South Asia Economic Focus - Documents & Reportsdocuments.worldbank.org/curated/en/959611468307160635/pdf/708830ESW0… · South Asia economic Focus, a biannual series prepared under

South Asia Economic FocusA Review of Economic Developments in South Asian Countries

Food InflationJune 2011

THE WORLD BANKWashington, D.C.

South Asia Region

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70883

South Asia Economic FocusA Review of Economic Developments in South Asian Countries

Food InflationJune 2011

South Asia Region

THE WORLD BANKWashington, D.C.

iiiSouth Asia Economic Focus – A Review of Economic Developments in South Asian Countries

Table of Contents

A Note on Fiscal Years and Financial Reporting by South Asian Countries . . . . . . . . . . . . . . . . . . . . . . . . . vi

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

CHAPTER 1: Why Food Prices Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

CHAPTER 2: Determinants of Food Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31 . The Trajectory of Inflation in Recent Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32 . Short-term Pressures: Global Food Prices, Aggregate Demand, and Domestic Supply Shocks . . . . . . .73 . Long-term Effects: Productivity Slow-down and Structural Demand Shifts . . . . . . . . . . . . . . . . . . . . .10

CHAPTER 3: The Impact of Agricultural Policies on Food Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . .191 . Historical Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .192 . Government Involvement in Agricultural Marketing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223 . Policies for Agricultural Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

CHAPTER 4: The Human Impact of Food Price Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .291 . Impact on Poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .292 . Mitigating the Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .313 . Bank Support to Safety Net Programs in South Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

CHAPTER 5: Policy Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

Country Pages: Eight countries – Eight Graphic Economic Narratives . . . . . . . . . . . . . . . . . . . . . . . .41

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51

South Asia Economic Focus – A Review of Economic Developments in South Asian Countriesiv

ANNEx 1: Developments in Global Commodity Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

ANNEx 2: Speculation, Financialization of Commodities, and the “New” Money . . . . . . . . . . . . . . . .63

ANNEx 3: South Asian Food Demand and Supply Balances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71

ANNEx 4: Impact on Poverty of the Increase in Food Prices – Methodology and More Results . . . .73

ANNEx 5: Selected Food Crisis Response Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77

ANNEx 6: Commodity Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81

Boxes2.1 Inflation In China – What is Different? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143.1 The Opium Economy in the Context of Afghanistan’s Agriculture and Food Security . . . . . . . . . .203.2 Agricultural Produce Markets Act (APMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .243.3 From the Arabian Nights – A Cautionary Tale from History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .263.4 Gujarat’s Agricultural Success . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .274.1 Recommendations for Safety-Net Policy Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32

Figures1.1 South Asia: Food Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12.1 WPI Inflation in Major Emerging Market Economies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32.2 South Asia: Consumer Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42.3 India: Food Articles’ Contribution to WPI Food Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42.4 South Asia: Contribution to CPI Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52.5 Global Food Price Index and Its Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72.6 Agriculture and Energy Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72.7 International Commodity Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82.8 The Price Spikes of 2007/08 and 2010/11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82.9 Imports of Rice, Wheat and Edible Oils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .92.10 Domestic and International Prices of Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .92.11 Domestic and International Prices of Wheat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102.12 Subsidization of Diesel Retail Fuel Prices Remains Particularly High in Bangladesh and

Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102.13 India: Household Inflation Expectations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .112.14 General Government Balances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .112.15 Total Government Debt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .112.16 India: Monetary Conditions Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .122.17 Industrial Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .122.18 Production Growth of Major Staple Food Items . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152.19 India: Growth Rates in Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152.20 India: Terms of Trade between Agriculture, Industry, and Services . . . . . . . . . . . . . . . . . . . . . . . .162.21 Annual Per Capita Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162.22 India: Household Survey Data on Consumption of Food and Non-Food . . . . . . . . . . . . . . . . . . . . .172.23 India: Shares of Food Types in Food Baskets, 1987/88–2007/08 . . . . . . . . . . . . . . . . . . . . . . . . . .173.1 Average Food Supply: Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .213.2 India: Food and Fertilizer Subsidies, 1990–2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223.3 India: Rice and Wheat Yields in Major Producing States, 2006–2009 . . . . . . . . . . . . . . . . . . . . . .233.4 India: Groundwater Use Over Net Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .254.1 Poverty Impacts of Recent Price Rises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30

Table of Contents v

A1.1 Rising World Consumption, Variable Supply, and Stock Draw-Downs have Fueled Consecutive Grain Price Spikes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

A1.2 Commodity Price Index (Nominal prices) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57A1.3 Commodity Price Index (Real prices) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58A1.4 Food Price Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58A1.5 Food Price Volatility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59A1.6 Grain Consumption and Stocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59A1.7 Fertilizer vs Crude Oil Price Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61A1.8 Food vs Fertilizer Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61A1.9 Copper and Aluminium Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62A4.1 Decomposition of Net Poverty Headcount Change by Commodity . . . . . . . . . . . . . . . . . . . . . . . .74A4.2 Decomposition of Net Poverty Gap Change by Commodity . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74

Tables4.1 Changes in Poverty Headcount . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .314.2 Safety Net Readiness Assessment in South Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .314.3 India: Household Consumption vs . Grain Delivieries to the PDS, 2007 . . . . . . . . . . . . . . . . . . . . .34A1.1 World Wheat and Rice Balances (million tons) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55A2.1 Types of “Speculative Activity” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64A2.2 Summary of Empirical Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67A3.1 Bangladesh: Production and Imports of Food Grain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71A3.2 India: Agricultural Production, 2003–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72A6.1 Overview of Commodity Risk Management Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84

South Asia Economic Focus – A Review of Economic Developments in South Asian Countriesvi

A Note on Fiscal Years and Financial Reporting by South Asian CountriesSouth Asian countries’ national income and product account data refer to fiscal years that cut across calendar years, except for Maldives and Sri Lanka which report according to calendar year.

The fiscal years for the respective countries are:

• Bangladesh and Pakistan: July 1–June 30• Nepal: July 16–July 15• India: April 1–March 31• Bhutan: July 1–June 30• Maldives and Sri Lanka: January 1–December 31• Afghanistan: 1 April–31 March

Reporting practices vary. Bangladesh, Nepal, and Pakistan report their fiscal data in the second year of the split, while India and Afghanistan report at the beginning of the fiscal year split.

Picture CreditsCover, pp. ix, 11: Michael Foley, pp. vii, 29: Simone McCourtie, pp. 19, 25, 39, 83: Ulrich Bartsch, Copyright World Bank.

viiSouth Asia Economic Focus – A Review of Economic Developments in South Asian Countries

Foreword

WeLCoMe To The FIRST ISSUe oF South Asia economic Focus, a biannual series prepared under the aegis of the Chief

economist’s office. This series reviews contemporary economic developments in South Asian countries, with each issue examining a single subject in depth. The analysis seeks to identify key factors underlying the issue, outline the policy challenges it poses to indi-vidual countries and the region, and offer practical solutions where possible. The publication is intended for audiences within the Bank, its partners and client countries in order to enrich fruitful discussion and policymaking.

The current issue was prepared by Ulrich Bartsch and Chandana Kularatne with inputs from John Baffes, Sudeshna Banerjee, Julie Dana, Madhur Gautam, Mohinder Gulati, Maros Ivanic, Maria Mini Jos, Ashi Kathuria, Annette de Kleine, Jie Li, Luc Laviolette, Nkosinathi Mbuya, Cem Mete, Mohua Mukherjee, Claudia Nassif, Shilpa Phadke, Martin Rama, Mansoora Rashid, Cristina Savescu, Monika Sharma, hassan Zaman, TG Srinivasan and the World Bank’s country economists in the region, and with editorial support from Peter honey and Robert Reinecke.

ixSouth Asia Economic Focus – A Review of Economic Developments in South Asian Countries

Executive Summary

WhILe SoUTh ASIAN CoUNTRIeS weathered the Global Financial Crisis (GFC) relatively well, and have since emerged from

their economic slowdowns, inflation has accelerated above comfort levels. Food prices were the biggest contributor to CPI inflation, although core infla-tion (calculated by excluding food and energy items) is accelerating in most countries. In fact, it overtook food inflation in India by the end of 2010.

This report focuses on the impact of policies and exogenous shocks on food inflation. It deals with four elements: 1) the pass-through of global food (and other commodity) prices, 2) macroeconomic policies, 3) market regulation and short-term supply shocks, and 4) long-term structural shifts and the terms of trade between agriculture and other sectors of the economy.

1. Food inflation is partly caused by increases in global food prices. They have risen markedly since mid-2010, which is part of a more general phenomenon of rising global commodity prices. Policies in the region differ in the extent to which they allow external trade of food commodi-ties, and pass-through of international prices to consumer prices.

2. While South Asian countries have made cautious progress toward rolling back macroeconomic stim-ulus measures they had adopted in the wake of the GFC, they have some way to go to reset their macroeconomic policy stances to neutral. South Asian countries have relatively high fiscal defi-cits and public debt burdens, and fiscal policies are still more expansionary than before the GFC. Monetary policy rates are low, and have not risen as fast as inflation. Policy rates are lower than rates in other regions, but growth in monetary aggregates is broadly in line with macroeconomic stability in most countries.

3. Short-term supply shocks to agriculture are mostly weather related. While sharp, often geographically concentrated price spikes are to a large extent caused by insufficient infrastructure (roads, cold storage),

red tape also restricts food markets in some coun-tries from discharging their resource allocation function smoothly.

4. Demand for food is undergoing structural shifts as incomes rise. Growth in consumption of pulses, fruits, meat, eggs, and dairy items is more than double the consumption growth in cereals. Inflation in these items has been higher than in cereals. Public intervention in agricultural marketing in India and Pakistan has high fiscal costs and narrowly supports cereal production, while high food infla-tion and continuing high rates of food insecurity are linked to an inadequate supply response in non-cereal food products. Input subsidies, on the other hand, contribute to the overuse of water resources, high losses of electricity utilities, and deteriorating soil conditions because of skewed application of fertilizer. While these policies therefore do not contribute to increasing agricultural productivity, their fiscal costs divert resources away from inter-ventions that actually could expand production: investments in agricultural research, education, and rural roads are the three most effective public spending items in promoting agricultural growth and reducing poverty.

South Asia Economic Focus – A Review of Economic Developments in South Asian Countriesx

The poverty and nutritional impact of food price spikes on the poor is significant since they spend a larger fraction of their income on food than relatively better-off individuals. Since the last food price spike in 2008, governments in South Asia have strength-ened safety nets, but gaps persist. The largest safety net interventions in the region—India’s and Pakistan’s public distribution systems for staple foods—are char-acterized by high leakages and therefore costs, while errors of exclusion are actually larger than the reverse; that is, large numbers of the deserving poor are not covered. These food based safety net interventions spill over into agricultural policies, which lower the agri-cultural supply response to rising non-cereal prices.

The report proposes five policy options for consid-eration: 1) in the face of rising inflation caused by rising food prices, demand management policies in South Asia may need to be deployed earlier than in advanced countries because of the high share of food

items in consumer baskets; fiscal consolidation would be a priority; 2) foodgrain stock management needs to improve, in particular in India; 3) over the longer term, policies aimed at increasing agricultural output and productivity would alleviate pressures on food prices; these would include a focus on technology, improved water management, rural infrastructure, agricultural diversification, and private sector invest-ment in marketing and the agro industry; 4) govern-ments should exploit the efficiency gains they could achieve (in terms of protecting and improving nutri-tional status) through provision of more nutritious foods (e.g. foods fortified with essential vitamins and minerals) and by increasing beneficiary knowledge on how to maximize household resources for nutri-tional impact; and 5) governments should explore developments of market-based tools and assistance for managing risks, particularly those that affect the government’s budget.

1South Asia Economic Focus – A Review of Economic Developments in South Asian Countries

IWhy Food Prices Matter

INTeRNATIoNAL FooD PRICeS ARe oN the rise again for the second time in four years, and are raising concerns about the impact on poverty,

overall inflation, and external and fiscal balances in developing countries. higher and more volatile food prices threaten food security by diminishing the ability of people to access food when they need it. In partic-ular, sudden and large food price increases—by eroding household purchasing power—complicate their efforts to adjust and often result in reduced calorie intake and deteriorating nutritional content, in turn pushing more people into poverty.

This report examines food and overall inflation trends in South Asia, which is experiencing relatively high inflation, and is home to a large number of poor. There are many more poor people who are net buyers of food than there are those who benefit from higher prices of agricultural products even in the predomi-nantly rural countries of South Asia. The report exam-ines both short-term and longer-term drivers of rising food prices in the region, including developments

in international commodity prices, domestic supply shocks, accommodative demand side policies, struc-tural changes in demand patterns, and long-term agri-cultural productivity trends. The impact on poverty is examined, as is the region’s preparedness for food price shocks.

The priorities laid out in the Bank’s Post-Crisis Directions paper (2010) and the mandate given to the Bank by the G20 are to focus on food price volatility, agriculture and food security, and agricultural produc-tivity. In line with these priorities, the report ends with some policy directions to manage the macroeconomic impact of food price inflation, and the potential spill-over into generalized inflation, to manage the social impact of the food price hikes, and to hedge against risks associated with food price volatility.

The report is organized as follows: Section II discusses the anatomy and short- and longer-run drivers of food and overall inflation in South Asia. Section III discusses the impact of government poli-cies affecting agricultural marketing, inputs and trade

FIGuRE 1.1 South Asia: Food Prices(y-o-y change in percent)

Bangladesh India Pakistan Sri Lanka Nepal Afghanistan World

–40

–20

0

20

40

60

80

1/20

07

4/20

07

7/20

07

10/2

007

1/20

08

4/20

08

7/20

08

10/2

008

1/20

09

4/20

09

7/20

09

10/2

009

1/20

10

4/20

10

7/20

10

10/2

010

1/20

11

Sources: CEIC and FAO.Note: Country series show food component of consumer price index changes, World series shows changes in FAO Food Price Index, which is based on international commodity prices.

South Asia Economic Focus – A Review of Economic Developments in South Asian Countries2

in South Asian countries. Section IV presents an assess-ment of the impact of food price increases on poverty and an assessment of the preparedness of South Asian countries social protection schemes to cope with this

impact. Section V concludes with some policy direc-tions that could be pursued by South Asia to improve agricultural productivity and mitigate the impact of food price volatility on its population.


Determinants of Food Inflation

1. The Trajectory of Inflation in Recent Years

Inflation rates in South Asia averaged close to 10 percent in the years leading up to the global commodity price boom of 2007–08, reached a high of 20 percent in the summer of 2008, and slowed markedly with the collapse of international commodity prices and economic slow-downs associated with the GFC. Inflation in most countries fell to the low single digits toward the end of 2009. Since then, average inflation has been on an upward trajectory and reached 10 percent by the end of 2010. South Asian countries broadly share this rebound in inflation with other emerging-market countries because the rebound is driven in part by the trajectory of international commodity prices (see Figures 2.1 and 2.2, Box 2.1).

Food prices were the biggest contributor to CPI inflation, although core inflation (calculated after removing food and energy prices) was trending up in most countries. In fact, in India core inflation was driving overall inflation in 2010, although food inflation was the biggest contributor to inflation in

the years prior to 2010. Inflation in India has risen every year since 2007, notwithstanding the see-saw trajectory in global commodity prices over 2007–09.

Non-cereal prices are rising fastest during the current food inflation episode, unlike during the last such episode in 2007–08, when cereal price increases were responsible for a larger share of food inflation.In India for example, the recent surge in food prices is due to a spike in fruit and vegetable prices, which increased by 22.8 percent (Figures 2.3 and 2.4). Items such as milk, eggs, meat, fish and spices also experi-enced double-digit inflation rates. The same is true for Bhutan and Nepal as prices there closely track food prices in India.1

The South Asian countries have different infla-tion stories:

Prices in Afghanistan rose at the end of 2010 because of difficulties in trade relations with its neigh-boring countries. economic growth is high because of largely donor-financed construction spending. Substantial differences between the Afghan and Pakistani governments regarding the interpretation of the Afghanistan-Pakistan Transit Trade Agreement

II

FIGuRE 2.1 WPI Inflation in Major Emerging Market Economies(y-o-y change in percent)

India Brazil China Thailand Philippines Malaysia Korea

0

–15

–10

–5

5

10

15

20

25

M1

2006

M3

2006

M5

2006

M7

2006

M9

2006

M11

200

6

M1

2007

M3

2007

M5

2007

M7

2007

M9

2007

M11

200

7

M1

2008

M3

2008

M5

2008

M7

2008

M9

2008

M11

200

8

M1

2009

M3

2009

M5

2009

M7

2009

M9

2009

M11

200

9

M1

2010

M3

2010

M5

2010

M7

2010

M9

2010

M11

201

0


(APTTA) have resulted in a postponement of its implementation. The areas of contention relate to bank guarantees, international requirements for sealed trucks, biometric systems and the installation of tracking systems. Meanwhile, thousands of containers bound for Afghanistan are stranded in Pakistani ports. Iran blocked fuel supplies to Afghanistan in

December 2010. It is estimated that 30–40 percent of Afghanistan’s fuel is imported from Iran. The blockade halted 2,500 trucks and led to a 70 percent increase in fuel prices in January 2011. The ban was lifted in early February, but the government has since tried to source fuel from other countries. Price increases in transportation and fuels were 12.2 percent and

FIGuRE 2.3 India: Food Articles’ Contribution to WPI Food Inflation(percent change, y-o-y)

–5

0

5

10

15

20

25

Cereals Pulses Fruits & Veg. Milk Egg, Meat and Fish

1/20

08

3/20

08

5/20

08

7/20

08

9/20

08

11/2

008

1/20

09

3/20

09

5/20

09

7/20

09

9/20

09

11/2

009

1/20

10

3/20

10

1/20

11

3/20

11

5/20

10

7/20

10

9/20

10

11/2

010

Source: CEIC.

FIGuRE 2.2 South Asia: Consumer Prices(y-o-y change in percent)

Bangladesh India Pakistan Sri Lanka Nepal Afghanistan Average

–20

–10

0

10

20

30

40

50

1/20

07

3/20

07

5/20

07

7/20

07

9/20

07

11/2

007

1/20

08

3/20

08

5/20

08

7/20

08

9/20

08

11/2

008

1/20

09

3/20

09

5/20

09

7/20

09

9/20

09

11/2

009

1/20

10

3/20

10

5/20

10

7/20

10

9/20

10

11/2

010

1/20

11

3/20

11

Source: CEIC.Note: Consumer price index (CPI) based; CPI for Industrial Workers for India.

Determinants of Food Inflation 5

FIGuRE 2.4 South Asia: Contribution to CPI Inflation(percent change, y-o-y)

Afghanistan

–20

–10

0

10

20

30

40

2007 2008

2008

2008

2009

2009

2009

2010

India

2007 2010

Srilanka

2007 2010

0

2

4

6

8

10

0

2

4

6

8

10

12

14

0

3

6

9

12

15

18

21

24

Miscellaneous Housing and Fuel Clothing Food

0

3

6

9

12

15

18

21

Bangladesh

2007 2008 2009 2010

0

2

4

6

8

10

Nepal

2007 2008 2009 2010

Pakistan

2007 2008 2009 2010

Source: CEIC, CSO-Afghanistan.Notes: For India: CPI Industrial Workers; Afghanistan, Bangladesh, Nepal, Sri Lanka and Pakistan: National CPI, Calendar Year (January–December).


26.2 percent, which indirectly affected the price of food items.

In Bangladesh, food price increases are the main driver of overall inflation, and are driven by interna-tional prices. Non-food inflation was 3.8 percent in January 2011. Growth in monetary aggregates is high and above the government’s target because of high growth in credit to public and private enterprises. Budget execution is better than expected, despite pressures from rising food and fuel prices, because of high revenue buoyancy. however, the fiscal stance for 2011 is likely to be expansionary with a deficit of 4.6 percent of GDP, compared to 3.1 percent in fiscal 2010.

Price developments in Bhutan closely track Indian prices. The Bhutanese currency, the ngultrum, is pegged to the Indian rupee, and India is Bhutan’s key trading partner.

India’s inflation was lower than the regional average prior to the international commodity price boom and only reached the low double digits at end 2008, partly because government policies shielded consumers from higher international energy prices. Inflation started rising in mid-2009 because of the impact of deficient monsoon rains on agricultural production and food prices, and some delayed pass-through of higher oil prices. Indian inflation reached a high of 16 percent in January 2010, the highest in the region at the time, but has since declined to slightly below 10 percent, which is about average. Core inflation has been on a rising trend since mid-2009 and reached 8.9 percent in March 2011. If the recent momentum is main-tained, WPI inflation will again reach double digits by September 2011.

Maldives is one of the most open economies in the world, largely because imports are so significant (almost 70 percent of GDP in 2010). Food and fuel products make up almost 40 percent of imports and comprise 40 percent of the CPI basket. The recent rise in international food and fuel prices, therefore, raises concerns over a mounting balance-of-payments deficit and consumer price inflation. economic growth is dominated by developments in the fiscal balance, which has been improving but is still not in line with macroeconomic stability.

With accommodative monetary policy leading to high liquidity associated with remittances, inflation in Nepal rose to nearly 15 percent in 2008 and has remained in double digits since. In addition, during most of fiscal 2010, Indian inflation was higher than that of Nepal which, given the open border, resulted in imported inflation. however, the two rates have been converging in recent months. As of mid-January 2011, annualized inflation was running at 11.3 percent.

Pakistan not only imported higher inflation from international commodity prices, but macroeconomic imbalances and the floods of 2010 also provided domestic sources for price rises. Inflation hovered around 25 percent from mid-2008 to early 2009, came down somewhat at the end of 2009, but is now again around 14 percent, the highest in the region. The surge after January 2011 resulted from supply short-ages mainly in food items after the devastating floods


of 2010, a widening fiscal stance partly because of a 50 percent wage hike for civil servants, financing of the fiscal deficit through monetization, but also from otherwise welcome adjustments to unsustainable struc-tural policies: an upward revision in electricity tariffs by 17 percent, and an end to interventions by the State Bank of Pakistan in the foreign exchange market to finance oil imports, which resulted in some rupee depreciation. however, the rupee has rebounded some-what in recent months.

In Sri Lanka, inflation remained under 7 percent throughout 2010, but rose to 9.8 percent in April 2011. Food prices have determined inflation. Fuel prices have had a minimal impact on inflation, because inter-national oil prices were not passed on to consumers until April 2011. Retail gasoline and diesel prices are unchanged since the end of 2009, as the government absorbed price increases by lowering fuel taxes.

Inflation rates in Sri Lanka and Afghanistan show the strongest correlations with international commodity prices, rising in 2008 before falling sharply in the last quarter of the year. however, while Sri Lanka’s infla-tion was close to zero through mid-2009, Afghanistan’s was strongly negative.

2. Short-term Pressures: Global Food Prices, Aggregate Demand, and Domestic Supply Shocks

Global Commodity Prices

From mid-2010, there has been a steep rise in the prices of most agricultural commodities, including food crops. In February 2011, the World Bank Food Price Index surpassed the record high of June 2008 (Figure 2.5). It had registered the largest annual increase since July 2008. A large contributor to the increase in global food prices on the supply side is the rising cost of energy (Figure 2.6).2 higher energy prices translate into increased costs of fertilizers, costs of fuel for trans-portation and running machinery, and lower produc-tion of food stuffs because of competition for land from the production of crops for biofuel. on the demand side, fast income growth in large developing countries has put pressures on the supply-demand balance (See Annex 1).

Wheat prices have risen markedly since mid-2010 while rice prices have remained mostly flat. however,

unlike the food price hike of 2007–08, where 48 percent of the increase in the overall food index was due to rising grain prices, fats and oils, meat, soybeans sugar are contributing the bulk of the rise in food prices (Figures 2.7 and 2.8).

Moreover, food prices have displayed extraor-dinary volatility over 2007–2010 with volatility in grains, vegetable oil, and soybeans rising. Since the 1960s, sugar has consistently been the most volatile

FIGuRE 2.6 Agriculture and Energy PricesNominal indices, 2000 = 100

0

100

200

300

400

1986

1989

1992

1995

1998

2001

2004

2007

2010

Agriculture Energy

223% up

50% up

Source: World Bank.

FIGuRE 2.5 Global Food Price Index and Its Components

Soybean Meal

Meat

Sugar

Fruits Oils Grains

Soybeans

2005

H1

2005

H2

2006

H1

0

50

100

150

200

250

300

2006

H2

2007

H1

2007

H2

2008

H1

2008

H2

2009

H1

2009

H2

2010

H1

2010

H2

2011

Q1

Total Food

Source: World Bank.


agricultural commodity over each decade, while meat prices have been least volatile on average. The increase in volatility is due to an increase in the frequency of supply shocks combined with limited reserves and an increase in the production of biofuels, and an increase in global macroeconomic volatility post-2000.

