A REBALANCING CHINA AND RESURGING INDIA A Rebalancing China and Resurging India: How will the pendulum swing for Russia? This report is written by staff and consultants of the World Bank. The findings, interpretations and conclu- sions expressed herein are those of the authors and should not be attributed in any manner to the Board of Executive Directors the World Bank or the governments they represent, the Government of the Russian Federation, or any of the reviewers. Any mistakes found in the report are the sole responsibility of the authors and the World Bank does not guarantee the accuracy of the data included in this work. ISBN 978-5-9618-0085-2 © The World Bank, The World Bank Group, 2017. www.worldbank.org Printed in Russia Alex Publishers alexpublishers.ru A Reader’s Guide This report assesses the future impact of two dynamically transforming economies – China and India – on Russia’s economy. China is rebalancing its economy whereas India is rapidly expanding. What does this hold for Russia? The report begins with a snapshot of findings, followed by eight chapters. Chapter 1 motivates the topic and identifies analytical and empirical gaps that this report fills. Chapter 2 examines the current pattern of trade between Russia and the two countries, and it discusses how important – or not – China and India’s economies are for Russia. Chapter 3 follows by summarizing the results of three complementary approaches for measuring Russia’s trade potential with China and India (and also the rest of the world). Chapter 4 intuitively describes the customized methodology developed for this report; its major caveats and assumptions, and its possible extensions (technical details, for those interested, are in the annexes). Chapter 5 outlines four plausible scenarios of the potential impact on Russia of changes in China and India, and chapter 6 presents the results. Chapter 7 explores the sensitivity of results to changes key in assumptions. Finally, chapter 8 concludes with emerging policy implications for Russia. Contents A Snapshot of Findings ...................................................................................................................................................................... 11 1. Exploring the Trinity of China, India, and Russia: Why it Matters?.................................................................................. 21 2. Russia’s Pivot East? Exploring Current Trade Patterns......................................................................................................... 25 3. From Under-trading to Over-trading: Boosting Russian Exports to China and India.............................................. 33 Measuring Russia’s trade openness ........................................................................................................................................ 33 (i) The gravity model of trade: Russia under-trades with many countries ................................................................ 34 (ii) Russia’s revealed comparative advantage: Beyond primary products, construction and transport services stand out .................................................................................................................................................................... 37 (iii) Examining Russia’s trade complementarity index: There is greater complementarity with India than with China ....................................................................................................................................................................... 39 4. Methodology, Caveats, and Extensions ................................................................................................................................... 41 5. Simulating the Future: Presenting Four Key Scenarios ...................................................................................................... 45 6. Simulating the Future: Presenting the Results ...................................................................................................................... 47 6.1. Scenario 1 – China’s Slowdown: This would have little impact on Russian growth but a more substantial impact on welfare .......................................................................................................................................... 47 6.2. Scenario 2—China’s Rebalancing: This would have small, positive effects on growth and welfare in Russia .................................................................................................................................................................................... 52 6.3. Scenario 3—India’s Expansion: This would significantly boost Russian exports but have little impact on growth or welfare ............................................................................................................................................ 57 6.4. Scenario 4—India’s expansion, China’s slowdown and its rebalancing: This combination would have little net impact on Russia ....................................................................................................................................... 61 7. Simulating the Future: A Discussion on Sensitivity ............................................................................................................. 63 8. The Swinging Pendulum: Policy Implications for Russia ................................................................................................... 71 Bibliography ........................................................................................................................................................................................... 73 Annex 1: Mapping Between the ENVISAGE Model and GTAP Database .......................................................................... 77 Annex 2: Literature Review- Impact of Transformations in China....................................................................................... 83 Annex 3: Foreign Direct Investment in Russia ........................................................................................................................... 87 Annex 4: Supplementary Tables and Figures Related to the Simulation Scenarios ..................................................... 91 Annex 5: Russia’s Current Trade Patterns ..................................................................................................................................... 93 Russia, China, and India’s Trade and FDI Flows ...................................................................................................................... 93 Composition and direction of Russia’s merchandise and services trade ..................................................................... 93 Sectors contributing to Russia’s export growth .................................................................................................................... 98 Annex 6: Presentation of the CGE model..................................................................................................................................... 99 Contents 5 Figures Figure 1: Growth in China has consistently exceeded the global growth rate .............................................................. 21 Figure 2: Data on consumption and investment reveal little rebalancing in China..................................................... 23 Figure 3: China’s share of services in GDP is rising ................................................................................................................... 23 Figure 4: Growth in India is highly cyclical, but it is trending upwards ............................................................................ 24 Figure 5: China is an important trading partner for advanced economies and EMDEs (2015) ................................ 25 Figure 6: Russia’s trade with China has expanded sharply (USD, billions) ....................................................................... 26 Figure 7: Russian exports to China consist mostly of fuels, 2015 ........................................................................................ 26 Figure 8: Russian imports from China are mostly manufactures, 2015 ............................................................................ 26 Figure 9: Russian exports to India are increasing but remain small (USD, billions) ...................................................... 27 Figure 10: Russian exports to India are not dominated by fuels, 2015 ............................................................................. 28 Figure 11: Russian imports from India are diverse, 2015 ....................................................................................................... 28 Figure 12: Russia’s GVC participation as a buyer and seller, 2011 ....................................................................................... 28 Figure 13: Russia’s GVC participation as a seller across manufacturing sectors, 2011 ................................................ 29 Figure 14: Russia’s value added in China and India’s exports (as a share of total foreign value added) ............... 30 Figure 15: China and India’s value added in Russia’s exports (as a share of total foreign value added) ............... 30 Figure 16: Russia’s net FDI inflows from China are greater than those from India........................................................ 31 Figure 17: Russia’s trade openness is below that of countries with a similar level of development, 2015 .......... 33 Figure 18: Commercial services trade is related to per capita income, 2015.................................................................. 34 Figure 19: Russia’s export potential in 2015................................................................................................................................ 35 Figure 20: Russia’s export potential in 2015, non-oil and gas exports .............................................................................. 36 Figure 21: Russia has been gaining market share in exports of transport services...................................................... 38 Figure 22: Russia’s trade complementarity index (goods and services) with India is greater than that with China ................................................................................................................................................................. 39 Figure 23: Russia’s services trade complementarity with China and India has fallen .................................................. 40 Figure 24: Russia’s services export growth has been less than China’s import growth (top) but has exceeded India’s import growth (bottom) in most services sectors ............................................................. 40 Figure 25: Russia’s share of world trade remains constant under the reference scenario ......................................... 46 Figure 26: China’s share of Russian exports rises and Europe’s share falls under the reference scenario ............ 46 Figure 27: China’s growth falls significantly in the slowdown scenario ............................................................................ 47 Figure 28: Exports to China from all regions decline in the slowdown scenario........................................................... 48 Figure 29: The drop in China’s imports is larger in primary products than in manufactures .................................... 48 Figure 30: Global market dependence on China differs greatly by region ..................................................................... 49 Figure 31: Russian exports to non-Chinese markets are higher than in the reference scenario due to lower prices ........................................................................................................................................................................ 49 6 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 32: Russia’s exchange rate depreciates as a result of the China slowdown ....................................................... 50 Figure 33: Russian exports of primary products are sharply lower in the China slowdown scenario ................... 50 Figure 34: The China slowdown would boost non-oil tradable sectors ........................................................................... 51 Figure 35: The China slowdown has little impact on Russian growth ............................................................................... 52 Figure 36: The China slowdown has a substantial impact on household welfare in Russia...................................... 52 Figure 37: China’s rebalancing involves a shift from investment to private consumption ........................................ 53 Figure 38: Rebalancing significantly changes the composition of China’s import demand ..................................... 54 Figure 39: Rebalancing has positive impacts on regions exporting agriculture and high-skilled services......... 54 Figure 40: China’s rebalancing significantly affects the composition of Russian exports .......................................... 55 Figure 41: China’s rebalancing results in an appreciation of Russia’s real exchange rate .......................................... 55 Figure 42: China’s rebalancing has a small positive impact on Russian growth ............................................................ 56 Figure 43: China’s rebalancing would slightly improve household welfare in Russia ................................................. 56 Figure 44: Higher growth in India would significantly increase exports to India as well as global exports........ 57 Figure 45: The impact of expansion on India’s imports differs by product ..................................................................... 58 Figure 46: After OPEC, China has the largest share of exports to India ............................................................................ 58 Figure 47: India’s expansion has the largest impact on exports of Russian primary products ................................ 59 Figure 48: The impact of India’s expansion on Russian GDP growth is small ................................................................. 60 Figure 49: The impact of India’s expansion on household welfare in Russia is also small ......................................... 60 Figure 50: Most regions’ exports to China are lower in the combined scenario............................................................ 61 Figure 51: The impact of the combined scenario on Russian growth and welfare is small ....................................... 61 Figure 52: The China slowdown scenario – Growth and household welfare are higher with a fiscal deficit financed through current expenditures adjustment ............................................................................ 64 Figure 53: The India expansion scenario – GDP and household welfare are lower if the exogenous fiscal balance is financed through increased current expenditures.............................................................. 65 Figure 54: China’s slowdown – a larger oil price decline results in lower GDP and welfare in Russia.................... 66 Figure 55: India’s expansion – A greater oil price response would boost GDP and welfare in Russia ................... 67 Figure 56: China’s slowdown – GDP is lower with Impediments to labor mobility ...................................................... 68 Figure 57: India’s expansion – the rise in GDP is smaller with impediments to labor mobility................................ 69 Figure 58: China’s rebalancing – Russia’s growth is higher but exports are lower with higher FDI inflows from China .......................................................................................................................................................... 70 Figure A3. 1: FDI inflows into Russia (USD, millions ................................................................................................................. 87 Figure A4. 1: The impact of the combined scenario (scenario 4) on Russia’s exports differs by sector................. 90 Figure A5. 1: Russia’s declining export performance............................................................................................................... 94 Figure A5. 2: Russia’s market share in the goods trade ........................................................................................................... 95 Figure A5. 3: Composition of Russia’s trade in services, 2015............................................................................................... 95 Figure A5. 4: Evolution of Russia’s sectoral services exports................................................................................................. 96 Figure A5. 5: Trends in Russia’s trade in commercial services ............................................................................................... 97 Figure A6. 1: Nested structure of production ............................................................................................................................. 100 Figure A6. 2: How import decisions are made ........................................................................................................................... 101 Figure A6. 3: How export decisions are made............................................................................................................................ 101 Contents 7 Tables Table 1: Russia’s export potential: Trade with China and India, 2015 ................................................................................ 36 Table 2: Russia’s export potential: Non-oil and gas trade with China and India, 2015 ................................................ 36 Table 3: Russia’s revealed comparative advantage in selected merchandise sectors ................................................. 37 Table 4: Russia’s revealed comparative advantage index for services sectors, 2015 ................................................... 38 Table A1. 1: Mapping between model and GTAP factors of production .......................................................................... 76 Table A1. 2: Mapping between model and GTAP sectors ...................................................................................................... 76 Table A1. 3: Mapping between model and GTAP regions ..................................................................................................... 79 Table A3. 1: Russia’s net FDI inflows by sector, 2015 ................................................................................................................ 88 Table A3. 2: Russia’s net FDI inflows and outflows by country, 2015 ................................................................................. 89 Table A5. 1: Export Performance of the world’s 10 largest economies ............................................................................. 93 Table A5. 2: Russia’s main service trading partners – 2015.................................................................................................... 96 Table A5. 3: Sectoral contribution to Russia’s export growth, 2005-2007 to 2013-2015 ............................................ 98 Boxes Box 1: Benchmarking Russian bilateral export relationships using a gravity model of trade .................................. 35 Box 2: Trade diversification and productivity: Literature review ......................................................................................... 43 Acknowledgments This report was prepared by a World Bank team led by Apurva Sanghi (Lead Economist for the Russian Federation and co-TTL) and Andrew Burns (Lead Economist, co-TTL). Calvin Djiofack (Senior Economist) and Dinar Prihardini (Economist) were the lead modelers, ably assisted by Eleanor Dalgleish (Consultant), Jagath Dissanayake (Consultant), Olga Emelyanova (Research Analyst), Claire Honore Hollweg (Economist), Irina Rostovtseva (Research Analyst), and William Shaw (Consultant). Farah Manji (Consultant) provided editorial assistance, and Marina Koroleva (Program Assistant) provided logistical support. Andras Horvai (Country Director for the Russian Federation), Maria De los Angeles Cuqui Gonzalez Miranda (Practice Manager, Macroeconomics and Fiscal Management Global Practice for Europe and Central Asia), and Dorota Nowak (Country Program Coordinator) provided overall guidance. We are especially grateful to the following peer reviewers for their careful and thoughtful comments: Alexander Morozov (Director, Department for Research and Forecasting, Central Bank of Russia), Vladimir Kolchyev (Deputy Minister of Finance, Russian Federation), Vladimir Tsibanov (Director, Budget Policies and Strategic Planning Department, Ministry of Finance, Russian Federation), Gabriel Di Bella (Resident Representative for Russia, IMF), Junaid Kamal Ahmad (Country Director for India, World Bank), Bert Hoffman (World Bank Country Director, China), and Hans Timmer (Chief Economist, Europe and Central Asia, World Bank). In addition, the team has benefitted greatly from conversations and discussions with World Bank colleagues, notably Cecilia Heuser, Aaditya Mattoo, Sebastian Saez, Frederico Gil Sander, and H.E. Pankaj Saran, Indian Ambassador to Russia. For queries, please contact the corresponding author, Apurva Sanghi, at “asanghi@worldbank.org”. Abbreviations ASEAN-5 Indonesia, Malaysia, the Philippines, Singapore, and Thailand BOP Balance of Payments BRI Belt and Road IniƟaƟve BRICS Brazil, Russia, India, China, and South Africa (emerging economies) CES Constant elasƟcity of subsƟtuƟon CET Constant elasƟcity of transformaƟon CGE Computable general equilibrium CIS Commonwealth of Independent States FDI Foreign direct investment ECA Europe and Central Asia EFTA European Free Trade AssociaƟon EMDEs Emerging and developing economies EU European Union FSGM Flexible System of Global Models GDP Gross domesƟc product GTAP Global Trade Analysis Project GVC Global value chains IAMC Integrated Assessment Modeling ConsorƟum IMF InternaƟonal Monetary Fund LES Linear expenditure system LPI LogisƟcs Performance Index, World Bank MFMOD Macro-Fiscal model OECD OrganizaƟon for Economic CooperaƟon and Development OPEC OrganizaƟon of the Petroleum ExporƟng Countries RCA Revealed comparaƟve advantage ROW Rest of the World SSP Shared Socioeconomic Pathways TCI Trade complementary index VAR Value at Risk A Snapshot of Findings A. RUSSIA PIVOTS TOWARDS CHINA AND INDIA 1. Like most nations, Russia’s economic prospects are closely linked to its ability to export and penetrate new dynamic markets. However, Russia’s trade performance has been rather modest in the last decade, with the country under-trading compared to countries at a similar level of economic development. Russia’s export to GDP ratio declined from 33 percent during 2005-2007 to about 28 percent in 2013-2015. Although traditional trade partners in Europe, the Organization for Economic Cooperation and Development (OECD), and the Commonwealth of Independent States (CIS) remain the top destinations for Russian exports, under the rubric of initiatives such as BRICS, Russia is beginning to deepen its economic relationships with new dynamic markets such as China and India. In the global market, China is now the world’s second largest importer after the United States, and in many metal markets, it represents more than half of global demand. Russia’s trade with China has increased substantially in recent decades: Merchandise trade between the two countries almost tripled over the past ten years. In addition, Russia’s trade with India has increased more than 15 percent in the last five years. 2. Recent developments also attest to the strengthening of Russia’s trade relationships with both China and India. Russia has publicly voiced its support for China’s One-Belt-One-Road initiative. And the recently concluded St. Petersburg International Economic Forum saw a revival of bilateral trade measures between Russia and India, which go beyond defense and into areas of pharmaceuticals, agriculture, automobile components, and mining and metallurgy. 3. Net FDI inflows from China to Russia have also increased substantially as net inflows from the rest of the world declined. Although net FDI from India to Russia is low, Russia reported positive net outward FDI to India for 2008, 2010, and 2013. Overall, Russia’s FDI flows are diversified across countries. 4. However, the current level of Russian exports to both China and India are below their natural potential. A gravity model analysis suggests that Russia has an untapped potential to increase merchandise exports to China by around 24 percent of its actual exports in 2015, and by nearly 17 percent to India1. The potential gap between Russia and China is bigger than that with India, indicating a higher prospect to increase Russian merchandise exports. This finding reflects the bigger size of the Chinese economy (compared to India), as well as the geographical proximity between Russia and China as captured in the gravity model. For example, China is able to benefit from Russia’s commodity exports but for reasons of geography and logistics, India is not. Nonetheless, the current pattern of below-potential trade also indicates untapped opportunities for Russia to grow its total exports. 