101086 Review, Estimation and Analysis of Agricultural Subsidies in Mongolia Kisan Gunjal and Charles Annor-Frempong March 30, 2014 Foreword The use of indiscriminate agricultural subsidies can lead to high financial and welfare costs, economic inefficiency, skewed resource allocation, trade distortions, and reduced competitiveness. On the other hand, used as judicious strategic policy instruments, smart subsidies can lead to desired socio-economic, food security, and developmental impacts for both targeted groups and for society at large. In Mongolia, direct government budgetary transfers to the agriculture sector have increased significantly over time, primarily through the Crop Protection Fund, Livestock Conservation Fund, and Small and Medium Enterprises Development Fund. However, there is a lack of reliable figures of total producer support estimates (PSE) that take into account the direct transfers to primary agriculture plus indirect support (or taxation) by way of the implicit market price support. This study was undertaken to develop a source of reliable information with which to monitor public expenditures on agricultural subsidies in Mongolia and to inform a strategy for improving the effectiveness of these subsidies. It was carried out by the World Bank in collaboration with partners in the Mongolian Government, primarily the Strategy Planning and Policy Department of the Ministry of Industry and Agriculture, as well as the Ministry of Finance, the National Statistics Office, and a number of other Government agencies. Following the global food prices crisis in 2008/09, and a sustained decline in agricultural production from the mid-1980s to 2007, especially that of wheat, the Government of Mongolia undertook some major food security and agriculture-livestock development policy initiatives. In September 2011, the Bank was invited to a workshop by the Ministry of Food, Agriculture and Light Industries to discuss global agricultural trends, policies, and impacts of high food prices. The Policy and Strategy Department then requested the Bank’s help in analysing the country’s current policy framework, in particular, the agricultural subsidy programs. The work led to this report, which the reader should find useful for reflection, research, and program design. The results of this study show that even though the government budgetary transfers to primary agriculture have increased over the selected five year period (2008 to 2012), total producer support has not. This indicates that the budgetary support, especially during 2011 and 2012, basically went to compensate farmers for the lower domestic market prices vis-à-vis international prices. The main message of the study is that given the variety of subsidy programs in place, it is extremely important that the total support to agriculture sector be accurately estimated and its economic, environmental, and fiscal impacts monitored on a regular basis. Bert Hofman Jurgen Voegele Country Director Senior Director China, Mongolia and Korea Global Practice, Agriculture MONGOLIA Review, Estimation and Analysis of Agricultural Subsidies As part of the MONGOLIA AGRICULTURE SECTOR REVIEW MINISTRY OF INDUSTRY AND AGRICULTURE THE WORLD BANK’S TECHNICAL ASSISTANCE TO MONGOLIA UNDERSTANDING THE CONSTRAINTS TO AGRICULTURE IN MONGOLIA March 2014 This report was prepared as part of the Mongolian agriculture sector review including direct and indirect agricultural subsidies, requested and supported by the Ministry of Industry and Agriculture (MIA). A consultation process was established throughout the preparation and review with the participation of MIA, the Ministry of Ministry of Finance and other relevant key stakeholders. This study was carried out by a World Bank team led by Charles Annor-Frempong (Task Team Leader) and Kisan Gunjal (Primary Author). The team is thankful to Mark L. Lundell (Sector Manager, ESACS) and Iain Shuker (Sector Manager, EASER) for their support and leadership, to Coralie Gevers (Country Manager, Mongolia) for her guidance and support and to Kofi Amponsah, in-charge of the Public Expenditure Review part of the overall sector review. The team is also grateful to Dr. Lkhasuren Choi-sh, General Director, Strategy Planning and Policy (SPP) Department of MIA for his direction and encouragement and for putting together a support team which helped in organizing stakeholder meetings and collecting and collating data at both sector and higher level government institutions. The team included Mrs. Suvdaa, SPP department, B. Tsogbadrakh, Head of Finance and Investment Division and Ms. Janbota, Budget Officer, Senior Officer all of MIA. The team also expresses their sincere gratitude to the following: Bolorchulum (Deputy Director, Livestock Conservation Fund), Batsaihan (Crop Production Support Fund Officer), Renchnsengee Tserernnadmid (Director, Department of Crop Production Policy Implementation), Bold Argazand (Sector Officer, Ministry of Finance), Badamtsetseg Batjargai (Director, Micro Economic Statistics Department, National Statistics Office) among others for collaborating and assisting the team in gathering expenditure and micro statistics data, which provided the basis for the analysis. Our special thanks go to L. Chinbat, General Director, Gatsuurt, Tsenguun Purevjav, CEO, Altan Taria (Milling Co.), and many others who provided useful information and their point of view. This study was coordinated with staff input from FAO. The primary author would like to thank Suzanne Raswant, Chief, in the Investment Centre Division, and David Hallam, Director, Trade and Markets Division, FAO, Rome, Italy. We are especially grateful to the peer-reviewers of the study, namely, Iain G. Shuker, Sergiy Zorya, Hardwick Tchale, and Stephen D. Mink, for providing guidance, critical review, and comments which greatly helped in improving the quality of the report. Gunnar Larson (Agriculture Global Practice) edited the report and pictures provided by Li Lou and Tina Puntsag. Finally, we are grateful to all those who helped in various ways in the completion of this study. i Acknowledgements ........................................................................................................................................ i Abbreviations and Acronyms ....................................................................................................................... v Executive Summary ...................................................................................................................................... 1 1 Introduction ........................................................................................................................................... 4 1.1 Agriculture in Mongolian economy .............................................................................................. 4 1.2 Agricultural policy and subsidies overview .................................................................................. 6 1.3 Objectives of the study.................................................................................................................. 6 2 Approach and Methodology.................................................................................................................. 7 3 Agricultural subsidy programs in Mongolia ......................................................................................... 8 3.1 Agricultural subsidy funds and programs ..................................................................................... 8 3.2 Institutional structure of subsidy programs ................................................................................. 13 3.3 Subsidy programs – direct payments and technical support ....................................................... 14 4 Subsidy calculations and analysis ....................................................................................................... 16 4.1 Payments based on outputs, inputs and other support................................................................. 16 4.2 Market Price Support for wheat and wool .................................................................................. 19 4.3 Subsidies to agro-processing sector ............................................................................................ 21 4.4 Producer Subsidy Equivalent (PSE) Estimates ........................................................................... 21 4.5 Nominal Protection Coefficient (NCP) for Wheat and Wool ..................................................... 22 4.6 International comparisons ........................................................................................................... 24 5 Analysis of potential impact of agricultural subsidy........................................................................... 25 5.1 Impact of subsidies on production/supply................................................................................... 26 5.2 Impact on terms of trade ............................................................................................................. 28 5.3 Fiscal impact ............................................................................................................................... 28 6 Conclusions and Policy Recommendations ........................................................................................ 31 7 References ........................................................................................................................................... 33 8 Appendices.......................................................................................................................................... 35 Appendix 1: PSE calculation categories ................................................................................................. 35 Appendix 2: Import Tariffs on selected commodities............................................................................. 37 Appendix 3: MPS and SCT Tables for Wheat and Wool ....................................................................... 38 Appendix 4: Fiscal Impact Indicators ..................................................................................................... 42 ii Figure 1: Wheat and Potato Production in Mongolia (tonnes), 1985-2012 .................................................. 4 Figure 2: Number of tractors and combine harvesters (left axis), and fertilizer use kg/ha (right axis) ........ 5 Figure 3: Number of livestock, total and different categories (’000 heads), 1985- 2012 ............................. 5 Figure 4: Relative size of funds, 2008-2012 – a) subsidy payments and b) subsidized loans .................... 15 Figure 5: PSE Components: MPS and budget transfers – Crop Production, Million MNT ....................... 18 Figure 6: PSE Components: MPS and budget transfers – Livestock Production, Million MNT................ 18 Figure 7: PSE Components: MPS & budget transfers – Primary Ag. and Agro-processing, Mill. MNT .. 18 Figure 8: Comparison of farm gate price and equivalent border price- wheat and sheep wool .................. 20 Figure 9: Estimated producer subsidy equivalent (PSE, %) to primary ag. sector, 2008-2012 .................. 22 Figure 10: Nominal Protection Coefficients (NPC) for wheat and wool farmers, 2008-2012 ................... 23 Figure 11: Mongolia primary agriculture PSEs in comparison with other countries, % ............................ 24 Figure 12: Performance of subsidized vs non-subsidized crops: Area and yield changes-2007 to 2012 ... 26 Figure 13: Percent change in number of animals, 2012 over 2011 ............................................................. 27 Table 1: Subsidy Funds/Programs for Herders, Farmers and Agro-Processors in Mongolia ..................... 10 Table 2: Funds to support primary agriculture and agro-processing sectors (in Million MNT) ................. 13 Table 3: Annual subsidy payments and subsidized loans1/ to agriculture sectors (Mill. MNT) .................. 15 Table 4: Estimated subsidies for crop and livestock sectors, 2008-2012 (Mill. MNT) .............................. 17 Table 5: Estimated subsidies for agro-processing industry, 2008-2012 (Mill. MNT) ................................ 21 Table 6: Estimated PSE (in Mill. MNT & %) to primary agriculture, 2008-2012 ..................................... 21 Table 7: Estimated nominal protection coefficients (NPC) for wheat and wool farmers, 2008-2012 ........ 23 Table 8: Mongolia agricultural PSEs in comparison with other selected countries (%) ............................. 24 Table 9: Performance of subsidized vs non-subsidized crops: Area and yield changes-2007 to 2012....... 26 Table 10: Terms of trade for wheat and wool during 2008 to 2012 ........................................................... 28 iii Table 11: Subsidies as compared to Government expenditures and revenues ............................................ 