Increasing investment fund activity in commodity futures exchanges is frequently cited as a contributor to commodity price inflation. Despite much conten-tion over the issue, however, empirical evidence shows small or no impact. Most of the evidence suggests that

investment fund activity will probably not alter long term price trends, but it may induce higher price vari-ability by exacerbating the length and amplitude of price cycles (see Annex 2).

Global Price Pass-through

South Asian countries vary in the extent to which inter-national food prices feed through to consumer prices depending on their openness to global markets and the extent to which food prices are insulated from interna-tional prices through subsidies and price caps. Inflation rates in Maldives, Sri Lanka and Afghanistan show the strongest correlations with international commodity prices.3 All countries in the region import a large share of their consumption requirements of edible oil (see Figure 2.9).

The degree of pass-through of international prices depends on the commodity. Bangladesh, India and Nepal allow limited pass-through of international rice prices to the domestic market. For instance, in Bangladesh the pass-through of rice prices is estimated at only 16 percent while there is complete pass-through of international wheat prices where imports account for 80 percent of domestic consumption. overall, for Bangladesh, the domestic food price change (caloric-weighted) between 2009Q1 and 2010Q4 is approx-imately 38 percent while for international prices it is 35 percent. Therefore in general, food prices in Bangladesh rose with international prices (Figures 2.10 and 2.11).

FIGuRE 2.8 The Price Spikes of 2007/08 and 2010/11(percent change, Apr–Jun 2008 from a year earlier and Dec 2010–Feb 2011 from a year earlier)

2007/2008 2010/2011

Beverages

Grains

Food

Agriculture

0 20 40 60 80 100

Source: World Bank, DEC Prospects Group.

FIGuRE 2.7 International Commodity Prices(Index, 2000 = 100)

50

100

150

200

250

300

350

400

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Wheat Rice SoybeansCrude oilPalm oil

Forecast

Source: World Bank, DEC Prospects Group.


Link Between Energy and Food Prices in South Asia

While there is a clear link between energy prices and food prices globally, the relationship is tenuous in South Asia because governments regulate domestic energy prices and pass-through of international prices is limited. Therefore, the contribution of domestic energy prices to food price inflation has been limited so far. In India, the prices of diesel, kerosene and LPG are regu-lated while petrol prices were deregulated in principle last year but still have been adjusted only partially.4 Bangladesh and Sri Lanka allow gasoline prices to adjust over time, but keep diesel heavily subsidized in order to protect their farmers.5 only Pakistan has a formula-based price adjustment mechanism for both diesel and gasoline (Figure 2.12).6 Governments in the region are keeping electricity prices artificially low to the agricultural sector and, therefore, electricity prices do not play a major role in food prices. In India, many farmers receive free, unmetered electricity.

Domestic Supply Shocks

Domestic supply shocks contributed to food price infla-tion in some South Asian countries. For instance, Pakistan faced higher wheat prices given the crop damage from the flooding of August-September 2010. This led to a jump in food inflation to 21.2 percent in September 2010, from 12.8 percent in July 2010 (y-o-y). The impact of higher wheat prices has been particularly large since wheat is the main grain staple. In India, inflation started rising in mid-2009 because of the impact of deficient monsoon rains on agricultural production, and unsea-sonal rains and transport disruptions in November 2010.7 In Sri Lanka, vegetable prices surged after devastating floods in early January. Bean prices rose 55 percent and coconut prices 70 percent compared to a year earlier. Some non-essential foods that are preferred additions to dishes rose even more over the year—red onions by 245 percent and chilies by 77 percent.

Macroeconomic Policies

even though the main driver of inflation in South Asia is food inflation, core inflation has been rising from 2009 pointing to general demand side pres-sures. Current account deficits are also widening in the region. While the level is not worrying as such, the widening supports the view that aggregate demand

is getting ahead of supply. on average, the countries had current account deficits of 2.4 percent in 2010 as compared with 1.7 percent in 2009. The deterio-ration in the current account deficit also reflects the real appreciation of regional currencies with the rising inflation rate differential between South Asian coun-tries and their trading partners.8

FIGuRE 2.9 Imports of Rice, Wheat and Edible OilsShares of domestic consumption, 2008/9–2010/11 period averages, zeros indicate no data available, ranked by wheat

0

20

40

60

80

100

120

140

Nep

al

Indi

a

Paki

stan

Afgh

anis

tan

Bang

lade

sh

Sri L

anka

*

Rice Wheat Edible oils

Source: FAO.

FIGuRE 2.10 Domestic and International Prices of Rice(Index, LCU, January 2007 = 100)

100

0

50

150

200

250

300

350

Jan-

07

Apr-0

7

Jul-0

7

Oct-0

7

Jan-

08

Apr-0

8

Jul-0

8

Oct-0

8

Jan-

09

Apr-0

9

Jul-0

9

Oct-0

9

Jan-

10

Apr-1

0

Jul-1

0

Oct-1

0

Jan-

11

Bangladesh Pakistan

Sri Lanka India

International rice price

Source: FAO.


Meanwhile, surveys show that inflation expecta-tions are rising and this holds risks for further upward pressure on core inflation.9 For example, household surveys in India reveal 1-year ahead expected inflation has risen to 13.1 percent in 2010Q4 from 6.2 percent in 2009Q1.10 The perceived current rate of inflation has also risen to 11.8 percent from 5.8 percent over the same period. If this trend continues, households could revise their inflation expectations upwards in tandem with perceived inflation in 2011 (Figure 2.13). Rising

inflation expectations and escalating food inflation are encouraging workers to demand higher wages, which contributes to higher core inflation.11

The growth in aggregate demand in the region is supported by an accommodative macroeconomic policy stance. South Asian governments widened their policy stances in the wake of the GFC, but for most it is probably now time to reset macroeconomic policies to neutral. Steps toward fiscal consolidation have been cautious at best so far despite the fact that South Asia’s deficit and public debt to GDP ratios are amongst the highest in the world (Figures 2.14 and 2.15).12

With regard to monetary policy, monetary aggre-gates expanded in line with the economic recovery in most countries despite low policy rates compared with other regions.13 Credit expansion is still mostly low compared with the growth rates prevalent during 2004–07.14 Monetary conditions in India have been tightened since late-2009, and are broadly neutral as indicated by a monetary conditions index (MCI, Figure 2.16).15 The index combines money supply growth, interest rates and changes in the exchange rate. IMF research shows that changes in the first two account for about 25 percent of inflation and changes in the latter about 10 percent.16

While rising core inflation and widening current account deficits hint at general demand-side pres-sures, capacity utilization rates draw a mixed picture. In India, capacity utilization indicators are stable, while the recent industrial production and imports data point to a slowdown rather than overheating (Figure 2.17). Different estimates of potential output measures across the region’s economies (Afghanistan, Bangladesh, India, Sri Lanka) suggest output gaps narrowed or closed in 2010.

3. Long-term Effects: Productivity Slow-down and Structural Demand Shifts

After the rapid advances during the “Green Revolution” in the 1960s and 1970s, agricultural growth rates in South Asia have been low and fairly stable, although short-term volatility of agricultural output has been high. The production of cereals and pulses has been increasing by around 2 percent per year since the early 1980s, while the growth in the production of vegetables and fruits has been around 4 percent. There are, however, weak indications of

FIGuRE 2.11 Domestic and International Prices of Wheat(Index, LCU, January 2007 = 100)

Bangladesh Pakistan

Sri Lanka India

International rice price

100

0

50

150

200

250

300

350

Jan-

07

Apr-0

7

Jul-0

7

Oct-0

7

Jan-

08

Apr-0

8

Jul-0

8

Oct-0

8

Jan-

09

Apr-0

9

Jul-0

9

Oct-0

9

Jan-

10

Apr-1

0

Jul-1

0

Oct-1

0

Jan-

11

Source: World Oil, U.S. Department of Agriculture and World Bank.* Sri Lanka’s wheat imports as a share of consumption is above 100% due to re-exports.

FIGuRE 2.12 Subsidization of Diesel Retail Fuel Prices Remains Particularly High in Bangladesh and Sri Lanka(US cents per liter prices as of November 2010, and U.S. retail price reference band of 84 for diesel and 76 for gasoline)

United States

China

Pakistan

Nepal

India

Sri Lanka

Bangladesh

84

104

92

91

82

66

63

76

111

86

118

115

119

125

Gasoline Diesel

Sources: GTZ, International Fuel Prices 2011, and World Bank.


FIGuRE 2.13 India: Household Inflation Expectations(Price change in percent)

0

2

4

6

8

10

12

14

16

Sep-

06

Dec-

06

Mar

-06

Jun-

06

Sep-

07

Dec-

07

Mar

-07

Jun-

07

Sep-

08

Dec-

08

Mar

-08

Jun-

08

Sep-

09

Dec-

09

Mar

-09

Jun-

09

Sep-

10

Dec-

10

Current 3-Months Ahead 1-Year ahead

%

Source: Reserve Bank of India.

FIGuRE 2.14 General Government Balances(Percent share of GDP)

–9–8–7–6–5–4–3–2–1

012

Sout

h As

ia

High

-Inco

me

coun

tries

Mid

dle

East

and

Nor

th A

frica

East

Asi

aan

d Pa

cific

Latin

Am

eric

aan

d Ca

ribbe

an

Sub–

Saha

ran

Afric

a

2007 2010 2013

Source: World Bank Databases and DEC Prospects Group Projections.

declining growth rates of agricultural production in the region (Figure 2.18).17

With population growth continuing at around 2 percent per year and income growth accelerating, it is not surprising that imports of the staple items: wheat, rice, maize, and vegetable oil, have increased sharply

FIGuRE 2.15 Total Government Debt(Percent share of GDP for fiscal years (*calendar years 2008 and 2009))

2007–08 2009–10

0102030405060708090

100

Afgh

anis

tan

Nep

al

Bang

lade

sh

Paki

stan

Bhut

an

Indi

a

Sri L

anka

*

Mal

dive

s*

Emer

ging

*

High

-inco

me*

Source: Reserve Bank of India.


FIGuRE 2.16 India: Monetary Conditions Index

Inde

x

–10

–8

–6

–4

–2

0

2

420

07m

1

2007

m3

2007

m5

2007

m7

2007

m9

2007

m11

2008

m1

2008

m3

2008

m5

2008

m7

2008

m9

2008

m11

2009

m1

2009

m3

2009

m5

2009

m7

2009

m9

2009

m11

2010

m1

2010

m3

2010

m5

2010

m7

2010

m9

2010

m11

Narrow Broad

Tightening

Loosening

Source: Authors calculations

FIGuRE 2.17 Industrial Production(Annual percent change)

Jun-

08

Aug-

08

Oct-0

8

Dec-

08

Feb-

09

Apr-0

9

Jun-

09

Aug-

09

Oct-0

9

Dec-

09

Feb-

10

Feb-

11

Apr-1

0

Jun-

10

Aug-

10

Oct-1

0

Dec-

10

25201510

505

1015202530

Bangladesh India Sri Lanka Pakistan

Sources: Thomson Datastream, Haver and World Bank, DEC Prospects Group.

from around 5 million metric tons in the early 1990s to double that level at the end of the 2010 decade.

With rising incomes, consumption growth has been accelerating and is now significantly higher than production growth for major food groups. This is most notable in India, where household surveys suggest that the consumption of food is increasing by around 3 percent per year. Within the food group, however, growth in consumption of pulses, fruits, meat, eggs, and dairy items is around 4 percent, while the growth rate in consumption of cereals is around 1.5 percent (Figure 2.19). While the data from the Indian household surveys are highly volatile, they

do indicate a gap between accelerating demand and slowing supply growth. Accordingly, the domestic terms of trade have been shifting in favor of agri-culture ever since the late 1980s, when the produc-tivity advances of the “Green Revolution” petered out (Figure 2.20).

Within this overall picture, the demand pressure on cereals is relatively lower as demand is shifting toward a higher-protein diet. Accordingly, higher-protein food articles and fruits and vegetables have been the main drivers of food inflation since 2008. The shift to higher protein foods is noticeable across the region (Figure 2.21).


The shift to a higher-protein, fruit- and vegetable-rich diet is also supported by Indian household survey data showing consumption baskets for different house-hold groups: richer households spend a higher share of their incomes on non-food items and, for food, a higher share on pulses, fruits, vegetables, eggs, meat, and dairy (Figure 2.22). Therefore, as incomes rise, households’ consumption patterns shift. This shift also emerges in comparing the average shares of various

food items in household consumption, based on Indian household surveys of the last 20 years (Figure 2.23). For example, in 1987–88 rural Indian households spent over 40 percent of their food budgets on cereals, but by the 2007–08 survey this had fallen to around 30 percent. A similar shift occurred among urban house-holds, though less pronounced. Such shifts represent differential growth rates of consumption for different food items.


BOx 2.1 Inflation in China – What is Different?

China and India have many characteristics in com-mon . Notably, both countries have more than 1 billion people each; they are the fastest growing economies in the world; and food prices have played a signifi-cant role in recent increases in their inflation rates . In China, inflation rose to 5 .4 percent (y-o-y) in March 2011, a 32-month high . A combination of domestic weather-related shocks and the global food price increase contributed to rising food prices . Vegetable prices, the key driver of inflation in 2010, peaked in February 2011 and have moderated since . Unlike in India, non-food inflation in China has been relatively moderate, registering 2 .3 percent in March 2011 . However, throughout 2010 and the first quarter of 2011, non-food inflation has been rising and is a grow-ing cause for concern among policy makers . Rising residential property prices—with inflation averaging 12 percent for new housing in 70 major cities—have also been a feature of inflation in China, and have been fueled by rapid credit growth .

The Chinese government has taken several steps to contain inflation . First, it ended the large fiscal stim-ulus implemented in 2008 to support the economy in the wake of the global financial crisis, reducing the

budget deficit from 2 .8 percent in 2009 to 1 .6 percent in 2010 . Second, the central bank raised the reserve requirement for banks six times in 2010 and three times in the first quarter of 2011 (to 20 .0 percent for large banks) . It also lifted the benchmark interest rate between January 2010 and March 2011 to 6 .06 percent . These actions helped moderate growth in domestic credit to the private sector to 20 .3 percent in December 2010 from 33 .1 percent a year earlier . Third, China took actions to curb house prices, includ-ing raising mortgage interest rates and down pay-ments, and directing banks not to lend for purchases of third (or more) homes . Fourth, the real apprecia-tion of the yuan, by about 4 percent, helped tighten monetary conditions . In addition to normalizing the overall macroeconomic policy stance, the government took measures to boost food supply and reduce the cost of production and logistics, including releasing grain from China’s large reserves, increasing subsidies to farmers, exempting transport of vegetables from road toll, and boosting food imports . More recently, it limited the increase in domestic fuel prices arising from higher oil prices, and applied moral suasion on manufacturers of food and consumer products .

% Y

ear o

n Ye

ar

Jan-

09

Mar

-09

May

-09

Jul-0

9

Sep-

09

Nov

-09

Jan-

10

Mar

-10

May

-10

Jul-1

0

Sep-

10

Nov

-10

Jan-

11

Mar

-11

–5

0

5

10

15Rising rates of headline, core and food inflation…

CPI FoodNon-food

–5

With GDP rebounding driven by investment…

0

5

10

15

20

2005 2006 2007 2008 2009 2010

NX Invest Gov cons HH cons GDP

% Y

ear o

n Ye

ar


BOx 2.1 Inflation in China – What is Different? (continued)

% Y

ear o

n Ye

ar

Jan-

09

01-J

an-1

001

-Feb

-10

01-M

ar-1

001

-Apr

-10

01-M

ay-1

001

-Jun

-10

01-J

ul-1

001

-Aug

-10

01-S

ep-1

001

-Oct

-10

01-N

ov-1

001

-Dev

-10

01-J

an-1

101

-Feb

-11

01-M

ar-1

1

Mar

-09

May

-09

Jul-0

9

Sep-

09

Nov

-09

Jan-

10

Mar

-10

May

-10

Jul-1

0

Sep-

10

Nov

-10

–5

0

5

10

15

Property prices are still rising but at a lower rate ....

Lend

ing

rate

s (%

)

Grow

th in

M2/

Requ

ire re

serv

es (%

)As monetary policy tightens…20

New housing

15

17

19

21

23

25

27

4.8

5

5.2

5.4

5.6

5.8

6

6.2

Lending rates Money supplyOverall property prices Required reserves

FIGuRE 2.18 Production Growth of Major Staple Food Items(y-o-y change in percent, actuals and long term averages)

Cereals Veg.&Fruits Pulses

–20–15–10

–505

10152025

1981

1982

1983

1984

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

Source: FAO.

FIGuRE 2.19 India: Growth Rates in Consumption(per capita, in percent)

Consumption Food Cereal Pulse_fruit

–2

0

2

4

6

8

10

1993/94 2001/02 2004/05 2005/06 2006/07 2007/08

Source: CSO NSS different rounds, author’s calculations.


FIGuRE 2.20 India: Terms of Trade between Agriculture, Industry, and Services19

51

1953

1955

1957

1959

1961

1963

1965

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

Agric-to-Industry Agric-to-Services

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

Axis

Titl

e

Source: CEIC.

FIGuRE 2.21 Annual Per Capita Consumption

0%10%20%30%40%50%60%70%80%90%

100%

Bangladesh India Nepal Pakistan Sri Lanka Average

Total cereals Pulses Roots & Tubers Edible Oils VegetablesFruits Milk Meat Eggs Fish

1990 2010 1990 2010 1990 2010 1990 2010 1990 2010 1990 2010

Source: Joshi et al. (2007).


FIGuRE 2.22 India: Household Survey Data on Consumption of Food and Non-Food(Consumption pattern across mean per capita expenditure deciles, 2004–05)

cereal pulse fruit oil bev salt spice non food

Urban

0–10

10–2

0

20–3

0

30–4

0

40–5

0

50–6

0

60–7

0

70–8

0

80–9

0

90–1

00

Rural

0%10%20%30%40%50%60%70%80%90%

100%

0–10

10–2

0

20–3

0

30–4

0

40–5

0

50–6

0

60–7

0

70–8

0

80–9

0

90–1

00

0%10%20%30%40%50%60%70%80%90%

100%

Notes: Computed from unit-level data using 61st round of NSS, Consumption Expenditure (Schedule1); the last thick round. MPCE refers to monthly per capita consumption expenditure. Households were split into consumption quintiles, and then average expenditure of households in each quintile of the different consump-tion categories were computed. The components of the food subcategories are: cereals—cereals and cereal substitutes; pulse fruit—pulses and pulse products, milk and milk products, egg, fish and meat, vegetables and fruits; oil bev—edible oil, sugar and beverages; salt spice: salt and spices; non-food 30—total non-food expenditure computed on the base of a 30-day recall period.

FIGuRE 2.23 India: Shares of Food Types in Food Baskets, 1987/88–2007/08(in percent)

cereal pulse fruit oil bev salt spice

Rural

1987

/88

1993

/94

2001

/02

2004

/05

2005

/06

2006

/07

2007

/08

1987

/88

1993

/94

2001

/02

2004

/05

2005

/06

2006

/07

2007

/08

Urban

0%10%20%30%40%50%60%70%80%90%

100%

0%10%20%30%40%50%60%70%80%90%

100%

Source: CSO NSS.


Notes1. The Bhutanese currency, the ngultrum, is pegged to

the Indian rupee.2. econometric evidence suggests a 10 percent increase

in energy prices leads to a 2–3 percent increase in food prices (Baffes, 2010). oil prices increased by 223 percent increase between 2004 and 2010 leading to a 50 percent increase in food prices.

3. Maldives is one of the most open economies in the world, largely because imports are so significant (almost 70 percent of GDP in 2010) while in Sri Lanka domestic prices follow world prices even though it produces 95 percent of the food it consumes.

4. Although in India there is sometimes a considerable lag between change in international gasoline price and domestic gasoline price. The Indian government increased both diesel and petrol prices in May 2011 with petrol prices rising by 44 percent since February 2010.

5. In both Bangladesh and Sri Lanka the loss is borne by the Bangladesh Petroleum Corporation and the Ceylon Petroleum Corporation, respectively. As such, it is not a direct transfer from the government but recorded in the respective company’s profit and loss accounts.

6. For instance, in January, the Pakistan government increased fuel prices, decreased them a few days later and increased them yet again in early March, before halving them once again.

7. Some delayed pass-through of higher oil prices also contributed to higher overall inflation during this period.

8. Between January 2007 and December 2010, there was a real appreciation of the Sri Lankan rupee of 27 percent, the most amongst all South Asian currencies.

9. IMF (2010) finds a 1 percentage point increase in expected inflation leads to a 0.2–0.4 percentage point increase in core inflation for India.

10. See The Reserve Bank of India’s Inflation expectations Survey of households conducted in 2010Q4 (Round 22),

11. In Sri Lanka, the minimum wages for formal private sector employees under Wage Boards increased, raising the overall nominal wage rate index for the whole sector by 32.0 percent in 2010. Informal sector wages in the Agriculture and Construction sectors also increased by 9.1 per cent and 7.3 per cent, respectively, in 2010. Monthly minimum wage hikes in Bangladesh for government workers of 80.4 percent occurred with effect from July 2010 and in India the average wage rates in the Indian Railways increased by 30.2 percent in 2009–10. Pakistan experienced a 50 percent wage hike for civil servants.

12. South Asia had the largest fiscal deficit among devel-oping countries in 2010, estimated at 8.4 percent, as compared with 6.7 percent on average during the period 2007–09. There is wide variation in fiscal defi-cits in the region in 2010, ranging from 2.5 percent for Bangladesh to 22.5 percent for the Maldives. In India,

the general government deficit rose to 9 percent of GDP in FY2009–10, with 6.8 percent of GDP central govern-ment deficit. only a marginal contraction in central government deficit is estimated to have been achieved with 6.7 percent of GDP in FY2010–11, although some further contractionary impulse was probably coming from India’s states, where borrowing limits were tight-ened. Maldives is struggling to correct macroeconomic imbalances driven by large fiscal deficits of 20.7 percent in 2010 while in Sri Lanka the deficit expanded to 6.8 percent. Large outlays for interest payments are slowing progress toward fiscal consolidation, and while improving in some countries (Afghanistan, Maldives, and Sri Lanka, for example), and the low tax base in countries such as Pakistan makes consolidation partic-ularly challenging. Domestic commodity price distor-tions continue to raise big fiscal concerns for South Asia.

13. In 2009 and 2010, real policy interest rates have been consistently negative in India, reaching a low of –11.5 percent in January 2010 (real interest rate calculated as the difference between the Reserve Bank of India’s repo rate and the concurrent CPI inflation rate). In Bangladesh and Pakistan, real interest rates were nega-tive throughout 2010. During 2010, the authorities began tightening monetary policy. India’s central bank has raised interest rates nine times since end-2009, but policy rates were still negative in real terms in early May 2011 (the nominal benchmark repo rate was set to 7.25 percent on May 3, 2011, while WPI inflation was 9 percent in March). only in Sri Lanka, policy rates have been moving in the opposite direction, with declining policy rates and positive real interest rates during 2010. With real interest rates at 0.2 percent in January 2011, the monetary policy stance is relatively accommodative.

14. In Sri Lanka, growth in credit extension to the commer-cial sector rose steadily in 2010 to 27 percent of GDP, its highest rate since July 2007. In Bangladesh, credit to the private sector also grew steadily at 27.6 percent, in 2010, up from 19.2 percent in 2009. Broad money supply has been climbing between 2009 and 2010 in Bangladesh, Pakistan and Sri Lanka, growing at 22.2 percent, 14.9 percent and 18 percent at the end of 2010, respectively. In India, growth in non-food credit accelerated to 23 percent in the first quarter of 2011. Credit to industry was up by 26.5 percent from the previous year, signif-icantly driven by the financing of telecom license fees.

15. The MCI uses coefficients from Kannan, Sanyal and Bhoi (2006).

16. See IMF (2010).17. Closer analysis of the data shows that changes in trend

growth for pulses and cereals are not statistically signifi-cant; i.e., it is uncertain that production growth rates are indeed declining. Production of vegetables and fruits is so unstable that there is no certainty of a growth trend; i.e., the production increase between 1981 and 2009 is not statistically significant.


I

SoUTh ASIAN GoVeRNMeNTS ToDAY follow very different approaches to marketing staple foods, but are quite uniform in their

attempts to support farmers and food production with input subsidies. While India and Pakistan maintain heavy government control over the marketing of wheat and India also of rice, the other countries have liberal-ized their agricultural sectors to a much larger extent. The Indian and Pakistani systems reduce the ability of the private sector to manage temporary, geographically limited supply disruptions. They are partly responsible for high food inflation over the short-term. on a more structural level, they distort agricultural incentives, and have high fiscal costs. They are maintained by the two governments’ reliance on large-scale distribution of subsidized food items as crucial safety net measures.

