) violation of the order of procedure of estimation of a winner or winners of the tender; 4) participation in the tender of the tender’s organizers or of the tender’s customers and (or) employees of the tender’s organizers or employees of the tender’s customers. 2. Alongside with the established by part 1 of the present article prohibitions concerning tenders’ procedure, if the tender’s organizers or the 100 Framework on Tenders prohibits any action that can lead to prevention, restriction, or elimination of competition during the tendering process. In 2009, the FAS received more than 15,000 complaints for alleged anticompetitive procurement conditions at regional and municipal levels. In more than 10,000 cases, evidence suggested that procurement rules were violated. Figure 2.18 Procurement complaints and violations, Figure 2.19 Violations by type, 2008–09 2008–09 30,000 27,464 25,000 Requirementsfor  participantsor the  19,233 applicationare  20,000 against the law 15,638 22% 14,337 14,017 15,000 11,826 Others 10,782 45% 10,000 9,172 8,683 8,451 5,165 5,334 5,000 Unfoundedrefusal toallow the  participant 0 24% Complaints received Violations detected Complaints received Violations detected Unreasonable  admission ofthe  2008 2009 participant: 9% Federal Regional+ Municipal Total Source: Federal Antimonopoly Service. Source: Federal Antimonopoly Service. 2.44. Anticompetitive practices in tendering processes have been targeted to foreclosure of new entrants and participants to the biddings. In fact, typical violations may substantially reduce competition in local biddings. For instance, in 24 percent of the cases in 2008–09 bidders were prevented from taking part in public procurement without justification while in 22 percent of the cases the bidding requirements for participants did not follow the legal framework (figure 2.19). In addition, municipal and regional authorities have adopted different approaches for using single source procurement bids and practices, which may facilitate collusion, even though a federal legal framework has been established (a factor that normally has an important effect in the construction sector). Mechanisms that have been used in other jurisdictions to reduce possibilities of collusion, such as Certificates of Independent Bid Determination, have been discussed to deter collusive behavior, but have not been implemented as they would require changes in the procurement law (box 2.3). It is expected that the launch of electronic bids will increase competition in this area. tender’s customers are federal bodies of executive authority, executive authorities of the subjects of the Russian Federation, bodies of local self- government, public off-budget funds, as well as during tenders’ procedure on placement of orders for goods, works and services for state and municipal needs it is forbidden to restrict access to participation in tenders which is not provided for by the federal laws or other statutory legal acts. 3. Alongside with the established by part 1 and 2 of the present article prohibitions concerning tenders’ procedure on placement of orders for goods, works and services for state and municipal needs, it is forbidden to restrict competition by means of including in the tenders’ lots structure of production (goods, works, services) which technologically and functionally are not connected with goods, works, services which provision, execution, rendering are the subject of the tender. 4. Violation of the rules established by the present article is a ground for the court to admit invalid the relevant tender and the transactions concluded in the result of such tender, including at the suit of the antimonopoly authority. 101 Box 2.3 Procurement and competition policy in Brazil The Brazilian Competition Policy System (BCPS) focuses strategically on tackling cartels, including bid-rigging cases, instead of merger reviews. In this way, it has increased the number of investigations and leniency applications, limiting the prevalence of horizontal anticompetitive practices. One essential characteristic of the Brazilian framework is the common approach that both procurement and competition policy have to safeguard competition in bidding process. Procurement rules consider collusion acts in the bidding process as felonies. But the Brazilian Competition Law expressly typifies price-fixing and negotiation of advantages in public or administrative bidding procedures as anticompetitive behavior. The implementation of this legal framework requires an effective institutional setup. The Secretariat of Economic Law of the Ministry of Justice (SDE), part of the BCPS, focuses primarily on cartels, conducts investigations, and receives denouncements of anticompetitive behavior in the public procurement process. SDE established a team focusing on bid rigging, set up an information technology forensic unit to analyze information collected in raids and by other means, and established cooperation links with the General Federal Government Controller (the body in charge of internal government controls) to facilitate investigations. In addition, some coordination agreements were signed with other public institutions (the Brazilian Federal Court of Auditors and the Public Expense Observatory that deals with fraud and corruption in government) and companies (the water utility in Sao Paulo) to help detect bid rigging. Regional offices in charge of fighting collusion in procurement are also part of the strategy. The advocacy component of the Brazilian strategy was key to its effectiveness. It includes involving BCPS bodies during the design of the procurement process as well as general information dissemination. Advocacy during the procurement process was especially relevant for granting public service concessions, to avoid restrictive eligibility rules that generate entry barriers or contract characteristics that discourage participation of smaller players. Recommending a design of auctions that makes collusion harder was also part of BCPS’s work. The other component of the advocacy work is raising awareness among procurement officers, businesspeople, and the general public. For that, several manuals and materials were prepared for procurement officials, training sessions were held, and “Guidelines for the Analysis of Complaints Involving Public Procurementâ€? were published by SDE. Raising awareness among the business community about the consequences of collusion was also important to prevent anticompetitive actions. Participation in leniency programs increased, given the perceptions of the potential liability for criminal sanctions, the potential for large fines, and the possibility of been prohibited from taking part in future public procurement processes. Advocacy actions were complemented by other mechanisms, such as online reporting of suspicious behavior by procurement agents who use ComprasNet, and the requirement of the Brazilian Ministry of Planning to present a Certificate of Independent Bid Determination, stating that bidders have not engaged in bid rigging. The introduction of the government’s e-procurement system and reverse auction for public procurement may also have supported competition in public procurement. Source: Submission by Brazil to Working Party No. 3 of the Competition Committee, OECD, 2007; Competition Law and Policy in Brazil, OECD/IADB, 2010.. Characteristics of Competition and Regulatory Conditions in Selected Russian Sectors 2.45. Competition in domestic markets also affects international competitiveness through interaction among vertical and complementary markets. Firms usually acquire many of their inputs (transport, financial services, energy, telecommunications services, and construction services) in local markets. If these upstream markets lack competition, goods and services necessary for production are not 102 provided at competitive prices. As a result, firms may be less competitive than their foreign rivals and less likely to compete globally. This section reviews the status of competition in three key economic sectors – transport, banking, and construction. Transport Figure 2.20 Number of transport segments with SOEs 2.46. SOEs have a substantial 12 market share in transport. A 10 9 government entity controls at least one 8 Mean=7 firm in the operation of all transport 6 infrastructure; air and rail passenger 4 transport services; and air, rail, and road cargo transport services. The only 2 services with no SOEs are maritime 0 passenger and cargo services and road passenger services. Such government ownership is higher internationally Note: The 12 transport services are air, rail, road, and maritime infrastructure (figure 2.20). operations; air, rail, road, and maritime passenger services; and air, rail, road, and maritime cargo services. 2.47. The share of SOEs in air Source: World Bank–ICN Survey on Competition in the Transport Sector (2011). transport services is less than half. Still, government influence is extensive. For example, all prices – including domestic and international fares, cargo fees, access charges to infrastructure, and fees in complementary markets (warehousing, cargo handling) – are subject to government control. Such pervasiveness is notable when compared with other countries with similar levels of state ownership (table 2.7). Table 2.7 Price controls in air transport, 2011 Russia Turkey Chile Market structure National, state or provincial government controls at least one firm in Operation of transport infrastructure Yes Yes No Cargo transport services Yes Yes No Passenger transport services Yes Yes No Market share of SOEs in domestic routes >50% No No No Market share of SOEs in international routes >50% No No No Price controls Prices of domestic fares are in some way regulated (minimum prices, max prices) Yes No Yes Prices of international fares are in some way regulated (minimum prices, maximum Yes No No prices) Prices of cargo transport services are in some way regulated Yes No Yes The government provides pricing guidelines to cargo transport companies Yes No No Prices of infrastructure use are in some way regulated (such as airport usage fees for Yes No Yes passengers) Prices of complementary markets (ground handling services, warehousing, cargo Yes Yes Yes handling) are in some way regulated Access charges to infrastructure are regulated Yes Yes Yes Source: World Bank–ICN Survey on Competition in the Transport Sector (2011). 2.48. Government regulations in air transport are also more onerous than in other countries. In particular, the process of obtaining authorization for new routes is burdensome, airlines may lose the right 103 to service a route if it is not operational for a determined period of time, and companies are subject to “common carriageâ€? (table 2.8). Table 2.8 Regulation in air transport, 2011 Russia Turkey Chile Companies operating the infrastructure or providing passenger or cargo transport services are subject to universal service requirements (such as obligation to serve Yes No Yes certain areas or customers) Companies providing cargo transport services are subject to common carriage (such as Yes No Yes cannot refuse to transport goods for anyone) Regulations limit expansion of transport services to new routes (such as burdensome Yes No No process to obtain required authorization per new route) Airlines lose the right to provide the service in a route if not operational for a Yes No Yes determined period of time Source: World Bank–ICN Survey on Competition in the Transport Sector (2011). 2.49. Anticompetitive behavior in air transport is seen. SOEs Box 2.4 Rail transport anticompetition cases have been sanctioned for refusal to deal with rivals and a market Excessive pricing player was sanctioned for excessive pricing. In 2004, the Federal Antimonopoly Service 2.50. The government dominates rail transport especially. (FAS) regional office in Arkhangelsk instituted legal proceedings against RZD. The FAS RZD, an SOE, has a market share greater than 50 percent for both asserted that from January 1 to July 1, 2004, domestic and international routes. RZD and its subsidiaries RZD’s fees exceeded the prices set by the maintain a monopoly in potentially competitive markets such as government for importing and loading cargoes. depot and repair of freight cars, terminal handling of containers, The FAS ordered RZD to transfer illegal revenues amounting to $14,000 to the federal specialized repair, and refrigerated and insulated rolling stock. This government. structure has led to some concerns. First, the media have reported State actions public complaints about transport prices, and the government has recognized capacity constraints. Second, charges of anticompetitive State ownership of the rail transport system has behavior have been successfully raised against RZD, which has resulted in state actions that discriminated against private businesses in complementary been sanctioned for refusal to deal with a rival and for excessive services. For example, in 2004, the Ministry of pricing (box 2.4). Railways required directors of railroads and head of stations to provide space on an 2.51. Government control over maritime transport services is uncompensated basis to the state enterprise still considerable. This is despite the fact that it has an ownership RailPharmacy. Lease agreements with other stake only in maritime infrastructure operation and none in competing companies that operate pharmacies and pharmacy kiosks on rail stations were passenger or cargo services. And it is because of the vertical cancelled and their space given to integration of infrastructure and primary cargo providers with RailPharmacy. Subsequent investigations ruled complementary services. Moreover, all prices – including passenger that this action by the ministry was a state action and cargo fares and prices of complementary markets – are that improperly advantaged another state-owned enterprise and was therefore a violation of the controlled by the government. This level of price regulation Competition Law. contrasts with Turkey and Chile, which impose only few price Source: FAS Report on Competition Policy and OECD controls on their maritime transport services (table 2.9). Peer Review of Competition Law and Policy in Russia (2005). 104 Table 2.9 Price controls in maritime transport services, 2011 Russia Turkey Chile Market structure National, state or provincial government controls at least one firm in: Operation of transport infrastructure Yes Yes No Cargo transport services No No No Passenger transport services No Yes No Market share of SOEs in domestic routes >50% No No No Market share of SOEs in international routes >50% No No No Price controls Prices of domestic fares are in some way regulated (minimum prices, maximum prices) Yes No No Prices of international fares are in some way regulated (minimum prices, max prices) Yes No No Prices of cargo transport services are in some way regulated Yes No No The government provides pricing guidelines to cargo transport companies Yes No No Source: World Bank–ICN Survey on Competition in the Transport Sector (2011). 2.52. The monopoly power of the SOE in port operations has led to anticompetitive behavior, particularly refusal to deal with rivals. The confluence of monopoly power of SOEs, restrictions on foreign ownership, and absence of intra- or interport competition has technically closed the sector to new entrants. Due to the absence of private investors, it is unsurprising that the maritime transport sector reports capacity constraints. 2.53. Government participation in road transport is limited. Except for prices of infrastructure use, all other prices are free from government control. However, self-regulation imposed by professional bodies or representatives of trade and commercial interests specify and enforce pricing guidelines, scheduling of services, and entry regulations. Such transfer of regulation can potentially restrict competition (for example, price fixing or entry deterrence) and is not necessarily optimal or warranted. Turkey and Chile have somewhat similar levels of state ownership, yet private organizations do not regulate prices or transport service schedules (table 2.10). Table 2.10 Regulations in road transport, 2011 Russia Turkey Chile Market structure National, state or provincial government controls at least one firm in Operation of transport infrastructure Yes Yes Yes Cargo transport services Yes Yes No Passenger transport services No No No Market share of SOEs in domestic routes >50% No No No Market share of SOEs in international routes >50% No No No Regulations Business organizations, professional bodies or representatives of trade and commercial interests are involved in specifying or enforcing pricing guidelines or Yes No No regulations Business organizations intervene in the scheduling of transport services Yes No No Source: World Bank–ICN Survey on Competition in the Transport Sector (2011). 2.54. Previous reports suggest that similar self-regulation is prevalent in other markets (box 2.5). Hence it is important to eliminate such practices among business associations and professions that have the effect of restricting entry or facilitating price coordination among members. Unduly restrictive 105 membership rules, exchange of detailed and sensitive commercial information, exclusive or closed industry standards, marketing restrictions, and “ethicalâ€? codes regulating prices might limit members’ ability to compete freely and deter the entry of newcomers. Box 2.5 Restrictions of professional associations Notarial chambers work with the Ministry of Justice and regional departments of justice in defining the number of notary positions that will be formed in each notarial district, both state employed and privately practicing notaries. Persons are assigned to fill these positions as they become free, on the basis of a recommendation of the notarial chamber. Candidates for the receipt of a position as a notary must complete a one year “stageâ€? with a practicing notary and possess a license after passing a qualifying examination. The number of available stages and the procedure and content of the examination are also determined jointly by the Ministry of Justice and notarial chambers. A candidate for a position as a private notary must be a member of notarial chamber. The law treats notarial services as a special, quasi-judicial category of activity – restricting the other earnings of notaries to fees from publishing and teaching activities (the same restrictions apply to judges) and specifically stating that notarial service is not considered entrepreneurial activity. However, private notaries are free to set their fees on the many notarial services that are not state mandated (on legally required notarizations, all notaries are required to charge the fees set by the state) and their earnings are their own. While it is clear that the system of notarial districts is a direct restriction on entry and notarial fees are reported high, the legal definition of notarial activity as “not entrepreneurial activityâ€? means that the Competition Law does not apply. Source: OECD 2005. 2.55. Beyond self-regulation, road transport services are subject to additional competition constraints. Trucks and new vehicles face high import duties that discourage entry, and regional and municipal authorities often provide preferential treatment to municipally owned enterprises, particularly in passenger services. Banking 2.56. State ownership and control are not limited to the infrastructure sector. The government also has substantial ownership of firms in banking. Kalyuzhnova and Nygaaard (2011) note that of the 10 largest banks in Russia, 6 are state owned (table 2.11). They also note that the share of assets of foreign- owned banks in the Russian banking sector is much smaller than that in neighboring countries (figure 2.21). 