29 iv ARD Agriculture and Rural Development ASDS Agriculture Sector Development Strategy BoM Bank of Mongolia CPF Crop Protection Fund DPs Development Partners ESW Economic and Sector Work FAOSTAT Food and Agriculture Organization Statistics GDP Gross Domestic Product GoM Government of Mongolia IFC International Finance Corporation LCF Livestock Conservation Fund MCT Multiple Commodity Transfers MDG Millennium Development Goals MES Ministry of Education and Science MIA Ministry of Industry and Agriculture MNLP Mongolian National Livestock Program MOFALI Ministry of Food, Agriculture and Light Industries MoF Ministry of Finance MoL Ministry of Labor MPS Market Price Support MNT1 Mongolian currency, Tugrik NGO Non-governmental Organization NLS National Livestock Strategy NPC Nominal Protection Coefficient NPFS National Program for Food Security NRP Nominal Rate of Protection NSO National Statistical Office NPFS National Program for Food Security OECD Organization for Economic Cooperation and Development O&M Operations and Maintenance PSE Producer Support Estimate/Producer Subsidy Equivalent PRSP Poverty Reduction Strategy Paper R&D Research and Development SCT Single Commodity Transfers SFPSP Staple Food Price Stabilization Program SME Small and Medium Enterprises WB World Bank WTO World Trade Organization UN United Nations 1 The average exchange rate for 2012 was 1357 MNT for one USD and at the end of October 2013 it was 1678. v With global food crises and food price volatility in recent years, agricultural subsidies have once again gained prominence as a policy instrument in many developing countries. In Mongolia too, subsidies to the agriculture sector mainly through government budgetary transfers, have increased over time. These gained prominence in 2008 when a global, regional (the drought in Russia, and Kazakhstan, the two main suppliers to Mongolia), and the national food production shortfall sent domestic wheat prices soaring to record levels. Wheat production had reached an all-time low during the years 2005 to 2007. Consequently, subsidies to crop, livestock, and agro- processing sectors have increased since 2008, and now represent a complex set of programs, sometimes with conflicting and overlapping goals and intended beneficiaries. A recent MIA assessment found that the working capital amount and the scope and demand for subsidy fund activities are increasing over time. The main types of crop subsidies in Mongolia, implemented under the Crop Protection Fund and aimed at increasing domestic food production, are in the form of wheat price support and subsidized soft loans for the purchase of machinery, fuel, seeds, and plant protection chemicals. Even bigger subsidies are provided to the livestock sector, mainly through the statutory 2 Livestock Conservation Fund, which was established in 2001 mainly to provide support for the protection of livestock herders from droughts and the severe winter weather events known as “dzuds�. Over the years, the Fund has been reformed several times. The latest such reform, the National Mongolian Livestock Program (MNLP), approved in 2010, was introduced to support development of livestock production for the 2010-2015 period by providing support to herders, and preferential loans to livestock breeding cooperatives and intensive livestock production entities. In addition to these two prominent funds, a number of other support programs have been implemented. These include the Small and Medium Enterprises (SME) Development Fund (covering crops, livestock and agro-processing activities among other SMEs), the Pasture Management Program (for irrigation of pastures, rodent/pest control), the Veterinary Program (for services and medicines), and subsidized loan programs for agro-processers (such as wheat flour mills and cashmere, wool, and meat processors). Credit subsidies have been widely used. The most common subsidized credit program involves a partial or full five-year loan at a seven percent annual interest rate, as opposed to the commercial bank loan rate of about 20 percent. Soft loans to agro-processors and commercial farmers are aimed at modernizing the processing facilities to build capacity to generate value added products locally, and to create growth and employment. It is very difficult to find accurate data from the public accounts, except for those which are clearly defined as “subsidies,� and refer to direct payments to herders and farmers. Furthermore, it is important to estimate a total subsidy equivalent by considering the implicit support/taxation by way of the market price support (MPS) to wheat and wool, the two most traded commodities. Therefore, using the standard OECD methodology, the total producer support estimates (PSE)3 2 In Mongolia there is a constitutional commitment to support livestock sector and herders. With a majority of the elected representatives having roots to farming and rural constituencies there is a political support for public budgetary transfers to the sector. 3 Producer support estimates (PSE) is used synonymously with producer subsidy equivalent in this study and includes the Government budgetary support and the implicit market price support (MPS) which can be positive or 1 are calculated. The results show that the total subsidies (the government budgetary transfers) paid out to the primary agriculture sector, in nominal terms4, ranged from 22 billion MNT (USD 15 Million) in 2009 to 91 billion MNT (USD 67 Million) in 2012. Subsidies to the livestock sector average double those to the crop sector. Crop sector subsidies, however, grew almost three times faster during the five year period between 2008 and 2012. The livestock sector generates about four times the level of GDP of the crop production sector. Counting only direct government subsidies, the crop sector is therefore proportionately more subsidized as a percentage of its GDP than the livestock sector. One of the main conclusions of this study is that even though the government subsidies (budgetary transfers) to primary agriculture have increased over the five year period, considering the MPS, the total PSE for the primary agriculture has not increased. This implies that budgetary support basically compensated farmers for the lower domestic market prices, while the international prices (and import prices) remained high. The PSE for the crop sector (predominently wheat), as a percentage of the total value of crop production, remained fairly high at 13 to 17 percent during 2008-2010, but came down drastically in the subsequent years reaching below one percent. In contrast, the PSE coefficients for the primary livestock production sector were much lower and, excluding 2008, have steadily gone up. Thus in aggregate, the PSE for primary agriculture shows a general decline, especially over the three years ending in 2012 when they reached 2.4 percent. For comparison with other countries in the region for which OECD estimates exist, it can be concluded that the overall level of subsidy (including direct and indirect payments) support to primary agriculture in Mongolia was fairly small and much lower than other states such as OECD countries (18.6%), China (16.8%), Kazakhstan (14.6%) and Russia (13.5%) in 2012. Only Ukraine at 1.3% and Turkey at -7.3% were lower than Mongolia. In terms of the potential impact of subsidies, the wheat subsidies seem to have achieved their goal of helping to increase production as the yield per hectare of the subsidized crop. Wheat yields increased more than threefold, and the area sown more than doubled between 2007 and 2012. Similarly, the number of sheep, the main subsidized livestock category, increased faster than any other type of livestock between 2011 and 2012. Because the carrying capacity of the land in a number of aimags has been reached and in some instances exceeded, this increase in number of sheep has generated adverse environmental impacts. The results of the study point to a number of issues with important policy implications, and to recommendations for improving the effectiveness and efficacy of agriculture subsidies in Mongolia. These include the following.  Rationalize agricultural subsidy programs to help resolve inconsistent and overlapping objectives, and to reduce the costs of delivering and implementing the programs. The negative. Although the MPS is calculated only for the selected two commodities (wheat and wool), direct subsidies paid to the primary producers of all other commodities such as meat, dairy, vegetables and others are included in the total subsidy transfers. The OECD category of General Services Support Estimates (GSSEs) for research and development, education and training, inspection and health services, were not included in the PSEs. 4 The subsidy amounts (in fact all values) are in nominal terms. The annual average inflation rates in Mongolia from 2008 to 2012 were: 25.1, 6.3, 10.1, 9.5, 15.0 percent, respectively. However, for ease of understanding and discussion with the Government officials, the nominal values and nominal budgets are used. The estimates are compared to nominal GDP and agricultural output values and public expenditure. Key subsidy values are shown in USD terms. 2 negative values of market price support (MPS) to wheat and wool during the five year period covered by the study suggests that part of the government budgetary transfers were simply used to compensate producers for the implicit taxation. In the absence of domestic market price reduction policies, a negative MPS arises mainly as the result of a lack of competitive market structure and a rise in the international price of the commodity without domestic price transmission. Therefore, a study on the market structure and market performance and roles of various intermediaries and their margins in the marketing channel is recommended to help design policies to improve market efficiency and to reduce the need for direct subsidies.  Investments in general services support (GSS), including research and development, education and training, infrastructure improvement, inspection and health services, are recommended as more effective options than subsidies to increase production. This is particularly important in the case of Mongolia, given that the subsidy outlays are more than double the MIA’s investment budget and nearly nine times higher than expenditures on agricultural R&D. A dollar spent on R&D investment is likely to yield significantly higher returns than a dollar spent on subsidy according to most literature on agricultural economics, suggesting that a reallocation of funds towards research is likely to increase returns and reduce costs for Mongolia’s limited government financial resources. Alternatives to subsidizing fertilizer, for example, investing in road infrastructure, eliminating bureaucratic hurdles and augmenting performance of financial institutions are also recommended (Banful, 2011) and are applicable in Mongolia.  Subsidy programs for the livestock sector in Mongolia generally provide short term financial support to herders, but do not contribute to improved long term food security or economic efficiency. Livestock subsidies may very well be attributable for increasing the number of livestock heads to unsustainable levels, and with serious environmental consequences. Current literature suggests that subsidies do not necessarily bring about any permanent structural or technological change, and therefore may not be at all useful in improving the economic efficiency of production (Jayne and Rashid; Dorward). Although the newly reformed Mongolian National Livestock Program aims to improve the quality of livestock commodities, modernize production systems, and promote adoption of improved technologies, the Program is not fully funded and implementation is incomplete. The recommendation for the Government is to remain mindful of the adverse environmental impacts its support to the livestock sector can have and follow the provisions of the MNLP rather than the ad-hoc payments to the sector.  In 2008, production shocks, low levels of food stocks, high food prices, and critical food security situations persuaded policy makers in a number of countries that smart subsidies were an attractive alternative. Smart subsidies typically involve objectives relating to pro- poor economic growth, the development of local markets, and the promotion of competition in input supply, the pursuit of regional integration and clarity of an exit strategy, and other purposes. These may also include innovative financing, voucher systems, warehouse receipt schemes, etc. intended to reduce input delivery costs and improve targeting to promote private input markets, poor farmers’ adoption of new technologies, increased output, and ultimately poverty reduction. Therefore, it is recommended that a smart subsidy strategy, to the extent possible, be followed with adequate public investment. 3 1.1 Agriculture in the Mongolian economy The agriculture sector contributes significantly to the Mongolian economy and is critical to achieving sustained economic growth and poverty reduction. Agriculture provides an estimated 43 percent of employment with 7 out of 10 jobs in the sector coming from livestock activities. The majority of rural residents dependent on agriculture for income and sustenance, and the sector’s performance has a profound impact on livelihoods throughout Mongolia. According to the 2007/08 household survey, the poverty rate in rural areas was at 43 percent compared to 30 percent in the urban areas. At the national level, a 2012 World Bank estimate of poverty headcount was 27.4 percent, down from 38.7 percent in 2010. Mongolia is a landlocked country with difficult logistics throughout much of its area. Reducing the overall incidence of poverty will necessarily entail doing more to improve the conditions of the country’s rural population. The performance of the agriculture sector has been uneven and is particularly affected by periodic weather related natural disasters. Given the severe water constraints and extremely harsh environment, crop cultivation is highly limited. Nonetheless, with the relatively low opportunity cost of land, wheat is the main cereal produced. Its land productivity, however, is very low in comparison to other countries. Wheat production dropped significantly from about 680,000 tonnes in the mid-1980s to a low of 73,400 tonnes in 2005 (see Figure 1), while the country went from an exportable surplus situation to imports of 350,000 tonnes in 2007/08 with rise in imports from Russia and Kazakhstan. Droughts in 2005 and 2007 lowered wheat production still further. Production has rebounded since, reaching 465,300 tonnes in 2012, but still remains below the national requirement. The drastic decline in agricultural production is attributed partly to the transition from a socialist to a market economy in the 1990s, and is accompanied by the decline in the use of farm machinery (see Figure 2) and other modern inputs such as fertilizer. Figure 1: Wheat and Potato Production in Mongolia (tonnes), 1985-2012 700000 Potatoes 600000 500000 Wheat 400000 300000 200000 100000 0 Source: FAOSTAT database (FAO) and National Statistics Office (NSO) 4 Figure 2: Number of tractors and combine harvesters (left axis), and fertilizer use kg/ha (right axis) 12000 20 Fertilizer consumption (kg/ha of arable land) 18 10000 Tractors 16 14 8000 Combine harvesters 12 6000 10 8 4000 6 4 2000 2 0 0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: FAOSTAT database (FAO) based on official data reported on FAO Questionnaires from countries and World Bank database (World Development Indicators: Agricultural & Rural Development) The livestock sector in Mongolia accounts for about 80 percent of agricultural output and supports about 210,000 rural households. The situation was aggravated by the severe dzuds of 1999, 2000 and 2001, when about 11 million heads of livestock died. More recently, in 2009 and 2010, a dzud killed another 11 million animals, reducing livestock numbers from 44 million to 32.7 million. However, in recent years the number of livestock has been building back up with the latest estimate for 2012 at 41 million, the majority of which are sheep, goats and cattle. Livelihoods and food security among the affected half million rural people is slowly being restored. However, the lingering effects of the livestock losses still weigh heavily on the livelihoods of those affected and will require a sustained effort to overcome. There are also questions about the environmental sustainability of the peak stocking numbers in recent times, and whether this contributes to the high mortality rates during dzuds and therefore to stock number volatility. Figure 3: Number of livestock, total and different categories (’000 heads), 1985- 2012 30000 50000 Horse Cattle 45000 25000 Camel 40000 Sheep Goat 35000 20000 Total number of livestock 30000 15000 25000 20000 10000 15000 10000 5000 Source: FAOSTAT database (FAO) and National Statistics Office (NSO) of Mongolia. 