Input subsidies in the major countries contribute to overuse of water resources, high losses of electricity utilities, and deteriorating soil conditions because of wrong application of fertilizer, and therefore contribute to the long-term slow-down in productivity growth in agriculture. The fiscal costs of current policies divert resources from more efficient interventions: invest-ments in agricultural research, education, and rural roads—the three most effective public spending items in promoting agricultural growth and reducing poverty.

1. Historical PerspectiveIn the 1950s and 1960s, South Asian countries had similar policies with regard to government involvement in the marketing of food commodities, but their poli-cies started diverging in the late 1970s. Liberalization started first in Sri Lanka, then in Bangladesh, and finally in Nepal in 1998. India and Pakistan, in contrast, still maintain a lot of the features of the systems they had established in the 1960s for their main staples, wheat and rice. especially in India, the government maintains a pervasive system of public procurement, storage, and distribution which gives the private sector only a limited

The Impact of Agricultural Policies on Food Supply

III

role in the handling of the two staples. Pakistan main-tains a similar system for wheat only, because rice is far less important in consumption.1 Afghanistan faces the uphill struggle of rebuilding its economy after decades of conflict, and the agricultural sector is affected by the widespread cultivation of poppy (see Box 3.1).

Systems for government intervention were set up with three main objectives: to increase production, stabilize market prices and risks, and provide subsi-dized food to vulnerable households. In the first of these objectives, the countries were remarkably successful. Cereal production in most countries more than doubled between 1961 and the early 2000s, while it almost quadrupled in Pakistan. Per capita availability of food increased in most countries (Figure 3.1). however, production increases were most impressive in the 1960s


BOx 3.1 The Opium Economy in the Context of Afghanistan’s Agriculture and Food Security

Afghanistan produces more than 90 percent of the world’s opium supply on small portions of its agricul-tural land, generating about 15 percent of national GDP . Opium is Afghanistan’s most important agri-cultural crop in value terms, providing much-needed livelihoods and jobs for segments of the rural popula-tion in the short run—but distorting the incentives for developing a sustainable, formal agricultural sector in the long run . In addition, the large criminal profits associated with the drug industry seriously undermine governance and fuel corruption, dysfunctional politics, and ultimately insecurity and conflict . Thus moving away from reliance on opium is a priority development objective for the medium term . But, since opium is a high-value, storable commodity with a ready market and a secure cash crop for an insecure environment, this will be no easy task .

Progress in eliminating opium cultivation in some areas over a number of years suggests that phasing out opium in Afghanistan over the next 10–20 years is not impossible . Success factors are multi-faceted: In addition to having a credible threat of law enforcement against opium cultivation and trade (but not massive eradication of standing crops in the fields, which is a symptom of failure to deter and fuels resentment and conflict), key ingredients include:

• Reasonably good local resource endowment (agri-cultural land and irrigation) to encourage a variety of agricultural activities, not just opium;

• Close access to markets for licit agricultural crops (e .g ., city vegetable markets), so farmers can sell produce without traveling far, crossing many check-points, or paying many bribes;

• Proximity and access to sizable labor markets (found in cities), so family members of rural house-holds can seek work but also return home if there is no day-labor available, thereby avoiding transport and lodging costs associated with more distant labor markets;

• Opportunities for a variety of other activities such as dairy, transport and other services; and

• The modicum of security usually found near larger cities is most suited to development of sustainable, non-opium agriculture .

The success stories usually associated with areas around cities, such as Jalalabad in the east, will not be easy to duplicate in more remote regions lacking infrastructure . What is required is sustained, broad-based, programmatic rural development, ranging from irrigation investments to horticulture, com-munity development, and better health for livestock (see DFID and World Bank, Economic Incentives and Development Initiatives to Reduce Opium Production, 2008) . Value chain development for both exports and import substitution will be critical, and encouraging the private sector through innovative programs will be much more effective than fragmented investments in parts of the value chain .

Yet, it is also clear that wheat is not the crop of Afghanistan’s future; nor can it replace opium . Export prospects for wheat are extremely limited given the large production of neighboring countries . Moreover, as a low-value, relatively less labor-intensive, yet rela-tively water-intensive crop, wheat is not well-suited for expansion in a country with Afghanistan’s resource endowment: limited arable land, sparse irrigation, water a binding constraint, and abundant labor supply . Shifting all of Afghanistan’s land currently devoted to opium cultivation to wheat, even if it were possible, would leave significant parts of the rural population less employed, poorer, less food-secure, and more vulnerable, with many households forced to take ex-treme measures, such as cutting health expenditures, stopping education of children, or even out-migrating to neighboring countries .

Thus, although efforts to enhance Afghanistan’s self-sufficiency in wheat are justified and have good prospects for success, the way forward for Afghan ag-riculture as a whole—which will also help address the opium problem—is to develop licit, high-value, labor-intensive cash crops . This will only be achieved with necessary investments and improvements (including private-sector milling and increased grain storage capacity) in key factors such as those listed above .

The Impact of Agricultural Policies on Food Supply 21

and 1970s, while the 1990s saw a distinct slowing down in agricultural production growth, and some studies show that total factor productivity actually declined.2 India and Pakistan became net exporters of cereals in the 1990s. With strong production growth, Sri Lanka continues to depend on rice imports, but the share of net imports in availability has declined significantly. In contrast, net imports of cereals as a percentage of avail-ability remained fairly stable in Bangladesh, whereas Nepal has gone from net exporter to importer since the 1980s, although the share of imports in avail-ability is small.

After several bumper harvests, India actually now faces a “problem of plenty”: stocks of wheat and rice far exceed requirements and storage capacity. Given the current international concerns about rapidly rising food prices, in particular those of wheat, the “problem of plenty” could easily turn into an “embarrassment of plenty”: a lifting of India’s ban on exports could have a significant downward impact on international wheat prices.

The question is whether the systems that served India and Pakistan well in the last fifty years are likely to prove equally successful in meeting the considerable challenges of the coming decades: fast income growth and continuing population growth in the context of increasingly binding land and water scarcity. evidence in the form of an emerging gap between demand and production growth highlighted in Section II, the rising fiscal costs of the systems, and the continuing gaps in providing food security to large segments of the population tilt the likely answer to the negative.3 The systems’ concentration on grains also reduces farmers’ incentives to respond to structural shifts in demand.

2. Government Involvement in Agricultural Marketing

Governments in the region are active in the agri-cultural sectors by providing public investments in infrastructure and research, and various input subsi-dies. only in India and Pakistan, however, do govern-ments play an intricate part in the marketing of food grains and impose strong restrictions on private-sector storage and trading.4 This section discusses government involvement in wheat and rice marketing in India and Pakistan, and effects of other (input) policies in the South Asia region.

India

The government notifies Minimum Support Prices (MSPs) for 24 food articles on the basis of costs and (increasingly) political considerations for procurement by the Food Corporation of India (FCI), although only wheat, rice, and coarse grains are procured in mean-ingful quantities.5 Covering sometimes vast distances, the FCI transports grains from surplus to deficit states and releases grains to the Public Distribution System (PDS) to be sold at subsidized prices (see Section IV). The FCI also holds buffer stocks in wheat and rice. It procures about one third of overall production of wheat and rice.6 The FCI maintains an open procure-ment policy, which means it buys at the MSPs any quantities of grain being delivered to its procurement centers within a specified time period. The amount of procurement therefore depends on the attractive-ness of the MSPs relative to the prevailing market conditions.7

Record quantities of procurement after the MSP increases in 2008 resulted in stocks of 40–50 million tons in 2010, which was roughly twice the level the government deems necessary as buffer stocks and far exceeded the FCI’s secure storage capacity. The “problem of plenty” of the large accumulation of stocks is not new: in 2002, stocks had reached 60 million tons under similar circumstances.8

FIGuRE 3.1 Average Food Supply: Crops(kg/capita/yr)

Cereals Fruits Vegetables

0

20

40

60

80

100

120

140

160

180

1961

–198

4

1985

–200

7

1961

–198

4

1985

–200

7

1961

–198

4

1985

–200

7

1961

–198

4

1985

–200

7

1961

–198

4

1985

–200

7

Bangladesh India Nepal Pakistan Sri Lanka

Source: Joshi et al. (2007).


high stocks lead to high wastage because of inade-quate storage capacity and technology. It has been esti-mated that the FCI looses 10–16 million tons of grains every year.9 The FCI’s inefficiencies not only lead to high losses of the grains it handles, they also drive up the costs of food handling. Comparisons show that the FCI’s handling and storage costs are significantly higher than those of the private sector.10

The increase in procurement has led to a signifi-cant increase in the fiscal costs of the system. Food and fertilizer subsidies have increased to over 1.5 percent of GDP since fiscal 2009, from around 1 percent in the mid-1990s (Figure 3.2). The last time subsidies approached 1.5 percent of GDP was in fiscal 2003, another year in which procurement expanded strongly and grain stocks reached 60 million tons. outlays on food subsidies are far higher than public investment in agriculture and outlays for extension services, which could increase agricultural production and lead to lower prices over time.

Pakistan

The government employs a system similar to India’s for public procurement, storage, and subsidized distri-bution of wheat only. Provincial Food Departments (PFDs) and the Pakistan Agricultural Storage and Supply Corporation (PASSCo) are responsible for

implementing the procurement targets set at the federal level. Public procurement absorbs 15–40 percent of total production of wheat. About 95 percent of procure-ment by PFDs is undertaken in Punjab province. Restrictions on the transport of wheat between prov-inces and ad hoc trade restrictions are used to protect prices. International trade of agricultural commodities is handled exclusively by the Trading Corporation of Pakistan (TCP). Trading decisions are not always well designed: the 2008 harvest was overestimated and 3 million tons of exports were allowed, forcing the govern-ment to import almost the same quantity at higher prices later. In the face of an expected bumper crop harvest, the government allowed exports of 1 million tons of wheat in January 2011, the first time since the wheat price rally in 2007.

Bangladesh

The country has come a long way from the pervasive food rationing and government procurement system it maintained prior to the 1980s. There is currently no large-scale government intervention in grain markets. Competitive private traders purchase and retail food; their numbers rose to 48,000 in the 1990s from about 4,000 in the 1960s. Public distribution of grains is limited to cover social safety schemes, the military, police and low-paid public servants. The government maintains public grain stocks for its safety-net programs and emergencies. It targets a level of 1.5 million tons for its public grain stocks, including emergency reserves of 1 million tons (equivalent to two weeks of consump-tion) with the remainder as safety net.

Nepal

The government initiated liberalization reforms in 1986, including removal of the MSP. The government also removed some agricultural subsidies as part of the structural adjustment program supported by the IMF in the 1980s. In 1998, the government downsized its public distribution system, through the Nepal Food Corporation (NFC) and began restructuring it in 2000. Increasing open market operations led to a decline in food procurement by the NFC and consequent declines in government stocks. Liberalization followed estimates that marketing costs for private traders were lower than those of the NFC by over 40 percent prior to 2000. The government also liberalized trade policy: it eliminated all quantitative restrictions and lowered

FIGuRE 3.2 India: Food and Fertilizer Subsidies, 1990–2012(in percent of GDP)

Food Fertilizer

0.0

0.5

1.0

1.5

2.0

2.5

1990

–91

1991

–92

1992

–93

1993

–94

1994

–95

1995

–96

1996

–97

1997

–98

1998

–99

1999

–00

2000

–01

2001

–02

2002

–03

2003

–04

2004

–05

2005

–06

2006

–07

2007

–08

2008

–09

2009

–10

2010

–11

2011

–12*

Sources: MinFin, CSO, author’s estimates. Note: GDP data fis based on the old seriesup to 2003–04, new series from then on.* Figures for 2011–12 are author’s estimates.


tariffs to the lowest average in South Asia. however, a ban on exports was imposed in 2008 to safeguard domestic supply of food. The reforms have improved some indicators of food security in Nepal (rising per-capita food availability and lower malnourishment), notably in the Terai plains, but the benefits have not spread evenly; remoter areas, such as the hills, remain relatively insulated from the improvements.

Government Policies and Short-term InflationIn India and to a lesser degree in Pakistan, large-scale public procurement hampers the private sector not only by pre-emption, but also by taxes and rules for moving grains across state borders, and caps on storage of grains designed to facilitate public procurement. Indian traders also face a requirement of transport in jute bags rather than in bulk.11 The private sector’s costs are increased by the uncertainty created by frequent ad-hoc changes of rules, in particular the stipulations under the essential Commodities Act (eCA).12 The low private sector involvement in grain marketing leads to insufficient investment in the supply chain, and espe-cially in storage facilities.

Marketing rules go beyond grains and put a wedge between retail and farm-gate prices for agricultural produce in general. Farmers in most places are obliged to sell products exclusively through mandis or wholesale markets, where a relatively small number of licensed traders can engage in oligopolistic behavior. While many states have made changes to the Agricultural Product Marketing Act (APMA), the system is still in place in many areas (see Box 3.2). The margin between whole-sale and retail prices has been increasing over a number of years. Reforms to APMAs in some states opened the doors for contract farming, which has resulted in increased incomes for farmers, higher private investment in agriculture, and improvements to the supply chain.13

The lack of development of market infrastructure in the wider sense (including oligopolistic conditions in mandis) exacerbates food price volatility. Markets are not integrated across areas, and buffer stocks are not available to tide over temporary disruptions.14 Apart from policies in India and Pakistan, the dearth of physical infrastructure across South Asian countries is to blame to a large extent, in particular rural roads and cold storage facilities, which leads to large losses of perishable goods, or lowers incentives to produce these goods in the first place.

In India, the simultaneous occurrence of high food inflation and large food-grain stocks has become a

matter of widespread concern. In the past, domestic open market sales were often announced, but the take-up by the private sector usually fell well short of target. The reason was the FCI’s attempt to sell grain at prices higher than the procurement prices to cover some of its costs, which resulted in low or no off-take when MSPs were relatively high. Stringent controls were also imposed on buyers, partly to avoid the sale of grains back to the FCI during the next procurement round. Grain released through open market operations was therefore sold only to millers in bulk.15

Structural Effects of Government Marketing RulesThe concentration of the government’s food policies on the FCI in India, and PASSCo in Pakistan, and their concentration on cereals from a few surplus producing states have in turn resulted in a skewed development of agriculture. Farmers in areas where the government is most active have little incentive to respond to struc-tural demand shifts and diversify production, because that would greatly increase their exposure to risks. Food production (but not necessarily that of wheat and rice) could also increase through extending the benefits of the Green Revolution to eastern states. Yields on the most productive land are multiples of the yields in more traditionally operated farms (Figure 3.3). Use

FIGuRE 3.3 India: Rice and Wheat Yields in Major Producing States, 2006–2009(3-year average, in million MT)

Rice Wheat

0

Mad

hya

Prad

esh

Chha

ttisg

arh

Biha

r

Assa

m

Oris

sa

Mah

aras

htra

Gujra

t

Jhar

khan

d

Utta

r Pra

desh

Karn

atak

a

Wes

t Ben

gal

Tam

il N

adu

Hary

ana

Andh

ra P

rade

sh

Punj

ab

5001,0001,5002,0002,5003,0003,5004,0004,5005,000

All India Averages

Source: CEIC.


of high-yield varieties and fertilizer is still much lower in rain-fed areas.16

3. Policies for Agricultural InputsCountries in South Asia broadly share their approaches to agricultural inputs: subsidies for credit, fertilizer, and irrigation are meant to improve small-farmer livelihoods and agricultural production. They fail on both fronts. While they probably have been the key to small-scale farmers adopting new technologies, especially during the initial stages of the Green Revolution in the late 1960s and 1970s, it is increasingly apparent that large-scale farmers now reap the most benefits from input subsidies, and public procurement.17 Subsidies also command important shares of government budgets,

BOx 3.2 Agricultural Produce Markets Act (APMA)

The Agricultural Produce Markets Act regulates the buying and selling of agricultural products in India’s states . Through the act, or local versions of it, states have established more than 7,000 wholesale markets (also known as mandi or APMC markets), and regulate all aspects of marketing, including the levy of a user fee, or cess .

The acts make mandis mandatory for the trading of agricultural produce . A limited number of licenses issued to traders and commission agents restrict the choice of sellers and buyers . This stifles competition, and generates economic rents for license holders . It also leads to under-investment in physical infrastruc-ture and, ultimately, lowers prices received by farmers and increases prices paid by consumers .

Recognizing the “malfunctioning of regulated mar-kets” and the “need for more transparency and ac-countability in the functioning of these markets”,a the government of India (GoI) proposed that states adopt reforms along the lines of a model state APMA . The model act provides for, among others, establishment of private markets, direct purchase centers, consumer

and farmers markets for direct sale, contract farming, electronic trading, and promotion of public-private partnerships in the management and development of agricultural markets in the country . Twenty-five states and union territories have amended their APMAs or made various provisions for the purpose .b

India has twenty-eight states and seven union ter-ritories, and progress in modifying their legislation has been slow; as the GoI noted last year, “the manner of implementation in most states reveals serious weak-nesses which discourage the entrance of new play-ers” . While some direct marketing options have been allowed in selected states, often with significant posi-tive impacts on farmers and consumers, restrictive clauses remain in most areas—either in the modified act or new rules, such as restricting private markets to a specified distance from existing regulated markets, registration requirements for contract farming, and variable or short lengths of time in permitting for direct purchase from farmers, all of which deter investments in storage and logistics .

a GoI, 2007: “Report of the Steering Committee of Agriculture and Allied Sectors for the Formulation of the Eleventh Five Year Plan 2007–2012 .b GoI 2010: “Mid-Term Appraisal for Eleventh Five Year Plan 2007–2012”, Planning Commission, New Delhi .

though investments in agricultural research, educa-tion, and rural roads are more effective public spending tools for promoting agricultural growth and reducing poverty.18 Public investment in agriculture is crowded out by food and input subsidies.19

Input subsidies have the detrimental side effects of “too much of a good thing”. Fertilizer subsidies lead to a skewed application of different types of fertil-izer and nutrient deficiencies in the most intensively farmed areas.20 Water subsidies (through lower prices of diesel and free electricity for irrigation pumps) have led to widespread overuse of underground aquifers and increased salinity of soils. In fact, a water crisis may be looming in a number of districts in India and Pakistan, which have seen a rapid decline in groundwater levels Figure 3.4).21 Water access exacerbates inequities, while under-pricing of canal irrigation water leads to chronic


funding problems for operations and maintenance.22 Free or heavily subsidized electricity for irrigation also plays havoc with the finances of electricity utilities, which have become a major fiscal burden. Among the states with the worst overexploitation of groundwater in India are two, Punjab and haryana, from which the FCI procures most farms’ output.

The access to water and water-use efficiency are some of the most pressing challenges Pakistani agri-culture is facing. Some studies show an intricate, well entrenched system of “facilitation payments” made by farmers to increase access to canal irrigation water in the absence of official water pricing.23 The Indus Basin irrigation system in Pakistan is the largest integrated irrigation system in the world. It covers 13.5 million ha of cultivable land, of which nearly 9 million ha can be irrigated throughout the year. Waterlogging and soil salinity have become the major problems impeding agricultural growth and development. Agricultural productivity declines unless adequate drainage and salt export facilities are available, which have high energy and capital requirements, or water use efficiency is increased significantly to reduce negative impacts on the environment.24

efforts led by NGos for Poverty Reduction through Irrigation and Smallholder Markets (PRISM) combine small-plot irrigation technology and integrated service provision (ISP) to enhance small farmers’ ability to

participate effectively in markets for high-value agricul-tural commodities. Data from field projects in Nepal and India suggest that the PRISM approach can lead to significant additional income for small farmers and other micro and small enterprises in agricultural value chains.25

FIGuRE 3.4 India: Groundwater use Over Net Availability(in percent)

0

Punj

ab

20

40

60

80

100

120

140

Othe

r Sta

tes

Jam

mu

& K

ashm

irOr

issa

Chha

ttisg

arh

Jhar

khan

dAs

sam

Biha

rW

est B

enga

lAn

dhra

Pra

desh

Kera

laM

ahar

asht

raM

adhy

a Pr

ades

hAl

l Ind

iaUt

tara

khan

dUt

tar P

rade

shKa

rnat

aka

Guja

rat

Tam

il N

adu

Hary

ana

Raja

stha

n

Source: CentralGround Water Board, cited in: Shankar, Kulkarni, and Krishnan (2011).


BOx 3.3 From the Arabian Nights – A Cautionary Tale from History

Irrigation has been the key to agricultural production in Mesopotamia (parts of present day Iraq and Iran) for 6,000 years . The region has low rainfall and is supplied with surface water by two major rivers, the Tigris and the Euphrates .

The main challenges to irrigated agriculture in ancient Mesopotamia have always included:

• Silting of canals – silt built up quickly in the canal beds, threatening to block them;

• Soil salinity – evidence points to significant events in about 2000 BC, 1100 BC, and after 1200 AD;

• Water politics – Tensions often arose between up-stream and downstream users . For instance, long ago in Sumeria, the people of Lagash felt disadvan-taged because their city was far downstream in the Euphrates canal system . So they cut a canal to tap Tigris water rather than rely solely on the Euphra-tes . But after doing so they were dismayed to find the Tigris water brackish, which rapidly salinized the soil and destroyed their farming culture .

• Over-exploitation of resources – After a wave of Moslem expansion overtook Mesopotamia, the

Abassid Caliphate rose up to rule Baghdad for 500 years, from 762 AD . It renovated and greatly extended existing irrigation schemes in huge projects . This elaborate system provided the basis for the enormously rich culture of Baghdad, which is still remembered in legends such as those of Scheherezade, the Caliph of Baghdad, and the Arabian Nights .

• Institutional failure – When the Abbasid economy began to fail in the 12th century (mostly from overspending), the canals became silt-choked, the irrigation system deteriorated, and the lands be-came more salinized . The deathblow was an act of nature: massive floods in about 1200 AD changed the courses of the Tigris and Euphrates, cutting off most of the water supply to the Nahrwan Canal . The government was too weak (or bankrupt) by then to institute repairs, and the agricultural system collapsed . By the time the Mongols conquered the region in 1258 AD, they occupied what was effectively a wasteland . Iraq has remained mostly a desert ever since .

Source: Khan et al . (2004) .


BOx 3.4 Gujarat’s Agricultural Success

India’s western state of Gujarat is an outstanding per-former in agriculture—agricultural output has grown by almost 10 percent per year over the last decade, more than three times the all-India figure . Research by the International Food Policy Research Institute (IFPRI) points to three main sources of rapid growth in Gujarat’s agriculture: (1) cotton output growth (from 3 .05 million bales in fiscal 2003 to 11 .2 million bales in fiscal 2008, driven primarily by Bt, or insecticidal, cotton since 2002); (2) output from the high value segment (i .e ., livestock, fruits and vegetables); and (3) wheat, which grew at an average of 28 percent annu-ally between fiscal 2001 and 2008, when production jumped from 0 .6 million tons to 3 .8 million tons .

Four areas of reform have contributed to Gujarat’s agricultural success:

Technology development and diffusion. While the public sector has played a role in production and dis-tribution of high-yielding variety seeds such as wheat, the private seed sector has taken a lead in developing and promoting the use of Bt cotton seeds . In Gujarat alone, 26 private seed companies have registered 113 varieties of Bt cotton . Not only has the yield more than doubled in five to six years, more than 50 percent of the total cotton area in Gujarat is now under Bt cotton .

A holistic approach to electricity and water use. Gujarat is a drought-prone state, with irrigation cover of just 36 percent of gross cropped area . Better water management includes concerted efforts to recharge the water table, regulate electricity for agricultural use (by separating feeder lines for irrigation and other uses) and providing subsidies to farmers who use water-saving technologies, such as drip irrigation .

Programs include:

• Sujalam Safalam (Water Harvesting) Scheme – Aims to improve surface water supply and recharge the water table through construction of check-dams and deepening of existing tanks

so that farmers will use surface water instead of pumping from wells, which uses more energy .

• Drip Irrigation Scheme – This ambitious irrigation scheme aims to conserve energy by assigning 80,000 ha of land (with 50 percent grants) to farm-ers on condition they use drip irrigation . It is ex-pected to cut the agricultural sector’s dependence on electric power .

• Jyotigram Yojana for rural electrification – This scheme provides agricultural consumers with con-tinuous power from dedicated agricultural feeders for eight hours each day at preannounced hours .

• Mass awareness drive for energy conservation – This extensive public education program employs various agencies to lead energy-conservation workshops, seminars, exhibitions and live demon-strations . Energy audits of industries and the use of capacitors are promoted .