106 Table 2.11 Bank assets and ownership of the 10 largest banks in Russia, 2008 Percentage of Bank banking assets Ownership Sberbank 23.7 State VTB 8.0 State Gazprombank 4.7 State Rosselhozbank 2.9 State Bank of Moscow 2.8 State Alfa Bank 2.5 Private domestic UniCredit Bank 2.1 Private foreign Raiffeisenbank 2.1 Private foreign VTB-24 2.0 State Rosbank 1.7 Foreign Source: Kalyuzhnova and Nygaard 2011. Figure 2.21 Share of assets of foreign-owned banks 60 50.9 51.1 47.1 50 40 Percent 30 18.7 17.2 20 7.4 10 0 2003 2007 2008 Russia FSU,Average Note: Former Soviet Union average is the unweighted average of Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, the Kyrgyz Republic, Latvia, Lithuania, Moldova, and Russia. Source: Kalyuzhnova and Nygaard (2011), citing data from EBRD. 2.57. The government plays an active role in the market through two channels –the state-owned commercial banks and the state investment vehicle, Vneshecombank (VEB). VEB, the government’s crisis management vehicle in 2008, was instrumental in refinancing Russian corporations’ debt to foreign banks, providing subordinate loans to 17 banks, supporting the Russian stock market, and extending state guarantees to banks that lend to “priority enterprises.â€?88 More recently, VEB has become the Russian government’s arm for its “social and economic development initiatives.â€? Its credit activities are directed by the Russian government – two thirds of VEB’s financial lending in 2007 was directed to state- controlled companies. 2.58. Recent World Bank research resonates with previous findings. Anzoategui and others (2010) find that, while the Russian banking sector has many players (around 1,007 banks), it is fairly concentrated and dominated by state banks. The largest banks control about 70 percent of total bank assets, and six government banks account for 52 percent of total bank assets and 60 percent of deposits. 88 Kalyuzhnova and Nygaard 2011. 107 Detailed measures of concentration – the H-statistic and Lerner index – show that Russian banking operates under monopolistic competition, with an H-statistic of 0.74 and a Lerner index of 0.138 (table 2.12). 2.59. Even though concentration levels in Russia are not much higher than in Brazil, India, or China, contestability is obstructed by differences in supervisory practices across institutions and an unclear and not entirely credible exit process. Due to complex supervisory regulations, the top 20 banks and state-owned banks seem to have more market power than smaller banks and privately owned institutions. Larger banks are deemed able to “get away with thingsâ€? – that is, take excessive risks – that smaller banks cannot. Table 2.12 H-statistics and Lerner indices for BRICs Statistics Russia Brazil India China Panel A: H-statistics H-stat (2002–08) 0.741 0.821 0.683 0.73 [Std error] 0.017 0.052 0.065 0.048 P value for H stat = 0 0.00 0.00 0.00 0.00 P value for H stat = 1 0.00 0.00 0.00 0.00 P value for H stat. Russia=H-stat other vs. H stat 0.05 0.92 0.69 Russia < H stat other P value for H stat. Russia=H-stat other vs. H stat 0.95 0.08 0.31 Russia > H stat other Panel B: Average Lerner indices Lerner (average 2002–08) 0.138 0.054 0.145 0.209 [Std error] 0.01 0.005 0.007 P value for Lerner Russia=Lerner other vs. 1.00 0.09 0.00 Lerner Russia < Lerner other P value for Lerner Russia=Lerner other vs. 0.00 0.91 1.00 Lerner Russia > Lerner other Panel C: Median Lerner indices Lerner (median 2002–08) 0.116 0.069 0.141 0.211 P value for Lerner Russia=Lerner other vs. 1.00 0.00 0.00 Lerner Russia < Lerner other P value for Lerner Russia=Lerner other vs. 0.00 1.00 1.00 Lerner Russia > Lerner other Source: Anzoategui and others 2010. 2.60. The extensive state ownership in banking and the strong market power of SOEs is particularly worrisome given that banking has a cascade effect on the rest of the economy. Availability of credit is crucial for the formation of new firms and the competitiveness of incumbent firms. The following four elements present serious challenges to market competition: the government’s control of domestic credit; provisions that require and encourage explicit recognition of national treatment; rules that provide for exclusion or exemption of certain firms from liability under the general competition law; and barriers to foreign direct investment by restrictions on foreign ownership. Construction 2.61. Construction is an important sector in the Russian economy. In 2009, it accounted for 5 percent of GDP and 8 percent of employment. Bakatina and others (2009) noted that construction and engineering accounted for 46–50 percent of investment in Russia during 2000–2007, and grew faster than the overall economy during 1998–2007, posting a compound annual growth rate of 9 percent (as against 7 percent of the aggregate economy). Construction also registered the highest growth in the number of business entities from 2008 to 2009 (figure 2.22). 108 Figure 2.22 Change in number of business entities in sectors in Russia, 2008 to 2009 (%) 160 118.3 120 110.7 109.3 98.8 99.5 101.2 102.0 103.2 99.4 99.6 98.0 95.3 80 40 0 Source: Federal Antimonopoly Service 2010. 2.62. Despite the decade-long growth in construction, the sector has not yet peaked and growth potential remains high for three reasons. First, the government has set ambitious targets for residential construction. 89 Before the global crisis, the government had stated a target of increasing per capita housing stock from 21 square meters to 33 square meters by 2020. Second, there is room for productivity gains, as construction in Russia is only about 21 percent of that in the United States and around a third of Sweden’s. Third, some factors restrict the activities of construction companies, and tackling them could boost growth in the sector (table 2.13). Table 2.13 Factors restricting business activities of construction companies (% of respondents) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 High level of taxation 81 73 67 64 60 45 45 42 43 40 Insolvency of customer 81 65 62 55 48 38 32 27 24 43 High prices for materials, structures and articles 53 45 50 47 45 36 37 42 46 32 Lack of orders 29 30 35 33 27 18 15 12 11 27 Competition from other construction firms 16 24 30 33 35 31 35 35 32 29 Lack of skilled workers 14 20 22 23 28 24 25 26 30 16 Lack and depreciation of machines and equipment 19 19 14 14 13 7 6 7 5 3 High interest for commercial credits 14 10 9 11 16 12 14 13 11 18 Note: The columns do not sum to 100 because respondents could choose multiple factors. The percentages indicate the proportion of all respondents who perceive that a given factor restricts business activities. Source: ROSSTAT. 2.63. Competition constraints have been identified in the Russian construction market, in particular related to the lack of a level playing field for incumbents and new entrants. The informal relationship that incumbents keep with regional and local authorities, documented several times, could 89 Bakatina and others 2009. 109 obstruct the entry of new players. The anticompetitive effects of such informal relationships cannot be overestimated given two factors, namely, the process for allocating land for residential construction and the infrastructure connection fees and costs to fulfill utility-connection specifications. 2.64. Despite the abundance of land, demand for housing in Russia is high due to the limited number of plots officially designated for residential housing and to lack of clarity in land-ownership rights and potential use. Also, the presence of weak and overabundant regulation, permeated with informality, creates a skewed competitive environment in which to compete for land plots. There is no unified database of land plots with complete information about ownership and use status or potential restrictions on future use. Competitive intensity in residential construction is low because of the rapid growth of the market and administrative barriers to the expanding supply. These barriers affect current and new players alike, though there is some relationship-based advantage for incumbents. Thus consumers’ choices are limited to the suppliers that gain access to land plots. According to the FAS, in 2010 the Russian government took some measures to promote transparency by creating a website (www.torgi.gov.ru) where future land auctions will be publicly posted and all information disclosed. 2.65. The major sunk costs in the Russian construction sector appear to be the formal and informal fees companies are often required to pay, such as infrastructure connection fees and costs to fulfill utility-connection specifications. Anecdotal evidence suggests that these fees can be astronomical, as there is no real transparency in determining them, which often depends on regional and Box 2.6 Anticompetitive behavior of regional local authorities’ interpretations, allowing ample room for authorities in construction markets corruption. Bakatina and others (2009) cited figures as In the Murmansk Region, the owners of high as US$1,800–US$4,000 per kilowatt of installed properties were about to select property capacity in the Moscow district that developers are asked management firms for apartment buildings and multifamily housing. The selection was to pay, depending on the district. expected to be competitive given that new property management companies had entered 2.66. Construction markets have characteristics the market. However, the competition did not prone to collusive and cartel behavior. Cartel behavior occur as municipal administrators used their has been documented in various sectors in Russia. An powers to influence the selection process. In interview in October 2010 with the Head of the Cartel particular, the administrators conducted meetings with property owners and limited the Department of the FAS, Alexander Kinev, noted that in choices to certain property management firms. 2009, the FAS had initiated 400 cases on collusion and It was also found that the Administration of more than 400 cases of economic agents conspiring with Magnitogorsk had awarded the contract for the authorities. The potential for collusive and cartel construction and property management to behavior exists particularly in construction, given its Magnitogorsk Investstroi, without going poorly regulated public tenders of land plots and the through competitive processes, such as bidding. opaqueness of construction regulation and contract award. Two cases on property management that occurred in 2008 are given in box 2.6. 2.67. Licensing schemes for operation in each segment of the supply chain are cumbersome. This is one of the major obstacles to effective development of the Russian construction industry. It is estimated that it takes 700 days in Russia to obtain construction permits, versus 116 in Sweden, 75 in Canada, and 40 in the United States. Even other developing countries are much more efficient than Russia: India in 224 days, Kazakhstan in 231 days, and China in 336 days. Relative to per capita income, the costs in 110 Russia are huge (figure 2.23). The long and uncertain waits for zoning and construction rights make project cycles longer, translating into supply-chain and financing problems, and further reducing efficiency. This could eventually further undermine competition by ostracizing small and medium businesses that cannot bear the cost without additional financing. Bakatina and others (2009) estimated that inefficient processes and low skills in the Russian construction sector account for half (49 percent) of Russia’s productivity gap with the United States. Poorly protected development rights hold back development of project financing, making it hard for industry players to fund their operations effectively and often causing delays due to unsecured financing. Figure 2.23 Dealing with construction permits 4,500 CostofConstruction(%ofincomepercapita) 4,000 Cost(%ofincomepercapita) Average 3,500 3,000 2,500 2,000 1,500 1,000 500 Ͳ Source: World Bank, Doing Business, 2011 2.68. Quality standards, certification requirements, and phytosanitary rules vary among market participants. Current regulatory standards in Russia often exceed those of the EU, partly stemming from the poorer quality of Russia’s public services. One example is the regulation on fire-resistance for materials. Due to firefighters’ sometimes slow response, Russian standards mandate that metalwork be fire-resistant for up to two hours, compared with one hour in the EU. This drives costs higher for developers and lowers their productivity. Additionally, utility companies often have monopolies in the market and there are no clear rules on infrastructure connections, resulting in astronomically high fees for utility connections. And arbitrary and frequent changes in regulations lead to increased uncertainty and disrupt the business process. Many industry experts have argued that the new law on “self-regulatory organizations in constructionâ€? could disadvantage small and medium developers. Given that regulation often occurs at the local level, a greater degree of arbitrariness and informality may occur. 2.69. Unequal enforcement of laws and regulations between entrants and incumbents for land plot allocations also affects entry in construction. Informal relationships between incumbents and the public sector are often important in securing tenders, and evidence suggests that tenders are not conducted in the most competitive way, and that current regulation of the industry obstructs competition and limits efficiency. 111 2.70. Government procurement procedures for construction have improved over the past few years but there is still room for further enhancement. On July 1, 2010, a new law came into effect, mandating that bidding for federal government contracts for construction should take place through an open electronic auction, instead of the usual “hammerâ€? auction (some exceptions apply). Regional and municipal authorities must follow the law from January 1, 2011. Failure to do so carries a penalty of RUB30,000. Before this law, bidding could be executed via conventional open or electronic auctions. Recently, the central office of FAS Russia (dealing with federal customers) repealed 21 construction- bidding cases for failure to have an electronic auction. As part of the new legislation, clients are required to publish on official websites all construction documents, as they contain comprehensive requirements for the work. According to FAS Russia, this is a simple requirement to meet, because project documentation is originally prepared in electronic format and to collect the individual files and post them on a website is not technically challenging. 2.71. However, the law has a worrisome aspect. It has a provision giving clients the right to require construction firms to have had experience in a similar large project over the previous five years if the initial (maximum) contract price exceeds RUB50 million. The law also states that the cost of such work should not be less than 20 percent of the initial contract price (the price of the lot). This provision is anticompetitive as it could limit those interested to incumbents who have greater experience than new entrants. 112 References Bakatina, Daria, Jean-Pascal Duvieusart, Vitaly Klintsov, Kevin Krogmann, Jaana Remes, Irene Shvakman, and Yermolai Solzhenitsyn. 2009. “Lean Russia: Sustaining Economic Growth through Improved Productivity.â€? McKinsey Global Institute, London. Berkowitz and De Jong (2002). “Integration: An Empirical Assessment of Russia,â€? William Davidson Working Paper Number 488. Conway, Paul, Tatiana Lysenko, and Geoff Barnard. 2009. “Product Market Regulation in Russiaâ€? OECD Economics Department Working Papers 742, Organisation for Economic Co-operation and Development, Paris. Crawford, David. 2009. “Recent Developments in Competition Policy.â€? Presented at the ACT Economic Society, May 3. Desai, Raj M., and Itzhak Goldberg. 2008. Can Russia Compete? Enhancing Productivity and Innovation in a Globalizing World. Washington, DC: Brookings Institution. Gluschenko, Konstantin. 2006. “Russia’s Common Market Takes Shape: Price Convergence and Market Integration among Russian Regions.â€? BOFIT Discussion Papers 7/2006, Bank of Finland, Institute for Economies in Transition, Helsinki. Kuznetsov, Boris, Tatiana Dolgopyatova, Victoria Golikova, Ksenia Gonchar, Andrei Yakovlev, and Yevgeny Yasin. 2010. Russian Manufacturing Revisited: Industrial Enterprises at the Start of the Crisis. Center for Comparative Economics UCL. OECD (Organisation for Economic Co-operation and Development). 2005. Competition Law and Policy in Russia: A Peer Review. Paris: OECD Publishing. OECD (Organisation for Economic Co-operation and Development). 2008. Indicators of Product Market Regulation. Paris: OECD Publishing. OECD (Organisation for Economic Co-operation and Development) and IDB (Inter-American Development Bank). 2010. Competition Law and Policy in Brazil: A Peer Review. Paris: OECD Publishing. Productivity Commission. 2005. Review of National Competition Policy Reforms. Inquiry Report 33. Canberra: Commonwealth of Australia. WEF (World Economic Forum). 2010. The Global Competitiveness Report 2010–2011. Geneva. World Bank. 2008. Trade Restrictiveness Indicators 2008. Washington, DC. 113 Chapter 3: Commercializing Public Research in Russia:  Scaling up the Emergence of Spinoff Companies x Increased commercialization of public research hinges upon improving some of the pillars of the Russian innovation system. Those pillars include the incentive framework determined by the intellectual property regime, the organizational arrangements, the availability of qualified human capital, and the finance for early-stage innovation. The key to increasing research commercialization is to broaden the potential basin for innovative ideas in the Russian research and innovation landscape. Efforts should be made to mainstream the research conducted in the Russian Academy of Sciences (which receives the majority of public funding), in the defense sector, and in agriculture, with a view to leveraging Russia’s potential comparative advantage in food and agricultural production. x Allocating public funding based on scientific output, active promotion of commercialization efforts, and stronger results-based management of public research organizations would stimulate these organizations to commercialize their research output. A system of academic career development based on performance metrics that include entrepreneurial achievements, as well as active support for young scientists and for international collaboration, would also help align human capital with commercialization efforts. x A cross-cutting area that deserves particular attention is to revise the intellectual property regime for federally funded R&D. This should aim at transferring full ownership (not only use) of research output – including transferability to third parties with a minimum royalty payment to the research team – to public research organizations. x Finally, the lack or inadequacy of instruments to fund early-stage new ventures impedes the creation of a “deal flowâ€? for venture capital investment. This can be addressed through providing funds for early-stage development of technologies and enhancing the supply of financing and services, including mentoring, to innovative start-ups. Russia’s Innovation System and Commercialization Efforts 3.1. The low productivity of R&D limits Russia’s supply of “ideasâ€? as the country spends more per patent than countries that are more R&D intensive, implying inefficiency in the innovation process. Even with government R&D expenditures at 65 percent of the total, that share is relatively low in Russia, alongside a high ratio of expenditures per patent. More advanced economies like Japan and Finland present the opposite situation: it is less costly to patent there, and they spend more on R&D (as measured by lower R&D expenditures per U.S. patent and larger R&D expenditures as a share of GDP; figure 3.1). This chapter was prepared by Paulo Correa (TTL-ECSPF) and Juan Julio Gutierrez, Financial and Private Sector Development, ECA region, The World Bank, with inputs from Jose Luis Guasch, (LCSPF), Donato De Rosa, Dragana Pajovic, and Alina Tourkova (ECSPF). 