5. Russia’s integration in the global value chains of China and India is also limited. A global value chain index (GVC), which measures Russia’s value added embodied in exports of China and India as a share of total foreign value added embodied in these exports, is low. In total, Russia has less than a 3 percent market share in China and less than a 2 percent market share in India (measured on a value-added basis). 6. Russia has a revealed comparative advantage (RCA) in several merchandise industries and also in some services sectors. Unsurprisingly perhaps, Russia has a revealed comparative advantage in merchandise sectors, predominantly natural resource-based industries. Surprisingly perhaps, Russia also has a revealed comparative advantage in key services sectors, including construction (due to nuclear plants – an area where India can continue to benefit) and transport services. As discussed in the report, Russia’s share of global transport services exports has increased in recent years, and exports of small services sectors, including communications and intellectual property, have also grown faster than the world import growth of these services. 1 A gravity model analysis predicts the level of exports between two economies based on size, income level, distance, as well as whether countries share a common border, whether they share a common language, and whether one was a colony of the other or whether they were colonies of the same country. 12 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? 7. These developments are occurring in the context of significant changes in Russia’s economy. Russia’s economy has been coping with the twin shocks of low oil prices and economic sanctions since mid-2014. It entered a recession period that saw GDP contracting by 2.8 percent in 2015 and 0.2 percent in 2016. However, over the last two years, the government’s policy response package of a flexible exchange rate policy, expenditure cuts in real terms, and emergency bank recapitalization has helped Russia’s economy stabilize. Supported by firming commodity prices, the economy is moving from recession to recovery, with projected growth to be between 1.3 and 1.4 percent between 2017 – 2019 (World Bank estimates). 8. Several sectors are benefiting from the sharp ruble depreciation of 2014-2015, setting in motion a process of diversification, which has been slow. In 2016, the following non-oil sectors recorded export growth: food products, chemicals and rubber, wood and pulp, textiles, metals and metal goods, machines and equipment, transport vehicles. As expected, the relative price adjustment also facilitated the import substitution process, supporting production in several tradable sectors. However, this adjustment is slow due to relatively low levels of spare capacity (the capacity utilization level remained at historically high levels in most tradable sectors), limited availability of labor, and medium-term factors that adversely affect labor productivity. 9. Dynamic changes in China and India’s economies therefore present Russia with both opportunities and challenges. Opportunities come primarily from China’s rebalancing of its demand, which increases the importance of consumption compared to investment, and India’s emergence as one of the fastest growing large economies in the world. Challenges stem mainly from China’s slowdown (which reduces demand for Russia’s commodity exports), low levels of trade flows between Russia and India (compared to Russia and China), and as outlined above, the current sub-optimal Russia-China and Russia-India bilateral trade patterns. The ongoing diversification process is an opportunity as it can position Russia to take advantage of changes in China and India’s economies, but its slow pace – and other structural issues – remain a constraint. B. ASSESSING IMPACT IS A TRICKY AFFAIR 10. The impact of changes in China and India on Russia’s economy is subtle. Beyond first-order, direct effects on bilateral trade, changes in China and India’s economies affect Russia’s economy in subtle and indirect ways. This can happen, for example, because of third-country effects (how changes in China and India affect Russia’s trading partners, that then affect Russia), and through changes in the global price of oil. Another indirect and elusive channel of impact is how a slowdown in China’s economy could have a positive effect on Russia. This is because lower Russian commodity exports to China would lead to a more depreciated ruble, thereby increasing demand for Russian goods from other parts of the world. Another aspect is assessing the impact of changes in China only (holding changes in India constant), and vice-versa, as well as changes in both China and India simultaneously. And yet another subtlety is isolating the impact on Russia stemming from just the China slowdown vs. China rebalancing (and both). Isolating such impacts is necessary not only to get a better understanding of underlying dynamics but also for evaluating appropriate policy levers. 11. This report develops a customized methodology that can capture these subtleties. The analysis develops a computable general equilibrium (CGE) model, customized to address the above-mentioned nuances and subtleties, and through carefully constructed future scenarios, it can assess and quantify such impacts. No methodology is perfect, however, and Chapter 7 notes the caveats and limitations as well as efforts made to overcome at least some of these limitations2. 2 While non-economists like to criticize economists for their models, economists are even more critical. In his 2015 book “Economic Rules”, Dani Rodrik notes that the economist Kenneth Boulding supposedly remarked, “Mathematics brought rigor to economics; unfortunately, it also brought mortis”. In our modeling work, we clearly do not attempt to capture every single aspect of reality; only the most relevant ones. A Snapshot of Findings 13 C. UNFOLDING THE FUTURE: WHAT THE ANALYSIS REVEALS 12. A reference scenario is used as a standard of comparison in measuring the impact on Russia of changes in the global economy. The construction of the reference scenario requires various assumptions about the evolution of the model’s exogenous variables over time (2011-2030). Actual oil prices are used through 2016 (after which they are determined endogenously by the model). The reference scenario assumes that growth in China and India equals the trend before 2013, and the composition of GDP remains unchanged. Russia’s growth follows the World Bank projections of between 1.3 and 1.4 percent until 2019. Growth is assumed to be 2 percent thereafter. Russia’s share of world trade remains at about 3 percent through 2030, but China’s and India’s shares of world trade increase sharply. This trend is consistent with observed growth patterns as both China and India are expected to grow at a rate significantly higher than the global growth rate. 13. The impact on the Russian economy is measured against this reference scenario using four specific alternative scenarios developed for this analysis (Table E.1). These four scenarios are (i) a slowdown in China, (ii) a rebalancing of Chinese demand that increases the importance of consumption compared to investment, (iii) an increase in GDP growth in India, and (iv) all the above three changes simultaneously. The time horizon for the analysis is 2017 – 2030. Table E.1. Recapitulation of scenarios Scenario China growth India growth China composition assumption assumption assumption Reference Pre-2013 trends, 6.5% Pre-2013 trends, 6% Unchanged with investment at 47% of p.a. on average p.a. on average GDP #1 China’s slowdown Slowdown to 4.6% Same as Reference Same as Reference p.a. on average #2 China’s Same as Reference Same as Reference Investment falls to 35.5% of GDP, with rebalancing commensurate increase in household consumption share of GDP #3 India’s expansion Same as Reference Improvement to 8% Same as Reference p.a. on average #4 China’s slowdown Slowdown to 4.6% Improvement to 8% Investment falls to 35.5% of GDP, with and rebalancing, with p.a. on average p.a. on average commensurate increase in household India’s expansion consumption share of GDP #1. The China slowdown scenario: Don’t let me down 14. By itself, the impact of China’s slowdown on Russia’s growth would be small, but the impact on welfare would be more significant. Russian GDP would only be lower by 0.17 percent in 2030 as a result of a slowdown in China (Figure E.1). The key factor driving the GDP effect is the decline in investments due to lower household savings. Slowing growth in China, a major source of global demand for oil and minerals, would reduce the prices of Russia’s natural resources exports (Russia’s principal export), thus reducing the terms of trade and lowering government revenues. The decline in the government’s natural resource revenues would require increased direct taxes to meet the assumed (fixed) fiscal balance. The combined effect of increasing taxation and deteriorating terms of trade would sharply reduce household welfare and savings3. 3 The difference in magnitudes of the effect on GDP vs. household welfare is driven by the assumption of a fixed fiscal balance. This requires an increase in direct taxes to compensate for government revenue losses, which is equivalent of resource transfers from households to gov- ernment. If the assumption of a fixed balance is dropped (as discussed in Chapter 8 on sensitivity), the situation reverses; i.e., the impact on household welfare is low but GDP losses are higher. 14 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure E.1: The China slowdown has little impact on Russian growth but a substantial impact on household welfare Household effect Household effect 0,0 -0,5 Change from Baseline (%) Change from Baseline (%) -1,0 -1,5 -2,0 -2,5 Household utility Household saving Source: Authors’ estimates. 15. A continued slowing of the Chinese economy would have a substantial impact on Russian trade. Growth in China has fallen from 10.5 percent per year from 1990 – 2010 to below 7 percent in 2015. A continued slowing in China, from the current 6.5 percent growth to 4.6 percent by 2030 (while maintaining the historical composition of growth), would result in a fall of Russian exports to China by 17 percent. All Russian sectors are affected, with the magnitude of the shortfall ranging from 8 percent for high-skilled services to 24 percent for natural resources (mainly mining products). By 2030, the level of oil and gas exports, the top Russian export product to China, is 18 percent lower than the reference scenario. 16. However, a slowdown in China would also offer some opportunities for Russia. Compared to the reference scenario, lower demand for Russia’s exports to China would lead to a more depreciated ruble, increasing demand for Russian goods from other regions. This would help to limit the decline in Russia’s total exports (again, compared to the reference scenario) to 3.5 percent by 2030 and provide greater incentives for the growth of non-oil tradable sectors. While Russia’s oil and gas sector would be negatively affected by the China slowdown, the non-oil tradable sector would be better off. Lower exports of primary products entail a 1.7 percent depreciation (compared to the reference scenario) of the Russian real exchange rate by 2030, improving the competitiveness of Russian products in both international and domestic markets (referred to as the “reverse Dutch Disease”). By 2030, Russia’s high-skilled manufacturing exports increase by around 8 percent and low-skilled manufacturing exports increase by 3.1 percent compared to the reference scenario. #2. The China rebalancing scenario: Here comes the sun 17. By itself, China’s rebalancing would have a small positive impact on Russia. We assume that by 2030 the share of consumption in China’s GDP rises by 10 percentage points and the share of investment falls by 10 percentage points while growth continues at the historical trend of 7 percent. By 2030, Russian exports to China would be 0.9 percent higher than in the reference scenario due to rising Chinese demand for oil and agricultural products. However, Russia’s exports to other countries would be lower as the real exchange rate appreciates. The impact on GDP and household welfare would be marginally positive (Figure E.2). A Snapshot of Findings 15 Figure E.2: The China rebalancing scenario has a small positive impact on Russian growth GDP effect Russia GDP by expenditures (% deviation from baseline) 0,04 0,10 0,09 0,08 Сhange from Baseline (%) (%) 0,03 Baseline (%) 0,07 Baseline GDP at constant prices 0,06 Private consumption 0,02 0,05 from from 0,04 Investment 0,04 Change Exports Change 0,03 0,01 Imports 0,02 0,01 0,00 0,00 OECD EU and EFTA India Major OPEC Russian Rest of ECA Rest of the 2030 America no Federation World Mexico Source: Authors’ estimates. #3. The India expansion scenario: Ticket to ride 18. A more rapid expansion in India would lead to substantial demand for Russian exports but only a moderate GDP growth gain. We assume that GDP growth in India increases from a historical average of 6 percent to 8 percent per year through 2030. By 2030, Russian exports to India are 8 percent higher and total Russian exports are 2.1 percent higher than in the reference scenario. Nevertheless, Russia’s GDP is only 0.06 percent higher by 2030 than in the reference scenario (Figure E.3). This is because of the low level of Russia– India trade. The current share of Russian exports to India is barely 2 percent (in contrast to 11 percent for China). Household welfare is marginally 0.3 percent higher by 2030 due to favorable terms of trade. Figure E.3: The impact of India’s expansion on Russian GDP growth is small Russia Russia GDP byby GDP expenditures (% expenditures (%deviation deviationfrom baseline) from baseline) 0,9 0,8 Change from Baseline (%) 0,7 0,6 GDP at constant prices 0,5 Private consumption 0,4 Investment 0,3 Exports 0,2 Imports 0,1 0,06 0,0 2030 Source: Authors’ estimates. 16 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? #4. The simultaneous China slowdown, China rebalancing, and India expansion scenario: All together now 19. A combination of a slowdown in China, a rebalancing of China’s economy, and a more rapid expansion in India would have a small – but negative – impact on Russia. The negative impact of a slowdown in China is not entirely offset by the positive effect of both the rebalancing of China’s economy and the expansion in India’s economy. This is because China is a bigger trading partner for Russia than India, and given that the Chinese share in global trade is about five times the size of India’s contribution, even with a higher growth rate, the positive India effect is not sufficient to outweigh the negative China effect. By 2030, Russian exports to China would be 17 percent lower, its total exports 1.5 percent lower, and its GDP 0.07 percent lower than in the reference scenario (Figure E.4). Figure E.4: The impact of the combined scenario on Russian growth and welfare is small Household effect Household effect 0,2 0,0 -0,2 Change from Baseline (%) Change from Baseline (%) -0,4 -0,6 -0,8 -1,0 -1,2 -1,4 -1,6 Household utility Household saving Source: Authors’ estimates. D. TWEAKING THE MODEL: HOW ASSUMPTIONS AFFECT RESULTS 20. The first sensitivity analysis relates to how Russian fiscal policy responds to changes in China and India. In the scenarios outlined above, the default is that the direct tax rate changes in response to external shocks to maintain a fixed fiscal balance. However, if the fixed fiscal balance is achieved through expenditure cuts, itresults in larger household savings in response to lower natural resource revenues and indirect taxes following a slowdown in China. The combination of reduced government expenditures and larger household savings increase GDP by 0.08 percent above the level than if the direct tax rate increases to compensate for the loss in revenues (Figure E.5). As expected, household welfare is higher with adjustment through reduced government current expenditures than through raising direct taxes. Through a similar but reverse process, more rapid growth in India results in a lower GDP in Russia in the case of reduced government current expenditures rather than an increased direct tax rate (Figure E.6). A Snapshot of Findings 17 Figure E.5: The China slowdown scenario: Growth is lower but household welfare is higher with an endogenous fiscal balance 1,3 2,1 Figure E.6: The India expansion scenario: GDP is higher but household welfare is lower with an endogenous fiscal balance 0,41 0,16 Source: Authors’ estimates. 21. The second sensitivity analysis relates to oil prices. A greater response of oil prices to changes in global demand than what is assumed in our scenarios would magnify the impact on Russia of a China slowdown and an India expansion. In our model, the change in the oil price reflects adjustments to market equilibrium, and thus does not capture major determinants of oil price changes related to speculative forces or price bubbles. A larger fall in the oil price due to a slowdown in China results in lower growth and welfare in Russia, while a larger rise in the oil price, due to more rapid growth in India, results in improved growth and welfare in Russia. 18 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? 22. A third sensitivity analysis relaxes the assumption that labor is perfectly mobile across different sectors of production. Existence of labor market frictions, such as limited access to information, limited mobility, or regulatory restrictions, may impede the movement of labor between sectors. If we assume slower adjustment in labor markets (by lowering labor substitution elasticities), negative external shocks result in a greater reduction in Russia’s GDP and welfare, and positive external shocks lead to a smaller increase in GDP and welfare than with more rapid adjustment. Thus, with slower adjustment in labor markets, by 2030, Russia’s GDP is 0.05 percent lower in response to a slowdown in China compared to more rapid labor market adjustment. Conversely, in response to more rapid growth in India, assuming that labor market rigidities slow adjustment, GDP rises by slightly less4. E. BEYOND THE MODEL: THE SURPRISING ROLE OF FDI 23. A greater increase in FDI outflows as a result of a rebalancing of China’s economy would mean a larger increase in Russia’s GDP. The methodology, as applied, captures changes in the real economy and not those that may occur in the financial sector, such as changes in FDI flows. We address this important macro-financial linkage by simulating an adhoc increase of FDI, equivalent to 1 percent of Russia’s 2017 GDP, spread over the next 12 years (2018 – 2030). The findings are surprising: Russia’s GDP would be 0.9 percent higher – or fifty times greater than the impact in the reference scenario (Figure E.7)5. Figure E.7: Greater FDI inflows from China would result in higher growth in Russia (China rebalancing scenario; % change from baseline) Russia GDP by expenditures (% GAP from baseline in 2030) 1,8 1,6 1,4 Change from Baseline (%) 1,2 GDP at constant prices 1,0 0,91 Private consumption 0,8 Investment Exports 0,6 Imports 0,4 0,2 0,0 2030 Source: Authors’ estimates. 4 In response to changes in prices, the ability of firms to find alternative export markets improves their adjustment to external shocks. The model does not fully consider barriers to trade that may limit substitution in import and export markets. If we halve (compared to the GTAP levels used in the model) the elasticities of substitution between domestic goods and exports, and the elasticities of substitution between exports for different destinations, then growth and welfare in Russia are even lower in response to a deterioration in the terms of trade. Thus, lower trade elasticities mean that Russia’s GDP and welfare decline by more in response to a slowdown of growth in China. Conversely, more rapid growth in India would result in a smaller rise in Russia’s GDP with lower trade elasticities. 5 An increase in FDI increases available capital, reducing its cost and leading to expansion of capital-intensive sectors. A Snapshot of Findings 19 F. POLICY IMPLICATIONS: REAPING REWARDS, LIMITING LIABILITIES 24. Perhaps the most important policy implication for Russia is the urgency to speed up domestic structural reforms. The four scenarios summarized above assumed rapid adjustment in labor and goods markets. Introducing labor market rigidities and impediments to adjustments in goods markets increases the impact of negative external shocks (e.g., a slowdown in China) and reduces the benefits from positive ones (e.g., a rebalancing in China and more rapid expansion in India). These results highlight the potentially high costs to Russia of low labor productivity, immobility, and rising informality (which impede labor market adjustment), and of poor connectivity (which impedes adjustment in goods markets: out of 160 countries, Russia ranks a low 99 in the World Bank’s 2016 Logistics Performance Index (LPI), well below neighboring Kazakhstan and all other BRICS). Another impediment is the existence of non-tariff barriers in countries that trade with Russia, which may limit Russia’s (and other countries’) ability to adjust smoothly to changes in the international economic environment. This therefore underlines the importance of negotiations to reduce non-tariff barriers. 25. The findings also suggest specific areas that merit increased policy attention: a. The finding that Russian exports to both China and India are below their natural potential further underscores the importance of export diversification, particularly reducing dependence on natural resources. In addition, the high level of complementarity between Russian exports and Chinese/Indian imports points to potential positive effects of trade agreements. b. The findings regarding Russia’s revealed comparative advantage point towards deepening efforts to promote diversification into non-oil traded goods (manufacturing) and supporting trade in services, particularly in high-skilled services (e.g., communication, financial insurance, business services, tourism, defense, education, and health services). c. The findings emphasize the importance of policy measures that increase mutually beneficial trade between China, India, and Russia, and by extension, those that increase strategic partnerships between large emerging economies. For example, from being a consumer/importer of Russia’s nuclear machinery, equipment, and technology, India is now positioning itself as a low-cost supplier/exporter of such machinery, equipment, and technologies to Russia, thereby increasing Russia’s global competitiveness in this area. There may well be implications for China’s Belt and Road Initiative (BRI), and efforts to deepen the already thriving cross-border trade along the Russia–China border could yield even more dividends. 26. Finally, FDI emerges as an important contender. FDI is a potentially important channel through which Russia may gain from China, which is increasingly looking for investment opportunities abroad because of its changing economic structure. Given their geographical proximity and shared borders, Russia is in a good position to capture outward flowing Chinese FDI, particularly in its Far East region. Beyond energy, where Indian firms have been acquiring stakes in Russian oil fields for example, there may also be important opportunities for increasing FDI between Russia and India. Potential sectors where Russia can benefit further from incoming Indian FDI include pharmaceuticals, attracting Indian IT firms to invest in Russian techno parks (which would support Russia’s digital economy initiative), and mining and metallurgy in the Arctic. Policy changes that improve the attractiveness of the Russian economy to FDI could therefore have a significant impact on growth. G. CAN THE PENDULUM BE SWUNG? 20 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Overall, the impact of these four scenarios on Russia’s GDP would be small. The seemingly anti-climactic finding may suggest that changes in the Chinese and Indian economies are not of great concern to Russia. Alternatively, these small changes could indicate limits on Russia’s ability to benefit from the opportunities offered by a rebalancing in China and more rapid growth in India. Moreover, the implications of these scenarios for household welfare in Russia are more significant, largely driven by changes in the terms of trade. In general, it appears that likely changes in economic developments in China and India present more of a challenge than an opportunity for Russia, largely due to Russia’s limited non-oil trade with both countries. But if well prepared, changing economic fortunes in China and India may well swing the pendulum in Russia’s favor. 