Legislative reform. Gujarat was one of the first states to amend the laws governing the marketing of agricultural produce and allow farmers to sell their output directly to private buyers rather than official procurement outlets. In fiscal 2005, Gujarat allowed companies to buy crops from farmers one year in advance, reducing their market risks by allowing them to hedge against price fluctuation . The hedging guar-anteed a minimum price and allowed some flexibility to account higher prices at the time of a transaction . It also has encouraged contract farming by attracting private companies—for example, ITC and Pepsi—to enter into contracts with farmers .

Technological advancement. Rejuvenation of the agricultural research systems and introduction of innovative extension services made research and know-how available directly to farmers on their farms . Under the “Krushi Mahotsav” program, agricultural scientists, elected representatives, and farmers spend a month, during April/May, touring rural areas demon-strating the best technologies for soil health, organic farming, farming inputs, irrigation, etc .

Source: Gulati and Shreedhar (2009) .


Notes1. Ganesh-Kumar et al. (2010).2. Fang, hazell and haque (2000).3. See Deaton and Dreze (2009) on the long-term decline

in availability of food in India.4. Bhutan has a bilateral agreement with India for the

duty-free import of food articles. Food markets are influ-enced by the Food Corporation of Bhutan (FCB), which manages the acquisition, management and disposal of a small public reserve of rice, wheat, vegetable oil and sugar, and purchases of selected food commodities from India and subsequent selling at controlled prices in district-level retail shops. The FCB’s strategic food stocks consist of: rice (1,400 tons), wheat (180 tons), vegetable oil (58 tons) and sugar (200 tons).

5. Purchases are made in bulk only, which excludes marginal and small farmers from the price guarantee offered by FCI.

6. Procurement by the FCI absorbed 57 million tons and 55 million tons of mainly rice and wheat in fiscal 2009 and 2010. Procurement of other crops is limited and may not influence prices as much.

7. This is true to the extent that farmers are able to decide whether to sell to the FCI or private traders, a choice which is not always available because of crowding out of the private sector.

8. Basu (2010). See also World Bank (2004). A high proportion of the grains are stored by building pyra-mids of sacks of grain on cement platforms and covering them with polyester tarpaulins. The system leads to high losses from pests and moisture, and does not allow adequate “first in, first out” rotation, which results in ageing of stocks.

9. World Bank (2004).10. Ibid.11. Ganesh-Kumar et al. (2007).12. World Bank (2004).13. Chakraborty (2009).14. Ministry of Finance of the Government of India (2011).15. Basu (2010).16. Fan, hazell and haque (2000).17. Sharma and Thaker (2009).18. Fan, Gulati, and Thorat (2008).19. Kumar and Mittal (2006).20. World Bank (2004).21. Shankar, V., h. Kulkarni, S. Krishnan (2011).22. Kumar and Mittal (2006).23. Rinaudo (2002), Wade (1990).24. Khan et al. (2004).25. Magistro et al.(2004).


IVThe Human Impact of Food Price Inflation

The PoVeRTY AND NUTRITIoNAL impact of food price spikes on the poor is signif-icant since they spend a larger fraction of their

income on food than relatively better off individuals. The malnutrition status of poor households in South Asia—a result of poor diet, lack of access to health services, poor sanitary environment and lack of aware-ness—was already precarious before the increase in food prices. Afghanistan, for example, has the highest levels of chronic child malnutrition in world. Most countries in South Asia have double the rates of child malnutrition of many Sub-Saharan African countries. The food price increase has further exacerbated this vulnerability. Since the last food price spike in 2008, governments in South Asia have strengthened safety nets, but gaps continue to exist. The largest safety net interventions in the region—India’s and Pakistan’s public distribution systems for staple foods—are characterized by high leakages and therefore costs, while errors of exclusion are actually larger than the reverse, i.e. a large number of the deserving poor is not covered. This section presents results of a simula-tion exercise aimed at estimating the likely impact of recent food price increases on the poor. The second part discusses safety net approaches and their effects on food security, and the World Bank’s engagement with governments in the region on safety nets.

1. Impact on Poverty1

The poor experience large declines in their real incomes and poor food producers have little opportunity to respond by increasing output within a short period of time. The evidence from the 2008 food price spike suggests that in most countries poverty increases when food prices rise substantially, even in rural areas, because both rural and urban poor are typically net consumers of food.2

In 2010–11, the rise in food prices is showing across a larger range of commodities than in 2008

when it was mostly confined to traded grains, which will make it more difficult for the poor to compen-sate for price increases by shifting their purchases to cheaper calories, foods which are poorer in protein and vitamins and minerals, as was the case during the 2008 crisis. even short-lived food price hikes reduce calorie intake, compromise dietary diversity reducing access to proteins and essential micronutrient rich food and tend to have long-term consequences, especially on infants and young children.3

To understand the magnitude of the problem, we simulated the likely poverty impact of the food price increases that occurred between June and December 2010. The analysis is based on survey data for house-hold food production, sales and consumption of key agricultural commodities.4 Given the relatively fast change in food prices, the analysis assumed that price changes have not yet translated into noticeable changes in wages. In addition, we have not incorporated possible policy measures that might insulate poor net buyers of


food from the price hike. The results presented below are therefore indicative only.

The simulations suggest that the number of poor increased by 1.4 percentage points in South Asian coun-tries (Figure 4.1). In India and Nepal, the increase in the poverty headcount is less than the median while Bangladesh and Pakistan are above, with Sri Lanka at the median. For the impact on the poverty gap, in Nepal, Pakistan and Sri Lanka, the increase in the poverty gap is less than the median while the opposite is true for Bangladesh and India. except for Nepal, the net change

in the poverty headcount is greater than the impact on the poverty gap. Pakistan experiences the highest net percentage increase in the poverty headcount whereas Bangladesh experiences the highest percentage increase in the poverty gap due to the food price increase. Nepal faces the least net change in both poverty headcount and gap among the South Asian countries.

Across all the South Asian economies, the median of people exiting poverty is 0.06 percent while those entering poverty are 1.49 percent, driving 15 million South Asians into poverty. (Table 4.1). of the South

FIGuRE 4.1 Poverty Impacts of Recent Price Rises

Into poverty Out of poverty Net change Urban Rural

Change in poverty gap % Net change in poverty headcount Beef Rice Sugar Oils and fats Wheat

Change in Poverty Headcount

–0.6

–0.1

0.4Perc

enta

ge p

oint

s

0.9

1.4

1.9

2.4Ba

ngla

desh

Indi

a

Nep

al

Paki

stan

Sri L

anka

Net Change in Poverty Headcount: Rural vs Urban

0.0

0.5

1.0Perc

enta

ge p

oint

s

1.5

2.0

2.5

3.0

Bang

lade

sh

Indi

a

Nep

al

Paki

stan

Sri L

anka

Impact on Poverty Gap vs Poverty Headcount

0.0

0.5

Perc

enta

ge p

oint

s

1.0

1.5

2.0

2.5

Bang

lade

sh

Indi

a

Nep

al

Paki

stan

Sri L

anka

Estimated or Observed Price Change (June–Dec 2010)

0.0

0.5

1.0Perc

enta

ge p

oint

s

1.5

2.0

2.5

3.0

Bang

lade

sh

Indi

a

Nep

al

Paki

stan

Sri L

anka

Source: Ivanic et al. (2011).

The Human Impact of Food Price Inflation 31

Asian countries, while Bangladesh has the largest percentage change of individuals exiting poverty with the food price hike, it also has the greatest percentage of individuals moving below the poverty line. In Pakistan, there is no decline in poverty.

2. Mitigating the ImpactAs shown in the previous section, the current food price shock is likely to increase the poverty headcount and the poverty gap in the region. Given that poverty is still a pressing problem in South Asia, governments are called upon to scale up and improve targeting of existing social protection programs, and where such programs are weak and nonexistent, to implement safety nets to mitigate the impact on the large number of poor. If food is distributed as part of a safety net response, it should be fortified with essential micronutrients to ensure its high nutritive value safety nets can have a greater impact upon protecting and improving nutritional status, through provision of more nutritious foods when food is distributed (e.g. foods fortified with essential vitamins

and minerals) and by increasing beneficiary knowledge on how to maximize limited household resources for nutritional impact (e.g. adequate intra-household allo-cation of food to women and children).

Social Protection in South Asia since the last food crisis

Numerous social protection schemes currently exist in South Asia, including subsidies on food and energy, cash transfers, social pensions, social assistance, food transfers, workfare, stipends, and social care services. The largest South Asian countries have large systems for the distribution of subsidized food, while cash transfer programs are very small-scale, often short-term, and lacking robust systems for administration and delivery of program benefits and services. This has been changing in recent years, with growing investment in well targeted and administered safety net programs (SNPs) in the region. India, for example, has recently introduced a health insurance program for the poor (RSBY), which features a cashless and paper less system, with strong private partnerships and a robust monitoring and eval-uation system. Pakistan has also recently initiated a national cash based safety net program (BISP), which relies on a modern targeting, administration and delivery system. As the development of safety net systems takes time, the current preparedness for a food price shock with respect to coverage of the poor, and the targeting and quality of administrative systems varies markedly across South Asian countries (Table 4.2).

The 2008 food crisis provides important lessons regarding the effectiveness of different safety net programs (see Box 4.1). At the time of the previous crisis, it became clear that emergency response

TABLE 4.2 Safety Net Readiness Assessment in South Asia

Assessment Criteria Countries

Crisis Ready Have one or more programs with high coverage of poor, highly progressive targeting and good administration

None

Moderate Base Have one or more operating and progressively targeted programs to build on, but with less than full coverage and/or a need for administrative improvements

Bangladesh, Pakistan,India

Weak Base A large scale response would require fundamental changes to range, size, or targeting of programs and significant building of institutional capacity

Sri Lanka, Nepal, Maldives

Unprepared Very small programs with little institutional development, often geared only to specific sub-groups of the population

Afghanistan, Bhutan

Source: Authors.

TABLE 4.1 Changes in Poverty Headcount(‘000)

Out In Total

Bangladesh –736 .02 3115 .43 2379 .41

India –4944 .82 14168 .88 9224 .06

Nepal –18 .32 61 .07 42 .75

Pakistan 0 .00 3301 .84 3301 .84

Sri Lanka –10 .05 304 .64 294 .59



BOx 4.1 Recommendations for Safety-Net Policy Responses

Policy responses should be designed according to country context and need to be administered effec-tively and efficiently to reach the target group . A loose ranking of programs for the short-run response could look as follows .

Direct Transfers• Targeted cash transfers of adequate coverage,

generosity, and quality is the best option . Programs that also provide quality consumer education will lead to better decisions on how the cash is used (e .g . to purchase nutritious food, to improve intra-household distribution of the food) .

• Where Conditional Cash Transfer (CCT) programs already exist, increasing their benefit or coverage may be a key part of the response . However, es-tablishing new CCTs may take too long and exclude the neediest or those suffering from acute but transitory income shocks .

• Other good options would include raising benefits across a large spectrum of social transfers, such as social pensions, survivorship pensions, disability pensions, and unemployment benefits, where they cover the poor . Food stamps or vouchers have slightly higher administrative costs than cash, but can be politically popular .

• Food distribution in-kind is appropriate where markets are functioning poorly, where foreign as-sistance is only available in-kind, or where stra-tegic grain reserves need to be rotated . In other circumstances, in-kind programs will have higher than necessary administrative costs per unit of value transferred as well as potential leakage as in Bangladesh . They also have a limit on how much support can be transferred per beneficiary . Different types of food distribution include take-home rations, school feeding programs, distribution of fortified foods, onsite feeding through health centers, and ready-to-use therapeutic foods in the home .

• Public works programs rarely achieve sufficient coverage to be the whole response to rising food prices, however, where public works programs ex-ist, increasing their benefit or coverage may help . It is also important to ensure that public works programs, which often involve heavy physical labor, be designed so as to not further compromise

the poor nutritional status of poor beneficiaries . For example, heavy labor during pregnancy may compromise the health of the pregnant woman and the development of the unborn child . Women’s participation in public works programs may also limit their ability to care for their children and thus compromise the growth and development of these children .

• Immediate across-the-board wage increases through public sector and minimum wages are not desirable . Both instruments represent a permanent increase in wages in response to a shock that may be temporary, thereby fueling inflation and fiscal expenditures over the long run . Moreover, they fail to increase wages among the poor, who are concentrated in the private, informal sectors .

Indirect transfers• Fee waivers or vouchers for health and scholar-

ships for education help households maintain access to services even if households become poorer .

• Lifeline pricing for networked utilities can be ap-propriate where the poor are connected to the net-work, have individual meters, volume differentiated tariffs are used, and the subsidized block of service is consonant with use by low-income households .

• General food price subsidies are distortive, costly, and hard to eliminate, although sometimes adroit choice of commodities can result in transfers that are nearly neutral in incidence and inclusive of the poor . They also have physical limitations (quantities of specific food items consumed) on how much income can be transferred in this way . General fuel subsidies tend to be very regressive and often not well targeted .

Further considerations:• In some, but not all, cases it will be appropriate to

scale back emergency social protection interven-tions again as food prices find their new long-term level and households and wages adjust to it . How-ever, where safety nets were grossly inadequate it may be desirable to keep them at scale .

• Specific nutrition and health interventions are often needed to complement social protection programs .

Source: World Bank (2011) .


mechanisms were not well developed and that putting in place best-practice safety net programs was required. As these programs would take time to be crisis ready, second-best options were therefore needed to respond to the immediate crisis needs. Improving coordination among related (small scale) programs enhances their ability for effective service delivery. Consolidation of various duplicative safety net interventions under one government authority, where politically feasible, is important for enabling efficient and timely responses to future crises.

Country Stories5

Afghanistan is the least prepared country in South Asia because it currently has no scalable, targeted SNP. existing interventions in Afghanistan remain small in terms of coverage and funding. The majority of the poor and vulnerable are not assisted directly through any government-sponsored programs. Food aid is the core safety net, delivered via small and scattered inter-ventions including a mix of school feeding, food for work, and emergency feeding.

over the course of 2010, the Ministry of Labor and Social Affairs, the line ministry responsible for social protection has been working intensively on preparations for an IDA-funded unconditional cash transfer (UCT) pilot, in close cooperation with other ministries and non-governmental bodies. It is antic-ipated that by early summer 2011, evaluation of the pilot would be completed and the scale-up of activi-ties would be considered. The new program, if eval-uated as a success, could become an intervention to respond to various shocks including increased food prices. A pilot community and geographic targeting approach is being put in place in response to the rising food prices. The World Bank supports this effort with US$2.5 million.

The capacity to respond to the food crisis by the government of Bangladesh is spread among several programs in operation for at least five years, each progressively targeted but with coverage of less than ten percent of the poorest quintile and concentrated in rural areas. The key programs used to respond to the food crisis are fairly well targeted to the poor. The main program providing coarse rice in rationed quantities in open markets (oMS) is a self-targeted program for the poor as the non-poor have few incen-tives to stand in long lines for small quantities of infe-rior quality rice. Thus oMS is self-targeting because it

provides low-quality rice, which is not of interest for better-off consumers. Rice is sold at a subsidized price of 25 taka per kilogram for up to 5 kg per household using licensed dealers, which are allowed a commission of 1.5 taka per kilogram. The government increased the number of oMS dealers in Dhaka and coverage has been extended nationwide involving about 3,000 dealers. During the first eight months of fiscal 2011, 396,000 tons of rice was distributed through oMS, representing 72 percent of the annual target.6

The second scheme employs Fair Price Cards targeted at the most vulnerable as identified by commit-tees composed of government officials, people’s represen-tatives and school teachers. The government has so far distributed 69,600 tons of rice through Fair Price Cards in FY2010–11, and plans to increase the number of these cards to 2.23 million to cover the ultra-poor house-holds, village defense police, and third- and fourth-class employees of public and private organizations. In addition to these main schemes, the government also allocates rice under Vulnerable Group Feeding (village level help in periods of distress), Vulnerable Group Development (food and training for women), Test Relief (food for worker as disaster response), Gratuitous Relief (food grants disaster relief ), and Food for Work (rural infrastructure projects for women).

The Vulnerable Group Feeding (VGF) program is targeted at the more geographically food-insecure parts of Bangladesh using a food-vulnerability map devel-oped by World Food Program (WFP). Within these districts, various targeting criteria are used to identify the extreme poor—around 60 percent of VGF benefi-ciaries are from the bottom 40 percent of the popula-tion. The recently established employment Generation Program has been recently assessed as well targeted and generally effective. It could potentially be used as an additional mechanism of response and its ongoing presence already assists more than half a million poor households every year.

Current programs spend over 2.8 percent of GDP and reach 4–5 million beneficiaries (15 percent in rural and 5 percent in urban areas). Programs provide in-kind transfers, cash, or a combination of the two which could be scaled up to respond to a crisis.

The government has started a significant process to enhance decentralized service delivery and social accountability. Bangladesh is also aligning itself to promote a more efficient response during a crisis, in particular through the strengthening of results-based monitoring and evaluation (M&e).


In India, a plethora of SNPs exist, including for the provision of subsidized food, various other in-kind transfers (e.g., school feeding), public works, and other cash transfers such as social pensions for the elderly, widows, and disabled; housing; scholarships, and as noted above has a fairly recently-introduced social insurance (RSBY, a subsidized health insurance) and subsidized rural credit. Centrally-sponsored schemes and state-level programs exist side by side. Most of these programs still do not fortify the food which is distributed, despite this being a low cost and techni-cally feasible approach which would yield significant nutritional benefits to poor households.

The largest program provides subsidized food through the Public Distribution System (PDS). Inefficiencies in the procurement and storage of food by the FCI were discussed in Chapter II. In addition,

sales through the PDS are fraught with high leakages, on the one hand because of failures to identify the poor—both failures of inclusion of non-poor house-holds and exclusion of poor households who really should have had access—and on the other hand by diversion of subsidized stocks to the open market. one recent study shows that 44 percent of persons who should have had access were excluded.7 Another study shows that a large share of relatively better-off households buy grains from the PDS, while only 30 percent of households in the lowest expenditure quin-tile buy from the PDS.8

Data on food provisions to and purchases from PDS stores shows large differences between states (Table 4.3). Some states suffer from large-scale diversion of food meant for distribution to the poor, while others have plugged leaks quite successfully. A comparison of data

TABLE 4.3 India: Household Consumption vs. Grain Delivieries to the PDS, 2007Consumption from PDS

as per HH survey Grain deliveries to the PDS Consumption/Deliveries

Rice Wheat Total Rice Wheat Total Rice Wheat Total

(in thousands tons) (in percent)

Bihar 80 100 170 970 660 1,630 7 .9 14 .7 10 .7

Jharkhand 100 50 150 540 290 830 18 .5 16 .0 17 .6

West Bengal 350 210 560 1,030 1,500 2,530 34 .3 13 .8 22 .1

Assam 330 10 330 1,130 260 1,400 28 .7 2 .8 23 .9

Gujarat 120 220 340 450 440 880 27 .5 49 .5 38 .4

Rajasthan 40 470 510 160 990 1,140 25 .0 47 .7 44 .6

Uttar Pradesh 1,220 800 2,020 2,580 1,640 4,220 47 .2 49 .1 47 .9

Haryana 20 140 160 60 260 320 35 .6 53 .2 49 .8

Orissa 860 0 860 1,460 130 1,590 58 .8 2 .7 54 .1

Karnatak 980 190 1,170 1,630 270 1,910 60 .0 69 .4 61 .4

Maharashtra 720 780 1,490 1,120 1,270 2,400 63 .7 60 .9 62 .2

Madhya Pradesh 330 810 1,140 430 1,320 1,750 75 .5 61 .5 64 .9

Andhra Pradesh 3,010 20 3,030 3,600 40 3,640 83 .6 46 .8 83 .2

Kerala 840 120 960 860 290 1,150 97 .1 43 .2 83 .6

Himachal Praddesh 200 190 400 230 220 460 86 .9 86 .3 86 .6

Tamil Nadu 3,260 120 3,380 3,620 90 3,710 90 .1 133 .3 91 .1

Punjab 0 150 150 10 150 160 18 .4 98 .8 94 .8

Chhattisgarh 790 10 800 750 30 780 106 .3 28 .0 103 .0

All-India 14,290 4,640 18,930 22,290 10,830 33,120 64 .1 42 .8 57 .2

Source: Himanshu and Sen (2011).


on quantities of grains released to “fair price stores” on one hand, and household-survey data on the purchases of such grains on the other, shows nearly two-thirds of the wheat and 40 percent of the rice that is meant to go to poor households ends up in the open market. In Bihar and Jarkhand, for example, only 11 percent and 18 percent of the grain delivered to the PDS is accounted for in the 2007–08 round of the household survey.9 on the side of the spectrum are Chhattisgarh, Punjab, and Tamil Nadu, where nearly 100 percent of food delivered to the PDS is purchased through offi-cial channels.

The Government of India announced pilot programs for transforming subsidies on LPG and kerosene into direct cash transfers in the FY2011–12 Budget. While the modalities still have to be worked out, it is hoped that targeting can be improved and fiscal savings therefore realized. A successful implemen-tation of these pilot programs would open the door for broader move away from subsidies toward cash transfers, although there is a vigorous debate in India about whether cash transfers can be a viable alterna-tive to food subsidies.

As in India, the government of Pakistan maintains a large system to provide subsidized wheat and a few other goods to poor households. PASSCo and PFDs release wheat to flour mills at predetermined, uniform prices across the country. The release prices are gener-ally below the open market prices and give the govern-ment a handle on wholesale wheat prices, although the wheat subsidy mainly benefits flour mills, which use wheat from public stores for some of their processing and buy additional wheat in the open market, while they sell their entire output at higher prices to shops. Wheat and other commodities are also sold at subsi-dized prices directly to urban consumers by the Utility Store Corporation (USC) at prices that are 3–15 percent below market prices.

Wheat subsidy is incurred at both federal and provincial level. At the federal level, the government absorbs the cost differential between the domestic support and sales price, and extends budgetary support to the Trading Corporation of Pakistan (TCP) and PASSCo for losses incurred in their wheat trading operations. At the provincial level, wheat subsidies are incurred to meet the shortfall that occurs in the trans-action of wheat by the Provincial Food Departments (PFDs), particularly incidental charges being borne by the provinces, and direct subsidies to the consumer via various schemes (e.g., Ramzan package or Sasti Roti). To

the extent comparisons are possible, the costs incurred by PASSCo and PFDs are significantly higher than those of private traders, indicating inefficiencies in handling wheat.10

The system of government intervention is inef-ficient in the sense that producer surplus losses and budgetary costs from subsidies are significantly higher than gains for consumers. A recent partial equilibrium analysis of costs and benefits of the government’s wheat policy concluded that the millers absorb most of the benefits from government subsidies, while consumers benefit at the expense of farmers.11 Lower farm-gate prices lead to lower production of wheat, as shown by another recent study which uses a computable general equilibrium model to simulate the effects of a removal of producer taxes and consumer subsidies.12 The authors conclude that removal of the distortions in wheat prices would be welfare-improving across all household groups. Income effects would dominate price effects; i.e., income from increases in factor prices would outweigh welfare losses from higher prices of wheat. higher prices of wheat from a removal of subsi-dies would be mitigated by increasing production.

To provide a more direct safety net support, and eventually phase out untargeted subsidies, Pakistan has initiated a new cash transfer program, the Benazir Income Support Program (BISP), to protect vulner-able households against chronic poverty and adverse economic or agro-climatic shocks. over the last two years, targeting, administrative and technical capacity has been strengthened considerably. By early July, beneficiaries will be determined on the basis of a new transparent targeting system. The introduction of this national safety net has led Pakistan to more than double its SSN spending-to-GDP ratio from 0.4 percent to nearly 1 percent. The volatile security situation still presents a challenge for program implementation in parts of Pakistan.

Sri Lanka has the large-scale Samurdhi program. It was conceived to alleviate poverty and create oppor-tunities for the youth, women, and the disadvan-taged. The bulk of program resources are distributed as consumption grants to households, with eligibility determined by a community based targeting system. Consumption grants are provided in the form of food stamps, which account for 80 percent of the program’s budget. Samurdhi also provides basic banking services, insurance, and food-for-work schemes. Food stamps can only be used in “cooperative” stores, which are a part of a de facto government owned distribution network.


The program also employs a large number of village level community workers, the niyamakas.

The Samurdhi program shares the targeting diffi-culties of the Indian PDS: Samurdhi misses almost 40 percent of households ranked in the lowest expen-diture quintile, while a substantial number of house-holds with higher relative welfare receive Samurdhi consumption grants and other forms of Samurdhi assistance. Around 44 percent of the total Samurdhi transfer budget is spent on households from the third, fourth, and fifth quintiles—those who are well-off in relative terms.13 The Government is currently investing in a modern administration and targeting system for the Samurdhi program to improve its ability to read the poor.