5000 0 0 5 1.2 Agricultural policy and subsidies overview The overall agricultural policy objective, implemented through legislative decrees and laws, is to ensure national food security by providing “the entire nation with stable supplies of accessible, nutritious and safe food to create healthy livelihoods and high labor productivity.� Furthermore, livestock production constitutes the largest agricultural sector and according to the 1992 Constitution, “Livestock is the national wealth of the country and subject to state protection.� Support to agriculture is therefore embedded in national policy. Increasing agricultural competitiveness, improving the quality of food products, and environmental sustainability and natural resources management are all guiding principles of the current agricultural policy. The policy is intended make government support to agriculture more rational. To reverse the declining trend in agricultural production, the Government of Mongolia (GoM) has, in recent years, adopted two key programs and the MDG targets to put agriculture back on track as a lead sector of the economy, to address constraints to agricultural development, and to improve national food security by adopting the Mongolian National Program for Food Security (NPFS) 2009-2016 and the Mongolian National Livestock Program (MNLP) 2010. The NPFS aims to provide the entire country with secure supplies of accessible, nutritious, and safe food to enable healthy livelihoods and high labor productivity founded on the participation of the people, government, as well as the public and private sectors. The overall objective of the MNLP is to modernize the country’s livestock sector so that it is adaptable to the changing climatic and social conditions and create an environment where the sector is economically viable and competitive in the market economy. Despite the important initiatives outlined in these policy documents, a thorough and comprehensive review of the performance of the sector has not been undertaken. For example, the National Livestock Strategy (NLS) was approved by the Parliament in 2010 and sets out an ambitious agenda for modernizing the sector. Public expenditure in the sector has increased significantly and the NLS comes with a “guaranteed� contribution from the state budget. Most of these increased expenditures are believed to have gone to agricultural price and credit subsidies. Many of the recent policy initiatives, including the subsidy programs and the Agricultural Commodities Exchange Law, are insufficiently analyzed to afford us a full understanding of the country’s current policy framework, in particular, the impact of the subsidy programs no being implemented. Agricultural subsidy programs such as price supports for farm inputs and outputs, and direct or indirect payments, are used in many countries, both developing and industrialized. In developing countries the primary aim is to increase local food production and thereby increase domestic food availability and national food security. In Mongolia, both livestock and crop sectors have received rising public support. Yet no proper estimation of the actual amount of direct and indirect subsidies to agriculture, and no proper assessment of their effectiveness, efficiency, or impacts has been carried out. 1.3 Objectives of the study The main objective of this study is to understand the role of subsidies as a form of direct government intervention. The specific objectives are: 1. To review the current agricultural subsidy programs and policies. 6 2. To estimate the amount of subsidies to crop production, livestock production, and agro- processing. The official statistics under “subsidies and transfers� omits many subsidies that go to producers and processors through soft loans and other support programs. Nor do official statistics include the indirect subsidization (or taxation) of the sector arising from government policies and/or market failure. The study therefore seeks to estimate the direct subsidies to the primary agriculture sector and such indirect subsidies as market price support to wheat and wool, two of the most important, most subsidized, and most internationally traded commodities.5 3. To examine the production/supply, terms of trade and fiscal impact of these subsidies and discuss some of the policy recommendations to make them more effective. The methodology used in this study basically followed two steps, first the review of programs involving subsidy elements to agriculture and second, the calculation of total subsidy equivalent estimates. The review. The first step included a review of all the programs and polices related to agricultural subsidies in the country including extensive discussions and structured interviews with all stakeholders during a three week World Bank mission in the country. The key informants included technical and managerial staff of Government units within MIA, MoF, and MoL, and of farm organizations, selected private companies and organizations who are involved in delivering agriculture subsidies or subsidized inputs and outputs. Methodology of producer support estimates. The second step deals with analyzing raw data on subsidy funds and various other transfer outlays and converting them into proper subsidy estimates, direct and indirect, using a simplified OECD PSE methodology.6 The OECD manual states that the producer subsidy (or support) equivalent (PSE) includes all direct or indirect payments for outputs and inputs (A detailed list of support categories is shown in Appendix 1). An important item in the direct payments category in the case of Mongolia, from the methodology point of view, is the conversion of soft loans into actual credit subsidy, i.e. the interest concessions. The majority of the soft loans are of medium term five year loans. Working capital loans are more often shorter term, one year loans, some with a grace period. Most capital loans have different down payment terms but typically have a five-year repayment term, and generally have an interest rate of 7 percent as opposed to a typical commercial bank loan rate of around 20 percent. Accordingly, the concession on interest rates is equal to the difference 5 The MPS analysis of only two commodities is because of the time and resources constraints for this study. 6 In this study a modified/simplified OECD PSE methodology is followed since the market price support (MPS) component is calculated only for two selected commodities, wheat and wool, as opposed to all commodities in the other OECD studies. 7 between the annual commercial bank five year loan interest rate and 7 percent. To simplify the total interest concession calculations these assumptions were made for all loans. In addition to the direct payments for agricultural outputs and inputs, the OECD methodology also includes indirect support (or taxation) of agricultural production in the total producer support/subsidy equivalent (PSE). The indirect support/taxation consists primarily of government policy interventions called “Market Price Support� (MPS). According to the OECD MPS represents “the transfers from consumers and taxpayers to agricultural producers arising from policy measures that create a gap between domestic market prices and border prices of an agricultural commodity, measured at the farm gate level.� Thus the methodology 7 calls for calculating the difference between the farm gate price and the equivalent comparable international reference price (usually the border import price plus allowances for transport, handling, minimal processing and margins). As discussed in the objectives of this study, only wheat and wool were chosen for the MPS analysis. Finally, the PSEs are expressed as a percentage of the total value of the sector. The Producer Nominal Protection Coefficient (NPC). Another way of looking at the total support to a specific commodity is calculating the NPC,8 which is defined as “the ratio between the average price received by producers at the farm gate (including payments per tonne of current output), and the border price, measured at the farm gate. The NPCs are generally calculated based on the level of subsidization at each selected specific commodity level, the Single Commodity Transfer (SCT). The SCT is a ratio of total subsidies specifically designated for the commodity including the MPS and are linked to the SCT so that NPC is equal to 1/(1- percent SCT). In the case of Mongolia, wheat production dominates crop farming, with roughly 50 percent of crop GDP coming from the value of wheat. Since most of the other crop sector subsidies, machinery and other input loans are also accessible to wheat farmers, a 50 percent share of other multiple commodity transfers (MCT) are assumed for wheat. Thus NPC for wheat is calculated in two ways – 1) with the SCT and 2) with sum of the SCT and the share of the MCT. 3.1 Agricultural subsidy funds and programs Mongolian Government agriculture subsidies were high during the Soviet period and then declined sharply during the 1990s. After the 2008 global food price crisis, these subsidies increased again. Government support to Mongolian agriculture consists mainly of core programs that provide output-based payments primarily to wheat, wool, cashmere and meat producers. It also consists of technical support mainly through subsidized soft loans to buy machinery, purchase inputs, and adopt technologies to increase productivity and build capacity. The 7 Details are provided in Chapter 4 of the OECD’s “The PSE Manual�, 2010. 8 Government also supports the livestock sector through the provision of subsidized veterinary medicines and services. Wheat is the main crop in the country and wheat flour is the major food staple, covering approximately 55 percent of the daily caloric intake. Wheat production was controlled and heavily supported during the socialist period up to the 1990s, allowing the country to be self- sufficient and occasionally a net exporter. Following the breakup of the Soviet Union, Mongolian agriculture’s input service system collapsed, and wheat production reached its lowest points between 2005 and 2007. The Government responded by implementing a policy to support domestic production, assure adequate food availability and higher levels of self-sufficiency. The policy included major increases in wheat subsidies, including output-based payments and technical assistance to wheat farmers, for example through grants and loans. Furthermore, a seasonal 5 percent tariff on imported wheat flour from August to April was increased to 15 percent to protect farmers from competition. Meat is a staple food in Mongolia. The livestock industry consists mainly of sheep, goats, horses, cattle, and camels, and engages a large proportion of the workforce. Similar to the other agricultural subsectors, Government intervention in livestock production diminished in 1991 with a broad reduction of subsidies. However, the number of animals increased during the 1990s, mainly due to higher mobility of herds and more people reverting to livestock activities after the breakup of the Soviet Union. Yet, the livestock sector is under higher risk due to frequent disease outbreaks, and unusually harsh dzuds and droughts, which substantially reduced livestock numbers in recent years. Over the years, the Government has implemented several programs, with the objective of supporting primary producers, as well as assisting secondary processes, thereby raising the value added domestically especially for wool, cashmere and meat. The Government has also employed in recent years high taxes on exports of raw and washed cashmere, and wool. This has led to some 50 percent of the raw cashmere being smuggled into China to avoid duty taxes (WTO, 2005). Some of the long standing historical subsidy programs include the Crop Protection Fund, the Livestock Conservation Fund, the Small and The livestock industry consists mainly of sheep, goats, horses, cattle, Medium Enterprise Fund, the Fund for and camels, and engages a large proportion of the workforce. Wool and Cashmere Processors, the Meat Stabilization Fund, Veterinary Services/Vaccines Subsidization Program, Tax Concessions to Herders and Farmers, and the proposed Staple Food Price Stabilization Program. Some salient features, purpose/objectives, operational modalities, administering units, and the size and timeframe of these programs are given in Table 1. The Crop Protection Fund, one of the long-standing subsidy programs, was established in 1997 to intensify implementation of the policy to support crop production activities and crop producers. A further Government Resolution was passed in 1999 to provide “Procedure to 9 establish and disburse Wheat Fund.� Funding of the program has become more systematic and regularized since 2008 and includes subsidies in the form of wheat price support and technical support to the crop sector in the form of subsidized soft loans for machinery and equipment, fuel, seeds, plant protection chemicals, fertilizer, and the cultivation of sea buckthorn berries. As shown in Table 2, the size of the fund (amounts for loans and the direct payments) has fluctuated but grew, in nominal terms, from 24.3 billion MNT in 2008 to 44.2 billion MNT in 2009, came down in 2010 but rose steadily since reaching 44.9 billion in 2012.9 Table 1: Subsidy Funds/Programs for Herders, Farmers and Agro-Processors in Mongolia Name of Subsector/Commodities Responsible/Administrative Nature and Purpose Period and size of fund Fund/Subsidy covered Unit(s) Livestock Output-based payments for Established in 2001; In 2012 Conservation wool and cashmere; - 30 billion MNT. Funds for Fund Technical assistance (grants ad-hoc programs raised and loans): pastureland through issuance of irrigation, feed purchases, Government bonds. etc. Primary (herders) and The goals of the newly intensive agriculture; In Most of the provisions of Unit for Livestock reformed Mongolia National 2013 these payments will MNLP remain unfunded. Conservation Fund Ministry Livestock Program (MNLP, include skin, hide and of Industry and Agriculture. 