Distortions to Agricultural Incentives Project lead by Kym Anderson. Signe Nelgen University of Adelaide

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1 Distortions to Agricultural Incentives Project lead by Kym Anderson Signe Nelgen University of Adelaide Workshop on Meeting Food Security Goals with Good Policy, Medan, Indonesia, June 2013

2 Outline Purpose of the DAI project Output and Indicators Key findings of the studies Lessons for future effort to monitor and evaluate policies that affect agricultural and food markets

3 Premises behind DAI project Agricultural and food markets in DCs majority of world s poor Welfare affected by: own-country policies rest of world s policies Hence need global coverage of price distortions Global poverty and food insecurity could be reduced through policy reforms

4 Some of the key questions To what extent do govts. insulate domestic food markets from int l price fluctuations? What are the effects of interventions at different stages of the value chain on food security Are there differences between: HICs and DCs? Rising or falling int l price? Food-surplus and food-deficit countries? Food staples and non-staple farm products?

5 WB price indexes, Agricultural Price Index Food Price Index Grain Price Index

6 Farmers share in fob prices (Farm-gate price/fob Price) Farmer s share in fob prices in Ethiopia Coffee Oilseeds Pulses Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

7 Outputs of World Bank s DAI project Global database (by country plus regional and global aggregates) Analytical histories of price distortions 4 regional & 1 global volume plus >100 more-detailed Working Papers Analyses of causes and effects: Anderson, K. (ed.), The Political Economy of Agricultural Price Distortions, Cambridge University Press. Anderson, K., J. Cockburn and W. Martin (eds.), Agricultural Price Distortions, Inequality and Poverty, World Bank.

8 Country coverage for Asia 12 Asian countries included in the study of a total of 82 countries Bangladesh China India Indonesia Korea Malaysia Pakistan Philippines Sri Lanka Taiwan Thailand Vietnam

9 More than half a century of data: agricultural commodities updated to 2010/2011, based again on OECD s PSEs plus, for other DCs, domestic & border price indexes average 11 per country and 70% of value of production Estimates of nominal rates of assistance (NRAs), and consumer tax equivalents (CTEs)

10 Country information: Crop area Production and Consumption in tonnes or nb of livestock Price variables Farm-gate selling price Wholesale price Primary At different stage of processed product Mark-ups Cif import price Fob export price International reference price Exchange rates Trade variables (Trade status, Imports, Exports) Stock changes, inputs use of product Other variables: Fertilizer, Pesticides, Credits, Fuel, Electricity, Water, Employment

11 DAI s ag. price distortion indicators Provides estimates of Nominal Rate of Assistance (NRA) to farmer Think of as % by which domestic price of a farm product exceeds that in international market Also provides consumer tax equivalent (CTE) at farm-gate, as with OECD s CSE Not necessarily 70% of cons m value covered though => CTEs (and OECD s CSEs) may be overstated

12 Ag. distortion indicators: the RRA Also estimated a Relative Rate of Assistance (RRA) to producers of agric relative to nonagric tradable goods Think of as % by which domestic price of all farm relative to nonfarm tradable products exceeds that ratio in int l markets Defined as RRA = [(1+NRAag t )/(1+NRAnonag t )] 1, So if NRAag t < NRAnonag t, then RRA < 0

13 Findings of WB s DAI project: to mid-1980s Industrial countries used variable agric. import restrictions and export subsidies Developing countries used variable agric. export and import restrictions (plus overvalued exchange rates and manuf. tariffs)

14 Findings of WB s DAI project: from mid-1980s Reduction in farm supports in many HICs, plus re-instrumentation away from directly price-distorting measures Negative assistance to farmers in DCs has been approaching zero with econ. devt. But, mainly due to reduced export tax n, despite rising import restrictions, and evidence of agri protection growth in MICs

15 NRA (%) Farmer vs. Consumer Protection Nominal Assistance rates, : High-income countries Developing countries y = x y = x y = x y = x Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

16 Is the world nearly free of distortions now? NO, because: Still very wide cross-country dispersion of NRAs and RRAs within both HIC and DC country groups Still very wide cross-product dispersion of NRAs within each country s agric sector including continued anti-trade bias Still a strong tendency for HICs and DCs to insulate domestic markets from int l price flucts.

17 40.0 Global NRA averages by product, Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

18 NRAagric trends for HICs, norway iceland switzerland japan turkey EU27 Weighted Average canada russia us israel australia ukraine Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012). newzealand

19 60 50 NRAagric trends for DCs, Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012). ethiopia korea morocco sudan nigeria ghana colombia senegal mexico zambia vietnam philippines china Weighted Average rsa mozambique india brazil thailand chile cameroon chad benin tanzania uganda kenya dominicanrepublic togo indonesia pakistan bangladesh srilanka mali madagascar egypt malaysia burkinafaso zimbabwe ecuador argentina nicaragua coted'ivoire

20 RRA for HICs and DCs Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

21 Relative Rate of Assistance, % Is agric protection growth a thing of the past? Korea Japan 50 Taiwan India China ASEAN ln GDP per capita Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

22 National RRA averages (%), Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

23 Asian agric protection growth: NRAs

24 RS/MT IN PRICES Consumption side driven protection: Real domestic producer and international reference price for rice, India, DOMESTIC REFERENCE (IMP) REFERENCE (EXP) Domestic price Inclusive of domestic subsidy (Rs/T) Source: Anderson and Martin (2009, Figure 10.4)

25 Price transmission elasticities: Price transmission elasticities, key agricultural products, by region, and Developing countries Asia Developing countries High-income countries Shortrun Longrun Shortrun Longrun Shortrun Longrun Shortrun Longrun Shortrun Longrun Shortrun Longrun Product Rice Wheat Maize Unweighted average Source: Authors estimates based on NRA estimates from Anderson and Nelgen (2012).

26 Reason for govts. to alter their trade measures Majority of poor households are net buyers of food, hence such trade policy actions are nationally justified as poverty alleviating Yet, collectively, those actions exacerbate int l price spike, might that harm more poor in 3rd countries than it helps in the intervening countries?

27 Effects of insulating trade interventions: Think of int l market for a food product that is subjected to an exogenous supply shock (e.g. weather-related) when global stocks are low Shifts excess supply curve to left Then consider: food-exporting country group responses, or food-importing country group responses, and then their combination

28 If X taxes rise AND M tariffs are cut? ES 2 Price ES 1 P 3 P P 2 E 2 E 3 E ES 0 P 1 P x P 0 E 1 M N E 0 ED ED 0 Q 2 Q 1 Q Q 0 Quantity of international trade

29 Effects of insulating trade interventions: Int l price rises can be exacerbated if/when either exporting or importing (X or M) countries insulate However, when an equally large share of world s X & M countries so insulate, their impacts on quantity traded in int l market offset each other It s similar to the futility of many people standing up in a stadium to see better

30 Going forward Ongoing global database of annual NRAs and CTEs (hence also TRIs and WRIs), based on comparing border and domestic prices... to make it a global public good (not just national) Needed if price, trade, welfare, poverty, etc. effects of own-country s and rest-of-world s policies are to be estimated, using PE and CGE models

31 Going forward (cont.) Cover 70% of each country s agric value of prod n and cons m, so 10+ key products plus a guesstimate for non-covered 30% (esp. if distorted differently from 70%) Distinguish exporting & import-competing goods each year, to capture anti-trade bias and help identify border policy instruments used including for non-covered 30%

32 All Agric Distortions Research Project working papers, regional and poverty e-books, and global distortions database are freely available at: Report-builder interface at:

33 Thank you for your attention!