1. Exploring the Trinity of China, India, and Russia: Why it Matters? China’s economy is slowing and there is mixed evidence of a rebalancing of demand from high levels of investment to consumption. At the same time, growth in India is trending upwards. The net impact on Russia of these ongoing changes in China is unclear, and while rising growth in India is intuitively good for Russia and the world as a whole, the size of these effects is unknown. To the best of our knowledge, there is no study that looks specifically at the effects of China and India on Russia. There is also a dearth of quantitative analysis focusing on the effects of a booming India on the global economy. This study therefore fills these gaps. The rapidly changing global environment, and a redefinition of Russia’s relations with its main trading partners, offers Russia both opportunities and challenges. The changes include: (i) the slowdown of China since the financial crisis; (ii) the rebalancing of China’s economy marked by a reduction of investment in favor of consumption; and (iii) the rise of India as one of the largest growing global economies with historical relationships with Russia. These changes are likely to sharply alter the composition of Russia’s trade and have important implications for welfare. Understanding the implications of these changes is critical to designing appropriate domestic policy responses and to eventually leading to a re-shaping of trade agreements and policies. China is facing a period of reduced growth. GDP growth averaged 10.5 percent per year between 1990 and 2010. Even at the height of the Asian financial crisis in the late 1990s, China’s growth remained above 7.5 percent. During the global financial crisis in 2009, when global GDP contracted for the first time in at least 50 years, China’s GDP expanded more than 9 percent, fueled by exceptionally strong domestic stimulus. However, since 2009, the Chinese government has systematically revised growth forecasts down, publicly recognising that the previous rate of growth was unsustainable. China’s growth fell below 7 percent in 2015 (Figure 1). The recent slowdown is unsettling markets and raising concerns among policy makers about the impact on other economies. Figure 1: Growth in China has consistently exceeded the global growth rate Source: World Development Indicators. 22 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? However, analysts disagree on the drivers of the growth slowdown, and thus the implications for China’s prospects. Several papers such as Albert et al. (2015), Pettis (2013), Nabar and N’Diaye (2013), and the World Bank Group (2016) claim that slower growth is a structural trend, driven by slower productivity growth. Anderson et al. (2015) consider it too early to determine whether the slowdown reflects structural or cyclical changes and thus account for both scenarios in their modelling. Dorrucci et al. (2013) argue that the fundamental drivers of rapid growth remain, including rising inward FDI to support investment, coupled with an increasingly sophisticated export basket to boost penetration of new markets. However, the authors warn that continued rapid growth in the near future could have negative implications over the long term by providing policy makers with excuses to postpone needed reforms. Conversely, Albert et al. (2015) argue that the structural slowdown will provide the right economic climate to facilitate rebalancing. Their study highlights similarities between China’s slowdown and the Japanese experience during the 1970s and 1980s, when a sharp deceleration in investment and a gradual consumption slowdown led to a long period of slow growth. The evidence of a rebalancing of China’s economy is mixed. Since 2009, the high investment rate in China has been associated with falling returns to capital and rising non-performing loans, which will test the solidity of the banking sector and could expose vulnerabilities associated with the shadow-banking sector. A rebalancing of China’s economy, marked by a reduction of investment in favor of consumption, is essential to achieve the sustainable growth required for the country to become a high-income economy. Other important elements of this rebalancing could include a shift from manufacturing to services, from inward FDI to outward FDI, and from low-skilled intensive production to high-skilled intensive production. However, investment in China remains high and final consumption has increased very little as a share of GDP, equaling about half of GDP in 2015 (Figure 2). By contrast, the share of final consumption in GDP is 70 percent in India and more than 80 percent in the United States. On the supply side, the share of China’s services sector in GDP has risen from around 40 percent of GDP in 2000 to more than half, while the shares of manufacturing and agriculture have fallen (Figure 3). All of these changes could have far-reaching consequences for China’s economy and the rest of the world. Anderson et al. (2015) argue that rebalancing would soften the negative effects of the economic slowdown and boost the level of output over the long run. Gauvin et al. (2015) elaborate that an ambitious program of economic reforms is essential to prevent sluggish output growth, corporate defaults, and considerable stress on the banking sector, which could lead to a rise in economic insecurity and possibly social unrest. Exploring the Trinity of China, India, and Russia: Why it Matters? 23 Figure 2: Data on consumption and investment reveal little rebalancing in China United States India China 90 90 70 80 80 60 70 70 50 60 60 50 50 40 % of GDP % 0f GDP % of GDP 40 40 30 30 30 20 20 20 10 10 10 0 0 0 2000 2005 2010 2015 2000 2005 2010 2015 2000 2005 2010 2015 Final consumption expenditure, etc. (% of GDP) Final consumption expenditure, etc. (% of GDP) Final consumption expenditure, etc. (% of GDP) Gross capital formation (% of GDP) Gross capital formation (% of GDP) Gross capital formation (% of GDP) United States India China 90 90 70 80 80 60 70 70 50 60 60 50 40 50 % 0f GDP % of GDP % of GDP 40 40 30 30 30 20 20 20 10 10 10 0 0 0 2000 2005 2010 2015 2000 2005 2010 2015 2000 2005 2010 2015 Final consumption expenditure, etc. (% of GDP) Final consumption expenditure, etc. (% of GDP) Final consumption expenditure, etc. (% of GDP) Exports of goods and services (% of GDP) Exports of goods and services (% of GDP) Exports of goods and services (% of GDP) Source: World Development Indicators. Figure 3: China’s share of services in GDP is rising Source: World Development Indicators. 24 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? India has become the world’s fastest expanding large economy, offering opportunities to Russia. India’s GDP growth, while sharply cyclical, has trended upwards over the past 25 years (Figure 4). Its GDP growth, which averaged 5.2 percent per year between 1990 and 1995, increased to more than 7.5 percent in 2015. Going forward, economic growth in India is projected to remain higher than that of China. In June 2017, the World Bank predicted 7.6 percent growth in 2017/18. This is in line with other forecasts. The IMF forecasted resilient growth of 6.6 percent for the fiscal year 2016/17, rising to 7.2 percent in 2017/18. The Center for International Development at Harvard University (2015) projects an average annual growth of 7 percent until 2024. According to The Economist (2010), there are two reasons why India’s prospects are more buoyant than China’s. First, India has a young and growing workforce, unlike the unfavorable dependency ratio in China. Second, aspects of India’s democratic system may be weak, but nevertheless allow for a strong and more innovative entrepreneurial sector and large companies. Figure 4: Growth in India is highly cyclical, but it is trending upwards Source: World Development Indicators. How these changes in two large, dynamic economies play out for Russia is unknown. This report fills this gap by assessing the likely impact of these changes on Russia’s economy as measured by changes in Russia’s trade, GDP growth, and welfare. But impacts also depend on historical and current trading patterns, which is what the next chapter discusses. 2. Russia’s Pivot East? Exploring Current Trade Patterns Russia’s exports to China are substantial but dominated by primary products. In contrast, Russia’s exports to India are more diversified but quite small, largely because of geographical and technical limitations on India’s access to Russia’s main exports of oil and gas. This is also true when looking at bilateral FDI flows as well as trade that takes place in global value chains. China has become increasingly important to the global economy and to Russia China is the largest global trader, exporting almost 60 percent more than the United States, the second-largest global trader. China is an important trading partner for advanced economies as well as emerging and developing economies (EMDEs) (Figure 5). In 2015, the United States, the EU, Hong Kong SAR, China, Japan, the Republic of Korea, and the Association of Southeast Asian Nations (ASEAN)6 purchased about 70 percent of China’s exports. Final goods dominate in China’s exports: consumer goods amount to 36.4 percent of total exports, and capital goods amount to 44.2 percent. Manufactured products are the major component of exports, accounting for slightly over 94 percent of the total exports. Among them, office machines and telecommunications equipment, and textiles and clothing are China’s main exports. China is the world’s second-largest importer after the United States. Capital goods comprise 42.1 percent of its total imports, while raw materials account for 21.8 percent, intermediate goods 18.8 percent, and consumer goods 12.2 percent of total imports. Manufactured products accounted for 64.4 percent of imports in 2015, with the main categories being office machines and telecommunications equipment, and chemicals. Fuels and other mining products accounted for some 21 percent of China’s imports in 2015, while agricultural products accounted for 9.5 percent. Figure 5: China is an important trading partner for advanced economies and EMDEs (2015) Hong Kong SAR, China Share of China in total imports Share of China in total exports Source: UN Comtrade Database. The Chinese economy has also become a global leader in investment. In 2015, investment in China was four times the level in Japan, and it exceeded investment in the U.S. and EU by 35 percent and 25 percent, respectively. Exceptionally strong investment demand in China has created large export opportunities for Western European countries that specialize in the production of investment goods. In many metal markets, China represents more than 50 percent of global demand. This has created significant export opportunities for resource-rich countries, including Russia. 6 Indonesia, Malaysia, the Philippines, Singapore, Thailand,Brunei, Cambodia, Laos, Myanmar (Burma), and Vietnam. 26 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Russia’s trade with China has expanded rapidly over the past two decades (Figure 6). Russia’s exports to China equaled just under $30 billion in 2015, an increase from 5.4 percent of Russian exports in 1996 to 8.2 percent in 2015. China’s exports to Russia rose from 1.6 percent of Russian imports in 1996 to 19.2 percent in 2015, when China was Russia’s second largest partner for imports after the EU. Figure 6: Russia’s trade with China has expanded sharply (USD, billions) Source: UN Comtrade Database. Russia’s exports to China are dominated by natural resources, while its imports from China mainly consist of manufactures. Mineral fuels accounted for 67 percent of Russia’s exports to China (Figure 7), up from 1.8 percent in 1996, due to both robust growth of oil production and the 150 percent rise in oil prices over the period. Other natural resources such as wood constitute about 11 percent of Russia’s exports to China. By contrast, Russia’s services exports to China are small, accounting for only 0.3 percent of China’s US$469 billion of total services imports in 2015. In 2015, raw materials accounted for 67.5 percent of Russia’s exports to China, while intermediate goods totaled 15.6 percent, consumer goods 10 percent, and capital goods 6.8 percent of exports to China. While exports from Russia to China consist mainly of natural resources, manufacturing products comprise about 95 percent of Russia’s imports from China (Figure 8). China’s exports to Russia consist mainly of final goods (capital goods – 42.1 percent of total exports, consumer goods – 33.6 percent of total exports). Intermediate goods account for 12.7 percent of China’s exports to Russia, and raw materials account for 3.3 percent of the country’s exports to Russia. Figure 7: Russian exports to China consist mostly Figure 8: Russian imports from China are mostly of fuels, 2015 manufactures, 2015 Source: UN Comtrade Database. Source: UN Comtrade Database. Russia’s Pivot East? Exploring Current Trade Patterns 27 China’s net FDI to Russia is modest. Only a few years ago, outward FDI from China was negligible, but by 2015, outward FDI amounted to US$167 billion, roughly 70 percent of inward FDI. China’s share of Russia’s net FDI inflows rose from 0.2 percent in 2007 to 10 percent in 2015, largely reflecting declines in FDI from other sources in 2014- 15 due to low oil prices and economic sanctions. The expected rise in outward FDI in China, owing to structural changes in the economy, is likely to present an important opportunity for Russia to capture a larger part of the higher end of the value chain. India is less important as a trading partner to Russia India has also become an important participant in global trade. Its exports of goods and services totaled US$418 billion in 2015, or 1.7 percent of the world’s exports. India’s top merchandise exports during 2013-2015 were petroleum and coke, chemical rubber products, other manufacturing products, textiles, and other machinery and equipment. India has a larger share of services (37 percent) in its export basket than Russia, China, and many other large economies. The telecommunications, computer, and information services sector was the top Indian services export during 2013-2015, followed by other business services, and travel. In 2015, India’s total imports amounted to US$471 billion. Its top merchandise imports during 2013-2015 were oil, petroleum and coke, non- ferrous metals, other machinery and equipment, and electronic equipment. India’s top services imports during the same period were transport, other business services, and travel. Bilateral trade between Russia and India is small. In 2015, Russia exported around US$5 billion in merchandise to India, and imported US$2.3 billion from India, which accounted for just 1 percent of India’s total merchandise trade and 1.3 percent of Russia’s total merchandise trade (Figure 9). Unlike Russia’s total trade, oil and mineral fuels account for only 6.8 percent of Russia’s exports to India (Figure 10). In 2015, Russia’s exports to India consisted mainly of machinery and equipment (24.5 percent), precious and semi-precious metals and stones (22.2 percent), nuclear reactors and parts (11.9 percent), and arms (6 percent). Imports from India consist mainly of pharmaceutical products (20.7 percent), clothing (8.6 percent), tea (6.8 percent), parts for nuclear reactors (6.4 percent), and tobacco (5.4 percent) (Figure 11). Figure 9: Russian exports to India are increasing but remain small(USD,billions) 8 7 6 5 4 3 2 1 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Export Import Source: UN Comtrade Database. India imports around 0.6 percent of its services from Russia. In 2015, India imported US$123 billion worth of services from the world but its services imports from Russia were only around US$742 million. This accounted for 1.4 percent of total Russian services exports and 0.6 percent of total Indian services imports. Around 42.5 percent of India’s global services imports were transport services. Its other top global imports were other business services (24.3 percent) and travel (12.1 percent). 28 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Russia’s trade with India has been growing over the past twenty years, albeit slower than that with China. The share of Russian exports to India increased from 0.9 percent in 1996 to 1.3 percent in 2015 (a 9 percent annual average growth rate in nominal terms). The share of imports from India grew from 1 percent in 1996 to 1.2 percent in 2015 (a 6.7 percent annual average growth rate in nominal terms). Figure 10: Russian exports to India are not domi- Figure 11: Russian imports from India are diverse, nated by fuels, 2015 2015 Other Vehicles Iron Iron Precious stones 13% 3% 0% 3% Inorganic Food items and metals chemicals 22% 4% 3% Electric Other Rubber machinery 32% 3% 5% Paper Organic chemicals 3% 5% Optics Tobacco 4% 5% Fertilisers Iron Nuclear 14% 5% reactors, boilers, Arms machinery 6% 7% Mineral fuels Coffee, tea Nuclear 7% 7% reactors, boilers Electrical Clothing Pharma 12% machinery 8% 21% 8% Source: UN Comtrade Database. Source: UN Comtrade Database. Russia’s links to global value chains (GVCs) that include China and India are limited Russia buys less from GVCs than China and India, but itis an important seller of inputs for further downstream production. Figure 12 shows indicators of GVC participation from the perspective of a buyer (backward participation) and a seller (forward participation). Russia’s participation in GVCs as a buyer – measured as the foreign value added embodied in Russia’s gross exports as a share of gross exports – is lower than in China and India. This holds true for all sectors except agriculture, forestry, fishing, and hunting. Russia’s participation in GVCs as a seller – measured as Russia’s domestic value added embodied in other countries’ gross exports as a share of gross exports – is higher than in China and India, driven by Russia’s forward GVC participation in manufacturing sectors. Figure 12: Russia’s GVC participation as a buyer and seller, 2011 45 Percent of total gross exports 40 35 30 25 China 20 India Russia 15 10 5 0 Total Agriculture Mining, quarrying Manufacturers Services Total Agriculture Mining, quarrying Manufacturers Services Backward participation Forward participation Source: TiVA (2016). Russia’s Pivot East? Exploring Current Trade Patterns 29 Russia’s over performance in its forward participation in GVCs relative to China and India is due primarily to participation from natural resource intensive sectors. Figure 13 shows the forward GVC participation measure across manufacturing sectors – the sector’s domestic value added embodied in third countries’ exports as a share of the country’s total gross exports. Because natural resources are downstream, they tend to be used as inputs for further processing. Countries that tend to sell natural resources are therefore upstream in value chains and exhibit strong forward participation. In Russia, for example, there is over performance in basic metals, other non-metallic mineral products, chemicals and chemical products, coke, etc. Russia appears to be more integrated (as a seller) in the motor vehicles, food and beverages, and tobacco sectors than India or China. But China and India outperform Russia with respect to computer, electronic and optical equipment (and India in textiles, textile products, leather and footwear). Figure 13: Russia’s GVC participation as a seller across manufacturing sectors, 2011 Manufacturing nec; recycling Other transport equipment Motor vehicles, trailers and semi-trailers Electrical machinery and apparatus, nec Computer, electronic and optical equipment Russia India China Machinery and equipment, nec Fabricated metal products Basic metals Other non-metallic mineral products Rubber and plastics products Chemicals and chemical products Coke, refined petroleum products and nuclear fuel Pulp, paper, paper products, printing and publishing Wood and products of wood and cork Textiles, textile products, leather and footwear Food products, beverages and tobacco 0 1 2 3 4 5 6 7 8 Percent of total gross exports Source: TiVA (2016). Similar to the aggregate trends, Russia tends to be integrated in the value chains of China and India as a seller of primarily upstream, natural resource products. Figure 14 identifies how integrated Russia is in the value chains of China and India (and vice versa) by measuring the extent to which Russia sells inputs to China and India that are then used for further processing and export. It measures Russia’s value added embodied in exports of China and India as a share of total foreign value added embodied in these exports. The figure shows that Russia’s integration is quite limited. In total, Russia has less than a 3 percent market share in China and less than a 2 percent market share in India (measured on a value added basis). These are mostly in mining and quarrying (raw inputs), followed by basic metals. 30 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 14: Russia’s value added in China and India’s exports (as a share of total foreign value added) Services Manufacturing nec; recycling Other transport equipment Motor vehicles, trailers and semi-trailers India China Electrical machinery and apparatus, nec Computer, electronic and optical equipment Machinery and equipment, nec Fabricated metal products Basic metals Other non-metallic mineral products Rubber and plastics products Chemicals and chemical products Coke, refined petroleum products and nuclear fuel Pulp, paper, paper products, printing and publishing Wood and products of wood and cork Textiles, textile products, leather and footwear Food products, beverages and tobacco Total manufactures Mining and quarrying Agriculture, hunting, forestry and fishing 0 0,2 0,4 0,6 0,8 1 1,2 Percent of total foreign value added Source: TiVA (2016). China is an important source of inputs for Russian exports. Figure 15 identifies how integrated China and India are in the value chains of Russia. It shows the extent to which China and India sell inputs to Russia that are then used for further processing and export. It measures China and India’s value added embodied in Russian exports as a share of total foreign value added embodied in these exports. China’s market share is 10 percent of total foreign value added, while India’s is less than 2 percent. Surprisingly, this is driven by upstream products such as basic metals, and chemicals and chemical products (though machinery also appears to be important). This may reflect the composition of Russia’s exports and indicate where Russia is in the value chain. Figure 15: China and India’s value added in Russia’s exports (as a share of total foreign value added) Services Manufacturing nec; recycling Other transport equipment Motor vehicles, trailers and semi-trailers Electrical machinery and apparatus, nec Computer, electronic and optical equipment India China Machinery and equipment, nec Fabricated metal products Basic metals Other non-metallic mineral products Rubber and plastics products Chemicals and chemical products Coke, refined petroleum products and nuclear fuel Pulp, paper, paper products, printing and publishing Wood and products of wood and cork Textiles, textile products, leather and footwear Food products, beverages and tobacco Total manufactures Mining and quarrying Agriculture, hunting, forestry and fishing TOTAL 0 2 4 6 8 10 12 Percent of total foreign value added Source: TiVA (2016). Russia’s Pivot East? Exploring Current Trade Patterns 31 FDI flows between Russia, China, and India remain low Net FDI inflows from China to Russia have increased substantially while net flows from the rest of the world to Russia have declined. While Russia’s net FDI inflows from the world fell from US$55.9 billion in 2007 to US$6.4 billion in 2015, net FDI inflows from China rose from US$112 million to US$645 million over this period (Figure 16). However, compared to 2014, FDI inflows from China dropped in 2015, reaching $1.3 billion. Russia’s outward FDI to China is minimal. Although inward net FDI from India to Russia is low, Russia reported positive net outward FDI to India for 2008, 2010, and 2013. For example, in 2010, net FDI to India from Russia reached $600 million. Since 2012, however, net FDI to India from Russia has been zero or negative (in 2014). Figure 16: Russia’s net FDI inflows from China are greater than those from India Source: Central Bank of Russia. 32 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? 