2010) is to provide State meat milk of all animals support to the livestock except camels. sector to modernize in the areas of institutions, marketing and technology adoption. Crop Protection Output-based payments for Established in 1997; Cash Fund wheat; payments started since 2009. Technical assistance to In 2012 some 30 billion wheat farmers (grants and Primary agriculture MNT of which 11 billion Unit for Crop Protection soft loans); (wheat farmers, sea MNT in form of cash Fund Ministry of Industry Primary goal to increase buckthorn, some payments and Agriculture domestic production and vegetable producers) improve national food security. Fund for wool Subsidized credit to Established in 2011; Total and cashmere promote domestic processing loans in 2011 – MNT 97.8 processors and raise domestic vale billion (USD 66.3 million) Agricultural products and Department of Coordination added production and raise for wool processing processing Industry for Light Industry (MIA) competitiveness of local companies, and MNT 28.7 firms. billion (USD 19.5 million) for cashmere processing Meat Supply Subsidized credit granted to Established in 2005; Not Stabilization support the development of clear if it will continue Program cattle, horse, sheep, pig and Department of Coordination poultry meat, increase the Meat Processing Industry for Food Industry (Ministry slaughtering weight, increase (Meat) of Industry and Agriculture) the share of dam in overall pasture livestock herd and the number of offspring’s Small and Subsidized credit granted to Established in 1992; 2012 – Medium support small and medium Processing Industry, MNT 28.9 billion made SME Fund Unit (Ministry of Enterprises enterprises, increase Primary Agriculture and subsidized by SME with 40% Labor) Development employment and expand Intensive Agriculture for agriculture Fund production Staple Food Subsidized credit granted to Approved in November Price build meat warehouse 2012; Estimated budget for Stabilization capacity, milling capacity Food Processing Industry Department of Coordination 2013: Meat Processors Program and encourage intensive (meat and milling) and for Food Industry (Ministry MNT 87 billion (USD 57.9 livestock production Intensive Agriculture of Industry and Agriculture) million); Intensive Livestock farming MNT 100 billion (USD 66.6 9 Various values are presented in nominal terms. The inflation in Mongolia has been fairly high, for example, 12.5 percent in 2013. However, the Government officials could relate to the nominal values and nominal budgets better. These are compared to nominal values of GDP and agricultural output values and nominal expenditure. Key subsidy values will be shown in USD terms. 10 million) over next 3 years; Wheat flour millers MNT 63 billion (USD 42 million) Subsidies/grants Subsidizes and grants to Established in 2012; to deal with protect livestock producers Irrigation MNT 6.5 billion hazards/risks in from dzuds, involves (USD 4.3 million); Rodent livestock sector increased emergency fodder control 1.8 billion (USD 1.2 (part of reserves, irrigate pasture million); Feed MNT 1.5 Primary agriculture Unit for Livestock Mongolian land, rodent/pest control of billion (USD 1 million). (herders), and intensive Conservation Fund (Ministry National pastures and better Estimated budget for 2013 is agriculture. of Industry and Agriculture). Livestock management and MNT 7 billion (USD 4.66 Program) coordination of activities million), MNT 1.7 billion between the central and (USD 1.13 million) and regional governments. MNT 1.5 billion (USD 1 million). Tax concessions Long standing program. Herders full tax exemption There are no estimates of the Other famers pay 50 percent All herders and farmers Ministry of Finance total tax forgone; the MoF is tax on taxable income working on such estimates. Source: Information derived from the interviews with Ministries, including Ministry of Industry and Agriculture (MIA), National Agricultural Extension Center (NAEC). Provision for the protection of livestock and herders is made in the Mongolian constitution. A number of programs have been introduced for this purpose. The most important of these is the Livestock Conservation Fund, which was established in 2001, mainly to support for the protection of livestock herders from droughts and dzuds. Since then, the Fund has been reformed under various policies, programs, and corresponding Government decrees. The latest one is the “National Mongolian Livestock Program� (MNLP), 10 formulated in 2010 to support the development of livestock production for the years 2010-2015 by providing preferential loan support to livestock breeding cooperatives and intensified livestock production. The available credit under the Livestock Conservation Fund is intended to help farmers acquire machinery, ease working capital constraint and to adopt new technology. Since 2011, the Fund operates independently. The total size of the fund, with an income from the state budget transfers and the repayments of loans, has grown from about half a billion in 2009 to over 32 billion MNT in 2012. This fund included some 30.5 billion MNT worth of subsidy in 2008 to herders for cashmere, 9.8 billion MNT in 2011 and 29.3 billion MNT in 2012 to herders for sheep and camel wool. The remaining amount was disbursed as loans. According to the MIA, the loan repayment rate as of 2012 has been about 90 percent. The MIA assessment also states that the working capital amount, scope and need, and demand for the Fund activities, are increasing overtime. In addition to the Crop Protection Fund and the Livestock Conservation Fund, a number of other programs have been implemented, including the Small and Medium Enterprises Development Fund (covering crops, livestock and agro-processing activities), the Pasture Management Program (for irrigation of pastures, rodent/pest control), the Veterinary Program (for services 10 According to the official document (MIA 2010) the main goals and objectives of MNLP are as follows: 1. To provide great attention from the State to livestock sector as the one of the economic pillars of country, to create a favorable legal, economic and institutional environment, to maintain sustainable development and to develop a good governance to livestock sector. 2. To improve livestock breeding service according to social need, to increase productivity and production of high quality, to produce qualified bio-clean livestock product and to increase competitiveness in the market. 3. To raise veterinary service standard to international levels and to protect public health through securing livestock health. 4. To develop livestock sector that is adaptable in ecological change and able to persist risk. 5. To develop markets specialized for livestock and livestock products, to create processing and selling networks and to accelerate feedback of economy through incentive system. 11 and medicines), and subsidized loan programs for agro-processers such as cashmere processors, wool processors, meat processors, and programs to support wheat flour mills. 12 Table 2: Funds to support primary agriculture and agro-processing sectors (in Million MNT) 2008-12 2008 2009 2010 2011 2012 (Avg) Size of funds supporting primary agriculture and agro- processing sector 71,780 72,261 61,890 300,063 126,886 126,576 I. Primary agriculture 69,153 60,028 49,190 117,498 103,240 79,822 I.1. Crop production programs 24,458 47,810 38,017 68,496 48,979 45,552 A. Crop Production Fund 24,309 42,074 30,764 39,241 44,854 36,248 A1. Wheat subsidies 11,164 8,665 10,906 14,471 27,830 14,607 A2. Fertilizer subsidy 614 230 0 0 0 169 A3. Crop loans 1/ 12,531 33,180 19,858 24,770 17,024 21,472 B. SME Fund Crops (Loans) 149 5,736 7,253 29,255 4,125 9,304 I.2. Livestock Production programs 44,695 12,217 11,173 49,002 54,261 34,270 A. Livestock Conservation Fund 30,560 0 0 17,806 31,510 15,975 A1. Herders -Sheep and camel Wool subsidies 0 0 0 9,827 29,436 7,853 A2. Herders -cashmere subsidies 30,500 0 0 0 0 6,100 A3. Tech support loans 2/ 60 0 0 7,979 2,074 2,023 B. Pasture management (irrigate pastures, pest control) 11,500 5,228 5,815 3,170 5,823 6,307 B1. Grants 10,550 4,848 5,415 3,035 5,423 5,854 B2. Loans 950 380 400 135 400 453 C. Vet. Services - vaccines, services (Subsidy) 2,526 844 2,954 8,754 13,392 5,694 D. SME Fund Livestock ( Loans) 109 6,146 2,404 19,272 3,536 6,293 II. Agro-processing industry 2,628 12,233 12,701 182,565 23,646 46,754 A. Meat Stabilization Fund (Subsidies) 2,400 2,400 1,400 8,000 10,800 5,000 B. SME Fund Food processing (Loans) 228 9,833 11,301 48,065 5,746 15,034 C. Wool Processors (Loans) 0 0 0 28,700 4,700 6,680 D. Cashmere Processors (Loans) 0 0 0 97,800 2,400 20,040 Source: Calculations based on data from NSO, MIA. 1/ Including soft loans for machinery, equipment, fuel, seed, chemicals, fertilizer and production/promotion of sea buckthorn. 2/ Including support to intensified livestock production, animal health and livestock market project, renovation of technology and hay, fodder planting and machinery. 3.2 Institutional structure of subsidy programs At least nine subsidy programs are currently in operation in Mongolia (Table 1). Most of these, including wheat price subsidy and crop and livestock technical support programs, are operated by the MIA. In general the primary agriculture programs are administered by special units within the agriculture side of MIA. For example, as shown in column 4 of Table 1 – Responsible/Administrative Unit – the crop protection fund and the livestock conservation fund are managed by special units by these names. The Livestock Production Department also operates the veterinary program subsidies and a primary implementer of grants and subsidies under the Mongolia National Livestock Program. The Department of Coordination for the Light Industry side of the MIA is responsible for administering and providing technical guidance to wool and cashmere processors’ subsidy programs and to meat supply stabilization loans to meat processors/suppliers. Small and medium enterprise (SME) units under the Ministry of Labor also manage soft/subsidized loans to commercial crop and livestock producers and agro-processors. 13 The funding of most of the ad-hoc subsidy programs comes from extra-budgetary allocations with parliamentary decrees either through special bond offerings or from Ministry of Finance allocations. Funds for soft loans by the SME units are provided through the selected commercial banks that administer the subsidized loans. Most of the soft loan funds are intended to be revolving funds in the sense that the loan recoveries of past loans will provide capital for new loans. However, most of these are in their initial years and do not yet appear to have sufficient rates of recovery. Some verification or control mechanisms exist. For example, when a herder delivers wool to a local delivery point of a wool processing company he/she deposits the transaction paper with the local Soum administration office. This transaction information is then transmitted from the Soum office to the Aimag office, and then to the national office. In parallel the record of purchase travels from a local processor to national processors’ association office and further to the national Government office. When the two records reconcile, the herder receives the due payment. This is meant to eliminate potential fraud in the process. The Ministry of Industry and Agriculture, the Ministry of Labor, and the Ministry of Finance and Commercial Banks are each involved in agriculture subsidy programs in Mongolia. Some of the funds and programs overlap in terms of their goals and the beneficiaries they cover. Examples of this include, SME funds dealing with crop, livestock and agro- processing soft loans, the Staple Food Price Stabilization Program dealing with meat processors, intensive agriculture, wheat millers, etc. There is a need to examine these administrative Meat is a staple food in Mongolia. structures in order to harmonize the various subsidy programs to improve institutional, operational and financial management of all subsidy programs to streamline and make them more efficient. 3.3 Subsidy programs – direct payments and technical support All support programs are combined into three broad groups in Table 2 and summarized as subsidy payments and subsidized loans in Table 3 and Figure 4. The broad categories are crop production support programs, livestock production support programs and agro-processing industry support programs. They include the size of funds distributed as direct payments (price support), grants for specific purposes, loans for short term and long term investments and other subsidy schemes. These amounts are not actual subsidies per se, but rather funds used to provide subsidies. For example, loans themselves are not subsidies; the interest on these loans given up under the program would be actual subsidies. These are calculated and described later in this paper. Over the last five years (2008 to 2012), two forms of support have typically been used by the Government: direct payments in the form of price subsidies/grants, and soft loans with varying terms of concession. The livestock production support funds dominate the total support budget 14 amounting to 127.5 billion MNT (or 56 percent) of subsidy payments and 43.8 billion MNT (or 11 percent) of loans. Support to this sector is also more in the form of subsidies (ranging from 5.7 billion MNT in 2009 to 48.3 billion MNT in 2012) than loans. On the other hand, in relative terms, agro-processors have been supported mostly with soft loans, whereas, crop sector has been supported with direct subsidies and with loans in significant amounts. Table 3: Annual subsidy payments and subsidized loans1/ to agriculture sectors (Mill. MNT) 2008-12 2008 2009 2010 2011 2012 Total (Avg) Crop production programs Subsidies 11,778 8,895 10,906 14,471 27,830 73,880 14,776 Subsidized Loans 12,680 38,916 27,111 54,025 21,149 153,880 30,776 Livestock production programs Subsidies 43,576 5,691 8,369 21,616 48,251 127,503 25,501 Subsidized Loans 1,119 6,526 2,804 27,386 6,010 43,845 8,769 Agro-processing industry Subsidies 2,400 2,400 1,400 8,000 10,800 25,000 5,000 Subsidized Loans 228 9,833 11,301 174,565 12,846 208,772 41,754 Total support to primary agriculture and agro-processing sectors Subsidies 57,754 16,986 20,675 44,088 86,880 226,383 45,277 Subsidized Loans 14,026 55,275 41,215 255,975 40,005 406,497 81,299 Source: Calculations based on data from NSO, MIA. 1/ All figures are in nominal terms. New loan amounts made available to beneficiaries . Although not part of the analysis of this report, new subsidies already started in 2013 include the new fund for Staple Food Price Stabilization aimed at building warehouse capacity of meat processors, all intensive agriculture, and wheat millers. There are also other subsidies planned, such as subsidies for milk producers, vegetable producers, intensive farming of poultry, piggery, beef, etc. Similarly, some of the international donor support to agriculture in general is classified as grants/subsidies (e.g. projects by IFAD, EU, ADB, etc.), however, it is relatively small, not easy to isolate as subsidies and is mostly channeled through the Government. Hence it is not included in the calculations of this study. Figure 4: Relative size of funds, 2008-2012 – a) subsidy payments and b) subsidized loans a) Subsidy payments Crop production Livestock production Agro-processing 11% 33% 56% 15 b) Subsidised loans Crop production Livestock production Agro-processing 38% 51% 11% Source: Calculations based on data from NSO and MIA. The amounts that are available for the purpose of subsidies under the different funds and programs need to be converted into the actual subsidy or equivalent amounts. The total subsidy to a sector, using the OECD definition of the producer support/subsidy equivalent (PSE), is a gross transfer to agriculture from consumers and taxpayers. In addition to budgetary expenditures, support includes other estimated transfers which do not require actual monetary disbursements. Therefore, all direct or indirect payments for outputs and inputs are estimated and analyzed below. 