In the Maldives, the government provides small cash transfers, alongside energy subsidies meant to assist poor households. To phase out untargeted subsidies and ensure transfers reach the poor, the Government is developing a national targeting system to better direct cash transfers and subsidies to the poorest households in the country.

In Nepal, according to a recent survey of 1,680 rural households, two thirds of the poor faced shocks in the last year, and a majority of these were drought and weather related. Coping mechanisms are still largely informal with only 5 percent reporting government or NGo support as a coping strategy. however, that said, quarter of all surveyed households participate in at least one safety net program.

Compared to other South Asian countries, Nepal has seen the sharpest increase in social protection spending over the last three years. Spending on social protection (including civil service pensions, social assistance, and unconditional cash transfers) went up to 2 percent of GDP in 2010/11, from 0.5 percent of GDP in 2004/05. The expansion is primarily due to increases in the target population, such as lowering the age criteria for the old age allowance, and the individual benefits for the unconditional cash transfer programs, as well as the introduction of new programs. Benefit levels in existing programs, including the old age and single women’s allowances, have been raised to keep pace with inflationary pressures. The cash transfer programs through Ministry of Local Development alone reach almost 1 million beneficiaries. A recent Bank study finds that given that categorical nature of the programs, the social pension programs reach all income groups, but that limited resources and weak administration systems mean that the programs does not reach all

eligible beneficiaries. That said, individuals that the program does reach register a high level of beneficiary satisfaction with program delivery. Cognizant of these issues, the Government is investing in improving the financing, governance and administration of its main cash transfer program.

3. Bank Support to Safety Net Programs in South Asia

The Bank has been engaged on safety net issues in South Asia (with the exception of Bhutan). The partic-ular focus of our engagement is to improve the design and administration of safety net systems (including their coherence and coordination) so that countries are better able to both address chronic poverty and help households cope with economic or agro-climactic crisis. The Bank has been active for several years in this area and our assistance involves not just diagnostics on program effectiveness but also both analytic and advi-sory services as well as financial support to improve program design and implementation The specific nature of our engagement is detailed below.

The World Bank has helped Bangladesh by modi-fying and supporting the 100-day employment guar-antee program with a $150 million loan. With the revised design, which includes improvements in for example program registry, MIS and the payment system, the program should be more responsive during any future crisis. With World Bank grant support, the Government is also in the process of designing a cash transfer program conditional on beneficiary households utilizing nutrition services for their children under the age of two, and for continued attendance at schools by their children. The pilot will also include a base uncon-ditional amount to act as a safety net.

In the Maldives, the Bank supported the design and implementation of social pensions for those older than 65 through the Bank’s pensions and social protec-tion project. The Bank is also providing technical assis-tance through this project to support the development of a national targeting system.

The modernization of administration and delivery of the government of Nepal’s safety net program, both workfare and social pension program, is being strengthened through the Bank’s Social Safety Net Project. A conditional cash transfer is also being piloted and evaluated to assess how safety nets can support improvements in human capital of the poorest


and most vulnerable groups (and protect this against income shocks).

In Afghanistan, the Bank is supporting the devel-opment of safety nets through the Afghanistan Pensions and Social Safety Net project. A pilot program is being designed and evaluated for potential scale up nationwide.

The Bank is supporting the development of a modern safety net through the BISP program in Pakistan. As the development of the national system will take time, the bank has also financed short term emergency support for militancy affected families through the KP/FATA project and emergency cash support to families affected by the recent flood through the Flood emergency Cash transfer project. The Bank is also supporting the Government transform its uncon-ditional cash transfer program to a conditional cash transfer program to support human capital develop-ment of the poorest populations, including avoiding adverse impact on health and education of the poor during crisis.

The Bank is also supporting the Government of Sri Lanka’s Samurdhi program through IDF and other financing to improve its targeting and administration.

Given the lessons learnt from the crises, going forward the Bank will focus on these priority areas:

• Developing real time monitoring instruments to understand the level of risk and response read-iness of client countries;

• Developing and strengthening safety net systems, including establishing modern targeting, gover-nance and administrative structures to ensure effective delivery to target groups;

• Linking safety net programs to participation of the poor in health/nutrition and education programs and employment schemes to (i) reduce the impact of crisis or chronic poverty on human capital formation and (ii) to reduce benefit dependency and promote economic integration

• Promoting an integrated response of actions, combining diverse safety net instruments, along with other sectoral interventions in nutrition and agricultural investment;

• Making financing and technical expertise avail-able in a timely manner, yet ensuring consis-tency of short term response with longer term investment in safety nets; and

• Working to enhance the evidence base of how impacts are manifest and what works in times of crises.

Notes1. See Annex 4 for more details. This section and the

annex are based on Ivanic, Martin and Zaman (2011), Estimating the Short-Run Poverty Impacts of the 2010–11 Surge in Food Prices, World Bank Policy Research Working Paper 5633.

2. See Ivanic & Martin (2008), Dessus, herrera, & de hoyos (2008) and Wodon & Zaman (2010) for further discussion.

3. See Skoufias, Tiwari and Zaman (2011), Alderman, hoogeveen and Rossi, (2006), Mghenyi (2009), D’Souza and Jolliffe (2010), and Ahmed and Jansen (2010).

4. Where available, we used country-level data on actual changes in domestic food prices from Food Price Watch (World Bank, 2011). For other commodities, where prices are unavailable, import shares reported in Version 7 of the GTAP database to link global prices with domestic consumer prices is used (see hertel, 1997). In the case of Afghanistan, we were unable to estimate the impact of price changes on each household’s real income because an estimate of the quantity of goods produced by each household is unavailable. Instead we estimated the net change in food consumption from the increase in price, as observed through household consumption data.

5. See also Annex 5 for a table on food crisis response safety nets in South Asian countries.

6. To improve the quality of the diet of households who benefit from the schemes, this rice could be readily fortified with essential vitamins and minerals.

7. Khera (2010).8. himanshu and Sen (2011).9. Ibid.10. Slam (2003).11. Ahmad et al. (2010).12. Ibid.13. Glinskaya, e. (2003).


Policy Options

WITh FooD BeING SUCh A LARGe component of consumption basket and even without formal wage indexation, food infla-

tion—whether their origin is from supply shocks or from excess demand—can get passed through to overall inflation. Unlike advanced countries, where the received wisdom is to “look through” these increases, this may not be the best strategy in South Asia, and this means that demand management policies need to be deployed earlier than in advanced countries. In the case of South Asia, many central banks have begun the process of normalizing monetary policy with interest rate hikes, but in many of them, ex-post real rates are still negative suggesting room for further tightening. Some tightening of monetary conditions has been achieved by appreciating real exchange rates. In nearly all countries in the region, the process of normal-ization of fiscal policy is not complete and in many cases, fiscal balances have deteriorated. Fiscal consol-idation is therefore a priority in many countries both for demand management and to rebuild fiscal space to cope with future shocks.

Foodgrain stock management. Important in the whole region, but especially in India given the current situ-ation of high prices coexisting with excessive stocks, and potentially a new more extensive “right to food” based entitlement. A study is underway by CACP covering optimal level of stocks, efficient manage-ment of food grains, and the role of the private sector in procurement and distribution. More could be done to expand the fortification of stocks with essential vita-mins and minerals.

Increasing agricultural output and productivity. Considerable work exists on the necessary policies. For example, the Government of India recognizes the need for a comprehensive strategy with a focus on technology, improved water management, rural infra-structure, agricultural diversification, food security, and private sector investment in marketing and agro industry. The success of Gujarat offers salutary exam-ples of how such a comprehensive approach could work.

Safety nets. Increasing the role of the private sector in food grain marketing in India and Pakistan requires delinking of safety nets from direct public procure-ment of wheat and rice from farmers. This does not necessarily entail an end to the distribution of subsi-dized food from public stores as shown by the exam-ples of Sri Lanka and Bangladesh. Also, countries could better protect and improve nutritional status through provision of more nutritious foods (e.g. foods fortified with essential vitamins and minerals) and by increasing beneficiary knowledge on how to maximize household resources for nutritional impact (e.g. adequate intra-household allocation of food to women and children).

Managing Risks. over the last few years, volatility in exchange rates, interest rates, and commodity prices

V


has reached peaks similar to those seen during the financial crisis, a trend which seems unlikely to ease given uncertain political and economic conditions. Increased market volatility has generated renewed

interest among borrowers in market-based tools and assistance for managing risks, particularly those that affect the government’s budget. (See Annex 6)


Country Pages: Eight countries – Eight Graphic Economic Narratives


Afghanistan

Private consumption is the motor of growth fromdonor in�ows and the security economy... FIGURE C Contribution to Real GDP Growth, Expenditure

–20%–10%

0%10%20%30%40%50%60%

0

5

10

15

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25

Strong, but volatile real GDP growth...FIGURE A GDP Growth

... driven by the services sector and �uctuating agriculture ouput. FIGURE B Contribution to Real GDP Growth, Production

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10

Source: CSO.

… the current account de�cit has shrunk...FIGURE E Balance of Payments

Source: DAB.

0%

20%

40%

60%

80%

100%

2005/06 2006/07 2007/08

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Source: CSO, IMF and WB calculations. Source: DAB, IMF.

1.9

Investment (Gross Dom. Fixed) Real GDP GrowthPvt Consumption Net Exports Govt. Consumption

Exports Imports

2004/05 2005/06

f.o.b

in %

of G

DP

in %

of G

DP

… but trade is declining, FIGURE D Trade in Percent of GDP

2006/07 2007/08 2008/09 2010/11*2009/10

Source: CSO, IMF and WB calculations.

Construction Industry-others GDP Agriculture Services ManufacturingMining

2004/05 2005/06 2006/07 2007/08 2008/09 2010/11*2009/10

2010/11*2009/102008/09

–80%–70%–60%–50%–40%–30%–20%–10%

0%10%

2005/06 2006/07 2007/08 2008/09 2009/10 2010/11*

…and the afghani continues to appreciate.FIGURE F Nominal Exchange Rates, to Afs(Index Mar,22, 2009=100)

Source: DAB.

707580859095

100 DollorEuro

Pakistani Rupee

105110115

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Capital & Financial Account

Country Pages: Eight Countries – Eight Graphic Economic Narratives 43

BangladeshReal GDP growth is projected to rise on the back ofstrong domestic demand, private investment, and exports...FIGURE A GDP Growth (%)

…while in�ationary pressures have worsened, drivenlargely by a double-digit rise in food prices...FIGURE B Inflation(%) Y-o-Y

Source: Bangladesh Bureau of Statistics & WB Staff Estimate.

…narrowing the external current account surplus andpushing down reserves…FIGURE E Current Account Balance andForeign Exchange Reserves

Source: Bangladesh Bank and WB Staff Calculation.

05

1015202530

Source: Bangladesh Bank. Source: Bangladesh Bank.

…with exports and imports rising in the �rst part of theyear, in contrast to the sharp fall in remittance whichhas since recovered slightly...FIGURE D Cumulative Growth (%) inRemittance and Imports

Source: Bangladesh Bureau of Statistics.

Jul-0

6Oc

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...leaving �scal space to deal with stresses likely to emergefrom high food and fuel prices.FIGURE F Revenue and Annual DevelopmentProgram

Source: Ministry of Finance and IMED.

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General Food

Private Sector Credit M2

CAB (US$ Million, left axis) Reserves (in months of import, right axis)

–25–15

–55

15253545

Import Remittances

Non-Food

Jul-0

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Mill

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0500

1000150020002500300035004000

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6.66.4

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5.7 5.8

6.2

…and growth in money and credit is expected toremain high, as in 2010… FIGURE C Money and Credit Growth (%)

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ADP implementation in first 8 months (% of Total, right axis)Revenue/GDP Ratio (left axis)

0 891011121314

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Bhutan

0

3

6

9

12

15

Real GDP has averaged more than 8 percent of GDP, butgrowth rates show high volatility…FIGURE A GDP Level and Growth

…driven by �uctuating contributions from the electricityand construction of hydropower projects…FIGURE B Contribution to GDP Growth, Production

…current account de�cits averaged about 7 percent ofGDP, but strong donor in�ows brought positive balances…FIGURE E Balance of Payment

Source: BMacroeconomic Framework Coordination Committee of Bhutan, Ministry of Finance, January2010. The 2010/11 figures are Revised Estimates.

...and �scal prudence has resulted in manageable �scalbalances in recent years…FIGURE D Fiscal Balance

…the nominal exchange rate has �uctuated butappreciated against the dollar in recent years.FIGURE F Nominal Exchange Rate

Fiscal Balance to GDP Ratio

Current Account Overall Balance of Payments

Real GDP (Left Axis)

...grants and electricity, taxes and dividends aregovernment’s main sources of revenue… FIGURE C Government Revenue

Mill

ions

of 2

000

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Construction Electricity, Gas, and Water All Other SectorsPe

rcen

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Con

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toAn

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–20%0%

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Electricity Sector Grants Other Sources

2004

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2005

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5000100001500020000250003000035000

Fisc

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rcen

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DP

–8

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/05

2005

/06

2006

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2007

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2008

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2009

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2

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Perc

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2004

/05

2005

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per

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$

2004

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2006

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2007

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2008

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2009

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2010

/1140

42

44

46

48


IndiaA strong agricultural rebound in 2010 bolstered GDPgrowth, but industrial performance fell in Q3…FIGURE A Quarterly GDP by Sector of Production(y-o-y change, in percent)

…private demand was strong, while investment led therecovery in 2010. But recent quarters saw a strong drop-o�…FIGURE B Quarterly GDP by Sector of Use(y-o-y change, in percent)

With a strong revival in exports and slowing of imports in thesecond half of 2010/11, the current account de�cit stabilized...FIGURE E Current Account Deficit(in US$ billion)

Source: CSO, RBI, CEIC.

…and with a stable rupee-US dollar exchange rate, the in�ationdi�erential with major trading partners led to real appreciation.FIGURE D Real Exchange Rate(1993=100)

…non-food credit growth recovered, but is still lowcompared with the 2005–2007 period.FIGURE F Non-food Credit (y-o-y change, in percent)

While wholesale price in�ation moderated, core in�ationincreasingly drove overall in�ation... FIGURE C Components of Wholesale Price Inflation(y-o-y change, in percent)

Agriculture Services GDP Industry

–50–40–30–20–10

01020

07–0

8 Q1

07–0

8 Q2

07–0

8 Q3

07–0

8 Q4

08–0

9 Q1

08–0

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09–1

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10–1

1 Q1

–4%–2%

0%2%4%6%8%

10%12%14%16%

10–1

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10–1

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TotalConsumption

Investment PrivateConsumption

GovernmentConsumption

07–0

8 Q1

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0 Q2

09–1

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0%

10–1

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10–1

1 Q3

–20%–10%

10%20%30%40%50%60%70%

05–0

6 Q1

05–0

6 Q2

05–0

6 Q3

05–0

6 Q4

06–0

7 Q1

06–0

7 Q2

06–0

7 Q3

06–0

7 Q4

02468

1012

Dec-

09

Jan-

10

Feb-

10

Mar

-10

Apr-1

0

May

-10

Jun-

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Jul-1

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Aug-

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Core Food Energy

80859095

100105110

Jan-

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May

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Sep-

06

Jan-

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May

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Sep-

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May

-08

Sep-

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Jan-

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May

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Sep-

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May

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Sep-

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1982

–83

1984

–85

1986

–87

1988

–89

1990

–91

1992

–93

1994

–95

1996

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1998

–99

2000

–01

2002

–03

2004

–05

2006

–07

2008

–09

2010

–11 0

510152025303540

Dec-

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ay-0

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Mar

-03

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r-05

Sep-

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b-06

Jul-0

6De

c-06

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-07

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7M

ar-0

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Nepal

Jan-

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8Ju

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Mar

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2010 2011First sixmonths

Growth accelerated to about 5 percent, post-con�ict, withconsumption the main driver and investment and exportsplaying lesser roles…FIGURE A Real GDP growth decomposition byexpenditure (in percent)

…leaving high food and imported in�ation to drive the CPIinto double digits, though non-food in�ation has beencontained…FIGURE B CPI Nepal and India(y/y change)

Rapid private sector credit expansion fueled a real estate boom, now busting on a liquidity crunch, lower M2 growth and central bank interventions...FIGURE E Private credit growth and interbankinterest rates (in percent)

…but accommodative monetary policy and high remittanceallowed consumption-fueled imports and high trade de�cits.Slowing remittance brought reserve losses, lower M2 growth.FIGURE D Remittances and Trade Deficit(as percent of GDP)

…leading to fewer real estate transactions and a sharp risein speculative gold imports, while the asset quality of bankswith high real estate exposure looks threatened.FIGURE F Land revenue and gold imports(in NRs. million)

…partly because �scal prudence has been maintained...FIGURE C Overall and Primary Balances(in percent of GDP)

GDP growth

Primary BalanceOverall Balance

Private creditgrowth rate

M2 growth Weighted AverageInterbank Transaction Rate

Trade deficitincl. sevice

India CPIIndustrial

Nepal CPI

Consumption

Exports

Gross fixed capital formation

Nepal Food Nepal Non-Food

Workerremittances

Currentaccount balance

Reserves,net change

0

FY02 FY03 FY04 FY05 FY06 FY07 FY08 FY09 F10–15–10

–505

101520

05

10152025

FY 02 FY 03 FY 04 FY 05 FY 06 FY 07 FY 08 FY 09 FY 10(est.)

–7–6–5–4–3–2–1

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1000015000200002500030000350004000045000

FY06 FY07 FY08 FY09 FY10 FY10 Sixmonths

FY11 sixmonths

Land revenue Gold imports


MaldivesEconomic growth is in sync with the fortunes of tourism...FIGURE A Real GDP Growth, %

…which outstrip the contributions of government and construction...FIGURE B Contribution to Real GDP

Trade plays a key role...FIGURE E Trade, as a percent of GDP(including Services)

Source: MMA.

…and Eastern visitors begin to overstep the Western trend.FIGURE D Tourist Arrivals Composition

…while BOP pressure begins to undermine the currency peg.FIGURE F Balance of Payments, % of GDP

…while higher import prices drive up food in�ation... FIGURE C Inflation, Malé

Tourism GDP Growth

Food

Overall Balance

Non Food

0

–10

–5

0

5

10

15

20

Overall GDP Growth

GDP

Fisheries Tourism

Other Construction

China OthersEurope Asia excl. China

Government Administration

010

–10

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–20

30

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40

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2003–40%–30%–20%–10%

10%20%30%40%50%

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2004 2005 2006 2007 2008 2009 2010Est

2003 2004 2005 2006 2007 2008 2009 2010Est

Imports to GDP Exports to GDP

2003 2004 2005 2006 2007 2008 2009 2010Est

Current AC Bal Financial AC Bal

2003 2004 2005 2006 2007 2008 2009 2010Est

2003 2004 2005 2006 2007 2008 2009 2010Est

–0.15–0.10–0.05

0.000.050.100.150.200.250.300.35 2007 2010

73%

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64%

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20 40 60 80

100 120 140


Pakistan

6,000

8,000

10,000

12,000

14,000

16,000

Devastating �oods in July–August 2010 interruptedrecovery and resulted in weak real GDP growth…FIGURE A GDP Growth

...mitigated by strong growth in workers’ remittances,bringing in a positive current account for the �rst threequarters of 2011...FIGURE B Current Account Balance

…which contributes to persistent and worrisome double-digit in�ation...FIGURE E Trend in Inflation...

...but the biggest concern remains the large �scal de�cit arisingfrom �at tax revenue collection and expansionary spending…FIGURE D Fiscal performance (as % GDP)

…leading the central bank to keep the policy discountrate high.FIGURE F Interest Rates

…this, along with external disbursements, has improvedthe international reserve position, with mild appreciationof the exchange rate... FIGURE C SBP Forex Reserves and NominalExchange Rate

NER RS/US$ (LHS)

CAB

Trade Balance Current transfers

Income (net)

Services (net)

0%

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1%2%3%4%5%6%7%8%9%

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2000

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2001

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2002

/03

2003

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2004

/05

2005

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2006

/07

2007

/08

2008

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2009

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2010

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US$

billi

ons

FY06 FY07 FY08 FY09 FY10 (July–Mar)FY11

–30–25–20–15–10

–505

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14-J

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Expenditure (RHS)Tax Revenue

Fiscal deficit excl grants

12 m moving Average Y-O-Y Policy Rate 6-m KIBORCore Y-O-Y

4

6

8

10

12

14

16

0

4

8

12

16

20

24

2007/08 2008/09 2009/10 2010/11*

*Projected

81012141618202224

Feb-

09

Apr-0

9

Jun-

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09

Oct-0

9

Dec-

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Feb-

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Dec-

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Feb-

11

12%

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14%

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10-J

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914

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-09

18-S

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-Oct

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27-N

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Jan-

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Feb-

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16-A

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1-Ap

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Sri Lanka

Sterling Pound

Euro

US Dollar

Strong and consistent real GDP growth...FIGURE A Real GDP Growth, %

…driven by services and supported by manufacturing andconstruction…FIGURE B Contribution to Real GDP, %

…but in�ows to �nancial account remain steady...FIGURE E Balance of Payments, % of GDP

Source: CBSL .

…though trade declined...FIGURE D Trade, as a percent of GDP(Servicetrade not included)

…and the Sri Lankan rupee appreciated against manymajor currencies.FIGURE F Nominal Exchange Rates, LKR / Foreign Currency(Index, End April 2009 = 100)

4/20

095/

2009

6/20

097/

2009

8/20

099/

2009

10/2

009

11/2

009

12/2

009

1/20

102/

2010

3/20

104/

2010

5/20

106/

2010

7/20

108/

2010

9/20

1010

/201

011

/201

012

/201

01/

2011

…combined with higher consumption to fuel GDP growth… FIGURE C Contribution to Real GDP Growth, %

Agricultural GDP Growth

–12–10

–8–6–4–2

02468

0

4321

56789

Overall GDP Growth

GDP

ManufacturingServicesAgriculture

Industry Others

Mining

Construction

20030%

2004 2005 2006 2007 2008 2009 2010Est

2003 2004 2005 2006 2007 2008 2009 2010Est

Imports to GDP Exports to GDP

2003 2004 2005 2006 2007 2008 2009

Current AC Bal Capital AC Bal Financial AC BalOverall Balance

2003 2004 2005 2006 2007 2008 2009

0

4

–4

2

–2

6

8

10

Real GDP GrowthInvestment

Pvt ConsumptionNet Exports Govt Consumption

2004 2005 2006 2007 2008 2009 0

1%2%3%4%5%6%7%8%9%

5 10 15 20 25 30 35 40 45

80

90

100

110


References

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Developments in Global Commodity Markets

Food Supply and Demand Projections1

According to FAo projections, the global cereals market is expected to tighten considerably in 2011 with total utilization exceeding world production. The evolution of global prices for the remainder of 2011 will depend mostly on harvests of the winter crop, with any negative news on weather and harvest leading to further price increases. The winter crop accounts for the bulk of annual global wheat output and the overall wheat area for 2011 is now forecast to increase only marginally by about 1 percent over 2010. early indications suggest crop sowings were margin-ally reduced in the Russian Federation but close to last year’s levels in Ukraine.

overall, the world stock-to-utilization balance for cereals appears to be in a relatively healthier state than in 2008. however, the wheat markets appear to be more susceptible to price volatility than rice markets. The stock-to-utilization ratio is forecast to be higher for rice than for wheat, which largely explains the expec-tations in wheat markets driving price increases in the last few months (Table A1.1).

Modest but steady increase in global grains consumption, variable global grains supply due to weather shocks, trade policy responses to shocks, and resulting draw-downs of stocks held by the major grains exporting countries have combined to increase both uncertainty in global grains markets and broader food price volatility since 2005. Global grains consumption has increased by 26 percent since 1998/99, driven by

1Annex

TABLE A1.1 World Wheat and Rice Balances (million tons)

Wheat 2007/08 2008/09 2009/10 Estimate 2010/11 Forecast Change: 2010/11 over 2009/10 (%)

Production 611 685 682 653 –4 .3

Supply 722 829 862 833 –3 .4

Utilization 629 647 659 667 1 .2

Ending stocks 144 180 202 189 –6 .4

World stock- to utilization-ratio %

22 .2 27 .1 30 .2 27 .7 –8 .3

Rice 2007/08 2008/09 2009/10 Estimate 2010/11 Forecast Change: 2010/11 over 2009/10 (%)

Production 440 458 455 466 2 .3

Supply 544 569 580 591 1 .8

Utilization 436 445 449 460 2 .5

Ending stocks 111 125 130 136 4 .8

World stock- to utilization-ratio %

24 .9 27 .4 27 .2 29 6 .6

Source: FAO. Production data refer to first year shown. Supply is measured by adding production to opening stock.


population growth in developing countries, higher consumption of animal protein in response to rising incomes, and increased demand for biofuels. In the same period grain production increased by 20 percent, but with erratic weather causing significant produc-tion variability over years. Global stock draw-downs compensated for the production shortfalls with overall stocks falling below 20 percent of consumption by 2006/07 (Figure A1.1). FAo projects annual cereals demand growth of 1.4 percent between 2000 and 2030, including demand for grains used for biofuels, compared to 2.2 percent during the preceding 40 year period.2 While such a long-term rate of demand growth may at first appear modest, it still requires an increase in supply, and in this respect to a very large base. This poses an increasing challenge for growth of agricultural productivity in the face of growing land and water constraints and greater incidence of extreme weather events. In some regions demand is outstrip-ping supply, and unless there is growth in productivity they will become increasingly import dependent and vulnerable to variations of global prices.