114 Figure 3.1 Cost of patenting and gross R&D expenditures, 2008 8.5 LogGERD/Patentsgrantedinthe 8.3 Turkey Romania 8.1 Russia Portugal 7.9 CzechRep. China UnitedStates Poland Slovenia 7.7 Slovakia Croatia Spain 7.5 Hungary Luxembourg 7.3 Ireland Norway Austria 7.1 Italy Belgium Iceland UK Sweden France Denmark Finland 6.9 Netherlands Germany Israel Canada Switzerland Korea 6.7 U.S. Japan 6.5 Ͳ0.4 Ͳ0.2 0.0 0.2 0.4 0.6 0.8 LogGERD/GDP Source: OECD, UNESCO, U.S. Patent and Trademark Office, WDI. 3.2. The output from Russia’s scientific community has been decreasing as the productivity of researchers – published articles in science and engineering journals – has declined (figure 3.2).90 In Russia, academic output has always been low relative to other countries, partly related to the performance of R&D in government research institutions rather than in universities. Worryingly, academic productivity has decreased in the last few years of available data, despite the higher R&D investments as a proportion of GDP during the 2000s. Scientific publications are mostly concentrated in physics (30 percent), chemistry (20 percent), and engineering and technology (11 percent), while the number of scientific publications with international collaboration has remained stable in the last nine years (2000– 08), around 8,700, compared with a total number of publications of around 27,000.91 Figure 3.2 Science and engineering journal articles per researcher 0.035 0.034 0.033 0.032 0.031 0.030 0.029 0.028 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Source: Authors’ calculation based on WDI. 3.3. In parallel to declining scientific performance, the rate of researchers in the workforce has been diminishing. While in the mid-1990s, the proportion of researches in overall employment in Russia was 1.5 times the Organisation for Economic Co-operation and Development (OECD) average – almost 90 Fields considered by the National Academy of Sciences: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences. 91 UNESCO 2010. 115 twice the share in EU-27 countries and more than double the EU-15 country ratio – in 2008, it had become lower than in both (figure 3.3). At the same time, Russia’s intensity of researchers in the workforce has been continuously declining, compared with an increasing trend in Europe and OECD countries. Figure 3.3 Total researchers per thousand total employment 10 Researchers/1,000employment OECD EUͲ27 EUͲ15 Russia 9 8 7 6 5 4 Source: OECD Directorate for Science, Technology and Industry. 3.4. The declining scientific output and employment in research activity is framed within a context of substantial investments in R&D. In the last few years, Russia has invested US$10 billion– US$14 billion annually in R&D.92 This large absolute value surpasses the R&D expenditures in more innovative but smaller countries such as US$8 billion in Israel or US$9 billion in Finland. Yet this falls short of the R&D expenditures in larger advanced economies (US$50 billion in the United Kingdom, US$31 billion the Republic of Korea), as well as the expenditures in the other BRICs (for example, US$49 billion in China) and it is less than 5 percent of the top country in R&D expenditures (US$369 billion in the United States). Russia’s 2008 R&D expenditures as a share of GDP (1.03 percent) is certainly higher than some Eastern European countries (0.6 percent in Poland, 0.5 percent in Romania) and comparable with the other BRICs (for example, 1.0 percent in Brazil and 1.4 percent in China). Yet it is less than half the EU Lisbon Agenda target of 3 percent and much lower than that of economies at the technological frontier (2.7 percent in the United States, 3.7 percent in Sweden, and 4.7 percent in Israel). 3.5. Russia is among the world leaders, after the United States, Japan, and China, in the absolute numbers of R&D staff. In 2008, it had 761,300 people engaged in R&D, including researchers, technicians, and support staff. The ratio of 3,191 researchers per million people in Russia that year by far surpasses Eastern European country averages (1,600 in Poland and 876 in Romania), as well as the BRICs (for example, 628 in Brazil and 1,070 in China). The relative number of researchers in Russia is, 92 Ministry of Science and Technology 2009. 116 however, much lower than in economies at the technological frontier (4,663 in the United States, 5,214 in Sweden).93 3.6. Despite significant R&D financial resources and human capital, Russia’s standing has been eroding in the past 15 years. Russia’s relative position is either similar or worse than in the mid-1990s in both R&D spending as a share of GDP and the number of researchers as a proportion of the population (figure 3.4). Further limited evidence for 2009 indicates that budgetary expenditure on R&D was cut by around 30 percent that year along with decreases in private sector R&D. Figure 3.4 Evolution of R&D investments and number of researchers, 1996–2008 3,900 1.40 1.20 3,600 1.00 0.80 3,300 0.60 0.40 3,000 ResearchersinR&Dpermillion R&D/gdp 0.20 2,700 0.00 Source: Authors calculations based on WDI. 3.7. Yet despite its inefficiencies, the Russian innovation system is relatively strong in certain sectors, as measured by technological advantage. Even with overall low patent productivity, there are niches where Russia’s patent production is concentrated. Russia has a revealed patent advantage (RPA)94 in three of five fields of technology – instruments, chemistry, mechanical engineering, and other fields. 3.8. Within fields, Russia has a technological/patent advantage in some subfields but not in others. In instruments, the highest patent advantage is in analysis of biological materials, followed by measurement instruments and medical technology (figure 3.5). In chemistry, the RPAs are higher in food chemistry (the highest RPA in Russia), followed by materials and metallurgy, chemical engineering, environmental technologies, pharmaceuticals, and basic material chemistry, with just a slight RPA in biotechnology. In the mechanical engineering field, Russia shows RPA in all 10 subfields but two. Finally, the subfield of civil engineering has a high RPA. (The complete RPA/RTA is in annex 3B.) 93 UNCTAD 2010. 94 Revealed technological advantage (RTA) is defined as the share of a country in patents in a given field of technology filed with a given institution, divided by the country’s share of all patents in that institution. The revealed patent advantage (RPA) = log(RTA). 117 Figure 3.5 Russia’s RTA, 2002–07 7 6.3 6 5 4 3.2 3 2.4 2.2 2.1 1.9 1.9 1.7 1.6 2 1.5 1.4 1.4 1.3 1.2 1.2 1.2 1.0 1.0 0.9 0.8 0.8 0.8 1 0.6 0.5 0.4 0.4 0.3 0.3 0.2 0 Source: Authors’ elaboration using WIPO 2011 data (http://www.wipo.int/ipstats/en/statistics/patents/). 3.9. Russia has a technological advantage only in some of the sectors designated by the government as strategic. The Long Term Social and Economic Development Plan until 2020 of the Russian Federation (Concept 2020) identifies six sectors as strategic for the future development of the country. Russia, however, has technological advantage only in some of them – aviation and engine building, space industry, shipbuilding, and nuclear power. Neither is Russia particularly strong in the radio-electronic industry nor information and communication technology (ICT), also deemed strategic by Concept 2020. In particular, the nanotechnology sector, which has been given extensive policy attention and funding, does not show technological advantage (seen in publications in the field).95 3.10. “Strategicâ€? sectors accounted for around 44 percent of all R&D expenditures. Among the strategic sectors, the majority of resources – 52 percent – were employed by the transport, aviation, and space systems sector, followed by ICT at 16 percent, in 2007 (table 3.1). The heavier expenditures in transport may guarantee Russia’s place at the technological frontier in the field, especially in space and aircraft technology. Additionally, the relative large resources devoted to ICT may partly explain the emergence and growth of software start-ups and software exports in recent years. Formal investments in R&D in ICT may tilt Russia’s technological advantage to ICT-related fields of science, such as computer technology and information technology (IT) methods for management. In those fields, Russia did not have technological strength (see figure 3.5). 3.11. The Russian government has identified innovation policy as a key component for growth and so has designed a set of policy instruments to incentivize the commercialization of research results. Such improvements have led to the creation of more than 950 research-based start-ups in the last two years. Russia has made efforts to improve the national innovation system, through reforming the legal framework for intellectual property rights (IPR), providing public funds for venture capital, and developing innovatory policy instruments, while also increasing overall public participation in R&D expenditures. As a result of the stated policy focus on commercializing public research, June 2011 data 95 Although later reduced, the government invested $5 billion in 2007 into a new state corporation in nanotechnology, RUSNANO. 118 from the Ministry of Education and Science (MoES) show the emergence of 973 research-based spinoff companies since 2009.96 Table 3.1 Gross domestic expenditure on R&D in priority areas of science, technology, and engineering by source of funding, 2007 (thousand US$) Nano- Energy Transport, technology Life Natural and aviation, Total ICT and sciences resources energy and space materials efficiency systems Gross domestic expenditure 6,570,375 1,026,233 465,476 279,025 520,033 533,353 3,392,642 on R&D Sources of funding Federal budget 3,584,383 591,761 362,885 217,878 246,696 192,164 1,784,651 Regional and local budgets 147,631 18,984 6,596 9,785 23,946 3,286 86,617 Extra budgetary funds 2,838,361 415,487 95,995 51,362 249,391 337,903 1,521,374 Source: Indicators of Science (2009) – MoES, ROSSTAT, and the Higher School of Economics 3.12. The focus of innovation policy has been the commercialization of research stemming from higher education institutions. Accordingly, most spinoffs have started from university-based research. Nevertheless, universities have only a small share of both R&D expenditures and the number of researchers. Of the reported 973 intellectual property–based new companies, the vast majority – 97 percent – have started in higher education institutions, compared with only 3 percent in research institutes, including those from the Russian Academy of Sciences (RAS), which, in turn, receives the majority of R&D resources. 3.13. University participation in commercializing research far outstrips that from research institutes, though the latter are more numerous and better endowed for research. While 973 spinoffs have been initiated in 181 universities – an average of 5.1 per university – only 30 spinoffs are based in 25 research institutes – an average of 1.2 per institute. The participation of universities in research commercialization is more widespread, with 29 percent of the 621 higher education institutions having spinoffs. By contrast, only 4 percent of the 433 research institutes affiliated with the RAS have initiated spinoffs. 3.14. Results on research commercialization are starting to show through, but further fine-tuning of policies is needed if such commercialization is to be scaled up. Policy enhancements are needed more in the following areas: Russia’s innovation system structure and operation; human capital in R&D; the IPR regime and technology transfer; and early-stage financing for research-based companies. These four issues are analyzed in the following four sections. 96 nformation on Spin-Off Companies Founded by Russian Universities and Research Institutes (2011), presentation by Andrei Kolesnikov, Center for Science Research and Statistics from the Federal Ministry of Education and Science of Russia. June 16, 2011 - GDLN - Russia Series: Trade Promotion, Competition Policy, and Innovation, Commercialization of Research and Spin-off SMEs. 119 Challenges in Russia’s Innovation System 3.15. Contrary to more advanced economies where the business sector plays a leading role, the bulk of R&D expenditures in Russia are funded by the public sector (66 percent in 2009; figure 3.6). This share has continuously increased in the last few years, while that of both private and foreign sources has decreased to 27 percent and 6 percent, respectively, probably as a result of the global financial crisis. The number of small, innovative enterprises fell by around half. Many of them were working under contract to large firms that had outsourced R&D activities and cut their R&D spending in the wake of the recession.97 Figure 3.6 R&D expenditures for selected countries by source of funds, 2009 100% 4.0 6.6 1.4 1.3 3.5 5.7 8.0 6.9 6.5 90% 2.3 16.6 17.7 25.4 23.4 12.1 80% 28.4 27.1 6.3 70% 38.9 33.4 32.6 60% 66.5 50% 40% 75.3 72.9 71.7 67.3 67.3 30% 50.7 47.6 44.5 20% 10% 26.6 0% Japan Korea China Germany United France Canada United Russian (2008) (2008) States (2008) Kingdom Federation (2008) Industry Government Othernationalsources Abroad Source: OECD MSTI (2011). 3.16. The federal contribution to R&D is not homogeneous across strategic sectors, nor is private sector participation. Private funding of R&D, including foreign R&D, varies within strategic sectors, from 18 percent in living systems to 48 percent and 63 percent in rational use of natural resources and energy and energy efficiency, respectively. The federal contribution to R&D is by far the largest in industry nano-systems and material systems as well as in living systems (78 percent), and is also high in ICT (58 percent) and transport, aviation, and space systems (53 percent; see table 3.1). 3.17. The public sector is not only the main funding source, but also the main performer of R&D. Although the business sector apparently “performsâ€? 64 percent of total R&D, this is because in the business sector of official Russian statistics, state owned-companies and branches of research institutes that form part of the RAS are classified as business entities – and they conduct many of the publicly financed innovation activities (table 3.2). 3.18. In line with the proportion of government funding as a source of R&D, the Russian government owns around 65 percent of the 4,000 institutions performing R&D. As of 2009, the state owned around 2,600 R&D organizations, including research institutes affiliated with the RAS and state- owned enterprises performing R&D. The number of research institutes has risen in recent years, mainly as a result of splits and spinoffs rather than any increase in research capacity. Thus the structure of 97 Gaidar Institute 2010. 120 government R&D may be both too large and too fragmented, with many institutions performing little if any research, and others conducting research that does not need to be in the public sector. 3.19. Although universities are at the core of Russia’s policies for commercializing publicly funded research, higher education institutions only conduct 6 percent of total R&D. This ratio is well below that in other advanced economies. As a share of GDP it comes to 0.07 percent in Russia, against an average for OECD countries of over five times as high, at 0.39 percent. 3.20. Moreover, as of 2008 only a third of universities conducted R&D, down from 52 percent in 1996. Historically, research has been mostly in the hands of the research institutes affiliated with the RAS, with universities having teaching as their main mandate.98 Table 3.2 R&D by funding source and performer, 2007 R&D funding source R&D performer Rub US$ Rub US$ Sector (million) (million) % Sector (million) (million) % State 232,365 9,294.6 63 State 107,985 4,319.4 29 Business sector 109,265 4,370.6 29 Business sector 238,386 9,535.4 64 Foreign sources 26,796 1,071.8 07 Other sources 2,654 106.2 01 Higher education 23,472 938.9 06 Nonprofit organizations 1,237 49.5 003 Total 14,843.2 Total 14,843.2 100 Source: Indicators of Science – MoES, Higher School of Economics, 2009. 3.21. The institutional structure of the Russian innovation system carries a heavy legacy from Soviet times. Public research organizations, led by research institutes affiliated with the RAS, receive a high proportion of resources devoted to R&D. The RAS has generally received around 60 percent of government funding to science, which it allocates among its 433 institutes (with 76 percent going to natural sciences in 2009). The Russian Academy of Medical Sciences received 6 percent for 69 institutions. These research institutes are, it will be remembered, counted as part of the business sector (table 3.3). Higher education institutions (621 of them) received 5.5 percent of government funding. 3.22. Only a small proportion of the government budget for research institutions is allocated competitively, unlike the more advanced economies. Although there is a government desire to allocate more government R&D funds competitively, the government budget apportioned only 14.6 percent of all civil science funding competitively. Half of that was channeled through the Russian Foundation for Fundamental Research and the Russian Humanities Science Fund. 99 More developed economies have higher shares of competitively allocated funding. Most public financial support for R&D in the United States is awarded by mission-oriented agencies and other research bodies (such as the National Academy of Sciences) in response to individual demands. In Israel, around 30 percent of government-funded R&D is allocated competitively through universities or the Ministry of Industry, Trade and Labor.100 98 UNESCO 2010. 99 MoES 2009. 100 ERAWATCH 2010. 121 Table 3.3 Number of institutions, personnel by performing sector Number of R&D personnel, % in intramural R&D Number of organizations headcount expenditure 2006 2007 2008* 2006 2007 2008* 2006 2007 2008* Government sector 1,341 1,483 1,480 27 29.2 29.8 274,802 272,255 274,515 Business sector 1,682 1,742 1,663 66.6 64.2 63.2 486,613 478,401 467,144 Higher education 540 616 621 6.1 6.3 6.6 44,473 49,059 49,363 Private nonprofit 59 116 138 0.3 0.3 0.4 sector 1,178 1,420 1,741 Total 3,622 3,957 3,902 100.0 100.0 100.0 807,066 801,135 792,763 Source: Indicators of Science – MoES, Higher School of Economics, 2009. 3.23. Most of the budget for research institutions, including universities, is apportioned based on personnel headcount. The government allocates budgets to public research organizations and higher education institutions in amounts it deems sufficient to cover anticipated costs. The financing system takes into account the number of employees. Thus if research institutes’ directors were to have fewer employees, they would receive less from the state budget. 3.24. As a result, there are incentives to inflate payrolls and many “researchersâ€? have other jobs, affecting the quality of research. Even though still formally associated with research institutes, the number of specialists working in more than one job grew steadily in the 2000s. At least at the start of the decade, about 40 percent of researchers had R&D as a part-time job.101 The headcount financing system creates incentives to inflate costs and fails to establish a link between resources and outputs. 