3. From Under-trading to Over-trading: Boosting Russian Exports to China and India Russia has significant potential to boost its exports. Its potential for trade growth is greater with China than with India. Indeed, with its current production structure, Russia “over-trades” with China and “under-trades” with India. However, excluding oil and gas, Russia under-trades with both countries. Russia’s revealed comparative advantage (RCA) is almost exclusively in primary commodities, except for construction services due to nuclear plants (an area where India can continue to benefit). Russia also has strong growth potential in transport services and smaller services sectors, including communications, where exports have been growing faster than the world import growth of these services over the last decade. Our analysis relies on a variety of different quantitative techniques to explore Russia’s trade potential with China and India for both goods and services. First, we benchmark Russia’s level of exports and imports of goods and services (as a share of GDP) relative to what is expected given the country’s level of economic development. Second, we identify sectors where Russia currently exhibits a revealed comparative advantage in order to identify those sectors that may offer export diversification opportunities with China or India. Third, we use a gravity model of trade to see if the current level of trade with China and India is below or above the level predicted based on structural factors. And fourth, we use indicators of trade complementarity to identify whether Russia exports products that China and India import. Measuring Russia’s trade openness Russia is under-trading against countries at a similar level of economic development. The trade-to-GDP ratio is one of the most basic indicators of openness to foreign trade and economic integration. By weighting the combined importance of exports and imports of goods and services according to the size of 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 positive relationship between trade openness and per capita income; countries tend to trade more as incomes rise. Figure 17 shows the location of each country in the world along these two dimensions. The fitted line is the expected trade openness given each country’s per-capita GDP. Benchmarking total openness (exports and imports of goods and services relative to GDP) for 2015 shows that Russia’s level of trade openness is significantly below that of other countries at a similar level of economic development. Figure 17: Russia’s trade openness is below that of countries with a similar level of development, 2015 Source: WDI. 34 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Russia’s trade in services is also lower than what is expected for its income level. Scatter plots of GDP shares of commercial services exports and imports against per capita income (Figure 18) also suggest that countries tend to trade more services as income rises. Russia trades less than what is expected for its income level, as do its top trading partners7. This suggests the existence of untapped opportunities for Russia to grow its total exports, including services exports. Figure 18: Commercial services trade is related to per capita income, 2015 Source: WDI. (i) The gravity model of trade: Russia under-trades with many countries One wonders how ‘natural’ Russia’s export linkages are and if there is potential to increase exports after taking into account other structural factors such as geographic proximity or economic size. After all, Russia is a large economy that appears to be already trading at higher levels than other large economies. Therefore, its lower level of openness relative to other countries at a similar level of economic development may be the norm rather than something that merits a raised eyebrow. To answer this question, we benchmark Russia’s bilateral exports by comparing observed bilateral trade outcomes with the predicted outcomes using a gravity model of trade. We can then assess whether bilateral exports are in line with what is expected given a country’s economic mass, bilateral distance, and other determinants included in the model (see Box 1: Benchmarking Russian bilateral export relationships using a gravity model of trade for the specifications of the gravity model and the Annex for the results of the estimations8). 7 We also conducted the analysis after removing countries with a services trade share exceeding 100 percent. Russia and its top trading part- ners were still trading below that which is expected for their level of development. 8 Given the vast difference in both quality and quantity of infrastructure between China and India, it is reasonable to ask whether this modeling approach can capture these differences. While the model can control for the quantity/quality differences if such data are available, the goal, however, in this approach is to control for natural determinants of trade and not observed trade. The residual (difference between natural potential and observed trade) can be explained by policy variables, including differences in infrastructure. From Under-trading to Over-trading: Boosting Russian Exports to China and India 35 Box 1: Benchmarking Russian bilateral export relationships using a gravity model of trade We use a theory-grounded gravity model to evaluate Russia’s export relationships with China and India. The gravity model has been extensively used in international trade due to its intuitive empirical and theoretical appeal. Anderson and van Wincoop (2003), Feenstra (2004), and Baldwin and Taglioni (2006), among others, present exhaustive literature reviews on the gravity equation as applied to international trade. Our specification of the gravity model follows the micro-founded model of Helpman, Melitz, and Rubinsten (2008). Specifically, we regress the log of bilateral merchandise exports for each year from 2005 to 2015 among 224 countries on the following bilateral characteristics: distance (great circle distance between the most important cities in terms of population), contiguity, common official language, colony, common colonial power, log of GDP, as well as time fixed effects, and time-invariant exporter and importer fixed effects. The model controls for zero trade flows with the use of the Heckman sample selection correction method. When observations with non-existent bilateral trade are dropped, our dependent variable is not really measuring bilateral trade, but one contingent on an existing relationship. Therefore, an important variable left out of the model is the probability of being included in the sample; i.e., having a non-zero trade flow. To the extent that the probability of selection is correlated with GDP or distance, this has the potential to bias estimates. The results show that Russia under-trades with many of the largest economies. Figure 19 plots the results of the gravity model, with a country’s predicted exports on the x-axis and its actual exports on the y-axis for all bilateral export relationships. The black line is the 45-degree line, and the gray lines are the lower and upper bounds of an interval including points where the probability that predicted exports equal actual exports is 95 percent or more. In blue are all of Russia’s bilateral relationships, with those that are outside of the 95 percent confidence interval identified with their ISO country code. The figure also identifies Russia’s export relationships with EU countries in green, the United States in yellow, and China and India in red. The results show that Russia under-trades with the United States as well as with several large European economies such as France and the United Kingdom. Figure 19: Russia’s export potential in 2015 Source: Authors’ estimates using COMTRADE data. 36 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? The results also show that Russia under-trades with China and India. The gap between actual and predicted trade flows is nearly a quarter of Russia’s trade with China (Table 1). This result could be due to Russia’s highly concentrated export basket to China. The gap is about 17 percent for India (Table 1), though in nominal values it is smaller. Therefore, we excluded oil and gas from the bilateral trade relationships and re-estimated the gravity model. Table 1: Russia’s export potential: Trade with China and India, 2015 Importer Actual Trade (US$ Potential Trade Gap (% of actual billions) exports) China 33.2 41.4 24.7 India 4.5 5.3 17.4 Source: Authors’ estimates using COMTRADE data. In terms of non-oil exports, the gravity model results suggest that Russia continues to under-trade with China but no longer with India (Table 2). The gap between actual and predicted trade flows is now nearly one- third the actual non-oil and gas trade flows between Russia and China. On the other hand, the predicted trade between Russia and India exceeds the actual trade between these countries in non-oil and gas products. Figure 20 plots the results of the gravity model predicting non-oil exports to Russia’s key partners. Russia continues to under-trade with key EU countries as well as the United States for non-oil exports. Table 2: Russia’s export potential: Non-oil and gas trade with China and India, 2015 Importer Actual Trade (US$ Potential Trade Gap (% of actual billions) exports) China 15.9 25.4 60.4 India 4.5 3.1 -31.0 Source: Authors’ estimates using COMTRADE data. Figure 20: Russia’s export potential in 2015, non-oil and gas exports Source: Authors’ estimates using COMTRADE data. From Under-trading to Over-trading: Boosting Russian Exports to China and India 37 (ii) Russia’s revealed comparative advantage: Beyond primary products, construction and transport services stand out The above analyses confirm untapped export potential for Russia, especially in non-oil merchandise trade. However, these opportunities may not be achieved if Russia cannot compete in export sectors other than oil and gas. This section digs deeper and reviews the merchandise and services sectors where Russia reveals a comparative advantage. Russia has a revealed comparative advantage (RCA) in several merchandise industries. We analyzed the merchandise sectors in which Russia has a comparative advantage using Balassa’s revealed comparative advantage index9. The index gives a value of greater than one for industries that have a comparative advantage. Table 3 suggests that Russia has a revealed comparative advantage in several merchandise sectors, predominantly natural resource based industries. Table 3: Russia’s revealed comparative advantage in selected merchandise sectors Sector RCA in 2015 Gas 9.7 Petroleum and coke 6.3 Oil 6.0 Wheat 5.9 Coal 5.6 Forestry 3.7 Iron and Steel 2.2 Other grains 1.9 Non-ferrous metals 1.6 Electricity 1.5 Other mining 1.3 Vegetable oils 1.2 Lumber 1.1 Source: Authors’ calculations using COMTRADE data. Russia has a revealed comparative advantage in construction and transport services. The country’s RCA index for the construction and transport sectors exceeds 1 (Table 4). Transport includes all transport services involving the carriage of people and objects from one location to another as well as related supporting and auxiliary services. Russia’s revealed comparative advantage in transport services may include auxiliary services to the transport of oil and gas pipelines. Also included in this sector are postal and courier services. Construction covers the work performed on construction projects and installations by an enterprise outside the economy of residence of that enterprise. 9 Technically, the revealed comparative advantage (RCA) index for country i in sector j is calculated as follows: where xi,j is exports from i in sector j, Xi is total exports of i, xw,j is exports from the world in sector j, and Xw is total world exports. 38 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Table 4: Russia’s revealed comparative advantage index for services sectors, 2015 Sector RCA in 2015 Construction 2.22 Transport 1.04 Goods-related services 0.93 Other business services 0.66 Government goods and services 0.61 Personal, cultural, and recreational services 0.46 Telecommunications, computer, and information services 0.45 Travel 0.37 Insurance and pension services 0.24 Financial services 0.16 Charges for the use of intellectual property n.i.e. 0.13 Source: Authors’ calculations using UNCTAD data. We now assess how sectoral export dynamics since 2010 have contributed to Russia’s overall export performance in services. We ask whether Russia’s services have been showing losses or gains in competitiveness in world markets. This is shown in Figure 21, which compares the world import growth rate of different services sectors (horizontal axis) and the export growth rate of Russia in these sectors (vertical axis) for the period 2010 to 2016. The circles are labeled according to Balance of Payments (BoP) categories, and the size of the circles represents the importance of the sector in the countries’ export baskets to the world. Sectors above (below) the 45-degree line represent a gain (loss) in world market share. Consistent with a revealed comparative advantage, Russia’s transport services exports have been gaining world market shares. From 2010 to 2016, the growth rate of Russia’s exports of transport services – an important export sector for the country –exceeded the world import growth rate of this sector. Russia’s exports of smaller services sectors, including communications and intellectual property, have also grown faster than the world import growth of these services. Russia’s exports of other services, with the exception of finance and construction, have declined. Figure 21: Russia has been gaining market share in exports of transport services Source:Authors’ calculations using data from UNCTAD. From Under-trading to Over-trading: Boosting Russian Exports to China and India 39 (iii) Examining Russia’s trade complementarity index: There is greater complementarity with India than with China The opportunity for Russia to take advantage of the rebalancing of China and the acceleration of India is also dependent on the degree of trade complementarity with China and India. The trade complementarity index (TCI) gauges the potential for trade between two countries by measuring how well the export structure of one country matches the import structure of another country. The index is based on total exports and imports of goods and services at the disaggregated sectoral level that are then aggregated into a single index for each country pair. The index number varies between 0 and 100. The higher the index number, the higher the potential for that country to export to the other market10. The trade complementarity index between Russia and China is increasing, though it remains lower than that between Russia and India. Figure 22 illustrates how Russia’s trade complementarity with China and India has evolved during the past decade. In 2015, Russia’s trade complementarity index with India was around 22 percent higher than that with China. While the Russia India trade complementarity index has stagnated, the Russia-China trade complementarity index has increased by around 14 percent over the past decade. Figure 22: Russia’s trade complementarity index (goods and services) with India is greater than that with China Source: Authors’ calculations using COMTRADE and UNCTAD data. Russia’s services trade complementarity with India and China is decreasing. We recalculated Russia’s trade complementarity indices with China and India only using data for services trade. The resulting indices (Figure 23) suggest that services trade complementarity between Russia and China and Russia and India has decreased by around 18 percent and 8 percent, respectively. 10 The TCI between exporter i and importer j is calculated as: where xi,p is exports from i in product p, Xi is total exports of i, mj,p is imports of j in p, and Mj is total imports of j. 40 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 23: Russia’s services trade complementarity with China and India has fallen Source: Authors’ calculations using UNCTAD data. Looking across services sectors, we see that Russia’s services export growth has been lower than China’s services import growth across different products. Figure 24 is similar to Figure 23 above, and plots China’s import growth of different services sectors between 2010 and 2016 on the horizontal axis against the export growth rate of Russia on the vertical axis. Because we do not have bilateral services trade data between Russia and China at the sectoral level, we cannot tell from this figure if Russia is gaining or losing share in the China market. We can only see complementarity at the sectoral level between Russia’s services exports and China’s services imports. In fact, China’s imports of different services sectors have been quite strong and robust, including, for example, travel services and personal services – sectors where Russia’s export growth has been negative. For India, on the other hand, in sectors such as transport, communication, finance services, and personal services, Russia’s exports of these services sectors have been more robust than India’s imports of these services sectors. Sectors such as other business services and travel services – which India imports – are important sectors for Russia. Figure 24: Russia’s services export growth has been less than China’s import growth (top) but has exceeded India’s import growth (bottom) in most services sectors Source: Authors’ calculations using data from UNCTAD. Notes: The line passing through the scatter is a 45-degree line in a graph with equal scales in both axes. Sectors above the line indicate that Russia’s export growth for those sectors are higher than China or India’s import growth for the same sectors. The size of the circles represents the importance of the sector in the countries’ export baskets to the world. The circles are labeled according to sector’s initials: transport (TRN), travel (TRV), communications (COM), construction (CON), insurance (INS), financial (FIN), computer and information (IPS), other business (OBS), personal, cultural, and recreational (PER). 4. Methodology, Caveats, and Extensions This report develops a cutting-edge, customized CGE model to analyze the impact on Russia of various scenarios for economic activity in China and India. The CGE captures direct, indirect, and second-round effects. With certain caveats, the model’s ability to represent complex economic interrelationships among many agents (such as consumers, firms, governments), sectors, and countries can generate conclusions that may not be obvious, and it can be extended to address other relevant policy issues currently beyond the scope of this report. A. A CGE model has many advantages for quantifying the impact of external shocks… Structural changes from policy reforms or external shocks have many indirect and complex repercussions on the economic activity of different sectors and on different segments of the population. Applied general equilibrium models based on the best available data have emerged as effective tools to assess these effects. The CGE model captures the ex-ante impact of simulated reforms and shocks on a range of macro indicators, including the national accounts (GDP growth, consumption, investments, fiscal balance), external accounts (real exchange rate, trade, debt, current account), and industry indicators (output, employment). It may also capture the distributive effects of a policy, particularly critical as the successful implementation and sustainability of policies depends on the proper management of their distributive effects. Overall, the CGE model can help estimate the economy-wide impact of reforms, including third-country effects, while identifying winners and losers; e.g., in terms of sectors (agriculture or others), factors (wage earners, capitalists), or other characteristics. The CGE model used for this analysis is the World Bank’s dynamic global model, ENVISAGE. ENVISAGE is a flexible framework that has been successfully applied in numerous countries. The model is based on the GTAP 9 database, which contains a consistent set of Social Accounting Matrices (SAM) for 141 regions; it is the standard database for global CGE models. The original GTAP database is aggregated for this analysis. Annex 1 provides a list of the sectors, factors of production, and regions identified in the model and their mapping to the original GTAP sectors, factors, and regions. ENVISAGE is a recursive, dynamic computable general equilibrium model, which explicitly models the year- by-year effects of a particular policy on the economy. This approach links a sequence of static equilibriums with a set of equations, which update, at every period, certain macroeconomic variables such as population, productivity, and the capital stock. As a first step, we present the static block before introducing the dynamic block. Annex 6 describes the model in detail. B. The following key macroeconomic closures shape the findings... Macroeconomic closures determine how macro balances are restored after a shock. Specifically, these closures specify how the model achieves (i) balanced government accounts, (ii) the macro equilibrium of the capital account (i.e., the investment and savings balance), and (iii) the macro equilibrium of the accounts with the rest of the world (i.e., external balance). The closure rules adopted in the model are discussed below. The government budget balance is exogenous across different scenarios, as is the level of government spending (in real terms). Hence, the level of direct taxes is endogenous and adjusts, in response to policies and economic shocks, to cover any changes in the revenues in order to keep the fiscal balance at the exogenous level. This is a plausible choice given the Russian authorities’ current policy stance of tight fiscal policy. However, in the chapter on sensitivity results, we consider an alternative closure where the fiscal balance is endogenously determined. 42 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? For the savings-investment balance, we assume a savings-driven closure. Aggregate investment—which together with an exogenous rate of depreciation determines the next period’s capital stock—is flexible to ensure that the investment cost will be equal to the savings value. The volume of available savings is determined by an exogenous level of foreign savings, endogenous government savings, and endogenous household savings. In this context, an increase in government revenue, from a new source of tax revenue for example, would also be reflected in higher public savings and therefore stimulate current investment and growth. External balance ensures that the path of foreign liabilities is sustainable. This is achieved through adjustment of the real exchange rate, while the current account is fixed by the available quantity of foreign saving. To maintain the current account constant, domestic prices adjust so as to generate appropriate changes in the volumes of imports and exports demanded. The main implication of this closure is that an increase in exports, for example, would generate an appreciation of the real exchange rate, penalizing the competitiveness of the non-mining sector (the “Dutch disease”). C. Dynamic module The dynamic path follows the neoclassical growth framework (Solow-Swan growth model), implying that the long-run growth rate of the economy is determined by three main factors: capital accumulation, labor supply growth, and increases in productivity. The stock of capital is endogenous, while the latter two are exogenously determined: Capital accumulation. The capital stock in each period is the sum of depreciated capital from the previous period and new investment. Labor supply. For each type of labor, the maximum stock of labor available in each period grows exogenously based on population projections by age cohort and cohort-specific participation rates. Productivity. For the final determinant of growth, ENVISAGE assumes exogenous technical progress specific to sector and production factors. Thus, in the simulations, the real GDP growth rate differs from the growth rate under the baseline scenario due to the policy or shock being simulated. Specifically, policies or shocks affect real GDP growth through their effects on the accumulation of labor and capital. The model can also reflect productivity improvements due to higher energy efficiency and changes in the cost of international trade and transport services. Following the base year (2011), the model is solved year-by-year through 2030. In order to generate a dynamic solution, certain assumptions have been made regarding the evolution of the model’s exogenous variables. In general, GDP and population growth are exogenous and are taken from the scenarios of the shared socio- economic pathways (SSP) developed by the Integrated Assessment Modeling Consortium (IAMC) community. The IAMC scenario considered is the SSP2, “Middle of the Road”. Different assumptions are made for Russia. BaU (business-as-usual, or reference) growth has been calibrated using the near and medium-term assumptions of the World Bank. For years beyond the projection period (2020-2030), GDP is assumed to increase by 2 percent a year11. The actual oil price is used through 2016, and the model determines the oil price endogenously from 2017 onwards. D. But like all methodologies, it comes with caveats… The methodology assumes no impediments to the movement of labor and capital across sectors. This is a simplification of reality where they may be frictions preventing factors from moving out of sectors in decline and into expanding sectors. While the methodology has limitations, it illustrates Russia’s potential to reap the benefits of the changing structure of the Chinese economy and the economic emergence of India. The sensitivity analysis demonstrates the effects of relaxing some of these assumptions and hence goes some way to addressing the limitations of the methodology. The presence of rigidities means that the slowdown in China results in a larger reduction in Russia’s GDP as the economy is less able to adjust in response to lower Chinese demand for imports. 