The world grains stock-to-use ratio is often cited as a measure of both the physical liquidity of grain markets and an indicator of the likelihood of grain price increases. historical evidence suggests that grain prices spike when global stock-to-use ratios are low.3 Both the FAo and USDA publish stock-to-use esti-mates. They reflect the difference between estimated production and carry-over stocks on the one hand,

and estimated consumption and trade on the other. The stock-to-use measure thus includes (conceptually) all commercial, public and household stocks, whether or not the stocks in question are actually available for international sale. over half of global stocks of rice and wheat are estimated to be held by China and India, where public-sector stocks play a major role.4 There is global uncertainty as to the triggers for release of these stocks, their actual magnitudes, and their condi-tion, and it is not clear whether perceptions of these factors are adequately reflected in international prices. International markets, however, are clearly very sensitive to changes in perceptions of stocks likely to be avail-able for sale. When the USDA downsized its estimates of US corn production in the fall of 2010, the upward impact on global corn prices was sharp and immediate.

For the time being, stock-to-use ratios for major individual exporters tend to be a better indicator of grain price volatility than global stock-to-use measures. The US, for example, which accounts for 55 percent of global exports of corn, presently has a domestic corn stock-to-use ratio of 5 percent, an all-time low.5 This can be compared with a published—and historically ample—global corn stock-to-use ratio of 20 percent. For wheat, France, a major exporter to North Africa, has a 7 percent stock-to-use ratio, which is very low compared to the global figure of 26 percent. The bottom line is that improvements in understanding of which stocks will actually influence international prices may themselves help increase market price predictability.

The current global grains market situation is similar to the food price spike in 2007/2008 in three respects, as listed below.6

• Higher energy prices. Agriculture is significantly more energy intensive than industry with inputs such as irrigation, fertilizers and transport most heavily affected.

• Depreciation of the US dollar against major curren-cies. Trade in many agricultural commodities is denominated in US dollars. expressed in other currencies, price increases and volatility are less dramatic.7

• Financial investment in agricultural commodi-ties remains high. The Chicago Board of Trade alone accounted for an estimated US$ 5 trillion in wheat, corn and soy futures trading in 2010 (28 percent over the previous year, but down from US$ 6 trillion in 2008). Clearly the value of these financial transactions far exceeds the

FIGuRE A1.1 Rising World Consumption, variable Supply, and Stock Draw-Downs have Fueled Consecutive Grain Price Spikes

1998

/199

9

2000

/200

1

2002

/200

3

2004

/200

5

2006

/200

7

2008

/200

9

2010

/201

1

Stock-to-Use

Mill

ions

MT

(Con

sum

ptio

n,

Prod

uctio

n)

Perc

ent (

Stoc

k-to

-Use

)

10

15

20

25

30

35

40

1,400

1,500

1,600

1,700

1,800

1,900

2,000

Production Consumption

Source: USDA.

Annex 1. Developments in Global Commodity Markets 57

respective US crops (although the exchange is also used for hedging transactions for non-US crops). however, there is no evidence that the significant increase of financial investment in agricultural derivatives influences the level of prices (see Annex 5).

Yet, the current situation also differs from 2008 in several critical respects. Firstly, recent international price increases are more widespread across agricultural commodities than in 2008 and include increases in sugar, edible oils, beverages, animal products, and raw materials such as cotton, rather than being predom-inantly driven by major grains. Secondly, weather is more clearly a major factor, and the frequency of droughts, floods and extreme temperatures seems to be increasing. on the positive side, trade policy responses so far have been less damaging than in 2008 when they greatly exacerbated shortages.

The bottom line is that agricultural commodity price uncertainty and volatility are likely to continue in the foreseeable future, largely due to the continuing uncertainty on the supply side. In the short-term, assuming a normal 2011/12 crop year, international food prices are expected to decline from the current peak, but they are likely to remain above their pre-2007 levels. over the longer term, energy prices and total factor productivity are two key forces likely to shape world food price levels.

Since prices of staples remained 25–35 percent higher in many developing countries in 2009 compared to 2006, even when global prices fell,8 many farmers had an incentive to increase production. higher local production allowed developing countries in aggre-gate to enter 2010/11 with higher production (3.8 percent), higher stocks (3.4 percent), and more trade (5.4 percent) than in 2009/10. This which helped offset sharp, weather-induced production declines in developed countries.9

Commodity PricesThe recent rise in global commodity prices, from July 2010, is fueling headline inflation in both advanced and emerging economies. of all the different commodity groups, the global price rises and price volatility of agri-cultural commodities has percolated to the top of the political agenda in many of the emerging economies and, in particular, the South Asia region’s economies.

Moreover, the surge in wholesale food prices is slowly filtering into retail prices in poor and rich nations alike.

This rise in commodity prices is not restricted to a particular group of commodities but broadly affects agricultural, energy and metal prices.10 (Figure A1.2) In nominal prices, between 2009 and 2010, agricultural prices rose on average by 17.0 percent, energy prices by 26.5 percent and metals and minerals by 47.5 percent. Both the average agricultural and energy price indices have surpassed the peak reached during the food and fuel price rise of 2008. In fact, prior to the current price rise, agricultural, energy and metals and mineral prices in 2008 reached their highest level since 1960.

even though average real agricultural and metal and mineral prices in 2010 surpassed their 2008 levels, the average real agricultural price in 2010 is still below its record high of 280.65 in 1974.11 For 2010, the agri-cultural average real price index is 191.81. Average real commodity prices for agricultural energy and metals and minerals are also on an upward trend in 2010 after declining in 2009. The average real energy price in 2010 is 224.77, still below its historic high of 273.56 in 2008 (Figure A1.3).

Although each market has very different demand and supply dynamics, the uniformity of the price increases across a variety of commodity markets reflects both the interconnectedness of markets and the macro-economic trends influencing prices in these markets. There are numerous factors that may be contributing to this commodity price surge and each factor may have a varying impact on the individual market’s price increase. For example, buoyant demand from emerging economies, supply constraints and restrictions to trade,

FIGuRE A1.2 Commodity Price Index (Nominal Prices)

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

Inde

x, 2

000=

100

–40

10

60

110

160

210

260

310

360

Agriculture Energy Metals & minerals

Source: World Bank.


particularly for food, have all contributed to the latest global commodity price rise. The role of emerging markets in driving this price hike is related to rising income levels in these economies coupled with an improved standard of living, population growth and increased urbanization. Also, the weakness of the US dollar has fueled the increase in commodity prices, particularly crude oil.

AgricultureFrom mid-2010 there has been a steep rise in the price of most agricultural commodities, including food crops. In February 2011, the World Bank Food Price

Index registered 292.61, slightly above the record high of 292.60 recorded at the height of the food crisis in June 2008. This is the largest annual increase since July 2008. The average growth for the first three months of 2011 is 33.1 percent over the previous year. The rise in nominal agricultural prices is a function of recent supply shocks and long-term structural change in global demand. In general, long-run worldwide demand for food has been driven by three factors: (1) rising population growth; (2) rising levels of afflu-ence; and (3) increasing demand for biofuels.12 For instance, demand pressure from across the emerging world, particularly in China and India—with 2.5bn people between them—has placed upward pressure on the cost of food. Additionally, arable land is being lost with the increasing use of corn, wheat and sugar cane for the production of biofuel, ethanol in partic-ular. Record ethanol production in the US will also swallow up nearly 40 per cent of the US corn crop in 2010/11, from 31 percent of output in 2008/09. This jump in food prices may push up long-term general price expectations. In addition, real food prices regis-tered 249.9 in February 2011, which were last witnessed in April 1975. Real food prices have been steadily rising since January 2001 after declining from record highs in November 1974. (Figure A1.4)

Average food price volatility has increased in the 2000s, with volatility in grains, vegetable oil and soybeans rising each decade (Figure A1.5). Since the 1960s, sugar has consistently been the most volatile agricultural commodity over each decade, while meat prices have been least volatile on average. The increase in volatility is due to an increase in the frequency of supply shocks combined with limited reserves and increase in the production of biofuels, increase in global macroeconomic volatility post-2000 and the emergence of India and China.

Falling stocks and rising consumption-to-production drive up cereals prices (Figure A1.6). In the second half of 2010, cereals prices grew by 17.9 percent on average, with corn prices contrib-uting 73.2 percent to the increase. This trend has continued, with February 2011 recording the highest year-on-year growth for cereals: 54.1 percent since August 2008.13 A rapid rise in corn prices since July 2010 has been the main driver of growth in cereals prices registering 15 percent and 33 percent quarter-on-quarter growth in the third and fourth quarters of 2010. Corn prices hit 30-year highs with stocks dwindling rapidly. Given that the US is the world’s

FIGuRE A1.3 Commodity Price Index (Real Prices)

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

Inde

x, 2

000=

100

–40

10

60

110

160

210

260

310

360

Agriculture Energy Metals & minerals

Source: World Bank.

FIGuRE A1.4 Food Price Trends

1960

M01

1963

M01

1966

M01

1969

M01

1972

M01

1975

M01

1978

M01

1981

M01

1984

M01

1987

M01

1990

M01

1993

M01

1996

M01

1999

M01

2002

M01

2005

M01

2008

M01

2011

M01

Food

Pric

es

050

100150200250300350400450

Real Food Price Index Nominal Food Price Index

Source: World Bank.


largest corn producer, the decline in US corn stocks-to-demand is a harbinger of higher corn prices in the future. In 2009/10, for the first time since 2006/07, consumption surpassed production with corn stocks declining by 1.8 percent. Corn (US No. 2, Yellow) prices rose by 52.9 percent in January 2011, its highest annual growth rate since August 2008. The growth rate in corn prices has been rising exponen-tially since July 2010, averaging 34.6 percent in the last seven months. The USDA expects corn stocks to decline by 3.5 percent in February 2011 from those of the previous month. Increased demand for high-fructose corn syrup from countries such as Mexico, as they substitute away from higher priced sugar, contributes to higher demand for corn. China, after years of self-sufficiency, was a net importer of corn in 2010, partly because of drought—bringing in nearly 1.3 million tons compared to 47 thousand metric tons the previous year. This aggravated the global shortage of corn stocks. In addition, rising wheat prices prompted corn substitution, further raising corn consumption, lowering stocks and raising prices.

In February 2011 wheat prices hit their highest level in 34 months. In February benchmark wheat prices escalated on average by 79.4 (y-o-y), reaching a US$ 350 per ton. This is the highest rate of increase since April 2008. Wheat prices have been affected by a string of supply shocks: drought-induced crop failures in leading cereals exporters Russia, Ukraine and Kazakhstan; concern about the La Nina weather phenomenon bringing dryness in the crop belts of Argentina (the world’s second-largest corn exporter) and Brazil; and a cold snap in the US, the world’s biggest wheat exporter, all of which make approaching harvests seem fragile. Poor harvests have led traditional wheat exporters to impose export restrictions.14 The cumula-tive impact of these supply shocks has already dented wheat stocks. February 2011 production fell by 218 thousand metric tons, a decline of 0.12 percent over the previous month.

China, the world’s biggest wheat producer, with 18 percent of the global harvest, may have to buy large quantities on global markets, putting even more pressure on wheat prices.15 These production shocks, coupled with narrowing of domestic stocks world-wide, have resulted in hoarding of wheat by North African and Middle eastern countries, which are rela-tively dependent on international markets for food supplies. Since wheat is a large contributor to food infla-tion, governments are prone to hoarding it as a hedge

against shortages. This “accordion effect” of buying more now to guard against higher prices later serves to bring forward price increases. Between June 2010 and December 2010, the price of wheat increased by large amounts in Kyrgyzstan (54 percent), Bangladesh (45 percent), Tajikistan (37 percent), Mongolia (33 percent), Sri Lanka (31 percent), Azerbaijan (24 percent), Afghanistan (19 percent), Sudan (16 percent), and Pakistan (16 percent). overall, high prices have induced farmers across key producing regions (the european Union, Russia, and Ukraine) to increase acreage. The concerns about fragility notwithstanding,

FIGuRE A1.5 Food Price volatility(Average Coefficient of Variation)

1960–79

0.000.020.040.060.080.100.120.140.160.18

Tota

l Foo

d

Grai

ns

Vege

tabl

eOi

ls

Frui

ts

Mea

t

Suga

r

Soya

bean

Mea

l

Soya

bean

s

1980–99 2000–10

Source: Authors calculations.

FIGuRE A1.6 Grain Consumption and Stocks

Ratio %

Consumption-to-Production Ratio

1990

/91

1991

/92

1992

/93

1993

/94

1994

/95

1995

/96

1996

/97

1997

/98

1998

/99

1999

/00

2000

/01

2001

/02

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

–30

–20

–10

0

10

20

30

0.50

1.00

1.50

2.00

2.50

Growth rate in Ending stocks (r.h.s.)

Source: FAO.


better yields are expected for 2011, barring adverse weather events similar to 2010.

Rice prices recorded in March 2011 declined 1.9 percent over the previous year. This represents 15 consecutive months of declining rice prices.16 The falling rice price is indicative of rising levels of produc-tion and ample global stocks. Good harvests in Thailand and Vietnam, the world’s two largest exporters, keep the export market well supplied and the cost of the rice below the record level of US$ 960 per ton in May 2008. however, month-on-month the bench-mark rice price has risen between July and December 2010—partly in response to rice importers in Asia having stepped up buying. In the last week of January 2011, Bangladesh, one of the world’s top three rice importers, raised its overseas buying target to 1.2m tons, up from an initial estimate of 600,000 tons. Coupled with this, crop failures in Indonesia brought on by heavy rain are contributing to the recent price rise, given that Indonesians eat more rice per capita than any other country.17 The domestic price of rice was significantly higher in Vietnam (46 percent) and Burundi (41 percent) between June–December 2010. Rice prices have increased in line with global prices in Indonesia (19 percent), Bangladesh (19 percent), and Pakistan (19 percent). These Asian countries are large rice consumers, especially among the poor. Rice price increases in Sri Lanka (12 percent) and China (9 percent) were relatively moderate in the second half of 2010, while in Cambodia and the Philippines the retail price of rice remained largely unchanged during this period.

Both corn and soya bean meal are important ingre-dients in animal feed as carbohydrate and protein.18 The tightening market partly reflects stronger appe-tites for meat in emerging markets. The rising incomes in emerging markets have shifted consump-tion towards middle-class foods with high protein content. Beef prices rose from US$ 2,648 to US$ 4,140 per ton between october 2009 and March 2011, representing close to a 56 percent increase. The rising average price of meat and poultry is likely to continue in 2011 if the forecast of rising demand by mainly BRIC economies is realized. In addition, rising demand for meat has increased imports of soya bean meal which rose in China by 18.6 percent in 2009/10 (y-o-y). The demand for milk powder is also a “middle-class” good whose price has risen in the past year with increased demand from Brazil, China and Russia.

Unlike the food price hike of 2007/08, there is a shift in the composition of demand towards, not only mean, but also fats and oils and sugar are contributing more to the rise in food prices. Between July 2010 and March 2011, fats and oils contributed 40 percent to the average annual growth.

Sugar prices rose consistently throughout the global financial crisis, hitting a 30-year high. US raw sugar prices hovered close to 40 cents per pound between January 2010 and March 2011, the highest since January 1975. World sugar prices rose by approximately 100 percent between May 2010 and January 2011, and declined marginally by March 2011. Prices have been driven by supply shortfalls from Brazil, the largest exporter, and weather shocks in Australia. Globally, stocks of sugar declined by 6.4 percent in the September-october marketing seasons of 2008/09 and 2009/10. Recently, cyclone Yasi provided a supply shock to world-wide sugar output, damaging cane crops in Australia, the world’s third-largest exporter of the sweetener. In addition, falling expectations for the crucial Indian crop, and speculation that Russian imports could be brought forward, contributed to rising global sugar prices. Rising sugar consumption in BRIC and devel-oping countries has also helped fuel the price rise.19

Vegetable oil prices have risen at an annual rate since october 2009. Since the fourth quarter of 2010, coconut oil prices risen rising every month above 100 percent annually. Coconut oil prices have risen by 192 percent between october 2009 and January 2010. With most South Asian countries using coconut oil for cooking, this will have an impact on the region. For instance, the price of cooking oil rose by 43 percent in Bangladesh over the past year.

Fertilizer prices have risen steadily by 47 percent between September 2009 and January 2011. Fertilizer prices are affected by crude oil prices, with modern farming relying on hydrocarbons in the form of fertil-izer and fuel for tractors and transport (Figure A1.7). Thus, fuel prices influence fertilizer prices which in turn influence food prices. Therefore, as the growth of India and China impacts the cost of energy this inflates the input cost and subsequently the price of food. Moreover, food prices are less volatile than fertil-izer prices; the latter having risen more than food prices during the 2008 food price crisis, lowering the relative food-to-fertilizer price ratio (Figure A1.8). The rela-tive food-to-energy price ratio was constant during the food-price crisis of 2008. This shows that farmers may not be able to reap the full benefits of higher food


prices because input costs, such as fertilizer and fuel prices, may be rising faster than the earnings from their food production.

Energy and Metals

Crude oil prices reached their highest levels in two years in January 2011, surpassing US$ 100 a barrel.20 The surge continued through March, when they were 36 percent higher than a year earlier. The inability of production to keep up with growing demand has led to a decline in world stocks by 0.1 percent and net demand rising by 0.7 percent annually in 2010. Though stocks are falling, they are still at comfort-able levels, unlike the 2008 fuel price crisis. When the global financial crisis depressed world oil demand, the opec cartel’s effective idle capacity surged to a peak of more than 6 million barrels per day in early 2009. Since then, rising consumption in emerging markets has eroded opec’s effective spare capacity to below 5 million barrels per day, by the IeA’s estimate. Recent political uncertainty in the Middle east-North Africa region is limiting supply further.

Moreover, there has been a huge structural shift in oil demand. Fifty years ago, the centre of gravity for demand was in the US and europe. Nowadays it has shifted to Asia. oil demand in emerging markets provides the bulk of incremental growth. We expect non-oeCD oil demand growth to expand at four times the rate of oeCD growth in 2011.

With rising crude oil prices, alternate sources of energy such as natural gas are becoming increasingly popular. however, the rising supply of shale gas in North America is keeping gas prices low. The US resi-dential gas price has fallen steadily from US$ 15.50 per thousand cubic feet to US$ 9.80 between August 2010 and January 2011.

Since coal is relatively cheaper than crude oil, rising demand has led to rising coal prices throughout 2010. In January 2011, coal prices rose to US$ 137 per ton, an annual increase of 41.2 percent. Bad weather has hit key coal exporters Colombia and Australia, as the market is extremely vulnerable to cold weather. Furthermore, China is poorly endowed with alter-native energy sources and the speed of its coal-based electricity expansion has forced it to start importing coal for the first time. China uses coal to produce elec-tricity, needed for smelting aluminum. This too has pushed up coal prices.

Although aluminum prices rose by 32 percent to US$ 2,555 per ton from mid-2010 to March 2011, aluminum remains a long way from its peak of US$ 3,380 per ton, in July 2008. (Figure A1.9) Aluminum is used for numerous consumer and industrial prod-ucts, from cars and aircraft to drinks cans. Thus aluminum prices are also rising with growing demand from emerging markets, given that it is the most widely used metal after steel. This has pushed the benchmark aluminum price to US$ 2,500 per ton for the first time since the collapse of Lehman Brothers. Aluminum prices may continue on this upward trajectory due to supply constraints in the market. China has curbed

FIGuRE A1.8 Food vs Fertilizer Prices

Grow

th (%

)

2005

H1

2005

H2

2006

H1

2006

H2

2007

H1

2007

H2

2008

H1

2008

H2

2009

H1

2009

H2

2010

H1

2010

H2

2011

Q1

0.00

0.20

0.40

0.60

0.80

1.00

1.20

–60–40–20

020406080

100120

Fertilizers Nominal Food Price Index EnergyRatio of Food to Fertilizer price Ratio of Food-to-Energy Price

Source: World Bank.

FIGuRE A1.7 Fertilizer vs Crude Oil Price Index

Inde

x

0

100

200

300

400

500

600

700

Fertilizers Petroleum crude

2005

H1

2005

H2

2006

H1

2006

H2

2007

H1

2007

H2

2008

H1

2008

H2

2009

H1

2009

H2

2010

H1

2010

H2

2011

Q1

Source: World Bank.


production of aluminum in order to reduce energy consumption.21 electricity accounts for 40 percent of that country’s production costs, and

Copper prices have historically been higher than aluminum prices. Indeed, copper is now nearly four times as expensive as aluminum—the highest such ratio on record, reaching a peak of US$ 9,868 per ton in February 2011—a 52 percent increase over mid-2010. Demand for copper is driven mostly by its use as a conductor of electricity. China’s expansion of its elec-tricity grid is fueling the worldwide price of copper, with imports of the metal hitting record levels. The limited supply response is contributing to the price hike. Copper prices reached US$ 10,000 a ton in the first week of February 2011.

OutlookFood prices are expected to rise 8 percent above 2010 levels, assuming a normal crop year, and that oil prices do not rise further wheat and maize are expected to average 13 and 12 percent higher than 2010 levels while rice prices are expected to remain almost unchanged. Soybean and palm oil prices are expected to be 11 and 17 percent higher.

Metals prices are expected to rise by almost 20 percent in 2011 on persistently strong demand, led by China, and weak supply response for some metals, notably copper and tin.

Notes1. This section draws heavily on World Bank (2011a,

2011b).2. FAo (2002).3. Wright (2009).4. The USDA made major revisions to its estimates of

Chinese stocks in 2001, but this had little impact on global price behavior at the time, possibly because China in 2002/2003 was a significant grains exporter (Wright 2009, op. cit).

5. USDA (2011).6. World Bank (2011a).7. World Bank (2011b).8. World Bank Food Price Watch, various issues since

January 2009.9. FAo (2010).10. For instance, oil price increases impact the price of

food: a 10 percent increase in crude oil prices is asso-ciated with a 2.7 percent increase in the World Bank Food Price Index. See Baffes (2010).

11. The World Bank Food Price Index is deflated using the World Bank Manufactures Unit Value Index.

12. In the run-up to the 2007/08 crisis, the oeCD esti-mated that about 60 percent of increased demand for corn was due to policies on biofuels and energy in devel-oped countries, which could lead to similar increases in the future.

13. Cereals comprise corn, rice and wheat and barley.14. Russia and Ukraine placed a moratorium on exports

with the onset of drought.15. The United Nations’ Food and Agriculture organization

announced that 12.75 million acres of China’s 35 million acres of wheat fields had been affected by drought.

16. Rice was a key reason for the contagion that precip-itated the 2008 crisis, when many large exporters banned its export.

17. Indonesia imported 1.2m tons of rice this year.18. It takes about 11 pounds of grain to produce 1 pound

of beef; 7 pounds of grain to produce 1 pound of pork; 3 pounds of grain to produce 1 pound of chicken.

19. BRIC countries represent 36.4 percent of total sugar consumption in 2010/11, a rise 2 million metric tons over previous year.

20. In late-February 2008, crude oil reached a record high, above US$ 146 per barrel.

21. Aluminum production is energy intensive. It takes about 15.7 kilowatt hours of power on average to produce one kilogram of workable aluminum.

FIGuRE A1.9 Copper and Aluminium Prices

$/m

t

%

2005

H1

2005

H2

2006

H1

2006

H2

2007

H1

2007

H2

2008

H1

2008

H2

2009

H1

2009

H2

2010

H1

2010

H2

Ave

Jan–

Mar

201

1

–60

–40

–20

0

20

40

60

80

100

0

2,000

4,000

6,000

8,000

10,000

12,000

Aluminum Copper Aluminum Copper

Source: World Bank.