3.25. Russia’s investment in research, both basic and applied, has risen over the years, but development expenditures have fallen. This may diminish the capabilities to commercialize research results by bringing innovations to the marketplace. The development side of R&D fell to 59 percent in 2009 from 70 percent in 2000, while basic and applied research grew by 8 and 4 percentage points, respectively (figure 3.7). Russia’s structure of R&D differs from that in more advanced economies, where R&D expenditures are less concentrated in basic research and more in applied R&D, with Israel devoting as much as 82 percent to the development side. Russia’s R&D structure also differs from that of Eastern European countries, which devote higher proportions of R&D to basic research and less to development. For example, the proportions of basic research in Poland and the Czech Republic are 38 percent and 30 percent, respectively, while development amounts to 39 percent and 46 percent.102 3.26. Part of the innovation policy focus is to change the character of the work performed by research institutions. The Russian government has plans to increase the number of higher education institutions that are performing basic R&D. Basic research has traditionally been performed by the RAS.103 At the same time, the plan includes the reduction of branch institutes and design bureaus – that is, large research institutions affiliated with ministries – that conduct applied research.104 101 Yegorov 2009. 102 OECD 2011. 103 Yegorov 2009. 104 MoES 2009. 122 Figure 3.7 Russian R&D by character of work, 2000–09 100% 90% 80% 70% 62% 59% 70% 70% 69% 69% 69% 70% 69% 67% 60% 50% 40% 30% 19% 20% 15% 15% 20% 16% 16% 16% 16% 16% 16% 10% 15% 18% 19% 21% 13% 14% 15% 15% 14% 14% 0% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Basicresearch Appliedresearch Experimentaldevelopment Source: OECD 2011. 3.27. The government has been planning to turn many of the research institutes into autonomous institutions to give them more flexibility, but the new status may make spinoffs from autonomous institutions ineligible for state support. The new status is designed, first, to make the new autonomous organizations less dependent on guaranteed budgetary funding and more reliant on competitive funds; and second, to provide flexibility to undertake joint R&D with private firms, which is constrained in a budgetary organization status.105 Nevertheless, in practice, the change to autonomous status of federal universities in June 2010 has created a legal vacuum in which the newly designated institutions are ineligible for any type of program support or finance, which are designed only for companies established under Federal Law 217 of July 2009,106 as discussed below. Policy Recommendations x Receiving the bulk of public R&D funds, the RAS should undertake commercialization efforts. Institutes affiliated with the RAS encompass more than 60 percent of both R&D expenditures and researchers, but their contribution to research commercialization through start-ups is minimal. x Strengthen results-based management of public research organizations in RAS institutes and universities. The allocation of public funding should be based on scientific output, and include metrics that acknowledge commercialization efforts. This is a way to incentivize research institutions to increase scientific efficiency and to undertake research with market potential. x Agricultural research should have a renewed emphasis, which could leverage Russia’s technological advantage in food chemistry. The reason is that not all innovation deals with high- tech sectors, which are the strategic sectors chosen by the government. This could be a sector in which to expand commercialization efforts. 105 Gianella and Tompson 2007. 106 Kolesnikov 2011. 123 Human Capital 3.28. Despite the focus of the research commercialization policy, university researchers form the smallest proportion of the total among institutions conducting R&D. While university-based researchers account for 5.3 percent of the total, research institutes (mostly under the RAS) account for 59.9 percent of the total, design bureaus (linked with ministries, such as interior or defense) 22 percent, and industrial enterprises 6.8 percent.107 3.29. Moreover, the number of university researchers has not kept pace with the increase in total faculty staff. Thus the share of faculty engaged in research has fallen, from 24 percent in 1996 to 19 percent in 2008. The number of university-based researchers climbed by only 10 percent from 26,300 to 28,900 between 1996 and 2008, which should be set against the 40 percent rise in the number of faculty, from 243,000 to 341,100. This trend is worrisome for the policy objective to increase the number of spinoffs from university publicly funded research, because the critical human mass to create a deal flow of inventions is small, or stagnant at best. 3.30. Despite the relative decline in the number of researchers, Russia may have too many researchers given the level of R&D spending. While U.S. R&D expenditures are two times Russia’s and Sweden’s three times, the number of researchers in the United States is only 1.2 times Russia’s and Sweden’s 1.5 times. In other words, the average R&D resources for each researcher fall short of those in more advanced economies. Furthermore, more than 70 percent of researchers in Russia hold no advanced scientific degree.108 3.31. The composition of R&D personnel in Russia reveals an unhealthy imbalance, with too few researchers relative to auxiliary personnel. Unlike many other countries, researchers in Russia account for less than half of R&D personnel: 375,800 (or 49 percent) in 2008. The rest are mainly support and auxiliary staff (43 percent), rather than technicians serving the scientific process (8 percent). As a result, Russia ranks 10th globally in the number of people engaged in R&D per 10,000 employees but 19th in researchers. 3.32. Russian R&D human capital is aging, while the share of middle-career researchers, the ones most likely to publish, is decreasing. Among R&D personnel, 57 percent or more of researchers with the highest skills, proxied by a PhD degree, have passed the official retirement age (table 3.4).109 In 2008, researchers were 49 years old on average, against an average of 40 for those working in the national economy as a whole.110 3.33. Average wages for researchers are low and uncompetitive in the international market. Researchers working in public research institutions, the private sector, or higher education institutions cannot expect to earn more than US$600 a month. 107 Higher School of Economics 2010. 108 UNESCO 2010. 109 55 years for women and 60 for men. 110 UNCTAD 2010. 124 Table 3.4 Age of researchers by educational attainment Year Age category (years) 2002 2004 2006 70 and older 3.8 4.6 5.9 Researchers 60–69 17.9 17.4 17.2 50–59 27 27.8 27.8 40–49 23.9 21.9 19 30–39 13.8 13 13.1 Under 29 13.5 15.4 17 70 and older 20.3 22.2 24.7 60–69 36.1 34 32.4 50–59 28.1 29.7 29.9 PhDs 40–49 13.5 12.3 11.3 30–39 2 1.6 1.8 Under 29 0.2 0.1 0.1 70 and older 5.9 7.4 9.7 Candidates of 60–69 26.4 25.1 23.8 Science 50–59 28.5 28.9 29 40–49 23.5 21.4 18.8 30–39 12.1 13 14.3 Under 29 3.5 4.1 4.5 Source: Indicators of Science (2009) – MoES, ROSSTAT and the Higher School of Economics 3.34. Nevertheless, the rate of engineers (and scientists to a smaller degree) graduating from Russian universities is very high. The share of engineers among new university degrees in Russia (27.3 percent) is lower only than in Korea (figure 3.8). Ukraine, Mexico, Japan, the United Kingdom, and the United States all had lower rates than Russia. By contrast, the equivalent figure for science degrees (5.8 percent) was lower than most comparators, at roughly half the share in Mexico and even less than that in the United Kingdom. Figure 3.8 Share of all new university degrees awarded in science or engineering, 2007 Korea Finland Russia. Mexico Ukraine CzechRep. Engineering UK Turkey Science Japan Romania U.S. Brazil 0 10 20 30 40 % Source: UNESCO. 125 3.35. There is evidence of a brain drain from Russia to the west, with a large share of science and engineering graduates studying abroad and not returning. Russia had the eighth-largest number of science and engineering graduates receiving PhDs in the United States in 2002 (table 3.5). By 2007, less than one-fourth of those graduates had returned to Russia. The share of Russian graduates remaining in the United States is higher than graduates from other economies such as Korea and Turkey (and above the all-country average of 62 percent). Russia should leverage better the skills and knowledge of those graduates who remain in the United States and other countries where they study, through stronger and wider business and research diaspora networks, similar to those established by China and India. Table 3.5 Foreign science and engineering PhD recipients in the United States and share staying there Foreign doctorate % remaining in the United States recipients in 2002 Country of origin 2003 2004 2005 2006 2007 China 2,139 97 93 92 92 92 Korea, Rep. 814 61 53 47 44 41 India 615 91 89 85 83 81 Turkey 315 53 49 46 44 42 Canada 258 65 64 58 52 55 Mexico 173 36 34 28 28 32 Germany 164 58 58 54 51 52 Russia 161 83 85 82 80 77 Japan 144 44 38 36 32 33 Romania 121 88 88 89 87 86 Brazil 119 32 34 32 30 31 Italy 107 60 62 61 61 63 United Kingdom 89 68 65 64 68 64 France 83 54 50 50 49 45 All countries 7,850 69 66 64 62 62 Source: Oak Ridge Associated Universities 2010. 3.36. The most qualified R&D personnel are concentrated in fields that, though considered strategic, receive small proportions of R&D expenditures. The most skilled researchers among R&D personnel (those with PhD and Candidate of Science degrees) are concentrated in the natural science field (table 3.6). However, the strategic sectors that may intensively use these researchers (life sciences and natural resources) do not receive large shares of allocated resources (see tables 3.1 and 3.5), both areas together only taking 12 percent of total R&D spending in strategic sectors. Table 3.6 R&D personnel by educational attainment and field of science, 2007 Total Candidates of Field of science % PhDs % % researchers Science Total 392,849 25,213 78,512 Natural 94,668 24 11,479 46 33,359 42 Technical 244,475 62 4,809 19 23,552 30 Medical 16,734 4 3,934 16 7,540 10 Agricultural 13,743 3 1,478 6 5,100 6 Public 13,740 3 1,632 6 5,008 6 Humanities 9,489 2 1,881 7 3,953 5 Source: Indicators of Science (2009) – MoES, ROSSTAT and the Higher School of Economics 126 3.37. R&D researchers do not work with appropriate equipment or facilities. Even with recent replacements, much R&D equipment is obsolete and of declining value. UNESCO (2010) reports that 25 percent of machinery and equipment used in R&D is more than 10 years old and 12 percent is more than 20 years old, with a degree of wear and tear for R&D equipment of 55 percent. This is particularly problematic for high-tech sectors where depreciation of equipment is higher than in other less technology- intensive sectors. Also, between 1998 and 2005 the value of capital assets used in R&D declined by more than 50 percent, in constant prices. The lack of adequate replacement of R&D equipment forced some research institutions to discontinue regular scientific experiments.111 UNESCO (2010) also reports that only 7 percent of installations where research is carried out were specifically designed for R&D. 3.38. Old equipment is prevalent, even though growth in machinery investment has surpassed GDP growth to become the most important innovation-related expense. In 2007, the purchase of machinery and equipment accounted for 58.5 percent of total spending on technological innovation, R&D itself 16.5 percent.112 Between 1998 and 2008, the accumulated growth in investment in machinery and equipment was higher – at around 210 percent – than overall GDP growth of 100 percent. 113 In that regard, Russia’s innovation expenditure structure is similar to that of countries like Korea during its catch-up phase, when it relied heavily on acquiring machinery and equipment to gain access to foreign- embodied knowledge. 3.39. One upshot of these negative trends among the Russian R&D workforce can be seen in the low and falling number of publications. Besides what was presented in figure 3.2, case study evidence corroborates the R&D human capital performance. For instance, within the Siberian branch of the RAS – generally reckoned one of the more active and successful branches – an estimated 20–25 percent of researchers have published nothing for at least three years.114 Policy Recommendations x Career development for researchers should be based on performance, and support for young scientists should be a priority. x Career development should include entrepreneurial achievements related to commercialization as part of the criteria for advancement, with sabbatical years for initiating new ventures based on research discoveries an option. x The brain drain can be addressed through “brain circulation,â€? securing international research collaboration with Russian researchers based abroad. Croatia’s Unity through Knowledge Fund is an example of an up and running initiative that has achieved success in such collaboration (box 3.1). 111 Yegorov 2009. 112 MoES 2009. 113 Crane and Usanov 2010. 114 Yegorov 2009. 127 Box 3.1 Croatia’s Unity through Knowledge Fund The Unity through Knowledge Fund (UKF) provides grants for joint scientific projects between Croatian scientists in the country and those abroad. The International Labour Organization and the European Regional Economic Forum have recognized the UKF as a good practice organization for improving the mobility of highly qualified experts, and critical for promoting linkages between migration and development. UKF focuses on three areas: support to outstanding young scientists and professionals from Croatia to visit top-class research and development centers abroad in order to establish cooperation (with grants up to €10,000); cooperation and knowledge with researchers and experts of Croatian origin to advance science and technology (with grants again up to €10,000); and engagement of young researchers and professionals in Croatian enterprises who have a doctorate. The objective of this subprogram is to prevent the brain drain and to help research-related professionals stay in the country. The success of UKF in attracting Croatian researchers abroad can mainly be attributed to the way it is administered and governed. Since the first call for proposals, the selection process has been driven by academic excellence, fairness, and transparency. These were achieved through a combination of simple rules, streamlined processes, expert evaluation, and a “sounding boardâ€? comprising local and international researchers as well as leading representatives from the multinational and local business community. The novel idea of bringing in these leading corporate figures to supervise the program was aimed at strengthening the credibility of the program, ensuring that it was merit-based and impartial, and encouraging the best researchers, particularly those abroad, to apply for grants. Russia’s Intellectual Property Legal Framework 3.40. Patent applications by Russian scientists – a prerequisite for subsequently commercializing research through licensing and start-ups based on intellectual property (IP) – though increasing in number, are fewer than in more advanced economies. The number of patent applications averaged, in 1999–2007, only 0.5 per researcher. The number in the United States, for example, was almost three times as high, at 0.14. 3.41. Patent applications by Russian scientists are often made solely in Russia, which does not protect the IP in global markets. In Russia, only 4 percent of total applications are registered abroad, against, for example, 26 percent in Korea (calculations based on WIPO 2010). It may be that a large home market, at least in certain product categories, does not push companies to foreign markets, and therefore they feel no need for IP protection abroad.115 Yet truly groundbreaking inventions may indeed have an international market. Table 3.7 Patents filed and granted in Russia, 2005–09 2005 2006 2007 2008 2009 Filed with ROSPATENT, total 32,254 37,691 39,439 41,849 38,564 by Russian applicants 23,644 27,884 27,505 27,712 25,598 by foreign applicants 8,610 9,807 11,934 14,137 12,966 115 Kaartemo 2009. 128 Decisions on granting, including: 24,916 25,382 28,212 29,903 32,144 to Russian applicants 20,749 20,323 22,066 22,668 23,502 to foreign applicants 4,167 5,059 6,146 7,235 8,642 Source: ROSPATENT Annual Report 2009 3.42. Weaknesses in the IPR regime have been cited as a major impediment to commercializing R&D outputs in Russia. In an enterprise survey conducted by the Interdepartmental Analytical Centre, 50 percent of respondents cited IPR as a major impediment, citing only lack of access to financing (57 percent) more frequently.116 3.43. The Russian government has made improvements in the IPR legal framework, though there is still uncertainty, discouraging both patenting and licensing. Two major pieces of legislation govern IP in Russia: Part IV of the Civil Code from 2008 provides a foundation to treat the IP generated with public funding; and Federal Law 217 (2009) deals exclusively with the use of IP generated with public funds to form start-up companies by universities and research institutes under the RAS. We take them one by one. 3.44. Part IV of the Civil Code establishes the conditions under which the right to technology belongs to the state.117 IP belongs to the state in defense-related research and, potentially, any discovery registered in any stage of the innovation process funded by the government. The Civil Code protects most forms of IP (patents, designs, trademarks). If a technology is developed for needs of defense or security, and if the state assumed the financing before the development of the technology or later to bring the technology to the stage of practical application, the right to the technology belongs to the state. In addition, if after six months of completion of work on creation of the technology, the developer has not made all provisions for all legal actions necessary for recognition of the IPR, the state becomes the owner. In all other cases, the right to the results of intellectual activity must belong to the organization í the R&D executor. The Civil Code language is rather vague, especially when defining IP from publicly funded research that is not defense related. The bottom line is that the state retains rights to the IP generated with public funds in defense-related research and in any other case it deems necessary. In the words of a Russian IP expert, the government’s rights never end. 3.45. The benchmark in regulation of IP stemming from public funds is the U.S. Bayh-Dole Act, which homogenized IP treatment, assigned clear ownership and transfer rights, and regulated the distribution of gains from commercialization. In the United States, the insignificant commercialization of research by universities motivated the adoption of the Bayh-Dole Act in 1980. The act transfers to the universities the IP rights resulting from publicly funded research, establishes a minimum amount of royalties to be shared with the researcher, and greatly simplifies the process of IP management (which had been subject to more than 20 different pieces of legislation). These changes enabled more universities to afford the investment required for effectively monitoring, protecting, and marketing IP, and encouraged academic researchers to engage in the related activities. Legislation inspired by the Bayh-Dole Act has thus far been adopted in around 20 OECD countries. 116 Gianella and Tompson 2007. 117 Clause 1 of Article 1546 of Chapter 77 “Rights of the Russian Federation and Subjects of the Russian Federation to Technology.â€? 129 3.46. In July 2009, Federal Law 217 was enacted to regulate the use of IP generated with public funds to form start-up companies by universities and RAS research institutes. The creation of the new firm has to be notified to the federal government, specifically to the MoES. Universities and public research institutions can be sole founders or cofounders of start-ups based on IP. The participation of the university or research institute cannot be less than 25 percent in the case of a joint stock company and 33.3 percent in the case of a limited company. 3.47. As of June 2011, 973 start-ups had been created, based on IP produced by publicly funded research under Federal Law 217 (see annex 3D). The great majority of these new firms (97 percent) stemmed from university research and very few from research institutes (3 percent; table 3.8). 