4.1 Payments based on outputs, inputs and other support Direct payments to crop sector include mainly wheat price support to the quantities either sold to the participating millers and/or trading companies or to Government procurement centers. Not all production is subsidized. For example, only about 60 percent of wheat produced, on average during 2008-2012, received a price subsidy. Limitations are applied in terms of quality control, the timing of deliveries (purchased before 1st of December). Wheat sold as feed and to breweries does not receive a subsidy. The subsidy in 2012 was 100,000 MNT per tonne for the actual quantity of wheat subsidized however, given that only 60 percent of the production received this subsidy, the effective wheat subsidy amounts to 60,000 MNT per tonne (about US$44) when the subsidy is distributed over total production. Wheat subsidy payments increased steadily over the five year period from 11.16 billion MNT in 2008 to 27.83 billion MNT in 2012, an increase of about 2.5 times (Table 4 and Figure 5). The other major component of subsidy, the interest concessions to wheat, vegetables and other crops, is comparatively smaller but grew by more than 7 fold during these five years. The bottom part of Table 4 shows conversion of subsidy support with and without MPs in US dollar equivalents using the annual average exchange rates. Given the severe water constraints and extremely harsh environment, crop cultivation is highly limited. 16 According to the official data fertilizer subsidies were offered only during 2008 and 2009. The total crop sector subsidies grew from 13.57 billion MNT in 2008 to 40.67 billion MNT in 2012 or by three fold in the five year period, with an average amount of 22.64 billion MNT per year. As far as livestock is concerned, the ad-hoc payments of large amounts, such as the 30.5 billion MNT in 2008 to cashmere herders and 9.83 billion MNT and 29.44 billion MNT during 2011 and 2012, respectively, to sheep and camel wool herders were delivered (see Figure 6). Veterinary subsidies in the form of the vaccination of animals and veterinary services to farmers and herders based on the actual expenditure for agriculture are included under this category. Given the importance of the livestock sector in Mongolia, the veterinary support expenditures, have increased from 2.53 billion MNT in 2008 to 13.39 billion MNT in 2012, more than fivefold. Interest concessions are the smallest component of livestock subsidies in an absolute amount but have grown the most, especially in 2011 and 2012. Total subsidies to the primary livestock production sector amounted to about 50 billion MNT as opposed to 40 billion for crop production, with an annual average spending of 26.35 billion, some 3.7 billion MNT or 16 percent higher than for crop production. The livestock GDP in general is about four times that of the crop production GDP. Table 4: Estimated subsidies for crop and livestock sectors, 2008-2012 (Mill. MNT) 2008-12 Ratio of Primary Agriculture 2008 2009 2010 2011 2012 (Avg) 2012/2008 (In Million MNT) Crop production sector Wheat subsidies 11,164 8,665 10,906 14,471 27,830 14,607 2.49 Fertilizer subsidy 614 230 0 0 0 169 0.00 Interest consession on crop loans (credit subsidy) 1,788 7,224 7,452 10,014 12,836 7,863 7.18 Market Price Support (MPS) for wheat before subsidy 8,939 12,283 22,387 -8,839 -39,511 -948 -4.42 Total subsidy to crop sector excluding market price support 13,566 16,119 18,359 24,485 40,665 22,639 3.00 Total subsidy to crop sector including market price support 22,505 28,401 40,746 15,646 1,155 21,690 0.05 Livestock production sector Wool subsidies 0 0 0 9,827 29,436 7,853 Cashmere subsidies 30,500 0 0 0 0 6,100 Pasture Management Grants 10,550 4,848 5,415 3,035 5,423 5,854 0.51 Veterinary subsidies 2,526 844 2,954 8,754 13,392 5,694 5.30 Interest consession on livestock loans (credit subsidy) 158 204 178 1,482 2,211 846 14.02 Market Price Support (MPS) for wool before subsidy -2,594 -3,441 -368 2,439 -1,988 -1,191 0.77 Total subsidy to livestock sector excluding market price support 43,734 5,895 8,546 23,098 50,462 26,347 1.15 Total subsidy to livestock sector including market price support 41,139 2,454 8,178 25,537 48,474 25,157 1.18 Total primary agriculture sector Total subsidies to Primary Agriculture excluding MPS for wheat and wool 57,300 22,014 26,905 47,583 91,128 48,986 1.59 Total subsidies to Primary Agriculture including MPS for wheat and wool 63,644 30,856 48,924 41,183 49,628 46,847 0.78 (In Million USD) Average exchange rate MNT/USD 1166 1438 1357 1266 1357 1317 1.16 Total subsidies to Primary Agriculture excluding MPS for wheat and wool (Million USD @annual average exchange 49 15 20 38 67 38 1.37 Total subsidies to Primary Agriculture including MPS for wheat and wool (Million USD @annual average exchange 55 21 36 33 37 36 0.67 Source: Subsidies - Author's calculations. Source for exchange rate: Monthly Bulletin of Statistics of Mongolia 17 Figure 5: PSE Components: MPS and budget transfers – Crop Production, Million MNT 50,000 40,000 Market Price Support (MPS) for wheat 30,000 before subsidy 20,000 Interest consession on crop loans (credit subsidy) 10,000 Fertilizer subsidy 0 -10,000 Wheat subsidies -20,000 Total subsidy to crop -30,000 sector including market price support -40,000 2008 2009 2010 2011 2012 Figure 6: PSE Components: MPS and budget transfers – Livestock Production, Million MNT 50,000 45,000 Market Price Support (MPS) for 40,000 wool before subsidy 35,000 Interest consession on livestock loans (credit subsidy) 30,000 Veterinary subsidies 25,000 Pasture Management Grants 20,000 Cashmere subsidies 15,000 10,000 Wool subsidies 5,000 Total subsidy to livestock sector including market price support 0 -5,000 2008 2009 2010 2011 2012 Figure 7: PSE Components: MPS & budget transfers – Primary Ag. and Agro-processing, Mill. MNT 140,000 120,000 Total subsidies to agro-processing sector 100,000 Market Price Support (MPS) for wool before subsidy 80,000 Total subsidy to livestock 60,000 sector excluding market price support 40,000 Market Price Support (MPS) for wheat before subsidy 20,000 Total subsidy to crop sector 0 excluding market price 2008 2009 2010 2011 2012 support -20,000 Total Subsidies to Primary Agriculture including MPS for -40,000 wheat and wool -60,000 18 4.2 Market Price Support for wheat and wool The indirect support (or taxation) of agricultural production, is estimated by calculating Market Price Support (MPS), which measures the difference between domestic market price and the corresponding international reference price (usually the border import price plus allowances for transport and processing and margin) measured at the farm gate of a specific agricultural commodity. The MPS estimation is necessary Most of the Government policies in Mongolia in recent years have been aimed when there is government policy at raising the price of wheat and wool. intervention, such as import tariffs, other trade restrictions, export subsidies, and so on. These affect the market price. Low levels of tariff in Mongolia mean that there is likely to be fewer distortions in the market price resulting from policy intervention. However, besides the policy interventions, deviations in prices received by farmers compared to the true competitive reference price could also be due to the inherent market structure, conduct, and performance problems. A particularly relevant question in the case of Mongolia is what generates negative MPS for wheat and for wool. Obviously, negative MPS arises when the farm gate price is lower than the equivalent competitive international price of wheat (an imported commodity) and of wool (an exported commodity). In theory, there could be three possible reasons for the negative MPS in Mongolia: 1. the existence of policies to reduce the domestic price (and thereby the farm gate price), 2. imperfect competition in that commodity market, and/or 3. high oscillation (especially increases) in international price, with low transmission to local market and farm gate prices. Most of the Government policies in Mongolia in recent years have been aimed at raising the price of wheat and wool. The likely reasons for negative MPS could therefore be the lack of market competition as well as an inability on the part of the domestic market to adjust quickly to the increases in international market as happened in 2011 and 2012 in case of wheat (Figure 8). Normally, the MPS should be calculated for all agricultural commodities, but owing to certain constraints, it was agreed to cover only the two selected commodities, wheat and wool. The tariff on wheat imports is 15 percent except during the off-season of July to April when it is 5 percent (a complete list of official import tariffs currently in place since 1 July 1999 is shown in Appendix 2). Farmers may benefit from the wheat import tariff, but they lose on the fertilizer tariff, which is also 5 percent. For livestock, the tariff on the import of live animals is 5 percent with other veterinary non-tariff restrictions. There is no tariff for breeding animal imports, while the tariff for eggs and vegetables is 15 percent. The MPS calculated for wheat and sheep wool is presented in Table 4 and the total subsidy amounts shown with and without MPS. The results are interesting as the MPS for these two commodities is positive in some years and negative in others. Wheat farmers, for example received a huge implicit subsidy (MPS) during 2010 (about 22 billion MNT) due to the lowest 19 import price of the commodity (see Figure 5). In 2011 and 2012 however, Mongolian wheat farmers bore an implicit tax as international prices shot up and consequently the equivalent reference prices remained higher than the farm gate prices including the price subsidy received by farmers. The farm gate price (before adding the subsidy) of wheat has been declining over the years and especially in 2012, giving rise to a much larger implicit tax (of about 39.5 billion MNT), wiping out the subsidies provided by the Government almost entirely. So, including MPS, the total subsidy amounts to the crop sector show a peak in 2010 but a decline in the next two years. Figure 8: Comparison of farm gate price and equivalent border price- wheat and sheep wool 500,000 700 450,000 600 400,000 350,000 500 300,000 400 250,000 200,000 300 Farm gate price (wheat, MNT/t) 150,000 Farm gate price (sheep wool, MNT/kg) 200 Reference border price (wheat, MNT/t) 100,000 Reference border price (sheep wool, MNT/kg) 100 50,000 0 0 2008 2009 2010 2011 2012 2008 2009 2010 2011 2012 By contrast, the MPS for wool has been much smaller, indicating less distortion and a small difference in international export price and the price paid to farmers. Even though the farm gate domestic price for sheep wool (before subsidy) has been rising in general, the wool herders also faced an implicit tax during the 2008-2012 period, except in 2011 when the price received by herders exceeded the relatively low international price for wool.11 Thus ignoring the MPS due to possible market distortions in all other livestock primary production sector commodities, the total subsidy to the sector, excluding the one-time subsidy payment to the cashmere herders in 2008, shows an increasing trend, going from about 2.45 billion MNT in 2009 to 48.47 billion MNT in 2012, with an annual average subsidy over 2008-2012 period of about 25 billion MNT, slightly higher than the 22.64 billion MNT to the crop sector. The total subsidy to the primary agriculture including the MPS for only wheat and wool was 64 billion MNT in 2008, dropping to 31 billion in 2009, and gradually reaching a high of about 50 billion MNT in 2012. It should be noted that, these estimates of subsidy with MPS do not cover all commodities. However, MPS to other commodities could be positive or negative. The overall effect of their exclusion is therefore ambiguous on total MPS. Furthermore, not included in the study is the estimate of total tax concessions to herders and farmers. The data required for computation were not available. Exclusion of this underestimates the total support to the agriculture sector. 11 The MPS calculations are made using the adjusted average per unit export value of total wool quantity exported as a proxy for international reference price. Several simplifying assumptions were necessary as the quality differences and international prices are very complex. Also, MPS for all other commodities is not calculated, which could change the conclusions about subsidies to the primary agriculture sector. A full study of PSE estimation is, therefore, required. 20 Similarly, lack of available data on arrears on soft loans also underestimates the total subsidy support. 