Speculation, Financialization of Commodities, and the “New” Money

IN The CoNTeXT oF The PoST-2005 commodity price boom, speculation has been one of the most frequently discussed and, perhaps, poorly

understood concepts. We note that the financial and popular media speculates widely, giving most atten-tion to investment fund activity in commodity futures exchanges; some say the funds have caused a speculative bubble, while others argue that they have not only not affected prices at all but that they have injected liquidity into the market, thus facilitating price discovery. We argue here that although the views on the effects of such investment activity on commodity markets are very strong and diverse, the empirical evidence is weak, showing small or no impact. We conclude by noting that while it is unlikely that investment fund activity will alter long-term price trends, it may induce higher price variability by exacerbating the length and the amplitude of price cycles.

What Is Speculation?Kaldor (1939) defined speculation as “…the purchase (or sale) of goods with a view to resale (repurchase) at a later date, where the motive behind such action is the expectation of a change in the relevant prices relatively to the ruling price and not a gain accruing through their use, or any kind of transformation effected in them, or their transfer between markets.” Thus, according to Kaldor, most financial activities would be classified as speculation. In the context of the current debate, six types of “speculative” activities have been mentioned in the literature (see Table A2.1). First is that it takes place in the futures exchanges. These speculators are indispensible entities of commodity futures exchanges since they provide the necessary liquidity and ensure that the market clears.

A second type of speculative activity is when market participants hold inventories beyond what is justified by business needs or when they hold large quantities of commodities with the expectation that

an upward movement in prices will generate profits (often referred to as hoarding). Unless such activity entails market manipulation, holding inventories is the inter-temporal equivalent of Adam Smith’s “invisible hand”: traders buy at current prices to sell later when (in their opinion) the market will be tight, thereby balancing the market and hence reducing price vari-ability. There is no evidence that hoarding took place during the recent boom, as known inventories of most (non-perishable) agricultural commodities reached historical lows. Two exceptions may be rice, during mid-2008 (in various east Asian countries), and cotton in late 2010 (in China).

Third, market manipulation often takes place. There have been many such cases. For example, in the 1950s US onion producers argued that traders in the Chicago Mercantile exchange cornered the market. This led to the passage of the onions Futures Act which prohib-ited futures contracts on onions. other cases include that of the hunt brothers, who attempted to corner the silver market in the late 1970s and early 1980s; Sumitomo’s chief copper trader, Yasuo hamanaka, who cornered the copper market in the 1990s; and British Petroleum’s cornering of the propane market in 2006 (it resulted in a US$ 300 million fine). Although there are no known (or proven) cases for market manipu-lation during the recent boom, even if cases become known, they are likely to be isolated events.

The last three are financial activities often pinned to speculation: hedge funds, commodity trading accounts (or advisors), and investment funds (including various investment, pension, and sovereign wealth funds):

• Hedge funds undertake investment and trading activities in a broad range of assets, including commodity markets. The fund may trade and invest in commodity asset classes in order to “hedge” the diverse risks inherent in their port-folios. In such a case, taking a position in the futures market for a particular commodity or commodity class can represent an investment

21

Annex


in a non-correlated asset that provides diversi-fication benefits to the overall portfolio. hedge funds have existed for decades and their effect on commodity markets is typically short term (i.e., they affect short-term price movements).

• Commodity trading advisors (CTAs) are asset managers who operate almost exclusively in commodity markets. They invest for portfo-lios under management and for clients with the objective of earning profits from market vola-tility. Because CTAs use fundamentals and/or technical analysis as their guiding principles, they may enhance price discovery and thus reduce market price variability since they iden-tify movements in fundamentals in advance of other market participants.

• Inve s tment funds—rela t i ve l y re cen t phenomena—represent in many respects the flow of “new” money into commodity markets. It is this type of activity that rests (or should rest) at the core of the current debate. The next para-graphs elaborate on the origins of this invest-ment activity.

The Origins of Investing in Commodity MarketsThe commodity price increases of the last decade have often been linked to “new” money that found its way into commodity markets, setting the stage

for the so-called “financialization” of commodities. A number of events led to this. First, the publication of an influential book argued that commodities should have been part of every investor’s portfolio (Rogers 2004). A little later Gordon and Rouwenhorst (2006) compared a hypothetical commodity-based portfolio with bond and equity portfolios and concluded that the risk premium on commodity futures is essentially the same as equities, commodity futures returns are negatively correlated with equity returns and bond returns, a reflection of the different behavior of such asset classes over the business cycle.

Second, during the early part of the past decade, investment fund managers—including those of sover-eign wealth and pension funds—noted that existing classes of assets (such as money funds, equities, and bonds in both developed and emerging economies) were becoming increasingly correlated amongst themselves. In their search for new uncorrelated assets they began including commodities in their portfolios.

Third, during the past decade or so, many high-income countries have pursued lax monetary poli-cies which may have caused what many describe as “excess liquidity”. Many authors (e.g., eckaus (2008), Wray (2008) and Calvo (2008)) have argued that such liquidity may have found its way into commodity markets, causing the “third” price bubble (following the equity/dot.com and housing bubbles).

Finally, numerous authors argued that commodities (especially in the extractive industries) have entered a super cycle, that is, a prolonged period of increasing

TABLE A2.1 Types of “Speculative Activity”Activity Function Effect

Speculation in futures exchanges

Important activity for the functioning of futures markets

Injects liquidity into the market and improves price discovery

Market manipulation Isolated cases such as the cornering of the cop-per and silver markets

These are illegal activities

Building up inventories Accumulation of physical stocks with the expec-tation that price increases will generate profits

Traders buy at current prices to sell later, when the market will be tight, thus balancing the market and reducing price variability

Commodity Trading Accounts (CTAs)

Professionally managed commodity invest-ment vehicles that take consideration of market fundamentals

They enhance price discovery since they ex-amine the fundamentals very carefully and use technical analysis

Hedge funds Short-term profit seeking Believed to be associated short term volatility (i .e ., day-to-day)

Investment funds Taking long positions in futures exchanges by in-vestment, pension, and sovereign wealth funds

They may amplify commodity cycles due to their size and nature of investment, but are unlikely to affect long-term trends

Annex 2. Speculation, Financialization of Commodities, and the “New” Money 65

prices. heap (2004), in an influential report argued that a super cycle is underway, driven primarily by economic growth (and hence commodity-demand growth) in China. he noted that there have been two super cycles over the past century (at the beginning of the 20th century and during the Korean War). Indeed, World Bank (2009) showed that as of the early 1990s, demand for metals by China was so large that it effec-tively reversed global metal intensity (i.e., metal use per unit of world GDP) and by 2010 it reached levels similar to those of the early 1970s. econometric work by Cuddington and Jerrett (2008) and Jerrett and Cuddington (2008) for the metals market confirmed the super cycle hypothesis.

Blaming “Speculators”: Who Said What?historically, blaming speculation in futures markets has originated from politicians and populists, often reflecting ideology or the search for scapegoats to blame for unpopular price increases (Jacks 2007). Most econ-omists and market participants, however, have been strong defenders of futures markets, which are viewed (rightly) as the most important price discovery mech-anisms. Surprisingly, the “speculation” debate of the recent commodity boom appears to have divided even economists and market participants, as the rest of this section elaborates.

Krugman, in a series of blogs and editorials, rejected the view that speculation fueled the commodity boom. he argued (New York Times, May 13, 2008) that, “If the price is above the level at which the demand from end-users is equal to production, there’s an excess supply—and that supply has to be going into inventories. end of story. If oil isn’t building up in inventories, there can’t be a bubble in the spot price.” Krugman also dismissed the idea that commodity trading activity in futures exchanges may have affected spot commodity prices at all: “… a futures contract is a bet about the future price. It has no, zero, nada direct effect on the spot price” (New York Times, June 23, 2008).

Wolf shared similar views. he wrote in a Financial Times editorial (May 13, 2008) that “if speculation were raising prices above the warranted level, one would expect to see inventories piling up rapidly, as supply exceeds the rate at which oil is burned. Yet there is no evidence of such a spike in inventories.” Similarly, Wright (2009) noted that if long futures positions were

behind the grain price spike of 2008, stocks would have increased. Frankel cited the Congressional testimony by the chief economist of the Commodities Futures Trading Commission to support in his weblog (July 25, 2008) that, “The evidence does not support the claim that speculation has been the source of, or has exacerbated the price increases.” The evidence refers to Congressional testimony (April 3, 2008), which concluded that: “Looking at the trends in the market-place, combined with studies on herding behavior and the impact of speculators in the markets, there is little evidence that changes in speculative positions are systematically driving up crude oil prices.”

Verleger (2009: 1), citing analysis and data from the International energy Agency (2009), concluded at his US Commodity Futures Trading Commission testimony that the 2007/08 crude oil price spike was caused by the incompatibility of environmental regu-lations with the global crude supply. Speculation, he argued, had nothing to do with the price increases. Yet, Verleger (p. 2) acknowledged that the possible liqui-dation of futures positions was one of the key reasons tied to the collapse of oil prices from July 2008 to December 2008; which begs the question why the decline in oil price would have been caused by liqui-dation of futures positions when the increase was not caused by activities in that sphere?

The IoSCo Task Force of Futures Markets (2009), formed at the request of the G-8, reviewed several reports by international organizations, central banks and regulators and concluded that economic funda-mentals, rather than speculative activity explained commodity price changes during the boom period. The report recommended that regulators should (p. 3): (i) understand with greater clarity the role of speculative and commercial activity in commodity futures markets; (ii) gain a more comprehensive view of trading activ-ities in, and the structure of, the underlying markets that may affect price formation on commodity futures markets; and (iii) detect, deter, and prosecute manipu-lation and other trading abuses involving commodity futures, and related commodity markets. IoSCo’s conclusions, however, are somewhat inconsistent. If regulators do not have clarity on the role of speculative and commercial activity in commodity futures markets and they need to gain a more comprehensive view of trading activities, how did they conclude that such activities did not play a role during the recent boom?

At the other end of the spectrum, Soros (2008) called commodity index trading at his US congressional


testimony intellectually unsound, potentially destabi-lizing, and distinctly harmful in its economic conse-quences. eckaus (2008) noted that while the most frequently cited factors—increased demand, dollar depreciation, geopolitical concerns, and issues regarding depletion of resource—played some role in the crude oil price increases after 2004, speculation played a much larger role than most analysts believe. After comparing the oil price increases with the dot.com and housing bubbles, he asked (p. 8): “Is a speculative bubble irra-tional? No, it is rational to ride along and trade in a speculative bubble as long as it is expanding. The moment of truth comes only at the end, when the bubble bursts.”

Similarly, Khan (2009) examined a variety of indi-cators that might have affected commodity prices and concluded that while market fundamentals played a key role in the run-up of the oil prices after 2003, the price increase during the first half of 2008 was a price bubble. he argued that in the absence of speculative activity, oil prices would have been in the range of US$ 80–90 per barrel (oil prices averaged a little more than US$ 100 per barrel during the first half of 2008) and concluded that in order to avoid similar episodes in the future, more regulation should be put into place.

Medlock and Jaffee (2009) attributed the oil price increase of 2008 to the presence of non-commercial players, who (p. 3) “have increased their footprint in the marketplace dramatically since the late 1990s”. They also argued that trading strategies of financial players may have influenced the correlation between the US dollar and the price of oil. Wray (2008) argued that the commodity price increases was the boom following the equity and housing of the late-1990s and mid-2000s. he linked all three booms to the excessive monetary ease and limited degree of regulation and supervision of financial institutions, and assigned responsibility to various money managers who created numerous esoteric and complex instruments and practices that (p. 7) “spread as quickly as a deadly virus in a sci-fi flick”.

Calvo (2008), responding to Krugman and other commentators, noted that speculation and low inven-tories are not necessarily inconsistent with each other, and concluded that increases in commodity prices during 2007/08 were a result of portfolio shift against liquid assets by sovereign investors, sovereign wealth funds, partly triggered by lax monetary policy in the US. Roubini (2009) said of the early-2009 crude oil price increase: “… improving fundamentals … justify oil going from $30 to maybe $50. I think the other $30

is all speculative demand feeding on it—speculators and herding behavior.” De Schutter (2010) concluded that a significant portion of the increases in food price and price volatility during 2007 and 2008 could only be explained by the emergence of a speculative bubble.

Yet, the Empirical Evidence Has Been WeakThe empirical evidence on whether financial invest-ment in commodities contributed to the recent boom is, at best, mixed (see Table A2.2). one of the first empirical studies was the IMF’s 2006 World Economic Outlook (IMF 2006). Based on a VeCM model and monthly data for the 1995–2006 period, it examined the markets of crude oil, copper, sugar, coffee, and cotton and found no evidence that speculative activity affects price levels in either the short- or long-term. The IMF reached a similar conclusion in its 2008 World Economic Outlook when it examined 50 commodities and weekly data for the 1997–2008 period. Büyükşahin and harris (2009) used daily data from 2000 to 2009 and, based on Granger causality tests, found no statis-tical evidence that the numbers of contracts held by any group (including index traders) affected crude oil prices. A similar conclusion was reached by the US Commodity Futures Trading Commission (CFTC 2008).2

haigh, hranaiova and overdahl (2007), using VAR and daily data for the natural gas and crude oil market, failed to observe a link between price vola-tility and changes in hedge fund positions. Kilian and Murphy (2010) examined the crude oil market within a VAR framework over 1973–2009 and elim-inated speculation as an explanation of the 2003–08 crude oil price surge.

Irwin, Sanders, and Merrin (2009), and subse-quently Sanders and Irwin (2010), based on results of Granger causality tests between open positions and futures prices for various agricultural commodities, expressed strong skepticism that futures trading activity had led to bubbles in agricultural futures prices. Verleger (2009) argued that money-flows into oil contracts did not affect futures markets; his conclusion was based on simple correlation analysis. Moreover, in a subse-quent study Verleger (2010: 65) attributed the stability of energy prices during December 2009 and January 2010 partly to the increase of passive investors who allocated a portion of their portfolios to commodi-ties, and noted further that credit for the absence of a


price surge during these two months should be given to the financial engineers who had the foresight to integrate energy markets with investors. Till (2009), based on daily data, examined the crude oil market and concluded that the balance of speculators in the US oil futures and options market was not excessive relative to hedging. Stock and Whaley (2010) regressed finan-cial returns of twelve agricultural commodity prices

(weekly data) on a number of variable including posi-tions by speculators and concluded that inflows and outflows from commodity index investments do not cause futures prices to change.

other authors have reached somewhat different conclusions. Robles, Torero, and Braun (2009) iden-tified speculative activity in the futures market as a source of the 2007/08 agricultural commodity price

TABLE A2.2 Summary of Empirical Evidence

Study Model characteristics Key conclusion

LITTLE OR NO IMPACT

IMF (2006) VECM, monthly data, 1995–2006, crude oil, copper, sugar, coffee, cotton

Little evidence that speculative activity affects either price levels over the long run or price swings in the short run .

Haigh, Hranaiova, and Overdahl (2007)

VAR, daily data, 2003–04, gas and crude oil Failed to observe a link between price volatility and changes in hedge find positions .

IMF (2008) Financial returns, weekly data, 1997–2008, fifty com-modities

No apparent systematic connection between financialization and price changes .

CFTC (2008) Granger causality, daily data, crude oil Failed to find that changes of traders’ positions caused changes in crude oil prices

Büyükşahin, and Harris (2009)

Granger causality, daily data, crude oil Failed to find that changes of traders’ positions caused changes in crude oil prices

verleger (2009) Correlation analysis, crude oil Money-flows into oil contracts have not affected oil prices

Till (2009) T index, daily data, 2006–09, crude oil The balance of outright speculators in the US oil futures and options markets was not excessive relative to hedging

Kilian and Murphy (2010) VAR, monthly data, 1973–2009, crude oil The results eliminate speculation as an explanation for the 2003–08 oil price surge

Irwin, Sanders, and Merrin (2009)

Granger causality, daily data, 2003–08, ten agricultural commodities

Positions of long-only index funds do not lead futures prices .

Sanders and Irwin (2010) Granger causality/T index, weekly data, 2006–09, twelve agricultural commodities

The evidence that index-fund positions impact returns across commodities is scant .

Stoll and Whaley (2010) Granger causality, weekly data, 2006–09, twelve agricul-tural commodities

Inflows and outflows from commodity index investment do not cause futures prices to change .

MODERATE IMPACT

Gilbert (2007) Granger causality, monthly data, 2003–08, five metals and four food commodities

Some evidence that index investment may have been responsible for raising some commodity prices during the recent boom .

Plastina (2008) Granger causality, monthly data, 2006–08, cotton Investment fund activity might have pushed cotton prices 14 percent higher .

Robles, Torero, and Braun (2009)

Granger causality, monthly data, 2002–2008, food com-modities

Speculative activity might have been influential .

Gilbert (2010) 3SLS, monthly data, 2006–2009, food commodities Index-based investors appear to have inflated food com-modity prices .

Tang and xiong (2010) Co-movement analysis, daily data, 1998–2009, twenty-four non-energy commodities

Large commodity price volatility of recent years was related to the presence of index investors .

Silvennoinen and Thorp (2010)

Bivariate conditional volatility, daily data, twenty-four commodities (agriculture, metals, and energy)

Higher commodity returns volatility is predicted, among oth-ers, by financial traders’ open positions .


increases. Their conclusion was based on Granger causality tests using monthly data during 2002–08 for a number of food commodities. Plastina (2008) concluded that between January 2006 and February 2008, investment fund activity might have pushed cotton prices 14 percent higher than they would other-wise have been. Gilbert (2007) found that futures posi-tions did not affect the prices of metals at the London Metal exchange but they strongly affected the prices of soybeans at the US Chicago Board of Trade. In a more recent paper, however, Gilbert (2010: 420) concluded that by investing across many commodity futures, index-based investors may have inflated food commodity prices.

Tang and Xiong (2010) looked at co-movement of daily prices for twenty-four non-energy commod-ities traded at futures exchanges for the 1998–2009 period and concluded that the large price volatility of recent years could be attributed, at least in part, to the presence of index investors. Similarly, Silvennoinen and Thorp (2010) used daily data for twenty-four commodities (agriculture, metals, and energy) and, by examining the conditional volatility and correla-tion dynamics between these commodity prices and other assets, concluded that commodity returns vola-tility is predicted, among others, by financial traders’ open positions.

Can Investment Fund Activity Affect Commodity Prices?There are four reasons why that may be so. First, invest-ment in commodities is a relatively new phenomenon, and funds have to date flowed mostly in, not out, implying that some markets may have been subject to extrapolative price behavior; that is, high prices leading to more buying by investment funds, in turn leading to even higher prices, and so on.

Second, index funds invest on the basis of fixed weights or past performance criteria. hence, invest-ment behaves differently from what market fundamen-tals would dictate, especially in the short run.

Third, most of the sovereign wealth funds (a key source of index-fund activity) are commodity-based. Therefore, when commodity prices increase, the value of these funds goes up, in turn increasing their expo-sure to commodities.

Fourth, the large size of these funds compared to commodity markets may exacerbate price move-ments as well. While there are no precise estimates on their size, a broadly accepted range, as of mid-2008 was US$ 250–300 billion (Masters 2008). A report by a major commercial bank estimated that an addi-tional US$ 60 billon went into commodities during 2009, placing the 2009 total estimate to US$ 230–240 billion, marginally lower than in 2008 due to lower commodity prices. A more recent estimate by a major investment bank (october 2010) placed the estimate at US$ 350 billion. In view of the recent spike, it may have exceeded US$ 400 billion. Almost two-thirds of those funds are invested in energy markets. Although these amounts represent a little more than 1 percent of the global value of pension and sovereign wealth fund holdings in 2009 (the global value of these two groups was estimated at US$ 20 trillion and US$ 4 tril-lion) they are large compared to the size of commodity markets. or, as Soros characteristically put it, “… the institutions are piling in on one side of the market and they have sufficient weight to unbalance it”.

Tentative ConclusionIn the context of the post-2005 commodity price boom, the question is often formulated as to whether “spec-ulation” was behind the commodity price increases. There are two problems with the way in which the question is posed. Firstly, among the numerous types


of speculation often discussed in the literature, only one matters: investment-fund activity in commodity futures exchanges. Second, it is unlikely that even this type of activity would have a monotonic (i.e., increasing) impact on commodity prices.

Thus, the question should be reformulated along the following lines. “Is investment fund activity partly responsible for post-2005 commodity price move-ments?” A likely answer to this question could be: “Any commodity-related activity on the financial side is unlikely to alter long-term price trends, which will

ultimately be determined by market fundamentals. But, such activities can induce higher price variability in the sense of exacerbating the length and the ampli-tude of price cycles.”

Notes1. John Baffes, 8–1880, [email protected], June

1, 2011.2. haigh, and Robe (2010) and Commodity Futures

Trading Commission (2008).


South Asian Food Demand and Supply Balances

Afghanistan: Grain production for 2010 is projected to be about 11 percent lower than in 2009, resulting from a drop in wheat production, from 5.1 million tons to 4.5 million tons. Afghanistan is therefore likely to face a wheat deficit of at least 1 million tons this year, with more details emerging toward the end of the growing season that runs to April. Nevertheless, the deficit is expected to be roughly twice that of the annual average of about 0.5 million tons over the past decade, although it has reached 2.3 million tons.

Bangladesh: Total rice production rose from 26.2 million tons in fiscal 2008 to 32.1 million tons in 2010. Aggregate rice (paddy) output in 2009 reached a record 50 million tons. For 2010, the output of (irri-gated) main season rice is 28.5 million tons, or 3 percent above last year’s level. The winter wheat crop has also been good, with production at 1 million tons. Total wheat production has risen from 7.4 million tons in fiscal 2006 to 8.5 million tons in 2010. Despite this, rising grain consumption has led to an increasing need for imports. Bangladesh is likely to require higher grain imports this year above the 3 million tons of recent

years to be able to retain public stocks at their target level of 1.5 million tons. Wheat imports have been high, reaching 1.8 million tons, which is double the level of domestic production. The Bangladesh govern-ment has been issuing tenders and buying relatively small shipments. The government is reportedly plan-ning to purchase about 1 million tons by end-June 2011, but it has decided not to buy domestically in order to avoid pressure on prices (Table A3.1).

India: Food-grain production suffered a significant set-back following the 2009 shortfall in monsoon rains, but recovered well with the near-normal 2010 monsoon. The estimate for fiscal 2011 pegs output at around 232 million tons, about 6.4 percent above that for 2010. Despite the good 2010 monsoon, production is estimated to have been lower in fiscal 2011 than the recent record in fiscal 2009. At the same time, grain stocks (mainly rice and wheat) reached 40–50 million tons, which far exceeds secure storage capacity. Food grain output increased by only 1.6 percent in fiscal 2009, and is estimated to have declined by 7 percent in 2010. Wheat is a winter crop and was not strongly

3Annex

TABLE A3.1 Bangladesh: Production and Imports of Food Grain

Production (million MT) Import (million MT)

FY08 FY09 FY10 FY11 FY08 FY09 FY10 FY11

Actual Actual Actual Target Estimate Actual Actual Actual TargetActual

(Till Mar 13, 2011)

Rice 28 .9 30 .9 32 .3 35 .4 … 2 .1 0 .6 0 .1 1 .3 1 .2

Aus 1 .5 1 .9 1 .7 2 .7 2 .1 … … … … …

Aman 9 .7 11 .2 12 .2 13 .5 12 .8 … … … … …

Boro 17 .8 17 .8 18 .3 19 .2 … … … … … …

Wheat 0 .8 0 .8 1 .0 1 .2 … 1 .4 2 .4 3 .4 2 .4 2 .3

Total 29 .8 31 .7 33 .2 36 .5 … 3 .5 3 .0 3 .5 3 .8 3 .4

Source: BBS, DAE, and FPMU


affected by the monsoon shortfall in 2009. Production in fiscal 2010 actually increased slightly above that of 2009, and may have increased by close to 1 percent in 2011, to a new record 81.5 million tons (Table A3.2).

Nepal: The principal staple food is rice, which comprises two-thirds of total cereal consumption, with wheat constituting another 12–15 percent. In general, the price of rice is influenced by production and demand on the domestic side and policy decisions by India. As a net rice importer for most of the last two decades, Nepal has relied heavily on imports—both formal and informal—from India, despite India’s occa-sional export bans. Because of Nepal’s long and largely unregulated border with India, price levels in Nepal are highly correlated with those in India. even during India’s rice export ban, quantities imported from India were not notably affected. Because food availability and access in Nepal are geographically very unevenly distributed, the concept of national food security has little meaning. Rice consumption varies from region to region, because certain remote areas tend to be rice-deficient and people substitute with wheat.