3.48. The participation of universities in the commercialization process far exceeds that of research institutes, though the latter receive the bulk of both financial and human capital resources in R&D. Research institutes encompass the bulk of R&D resources, around 60 percent of government funding for R&D and number of researchers. Almost a third, 29 percent, of the 621 universities in Russia have spinoffs based on research. By contrast, only 4 percent of the 433 research institutes affiliated with the RAS have initiated spinoffs. By number of start-ups, 943 have been initiated in 181 universities – an average of 5.1 – but only 30 from 25 research institutes – an average of 1.2. Table 3.8 Enterprises created by academic departments and RDIs related to the Federal Law 217, August 2, 2009 Number of start-ups, Number of start-ups, November 2010 June 2011 Number of enterprises, organized by academic 602 943 departments Number of enterprises, organized by RDIs 12 30 Number of institutions, Number of institutions, November 2010 June 2011 Number of academic departments that created 145 181 enterprises Number of RDIs that created enterprises 10 25 Source: MoES 2010, 2011. 3.49. The MoES has provisions on proportions of ownership for start-ups among university/RDI, research team, and (as the case may be) private investors. Most universities are affiliated with the MoES, and spinoff companies from universities adhere to MoES rules, which state that a third of the ownership can be private; the university may own the above minimums and the rest of the new company can be the property of the research team. 3.50. A spinoff finds it difficult to sublicense the IP since the company does not own the patent that supports the company, and the universities do not grant the IP to the companies on an exclusivity basis. In consequence, the IP may not be resold (sublicensed) to third parties by the spinoffs unless this is stipulated by Federal Law. However, according to the MoES, a planned amendment to Federal Law 217 would change this situation.118 3.51. Besides the right to transfer the IP, the distribution of royalties is a key aspect to guarantee greater efficiency in technology transfer. However, further improvements in Russian legislation are 118 Kolesnikov 2011. 130 needed to define royalty distribution. The evidence implies that shifting the royalty distribution formula in favor of faculty members (such as allowing faculty members to retain 75 percent of the revenue, instead of 33 percent) would elicit more invention disclosures and greater efficiency in technology transfer.119 Indeed, Markman and others (2005), using data on 113 U.S. technology transfer offices, found that universities allocating a higher share of royalty payments to faculty members tend to be more efficient in technology transfer activities. 3.52. Less than 10 percent of patents granted are contracted away either in patent assignments or licenses. Exclusive-license contracts represent less than one-fifth of patent assignments or nonexclusive license contracts (table 3.9). Table 3.9 Registration of license contracts and patent assignment contracts 2005 2006 2007 2008 2009 Patent assignment contracts 1,281 1,451 1,674 1,524 1,054 Exclusive license contracts 167 212 276 215 228 Nonexclusive license contracts 674 751 902 1,005 1,083 Total 2,122 2,414 2,852 2,744 2,365 Source: ROSPATENT Annual Report 2009 3.53. The inclusion of intangibles (IP) as an asset of the start-up is a welcome development, but skilled independent valuation of high-value IP is nonexistent. According to Federal Law 217, items like equipment and facilities can be considered assets of the new company. The IP can be considered an intangible asset and its value can be decided by the start-up founders up to about US$17,000 (RUB500,000) but would need an independent evaluator if the IP value is higher. This requires skilled valuation of high-value IP, but expert opinions consider that the Russian market does not provide this service. 3.54. As IP is an intangible asset in the start-up’s balance sheet, it could be considered part of the start-up capital for financing entities like RUSNANO and the Russian Venture Company’s venture funds. Federal Law 217 also states that IP may not only reach the marketplace through spinoffs but also through license sales. IP belongs to the university, not to the department where the inventor or research team is hosted, but the latter gets the larger part of the royalties. Usually, the contract is between the professor (inventor) or the research team and the university, and they then sell the IP. Registration of license agreements is mandatory by law. 3.55. All national research and federal universities have been directed to become autonomous institutions. 120 However, start-ups from not-budgetary institutions lose the special privileges and government support under Federal Law 217. Start-ups that fulfill MoES requirements121 to belong to the Register of Notifications on Established Companies can use, for example, the Simplified Taxation System and get a potential reduction of the insurance contribution from 34 percent to 14 percent. 119 Phan and Siegel 2006. 120 According to the Federal Law on Autonomous Institutions (No. 174, dated November 3, 2006). 121 The selected criteria of compliance with Federal Law 217, dated August 2, 2009: 1. Completeness of information on companies as required by MOES Executive Order No. 718, dated December, 2009. 2. Results of ROSPATENT’s review. 3. Compliance with legislation (Civil Code, Part 4; Federal Law on LLC; Federal Law on Registration of Legal Entities). 131 3.56. The Russian legal regime for IP and technology transfer is developing incrementally as the Ministry for Economic Development and the MoES work on amendments to address inconsistencies and imprecision. According to government officials, Federal Law 217 is seen as a test to gauge the demand for publicly funded IP to start new companies. Yet according to experts, the market for IP in Russia is very small and there is no demand from the market. Research Commercialization through Technology Transfer Offices 3.57. International experience shows that technology transfer offices (TTOs) may play a central role in accelerating the commercialization of public research. Their main role is to match the universities’ “supplyâ€? of potentially commercial ideas with businesses’ “demandâ€? or needs. As such, TTOs are responsible for managing the IP that emerges from public research – evaluating its commercial potential, identifying potential users in the business community, and defining the best form of research commercialization (spinoffs, licensing). 3.58. To address the lack of information on the particularities of Russian TTOs, the World Bank and the MoES engaged in a joint initiative to survey existing TTOs in Russia (see annex 3A). The survey was conducted between January and May 2011 covering the 112 registered TTOs, with a response rate of 65 percent of the TTOs providing accurate contact information. The following paragraphs present the survey results. 3.59. The majority of TTOs were created between 2003 and 2008 and their emergence is not a consequence of IPR legislation, unlike the U.S. experience. Most of the surveyed TTOs, 81 percent, started operating before 2008 – that is, before the main new IP laws were enacted.122 TTOs were initially established in 2003 on the basis of RAS institutions, universities, and public research centers in six federal districts. TTO creation is not a stated goal of the Russian IPR legislation (Part IV of the Civil Code and Federal Law 217). Unlike the United States where the initiative came from universities as an unintended consequence of the Bayh-Dole Act, in Russia TTOs have been set up by the MoES. 3.60. The average staff size of Russian TTOs is in line with comparable institutions in other countries. Russian TTOs had an average of 5.6 full-time employees in 2010. In the United States, TTOs are relatively small, often at most with five full-time equivalent staff.123 3.61. The Russian TTO staff’s professional background is roughly a third each of businesspeople, university faculty, and university administrators, which may indicate a healthy balance. Several factors influence the success of TTOs, including finding a personnel mix with the appropriate scientific and business skills. 3.62. Inventors take full part in the licensing process, as reported by 75 percent of the TTOs. An important challenge for commercializing public research is balancing the interests of researchers and research organizations. The process of commercialization often requires an additional engagement from the researcher that is inconsistent with his or her career objectives. Researchers in faculties and public institutes are traditionally rewarded based on academic accomplishments, such as publication of scientific 122 TTOs around the world are relatively young institutions. For example, in Japan more than 90 percent were established after 1990 and even in the United States the TTO median age was only 12 years in 2006 (Phan and Siegel 2006). 123 Phan and Siegel 2006. 132 papers, more than, for example, obtaining or licensing patents or collaborating with the business sector. But in Russia, scientists seem to massively engage in a (limited) commercialization process. 3.63. More than half of Russian TTOs pay their personnel using both the university/research institution pay scale and incentives, bonuses, and success fees related to performance. Research in other countries has shown that career opportunities for university technology licensing officers are limited and often short, which implies difficulties in recruiting and retaining appropriate talent. 124 This is especially true for technology transfer officers with broad-based commercial skills that may be better used elsewhere. In Russia, a significant share of TTOs give their personnel performance-related payment to complement the institutional pay scale, even though they are public employees (figure 3.9). 3.64. Russian TTOs perform several other activities besides technology transfer. Only 40 percent of TTOs had technology transfer as their main activity. Other main activities are coordination of R&D (13 percent), consulting (11 percent), and training (11 percent). 3.65. As a result, proceeds from technology transfer are marginal. Russian TTOs’ budgets come mainly from the parent institution, averaging 40 percent. Other important sources are consulting fees (18 percent) and fees received as a broker for university/research institution contract research (10 percent). License royalties and equity in new companies represent 7.3 percent and 3.6 percent of the average TTO budget, respectively (figure 3.10). 3.66. Russian TTOs reliance on public support is not unusual but the income from technology transfer activities should increase in the future. Some level of public support to the TTO in the initial years may be necessary, because fixed and operational costs are not negligible while returns tend to be small, and the licensing to patenting ratio is very low; returns from spinoffs need time to mature and contract research will only develop in gradual steps. Despite evidence that specific TTO activities that favor new venture creation include early-stage technology and licensing for equity, such a strategy is the least likely to be favored by the university and thus unlikely to be used. Evidence from the United States confirms that TTOs are concentrated in short-term cash maximization, because the main mechanism favored by most TTOs was licensing for cash (72 percent), with licensing for an equity stake and sponsored research less popular at 17 percent and 11 percent, respectively.125 3.67. Russian TTOs and/or their parent institution tend to provide accompanying innovation services. Half of TTOs report offering both incubation and prototyping services. The presence of auxiliary innovation services is welcome, as most research results need further development before they reach a phase where they can be patented or commercialized (figure 3.11). In the United States, from inventions licensed in a five-year period, TTOs reported that 45 percent were at the proof of concept stage, 37 percent were laboratory prototypes, 15 percent were manufacturing-ready technologies, and 12 percent were market-ready inventions.126 124 Phan and Siegel 2006. 125 Markman and others 2005. 126 Thursby and others 2001. 133 Figure 3.9 TTO personnel Figure 3.10 Sources of TTO Figure 3.11 Additional services payment system, 2010 income, 2010 provided by TTO or parent institution, 2010 8% 20.4 21% 20% 39.5 13% 51% 54% 18.4 18% 15% 0.4 9.9 7.3 0.5 3.6 univ. pay scale and bonus from parent institution incubator and prototyping services licenses royalties in 2010 only univ. pay scale equity in new companies only incubator ss broker for research only bonus rent of space only prototyping ss rent of equipment consulting fees none additional ss other payment system other Source: World Bank/MoES survey, 2011. 3.68. Patent applications through TTOs are made mostly in Russia but patenting abroad is negligible. On average, each TTO applied for 34 local patents. The total 1,715 patents represent around 5 percent of total patent applications made in Russia. Patent filing in the European Patent Office and U.S. Patent and Trademark Office is almost nonexistent – on average, not even 1 patent is filed annually. 3.69. The TTOs surveyed initiated around a third of start-ups based on research discoveries. Of the 612 IP-based start-ups reported by the MoES, 200 were founded using licenses of the TTOs’ parent institution technology. Technology Transfer from R&D in Defense 3.70. Russian R&D discoveries in defense could be a major source of civilian innovation, but their use remains limited. The Soviet industrial base is still the core of Russia’s high-tech industries: advanced materials, nuclear power, aerospace, and other sectors of the defense industry. In Soviet times, the connection between military-oriented industries and R&D institutions was intense. R&D institutes were integral parts of the organizations of higher ministries, which coordinated all stages of innovation.127 However, there have not been major spillovers of technology to the civilian sector, because most of the discoveries in defense R&D have remained secret and are inaccessible to the private sector, and because much of the technology developed, especially in Soviet times, falls in the category of know-how as opposed to patents, making commercialization difficult. 127 Yegorov 2009. 134 3.71. The government still owns a large proportion of defense firms, and sector consolidation efforts are under way (box 3.2). Nowadays 40 percent of firms in the defense sector are fully government owned, 40 percent are mainly private (government has 25 percent or less ownership), and the rest have significant government participation. Russian defense firms are relatively small and there are government efforts to consolidate the industry by creating large holding companies.128 Box 3.2 Commercializing the discoveries of Russian weapons scientists In 2007, LARTA, a U.S. nonprofit, private corporation devoted to accelerate the market readiness of early- stage enterprises, worked with several Russian companies on a very small-scale program funded by the U.S. Department of Energy – the Global Initiative for Proliferation Prevention. The objective was to get the start-ups ready to present at a LARTA-produced conference to penetrate the U.S. market. They were essentially “pitch sessionâ€? training. The short-term program focused on supporting former Soviet Union weapons engineers and scientists who were leveraging their skills for the development and marketing of commercial products or services. The program aimed to increase the capacity of the supported institutions and businesses through: x Initial assessments of the Russian companies to identify capacity-building needs. x Remote group training and short-term individualized mentoring sessions, where U.S.-based experts and principal advisors worked with Russian companies on preparing their business presentation. x Two web seminars provided to participants to familiarize them with issues of importance to commercialization, including one focused on building a market-ready presentation tailored to specific audiences relevant to the companies. x Support in networking with U.S. partners. x Participation in LARTA’s venture forum in the United States, where companies presented to investors, industry leaders, and potential customers. The program included six companies from among 34 applicant companies in a broad range of sectors. The technology commercialization stemming from discoveries of scientists formerly engaged in the defense sector were: x Kinetic Technologies. It entered a joint R&D project with a large U.S. aerospace products manufacturing company. Kinetic was founded in 1998 by scientists and engineers from Moscow State University and the Russian research center, Kurchatov Institute. The leading specialists from the top Russian federal research laboratories collaborate with KINTECH in a wide range of high-tech applications – plasma science, nuclear science, hydrogen energy, aerospace, and chemical industries. x Attometrix. It received a follow-up discussion from a U.S. venture fund. The firm was founded in 2004 and specializes in building bio-analytical devices and nano-biotechnology. x BIOCHIP-IMB. It reported an engagement in a business partnership with a company that it met through LARTA, thus saving it over half a year of business development. It builds biochips for medical diagnostics and other applications. x International Center for Electron Beam Technologies (ICEBT). It signed a business deal with a large U.S. coatings company. ICEBT offers medical substances, electron beam technology, heterogeneous solid- phase or liquid-phase colloid systems, and nanoparticles of metals and/or oxides for the medical, pharmaceutical, and food additives/nutrients industry. 128 Crane and Usanov 2010. 135 3.72. Foreign companies have been interested in commercializing Russia’s research discoveries through acquiring IP and joint ventures. Foreign investment in Russia’s R&D has been highly correlated with the defense-conversion strategy pursued by Western countries both through multinational enterprises as well as government agencies in the 1990s, an approach that continues today. The strategy focuses on acquiring Russian R&D outputs or engaging in joint R&D in sectors where Russia had technological leadership. Different pieces of evidence show that the type of relations established at that time are still used.129 3.73. The main Russian counterparts for foreign R&D investment have been research institutes affiliated with the RAS and their scientists and, less importantly, with design bureaus and universities. These institutions – where much of the most advanced technology resides – do not produce any final product or service, as they were established to do research for enterprises that designed or produced military equipment.130 The main channels through which foreign companies have invested in R&D in Russia are subcontracting, large-production joint ventures, small spinoff joint ventures, wholly owned R&D laboratories, and funding research by academic laboratories or academic institutions. Policy Recommendations x Transfer full ownership (not only use) to public research organizations including transferability rights (with minimum royalty payment to research team). This can be accomplished for all research institutions by amending Civil Code Section IV and Federal Law 217 as they both apply to the research institutes’ part of the RAS and the higher education institutions (universities). x Expand commercialization efforts to include technologies stemming from R&D in the defense sector, which includes market-friendly IP management. Early-stage Financing 3.74. Firms view lack of access to financing as the major impediment to commercializing R&D outputs. Among firms polled in an enterprise survey conducted by the Interdepartmental Analytical Centre, 57 percent cited funding difficulties as the major impediment to such commercialization.131 3.75. In Russia, a large majority of firms rely on retained earnings to finance R&D, and the shortage of own funds and the cost of borrowing are the principal barriers to investment and innovation, notably affecting small and medium enterprises. R&D activities in Russia are highly concentrated in large firms, while the gap between desired and actual levels of R&D activity, as a share of turnover, is much higher for smaller firms. Access to finance appears to be much more constraining for start-ups and small and medium enterprises. 