4.3 Subsidies to agro-processing sector In addition to subsidies for primary agriculture, Government support is provided to agro- processing firms as an incentive to modernize processing technology and increase the capacity to take advantage of economies of scale to increase the competitiveness of domestic firms, and to generate employment in the larger economy. The purpose of soft subsidized loans for wool and cashmere processors is to protect them from foreign competition, mainly from China. The main beneficiaries of the soft loans include meat processing plants, wool and cashmere processors, and various other small and medium enterprises, with the meat stabilization program and cashmere processing firms receiving the lion’s share. Subsidies to the agro-processing industry were fairly low, under 2.5 billion MNT in the beginning, but became particularly significant during 2011 and 2012, reaching a peak at 27.4 billion in 2012, and averaging about 11 billion MNT (Table 5). Given the average annual inflation rate of about 13 percent during the period between The purpose of soft subsidized loans for wool and cashmere processors is 2008 and 2012, this represents a real to protect them from foreign competition. increase. Table 5: Estimated subsidies for agro-processing industry, 2008-2012 (Mill. MNT) 2008-12 2008 2009 2010 2011 2012 (Avg) Meat Reserve stabilization subsidies 2,400 2,400 1,400 8,000 10,800 5,000 Interest concession on loans to wool Processors - - - 2,760 3,596 1,271 Interest concession on loans to cashmere processors - - - 9,405 10,483 3,978 Interest concession on SME Food processing loans 32 60 62 985 2,527 733 Total subsidies to agro-processing sector 2,432 2,460 1,462 21,150 27,406 10,982 Source: Calculations based on data from NSO, MIA. 4.4 Producer Subsidy Equivalent (PSE) Estimates The total PSE figures (producer support/subsidy equivalent, including the MPS for wheat and wool), for primary agriculture are presented in relation to the total value of each sector (see Table 6 and Figures 9). More specifically, PSE% = PSE including the MPS divided by the total value (income) received by farmers (which is equal to the value of production at the farm gate price plus the PSE excluding MPS) (OECD 2010). Table 6: Estimated PSE (in Mill. MNT & %) to primary agriculture, 2008-2012 21 2008 2009 2010 2011 2012 2008-12 (Avg) Crop Production Producer Subsidy Equivalent 22,505 28,401 40,746 15,646 1,155 21,690 Total Production Value 171,526 211,581 244,529 273,321 415,987 263,389 PSE (%) 13.12 13.42 16.66 5.72 0.28 8.24 Livestock Production Producer Subsidy Equivalent 41,139 2,454 8,178 25,537 48,474 25,157 Total Production Value 1,096,197 972,579 964,191 1,103,763 1,668,150 1,160,976 PSE (%) 3.75 0.25 0.85 2.31 2.91 2.17 Total primary agriculture output Producer Subsidy Equivalent 63,644 30,856 48,924 41,183 49,628 46,847 Total Production Value 1,267,722 1,184,160 1,208,720 1,377,084 2,084,138 1,424,365 PSE (%) 5.02 2.61 4.05 2.99 2.38 3.29 Source: Author's calculations Figure 9: Estimated producer subsidy equivalent (PSE, %) to primary ag. sector, 2008-2012 20% Crop Production 15% Livestock Production 10% 5% 0% 2008 2009 2010 2011 2012 Source: Author's calculations The results show that the PSE for the crop production sector, as a percentage of the total value of crop production, remained fairly high at 13 to 17 percent during 2008-2010 but declined dramatically in subsequent years, reaching a low of 0.28 percent in 2012. This was largely the result of rapid global grain price changes without corrreponding changes in domestic farm gate prices. The PSE coefficients for the primary livestock production sector were lower compared to the crop sector but, excluding 2008, they steadily increased from 0.25 percent in 2009 to 2.9 percent in 2012. When the two are combined (the total support to agriculture) the PSE numbers show some fluctuation in the relative measure but a general decline from more than 5 percent in 2008 to less than 2.4 percent in 2012, with a five-year average remaining at 3.3 percent. 4.5 Nominal Protection Coefficient (NCP) for Wheat and Wool In order to see the level of subsidization for each commodity, the Single Commodity Transfer (SCT) and the Producer Nominal Protection Coefficient (NPC) are calculated. The NPC is the ratio between the average price received by producers at the farm gate and the border price, measured at the farm gate. However, in the case of Mong olia, wheat production dominates crop farming, with roughly 50 percent of the crop GDP coming from the value of wheat. Since most of the other crop sector subsidies, machinery and other input loans are also accessible by wheat 22 farmers, a 50 percent share of other multiple commodity transfers (MCT) are assumed for wheat. Thus the NPC for wheat is calculated with and without share of MCT. The full producer NPC for wheat, shown in Table 7 and Figure 10, implies that during 2010 about 35 percent higher payments were received over and above the relevant border price (assumed international competitive price). Thus the level of subsidy equivalent protection to farmers was 35 percent in 2010. Whereas, during 2012, the worst year, wheat producers paid an implicit tax of 3 percent on the wheat they sold. The estimated NPC ratio with the SCT for wheat in Mongolia is estimated to be 0.93 in In Mongolia, wheat production dominates crop farming. 2012, implying the farmers received only 93 cents for each tugrik they should have received based on the international prices. This ratio goes up slightly to 0.97 if we consider additional subsidies potentially acquired by wheat producers through the MCT. During the last five years, wheat producers have gone from receiving a moderate level of positive protection to a moderate level of negative protection. Table 7: Estimated nominal protection coefficients (NPC) for wheat and wool farmers, 2008-2012 2008 2009 2010 2011 2012 NPC for wheat (including only Single Commodity Transfers (SCT)) 1.23 1.14 1.35 1.04 0.93 NPC for wheat (including SCT and share of Multiple Commodity Transfers, MCT)) 1/ 1.24 1.17 1.39 1.07 0.97 NPC for wool (including SCT) 0.70 0.65 0.97 2.56 3.51 Source: Author's calculations 1/ Assuming wheat share of MCT is proportionate to its share of the total value of all crop production (on average approximately 50 percent). Conversely, the NPC ratio of 3.51 for wool producers in 2012 implies that the price received by wool herders (sheep and camel) was more than three times the equivalent border price due to a high level of government payments during this particular year. This is consistent with the overall value of the commodity. For example, in 2012 the total value of wool production at farm gate prices was under 9 billion MNT, while the total subsidy paid to wool herders was over 29 billion MNT. Thus the NPC analysis, consistent with the PSE estimates, shows that wool herders were taxed heavily in 2008 and 2009 but were heavily subsidized during 2011 and 2012. Figure 10: Nominal Protection Coefficients (NPC) for wheat and wool farmers, 2008-2012 23 4.00 3.50 NPC for wheat (including only Single 3.00 Commodity Transfers 2.50 (SCT)) 2.00 1.50 NPC for wheat 1.00 (including SCT and share Multiple 0.50 Comm. Transfers, 0.00 MCT) 2008 2009 2010 2011 2012 Source: Author's calculations 4.6 International comparisons The PSEs for the primary agriculture sector in Mongolia are compared to similar estimates available from different OECD studies (Table 8 and Figure 11). The overall level of subsidy support to primary agriculture in Mongolia has been fairly small (2.4% in 2012), much lower than OECD countries (18.6%), China (16.8%), Kazakhstan (14.6%) and Russia (13.5%) in the same year. Only Ukraine at 1.3% and Turkey at -7.3% were lower than Mongolia. Most countries, including Mongolia, show a generally declining trend. Thus, it can be concluded that the overall level of subsidy (both the direct and indirect levels) support to primary agriculture in Mongolia is fairly small, much lower than other countries in the region and has been declining over the last five years (2008 to 2012). Table 8: Mongolia agricultural PSEs in comparison with other selected countries (%)12 2008 2009 2010 2011 2012 OECD Countries 20.75 21.9 19.23 18.26 18.56 China 2.91 11.51 15.35 12.94 16.81 Kazakhstan 3.88 13.78 9.39 10.80 14.61 Russia 20.52 20.74 21.52 15.08 13.47 Mongolia 5.02 2.61 4.05 2.99 2.38 Ukraine 3.05 7.94 6.67 -4.37 1.32 Turkey -22.14 -26.36 -24.15 -17.33 -7.32 Source: Mongolia - WB Mission calculations; Other countries - OECD calculations (http://stats.oecd.org/Index.aspx?DataSetCode=MON2012PSCT_EE#) Figure 11: Mongolia primary agriculture PSEs in comparison with other countries, % 12 In order to make a fair comparison, MPS for other commodities such as meat, dairy and vegetables, which are traded commodities but in smaller quantities in Mongolia, need to be calculated. These are included in other countries’ PSEs, for example of Russia and Ukraine. 24 Source: Mongolia - Author’s calculations; Other countries - OECD calculations (http://stats.oecd.org/Index.aspx?DataSetCode=MON2012PSCT_EE#) Agricultural producer subsidies can have varied impacts on production, trade, incomes, market prices, and overall economic growth and welfare through possible distortions and stimuli. As indicated by subsidy experts, the sustained long term use of subsidies has a distortionary impact on markets, prices and resource allocation. However, smart subsidies13 may bring about desired results in the early stages of agricultural development by correcting for market failures and promoting the adoption of new technologies (Kaur and Sharma, 2012 and Fan, 2008). Analyses of economic, social, and environmental impacts require a great deal of long-term data, and time 13 Ten features of smart subsidies by Morris et al. 2007 (The World Bank publication) are: 1. Promoting fertilizer as part of a wider strategy, 2. Favoring market based solutions in input supply, 3. Promoting competition in input supply, 4. Paying attention to demand, 5. Insisting on economic efficiency, 6. Empowering farmers, 7. Involving an exit strategy, 8. Pursuing regional integration, 9. Ensuring sustainability, and 10. Promoting pro-poor economic growth. Alternatively, according to the literature review carried out by Meyer (2011) for the World Bank, the guidelines for “smart� or “market-friendly� subsidies include: “subsidize the institution but not the borrowers to reduce distortions; avoid subsidies to institutions that undermine competition; subsidize the creation of public goods that benefit the entire financial sector; subsidize individual financial institutions where there is natural spillover to nonsubsidized institutions; identify quantitative performance measures so subsidies to financial institutions do not dull incentives for high performance; conduct comparative cost-benefit studies to identify subsidies that generate the greatest payoff; require grant recipients to demonstrate commitment through matching contributions; and design grants to financial institutions so recipients clearly understand the dif ference between grants and loans.� 25 and financial resources. The scope of this study is limited to five years. Longer time series and/or full panel household survey data would enable analyses to better capture equity and economic welfare impacts. The analysis here is limited and is carried out to improve impacts of different programs based on the lessons learned from international experience and establish an empirical basis for future assessments of links between farm support and agricultural growth in Mongolia. 5.1 Impact of subsidies on production/supply In the crop production sector only wheat is offered direct price support. There is some secondary support across the board, including to wheat farmers, but in less significant amounts. To see the impact of wheat subsidization, changes in the area planted and yields over the five-year period are calculated. Significant direct cash subsidies were provided to wheat farming from 2008 to 2012. The benefits of these subsidies were however negated by implicit taxation when compared to the border reference prices, especially during 2011 and 2012. Although the area cultivated with other crops is much smaller than the wheat area, the relative changes over time are important. The area planted with wheat grew at more than double and yields increased more than three times the rate of other, non-subsidized crops (Table 9 and Figure 12). While fertilizer use in Mongolia remains low compared to industrialized countries, it doubled from 8.6 kg/ha of arable land to 18 kg/ha between 2007 and 2010. And although other factors may be attributable for these changes, it is highly likely that direct subsidies to wheat played a significant role in increasing wheat productivity. On the negative side, it also means that the subsidies have promoted further mono-cropping of wheat in the country, going against the desirable production and diet diversity objectives as well as the allocation of resources in favor of this one crop. Table 9: Performance of subsidized vs non-subsidized crops: Area and yield changes-2007 to 2012 Area sown Yield/ha Area sown Yield/ha Area sown Yield/ha Crops grown 2007 2007 2012 2012 2012/2007 2012/2007 (000 ha) (t/ha) (000 ha) (t/ha) % change % change Subsidized crop (Wheat) 122 0.9 297 1.565 144% 74% Non-subsidized crops (Non-wheat) 1/ 23 - 38 - 71% 20% Source: Calculations based on data from NSO. Compiled by author. 1/ Calculated from production of potatoes, vegetables and fodder crops weighted by their respective proportion of area sown. Figure 12: Performance of subsidized vs non-subsidized crops: Area and yield changes-2007 to 2012 160% 140% Subsidized crop (Wheat) 120% Non-subsidized crops (Non-wheat) 100% 80% 60% 40% 20% 0% Area sown Yield t/ha Source: Calculations based on data from NSO. 26 In the livestock sector, the total number of animals reached a historical high of 44.0 million heads in 2009, which was brought down to 32.7 million in 2010 by the severe dzud in the 2009/10 winter. The number of animals increased again to 40.9 million in 2012. In 2011 and 2012, livestock subsidies were directly exclusively at wool production, mainly sheep and to a lesser extent to camel wool. Although the data series were not long enough to draw any definite conclusions, the rate of increase in numbers of sheep far exceeds that of any other type of livestock (Figure 13). Again, it is difficult to establish that subsidies were responsible, but they could be one of the factors. If so, this would be an unintended effect of the subsidy policies as the official goal is not to increase livestock numbers because they have already reached or exceeded the ecological carrying capacity of the land. According to the Mongolian National Livestock Program document the average carrying capacity of 100 hectares of pasture land is 60 sheep equivalent animals. The total number of animals was brought down The number of animals have already exceeded by up to 9 to 32.7 million by “dzuds� – severe winter weather events. times this limit in some aimags. Some of the livestock subsidies, such as the direct payments for raw wool and cashmere, may be responsible for increasing the already unsustainable number of livestock heads, and therefore instrumental in raising the overall environmental costs. Subsidies to the livestock sector should take into account environmental consequences, including ecological carrying capacity and the long term sustainability of pasture resources. As shown in literature, the economic efficiency of production may not improve because the subsidies do not bring about any permanent structural or technological changes. And while the newly reformed Mongolian National Livestock Program aims to improve the quality of livestock commodities, modernize production systems, and promote the adoption of improved technologies, the Program is not yet fully funded and implemented. Figure 13: Percent change in number of animals, 2012 over 2011 20.0% 15.8% 15.0% 12.6% 10.5% 10.2% 9.2% 10.3% 10.2% 10.0% 5.0% 0.0% Total Camel Horse Cattle Goat Sheep All except sheep Source: Calculations based on data from NSO. The primary goal of the subsidy to wool herders is to increase their welfare and to encourage them to sell to the local wool processors. Although both goals are achieved with nearly 100 27 percent procurement by local processors, the overall consistency with the national sector development program objectives needs to be addressed. 