11 The SSP2 GDP growth for Russia for that period is around 3 percent. Methodology, Caveats, and Extensions 43 Similarly, there is a smaller increase in Russia’s GDP from India’s expansion in the presence of frictions. Moreover, like most CGE models, this model does not capture the productivity effect of policy shocks as technological progress is exogenous. This is another limitation as recent economic literature emphasizes the potential benefits of trade diversification on productivity (Box 2). The main strength of the CGE approach remains its ability to capture long- term structural changes across sectors, and help in identifying new trade opportunities in the context of the quest for trade diversification. Box 2: Trade diversification and productivity: Literature review Increasing trade diversification can increase productivity and growth. Beginning in the early 2000s, trade theory increased the emphasis on the benefits of trade diversification as opposed to the traditional Ricardian view that specialization according to comparative advantage provides the optimal allocation of resources. The theoretical arguments for the benefits of diversification are clear. However, empirical results vary due to different effects at different levels of development as well as the problems in identifying causality. Three issues have been highlighted for developing countries. First, countries specializing in a limited number of primary commodities may face high volatility in export prices and may have difficulties in coping with sharp changes in prices by switching to alternative products. This rigidity can accentuate the impact of adverse shocks on growth. In addition, studies of the “natural-resource curse” hypothesis (Sachs and Warner, 1997) show how concentration in oil and minerals can impair production in potentially higher- productivity sectors over the long term. Second, exports by developing countries may be associated with technology diffusion (e.g., new production, management or marketing techniques) from advanced countries that improves productivity. Empirical studies have been based on the idea that firms learn by exporting (see for example Aw and Hwang, 1995; Tybout and Westbrook, 1995; Haddad, 1993). Other papers using micro-level data have found some evidence of «learning-by-exporting» (Crespi et al. 2008; De Loecker, 2007, Aw et al., 2007; Van Biesebroeck, 2005; Girma et al., 2004). Empirical studies find that trade leads to international diffusion of technology (see for example, Coe et al., 2009; Alcala and Ciccone, 2004). However, Clerides et al. (1998) and Melitz (2003) find that exporting firms tend to have higher productivity than non-exporting firms because only the most productive firms become exporters, and not because exporting raises productivity. Other studies (Demidova et al., 2006; Eaton et al., 2004, 2007; Helpman et al., 2004; Bernard and Jensen, 1999) confirmed this ‘selection effect’ at the firm level. Some authors have focused on the relationship between export diversification and productivity. Hausmann et al. (2007) find that countries that export goods associated with higher levels of productivity grow more rapidly. Hesse (2008) finds a positive effect of export diversification on per capita income growth for developing countries over 1961-2000 using dynamic panel growth models based on the GMM estimator. Some cross-country empirical studies find a U-shaped relationship between export diversification and GDP per capita (exporting is associated with declines in productivity at low income levels, but eventually with higher productivity as incomes rise—see Cadot et al., 2011; and Klinger and Lederman, 2006). Xuefeng and Yasar (2016) explain a U-shaped relationship in China between firms’ export market diversification and their productivity by the evolution of costs: costs are initially high (and thus productivity low) due to a lack of knowledge and experience, but they eventually decline as export market expansion generates learning as well as economies of scope and scale. Finally, increased import competition may force improvements in productivity by domestic firms that produce close substitutes, and it can increase overall productivity as less-productive firms are forced to exit (Carrère et al. 2011). Empirical studies find that trade liberalization improved productivity in import competing sectors in Chile (Pavcnik, 2002) and increased productivity growth more in less protected sectors in Cote d’Ivoire. Other studies on developing countries (Fernandes, 2007, for Colombia; Krishna and Mitra, 1998, for India; Tybout and Westbrook, 1995, for Mexico) find a positive effect of increased import competition on domestic productivity. Ethier (1982), Markusen (1989), and Grossman and Helpman (1991) provide evidence that productivity gains can arise from increasing varieties of imported inputs, leading to lower input prices, access to higher quality inputs, and access to new technologies incorporated in the imported varieties. 44 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? E. The methodology developed and data collected for this report could be extended… While the focus of this particular report is on China, India, and Russia, the model is replicable and scalable, and it can be used to analyze other issues (currently beyond the scope of this report) as outlined below: (i) The model could be extended to other groups of countries; for example, the Eurasian trading bloc, the EU, or the BRICS. (ii) Other scenarios could be addressed, such as a global rise in protectionism, shifts in China and India to clean energy to reduce climate change, stronger productivity growth in Russia, or sharp changes in demand in one or more of Russia’s trading partners. (iii) The CGE approach developed can be combined with spatial analysis to identify Russian regions that hold the most potential for mutually beneficial cross-border linkages. While certain Russia–China border regions are obvious candidates, this work could usefully shed light on non-border Russian regions that can advance trade in services (which need not necessarily be constrained by geography or topography). 5. Simulating the Future: Presenting Four Key Scenarios Scenarios simulating the impact on Russia of changes in economic activity in China and India include a slowdown in China, rebalancing in China, more rapid expansion in India, and a combination of all three scenarios. These four scenarios are based on realistic, credible assumptions for the evolution of these two economies over the next 15 years. The goal is to evaluate the potential impact of changes in the level and pattern of growth in China and India on production and trade in the Russian economy. In addition to a baseline (or reference scenario), we consider four scenarios: i) a growth slowdown in China; ii) economic rebalancing in China; iii) growth expansion in India; and iv) a combination of the Chinese slowdown, rebalancing, and India’s expansion. These scenarios could also affect the Russian economy through financial channels, for example trade credit or foreign investment, or through remittances. However, we are only concerned with the real economy, while financial flows are considered exogenous. Scenario 1. China’s slowdown: Chinese growth slows from the current 6.5 percent to 4.6 percent in 2030 while maintaining the historical composition of growth (a similar scenario was considered in World Bank, 2015). Scenario 2. China’s rebalancing: GDP growth remains at the historical trend, but the share of investment in GDP gradually falls from 46.7 percent in 2015 to 35.5 percent in 2030 while the difference accrues to household consumption. This implicitly assumes that the decline in investment is compensated by increases in labor productivity to achieve the same level of growth. Scenario 3. India’s expansion: India’s growth improves from around 6 percent per year over 2015-30 in the reference scenario to around 8 percent. Scenario 4. India’s growth improvement and China’s slowdown and rebalancing: This combines the assumptions in the above three scenarios. Although results are available for a wide range of indicators for the eight groups of countries and regions considered in this model, our discussion will focus mainly on Russia and the effects on trade, sectoral output, growth, and welfare. These scenarios are compared to a baseline (or reference scenario) based on past trends. The reference scenario assumes that growth in China and India equals the trend before 2013, and the composition of GDP remains unchanged. Specifically, the reference scenario assumes that: i) China grows at around 7 percent per year from 2015-30; ii) Indian growth averages around 6 percent between 2015-30, converging to 5 percent in 2030; and iii) China’s economic structure remains the same as it has in the last five years (investment at 45 percent of GDP and final consumption at 31 percent of GDP). The aim is not to present the most likely forecast, but rather to construct a counterfactual scenario not affected by the policy assumptions underlying the other scenarios in order to serve as a standard of comparison. In the reference scenario, Russia’s share of world trade stagnates but China and India’s increase. Russia’s exports remain at around 3 percent of global exports from 2015 to 2030 (Figure 25). By contrast, China’s share of world exports rises from around 10 percent in 2011 to nearly 18 percent in 2030 due to the assumed rapid expansion of GDP. Similarly, India’s share of world exports rises from around 2 percent in 2015 to nearly 5 percent in 2030. The global export share of Russia’s top trade partner, the EU and the European Free Trade Association (EFTA) region, would fall from around 35 percent in 2015 to 25 percent in 2030. 46 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 25: Russia’s share of world trade remains constant under the reference scenario Contribution to World Exports 35 (%) 30 World Totalworld Exports exports (%) 25 OECD America no Mexico EU and EFTA 20 China of total India 15 Share of Major OPEC Share Russian Federation 10 Rest of ECA Rest of the World 5 0 Source: Authors’ estimates. Despite China’s rising share of Russian exports under the reference scenario, the EU would remain the top destination for Russian products in 2030 (Figure 26). China’s share of Russian exports would increase from around 10 percent in 2015 to around 17 percent in 2030, while India’s share would rise from 1.5 percent in 2015 to nearly 3 percent in 2030. Russian exports to India would remain low compared to those heading to China and other major Russia markets such as the OECD and the rest of the Europe and Central Asia (ECA). Figure 26: China’s share of Russian exports rises and Europe’s share falls under the reference scenario Destinations of Russia Export in the reference Scenario 50 45 Share of Total Russian Exports (%) 40 35 30 OECD America no Mexico 25 EU and EFTA China 20 India 15 Rest of ECA 10 5 0 Source: Authors’ estimates. 6. Simulating the Future: Presenting the Results The impact of the four scenarios on growth in Russia is generally small due to general equilibrium effects (e.g., in the China slowdown scenario, higher Russian exports to third countries due to a real depreciation of the ruble partially compensate for slowing demand from China), modeling assumptions (e.g., frictionless intersectoral movement of labor and capital), and current trade patterns (Russian trade, excluding oil and gas, with these two countries is well below its potential). Perhaps these surprisingly small effects should simply reduce concerns over the impact on Russia of changes in China and India. On the other hand, these results could also indicate Russia’s inability to capitalize on the opportunities offered by China’s rebalancing and India’s growth. Moreover, the China slowdown scenario shows significant effects on welfare in Russia, largely stemming from changes in the terms of trade. The general conclusion that emerges is that a slowing and rebalancing China, along with a more rapidly expanding India, on balance, would present more of a challenge than an opportunity for Russia. 6.1. Scenario 1– China’s Slowdown: This would have little impact on Russian growth but a more substantial impact on welfare The slowdown in China (illustrated in Figure 27) reduces Chinese demand from all regions for final goods and services and for intermediate inputs. By 2030, the value of world exports to China is around 15 percent below the level in the reference scenario (Figure 28). All groups and countries considered in our analysis experience lower exports to China, ranging from 11 percent in India to 18 percent for other ECA countries. The most affected products are natural resources, agriculture, oil and gas, and low-skilled services (Figure 29). Figure 27: China’s growth falls significantly in the slowdown scenario China Slowdown: China GDP growth 9 8 7 GDP Annual Grwoth (%) 6 5 4 China Reference 3 China Slowdown 2 1 0 Source: Authors’ construction . 48 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 28: Exports to China from all regions decline in the slowdown scenario Trade effect for selected regions Change from Baeline (%) 5 0 -5 -10 -15 -20 Exports to China Total exports Source: Authors’ estimates. Note: Cumulative percentage change from the baseline by 2030. Figure 29: The drop in China’s imports is larger in primary products than in manufactures Source: Authors’ estimates. Note: Cumulative percentage change from the baseline by 2030. The impact of the China slowdown is greater for exporters of primary products than for countries heavily dependent on the Chinese market. For example, more than 40 percent of exports from India and 50 percent of exports from the rest of the world (mainly other Asian countries) go to China (Figure 30). Nevertheless, these countries’ exports are less affected by China’s slowdown than exports from OPEC and the Rest of ECA, which mainly export primary commodities, even though China accounts for a smaller share of their trade. Simulating the Future: Presenting the Results 49 Figure 30: Global market dependence on China differs greatly by region Exports to India : Reference scenario 30,0 (%)(%) Region 25,0 region the 20,0 OECD America no Mexico teh ofof EU and EFTA Exports exports 15,0 China Major OPEC Total of total 10,0 Russian Federation Share of Rest of ECA Share 5,0 Rest of the World 0,0 Source: Authors’ estimates. Like other primary exporters, Russia’s exports to China are substantially affected by the slowdown12. By 2030, Russian exports to China are 17 percent lower in the China slowdown scenario than in the reference scenario (Figure 28). All Russian sectors are affected (Figure 33), with the magnitude of the shortfall ranging from 8 percent for high-skilled services to 24 percent for natural resources (mainly mining products). By 2030, the level of oil and gas exports, the top Russian export product to China, is 18 percent lower than in the reference scenario. However, the impact of the China slowdown on total Russian exports remains limited, thanks to third country effects. Russia’s exports to the world are only 3.5 percent lower by 2030 than in the reference scenario as lower exports to China are compensated by rising exports to all other regions. The gain ranges from a 2.5 percent increase in exports to the rest of ECA to almost 8 percent to India (left panel of Figure 31). Other countries buy more Russian goods because lower demand from China results in lower prices of Russia’s exports than in the reference scenario (right panel of Figure 31). Figure 31: Russian exports to non-Chinese markets are higher than in the reference scenario due to lower prices Effect byby Effect destination of Russian destination of Russian exports exports Russian Exports Russian Exports price price 10 0,0 Agriculture High-Skill Low-Skill Natural Oil, Gas, and High-Skill Low-Skill -0,1 Manuf Manuf Resources Refined oil Services Services 5 -0,2 -0,3 Change from Baseline (%) Change from Baseline (%) 0 OECD EU and EFTA China India Major OPEC Rest of ECA Rest of the -0,4 America no World -5 Mexico -0,5 -0,6 -10 -0,7 -15 -0,8 -0,9 -20 -1,0 Source: Authors’ estimates. 12 Around 55 percent of Russian exports to China are made up of gas and oil. 50 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Lower primary product exports in the China slowdown scenario create new opportunities. While Russia’s oil and gas sector is negatively affected by the China slowdown, the non-oil tradable sector will be better off. Lower exports of primary products entail a 1.7 percent depreciation (compared to the reference scenario) of the Russian real exchange rate by 2030 (Figure 32), improving the competitiveness of Russian products in both international and domestic markets (referred to as the “reverse Dutch Disease”). By 2030, Russia’s high-skilled manufacturing exports increase by around 8 percent and low-skilled manufacturing exports increase by 3.1 percent compared to the reference scenario (Figure 33). The competitiveness of the agricultural sector improves in the local market as production remains unchanged (Figure 34) despite much lower exports. In addition, lower oil and gas production would free labor and capital for use in other sectors at cheaper prices, therefore reducing the cost of production. Figure 32: Russia’s exchange rate depreciates as a result of the China slowdown Real Exchange Rate: China Slowdown Scenario 0,0 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 -0,2 -0,4 Change from Baseline (%) -0,6 -0,8 -1,0 -1,2 -1,4 -1,6 -1,8 Source: Authors’ estimates. Figure 33: Russian exports of primary products are sharply lower in the China slowdown scenario Change from Baseline (%) Source: Authors’ estimates. Simulating the Future: Presenting the Results 51 Figure 34: The China slowdown would boost non-oil tradable sectors Production effects in Russia 4 3,04 3 2 1,25 -0,08 -1,22 -0,02 -0,44 Change from Baseline (%) 1 0 Agriculture High-Skill Low-Skill Natural Oil, Gas, and High-Skill Low-Skill -1 Manuf Manuf Resources Refined oil Services Services -2 -3 -4 -5 -5,42 -6 Source: Authors’ estimates. Exchange rate depreciation, however, does not automatically result in an increase in the domestic production of tradables. Entrepreneurs have to be able to shift investment to tradables, and workers have to move into jobs in tradable sectors with rising wages. Thus, limits on start-up firms (e.g., due to cumbersome regulations), low levels of financial sector development, and other such impeding factors can slow the output response to exchange rate depreciation. Also relevant is global demand for Russian tradable goods, which in general remains soft. Such impediments may be particularly important in Russia, where the dominant role of government during a prolonged period of high oil prices may have encouraged rent seeking and discouraged entrepreneurial activity. On the other hand, it is important to avoid underestimating the potential of increases in domestic production of tradables in response to a large real depreciation. A major goal of policy should be to facilitate the changes in economic structure that are necessary to capitalize on this opportunity. Before discussing the growth effect, it is useful to explain the key drivers of growth in this model. The level of GDP is determined by three factors: the supply of workers, investment, and productivity. Since productivity is exogenous, and unemployment and international migration are assumed to be zero, the main driver of growth in our simulations is investment. Investment is equal to total savings available from domestic (household and government) and foreign sources (the latter is assumed to be constant). Growth in this model thus depends on anything that affects household savings (e.g., changes in the terms of trade and direct tax) or government revenue (e.g., indirect taxes and the returns from extractive sectors). As noted above, the government closure in this model assumes that the fiscal balance is fixed and that government expenditures are fixed. Therefore, government savings do not change while changes in direct taxes to meet the fiscal target affect available household incomes and savings13. The impact of slower growth in China on Russia’s growth is modest. Russian GDP is only 0.17 percent lower by 2030 than in the reference scenario (Figure 35) due to lower exports (2.5 percent), investment (0.75 percent), and final consumption (1.2 percent). The change in exports is due to lower Chinese demand, as discussed above. Investment is lower because of lower household savings due to two factors. First, the depreciation of the exchange rate in comparison with the reference scenario (Figure 32) means that tradable consumption goods are more expensive, reducing households’ disposable income. Second, government revenues are lower in the China slowdown scenario due to lower oil and gas prices, coupled with reduced indirect taxes due to lower imports. Therefore, direct taxes on households must be higher to maintain the (assumed) fixed government budget deficit. On the other hand, imports are substantially lower in the face of the (assumed) fixed current account balance and lower export revenues, which make a positive contribution to GDP. The magnitude of the growth effect is similar to that in IMF (2014), which finds that on average, a 1 percentage point slowdown in China can lead to a 0.15 percentage point fall in growth in advanced economies and a smaller impact on emerging markets. 13 The sensitivity analysis below will consider an alternative government closure where the fiscal balance is assumed to be endogenous and the direct tax rate constant. 52 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 35: The China slowdown has little impact on Russian growth Russia GDP by expenditures (% GAP from baseline in 2030) 0,0 2030 -0,17 Change from Baseline (%) -0,5 -1,0 GDP at constant prices Private consumption -1,5 Investment Exports -2,0 Imports -2,5 -3,0 Source: Authors’ estimates. However, the impact on household welfare is significant. By 2030, welfare in Russia is lower by 1.3 percent in the China slowdown scenario than in the reference scenario (Figure 36). Lower terms of trade, coupled with higher direct taxes to compensate for lower indirect taxes and hydrocarbon revenues (see above), result in a pronounced welfare loss for Russian households. Figure 36: The China slowdown has a substantial impact on household welfare in Russia Household effect Terms of Trade : China Slowdown Scenario 0,0 0,0 -0,22019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 -0,5 -0,4 Change from Baseline (%) Change from Baseline (%) -0,6 -1,0 -0,8 -1,0 -1,5 -1,2 -1,4 -2,0 -1,6 -1,8 -2,5 -2,0 Household utility Household saving Source: Authors’ estimates. Simulating the Future: Presenting the Results 53 6.2. Scenario 2–China’s Rebalancing: This would have small, positive effects on growth and welfare in Russia This scenario assumes a shift from investment to consumption (Figure 37) while maintaining the same level of growth as in the reference scenario. This is achieved in the model by reducing household savings to the level that generates the targeted final consumption and investment. At the same time, productivity is increased to Figure maintain the 37: China’s unchanged rebalancing growth involves level despite lowera shift from investment to private consumption investment. China Rebalancing: Economic Structure (%GDP) 60 50 Share of GDP (%) 40 30 Private consumption Public consumption 20 Investment 10 - Source: Authors’ estimates. Rebalancing would lead to substantial changes in the level and product composition of China’s imports. The demand for consumer goods is higher while demand for investment goods is lower than in the reference scenario. Thus, China’s import demand would shift from relatively capital-intensive sectors (high-skilled manufacturing, construction) towards less capital-intensive sectors (low-skilled manufacturing, agriculture, high-skilled services). In particular, by 2030, China’s imports of agricultural products are 3.9 percent higher, and high-skilled services (air transport, communication, financial services n.e.s., insurance, business services n.e.s., recreation and other services, public administration and defense) are 4.35 percent higher than in the reference scenario (Figure 38). Oil and gas imports also are significantly higher, reflecting the importance of oil in final consumption. Similarly, imports of low-skilled manufactures (mainly food products, textile apparel) are 1.24 percent higher by 2030. By contrast, imports of other natural resources (mostly coal and minerals) that are mainly used for investment are 2.39 percent lower. Chinese imports of low-skilled services (mainly construction, electricity, and transport) are 5 percent lower, reflecting lower investment in construction. 