3.76. The Russian government has taken steps to address the lack of funding through the creation of the Russian Venture Company (RVC). 132 RVC was established in accordance with Resolution No. 838-p of 7 June 2006 to stimulate the creation of the venture investment industry and 129 Crane and Usmanov 2010; Bernstein 1999. 130 Bernstein 1999. 131 Gianella and Tompson 2007. 132 Other government funds include the Investment Foundation of the Russian Federation; Open Joint Stock Company Russian Band for Development; and the Open Joint Stock Company Russian Investment Foundation for Information-Communication Technologies. RVC is the biggest. 136 considerably increase funding for such venture foundations, development of innovation industries, and access to world markets for Russian science–intensive technological products and services (Box 3.3). Box 3.3 The Russian Venture Company The sole shareholder of OJSC Russian Venture Company (RVC) possessing 100 percent of its equities is the Russian Federation represented by the Federal Foundation for Promotion of Small Enterprises in Science and Technology. As a result of two competitions conducted by OJSC RVC in 2007 and 2008 there were established 7 venture foundations with the total capitalization of RUB19.98 billion (US$670 million): 5. VTB Venture Foundation (net asset value of RUB3.09 billion, US$104 million). 6. Bioprocess Capital Ventures (net asset value of RUB2.9 billion, US$102 million). 7. OJSC Alliance ROSNO Assets Management (foundation size of RUB3.06 billion, US$102 million). 8. LLC Maxwell Asset Management (foundation size of RUB3.06 billion, US$104 million). 9. CJSC Leader (foundation size of RUB3 billion, US$102 million). 10. LLC Managing Company North Asset Management (foundation size of RUB1.8 billion, US$60 million). 11. CJSC Managing Company CenterInvest (established foundation size of RUB2 billion, US$67 million). As of July 1, 2009, two foundations (CEIF VTB-Venture Foundation and CEIF Bioprocess Capital Ventures) financed 14 innovation companies with a total amount of RUB1.74 billion (about US$60 million), while the total number of projects analyzed by all foundations exceeds 1,500. As of August 2010, 10 RVC– backed funds ran a portfolio of 31 companies, with invested capital totaling RUB4.5 billion (about US$150 million). Among the main areas for investments by the established venture foundations are biomedical technologies, power engineering and energy saving, ICT systems, software manufacturing technologies, and “critical technologies.â€? Note: CEIF is ; CJSC is closed joint stock company; LLC is limited liability company; OJSC is open joint stock company; VTB is . 3.77. Venture capital investors are forced to invest in mature and/or foreign companies and are particularly affected by the lack of viable exit strategies due to the underdevelopment of the market for initial public offerings and the lack of depth of financial markets. Statistics from the Russian Venture Capital Association show that 80 percent of investment capital is dedicated to financing restructuring or business expansion and only 20 percent is earmarked for early-stage financing of new companies. Several of the leading Russian funds have searched for an answer by investing in international projects or by copying Western projects, but without any real technological innovation. The best example of this is the fund Digital Sky Technologies, investing in Facebook, ICQ, Vkontakte, Mail.ru, and others. 3.78. The problem with investing in Russian start-ups is the lack of investment projects that fit the investment criteria, rather than an absolute lack of sufficient volume of investment capital. Also, Russian technology start-ups lack experience in developing business plans that reflect the fundamentals required for equity investment, and lack access to affordable legal, accounting, and consulting services that are required to prepare an “investableâ€? business plan and to properly protect their IP. 3.79. There is an almost total absence of early-stage venture capital (or “angelâ€? investors) in Russia, because venture capital is aimed at assisting business growth at a later stage. Although 137 FASIE provides funding up to RUB3 million (about US$100,000), companies assess the funding gap in the range of RUB10 million to RUB150 million (US$330,000–US$5 million).133 Nevertheless, FASIE’s budget is very limited: it receives 1.5 percent of the federal civilian R&D budget, which amounted in 2009 to RUB1.34 billion (around US$45 million) and in 2010 FASIE to RUB2.55 billion (about US$85 million). 3.80. Early-stage financing through business angels does not cover the financing gap and is not widely used due to mistrust and lack of an entrepreneurial culture. Although the financial gap can be covered on certain occasions by business angels, their requirement is to acquire control of the spinoff, which from the point of view of the entrepreneurs is often not desirable. The idea of becoming a serial entrepreneur – one who funds a company based on IP, nurtures it and sells it, and later starts again with a new company – is not an idea that Russian entrepreneurs seem to like. 3.81. RVC’s seed capital to fund early-stage ventures is not used because the 25 percent co- financing required is hard to obtain for the start-up. RVC launched its RVC Seed Fund in October 2008. Its mission is to invest in Russian innovation-based start-ups promising high-growth opportunities in Russian and foreign IT markets. This RUB2 billion (about US$68 million) vehicle is assisted by a network of venture partners – special entities that have access to academic, technological, and financial resources required for their activities. As of August 2010, the RVC Seed Fund had awarded venture partner status to 58 companies from different regions of Russia. By late 2010, the network included about 100 venture partners. Nevertheless, companies implementing innovation projects at the earliest stages will receive up to 75 percent of the investment required from the Seed Fund, meaning they have to match the remaining 25 percent, which often proves difficult. Policy Recommendations x Provide funding – including matching grants – for early-stage development of technologies to address the financing gap between the FASIE program and venture capital funding. x Enhance the supply of financing and services (including mentoring) to innovative start-ups to prepare a pipeline of venture capital investments. 133 FASIE is a nonprofit state organization, set up in 1994 by the Russian government, to implement state policy for the development and support of small innovative businesses 138 References Aslund, A., S. Guriev and A. Kuchins (editors). 2010. Russia after the Global Economic Crisis Barba-Navaretti, G. and A. Venables. 2004. “Multinational Firms in the World Economyâ€? Bernstein, D. 1999. “Commercialization of Russian Technology in Cooperation with American Companiesâ€?. Center for International Security and Cooperation. Stanford University Cantwell, J. and R. Mudambi. 2000. "The Location of R&D Activities: The Role of Investments Incentives." Management International Review Crane K. and A. Usmanov. 2010. Role of High Technology Industries in Aslund, A., S. Guriev and A. Kuchins (editors) Russia after the Global Economic Crisis Desai, R. and Goldberg, I. (editors). 2008. Can Russia Compete? Brookings Institution Press Gianella, C. and W. Tompson. 2006. Stimulating Innovation in Russia: The Role of Institutions and Policies. OECD. Gokhberg L. and T. Kuztnetzova (2010). “Russian Federation Country profileâ€? in UNESCO Science Report 2010. Graham, S., R. Merges, P. Samuelson, and T. Sichelman. 2009. High Technology Entrepreneurs and the Patent System: Results of the 2008 Berkeley Patent Survey. Berkeley Technology Law Journal Vol. 24:4 Hall, B., J. Mairesse, P. Mohnen. 2009. Measuring the Returns To R&D. NBER Working Paper 15622 Higher School of Economics. 2010. Science and Technology, Innovation, Information Society. Data Book. Moscow INSEAD. 2010. “Global Innovation Index 2009/10â€? Kaartemo, V. 2009. Russian innovation system in international comparison – the BRIC countries in focus Electronic Publications of Pan-European Institute 22/2009 Kane, T. 2010. The Importance of Startups in Job Creation and Job Destruction. Kauffman Foundation Research Series: Firm Formation and Economic Growth Kim, L. 1997. " Imitation to Innovation: The Dynamics of Korea's Technological Learning". Harvard Business School Press Kolesnikov, A. 2011. “Creation and Activities of Spin-off Innovative SMEs in Russian Regions – Key Trendsâ€?. Presentation at the World Bank Series on Russia Export Promotion Strategies. Session 3: Innovation, Commercialization of Research and Spin Of SMEs. Available at: http://web.worldbank.org/WBSITE/EXTERNAL/COUNTRIES/ECAEXT/0,,contentMDK:22956626~pagePK:1467 36~piPK:146830~theSitePK:258599,00.html Lin, J. and C. Monga. 2010. Growth Identification and Facilitation- The Role of the State in the Dynamics of Structural Change. The World Bank Policy Research Working Paper 5313 Litan, R., L. Mitchell, E.J. Reedy. 2007. “Commercializing University Innovations: Alternative Approaches.â€? NBER Working Paper 139 Markman, G., Phan, P., Balkin, D., and Gianiodis, P. 2005. “Entrepreneurship and University-Based Technology Transferâ€?. Journal of Business Venturing 20(2), 241-263. MoES (Ministry of Education and Science of the Russian Federation). 2009. National innovation system and state innovation policy of the Russian Federation. Background Report to the OECD Country Review of the Russian Innovation Policy New York Russian Academy of Sciences. 2010. “Yaroslav Roadmap 10-15-20 – International Experience and the Path Forward for Russian Innovation Policyâ€? OECD. 2003. Turning Science into Business – Patenting and Licensing at Public Research Organisations. OECD. 2010. Measuring Innovation: A New Perspective Phan, P. and D. Siegel. 2006. The Effectiveness of University Technology Transfer: Lessons Learned from Quantitative and Qualitative Research in the U.S. and the U.K. Rensselaer Polytechnic Institute Working Paper in Economics Solimano, A (ed.). 2008. The International Mobility of Talent, Types, Causes and Development Impact, Oxford Thomson, R. and P. Jensen. 2010. The Effects of Public Subsidies on R&D Employment: Evidence from OECD Countries. Melbourne Institute Working Paper No. 11/10 Thursby, J. G., Jensen, R., and Thursby, M. C. 2001. “Objectives, Characteristics and Outcomes of University Licensing: A Survey of Major U.S. Universitiesâ€?. Journal of Technology Transfer 26, 59-72 Tseveen G. and A. Stephan. 2010. Do External Technology Acquisitions Matter for Innovative Efficiency and Productivity?. Deutsches Institut für Wirtschaftsforschung Discussion Papers Watkins A. 2003. From Knowledge to Wealth – Transforming Russian Science and Technology for a Modern Knowledge Economy. World Bank Policy Research Working Paper 2974 World Bank. 2008. Special Economic Zones: Performance, Lessons Learned, and Implications for Zone Development. World Bank. 2010. Innovation Policy: A Guide for Developing Countries. Washington DC. World Bank. 2010. World Development Indicators Yegorov, Igor. 2009. Post-Soviet science: Difficulties in the transformation of the R&D systems in Russia and Ukraine. Research Policy 38 600–609 Zeng D (ed). 2010. Building Engines for Growth and Competitiveness in China Experience with Special Economic Zones and Industrial Clusters. World Bank. Zweig, D., W. Vanhonacker, C.S. Fung, and S. Rosen. 2005. ‘Reverse Migration and Regional Integration: Entrepreneurs and Scientists in the PRC’, Center on China's Transnational Relations Working Paper, 6. Hong Kong: Hong Kong University of Science and Technology. 140 Annex A: The World Bank Enterprise Survey – Data and Methodology For identifying the statistically significant investment climate (IC) effects on economic performance, the analysis uses a simultaneous equations system that relates the interactions between the IC with productivity, demand for labor, exports, foreign direct investment (FDI) inflows, and innovation (product development). Estimation always controls for firm size, region and sector, and yields elasticities and semi-elasticities of IC variables with respect to productivity, employment, wages, export propensity, and FDI propensity. The IC elasticities and semi-elasticities provide a measure of the sensitivity of outcome variables when the IC changes marginally. The sensitivity checks of the estimation results help present results robust to different estimations procedures, total factor productivity (TFP) measures, corrections for endogeneity, and so on. The data used for firm-level analysis are derived from the World Bank Business Environment and Enterprise Performance Survey (the Enterprise Survey), carried out in Russia and other countries in the Europe and Central Asia (ECA) region during 2008–09, with financial and balance sheet data for fiscal year 2007. The final dataset is based on a stratified random sample of manufacturing firms, with stratification variables being size, industry, and region. To ensure a large enough number of large establishments in the sample, a sampling approach that oversampled large firms was applied. The result in Russia is a sample with 777 manufacturing establishments. As a consequence of the particular sampling structure, proper weighting to correct for oversampling of large firms when doing descriptive analysis is a requisite. However, for regression analysis we use unweighted estimations given that we control for that by adding firm size, region, and industry dummies in the estimation, and the stratification is not based on the dependent variable of the regression. To the extent that we want to perform a number of international comparisons of IC conditions, we also use Enterprise Survey data for 27 other ECA countries. A system of equations is used to model the interrelations among the dependent and independent variables. This allows us to evaluate the relative importance of each variable on the sample means of the dependent variable: TFP, exports, FDI, employment, and innovation (proxied by product development; see equations and tables A.1 and A.2). Methodologically, robust micro-econometric techniques have been applied based on Escribano and Guasch (2005, 2008), Escribano and others (2010), and Escribano and Pena (2010). Concretely, we have used an instrumental variables (IV) estimator to alleviate the endogeneity coming from simultaneous casualty bias, controlling for observable fixed effects, with the information contained in the Enterprise Survey dataset. TFPc TFPc log TFPi D TFP  D Exp yi  D FDI TFP Exp yi  D RD TFP FDI yi  D IC TFP RD ICiTFP  D D Di  uiTFP ή logTFP - total factor productivity ή logL - employment log Li D L DTFP W logWi DTFP L logTFPi DExp yi L Exp DFDI L yiFDI DRD Lc yi DIC L RD Lc ICiTFP DD Di  uiL ή logW - real wage all in logs ή yExp - binary variable selecting those firms that export more Expc Expc than 10 percent of sales yiExp D Exp i  D TFP Exp log TFPi  D FDI yi  D RD Exp FDI yi  D IC Exp RD ICiExp  D D D  uiExp ή yFDI - binary variable indicating those firms that are receiving FDI (at least 1 percent of firms’ share is foreign) FDI c FDI c yiFDI D FDI  D TFP FDI log TFPi  D Exp yi  D RD FDI Exp yi  D IC FDI RD ICiFDI  D D Di  uiFDI ή yRD - binary random variable, taking a value of 1 for those firms developing new products or services RD c RD c yiRD D RD i  D TFP RD log TFPi  D FDI RD yiFDI  D Exp yi  D IC RD Exp ICiRD  D D D  uiRD ή D - vector of industry, region, and firm-size variables Table A.1 Structure of equations system Dependent Explanatory variables variables FDI R&D Product Competition Equation 1 TFP Exports Other IC variables inflows investment development variables FDI R&D Product Competition Equation 2 Employment TFP Exports Other IC variables inflows investment development variables Probability of FDI R&D Product Competition Equation 3 TFP Other IC variables exporting inflows investment development variables Probability of R&D Product Competition Equation 4 TFP Exports Other IC variables receiving FDI investment development variables Probability of FDI R&D Competition Equation 5 developing TFP Exports Other IC variables inflows investment variables new products 141 Table A.2 Contribution of the investment climate (explanatory variables) to the dependent variables of the equation Explanatory variables Innovation, quality and Regulatory Infrastructure and Finance and corporate Other control Competition Dependent skills environment logistics governance variables variables Exports ή Dummy for R&D ή Domestic competition (+) ή Manager’s time spent on ή Power outages (-) ή Purchases paid after delivery ή Dummy for decreased investments (+) ή Dummy for informal bureaucratic issues (-) ή Electricity from own (-) sales (-) ή Dummy for new products (+) competitors (+) ή Informal payments in tax generator (-) ή Dummy for quality ή Dummy for more than five inspections (+) certification (+) competitors (+) ή Dummy for gifts to receive ή Dummy for increased certificates (+) prices (-) R&D ή Dummy for new product (+) ή Dummy for informal ή Manager’s time spent on ή Dummy for own generator ή Dummy for incorporated ή Dummy for outsourcing (+) competitors (-) bureaucratic issues (-) (+) company (+) ή Dummy for own website (+) ή Dummy for gifts to get ή Dummy for limited ή Staff – skilled workers (+) construction permits (+) company (+) ή Staff – university education ή Dummy for external audit ή Capacity utilization (-) (+) (+) ή Dummy for training (+) ή Experience of manager (+) TFP ή Dummy for new product (+) ή Domestic competition (+) ή Dummy for gifts in tax ή Shipment losses in exports ή Dummy for loan or line of ή Dummy for incorporated ή Dummy for quality ή Dummy for informal inspection (+) (-) credit (+) company (+) certification (+) competitors (-) ή Days to clear customs in ή Sales paid after delivery (+) ή Dummy for decreased ή Staff with computer (+) exports (interaction) (-) ή New fixed assets financed by sales (-) ή Dummy for training (+) internal funds (+) ή Experience of manager (+) ή New fixed assets financed by equity (-) ή Dummy for subsidies (-) FDI ή Dummy for use of foreign ή Dummy for gifts to obtain ή New fixed assets financed by ή Capacity utilization (+) technology (+) construction permit (-) equity (+) ή Dummy for decreased ή Training of production ή Dummy for payments to ή Dummy for overdraft facility prices (-) workers obtain a contract with the (+) government (-) ή Dummy for checking or savings account (+) ή Dummy for external audit (+) Employment ή Dummy for quality ή Dummy for informal ή Dummy for security ή New fixed assets financed by ή Capacity utilization (+) certification (+) competitors (-) expenses (+) internal funds (+) ή Dummy for incorporated ή Dummy for website (+) ή New fixed assets financed by company (+) ή Staff with computer (-) trade credit (+) ή Dummy for training (+) ή Dummy for loan (+) ή Dummy for external audit (+) ή Dummy for subsidies (+) 142 Annex B: The Agricultural Sector in the Russian Federation Russia’s total land area is 1.7 billion hectares, with roughly a quarter intended for agriculture (402 million hectare in 2009). Of the land intended for agriculture, 49 percent is actual agricultural area (196 million hectare). Figure B.1 shows that by the end of 2009, only 59 percent of the agricultural land was actually used for temporary or permanent cultivation. Land under cultivation in Russia has decreased 38 percent over the past three decades (table B.1), though it has trended upward since 2007. For instance, the grain area in production has fallen considerably in the past two decades, from 63.1 million hectare in 1990 to 47.6 million hectare in 2009, mainly turning into fallow land. However, as a rise in food and grain prices in 2006–08 brought renewed interest to returning the fallow land to production, the area used for grain crops increased, from 75 million hectare in 2007 to 78 million hectare in 2009. Out of the total area under cultivation in 2009, 61 percent was used for cereal grains and pulses, an increase of 7 percentage points since the turn of the decade. The second-largest group was feed crops, amounting to 24 percent. Nonetheless, as a result of the Soviet regime pushing grain production onto marginal land in remote areas, production costs are often very high, and investments in physical and commercial infrastructure for storing, transporting, and exporting grain are, more often than not, inadequate.134 Figure B.1 Structure of agricultural land in 2009 (%) Arableland 28.9% Fallowland Permanentcrops 58.9% 9.5% Hayfield 0.6% Permanentmeadows 2.1% Source: ROSSTAT 2010. Table B.1 Area under crops in Russia (percent) 1980 1990 2000 2007 2008 2009 Total area sown (million hectares) 124.8 117.7 84.7 74.8 76.9 77.8 Cereals and pulses 60.5 53.6 53.8 59.2 60.8 61.1 Industrial (technical) crops 5.0 5.2 7.6 10.9 11.3 11.5 Potatoes, vegetables, melons, and gourds 3.8 3.4 4.4 3.6 3.7 3.8 Forage (feed) crops 30.8 37.9 34.1 26.1 24.1 23.5 Source: ROSSTAT 2010. In 2008, cultivation in Russia (measured by the amount of arable and permanent crops) was ahead of other comparable economies, such as Brazil and China (figure B.2). This is, however, still notably lower than in, for instance, India and Canada. In addition, the agricultural area in Russia amounts to roughly 18 hectares per agricultural population, against only 0.6 hectares in China and 0.3 hectares in India. 