5.2 Impact on terms of trade The terms of trade of the two major commodities traded internationally (i.e. wheat and wool), which are also subject to subsidization, are calculated and presented in Table 10. Wheat and wool are both exported. Other commodities, for example, raw cashmere, are traded but not supported at the farm level by direct subsidy policies at least during the period covered by the study. As seen from the price ratio of the domestic price received by farmers to the international price (or by the NPC already discussed earlier), wheat protection eroded over the years reaching more or less a parity level in 2011 and 2012. Thus, the direct subsidy to this commodity in last two years has reduced trade distortions. Given that the wheat imports currently are relatively small (under 100,000 tonnes in 2012 coming down from 350,000 in 2007) the direct trade distortion effects of wheat policies may be minimal. However, this may change if global wheat prices decline and the subsidies remain the same. Table 10: Terms of trade for wheat and wool during 2008 to 2012 2008 2009 2010 2011 2012 WHEAT Effective price received by producers (000 MNT/t) 1/ 522 448 385 391 360 International import reference price (000 MNT/t) 420 384 277 367 371 Terms of trade (Price ratio =domestic price received/international price) 1.24 1.17 1.39 1.07 0.97 WOOL Effective price received by producers (000 MNT/t) 2/ 275 268 421 1,077 2,010 International export reference price (000 MNT/t) 394 415 436 420 573 Terms of trade (Price ratio =domestic price received/international price) 0.70 0.65 0.97 2.56 3.51 Source: Calculations based on data from NSO, Ministry of Finance (MOF), Global Trade Information Services (GTI). 1/ Including SCT and MCT subsidies per unit for wheat farmers 2/ Including only SCT subsidy per unit for sheep and camel wool herders Support to wool, a major export commodity, on the other hand, has turned from hugely negative to hugely positive, and thus subsidies have changed the terms of trade. However, this also may have had no trade distorting effect because the processors purchase the wool from herders and export at competitive prices in international market. Thus, in Mongolia, subsidies paid to sheep herders during 2011 and 2012 are likely to act more as a welfare transfer to herders. 5.3 Fiscal impact To perform an analysis of their potential fiscal impact, agricultural subsidies (only primary sectors of crop and livestock production, not including agro-processing sector) are compared to the total income and Government spending in other key productive areas. The analysis includes the relative magnitude in each year during the selected five year period and also the possible discernible trends, if any. Agricultural subsidies as direct payments for output and/or inputs are calculated while those of other sector subsidies, for energy, 28 Government House of Mongolia transportation, and others, are as reported in the official Government expenditure. Thus, ignoring methodological differences, the total estimated primary agricultural subsidies on average form a substantial part of the total government subsidies. Agricultural subsidies on average were about 38 percent of total direct subsidy payments with a steady downward trend from 47 percent in 2008 to 27 percent in 2011 (see Table 11). This, however, is primarily due to relatively higher growth in non-agriculture subsidies including those for energy, transport and other sectors. This trend was reversed to 45 percent in 2012 with a big increase in wheat and wool subsidies. A similar magnitude and trend can be found when the agricultural subsidies are compared to the MIA’s expenditure including the annual outlay of various subsidy funds for crop and livestock. Agricultural subsidies grew at an average annual rate of 15 percent, while total MIA’s agriculture investment expenditures grew by 7 percent and R&D expenditure by 16 percent between 2008 and 2012. Table 11: Subsidies as compared to Government expenditures and revenues 29 2008 2009 2010 2011 2012 2008-12 (Avg) Subsidy as a ratio with expenditure: Ag. Subsidies (crop and livestock)/Total Subsidies (energy, agriculture, 0.47 0.40 0.28 0.27 0.45 0.38 transport, others) 2/ 3/ Ag Subsidies (crop and livestock)/Total Ag Expenditure 4/ 0.58 0.47 0.25 0.20 0.41 0.34 Ag Subsidies (crop and livestock)/Total Ag Investment Budget 2.49 1.27 2.46 2.01 3.14 2.36 Ag Subsidies (crop and livestock)/Agriculture R&D Expenditure 5/ 12.35 4.54 6.42 7.68 11.93 8.90 Subsidy as percentage of income: Crop subsidies/Crop GDP 8.02 7.90 7.74 9.30 10.09 8.87 Livestock subsidies/Livestock GDP 4.04 0.61 0.89 2.12 3.06 2.29 Ag Subsidies (crop and Livestock)/Crop and livestock GDP 4.58 1.88 2.26 3.51 4.44 3.49 Total Subsidies (energy, agriculture, transport, others)/Total GDP 1.87 0.84 1.14 1.58 1.45 1.40 1/ 2008 to 2011 are actual expenditures and 2012 is planned budget. 2/ Estimated subsidies in this study; These do not include the implicit subsidies calculated as the Market Price Support for wheat and wool, i.e. by comparing price received by farmers in relation to the international price. 3/ Including Government estimates of energy, transport, enterprises, and other subsidies; however, ag and agro-processing industry subsidies are as estimated in this in this study. 4/ Ministry of Industry and Agriculture (MIA) expenditure plus livestock fund for wool and cashmere subsidies, and agriculture subsidy part of the SME loans. Wheat subsidies are already included in the normal MIA budget. 5/ This includes R&D budgets reported by MIA, plus the agr research expenditure through the Science and Technology Fund under the Ministry of Education and Science. These subsidy outlays are more than double the investment budget handled by the MIA, which seems to fluctuate from year to year. There is a very little spent on R&D through the MIA as well as through the Science and Technology Fund under the Ministry of Education. As a result, if the data obtained are reliable, agricultural subsidies in Mongolia were on average nearly 9 times higher than the R&D expenditure during the five year period. If one assumes that a dollar spent on R&D investment is likely to have much higher return than a dollar spent on subsidy, then these figures imply a significant scope for reallocating government funds in order to increase the total return on the limited government financial resources. Another commonly considered indicator of fiscal impact is the size of subsidy in relation to the total income of the sector. This is shown in the bottom half of Table 11. The estimated crop subsidies (only direct output and input payments, not considering the MPS) have been fairly stable at around 8 to 10 percent of total crop GDP, with a slight increase in 2012, and averaging around 9 percent. On the contrary, the livestock subsidies were much less, ranging from 1 to 3 percent and generally rising from 2009 to 2012. Thus the combined ratio for the primary agriculture subsidies (crop and livestock) to its corresponding GDP ranged from 2 to 4 percent from 2009 to 2012. The value in 2008 was relatively high due to the one time large payment to Cashmere goat herders. The final The livestock GDP in general is about four times that of the crop production GDP. indicator, subsidies to GDP ratio, shows that the total subsidy 30 payments for agriculture and non-agriculture programs ranged from 0.8 percent of national GDP in 2009 to 1.6 percent in 2011, with an overall average of 1.4 percent from 2008 to 2012. The relative size of subsidies seems small but their ratios (2009-2012) to the GDP, which itself is growing at very high rate, is also increasing. Furthermore, the rising share of subsidies suggests likely squeezing out of other productive investments and R&D and allocations to agriculture sector. The issues discussed in the preceding chapters have a number of important policy implications, and point to a similar number of recommendations for improving the efficiency and effectiveness of agriculture subsidies in Mongolia. 1. Rationalize agricultural subsidy programs. By 2012, there were seven direct payments or grants programs and seven loan programs with varied terms and conditions for herders, farmers, and processors covering crops, livestock, and agro-processing companies. A number of these funds, grants, and soft loan schemes overlap in mandate and in intended beneficiaries, for instance the SME Fund operated by the Ministry of Labor also covers soft loans for primary agriculture that overlap with MIA’s programs targeting the very same beneficiaries. Subsidy schemes are authorized under parliamentary decrees, while funds typically come from the Government as ad-hoc extra-budgetary allocations to the concerned ministries. No clear or transparent method for determining the level of subsidies appears to be in place. Therefore, it is recommended that the streamlining and rationalization of agricultural subsidy programs be carried out to help resolve the inconsistencies and overlapping of objectives and beneficiaries and to improve the overall structure, implementation costs and efficiency. 2. Eliminate negative Market Price Support (MPS) and address problems of market structure. According to the findings of this study, market price support (MPS) was negative for both wheat and wool during some years of the five year period. This implies that part of the government budgetary transfers went only to compensate for implicit taxation. In the absence of domestic market price reduction policies, the negative MPS arises mainly due to the lack of competitive market structure and a rise in the international price of the commodity without domestic price transmission. To understand why the farm gate and the local market prices are lower than the equivalent competitive market prices a study of market structure and performance, and of the roles of various intermediaries and their margins in the marketing channel should be undertaken to inform policy that reduces the need for further subsidies by improving market efficiency. 3. Develop alternative strategies for investing in agriculture other than subsidies. If the main objective of a subsidy is to increase production, it is recommended that more efficient options, particularly investments in the General Services Support (GSS) through research and development, education and training, infrastructure improvements, inspection and health services, among others, be followed. This is particularly important in the case of Mongolia, given that the subsidy outlays are more than double the MIA’s investment budget and nearly nine times higher than expenditures on agricultural R&D. The common conclusion from the 31 literature is that a dollar spent on R&D investment is likely to yield much higher return than a dollar spent on subsidy. If this is true then the reallocation of funds can increase the total returns to the limited government financial resources. The literature suggests that investing in road infrastructure, eliminating bureaucratic hurdles and augmenting the performance of financial institutions is preferable to subsidizing fertilizer, for example (Banful, 2011). Rather than providing blanket subsidies, funds can be provided more selectively to support productivity and profitability enhancing measures. Examples of such highly productive activities mentioned by some of the stakeholders include - facilities for on-farm storage of crops, fencing of fields as animal herds can destroy farmers’ field crops, assistance for minimal grain processing (cleaning, sorting, grading), establishment and improved access to centralize grain marketing system, among others. 4. Subsidies to the livestock sector should take into account environmental consequences, including ecological carrying capacity, and the long term sustainability of pasture resources. Direct subsidies to specific groups of livestock herders are fairly controversial given their potential to promote bigger herd sizes. According to the MIA’s own estimates the current levels of animals have surpassed ecological limits by as much as nine times in some aimags. Subsidy programs for the livestock sector in Mongolia generally provide short term financial support to herders and do not greatly contribute to improved long term food security or improved economic efficiency. They may be even be responsible for increasing the number of head of livestock already at the unsustainable levels and thus raise overall environmental costs. As shown in the literature, the economic efficiency of production may not improve if the subsidies do not bring about any permanent structural or technological change (Jayne and Rashid; Dorward). It is noted, however, that the newly reformed Mongolian National Livestock Program aims to improve the quality of livestock commodities, modernize production systems and help adopt improved technologies but it is not yet fully funded or implemented for lack of financial resources. Therefore, it is recommended that the support to the livestock sector remain mindful of the environmental implications and follow the provisions of MNLP rather than the ad-hoc payments to the sector. 5. Adopting a smart subsidies strategy. The so-called smart subsidies described in the literature can play an important role in a successful agricultural and broader socio-economic development, especially when effectively applied to overcome market failures constraining productive use of modern inputs and technology. Smart subsidies typically involve an objective of pro-poor economic growth, the development of local markets, and the promotion of competition in input supply, the pursuit of regional integration and clarity of an exit strategy, among other desirable goals. The market smart subsidies also include innovative financing, voucher systems, warehouse receipt schemes, etc. intended to reduce input delivery costs and improve targeting to promote private input markets, the adoption of new technologies by poor farmers, increased output, and ultimately poverty reduction. Therefore, it is recommended that smart subsidy options, to the extent possible, be considered as a policy intervention when designing safety net programs that are economically productive and socially equitable. 