54 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 38: Rebalancing significantly changes the composition of China’s import demand Source: Authors’ estimates. The impact of China’s rebalancing on other countries’ exports depends on the commodity composition. The level of China’s total imports of goods and services in 2030 is only 0.01 percent lower than in the reference scenario. Countries exporting agricultural products, food products, oil and gas, and high-skilled services benefit from higher exports to China (Figure 39, right panel). Exports to China from the EU and OECD countries are generally lower in the China rebalancing scenario. While these countries export significant amounts of food and high-skilled services (for which rebalancing increases China’s demand), China’s imports of their high-skilled manufacturing products for use in industry are lower. By contrast, India exports the most high-skilled services to China as a share of total trade, and it experiences the largest gain in exports to China as a result of the rebalancing (Figure 39, left panel). Figure 39: Rebalancing has positive impacts on regions exporting agriculture and high-skilled services Share of national exports to China (%) Trade effect for selected regions Contribution of Key products to exports to China 3 (%) 80 (%) 70 Baseline from Baeline 2 60 50 40 1 30 Changefrom 20 0 10 Agriculture Change 0 Gas and Oil -1 High-Skilled services -2 -3 -4 Exports to China Total exports Source: Authors’ estimates. Simulating the Future: Presenting the Results 55 The rebalancing presents Russia with opportunities to diversify its trade with China beyond traditional goods. While Russian exports to China are only 0.9 percent higher in 2030 than in the reference scenario, sectoral changes are substantial (Figure 40). Higher Russian exports to China are driven by higher exports of agricultural products (3.7 percent) and high-skilled services (4.05 percent). Russia’s oil and gas exports to China are also higher, by 2.1 percent. However, Russia’s exports to other countries are generally lower than in the reference scenario as the rebalancing in China results in an appreciation of Russia’s real exchange rate (Figure 41). Figure 40: China’s rebalancing significantly affects the composition of Russian exports Source: Authors’ estimates. Figure 41: China’s rebalancing results in an appreciation of Russia’s real exchange rate Real Exchange Rate: Rebalancing Scenario 0,08 0,07 Change from Baseline (%) 0,06 0,05 0,04 0,03 0,02 0,01 0,00 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Source: Authors’ estimates. 56 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Overall, the growth effect on Russia of China’s rebalancing is small. Russian GDP is only 0.0 4 percent higher in 2030 than in the reference scenario (Figure 42). This modest improvement is driven by increases in exports (0.08 percent), investment (0.03 percent), and final consumption (0.04 percent). Investment is higher because household savings are higher as greater extractive resource revenues and indirect taxes result in a lower direct tax burden on households. Similarly, the welfare of Russian households would improve by 0.05 percent, mainly due to higher terms of trade (Figure 43). Figure 42: China’s rebalancing has a small positive impact on Russian growth Russia GDP by expenditures (% deviation from baseline) GDP effect 0,10 0,04 0,09 0,08 Сhange from Baseline (%) (%) 0,03 Baseline (%) 0,07 Baseline GDP at constant prices 0,06 Private consumption 0,02 0,05 from from 0,04 Investment 0,04 Change Exports Change 0,03 0,01 Imports 0,02 0,01 0,00 0,00 OECD EU and EFTA India Major OPEC Russian Rest of ECA Rest of the 2030 America no Federation World Mexico Source: Authors’ estimates. Figure 43: China’s rebalancing would slightly improve household welfare in Russia Household effect Terms of Trade: Rebalancing Scenario 0,12 0,025 0,10 Change from Baseline (%) (%) 0,020 Baseline (%) from Baseline 0,08 0,015 0,06 from 0,04 0,010 Change Change 0,02 0,005 0,00 0,000 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Household utility Household saving Source: Authors’ estimates. The impact of China’s rebalancing on Russia’s GDP is similar to that on other oil and gas exporters. China’s rebalancing has a positive impact on GDP in all groups of countries considered in this analysis. Russia and other oil exporting countries benefit the most as the rebalancing boosts Chinese demand for oil and gas. The growth effect is slightly bigger for Russia than for OPEC and the Rest of ECA since Russia also exports a significant amount of agriculture products to China (5 percent of total Russian exports to China). The impact of rebalancing on growth in India also is positive; high-skilled services that benefit from higher Chinese demand represent more than 60 percent of total Indian exports to China. The positive growth effect for other groups of countries reflects the general improvement of their terms of trade resulting from lower Chinese exports of competing products. Simulating the Future: Presenting the Results 57 These results differ somewhat from a similar analysis conducted by Lakatos et al. (2016). That study also finds that China’s rebalancing would increase GDP growth in the rest of the world but by a significantly greater magnitude than in this model (global GDP rises by 5 percent). In part, this difference results from a different definition of China’s rebalancing. Lakatos et al. (2016) assume not only a shift from investment to final consumption (as in this study), but also an increase in demand for imports of services due to the rising share of services in GDP, coupled with some rigidity in the sector’s use of capital. Given the lack of consensus on how the rebalancing would play out from the supply side, we focus our analysis only on the demand side where there is a broader consensus. The different results may also be driven by different levels of sectoral aggregation. The model used in Lakatos et al. (2016) has only one services product while this analysis differentiates between high-skilled and low- skilled services. This disaggregation enables us to distinguish between services that are investment-intensive (e.g., construction), for which Chinese demand declines as a result of the rebalancing, from other services for which Chinese demand rises. The same issue applies to the manufacturing sector. 6.3. Scenario 3—India’s Expansion: This would significantly boost Russian exports but have little impact on growth or welfare This scenario assumes an improvement in India’s GDP growth from 6 percent to around 8 percent on average. This is achieved in our model by increasing total factor productivity to hit the targeted growth level. Higher growth would increase Indian demand for final consumption goods and services as well as intermediate inputs from all regions. The value of global exports to India is around 16 percent higher than in the reference scenario, and the value of total exports is 6.39 percent higher by 2030. All countries considered in our analysis experience a gain in exports to India, ranging from 6 percent for the EU and EFTA to 40 percent for China. The impact on exports depends on the level and product composition of the country’s exports to India. China gains the largest percentage rise in exports (Figure 44) because exports to India represent 10 percent of total exports (the highest share after OPEC, see Figure 46), and China’s exports are concentrated in high-skilled manufacturing, for which demand in India rises substantially as a result of expansion (Figure 45). Figure 44: Higher growth in India would significantly increase exports to India as well as global exports Trade effect for selected regions 44 40 36 (%) (%) 32 Baeline 28 25,58 Baseline 24 from Change from 20 15,96 Change 16 12 8 6,39 2,70 3,72 4 1,10 0,91 2,11 0,06 0 OECD EU and China India Major OPEC Russian Rest of ECA Rest of the World America no EFTA Federation World Mexico Exports to India Total exports Source:Authors’ estimates. 58 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 45: The impact of expansion on India’s imports differs by product Imports effect Contribution of Key products to exports to India 30 90 24,71 25 Change from Baseline (%) 80 19,52 Share of national exports to India (%) 18,55 20 15,28 15,15 70 15 10,99 60 10 6,06 50 5 Agriculture 0 40 Gas and Oil 30 High-Skilled services 20 10 0 OECD EU and China Major OPEC Russian Rest of ECA Rest of the America no EFTA Federation World Mexico Source: Authors’ estimates. Figure 46: After OPEC, China has the largest share of exports to India Exports to India : Reference scenario 30,0 (%) region (%) 25,0 tehRegion 20,0 OECD America no Mexico Exports of the EU and EFTA Total exports 15,0 China Major OPEC of total 10,0 Russian Federation Share of Rest of ECA Share 5,0 Rest of the World 0,0 Source: Authors’ estimates. Simulating the Future: Presenting the Results 59 Expansion in India increases Russian exports. By 2030, Russian exports to India are 8 percent higher and total Russian exports are 2.1 percent higher than in the reference scenario. Total exports rise only modestly because Russia’s exports to India account for less than 2 percent of its total exports. The increase in Russian exports to India (compared to the reference scenario) ranges from 5 percent for high-skilled services to 28 percent for agriculture products (Figure 47, left panel). This result reflects the high complementarity between Indian imports and Russian exports, and it points to a significant potential to strengthen trade with India, not only in traditional products but also in new areas such as agriculture and services. Russia’s exports to other countries are generally lower in this scenario as higher demand for Russian goods from India results in a more appreciated real exchange rate (Figure 47, right panel). Figure 47: India’s expansion has the largest impact on exports of Russian primary products Real Exchange Rate: India Expansion Scenario 0,50 0,45 Change from Baseline (%) 0,40 0,35 0,30 0,25 0,20 0,15 0,10 0,05 0,00 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Source:Authors’ estimates. 60 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Despite a substantial trade impact, India’s expansion has a limited effect on growth or household welfare in Russia. In 2030, Russian GDP is only 0.06 percent higher than in the reference scenario as Russia’s trade links with India are limited (Figure 48). Higher GDP results from slightly higher exports (1.1 percent), investment (0.9 percent), and final consumption (1.3 percent). The growth mechanism is the same as explained in scenarios 1 and 2. Household welfare is only 0.3 percent higher by 2030, largely due to the terms of trade improvement (Figure 49). The impact of India’s expansion on GDP of the rest of the world is equally small, reflecting India’s low share total world trade (less than 5 percent by 2030). Figure 48: The impact of India’s expansion on Russian GDP growth is small Russia GDP by expenditures (% deviation from baseline) 0,9 0,8 Change from Baseline (%) 0,7 0,6 GDP at constant prices 0,5 Private consumption 0,4 Investment 0,3 Exports 0,2 Imports 0,1 0,06 0,0 2030 Source: Authors’ estimates. Figure 49: The impact of India’s expansion on household welfare in Russia is also small Household effect Terms of Trade: India Expansion Scenario 0,70 0,40 0,60 0,35 Change from Baseline (%) 0,30 Change from Baseline (%) 0,50 0,25 0,40 0,34 0,20 0,30 0,15 0,20 0,10 0,10 0,05 0,00 0,00 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Household utility Household saving Source: Authors’ estimates. Simulating the Future: Presenting the Results 61 6.4. Scenario 4—India’s expansion, China’s slowdown and its rebalancing: This combination would have little net impact on Russia This scenario combines the assumptions from the three scenarios presented above. It is our view of the most likely future scenario. The impact on Russia (and the world in general) reflects the negative effect of a slowdown in China, and the positive effects of China rebalancing and India expanding. The trade effect is negative for the world as a whole and for most groups of countries used in our analysis. By 2030, the value of world trade is 3 percent, and exports to China are 15 percent lower than in the reference scenario (Figure 50). The impact on Russia is similar to the global average: exports to China are around 17 percent lower, and total exports are 1.5 percent lower. China experiences the largest drop in trade (from the reference scenario), while India is the only country for which exports to China and total exports are higher in this scenario. Figure 50: Most regions’ exports to China are lower in the combined scenario Trade effect for selected regions 20 Change from Baseline (%) 15 10 5 0 -5 -10 -15 -20 Exports to China Total exports Source:Authors’ estimates. The combined impact on Russian growth of the China slowdown, China rebalancing, and Indian expansion is limited. The negative impact of a slowdown in China is not entirely offset by the positive effect of both the rebalancing of China and expansion in India (Figure 51). Similar to other major exporters of primary products, by 2030, Russian exports and terms of trade are lower compared to the reference scenario, and Russian GDP is also 0.07 percent lower. Figure 51: The impact of the combined scenario on Russian growth and welfare is small Household effect 0,2 0,0 -0,2 Change from Baseline (%) -0,4 -0,6 -0,8 -1,0 -1,2 -1,4 -1,6 Household utility Household saving Source: Authors’ estimates. 62 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? 7. Simulating the Future: A Discussion on Sensitivity The simulation results presented above are sensitive to oil prices, government fiscal closures, and assumptions on the potential frictions in labor markets and on international trade. Changes in assumptions for the exogenous parameters of the model and the approach to balancing the government’s fiscal accounts would produce somewhat, but not dramatically, different results. While the CGE simulations are consistent with the macro-framework for Russia, they are largely illustrative and not empirically grounded. The results rely on the assumptions and calibrating parameters presented in this report. This section assesses the sensitivity of our results to variations in the assumptions and parameters concerning: i) government closure; ii) the oil price; iii) factor rigidity; iv) trade elasticities; and v) FDI inflows. This sensitivity assessment is mainly focused on scenario 1 (China slowdown) and scenario 3 (India expansion), though scenario 2 (China rebalancing) is also assessed with regards to FDI inflows. Allowing the government account to adjust through spending changes would moderate the impact on Russia of slower growth in China and more rapid expansion in India The scenarios presented above (scenarios 1 and 3, hereafter referred to as the main scenario) assumed a fixed fiscal balance, achieved by changes in revenues from direct taxes on households. For the sensitivity analysis, we will assume an exogenous fiscal balance, but this time the government account is closed through adjustment in government expenditures. Thus, for example, an increase in government revenues from natural resources results in an automatic increase in government expenditures to maintain same fiscal balance level in the reference scenario. Figure52 shows the results of scenario 1 for growth, fiscal balance, price changes, and household welfare under this assumption of government closure. Reduced indirect tax receipts and natural resource revenues resulting from a slowdown in China lead to lower government expenditures and higher growth than in the main scenario where the direct tax rate rises to maintain a fixed fiscal balance. By 2030, GDP is 0.09 percent below the reference scenario compared to 0.17 percent lower when the direct tax rate increases to compensate for the loss in revenues. Higher growth is mainly due to higher savings from households, which has a positive impact on private investment. In fact, the shift from a fixed fiscal balance financed through increased direct taxes to a fixed fiscal balance financed through current expenditure reduction is equivalent to a transfer of resources from non-productive government use to households, for both final consumption and savings. Thus, household welfare is higher with fiscal adjustment through current expenditures in the China slowdown scenario although welfare remains below the level in the reference scenario. 64 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 52: The China slowdown scenario – Growth and household welfare are higher with a fiscal deficit financed through current expenditures adjustment Sensitivity Assumption -0,12 -0,39 Source: Authors’ estimates. Similarly, the India expansion scenario with a fixed fiscal balance financed through adjustment in current expenditures results in a lower GDP in Russia than is the case with a fiscal balance financed through direct tax adjustment (Figure 53). By 2030, GDP is 0.04 percent higher than in the reference scenario compared to 0.06 percent higher when direct taxes adjust to maintain the fixed fiscal balance. Lower growth is due to the decrease in household savings, which has a negative impact on private investment. The change of closure here is equivalent to a tax increase for households and an increase in non-productive government expenditures. As a result, the welfare gain from India’s expansion is 0.16 percent by 2030 compared to 0.34 percent under the previous closure rule (Figure 53). Simulating the Future: A Discussion on Sensitivity 65 Figure 53: The India expansion scenario – GDP and household welfare are lower if the exogenous fiscal balance is financed through increased current expenditures 0,17 Source: Authors’ estimates. Assuming larger changes in the price of oil would substantially increase the impact on Russia A larger decline in the oil price as a result of a slowdown in China would exacerbate the impact on Russia (Figure 54). Oil and gas are by far the most important export products for Russia (around 55 percent of exports in 2015). The change in the oil price in our model reflects an instantaneous adjustment to market equilibrium, and thus does not capture major determinants of oil price changes related to speculative forces or price bubbles. This sensitivity analysis assumes a larger response in the oil price than in the China slowdown and India expansion scenarios presented above. The oil price is 5 percent lower than in the reference case as a result of a slowdown in China (compared to the model-generated equilibrium price that is 2.5 percent lower in the main scenario) and 5 percent higher as a result of India’s expansion (compared to 1.6 percent higher in the main scenario). As expected, the assumption of a more dramatic decline in the oil price magnifies the growth and welfare losses for Russia generated by a slowdown in China. 66 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure 54: China’s slowdown – a larger oil price decline results in lower GDP and welfare in Russia Source: Authors’ estimates. Simulating the Future: A Discussion on Sensitivity 67 A higher oil price response to the India expansion scenario would lead to higher growth and welfare in Russia as the terms of trade improve substantially (Figure 55). However, exports would be lower in real terms as the appreciation of the exchange rate, driven by higher oil prices, reduces the competitiveness of non-oil tradable sectors. Figure 55: India’s expansion – A greater oil price response would boost GDP and welfare in Russia 1,9 1,37 Source: Authors’ estimates. Rigidities in labor markets exacerbate the negative impacts of external shocks and reduce their positive impacts The treatment of factor markets in our model features adjustment to a long-term equilibrium where factors are mobile across sectors. Wage rates are uniform across sectors and adjust to maintain the constant labor supply. The demand for labor across sectors is determined endogenously, with the most competitive sectors attracting the largest supply of workers. This approach cannot reflect market frictions, such as limited access to information or regulatory restrictions that may limit factor mobility14. To explore the potential impact of more rigid factor markets, this sensitivity analysis assumes lower factor substitution elasticities. We consider that the labor market elasticities are half the level assumed in the main scenario. All the parameters used in the main scenarios are from the GTAP behavior database. 14 The model does assume some rigidities, including that natural resources and land are sector-specific. The adoption of the vintage capital approach (Old versus New capital) also enables us to capture some rigidities in the capital market as explained above. 68 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? The negative effect of external shocks is magnified with impediments to the movement of workers across sectors and regions (Figure 56 and Figure 57). GDP is 0.22 percent lower than the reference scenario in response to a slowdown in China compared to 0.17 percent lower in the main scenario, which assumes more rapid labor market adjustment. Impediments to the reallocation of labor limit the release of workers from declining sectors to support expanding sectors. Conversely, assuming labor market rigidities, GDP rises by slightly less in response to more rapid growth in India. Figure 56: China’s slowdown – GDP is lower with Impediments to labor mobility Household utility Household saving -0,22 Terms of Trade Real exchange rate -1,9 -2,1 Source: Authors’ estimates. Simulating the Future: A Discussion on Sensitivity 69 Figure 57: India’s expansion – the rise in GDP is smaller with impediments to labor mobility Source: Authors’ estimates. Limitations on consumers and firms’ abilities to adjust lead to worse outcomes in response to external shocks As noted above, the impact on Russia of changes in China or India depends, in part, on the response in other countries (third country effects). The Envisage / CGE model assumes a certain potential to substitute among sources of supply of imports and destinations of exports. However, in reality, this substitution may be limited for various reasons such as trade barriers and non-trade barriers (e.g., product standards, geography, differences in language). This sensitivity analysis accounts for these rigidities by assuming lower trade elasticities. The elasticities used for the main analysis are from GTAP. In this section, the elasticities of substitution between domestic goods and imports, and the elasticities of substitution between imports of different origins are set to half of the corresponding GTAP levels. The impact of external shocks on growth and welfare are easier to mitigate if consumers and producers have more flexibility to adjust their purchases and foreign sales. Less flexibility in this respect leads to lower growth and welfare because of the deterioration in the terms of trade. For example, with lower constant elasticity of transformation (CET) export elasticities, Russian GDP and welfare are lower as a result of a slowdown in China, reflecting smaller third country effects. By 2030, GDP would be 0.33 percent lower than in the reference scenario, almost twice the level of impact in the scenario with higher elasticities. Likewise, the positive impact of India’s expansion would be weakened by lower CET elasticities, meaning less flexibility15. 15 Results are presented in the Annex. 