134 Liefert, Liefert, and Serova 2009. 143 Figure B.2 Land resources internationally, 2008 100 103.05 120 (haperagriculturalpopulation) %ofagriculturalarea 80 100 Agrculturalland 80 60 60 40 17.99 40 11.80 20 20 0.31 0.63 0 0 India Canada Russia Brazil China Arablelandandpermanentcrops Agriculturalland Source: FAO. [cite all “FAOâ€? sources as author-date and add to references] Productivity and profitability of the agricultural sector Value added by the agricultural sector in Russia accounted for 4.7 percent of GDP in 2009, a sharp decrease from the 16.6 percent share in 1990. There has been a similar drop in employment in the sector, from 14 percent 1990 to 7.8 percent in 2008.135 Both value added and employment in the services sector has increased notably (figures B.3 and B.4). Figure B.3 Sectoral composition of value added Figure B.4 Employment distribution (percent) (percent of GDP) 70 70 60 60 %oftotalemployment 50 50 %ofGDP 40 40 30 30 20 20 10 10 0 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Agriculture Industry Services Agriculture Industry Services Source: World Bank 2011c. Source: World Bank 2011c. Figure B.5 Total crops produced (million tons) 120 3 Agroexports/totalmerchexports,% Totalcerealsproduced(mlntons) 100 2.5 80 2 60 1.5 40 1 20 0.5 0 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Source: FAO. 135 ROSSTAT 2010. 144 The main agricultural products in Russia are cereal grains (mainly wheat, barley, sunflower, and rye) as well as dairy, sugar beet, potatoes, and vegetables. Exports are also highly concentrated in grains (in quantity and value; tables B.2 and B.3). Crop production in Russia has been recovering in the past decade from a slump in the 1990s. Looking at cereals (the major crop output, on the left axis of figure B.5), production increased from a low of 45 million tons in 1998 to 106 million tons in 2008, the same level as in the early 1990s. Similarly, exports of agricultural products increased from 0.8 percent of total merchandise exports in 1999 to peak in 2007 (2.2 percent). Wheat is the main contributor to agricultural exports, with 11.7 million tons exported in 2008. Table B.2 Top 10 production, 2008 (thousands of tons) Brazil Canada China India Russia Sugar cane 645,300 Wheat 28,611 Rice, paddy 193,354 Sugar cane 348,188 Wheat 63,765 Soybeans 59,242 Rapeseed 12,643 Maize 166,032 Rice, paddy 148,260 Cow milk 32,100 Maize 58,933 Maize 10,592 Vegetables 147,869 Wheat 78,570 Sugar beet 28,995 Cow milk 27,579 Cow milk 8,140 Sugar cane 124,918 Buffalo milk 60,900 Potatoes 28,874 Cassava 26,703 Potatoes 4,724 Wheat 112,463 Cow milk 44,100 Barley 23,148 Oranges 18,538 Peas, dry 3,571 Sweet potatoes 80,523 Potatoes 34,658 Sunfl. seed 7,350 Rice, paddy 12,061 Soybeans 3,336 Potatoes 68,760 Vegetables 31,402 Rye 4,505 Ind. ch. m. 10,244 Ind. pigmeat 2,838 Watermelons 67,203 Bananas 26,217 Cabbages 3,170 Ind. cattle 9,054 Ind. cattle 1,280 Ind. Pigmeat 47,178 Maize 19,730 Vegetables 2,221 Bananas 6,998 Lentils 4,043 Cabbages 37,073 Mango, guava 13,649 Hen eggs 2,119 Source: FAO. Table B.3 Top 10 exports, 2008 (thousands of tons) Brazil Canada China India Russia Soybeans 24,500 Maize 2,702 Garlic 1,536 Cake of soyb. 5,146 Wheat 11,720 Sugar raw 13,625 Cake of soyb 1,375 Fruit prp Nes 1,182 Maize 3,537 Barley 1,496 Soybean c. 12,288 Sugar raw 1,334 Apples 1,153 Rice milled 2,474 Sunfl. cake 608 Maize 6,433 Brew dregs 772 Food prep nes 1,051 Sugar refined 1,875 Sunfl. oil 490 Ref. sugar 5,848 Food prep 588 Beans, dry 960 Onions, dry 1,671 Wheat flour 453 Chicken m. 3,268 Bev. non-al 504 Preserv. veg. 903 Raw sugar 1,455 Beer of barl. 346 Soybean oil 2,316 Bananas 477 Tomato paste 817 Rapes. cake 1,119 Food prep 207 Coffee 1,567 Soybeans 370 Rice milled 809 Buffalo meat 460 Bev. non-al 118 Or. juice 1,275 Wine 320 Veg. frozen 767 Cotton lint 440 Bev. Dist. alc 102 Meat-Cattle 1,018 Beer of barl. 314 Waters, Ice 754 Oilseeds cake 385 Pastry 91 Source: FAO. Several factors have contributed to the emergence of Russia as a major grain exporter. The overall contraction of the livestock sector has played a part in Russia’s shift from importing grain and producing meat to exporting grain and importing meat.136 Rather than facing strong domestic demand for grain to feed a large livestock industry, Russia today is instead exporting grain produced at home. Also, growth in grain production has contributed to increasing exports. While, as mentioned, the area under cultivation for grain is considerably smaller today than two decades ago, grain production has been rising since the 2000s, as a result of growing yields. Russia’s grain yields grew from a low of 1.3 million ton per hectare in 1998 to 2.3 million ton per hectare in 2009. In addition, favorable weather for most of the 2000s has allowed grain production to prosper.137 A recent report by the OECD and FAO estimates that Russian exports of wheat could surge by more than 60 percent and are expected to reach as much as 26 million tons by 2019. This projection indicates that by 2019 Russia could surpass the United States, currently the world’s largest wheat exporter (figure B.6). 136 Since the opening of markets and privatization of agricultural land in the early 1990s, Russia’s earlier high meat production has decreased considerably, being replaced with high meat imports. Meat production has dropped from 10.1 billion tons in 1990 to an average of 4.8 million tons per year over 1996–2005. In recent years, as a result of government initiatives to increase self-sufficiency, this value increased to 6.7 million tons in 2009. 137 Liefert, Liefert, and Serova 2009. 145 Figure B6 Main wheat exporters Figure B7 Wheat production and price USA EU Canada Australia Russia Totalexports 70 250 160 140 60 200 Production,mlntons 120 50 Price,$/ton Miliontons 100 40 150 80 30 100 60 20 40 50 20 10 0 0 0 Note: Forecast for 2010–19. Source: FAO. Source: OECD and FAO 2010. The increasing wheat production has been Figure B.8 Cost and output of wheat, Russia and Canada accompanied by strongly increasing wheat 1200 30,000 prices (figure B.7). Price per ton increased Producerpriceindexforwheat, 1000 25,000 from US$49 in 1993 to a high of US$205 in Annualyeald(hg/Ha) 2008. A notable decrease in prices in 2009–10 800 20,000 1992=100 has come as the result of a large grain crop in 600 15,000 2008. Compared with Canada, however, another major exporter of wheat, price 400 10,000 volatility in Russia has been much more 200 5,000 prominent. Output of wheat has been almost consistently higher in Canada than in Russia 0 0 1992 1994 1996 1998 2000 2002 2004 2006 2008 over the past two decades (figure B.8). YealdRussia YieldCanada ProducerPriceRussia ProducerPriceCanada Source: FAO. Structure of the agricultural sector and land ownership Privatization and the reorganization of land in the 1990s led to the surfacing of several legal forms of private agricultural enterprises and steep reductions in state ownership. Large farms – so-called agricultural organizations – dominate the agricultural sector in Russia, accounting for 75 percent of sown land. However, these farms produce only 45 percent of total output (table B.4). Private household plots have increased their share in output (47 percent in 2009), while operating on roughly 4 percent of land and producing mainly for own consumption. There are also peasant farmers (including individual entrepreneurs). As with the agricultural organizations, they are commercially oriented, accounting for 7.5 percent of output in 2009 and operating on one-fifth of the land. These peasant farmers emerged as a result of active public policies in the early 1990s that aimed to build up individual family-type farming in Russia. Table B.4 Structure of agricultural output, current prices (%of total) Land area sown (% of total) 1970 1980 1990 1995 2007 2008 2009 2009 Agricultural organizations 68.6 71 73.7 50.2 47.6 48.1 45.4 75.3 Private household plots 31.4 29 26.3 47.9 44.3 43.4 47.1 4.4 Peasant farmers - - - 1.9 8.1 8.5 7.5 20.3 Source: ROSSTAT 2010. 146 Agricultural organizations were responsible for 78 percent of total grain output in 2008. This is, however, a decreasing share (from 91 percent in 2000), as peasant farms stepped up their grain production from 8.4 percent in 2000 to 21 percent in 2009. Other key outputs by agricultural organizations include sugar beets, sunflower seeds, and eggs (71–89 percent of total production). Private household plots produce only a fraction of the grain output but instead dominate in potatoes, vegetables, and fruit (71–84 percent). Peasant farmers, though still not a major producer group, have been the most dynamic of the farm groups, steadily increasing their production share, particularly in sunflower grains, wool, and sunflower seeds (21–29 percent of total production in 2008). The initial privatization process, which began in 1991, was based on the redistribution of land held by collective and state farms in the form of land shares to individuals (equal shares to each farm worker, pensioner, or employee of social services in agriculture), creating “joint share companies.â€? These shares could in turn be withdrawn from the collective for establishing own farms or kept as shares in joint cultivation.138 As a result, agricultural organizations today acquire land through lease contracts with individual shareholders or leasing of land plots from individuals who have already withdrawn their land shares. Transfer of land ownership through leasing or purchase of shares from the original shareholders to legal entities is becoming more common. Although a majority of agricultural land has been privatized, most of this land is represented by land shares and not by ownership of actual plots (only 6 percent of agricultural land in 2003). As only a land plot and owned land can be used as collateral, this type of land structure, along with high technical barriers to meeting basic requirements when mortgaging land, limits the effective control of land, along with much of the farmer’s incentive for future investment.139 In addition, World Bank (2006) notes that a sizable – albeit diminishing – group of unprofitable and inefficient enterprises are being sustained through state support for political and social reasons. Another trend is the emergence of agroholdings – complex institutional arrangements involving the takeover of insolvent farms’ assets by outside investors whose core business is outside the agricultural sector. Agroholdings are commercially oriented (as opposed to production for own consumption), have a multifarm structure, and consist of a consolidation of agricultural organizations, processing, and independent services units, with controlling stock belonging to one common holder.140 They operate mainly in grain production, as this sector represents the largest export opportunities. These companies are today the main investors in upgraded machinery, farm equipment, and modernization of primary agriculture, bringing new investments and technology to the industry.141 The legal structure of agricultural land in Russia is quite complex and is regulated by several acts, covering property registration, peasant farmers, cadastral legislation, and tax regulations. Although the legal reforms were already under way in the early 1990s, the issue of land ownership was not regulated until 2003, with the introduction of the Federal Law on Agricultural Transactions. A key component of this act is the issue of land sales, giving the local government preferential rights to buy land, with the seller required to formally notify the local government of the intent to sell the land. Similarly, an individual shareholder who wishes to either sell its land share or convert it into an actual land plot must inform the other shareholders as well as the local government. Moreover, the law stipulates that agricultural land is to be kept solely for agricultural use, with possibilities for regional governments to impose limits on the physical concentration of land by a single owner and with some restrictions on sales of agricultural land to foreigners (only leasing being permitted). There have been numerous changes to this law, however, and it continues to be amended. Public agricultural policies and support programs142 In addition to increased interest rates, as a response to the high inflation rates in 2007–08, there have been several other active measures taken by the Russian government to reduce inflation in food prices: x Price freezes. The government reached a voluntary price restraint agreement with major food producers and retailers to control retail prices on “socially importantâ€? food products, including bread, eggs, milk, and sunflower oil. The agreement lasted from October 2007 to April 2008. 138 Shagaida and Lerman 2008. 139 Shagaida and Lerman 2008. 140 Rylko and others 2008. 141 Liefert, Liefert, and Serova 2009. 142 Key sources of information on support programs and federal budgets are OECD (2009a) and USDA Foreign Agricultural Service (2010). 147 x Direct input subsidies. To mitigate higher energy prices, farms are provided subsidies for fuel costs for sowing. They also receive subsidies for mineral fertilizer, chemicals, and high quality seeds purchases, as well as for transporting seeds. Pig meat and poultry farmers receive per-ton subsidies. x Grain commodity interventions. These were implemented during October 2007–June 2008, through large releases of grains (nearly 85 percent of total intervention stock), mainly in industrial centers and regions with high grain imports. This pattern was reversed as a result of a large grain harvest in 2008, and the government initiated grain purchase interventions in late 2008. x Trade-oriented measures. Import duties on key foodstuffs were temporarily reduced to combat high inflation, including tariff cuts for dairy products, vegetables, and vegetable oil. Duties on poultry and eggs imported for breeding were removed. Export-restriction measures were also imposed in late 2007 through duties on wheat, meslin, and barley exports. As a way to prevent wheat and meslin outflows through the customs union, exports of these grains to Belarus and Kazakhstan were temporarily banned. These duties were removed in mid-2008, in response to large grain harvests. However, as a result of severe drought and wildfires in the summer of 2010, the government re-imposed bans on grain exports, expected to last until mid-2011. Russia’s trade deficit in the agricultural sector reached US$13.2 billion in 2009 and is mainly the result of large meat imports. The government has introduced a strategy to support investments in the meat industry so as to increase meat self-sufficiency, with beef, pork, and poultry subject to tariff rate quotas and allocated to countries on a historical import basis (box B.1). Box B.1 Evolution of Russia’s tariffs quotas (TRQs) for meat Russian meat production declined rapidly following the collapse of the Soviet Union. As a result, meat imports increased fast to sustain domestic demand. In 2002, Russia implemented meat TRQs for beef, pig meat, and poultry. The life span of the initial TRQs expired by the end of 2009, with amendments made starting in 2006. However, to promote domestic production, by restricting over-quota imports, the Russian government introduced prohibitive out-of-quota tariffs for pig meat and poultry. In December 2009, the government approved a decree to regulate meat imports to Russia in 2010–12. According to the law, the quota on poultry imports will be almost halved – from 952 kt in 2009, the quota for pork will gradually decline, while for beef it will rise. These TRQs have been developed taking into consideration the different trends of the various meat sectors. For poultry, the TRQ has been significantly reduced to reflect the desire of the Russian government to promote the development of the industry, which has grown recently by 10–15 percent per year. It is expected with the current level of protection that Russian producers will be able to mostly meet domestic demand for poultry products after 2015. In the case of pig meat, the reduction in the quota reflects the slower growth in demand combined with an inadequate supply level from the domestic market. Nevertheless, it is not expected that Russian producers will catch up on the current gap between supply and demand. Finally, an increase in beef imports is expected, as beef production in Russia is closely linked to the dairy herd. It is likely that the dairy herd will continue its long-term decline, leading to a reduction of domestic slaughtering. In accordance with the new trade regulations for 2010–2012, new tariffs have been adopted for all meat products. The allocation of quotas among countries has been worked out by the Russian authorities. Source: OECD and FAO 2010. The Russian government has heavily increased investment in the agricultural sector in the past five years, by initiating a comprehensive policy framework focusing on sustainable rural development, sustainable use of agricultural land, and an increase in Russia’s share of world agricultural production. In a short time, several strategic policy programs have emerged, focusing on mid- and long-term development goals. Key documents focused on agricultural development are below. x The Federal Law on Development of Agriculture (2006) sets out six broad objectives: improved competitiveness and quality of agricultural products; sustainable rural development and improved living standards of the rural population; conservation of natural resources used in agriculture; development of an 148 efficient agricultural market and improvement of market infrastructure; improvement of the investment climate in the agrofood sector; and agricultural input-output price parity support. x The State Program for Development of Agriculture Table B.5 Financial