6. Subsidies to the agro-processing industry. In addition to the primary agriculture sector, subsidies are also provided to a variety of agro-processors, including wool and cashmere processors, flour mills, and meat processors. The primary objective of this support has been to help the overall competitiveness of the local processing companies vis-à-vis foreign ones, by helping them to modernize and acquire economies of scale Subsidies to this sector are 32 also justified under the objective of growth and employment creation. For example, subsidies to wool and cashmere processors have forced them to organize themselves into associations, which may have implications for the export of raw wool and cashmere material. On the other hand, the national association of processors decides the overall maximum price level and where local companies operate exclusively in designated areas, thus reducing competition. Herders may have reduced bargaining power in the process. Similarly, there may be unintended consequences of wheat price subsidies, such as mills having the added bargaining power over farmers in accepting their deliveries of wheat especially when the deadline of the price subsidy period approaches. 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Byerlee (2007): Fertilizer Use in African Agriculture: Lessons Learned and Good Practice Guidelines. T h e World Bank. Meyer, Richard L. (June 2011): Subsidies as an instrument in agriculture finance: A Review. The World Bank. OECD (2010). OECD’s Producer Support Estimate and Related Indicators of Agricultural Support: Concepts, Calculations, Interpretation and Use, OECD, Paris. Portugal, L. (2002): Methodology for the Measurement of Support and Use in Policy Evaluation. OECD, Paris. Rashid, Shahidur, Dorosh, Paul A., Malek, Mehrab, and Lemma, Solomon (2013): Modern input promotion in sub-Saharan Africa: insights from Asian green revolution, Agricultural Economics 44 (2013) 705–721. 34 Roningen, V. (1999). The Impact of a Ban on Mongolian Raw Cashmere Exports. Gobi Regional Economic Growth Initiative. Schwartz, G., & Clements, B. (1999). Government Subsidies. Journal of Economic Surveys , Volume 13 (Issue 2), Pages: 119–148. The World Bank Group (Feb. 2010). Kazakhstan - Public Expenditure and Institutional Review for the Agricultural Sector. World Trade Organization (2005). Trade Policy Review, Mongolia. WT/TPR/S/145, 44-72. Appendix 1: PSE calculation categories Table A1. PSE Calculations - Market support and budget transfers in PSE according to OECD methodology) Categories Sources of data/infor mation A. Support based on commodity output A.1. Market Price Support A.2. Payments based on output B. Payments based on input use B.1. Variable input use B.2. Fixed capital formation B.3. On-farm services C. Payments based on current A (Area)/An (Animal number)/R (Receipts)/I (Income), production required C.1 Based on current receipts/income C.2 Based on current area/animal number D. Payments based on non-current (historical or fixed) A (Area)/An (Animal number)/R (Receipts)/I (Income), production required E. Payments based on non-current A (Area)/An (Animal number)/ R (Receipts)/I (Income), production not required E.1. Variable rates (vary with respect to levels of current output or input prices, or production/yields and/or area) E.2. Fixed rates F. Payments based on non-commodity criteria F.1. Long-term resource retirement 35 F.2. Specific non-commodity output F.3 Other non-commodity criteria G. Miscellaneous payments Labels -- With/without L (current commodity production limits and/or limits to payments) -- With V/F rates (variable or fixed payment rates) -- With/without C (input constraints). -- With/without E (commodity exceptions). -- Based on A/An/R/I (Area/Animal number/Receipts/ Income). -- Based on SC/GC/AC (a single commodity, a group of commodities or all commodities ). Source: OECD 2010 36 Appendix 2: Import Tariffs on selected commodities Table A2. Official import tariffs currently in place since 1 July 1999 Custom duty Commodity/description rate % Wheat imported in Bayan Ulgii, Tsagaan nuur, Khovd Yarant, Uvs aimag Borshoo, Zavkhan aimag Artssuuri, Gobi-altai aimag Burgastai ports 15 Wheat imported between 1 April and 1 July 15 Wheat imported between 1 July and 1 April 5 Wheat flour imported between 1 August and 1 April 15 Grain, flour, starch, dairy mixture, flour produce 5 Vegetables namely onions, cabbage, carrots and turnip cabbage 15 Other vegetables, fruit, nut or mixture of plant parts 5 Cotton wool 5 Chicken eggs 15 Livestock, animal 5 Meat sub products 5 Dairy products, honey, meat 5 Wool, animal fine and crude hair, fleece, horse fine yarn, woven fabric 5 *Source: Annex to Resolution No. 27; Parliament of Mongolia dated 03 June 1999, Ulaanbaatar city 37 Appendix 3: MPS and SCT Tables for Wheat and Wool Table A.3.1: Wheat Market Price Support and Consumer Support Estimate Units 2008 2009 2010 2011 2012 I. Level of production data 000t 210 388 345 436 465 II. Farmgate price data MNT/t 462,797 415,695 342,292 346,807 286,272 III. Value of production (at farm gate) data or [(I) * (II)/1000] MNT Mill 97,109 161,340 118,247 151,169 133,200 IV. Level of consumption data 000t 558 643 498 533 536 V. Consumption price (at farm gate) (II)-((IX.1)+(X.1))/(I)*1000+((IX.1)+(IX.2))/(IV)*1000 MNT/t 462,797 415,695 342,292 346,807 286,272 VI. Value of consumption (at farm gate) (IV) * (V) / 1000 MNT Mill 258,188 267,459 170,589 184,963 153,449 VII. Reference price (at farm gate) (VII.1)*(VII.3)*(VII.4)+(VII.2) MNT/t 420,197 384,048 277,488 367,086 371,187 1. Border reference price (average import price) data USD/t 331 240 181 265 249 2. transportation costs data USD/t 25 25 25 25 25 3. Quality adjustment data ratio 1 1 1 1 1 4. Official exchange rate data MNT/USD 1,182 1,451 1,346 1,268 1,355 VIII. Market price differential (II) - (VII) MNT/t 42,600 31,647 64,804 -20,279 -84,916 IX. Market transfers (IX.1) + (IX.2) - (IX.3) MNT Mill 8,939 12,283 22,387 -8,839 -39,511 1. Transfers to producers from consumers =IF((IV)>(I),(VIII)*(I)/1000,(VIII)*(IV)/1000) MNT Bill 8,939 12,283 22,387 -8,839 -39,511 2. Other transfers from consumers =IF((IV)<(I),0,((IV)-(I))*(VIII.)/1000) MNT Mill 0 0 0 0 0 3. Excess feed cost =IF((1)<(I),(1)*(VIII.)/1000,(I)*(VIII.)/1000) MNT Mill 0 0 0 0 0 X. Budgetary transfers (X.1) + (X.2) + (X.3) MNT Mill 0 0 0 0 0 1. Transfers to producers from taxpayers =IF((IV)>(I),0,((I)-(IV)) *(VIII.)/1000) MNT Mill 0 0 0 0 0 2. Transfers to consumers from taxpayers data MNT Mill 0 0 0 0 0 3. Price levies (-) data MNT Mill 0 0 0 0 0 XI. Market Price Support (MPS) (IX.1) + (X.1) + (X.3) MNT Mill 8,939 12,283 22,387 -8,839 -39,511 XII. Producer NPC 1/[100-(IX.1+X.1+XII.1)/(III.+XII.1)*100]*100 ratio 1.23 1.14 1.35 1.04 0.93 1. Payments on output total data MNT Mill 11,164 8,665 10,906 14,471 27,830 2. Payments on output per tonne (XII.1)/(I)*1000 MNT/t 53,205 22,324 31,571 33,199 59,811 XIII. Consumer Single Commodity Transfers (CSCT) (X.2) - ((IX.1) + (IX.2) + (IX.3)) MNT Mill -8,939 -12,283 -22,387 8,839 39,511 XIV. Consumer NPC 1/[100-(IX.1+IX.2)/VI.*100]* 100 ratio 1.04 1.05 1.15 0.95 0.80 Source: Author's calculations based on official NSO data (farm gate prices, production, trade volumes and values ), Ministry of Finance, supplemented by stakeholder interviews (e.g. transport costs, quality adjustment); 38 Table A.3.2: Sheep Wool Market Price Support and Consumer Support Estimate Units 2008 2009 2010 2011 2012 I. Level of production data t 21,818 23,444 24,534 18,685 19,100 II. Producer price (at farm gate) data MNT/kg 275 268 421 551 469 III. Value of production (at farm gate) data or [(I) * (II)/1000] MNT Mill 6,011 6,283 10,329 10,295 8,958 IV. Level of consumption data t 12,510 17,704 16,585 10,257 14,606 V. Consumption price (at farm gate) (II)-((IX.1)+(X.1))/(I)*1000+((IX.1)+(IX.2))/(IV)*1000 MNT/kg 275 268 421 551 469 VI. Value of consumption (at farm gate) (IV) * (V) / 1000 MNT Mill 3,446 4,745 6,982 5,652 6,850 VII. Reference price (at farm gate) (VII.1)*(VII.3)*(VII.4)+(VII.2) MNT/kg 394 415 436 420 573 1. Border reference price (f.o.b. or c.i.f.) data USD/t 1,004 853 958 987 1,205 2. Transportation, handling and processing costs data MNT/kg 80 80 80 80 80 3. Quality adjustment Only 40% is usable, rest is waste. ratio 0.40 0.40 0.40 0.40 0.40 4. Official exchange rate data MNT/USD 1,182 1,451 1,346 1,268 1,355 VIII. Market price differential (II) - (VII) MNT/kg -119 -147 -15 131 -104 IX. Market transfers (IX.1) + (IX.2) - (IX.3) MNT Mill -1,488 -2,598 -249 1. Transfers to producers from consumers =IF((IV)>(I),(VIII)*(I)/1000,(VIII)*(IV)/1000) MNT Mill -1,488 -2,598 -249 1,339 -1,521 2. Other transfers from consumers =IF((IV)<(I),0,((IV)-(I))*(VIII.)/1000) MNT Mill 0 0 0 0 0 3. Excess feed cost =IF((1)<(I),(1)*(VIII.)/1000,(I)*(VIII.)/1000) MNT Mill 0 0 0 0 0 X. Budgetary transfers (X.1) + (X.2) + (X.3) MNT Mill -1,107 -842 -119 1,100 -468 1. Transfers to producers from taxpayers =IF((IV)>(I),0,((I)-(IV)) *(VIII.)/1000) MNT Mill -1,107 -842 -119 1,100 -468 2. Transfers to consumers from taxpayers data MNT Mill 0 0 3. Price levies (-) data MNT Mill 0 0 XI. Market Price Support (MPS) (IX.1) + (X.1) + (X.3) MNT Mill -2,594 -3,441 -368 2,439 -1,988 XII. Producer NPC 1/[100-(IX.1+X.1+XII.1)/(III.+XII.1)*100]*100 ratio 0.70 0.65 0.97 2.56 3.51 1. Payments on output total data MNT Mill 0 0 0 9,827 29,436 2. Payments on output per tonne (XII.1)/(I)*1000 MNT/kg 0 0 0 526 1,541 XIII. Consumer Single Commodity Transfers (CSCT) (X.2) - ((IX.1) + (IX.2) + (IX.3)) MNT Mill 1,488 2,598 249 -1,339 1,521 XIV. Consumer NPC 1/[100-(IX.1+IX.2)/VI.*100]* 100 ratio 0.70 0.65 0.97 1.31 0.82 Source: Author's calculations based on official NSO data (farm gate prices, production, trade volumes and values), supplemented by stakeholder interviews (e.g. transport costs, quality adjustment); 39 Table A.3.3: Wheat Single Commodity Transfers units 2008 2009 2010 2011 2012 1 000t 210 388 345 436 465 I. Level of production Mill 97,109 161,340 118,247 151,169 133,200 II. Value of production (at farm gate)1 MNT Mill 20103 20947 33294 5632 -11681 III. Producer Single Commodity Transfers2 MNT Mill 20103 20947 33294 5632 -11681 A. Support based on commodity outputs MNT Mill 8,939 12,283 22,387 -8,839 -39,511 A1. Market Price Support3, 5 MNT Mill 11,164 8,665 10,906 14,471 27,830 A2. Payments based on output3, 6 MNT Mill 0 0 0 0 0 B. Payments based on input use MNT Mill 0 0 0 0 0 B1. Variable input use3, 6 MNT Mill 0 0 0 0 0 B2. Fixed capital formation3, 6 MNT Mill 0 0 0 0 0 B3. On-farm services3, 6 MNT C. Payments based on current A/An/R/I, Mill 0 0 0 0 0 production required, single commodity3, 6 MNT D. Payments based on non-current A/An/R/I, Mill 0 0 0 0 0 production required3, 6 MNT IV. % SCT*4, 7 % 18.57 12.32 25.78 3.40 -7.25 Source: Author's calculations Formulas involved in the calculation for each row above are given in the footnotes below: 1 MPS table 2 PSCTWT = AWT + BWT + CWT + DWT 3 TOTAL table 4 %SCTWT = 100* SCTWT / ( (PPWT*QPWT) + A.2WT + BWT + CWT + DWT) *This is underestimation as it includes only "wheat specific programs". Most other crop production programs, although not specified as wheat programs, do provide benefits to wheat producers. 5 Wheat specific MPS 6 Wheat specific programs 7 Wheat specific transfers / value of receipts from wheat production 40 Table A.3.4: Sheep Wool Single Commodity Transfers units 2008 2009 2010 2011 2012 I. Level of production1 t 21,818 23,444 24,534 18,685 19,100 Mill 6,011 6,283 10,329 10,295 8,958 II. Value of production (at farm gate)1 MNT Mill -3031 -3910 -859 11892 27066 III. Producer Single Commodity Transfers2 MNT Mill -3031 -3910 -859 11892 27066 A. Support based on commodity outputs MNT Mill -3031 -3910 -859 2065 -2370 A1. Market Price Support3, 5 MNT Mill 0 0 0 9,827 29,436 A2. Payments based on output3, 6 MNT Mill 0 0 0 0 0 B. Payments based on input use MNT Mill 0 0 0 0 0 B1. Variable input use3, 6 MNT Mill 0 0 0 0 0 B2. Fixed capital formation3, 6 MNT Mill 0 0 0 0 0 B3. On-farm services3, 6 MNT C. Payments based on current A/An/R/I, production Mill 0 0 0 0 0 required, single commodity3, 6 MNT D. Payments based on non-current A/An/R/I, production Mill 0 0 0 0 0 required3, 6 MNT IV. % SCT4, 7 % -50.42 -62.23 -8.31 59.10 70.49 Source: Author's calculations Formulas involved in the calculation for each row above are given in the footnotes below: 1 MPS table 2 PSCTWL = AWL + BWL + CWL + DWL 3 TOTAL table 4 %SCTWL = 100* SCTWL / ( (PPWL*QPWL) + A.2WL + BWL + CWL + DWL) 5 Wool specific MPS 6 Wool specific programs 7 Wool specific transfers / value of receipts from wheat production 41 Appendix 4: Fiscal Impact Indicators Table A.4.1 Subsidies compared to Government expenditure and revenues (Million MNT) 2008-12 2008 2009 2010 2011 2012 (Avg) Total Ag Expenditures (MIA) 2/ 98,803 46,648 106,175 238,968 223,033 142,725 % Change year-on-year - -53 128 125 -7 31 Total Ag Investment Budget (MIA) 23,000 17,300 10,917 23,670 29,031 20,784 % Change year-on-year - -25 -37 117 23 7 Agriculture R&D Expenditure 3/ 4,639 4,851 4,189 6,192 7,636 5,502 % Change year-on-year - 5 -14 48 23 16 Subsidies: Total Ag Subsidies (crop and livestock) 4/ 57,300 22,014 26,905 47,583 91,128 48,986 % Change year-on-year - -62 22 77 92 15 Crop Sector 13,566 16,119 18,359 24,485 40,665 22,639 % Change year-on-year - 19 14 33 66 50 Wheat Price subsidy 11,164 8,665 10,906 14,471 27,830 14,607 % Change year-on-year - -22 26 33 92 37 Livestock Sector 43,734 5,895 8,546 23,098 50,462 26,347 % Change year-on-year - -87 45 170 118 4 Agro-processing industry subsidies 4/ 2,432 2,460 1,462 21,150 27,406 10,982 % Change year-on-year - 1 -41 1347 30 257 Total Government subsidies 5/ 122,865 55,441 96,226 175,449 202,842 130,564 % Change year-on-year - -55 74 82 16 16 Ag subsidies (crop and livestock) as percent of 47 40 28 27 45 38 total subsidies Ag and agro-processing industry subsidies as 49 44 29 39 58 46 percent of total subsidies Source: Calculation based on data from MIA, compiled by author. 1/ 2008 to 2011 are actual expenditures and 2012 is planned budget. 2/ Ministry of Industry and Agriculture (MIA) expenditure plus livestock fund for wool and cashmere subsidies, and agriculture subsidy part of the SME loans. Wheat subsidies are already included in the normal MIA budget. 3/ This includes R&D budgets reported by MIA, plus the agri research expenditure through the Science and Technology Fund under the Ministry of Education and Science. 4/ Estimated subsidies in this study; These do not include the implicit subsidies calculated as the Market Price Support for wheat and wool, i.e. by comparing price received by farmers in relation to the international price. 5/ Including Government estimates of energy, transport, enterprises, and other subsidies; however, ag and agro- processing industry subsidies are as estimated in this in this study. 42