70 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Higher FDI inflows from China would significantly benefit the Russian economy Our analysis does not address the potential for a shift from inward FDI to outward FDI as part of China’s rebalancing. Although China’s net FDI to Russia is small, likely increases in outward FDI from China because of rebalancing represent an important opportunity for Russia. Only a few years ago, outward FDI from China was negligible, while inward FDI was around 3 percent of China’s GDP. This has changed dramatically: In 2015, outward FDI from China amounted to US$167 billion, roughly 70 percent of inward FDI. And the share of Russia’s net inflows of FDI coming from China increased from 0.2 percent in 2007 to 10 percent in 2015. While Chinese firms gained access to foreign technology and international markets through inward FDI in the past, these firms are increasingly gaining this access through outward FDI, similar to other economies that moved towards high-income status. To assess the likely effect of increased Chinese FDI to Russia, the China rebalancing scenario is combined with an ad hoc increase in FDI from China equal to 1 percent of Russia’s 2017 GDP over the following 12 years. An increase in FDI inflows would amplify the positive impact of China’s rebalancing on Russian growth and welfare. With an increase of FDI equivalent to 1 percent of Russia’s 2017 GDP, Russia’s GDP would be 0.9 percent higher than in the reference scenario, or it would experience fifty times the impact of rebalancing without higher FDI inflows (Figure 58). This points to the importance of creating conditions conducive to capturing a portion of FDI outflows generated by changes in China’s economic structure. On the other hand, higher FDI inflows accentuate the appreciation of the real exchange rate due to China rebalancing so that exports are lower in sectors with declining import demand in China, such as high-skilled manufacturing and low-skilled services (Figure 58). Figure 58: China’s rebalancing – Russia’s growth is higher but exports are lower with higher FDI inflows from China Source: Authors’ estimates. 8. The Swinging Pendulum: Policy Implications for Russia Changes in the global economic environment have important implications for the Russian economy. A slowdown in China, a shift in China from investment to consumption, and a more rapid expansion in India would affect Russia’s economy. The size and composition of Russian exports would be affected, leading to changes in the terms of trade and government revenues, thus affecting growth and welfare. Improving the flexibility of Russia’s economy would increase its ability to mitigate the impact of adverse developments while enabling it to benefit from positive ones. This analysis has several policy implications: (i) Overall, our analysis provides yet more reason for Russia to pursue domestic structural reforms, which would enable it to better capitalize on the opportunities that a dynamically changing China and India have to offer. This modeling exercise assumes a frictionless labor and goods market and low trade barriers. Reducing frictions in the Russian labor market (because of low immobility and rising informality) and in the goods market (because of poor connectivity) would enable Russia to take greater advantage of opportunities and cope more effectively with challenges presented by the global economic environment. Also, the potential for reductions in welfare due to adverse economic developments underlines the importance of improving protection for adversely affected households in Russia. (ii) The RCA findings, considering the necessary caveats associated with this approach, suggest sectors that hold promise for deepening trade relationships. These include not only predominantly natural resource based industries, but also key services sectors such as construction, transport services, and communications. (iii) The results may overstate the third country trade effects from external shocks because non-tariff barriers are not considered (although the model does capture the impact of trade tariffs). This underlines the importance of reducing non-tariff barriers, particularly within the Eurasian trading bloc. (iv) The finding that levels of Russian exports to both China and India are below their natural potential underscores the importance of export diversification, particularly reducing dependence on natural resources and promoting trade in services between China to Russia, such as increased tourism. (v) Finally, the results emphasize the importance of policy measures that increase mutually beneficial trade and FDI flows between China, India, and Russia. For example, from being a consumer / importer of Russia’s nuclear machinery, equipment, and technology, India is now positioning itself as a low-cost supplier / exporter of such machinery, equipment, and technologies to Russia, thereby increasing Russia’s global competitiveness in this area. There may well be implications for China’s new Belt and Road Initiative (BRI). China, for example, has won a $375 million contract to build a high-speed railway line connecting Moscow to Kazan, with a possible future extension to Beijing. 72 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Bibliography Agosin, M. R. (2007). “Export Diversification and Growth in Emerging Economies.” Working Paper No. 233. Departamento de Economía, Universidad de Chile. Ahuja, A., and A. Myrvoda.(2012). “The Spillover Effects of a Downturn in China’s Real Estate Investment.” IMF Working Paper, No. 12/266. Ahuja, A., and M. Nabar. (2012). “Investment-Led Growth in China: Global Spillovers.” IMF Working Paper, No. 12/267. Albert, M., C. Jude, and C. Rebillard. (2015). “The Long Landing Scenario: Rebalancing from overinvestment and excessive credit growth. Implications for potential growth in China.” Banque de France Eurosysteme, No. 572. Alcala, F., and A. Ciccone. (2004). “Trade and Productivity.” The Quarterly Journal of Economics, Vol. 119(2), pp. 612– 645. Anderson, D., J. Kriljenko, P. Drummond, P. Espaillat, and D. Muir. (2015). “Spillovers from China onto Sub-Saharan Africa: Insights from the Flexible System of Global Models.” IMF Working Paper No. 15/221. Aw, B.Y., and A. Hwang. (1995). “Productivity and the Export Market: A Firm-Level Analysis.”Journal of Development Economics, Vol. 47, pp.313-332. Aw, B.Y., M. Roberts, and T. Winston. (2007). «Export Market Participation, Investments in R&D and Worker Training, and the Evolution of Firm Productivity.»The World Economy, Vol. 30(1), pp. 83-104. Bandara, A. (2012). “Growth spillovers: Do China’s trade and investment matter for African growth?” UNDP. Bernard, A., and J.B. Jensen. (1999). “Exceptional exporter performance: Cause, effect, or both?” Journal of International Economics, Vol. 47, pp.1-25. Cadot, O., C. Carrère, V. Strauss-Kahn.(2011). “Export diversification: What’s behind the hump?” In The Review of Economics and Statistics, Vol. 93(2), pp. 590-605. Carrere, C., O. Cadot,V. Strauss-Kahn. (2011). “Trade diversification: drivers and impacts.” InTrade and Employment:From Myths to Facts,Jansen, M., R. Peters, and J.M Salazar-Xirinachs.ILO-EC International Labour Office – European Commission, Geneva, pp. 253-307 Cashin, P., K. Mohaddes, and M. Raissi. (2016). “China’s Slowdown and Global Financial Market Volatility: Is World Growth Losing Out?” IMF Working Paper, No. 16/63. Center for International Development at Harvard University. (2015). “New Global Growth Projections Predict the Decade of India.” Available at: http://atlas.cid.harvard.edu/rankings/growth-predictions/ Clerides, S., S. Lach, and J. Tybout. (1998). “Is learning-by-exporting important? Micro dynamic evidence from Colombia, Mexico, and Morocco.”Quarterly Journal of Economics (53), pp. 903–947. Coe, D. T., E. Helpman, and A. W. Hoffmaister. (2009). “International R&D spillovers and institutions.” European Economic Review, Vol. 53(7), pp.723–741. Crespi, G., C. Criscuolo, and J. Haskel. (2008). «Productivity, exporting, and the learning-by-exporting hypothesis: Direct evidence from UK firms.» Canadian Journal of Economics, Vol. 41(2), pp. 619-638. De Loecker, J. (2007). “Do Exports Generate Higher Productivity? Evidence from Slovenia.”Journal of International Economics, Vol. 73, pp.69–98. Demidova, Svetlana, H.L. Kee, and K. Krishna. (2006). “Do Trade Policy Differences Induce Sorting? Theory and Evidence from Bangladeshi Apparel Exporters.” NBER working paper No. 12725. 74 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Dizioli, A., J. Guajardo, V. Klyuev, R. Mano, and M. Raissi. (2016). “Spillovers from China’s Growth Slowdown and Rebalancing to the ASEAN-5 Economies.” IMF Working Paper No. 16/170. Dollar, D. (1992). “Outward-Oriented Developing Economies Really Do Grow More Rapidly: Evidence from 95 LDCs, 1976-1985.” Economic Development and Cultural Change, Vol. 40(3), pp.523– 44. Dorrucci, E., G. Pula, and D. Santabarbara. (2013). “China’s Economic Growth and Rebalancing.” European Central Bank Occasional Paper Series, No. 142. Duval, R., K. Cheng, K. Oh, R. Saraf, and D. Seneviratne. (2014). “Trade Integration and Business Cycle Synchronization: A Reappraisal with Focus on Asia.” IMF Working PaperNo. 14/52. Eaton, S. Kortum, and F. Kramarz. (2007). “An Anatomy of International Trade: Evidence from French Firms.”Mimeo. Eaton, S. Kortum, and F. Kramarz. (2004). “Dissecting Trade: Firms, Industries, and Export Destinations.”American Economic Review, Vol. 94, pp.150-154. The Economist. (2010). “India’s surprising economic miracle.” September 30. Available at: http://www.economist. com/node/17147648 Ethier, W. (1982). “National and International Returns to Scale in the Modern Theory of International Trade.”American Economic Review, Vol. 72(3), pp.389-405. Fernandes, A. (2007). “Trade Policy, Trade Volumes and Plant-Level Productivity in Columbian Manufacturing Industries.”Journal of International Economics, Vol. 71(1), pp.52-71. Gauvin, L., and C. Rebillard. (2015). “Towards Recoupling? Assessing the Global Impact of a Chinese Hard Landing through Trade and Commodity Price Channels.” Banque de France Working Paper, No. 562. Gill, Indermit S., Ivailo Izvorski, Willem van Eeghen, and Donato De Rosa. (2014). “Diversified development: Making the most of natural resources in Eurasia.” World Bank, Washington, DC. ISBN 978-1-4648-0119-8 (alk. paper) — ISBN 978-1-4648-0120-4 (ebook). Girma, S., D. Greenaway, and R. Kneller. (2004). «Does Exporting Increase Productivity? A Microeconometric Analysis of Matched Firms.» Review of International Economics, Vol. 12(5), pp.855-866. Grossman, G.M.,and E. Helpman. (1991). Innovation and Growth in the Global Economy Cambridge, MIT Press. Haddad, M. (1993). “How Trade Liberalization Affected Productivity in Morocco.” World Bank Policy Research Working Paper 1096. Halpern, L., M. Koren, and A. Szeidl. (2009).“Imported Inputs and Productivity.” Working Paper Central European University. Hausmann, R., J. Hwang, and D. Rodrik. (2007). “What you export matters.” Journal of Economic Growth, Vol.12(1), pp.1–25. Hesse H. (2008) “Export Diversification and Economic Growth.” Commission on Growth and Development, The International Bank for Reconstruction and Development / The World Bank, Working paper No. 21. Hicks, B., and L. Kilian. (2013). “Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003- 2008?” Journal of Forecasting, 32(5), 385–394. Imbs, J., and R. Wacziarg. (2003). “Stages of Diversification.”American Economic Review, Vol. 93(1), pp. 63–86. IMF. (2017). “A Shifting Global Economic Landscape.” January 2017. Available at: https://www.imf.org/external/ pubs/ft/weo/2017/update/01/#footT1 Bibliography 75 IMF. (2016). “Asia: Maintaining Robust Growth amid Heightened Uncertainty.” Regional Economic Update, Asia and Pacific Department. IMF. (2013). “World Economic Outlook, October 2013: Transitions and Tensions.” Kawai, M., and F. Zhai. (2009). “China–Japan–United States integration amid global rebalancing: A computable general equilibrium analysis.” Journal of Asian Economics, Vol. 20 (6), pp. 688-699. Klinger, B., D. Lederman. (2006). “Diversification, innovation, and imitation inside the global technology frontier.” World Bank Policy Research Working Paper No. 3872. Krishna, Pravin, and D. Mitra. (1998). “Trade Liberalization, Market Discipline and Productivity Growth: New Evidence From India.” Journal of Development Economics, Vol. 56 (2), pp.447-462. Lakatos, Csilla, Maryla Maliszewska, Israel Osorio‐Rodarte, and Delfin Go. (2016). “China’s Slowdown and Rebalancing: Potential Growth and Poverty Impacts on Sub‐Saharan Africa.” Policy Research Working Paper 7666, World Bank, Washington, DC. Markusen, J. (1989); “Trade in Producer Services and in Other Specialized Intermediate Inputs.”American Economic Review, Vol. 79(1), pp.85-95. Melitz, M. (2003). “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity.” Econometrica, Vol. 71(6), pp. 1695-1725. Nabar, M., and P. N’Diaye. (2013). “Enhancing China’s Medium-Term Growth Prospects: The Path to a High-Income Economy.” IMF Working Paper13/204. Pavcnik, N. (2002). “Trade Liberalization, Exit and Productivity Improvement: Evidence from Chilean Plants.”Review of Economic Studies, Vol. 69(1), pp. 245-276. Pettis, M. (2014). “The Impact of Reform on Growth.” Blog post, available at https://web.archive.org/ web/20140130204630/http://blog.mpettis.com/2014/01/the-impact-of-reform-on-growth/ PWC. (2017). “Global Economy Watch: Predictions for 2017: Globalisation takes a backseat.” January 2017. Roache, S. (2012). “China’s Impact on World Commodity Markets.” IMF Working Paper. Rodrik, D. (2015). Economic Rules: The Rights and Wrongs of the Dismal Science. W.W. Norton & Company. Sachs, J.D., and A. Warner. (1997). “Natural resource abundance and economic growth.”NBER Working Paper No. 5398. Tybout, J., and D. Westbrook. (1995). “Trade Liberalization and the Dimensions of Efficiency Change in Mexican Manufacturing Industries.” Journal of International Economics, Vol. 39, pp.53-78. Van Biesebroeck, J. (2005). «Exporting raises productivity in sub-Saharan African manufacturing firms.» Journal of International Economics, Vol. 67(2), pp. 373-391. World Bank. (2016). “The Impact of China on Europe and Central Asia.” ECA Economic Update Spring 2016 (April), Washington, DC. Doi: 10.1596/978-1-4648-0912-5. World Bank. (2017). “Global Outlook: Subdued Growth, Shifting Policies, Heightened Uncertainty.” In Global Economic Prospects: “Weak Investment in Uncertain Times.” January 2017. Xuefeng, Q., and M. Yasar. (2016). “Export Market Diversification and Firm Productivity: Evidence from a Large Developing Country.”World Development, Vol. 82, pp. 28–47. 76 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Annex 1: Mapping Between the ENVISAGE Model and GTAP Database Table A1. 1: Mapping between model and GTAP factors of production Model factors of production GTAP factors of production Unskilled labor Agriculture and other low-skilled workers Service and sales workers Clerical support workers Skilled labor Technicians and associate professionals Managers and professionals Capital Capital Land Land Natural resource Natural resource Table A1. 2: Mapping between model and GTAP sectors Model sectors GTAP sectors Agriculture Paddy rice Wheat Cereal grains nec Vegetables, fruit, nuts Oil seeds Sugar cane, sugar beet Plant-based fibers Crops nec Forestry Fishing Livestock Bovine cattle, sheep and goats, horses Animal products nec Raw milk Wool, silk-worm cocoons Natural Resources Coal Minerals nec Oil, Gas, and Refined Oil Oil Gas Petroleum, coal products 78 A Slowing China and Resurging India: How will the pendulum swing for Russia? Low-skilled Manufacturing Bovine meat products Meat products nec Vegetable oils and fats Dairy products Processed rice Sugar Food products nec Beverages and tobacco products Textiles Wearing apparel Leather products Wood products Mineral products nec Ferrous metals Metals nec Metal products Manufactures nec High-skilled Manufacturing Paper products, publishing Chemical, rubber, plastic products Motor vehicles and parts Transport equipment nec Electronic equipment Machinery and equipment nec Low-skilled Services Electricity Gas manufacture, distribution Water Construction Trade Transport nec Water transport Air transport Dwellings High-skilled Services Communication Financial services nec Insurance Business services nec Recreational and other services Public Administration, defense, education, health Annex 1: Mapping Between the ENVISAGE Model and GTAP Database 79 Table A1. 3: Mapping between model and GTAP regions Model regions GTAP regions Russian Federation Russian Federation China China India India OECD, excluding Mexico Canada United States of America European Union and Europe Free Trade Area Austria Belgium Cyprus Denmark Estonia Finland France Germany Greece Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Spain Sweden United Kingdom Switzerland Norway Rest of EFTA Bulgaria Major OPEC countries Indonesia Ecuador Venezuela (Bolivarian Republic of) Iran Kuwait Qatar Saudi Arabia United Arab Emirates Nigeria 80 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Rest of Europe and Central Asia Czech Republic Hungary Slovakia Slovenia Albania Belarus Croatia Romania Ukraine Rest of Eastern Europe Rest of Europe Kazakhstan Kyrgyzstan Rest of Former Soviet Union Armenia Azerbaijan Georgia Rest of World Australia New Zealand Rest of Oceania Hong Kong SAR, China Japan South Korea Mongolia Taiwan, China Rest of East Asia Brunei Darussalam Cambodia Laos Malaysia Philippines Singapore Thailand Vietnam Rest of Southeast Asia Bangladesh Nepal Pakistan Sri Lanka Rest of South Asia Mexico Rest of North America Argentina Bolivia Annex 1: Mapping Between the ENVISAGE Model and GTAP Database 81 Brazil Chile Colombia Paraguay Peru Uruguay Rest of South America Costa Rica Guatemala Honduras Nicaragua Panama El Salvador Rest of Central America Dominican Republic Jamaica Puerto Rico Trinidad and Tobago Caribbean Bahrain Israel Jordan Oman Turkey Rest of Western Asia Egypt Morocco Tunisia Rest of North Africa Benin Burkina Faso Cameroon Cote d’Ivoire Ghana Guinea Senegal Togo Rest of Western Africa Central Africa South Central Africa Ethiopia Kenya Madagascar Malawi 82 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Mauritius Mozambique Rwanda Tanzania Uganda Zambia Zimbabwe Rest of Eastern Africa Botswana Namibia South Africa Rest of South African Customs Union Rest of the World Annex 2: Literature Review – Impact of Transformations in China Study name Author (s) Year of Area of Methodo- Main scenarios Impact of Results publi- focus logy modelling cation The Spillover Ahuja, A., 2012 Real A two-region A temporary, exogenous The impact A 1% decline Effects of a and A. Myr- estate in- factor-aug- one standard-deviation shown on G20 in real estate Downturn in voda. vestment mented VAR growth shock to real estate trading part- investment China’s Real that allows for investment in China. “The ners should would reduce Estate Invest- interaction shock dampens within be larger than China’s real GDP ment between China a few months and dissi- the model ac- by 0.1% in the and the rest of pates fully after around 36 counts for. first year, which the G20 econo- months. Specifically, this is would cause mies. a onetime 49-percentage- global output point (seasonally adjusted, to decline by annualized) drop in real 0.05%. estate investment growth that reverts to trend growth largely within 4–5 months. While this is a temporary, negative growth shock, the decline in real es- tate investment level is permanent. The shock is approximately equivalent to a 2-percent drop from baseline in real estate investment level 12 months after. The analysis does not assume policy response beyond that which was already in the sample.” Investment- Ahuja, A., 2012 Global Factor-aug- The model A 1% slowdown Led Growth in and M. impact mented VAR was not in investment China: Global Nabar. intended in China would Spillovers to capture prompt a slow- indirect trade down in global exposure growth of 0.1%. through vertically- integrated intermediate economies. It does not cap- ture financial exposures. The Long Albert, M., 2015 Global Global VAR Baseline scenario – slow, Hard landing Landing C. Jude, and impact progressive slowdown in would result in Scenario: C. Rebillard. GDP from 7.4% in 2014 to a 7.5% cumu- Rebalancing 6.4% by end of 2019; lated growth loss from overin- after 5 years in vestment and Hard landing – drop from emerging econo- excessive 2015Q1 for 2 years, before mies; advanced credit growth. stabilising at 3%. economies Implications would see a de- for potential cline of -2.8%. growth in China 84 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Study name Author (s) Year of Area of Methodo- Main scenarios Impact of Results publi- focus logy modelling cation Growth Bandara, A. 2012 Endogenous Unreliable There is a grow- spillovers: Do growth model results for ing impact of China’s trade magnitude exports to China and invest- of Chinese from sub-Saha- ment matter FDI flow ran African coun- for African on African tries, though this growth? growth, due to trend has yet limited data. to overtake the influence of sub- Saharan exports to the RoW. China’s Slow- Cashin, P., 2016 Global GVAR model They estimate down and Mohaddes, estimated for that a 1% perma- Global Finan- K. & Raissi, 26 countries/ nent negative cial Market M. regions over Chinese GDP Volatility: Is the pe- shock would World Growth riod 1981Q1 to have a 0.23% Losing Out? 2013Q1. decrease in global growth. Spillovers Dizioli, A., J. 2016 ASEAN-5 GVAR -Private demand shock: 1) A negative from China’s Guajardo, lower investment due to GDP shock in Growth Slow- V. Klyuev, R. financial stress; China of 1% down and Re- Mano, and -Supply shock - lower would prompt balancing to M. Raissi. productivity growth in the global growth the ASEAN-5 tradable goods sector; to fall by 0.23%, Economies -Policy shock: changes in and oil prices to the government’s budget fall by 3%. composition. 2) Countries with consider- able trade with China and which are commod- ity exporters experience the greatest spill- overs: Malaysia, Singapore, and Thailand experi- ence growth falling by 0.38%, 0.32% and 0.26%, respec- tively. 3) Real oil prices would stabilise 2% below the baseline. 4) Again Malay- sia, Singapore, and Thailand suf- fer the greatest falls in growth. Annex 2: Literature Review- Impact of Transformations in China 85 Study name Author (s) Year of Area of Methodo- Main scenarios Impact of Results publi- focus logy modelling cation Towards Gauvin, 2015 Sampled Global VAR Hard landing scenario – Dummy Emerging econo- Recoupling? L., and C. 36 coun- method, China drops sharply over variables in- mies would be Assessing the Rebillard. tries, rep- adapted to a two year period, stabilis- cluded in the the worst hit by Global Impact resenting conditional ing at 3% growth per year, VARX model a hard landing, of a Chinese 88% of forecasting. while investment nearly to account with a growth Hard Landing the global Metal and stagnates for crises and loss of 7.5% through Trade economy. oil markets exceptional after five years. and Com- modelled sepa- Baseline soft landing sce- circumstanc- modity Price rately. nario – GDP growth slows es. Channels gradually from 7.4% in 2014 to 6.4% at end 2019. Model favours regional rather than indi- vidual country results, as for the latter “the drop in domestic GDP and invest- ment is not related to similar evolu- tion in foreign variables.” As such, impact results for some countries in a hard landing scenario will be under- estimates (Australia and Korea), whilst for others it may be an overestimate (Argentina). China-Japan- Kawai, M., 2009 China; CGE model United States and F. Zhai. Japan; based on a integration United global gen- amid global States eral equilib- rebalancing: rium model A comput- developed able general by van der equilibrium Mensbrugghe analysis (2005) and Zhai (2008). Model enhanced for report by incor- porating recent heteroge- neous-firms trade theory into an empiri- cal global CGE framework. 86 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Study name Author (s) Year of Area of Methodo- Main scenarios Impact of Results publi- focus logy modelling cation China’s Lakatos, C., 2016 China; LINKAGE, a Past trends - uses historic Only “real” 1) Past trends: slowdown and M. Mal- sub- global, multi- changes in macroeconomic effects of By 2030 average rebalancing: iszewska, I. Saharan sector, multi- variables to assume the China’s trans- annual real GDP Potential Osorio-Rod- Africa factor, dynamic growth rate will remain fixed formation growth of 6%, growth and arte, and D. CGE model. at 7% until 2030 and the are captured, and GDP per poverty Go. share of investment and and as such, capita growth of impacts on consumption will remain at the impact 3.7% Sub-Saharan 2015 levels. of financial 2) A 1% slow- Africa Slowdown scenario of markets and down of annual growth from current 7% to investment GDP in China 4.6% in 2030. linkages is from 2016-2030 Rebalancing scenario: the poorly ac- will lead to a share of investment in total counted for. global decline GDP falls gradually from in GDP of 0.6% 46.7% to 35.5% and growth and a decline in in the services sector from sub-Saharan Af- 50% in 2015 to 61% in rica by 1.1% by 2030. 2030 relative to Slowdown & rebalancing. the past trends scenario. 3) Chinese world exports to increase 7.9% faster by 2030 than in the past trends scenario. 4) GDP gains of 4.8% globally and 4.7% in sub- Saharan Africa by 2030, relative to the past trends scenario. China’s Im- Roache, S. 2012 VAR modelling A shock fall in pact on World China’s growth Commodity rate by 1% will Markets lead to a 2.5% decrease in the real price of oil after 4 quarters. Annex 3: Foreign Direct Investment in Russia In Russia, net inflows of foreign direct investment have decreased in recent years. In 2015, net FDI inflows fell to $6.5 billion, down from a peak of $69.2 billion in 2013. Between 2010 and 2013, net FDI increased from $43.2 billion in 2010 to $69.2 billion. The decline in net FDI inflows since 2013 reflects both an increase trend in de-investment and a decreasing trend in investment. The net FDI inflows are computed by considering positive FDI flows into Russia from foreigners net of negative FDI flows (dis-investment) out of Russia from foreigners. The data shows that positive inward FDI declined to US$134 billion in 2015 (down from US$194 billion in 2013). In addition, negative FDI flows increased slightly over the time period to US$128 billion (up from US$124 billion in 2013) (Figure A3.1). Figure A3. 