sustainability support under 2008–2012 succeeded the National Project for the State Program for Development of Agriculture, Development of the Agro-Industrial Complex 2006– aggregate spending, 2008–12 (percent of total) 2007 in setting out agricultural support measures. Capitalization of Rosselkhozbank 3.31 With a planned budget of RUB551 billion over the Capitalization of Rosagroleasing 2.05 five-year period, the program is laid out in Reduction of agricultural production risks 10.80 accordance with the 2006 Agriculture Law. Major Interest rate subsidies 83.84 shares of this budget are aimed toward financial Agricultural organizations 59.15 sustainability of agriculture (53 percent of total funding) and sustainable rural development (20 Smallholder farms 11.67 Technological modernization 13.02 percent). The three other components are the creation of basic conditions for agricultural production (13 Source: OECD 2009a. percent), development of priority agricultural sectors (12 percent), and regulation of agricultural markets (1 percent). Financial support is planned to increase by 30 percent in 2010 (against the 2009 allocation), with interest rate subsidies as the major tool (table B.5). Subsidies will continue to support already initiated projects as well as new investments in, among others, dairy, livestock breeding, and primary processing of meat and milk. Major shares of subsidies will be allocated to agricultural organizations and household farms. Other investment support implemented under the state program include programs for state leasing of agricultural machinery and pedigree livestock (Rosagroleasing) and capital grants for farm construction and land improvements (Rosselkozbank). x Other major public programs include the Program on Social Development of Rural Areas and the Federal Program for Soil Fertility Enhancement and Rehabilitation of Agro-landscapes as Russia’s National Heritage, both initiated in 2002 and extended until 2012. The latter program provided RUB41 billion in funding in 2008–10, mainly through subsidies and capital investments.143 x Measures to return agricultural land into cultivation are being taken by individual regions, for instance, through subsidized costs of physical delimitation and registration of land ownership rights, land allocation to owners of land shares, and regulatory simplifications in agricultural land transaction.144 x The state-owned United Grain Company was established in 2009, with the role of domestic grain market regulator and investor in grain market infrastructure (transport, storage, and ports). United Grain aims to invest an estimated RUB52 billion by 2015 to reduce handling costs for grain exports, thus achieving higher competitiveness for the Russian grain industry. Over the next three years, United Grain will receive RUB3 billion in government funding and plans to raise at least RUB10 billion from private investors. A recent key development is that the government, as part of the 2011–2013 Russian Privatization Plan, plans to sell 100 percent of its shares in the company by 2012.145 x The Russian Academy of Agricultural Sciences is responsible for providing support for research in the agricultural sector. Its main functions include developing and financing research programs, supporting and providing training to scientists from higher education and research institutions in the agricultural sector, and improving international cooperation. One outcome of the broader agricultural support program has been more clearly defined responsibilities of federal and regional governments in agricultural policies. The federal government – mainly through the Ministry of Agriculture – is responsible for formulating broad policy objectives, market interventions, and the development and financing of nationwide support programs in agriculture. Regions are, however, responsible for locally executing the federal programs. In 2009, it was envisaged that federal funds would be distributed to regions on the basis of matching funds. This has, however, proven difficult as numerous regions have been unable to cofinance projects, something that has resulted in planned decreases in the required share of cofunding from 50 percent in 2009 to 35 percent in 2010. The Ministry of Agriculture also plans to better select projects qualified for funding and to tighten control over their implementation. This will be done through selection of eligible projects by a special commission with representatives from banks, unions, and relevant ministries, based on, among other things, compliance of 143 Russian Grain Union 2010. 144 OECD 2009a. 145 Bloomberg Businessweek 2010a 149 socioeconomic development targets, the economic viability and pay-off period of the project, and the preservation or increase of jobs.146 Assuming that the current and planned support measures continue as anticipated, the OECD-FAO Agricultural Outlook 2010–2019 estimates that the Russian agricultural sector could experience 26 percent growth by 2019, relative to the 2007–09 base period. 146 USDA Foreign Agricultural Service 2010. 150 Annex 1A: A Note on the Gravity Model This annex explains the estimation of the gravity model used to assess the observed level of exports between Russia and its trading partners. Based on a theory-grounded model, this exercise allows us to compare pair-wise export relationships with the predicted value from the gravity equation. Bilateral export relationships are then labeled as undertrades (overtrades) if the realized export value is lower (higher) than what the model predicts. Given the divergence between our preliminary findings, reported earlier, and related research from the Centre for Economic and Financial Research at New Economic School (CEFIR), this annex explains our methodological approach and highlights the particular aims and constraints of this exercise. Particular attention is given to the Russia–China trade relationship. During the review meeting for this report, it was pointed out that the fact that Russia overtrades with China was at odds with related research from CEFIR where China and Russia undertrade one with another. In that respect, meeting participants suggested assessing this issue by considering the fact that the usual definition of distance may not be appropriate to Russia given the large size of the country.147 It was also suggested to account for the long border both countries share and, if plausible, to explore variations in trade patterns between Russian regions and the rest of the world. To assess this concern, we rerun our gravity specification sequentially from 2006 to 2008 and add a dummy variable for contiguity, which partly addresses the “distortionâ€? of the distance measurement. We also check the robustness of the results to alternative definitions of the distance variable and to the exclusion of the oil and gas sectors.148 The main finding is that the year of the analysis affects the result regarding the evaluation of the Russia–China export relationship. From this exercise it is apparent that Russian export value to China has progressively increased over time and it is getting closer to the predicted level. Since our evaluation of Russia export relationships must pick up Russian average bilateral trade patterns rather than year-specific events, our chosen specification estimates the gravity model for the average export value for 2006–08. Under this setup, Russia slightly undertrades with China. This result is robust to alternative definitions of distance. Considering only nonoil (and nongas) exports, exports to China are what the model predicts. We employ a “Russia-centeredâ€? gravity model to evaluate Russia’s trade patterns. We run a cross-country regression on Russia’s exports (using mirror data) on the following bilateral characteristics with trading partners: distance, contiguity, common language, colony, common colonial power, as well as log of GDP, and log of GDP per capita. We incorporate three innovations to the standard model. First, a measure of remoteness is computed by summing distances weighted by the share of GDP of the destination in world GDP. This is to note that relative distances matter greatly, alongside absolute distances. Second, we control for zero trade flows with the use of the Heckman sample selection correction method. When observations with nonexistent bilateral trade are dropped, as OLS does, our dependent variable is not really measuring bilateral trade, but one contingent on a relationship existing. An important variable left out of the model therefore is the probability of being included in the sample – that is, having a nonzero trade flow. To the extent that the probability of selection is correlated with trade costs (distance), this has the potential to bias OLS estimates. Third, we address heterogeneity of firms, following the Helpman, Melitz, and Rubinstein (2008) framework, by controlling for firm heterogeneity without using firm-level data using the fact that the features of marginal exporters can be inferred from the export destinations reached. We use an index for common religion across country pairs to satisfy the exclusion restriction.149 With these steps, the gravity result of whether a country overtrades or undertrades with a particular trade partner is better grounded on trade theory. The equation we estimate is: ÂŽÂ?ሺܺ௜ ሻ ൌ ߚ଴ ൅ ߚଵ ÂŽÂ?ሺ‫ܦ‬௜ ሻ ൅ ߚଶ ÂŽÂ?ሺ‫ܲܦܩ‬௜ ሻ ൅ ߚଷ ÂŽÂ?ሺܲ‫ܲܦܩܥ‬௜ ሻ ൅ ߚସ ÂŽÂ?ሺܴÝ?݉௜ ሻ ൅ ߚହ ܿ‫Ý?݊݋‬௜ ൅ߚ଺ ݈ܽ݊݃௜ ൅ ߚ଺ ܿ‫݈݋‬௜ ൅ ߚ଻ ܿ‫݈݋ܿ݉݋‬௜ ൅ ß?௜ 147 The typical measure of distance consists of the great circle formula (in kilometers) between the most important cities (in population) in two countries. The source of the data is CEPII (2004). 148 Given the overreliance of Russia on its oil and gas exports, it is instructive to do this exercise with and without these sectors. 149 Helpman, Melitz, and Rubinstein (2008) argue that while common religion strongly affects the formation of trading relationships it does not explain the overall export value between country-pairs. 151 Where ܺ௜ is the average value of Russian exports to country Ý… . The set of countries are the 182 economies reported in the Doing Business database. Ü´Ý?݉௜ is the remoteness variable explained above. ‫Ý?݊݋ܥ‬௜ Ç¡ ݈ܽ݊݃௜ Ç¡ ܿ‫݈݋‬௜ Ç¡ ܽ݊݀ܿ‫݈݋ܿ݉݋‬௜ are dummy variables that are equal to 1 if Russia shares a border with country Ý… , share a language with country Ý…Ç¡ has ever had a colonial link with country Ý… , and had a common colonizer after 1945, respectively. We define distances between Russia and country Ý… ሺ‫ܦ‬௜ ሻ as the “great circleâ€? distances between Moscow and the respective capitals of the partner country. Given Russia’s size, there may be a problem with this definition, as, for example, a country like Morocco is deemed closer to Russia than China, even though Russia shares an extensive border with the latter. One way to resolve this problem was proposed by Gros and Steinherr (1995), who disaggregated Russia’s economic space into several macro-regions, whose distances to Russia’s trading partners were estimated separately. In our analysis we confine ourselves to adding a dummy variable for contiguity, which in part addresses the “distortionâ€? of distance measurement. Specification of the gravity model differs from that of most models employed in the related literature, reflecting the particular aims and constraints of this exercises. This model investigates only Russia’s exports to other countries, as opposed to the bilateral trade setup of most gravity models. This country-centered specification is not unusual and allows us to focus on the idiosyncratic patterns of Russia’s foreign trade through a more precise modeling of the country-specific parameters. 150 In this way, we can predict Russia’s bilateral exports based on country-specific coefficients rather than on the average coefficient from a multicountry-type regression. Running the model year by year from 2006, it is notable how Russian exports to China have been expanding over time. In 2006, the gravity model predicts a slightly higher export value to China than the observed level. This difference is not observed in 2007 when the realized export value to China is very similar to the model prediction. Finally, in 2008 exports to China are slightly larger than what the model forecast (figure 1A.1). Figure 1A.1 Russian exports to China, 2006–08 Predicted v Actual Exports Predicted v Actual Exports 20 20 Log of Predicted Exports, 2007 Log of Predicted Exports, 2006 CHN CHN 15 15 10 10 5 5 5 10 15 20 5 10 15 20 Log of Actual Exports, 2006 Log of Actual Exports, 2007 Predicted v Actual Exports 20 Log of Predicted Exports, 2008 CHN 10 5 15 5 10 15 20 Log of Actual Exports, 2008 Source: UN Comtrade 150 See, for example, Hufbauer and Oegg (2003) and Lissovolik and Lissovolik (2004). 152 To assess the average trade patterns in Russia, we rerun the gravity model for the average export value in 2006–08, our preferred specification (figure 1A.2). Under this setup, Russia slightly undertrades with China. While results are robust to consider population weighted distance measures,151 they change a bit when we do not consider the oil and gas sectors (figure 1A.3). Russian exports to China are approximately what the model predicts indicating the fact that around 14 percent of Russian nonoil exports are directed to China over this period. Figure 1A.2 Total exports Figure 1A.3 Nonoil and nongas exports Predicted v Actual Exports Predicted v Actual Exports 20 Log of Predicted Exports, 2006-2008 Log of Predicted Exports, 2006-2008 CHN DEU 18 IND USA ITA DEU IND USA ITA CHN JPN 16 15 JPN BRA BRA 14 12 10 10 8 5 8 10 12 14 16 18 8 10 12 14 16 18 Log of Actual Exports, 2006-2008 Log of Actual Exports, 2006-2008 Source: UN Comtrade Source: UN Comtrade 151 Distance between two countries based on bilateral distances between the biggest cities of those two countries, the intercity distances are weighted by the share of the city in the overall country’s population. 153 Annex 1B: An Extended Version of the Product-space Analysis Exploring the network of relatedness between products, the product-space analysis indicates what merchandise goods a country exports competitively, which goods are closer to the ones currently produced, and whether the country has undergone a structural transformation over time. Applying the tools pioneered by Hidalgo and others (2007) to Russia, the product-space maps below indicate all tradable products at the four-digit Standard International Trade Classification level, with the black dots representing exports in which Russia has a revealed comparative advantage (RCA). The hypothesis is that firms that build up competence in producing a certain good can redeploy their human, physical, and institutional capital more easily if they seek to produce goods that are “nearbyâ€? those that they are producing already. This is predicated on the idea that structural transformations are not smooth movements along a continuum but a messy process beset by market failures. When such market failures are binding, it is harder for firms to hop longer distances without government coordination and support. In the analogy of Hidalgo and others (2007), the product/dots are trees that group themselves to form dense and sparse parts of a forest. Location of firms in the denser parts of the forest creates more opportunities for technological upgrading and structural transformation because market failures are less binding when firms have to make smaller adjustments to move to produce “nearbyâ€? goods requiring similar capacities. The center of the product-space, for example, is quite dense with better connectedness among industries related to metallurgy, vehicles, machinery, and the like. To the bottom right of the product-space lie the more sophisticated electronics and chemical industries. The scattered industries on the upper half are largely agricultural and resource-based. Countries that succeed in transforming themselves over time from producing unprocessed natural or agricultural goods and labor-intensive manufactures (such as footwear and garments) to more sophisticated manufactured products like machinery and chemicals tend to see higher rates of economic growth. Figure 1B.1 shows the products in which Russia has RCA in 2006–08 (black dots) on the product space map. This analysis reveals three things. First, Russia’s product space map has 97 products in which the country has achieved RCA. Second, the products in which Russia has developed comparative advantage are mostly in the periphery of the product space map and have few connections to other sectors, which imply that gaining comparative advantage in other sectors is more difficult since the capabilities needed to produce its current export basket are not easily redeployed to other sectors. Third, the products in which Russia has developed RCA are mainly resource-based: raw materials (26 products), forestry (11 products), cereals Figure 1B.1 Comparative advantage and the product (9 products), and oil and gas (3 products), though the space, Russia, 2006–08 country also developed comparative advantage in nonresource-based industries like capital-intensive goods (13 products) and chemicals (14 products). The following figures classify Russia’s exports into four categories. Figure 1B.2 shows a group of products that Russia has consistently been competitive in. There were 68 products with an RCA greater than 1 in both 1992–94 and 2006–08. These are mainly products from the extractive industries such as petroleum, natural gas, coal, aluminum, and nickel. It labels some of the top products from this category with at least 1 percent in Russia’s total exports in 2006–08. There is no product that represent at least 1 percent of Russian exports (with RCA>1) firmly embedded in the denser part of the product space. There were 29 major products that did not have an RCA greater than 1 in 1992–94, but did in 2006–08. Source: Authors’ calculations 154 Figure 1B.3 shows some of these “emergingâ€? products with at least a 0.2 percent share of national exports in 2008. New products in which Russia has developed RCA are roughly in the same sectors as the competitive products: mainly resource-based commodities like copper, wheat, and silver, and some low tech products such as sheets and plates of iron and steel. The third category is of “marginalâ€? products that Russia exported both in 1992–94 and 2006–08, but with an RCA of less than 1. There were around 30 of such marginal exports. Figure 1B.4 illustrates a few of these with national export share in 2008 of at least 0.05 percent. With external facilitation, some of these products could be upgraded and made more competitive. They include spirits liquors, leather, works of art, and cement. The fourth category includes goods that were competitive in 1992–94 but no longer in 2006–08. There were more than 46 major products in that category. Figure 1B.5 shows some of them with at least a 0.1 percent share of national exports in 1992–2008. 155 Figure 1B.2 Russia’s competitive products, 1992/94–2006/08 [2820] Waste and scrap metal of iron o r steel [6725] Blooms, billets, slabs & sheet bars of iron or steel [6672] Di am onds, unwork, cut • [3330] Petrol oils and crude oil [34 14 ] Petroleum gases and other gases [5623] Mineral or chemical ferti lizers ..~ Ia • • [6831] N ickel & nickel alloys [24 71] Sawlogs and veneer logs of conifers [3222] Other coal, whether or not pulverized • 156 Figure 1B.3 Russia’s emerging products, 1992/94–2006/08 [6746] Sheets & plates of iron or steel, rolled [6822] Copper and copper alloys, worked • • a [412] Other wheat (inc luding spelt and meslin), unmilled • [412] Durum wheat, unmilled [68 11 ] Si lver, unwrought, unworked [274 1] Sulphur of all kinds 157 Figure 1B.4 Russia’s marginal products, 1992/94–2006/08 [6612] Portland cement [7822] Special purpose motor lorries and vehicles * 158 Figure 1B.5 Russia’s declining products, 1992/94–2006/08 [97 10] Gold [2882] Other non-ferrous metal waste and scrap [263 1] Cotton, not / . 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