1: FDI inflows into Russia (USD, millions) Source: Central Bank of Russia Wholesale and retail trade (including motor vehicles and motor cycles), manufacturing, and financial and insurance activities dominate FDI inflows in Russia (Table A3.1). However, these three sectors also recorded the most dis-investment in Russia in 2015. They accounted for nearly two thirds of positive FDI inflows to the country and nearly 63 percent of negative FDI inflows from the country in 2015. However, mining and quarrying received the most net FDI inflows. This was followed by the manufacturing sector as a whole. Basic metals and fabricated metal products, as well as food products, beverages, and tobacco products, were the manufacturing sectors that received the highest net FDI inflows in Russia in 2015 (These were the two manufacturing sectors that received the most positive FDI inflows). However, other manufacturing sectors that also received significant positive FDI inflows also had negative FDI inflows, including coke and refined petroleum products, chemicals and chemical products, other non-metallic mineral products, and machinery and equipment. 88 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Table A3. 1: Russia’s net FDI inflows by sector, 2015 Positive FDI Negative FDI Sector inflows inflows Net FDI inflows (million US$) (million US$) (million US$) WHOLESALE AND RETAIL TRADE; REPAIR OF 37,998 34,001 3,997 MOTOR VEHICLES AND MOTORCYCLES MANUFACTURING 32,013 25,174 6,839 FINANCIAL AND INSURANCE ACTIVITIES 18,649 21,538 -2,889 MINING AND QUARRYING 17,426 6,503 10,923 OTHER SERVICE ACTIVITIES 9,974 12,318 -2,344 REAL ESTATE ACTIVITIES 5,789 5,450 339 INFORMATION AND COMMUNICATION 2,466 8,980 -6,514 TRANSPORTATION AND STORAGE 2,262 3,951 -1,689 CONSTRUCTION 2,078 3,129 -1,051 ELECTRICITY, GAS, STEAM AND AIR 1,120 3,061 -1,941 CONDITIONING SUPPLY AGRICULTURE, FORESTRY AND FISHING 671 401 270 ACCOMMODATION AND FOOD SERVICE 461 350 111 ACTIVITIES ARTS, ENTERTAINMENT AND RECREATION 363 513 -150 RENTAL AND LEASING ACTIVITIES 203 675 -472 PROFESSIONAL, SCIENTIFIC AND TECHNICAL 151 61 90 ACTIVITIES HUMAN HEALTH AND SOCIAL WORK ACTIVITIES 139 223 -84 WATER SUPPLY; SEWERAGE, WASTE 27 47 -20 MANAGEMENT AND REMEDIATION ACTIVITIES EDUCATION 4 2 2 PUBLIC ADMINISTRATION AND DEFENCE; 0 0 0 COMPULSORY SOCIAL SECURITY ACTIVITIES OF HOUSEHOLDS AS EMPLOYERS; UNDIFFERENTIATED GOODS-AND-SERVICES- 0 0 0 PRODUCING ACTIVITIES OF HOUSEHOLDS FOR OWN USE ACTIVITIES OF EXTRATERRITORIAL 0 0 0 ORGANISATIONS AND BODIES Source: Central Bank of Russia. Russia’s FDI flows are diversified across countries (Table A3.2). Data on net inward FDI into Russia shows that in 2015, at least 85 countries had inward investments into Russia (though in some of these countries net inward investment was negative – meaning that what the country invested in Russia was less than what the country dis-invested in Russia). Similarly, outward FDI from Russia was reported to over 90 countries in the world (again, not all of this was net positive). Of the net FDI inflows, around 91 percent came from countries in the non- Commonwealth of Independent States (non-CIS). Bahamas (US$5 billion), the British Virgin Islands (US$2.2 billion), and Jersey (US$2.1 billion) were the largest contributors to Russia’s net FDI inflows. The net FDI inflows from the CIS countries (Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan) were only around US$600 million, with Kazakhstan accounting for a large majority (72 percent). Other important sources of FDI into Russia include France, Germany, and the United Kingdom. In fact, China was the eighth most important source of net FDI into Russia but it ranked 109th in terms of negative net inward FDI. Net outward FDI from Russia is also reported to financial hubs including Cyprus, the British Virgin Islands, Bahamas, Annex 3: Foreign Direct Investment in Russia 89 and the Cayman Islands, but also to other countries including Turkey, Finland, and the United States. Russian FDI outflows to China and India are less important for the country, ranking 51st and 57th, respectively, though they were net positive in 2015. Table A3. 2: Russia’s net FDI inflows and outflows by country, 2015 Net inward FDI Net outward FDI Country Rank Value (million Country Rank Value (million US$) US$) BAHAMAS 1 5,090 CYPRUS 1 4,308 BRITISH VIR- 2 BRITISH VIRGIN 2 GIN ISLANDS 2,242 ISLANDS 3,296 JERSEY 3 2,122 TURKEY 3 1,475 BERMUDA 4 1,692 FINLAND 4 1,454 FRANCE 5 1,686 JERSEY 5 1,258 GERMANY 6 1,483 BAHAMAS 6 1,028 UNITED KING- 7 7 DOM 1,104 CAYMAN ISLANDS 934 CHINA 8 645 UNITED STATES 8 819 IRELAND 9 623 LUXEMBOURG 9 785 JAPAN 10 447 AUSTRIA 10 746 INDIA 109 -17 CHINA 51 11 INDIA 57 6 Source: Central Bank of Russia. 90 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Annex 4: Supplementary Tables and Figures Related to the Simulation Scenarios Figure A4. 1: The impact of the combined scenario (scenario 4) on Russia’s exports differs by sector 92 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Annex 5: Russia’s Current Trade Patterns Russia, China, and India’s Trade and FDI Flows Composition and direction of Russia’s merchandise and services trade Russia exported US$393 billion worth of goods and services in 2015, making it the 17th largest exporter in the world. Russia’s export share of GDP in 2013-2015 was nearly 28 percent. Of the top ten largest economies in the world, Russia’s export share of GDP was only lower than that of Germany, Italy, France, and United Kingdom – four economies integrated to one another through the European Union (Table A5.1). Table A5. 1: Export Performance of the world’s 10 largest economies Country Exports (US$ billions) Exports-to-GDP (%) Exports-to-GDP (%) 2015 2005-2007 2013-2015 Germany 1,573 40.6 46.0 Italy 547 26.1 29.4 France 726 26.9 29.2 United Kingdom 777 25.5 28.3 Russian Federation 393 33.0 27.9 China 2431 35.9 23.6 India 418 20.5 22.7 Japan 773 15.8 17.0 United States 2,264 10.7 13.3 Brazil 231 14.3 12.0 Source: Authors’ computations using data from World Development Indicators. Note: The table shows exports of goods and services as a percentage of GDP for the world’s top 10 largest economies (based on the average GDP between 2013- 2015). Russia’s export performance has declined over the past decade, mainly due to poor performance of merchandise exports. Russia’s Exports to GDP ratio has declined from 33 percent during 2005-2007 to about 28 percent during 2013-2015. The country’s declining export performance is mainly due to its poor performance in merchandise exports. During the past decade, Russia’s export share of GDP has been retrenching for merchandise and has been stagnant for services (Figure A5.1). Merchandise exports, as a percentage of GDP, experienced a steep decrease from around 32 percent in 2005 to less than 25 percent in 2013 (the year prior to the beginning of the recent recession in Russia). On the other hand, services exports, as a share of GDP, have largely been stagnant over the past decade. The recent slight upward trends in Russia’s export shares in GDP (both merchandise and services) are not due to an improvement in export performance, but instead due to the reduction of GDP at a faster rate than the reduction of exports during the recent recession in the country (Figure A5.1). 94 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Figure A5. 1: Russia’s declining export performance Source: Authors’ computations using data from World Development Indicators. In 2015, merchandise exports accounted for 87 percent of Russian exports. These exports are largely concentrated on fossil fuels and related products. Russia is the world’s largest exporter of natural gas and the second largest exporter of oil. The country’s top five merchandise exports to the world are oil, petroleum and coke, gas, chemical rubber products, and non-ferrous metals. The combined export value of the above five products in 2013-2015 (annual average) was nearly US$350 billion or 18.6 percent of GDP. In 2015, the top export destinations of Russia’s merchandise exports were China, Germany, the United States, Belarus, and Italy. In 2015, the top destinations for Russian oil exports were China, Germany, Poland, the Netherlands, and Japan; the top destinations for petroleum and coke exports were the United States, Singapore, Germany, France, and Belgium; and the top destinations for gas exports were Italy, Japan, Belarus, the Netherlands, and Ukraine. Russia’s global market share for goods trade steadily increased until the country underwent a recession. In 2013, Russia’s merchandise exports accounted for more than 2.75 percent of world merchandise imports and it was significantly higher than that in 2000 (Figure A5.2). However, Russia has not been able to increase its market shares in China and India during the past decade. Annex 5: Russia’s Current Trade Patterns 95 Figure A5. 2: Russia’s market share in the goods trade Source: Authors’ computations using data from COMTRADE. Russia exported around US$52 billion worth of services in 2015. The country’s top service exports were transport, other business services, and travel, which collectively accounted for nearly three-quarters of Russia’s services exports in 2015 (Figure A5.3). Figure A5. 3: Composition of Russia’s trade in services, 2015 Source: Authors’ computations using UNCTAD data. 96 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? The performance of Russia’s major services exports has declined over the last five years, though at a slower rate than the decline in GDP. Exports of transport, other business services, and travel, as a percentage of GDP, have increased over the past five years (Figure A5.4). However, in nominal terms, export values of those industries have decreased. Telecommunications, computer and information services, and financial services are emerging as new service exports in Russia. The exports of these two industries as a percentage of GDP have increased during the past five years. However, the export share of GDP of these industries is relatively small (Figure A5.3 and Figure A5.4). Figure A5. 4: Evolution of Russia’s sectoral services exports Source: Authors’ computations using UNCTAD and WDI data. The main destinations for Russia’s services exports were the United Kingdom, Switzerland, the United States, Germany and Kazakhstan. In 2015, the main destinations for Russia’s transport services were Switzerland (US$1.4 Billion), the United Kingdom (US$1.1 Billion), and Cyprus (US$0.9 billion). Russia’s transport services exports to China and India were US$737 million and US$257 million, respectively. The main destinations for Russia’s other business services were the United States (US$1.1 billion), the United Kingdom (US$968 million) and Turkey (US$963 million). China and India imported Russia’s other business services worth US$187 million and US$138 million, respectively. The main destinations for Russia’s travel services were Kazakhstan (US$1.2 billion), Ukraine (US$1.1 billion) and Germany (US$585 million). China and India imported US$460 million and US$34 million, respectively, worth of travel services from Russia in 2015. Table A5. 2: Russia’s main service trading partners – 2015 Exports Imports Destination US$ (million) Origin US$ (million) United Kingdom 3,198 Turkey 6,642 Switzerland 3,055 Germany 5,584 United States 2,775 United Kingdom 5,229 Germany 2,699 United States 4,921 Kazakhstan 2,527 Cyprus 4,414 Total 51,742 Total 88,617 Source: Central Bank of Russia. Annex 5: Russia’s Current Trade Patterns 97 In 2015, Russia imported US$282 billion worth of goods and services, making it the 20th largest importer in the world. Merchandise imports accounted for nearly 70 percent of total Russian imports in 2015. Russia’s top merchandise imports during the period of 2013-2015 were machinery and equipment, chemical rubber products, motor vehicles and parts, electronic equipment, and transport equipment other than motor vehicles. Russia’s top import origins for merchandise imports are the same as its export destinations (China, Germany, the United States, Belarus, and Italy). Russia imported machinery and equipment mainly from China, Germany, and Italy; chemical rubber products from Germany, China, France, the United States, and Italy; and motor vehicles and parts from Japan, Germany, and China. Russia’s GDP share of services imports has been increasing in recent years. In 2015, Russia’s services imports were 6.4 percent of its GDP, up from 4.4 percent in 2011 (Figure A5.5). However, in nominal terms, Russia’s imports of services have declined in recent years. In 2015, Russia imported US$88.6 billion worth of services, down from US$128.4 billion in 2013. Russia’s top services imports were travel, other business services, and transport, which collectively accounted for nearly three quarters of the country’s services imports in 2015 (Figure A5.5). Figure A5. 5: Trends in Russia’s trade in commercial services Source: World Development Indicators. Russia’s main import origins for services were Turkey, Germany, the United Kingdom, the United States, and Cyprus. In 2015, Russia’s main import origins for travel services were Turkey (US$4.8 billion), Egypt (US$3.1 billion), and Germany (US$2.6 billion). Russia imported travel services worth US$762 million from China and US$177 million from India. Russia’s top import origins for other business services were France (US$2.1 billion), the United Kingdom (US$1.8 billion), and Ireland (US$1.8 billion), while imports of other business services from China and India were US$151 million and US$33 million, respectively. Russia’s top import origins for transport services were Cyprus (US$508 million), the United Kingdom (US$408 million), and Belarus (US$398 million), and imports of transport services from China and India were US$137 million and US$10 million, respectively. Russia’s deficit in the balance of services is narrowing. In 2015, Russia’s deficit was US$36.9 billion compared to the 2013 deficit of US$58.3 billion. In 2015, the largest deficit was recorded in travel services (US$ 26.5 billion), followed by other business services (US$5.8 billion) and charges for the use of intellectual property (US$ 4.9 billion). Russia had the largest services trade surplus in transport services (US$5 billion). 98 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Sectors contributing to Russia’s export growth Natural resource based products are the top merchandise sectors that contributed to Russia’s export growth to the world as well as to China and India, while transport, other business services, and travel were the top services sectors that contributed to Russia’s export growth to the world during the past decade. Table A5.3 presents the sectoral contribution of Russia’s export growth with the world and with China and India in goods and services. The top twenty contributing sectors are presented in the table. Russia’s total exports (goods and services) to the world grew by more than 60 percent from the 2005-2007 period to the 2013-2015 period. Petroleum and coke, oil, and gas are the top merchandise exports that contributed to this growth. Russia’s merchandise exports to China more than doubled during the past decade, mainly driven by increases in oil, coal, non-ferrous metals, and lumber exports. Russia’s exports to India nearly doubled during the same period, mainly driven by other mining, non-ferrous metals, and chemical rubber products. Table A5. 3: Sectoral contribution to Russia’s export growth, 2005-2007 to 2013-2015 Export growth to the world Export growth to China Export growth to India Sector Contribu- Sector Contribution Sector Contribution tion (%) (%) (%) 1 Petroleum & Coke 18.0 Oil 79.6 Other Mining 40.5 2 Non-Ferrous Oil Coal 13.6 11.1 Metals 28.3 3 Non-Ferrous Chemical Rubber Gas 6.8 Metals 9.4 Products 12.6 4 Chemical Rubber Lumber Petroleum & Coke Products 4.1 8.0 7.1 5 Transport 2.9 Other Mining 5.4 Coal 6.9 6 Other Business Petroleum & Coke Veg & Fruit Services 2.6 4.8 5.7 7 Paper & Paper Paper & Paper Coal 2.1 Products 1.0 Products 4.4 8 Other Machinery Other Transport Other Mining 1.5 & Equipment 1.0 Equipment 3.2 9 Other Machinery & Other Food Electricity 1.3 0.9 Equipment 1.7 10 Other Machinery & Other Food Vegetable Oils Equipment 1.1 0.7 0.8 11 Other Travel Textiles 1.0 Manufacturing 0.4 0.5 12 Other Transport Oil Seeds Lumber Equipment 0.9 0.4 0.4 13 Telecommunications, Fabricated Metal Electronic Computer, and Infor- Products Equipment mation Services 0.9 0.3 0.4 14 Other Manufacturing 0.8 Vegetable Oils 0.2 Leather 0.3 15 Other Transport Fabricated Metal Wheat 0.7 Equipment 0.1 Products 0.1 16 Other Animal Electronic Equipment Wool 0.7 Products 0.1 0.1 17 Vegetable Oils 0.7 Veg & Fruit 0.1 Other Food 0.1 18 Lumber 0.6 Other Crops 0.1 Other Crops 0.1 19 Non-Metallic Non-Ferrous Metals Fishing 0.4 0.1 Minerals 0.0 20 Paper & Paper Prod- Beverages and Beverages and ucts 0.4 Tobacco Products 0.0 Tobacco Products 0.0 Total 63.5 115.4 92.2 Source: Authors’ calculations using data from COMTRADE and UNCTAD. Note: The table shows the contribution of each sector to total export growth, measured as the sector’s export growth multiplied by the share in exports. Annex 6: Presentation of the CGE model Static module The following sections provide an overview of the key relationships in the CGE model; a detailed discussion of the model can be found in Van der Mensbrugghe (2017)16. The model is developed from the neoclassical structural modeling approach presented in de Melo et al. (1982)17. The underlying assumptions are mainly those encountered in the standard CGE literature (de Melo and Tarr, 1992). Therefore, only three key aspects are laid out in this note: (i) the production function; (ii) the modeling of household income and consumption; and (iii) international trade. The production function The model considers an economy with eight sectors producing eight commodities. All sectors are assumed to produce under conditions of constant returns to scale and perfect competition, implying that prices equal the marginal costs of output. Producers maximize their profits by minimizing their unit variable cost under the constraint of a multi-level production function (illustrated in Figure A6.1). At the top level, output is obtained by combining value added and the intermediate aggregates, following a Leontief production technology. Therefore, any policy affecting a particular sector would affect that sector directly, but also indirectly affect them using the output of the sector as intermediate consumption. At the second level, the intermediate aggregates are obtained by combining all products in fixed proportions (Leontief structure), and total value added is obtained by aggregating the primary factors (capital, labor, land and natural resources) and energy using a nested structure. At each nest, firms make price-sensitive decisions regarding the inputs into production. For example, in the first nest, capital and skilled labor are combined into a bundle (KS bundle) based on the rental price of capital relative to the wage for skilled workers. An increase in wages would cause firms to substitute away from skilled labor towards capital. Using a nest allows the model to better capture the production decisions made by firms by tailoring the degree of sensitivity of each decision to relative prices. 16 Interested readers can find the model’s equations in this reference. 17 The theoretical framework relies on neoclassical assumptions of constant returns to scale and perfect competition, where firms maximize profits to determine output supply and factor demands. 100 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? In the next nest, this capital and skilled labor bundle is combined with natural resources (KF bundle). Unlike standard CGE models, ENVISAGE allows for firms to determine the energy intensity of production; the KF bundle is combined with energy (KEF bundle). In agriculture sectors, the KEF bundle is combined with land before it is combined with unskilled labor. For non-agriculture sectors, the KEF bundle is combined with unskilled labor. The structure of the production nests is shown in Figure A6.1 below. Figure A6. 1: Nested structure of production Source: Authors’ estimates. Factor markets Factor markets are assumed to be in perfect competition. The labor market is segmented between two occupation types: skilled workers who are technicians, associate professionals, professionals and managers, and unskilled workers who have occupations such as clerks, sales workers, etc. Each type of labor is perfectly mobile across the different sectors of production within a region; in the absence of wage gaps across sectors, this implies a uniform wage across all sectors within a region. The wage is set according to supply and demand of labor in each segment; flexible wages clear the markets for the two segments. For capital markets, ENVISAGE distinguishes between two vintages of capital: “Old” and “New”. Industries in decline release capital and this is added to the available stock of “new” capital. This “new” capital is fully mobile across sectors. This allows the model to capture some rigidities in the capital market by assuming that declining sectors will first release the most mobile types of capital. Capital in expanding sectors earn the same rate of return, while capital in declining sectors has a lower rate of return. Annex 6: Presentation of the CGE model 101 Household income and consumption The model consists of a single representative household. Households supply skilled and unskilled labor and receive wages in return. The amount of labor supplied is exogenous to the model. Households also receive income and transfers from other agents, including the profits from asset holdings. Households use their earnings for consumption, savings, and transfers. The consumption of a product by a household is determined by a Stone and Geary linear expenditures system (LES) utility function (Stone, 1954)18. This function decomposes consumption of a given product into necessities and discretionary consumption. In this configuration, the allocation of household consumption across products depends on relative price as well as income elasticities (commodity specific in this model). International trade ENVISAGE models bilateral trade flows between each region. On the import side (illustrated in Figure A6.2), this model follows the Armington assumption; there is imperfect substitution among goods originating in different geographical areas19. For example, basmati rice from India and jasmine rice from China are similar but they are not perfect substitutes. Import demand results from a nested CES function that aggregates domestic and imported goods. Domestic consumers first choose between imported goods and domestic goods based on their relative prices. They then determine the regional sourcing for the imported bundle. Export supply (illustrated in Figure A6.3), is symmetrically modeled as a Constant Elasticity of Transformation (CET) function; producers allocate their output to domestic or foreign markets according to relative prices. The underlying assumption is that there is a cost to preparing goods for export markets (e.g., selling cars in a right hand drive country versus a left hand drive country). Figure A6. 2: How import decisions are made Source: Authors’ estimates. Figure A6. 3: How export decisions are made Source: Authors’ estimates. 18 See Van der Mensbrugghe (2005) for the functional form used in the model. 19 See Armington (1969) for details. 102 A Rebalancing China and Resurging India: How will the pendulum swing for Russia? Each bilateral trade node is associated with four prices: the price received by producers (farm-gate prices), border price of exports (Free On Board), border price of imports (Cost Insurance Freight), and tariff-inclusive price of imports. Distinguishing between these four prices is needed because consumers make purchasing decisions based on prices that include tariffs, trade, and transport margins, while producers make production decisions based on prices excluding these items. Unlike single country models, the prices for goods and services traded (imported and exported) with the rest of the world are endogenous. World prices adjust to clear the global market for traded goods and services. Similarly, for non-traded goods, domestic prices adjust to clear the domestic market (domestic supply meets domestic demand). WB report 103 104 A Rebalancing China and Resurging India: How will the pendulum swing for Russia?