Pakistan: Wheat production for fiscal 2011 is projected to be 23.9 million tons, about the same as in 2010. however, due to an estimated increase in consump-tion of 1 million tons, ending stocks are likely to be lower; nevertheless, at 9 million tons they are at the level envisaged for the strategic reserve, and the govern-ment has lifted the ban on exports. Despite a sharp decline in rice production resulting from flood damage to 34 percent of the growing area, Pakistan is expected to have an exportable surplus of 1.5–2.0 million tons, from production of 5 million tons.

Sri Lanka: The supply of key food items such as fish, poultry and vegetables continues to be disrupted by the effects of adverse weather conditions leading to sharp price pressures. The weather is also of concern with respect to the forthcoming spring crop, with lower supplies possibly raising prices and main-taining food inflation at 10 percent for the first half of 2011.

TABLE A3.2 India: Agricultural Production, 2003–11(in million tons unless otherwise specified)

2003–04 2004–05 2005–06 2006–07 2007–08 2008–09 2009–10 2010–11

Foodgrains 213 .2 198 .4 208 .6 217 .3 230 .8 234 .5 218 .1 232 .1

Rice 88 .5 83 .1 91 .8 93 .4 96 .7 99 .2 89 .1 94 .0

Wheat 72 .2 68 .6 69 .4 75 .8 78 .6 80 .7 80 .8 81 .5

Coarse Cereals 37 .6 33 .5 34 .1 33 .9 40 .8 40 .0 33 .6 40 .1

Pulses 14 .9 13 .1 13 .4 14 .2 14 .8 14 .6 14 .7 16 .5

Oilseeds 25 .2 24 .4 28 .0 24 .3 29 .8 27 .7 24 .9 27 .9

Sugarcane (million bales)

233 .9 237 .1 281 .2 355 .5 348 .2 285 .0 292 .3 336 .7

Cotton (million bales)

13 .7 16 .4 18 .5 22 .6 25 .9 22 .3 24 .2 33 .9

Jute & Mesta (million bales)

11 .2 10 .3 10 .8 11 .3 11 .2 10 .4 11 .8 10 .1

Memo item:

Procurement by FCI (wheat+rice)

40 .3 40 .3 38 .0 36 .2 51 .6 60 .4 54 .9 …

Procurement by FCI (% of production)

25 .1 26 .6 23 .6 21 .4 29 .4 33 .6 32 .3 …

Source: Ministry of Agriculture, Government of India.


Impact on Poverty of the Increase in Food Prices – Methodology and More Results

The MoDeL INCoRPoRATeS A SeT oF observed and estimated changes in domestic agricultural and food prices for the South Asia

region countries.2 Where available, the model includes country-level data on actual changes in domestic food prices from Food Price Watch (World Bank, 2011). For other commodities, where prices are unavailable, we use import shares reported in version 7 of the GTAP database3 to link global prices with domestic consumer prices.4

We then calculate their implications for individual households’ costs of living and agricultural incomes using an expenditure function to characterize house-hold consumption, and factor in supply behavior and a profit function to represent household production activities through unincorporated enterprises such as family farms.5 Based on the simulated changes in indi-vidual households’ welfare relative to the US$ 1.25 extreme poverty line, we determine the changes in the poverty headcount and poverty gap for each country.6 essentially, this involves estimating the impact of price changes on each household’s real income by multi-plying the price change experienced by the household by the quantity of the good produced and by the nega-tive of the quantity consumed by that household.7 The model also allows for households to substitute away from commodities where prices increased.8

Impact of the Current food Price Hike

The median increase in the poverty headcount and poverty gap for South Asia region is 1.4 percentage points and 0.5 percentage points, respectively. In India and Nepal the increase in the poverty headcount is less than the median while Bangladesh’s and Pakistan’s are above, with Sri Lanka’s at the median. For the impact

on the poverty gap, in Nepal, Pakistan and Sri Lanka, the increase in the poverty gap is less than the median while the opposite is true for Bangladesh and India. except for Nepal, the net change in the poverty head-count is greater than the impact on the poverty gap. Pakistan experiences the highest net percentage increase in the poverty headcount whereas Bangladesh experi-ences the highest percentage increase in the poverty gap due to the food price increase. Nepal faces the least net change in poverty headcount or poverty gap amongst South Asia region countries.

Across all the South Asia region economies, the median of people exiting poverty is 0.06 percent while those entering poverty are 1.49 percent. of the coun-tries, although Bangladesh has the largest percentage change of individuals exiting poverty with the food price hike, it also has the greatest percentage of indi-viduals moving below the poverty line. Pakistan has no percentage change in the number of people exiting poverty.

The current food price surge has had a varying impact on the poverty headcount of South Asia region countries according to the magnitude of the price increase for each of the commodities and the consump-tion and income pattern generated by the sale of these commodities. The increase in rice price had the greatest impact on the rise in the poverty headcount and for the entire South Asia region. This is followed by wheat, then fats and oils (Figure A4.1).

In Bangladesh, where rice and wheat prices rose substantially, the rice price increase had the higher impact on the increase in the poverty headcount, since it has higher weighting on households’ net consump-tion. In addition, Bangladesh is a net seller of wheat, to the extent that an increase in the wheat price resulted in 0.02 percent decrease in the poverty head count.

In Pakistan, people are net consumers of wheat and wheat has higher weighting than rice in the

1

4Annex


consumption basket. Therefore, even though the increase in the domestic rice price is higher than that of wheat, the impact of the poverty headcount is attrib-utable more to higher wheat prices.

In India, the price increase in fats and oils contrib-uted to 58 percent of the increase in the poverty head-count, while in Sri Lanka the rise in the sugar price had the highest impact on the increase in the poverty headcount. Furthermore, although an increase in the price of rice has had the greatest impact on the gross reduction in poverty in India, since the country is net consumer of rice, there is an increase in the poverty headcount when rice prices rise.

on average across the region, the increase in the rice price accounted for most of the increase in the

poverty gap, most notably Bangladesh (86 percent of the increased gap) and India (39 percent) across all commodities. In Nepal, 59 percent of the increase in the poverty gap is attributed to the rise in oil and fats while in India it is 38 percent. As in the increase in the poverty headcount, wheat has the highest impact in Pakistan (69 percent) and sugar in Sri Lanka (45 percent) (Figure A4.2).

In the case of Afghanistan, the model is unable to estimate the impact of price changes on each house-hold’s real income because an estimate of the quantity of goods produced by each household is unavailable. Instead the model estimates the net change in food consumption from the increase in price, as observed through household consumption data. From this anal-ysis, Afghanistan appears to have been particularly hard hit by the increase in wheat prices. Wheat is the main staple of the Afghan diet, contributing 57 percent of the caloric content in the average bundle of food items consumed by the poor and near-poor. Furthermore, due to large fluctuations in weather and insecurity, wheat production is highly volatile and the country is dependent on its trading partners to meet frequent shortfalls. Analysis of the 2008 food price crisis sheds insight into the poverty impact in Afghanistan.9 The 2008 food price increases corresponded with a drought year resulting in wheat prices essentially doubling in rural and urban areas. This increase in wheat prices had large effects on overall wellbeing. The doubling in wheat prices resulted in an average decline of 20 percent in the real value of food consumption. With many people consuming at levels near the poverty line, subtracting from total consumption an amount equal to 20 percent of food consumption implied a 12 percentage point rise in poverty.

Notes1. This annex is based on Ivanic, Martin and Zaman

(2011), Estimating the Short-Run Poverty Impacts of the 2010–11 Surge in Food Price”, World Bank Policy Research Working Paper 5633.

2. The actual and imputed price change for the following commodities is collected for the South Asia region countries: wheat, maize, rice, other grains, beef, sugar, fruits, coffee, cotton and oils and fats.

3. See hertel (1997).4. Note that the model focuses on the commodities

where actual price change or imputed price (based on imports) for the South Asia region countries exists. The

FIGuRE A4.1 Decomposition of Net Poverty Headcount Change by Commodity

Perc

enta

ge p

oint

s

–0.50

0.00

0.50

1.00

1.50

2.00


Wheat Oils and fats Sugar Rice Beef


FIGuRE A4.2 Decomposition of Net Poverty Gap Change by Commodity

Perc

enta

ge p

oint

s


Wheat Oils and fats Sugar Rice Beef

–0.10

0.10

0.30

0.50

0.70

0.90

1.10

1.30

1.50


Annex 4. Impact on Poverty of the Increase in Food Prices – Methodology and More Results 75

model accounts for price changes for the majority of the food items.

5. Singh, Squire and Strauss (1986); and Deaton (1989).6. We use the definition of Foster, Greer and Thornbecke

(1984).7. See Deaton (1989) for a justification of this approach.8. We do this by introducing constant difference of elas-

ticities (CDe) demand system parameters to allow us

to capture the second-order impacts of price changes on households’ real incomes (hanoch, 1975). Note that this approach is consistent with imported goods being imperfect substitutes for domestically-produced goods, and the changes in domestic prices being a weighted average of the prices of imported and domestic goods.

9. See D’Sousa and Jolliffe (2010).


Selected Food Crisis Response Projects

5Annex


Coun

trySo

cial

saf

ety

nets

to fo

r vul

nera

ble

grou

psM

easu

res

put i

n pl

ace,

with

Wor

ld B

ank

supp

ort,

durin

g th

e la

st fo

od c

risis

Coun

try-s

peci

fic le

sson

s le

arne

d fro

m th

e la

st fo

od c

risis

Reco

mm

ende

d ne

xt s

teps

Afg

hani

stan

No

publ

ic s

afet

y ne

ts fo

r the

poo

r . Ca

sh

trans

fers

exi

st fo

r fam

ilies

of m

arty

rs a

nd

war

-rela

ted

disa

bilit

ies,

alo

ngsi

de in

-kin

d fo

od

aid

prog

ram

s .

A pi

lot s

afet

y ne

t pro

gram

, usi

ng a

com

-m

unity

+ g

eogr

aphi

c ta

rget

ing

appr

oach

is

bein

g pu

t in

plac

e in

resp

onse

to th

e fo

od

cris

is . T

he W

orld

Ban

k su

ppor

ts th

is e

ffort

by th

e sa

fety

net

com

pone

nt o

f the

Pen

-si

ons

and

Safe

ty N

et p

roje

ct . T

he s

afet

y ne

t pi

lot i

s ex

pect

ed to

be

scal

ed u

p, in

corp

orat

-in

g le

sson

s le

arne

d fro

m th

e pi

lot .

1 . T

imel

y m

onito

ring

and

eval

uatio

n is

crit

ical

. A s

cale

up

of th

e pi

lot

proj

ect w

ill in

corp

orat

e th

e re

sults

of

the

eval

uatio

n .2 .

Wea

k co

ordi

natio

n am

ong

rela

ted

(sm

all s

cale

) pro

gram

s cr

e-at

es o

bsta

cles

for e

ffect

ive

serv

ice

deliv

ery .

Dev

elop

men

t of a

wel

l-adm

in-

iste

red

and

targ

eted

saf

ety

net

syst

em .

Bang

lade

shEm

ploy

men

t Gen

erat

ion

Prog

ram

(wor

kfar

e);

Soci

al p

ensi

ons

(for d

isab

ility,

wid

ows

and

the

elde

rly);

Vuln

erab

le G

roup

Dev

elop

men

t pro

vide

s 30

kg

bags

of r

ice

for 2

4 m

onth

s to

poo

r wom

en .

Vuln

erab

le G

roup

Fee

ding

sch

eme

prov

ides

m

onth

ly fo

od ra

tions

to h

ouse

hold

s af

fect

ed

by d

isas

ters

and

lack

ing

agric

ultu

ral l

and

and

prod

uctiv

e as

sets

.Fa

ir Pr

ice

Ratio

n Ca

rd s

chem

e di

strib

utes

ca

rds

to p

oor h

ouse

hold

s en

ablin

g pu

rcha

se

of 2

0 kg

bag

s of

rice

or w

heat

/mon

th a

t a

redu

ced

rate

.O

pen

Mar

ket S

ales

pro

gram

pro

vide

s ric

e to

ru

ral a

nd u

rban

are

as, e

spec

ially

in D

haka

—en

-ab

ling

anyo

ne to

buy

up

to 5

kg

of s

ubsi

dize

d ric

e ea

ch d

ay .

Oth

er p

rogr

ams

incl

ude

Rura

l Em

ploy

men

t an

d Ro

ad M

aint

enan

ce P

rogr

am; F

ood

for

Wor

k, T

est R

elie

f, H

ill Tr

act A

rea

Dev

elop

-m

ent,

and

Food

for E

duca

tion

and

Gra

tuito

us

Relie

f .

Bank

hel

ped

mod

ify a

nd s

uppo

rt by

loan

a

prog

ram

form

erly

cal

led

the

“100

-day

em

-pl

oym

ent p

rogr

am” .

The

revi

sed

prog

ram

en

title

d Em

ploy

men

t Gen

erat

ion

Prog

ram

fo

r the

Poo

rest

will

be m

ore

resp

onsi

ve to

fu

ture

cris

es .

Also

, a R

SR-fu

nded

con

ditio

nal c

ash

trans

fer

pilo

t aim

ed a

t pro

mot

ing

educ

atio

n an

d nu

tritio

n of

chi

ldre

n fro

m e

xtre

mel

y po

or

fam

ilies

in ru

ral a

nd u

rban

are

as .

Cris

es m

ay p

rese

nt o

ppor

tuni

ties

to in

itiat

e m

uch-

need

ed re

form

s in

th

e so

cial

pro

tect

ion

sect

or .

The

deve

lopm

ent a

soc

ial p

rote

c-tio

n st

rate

gy o

utlin

ing

a co

here

nt

soci

al p

rote

ctio

n sy

stem

that

ad

dres

ses

prog

ram

ratio

naliz

atio

n,

and

adm

inis

tratio

n ch

alle

nges

(e .g

., a

unifi

ed ta

rget

ing

syst

em, e

ffec-

tive

paym

ent m

echa

nism

s, a

nd a

na

tiona

l ben

efici

ary

regi

stry

) .

Indi

aRa

nge

of s

afet

y ne

t pro

gram

s in

clud

es

prov

isio

n of

sub

sidi

zed

food

, in-

kind

tran

sfer

s (e

.g .,

scho

ol fe

edin

g), p

ublic

wor

ks, a

nd c

ash

trans

fers

suc

h as

soc

ial p

ensi

ons

for e

lder

ly,

wid

ows,

dis

able

d; h

ousi

ng; s

chol

arsh

ips,

and

re

cent

ly in

trodu

ced

soci

al in

sura

nce

(e .g

., RS

BY—

subs

idize

d he

alth

insu

ranc

e), a

nd

subs

idize

d ru

ral c

redi

t . St

ate-

leve

l pro

gram

s in

clud

e ta

rget

ed w

elfa

re d

istri

butio

n an

d im

plem

enta

tion

of a

nat

iona

l tar

gete

d pu

blic

di

strib

utio

n sy

stem

.

The

Bank

was

not

ask

ed to

wor

k w

ith th

e G

over

nmen

t to

resp

ond

spec

ifica

lly to

the

last

food

cris

is .

—Th

ere

stre

ngth

enin

g of

sys

tem

s fo

r id

entifi

catio

n, ta

rget

ing,

aw

aren

ess

gene

ratio

n an

d be

nefit

pay

men

t so

that

saf

ety

net p

rogr

ams

can

effe

ctiv

ely

targ

et th

e po

or in

tim

es

of d

isas

ters

.

(con

tinue

d on

nex

t pag

e)

Annex 5. Selected Food Crisis Response Projects 79

Coun

trySo

cial

saf

ety

nets

to fo

r vul

nera

ble

grou

psM

easu

res

put i

n pl

ace,

with

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deve

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incl

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; sin

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ce; a

nd p

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prog

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o su

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mod

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gove

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deve

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t sys

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stan

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incl

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edia

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lope

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resp

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to

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st 2

010

flood

s: in

thre

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onth

s, th

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vern

men

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aged

to

sup

port

1 .3

milli

on fa

milie

s w

ith c

ompe

nsat

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gran

ts . T

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st

ruct

ures

nee

d to

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cons

olid

ated

an

d m

ade

appl

icab

le to

futu

re

emer

genc

y re

cove

ries .

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gov

ern-

men

t is

prep

arin

g an

act

ion

plan

for

such

a s

yste

m .

Sri L

anka

An u

ncon

ditio

nal c

ash

trans

fer p

rogr

am,

Sam

urdi

, aim

s to

pro

vide

ass

ista

nce

to th

e po

or .

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ld B

ank

was

not

ask

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gove

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st fo

od c

risis

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-er

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ess,

the

Bank

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aged

to in

itiat

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d ca

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rwar

d a

dial

ogue

thro

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an R

SR-

fund

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rant

on

refo

rmin

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e ta

rget

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mec

hani

sm o

f Sam

urdi

and

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ting

it, a

long

w

ith a

n M

IS s

yste

m s

uppo

rted

by a

n ID

F, to

im

prov

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th ta

rget

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and

adm

inis

tratio

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wev

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ttem

pt to

pu

t in

plac

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cont

rols

in 2

008 .

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ing

trust

and

ens

urin

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int

deci

sion

mak

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in e

very

ste

p of

th

e w

ay w

ith c

ount

erpa

rts a

re

esse

ntia

l to

desi

gnin

g su

stai

nabl

e in

terv

entio

ns .

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incr

ease

of t

he s

afet

y ne

t co

vera

ge in

the

Nor

ther

n Pr

ovin

ce,

and

impr

ove

targ

etin

g of

Sam

urdi

.


Commodity Risk Management1

EVeNTS IN ReCeNT YeARS hAVe hIGh-lighted that governments face significant fiscal risk from exogenous shocks. The fuel and food

crises of 2007–08, and subsequent price increases in 2010, as well as the greater economic impact of natural disasters in populated areas, have a demonstrated nega-tive impact on public finances and the availability of resources for development priorities and essential public services. For many of these risks, market-based approaches may help governments mitigate the finan-cial impact of these shocks. But in practical terms, typi-cally, there are several constraints, including:

Governments typically do not focus on ex ante management of food/oil price shocks and on assessing the risk as a contingent liability with fiscal implications.

Interactions between public and private actors operating within food import/export supply chains are complex. Since price volatility affects different actors in different ways, there needs to be a range of solutions, ranging from fiscal responses to trading decisions to social safety net responses targeted directly to vulner-able producers or consumers. Identifying specifically who is at risk is an important first step.

• Governments may not have funds to cover hedging costs, which, in the case of the purchase of at-the-money option contracts (which create a price cap or a price floor), can range from 7–12% of the price level protected.

• If funds are available, governments are often reluctant to make the investment in hedging since such decisions are vulnerable to ex-post criticism (and associated political risk).

• Governments may lack the necessary legal and institutional frameworks to support hedging transactions.

• There may also be a lack of technical capacity to manage hedging programs.

Since many member countries are vulnerable to the risk of food and fuel price shocks, the World Bank Group is scaling up assistance in this area in an effort

to a) sharpen the ability to diagnose the fiscal impact of exogenous shocks, b) incorporate the use of financial products into risk management strategies that are put in place ahead of a crisis or shock, and c) strengthen confidence in using market approaches and having sound policy around them.

Advisory Services on Risk ManagementThese customized technical assistance services can be designed to help governments evaluate exposure to and find ways to manage a wide set of fiscal risks and contingent liabilities associated with exogenous shocks such as natural disasters, commodity price shocks (in particular food, fertilizer, and energy), and climate change. The main components of a commodity risk management advisory program can include:

a. Risk assessment to quantify the impact of specific risks on a government’s balance sheet and fiscal flows

b. Development of a risk management framework, which includes specifying objectives of a risk management strategy, analyzing the govern-ment’s capacity to absorb risk, and evaluating strategic alternatives

c. Cost/benefit comparison of available instru-ments, approaches, and hedging strategies

d. Developing an enabling environment to imple-ment transactions, which include governance and legal framework, coordination with other policies, information systems, public disclosure and audit processes, and monitoring procedures

e. education and capacity building of ministry staff, stakeholders, and decision-makers.

Facilitation of Commodity HedgesBecause of the complexity of local market and policy environments, solutions will need to be highly custom-ized, drawing on a mix of different tools and responses.

Annex6


Commodity hedging for governments and private sector entities could be facilitated by:

a. Providing assistance to help governments and private sector entities structure and execute phys-ical hedging transactions with existing market suppliers, and/or banks (for example for food products that are not well integrated with inter-national exchanges, such as rice, edible oils, and for fertilizer)

b. Intermediation of financial commodity hedges (for example for oil/energy products and exchange-traded commodities).

The following table summarizes various commodity risk management instruments, along with benefits and costs/risks/constraints for each. Also included is a short description of the government of Malawi’s approach to hedging the risks associated with the price and supply of maize.

Example – Malawi Government Hedging of Maize Price & Supply RisksIn 2005/06, Southern Africa experienced a severe drought-related food shortage. Affected coun-tries included Malawi, Zambia, Mozambique, and Zimbabwe and it was estimated that the volumes of imports needed to supply these countries would range from 1.5–2 million metric tons. In the past, Governments have attempted to manage this problem by subsidizing the price of maize but such responses tend to have a large cost both financially and in terms of negative impact on local and regional trade.

In June of 2005, the Government of Malawi announced that it would take an innovative approach to management of the food shortage by using South Africa exchange Market (SAFeX)-based instruments to help cap the cost. The World Bank provided tech-nical assistance to support this operation. This included training on futures and options and how the products could be used to manage specific exposures, risk assess-ment, communication with potential market providers, comparison of proposals, negotiation of contracts, and overall implementation.

Because the government was concerned not only about price increases but also about logistics constraints and delivery performance, the call option contract was

customized as an oTC (“over-the-counter”) contract which would give more flexibility than a standard finan-cial instrument. First, price protection was provided on a delivered basis, thus combining the price for white maize on the exchange in South Africa (SAFeX price) plus transport costs to Malawi. Second, the option contract carefully specified terms for physical settle-ment so that it could be used as a contingent import strategy if needed. Uncertainty about the extent of the food shortage, levels of commercial imports, trans-portation constraints, performance of local traders, the humanitarian response, and efficiency of procure-ment processes made the contingent import aspect of the contract very attractive to the Government. The contract with Standard Bank of South Africa, an oTC call option, represented one of the first-ever instances of macro level hedging by an African government. It covered imports of 60,000 mt of white maize, had a total value of approximately $17 million, and a premium payment of $1.53 million.

In November and December, 2005 as prices were increasing and the food shortage growing more severe, the government exercised the call option, elected for physical settlement, and allocated the majority of the maize to humanitarian operations. The maize purchased through the option contract had a better delivery performance than most other procurement procedures, and during the delivery period spot prices rose USD $50–90/mt above the ceiling price of the contract following increases in the SAFeX white maize price and transport costs over the period october–January. In May of 2006 and 2007, when the country was facing a projected maize surplus, the World Bank worked with the private sector to structure contin-gent export contracts, which were presented to the Government. The contingent export contracts (put options) were structured to help manage concerns about allowing exports and the risk of maize prices falling. Although the contracts were not taken up, they were useful as a demonstration of how contin-gent contracting could be used to help manage risks associated with maize surplus.

This approach has a number of indirect advan-tages in addition to the hedging benefits. Contingent import strategies based on call option structures help in planning because they can be put in place well ahead of eventual crises, then triggered or “called” on an as-needed basis. The approach showed the bene-fits of using customized risk management solutions to reduce the risk of increasing commodity prices and

Annex 6. Commodity Risk Management1 83

supply uncertainty. It also demonstrated that market-based strategies can be less costly and more efficient than non-market based attempts to stabilize prices. For the Government of Malawi, which spent an esti-mated $110 million on the humanitarian response, the call option was a success. The challenge will be to test similar market-based approaches in an effort

to replace traditional ex post reactions which can be costly, inefficient, and difficult to manage when the country is already in crisis.

Notes1. Prepared by Julie Dana,World Bank Treasury.


TABLE A6.1 Overview of Commodity Risk Management InstrumentsProduct Benefits Costs/Risks/Constraints

Forwards • Since forwards are physical supply contracts, the risk management solution is embedded in the supply contract and there is no need for a separate contract / documenta-tion .

• Pricing of forward contracts can be customized to the needs of the hedger—prices can be fixed, floating, or in-clude caps/floors, and collars (a pre-agreed range or band) .

• Depending on the pricing formula used, forwards will have same benefits as the financial products described below .

• May be complex for entities to implement if not directly involved in physical importing .

• Depending on the pricing formulas used, forwards will have same costs/risks/constraints as the financial products described below .

Futures • No upfront costs .• Provides ability to lock in forward prices through a finan-

cial contract .

• Prices are “locked in” and hedger has limited ability to take advantage of positive price movements that may occur in the future .

• Creates unknown and unpredictable future liability since hedger will owe the market counterparty if the market moves in an adverse direction .

• Requires financing of a credit line or a credit guarantee .• Requires managing cash flow /liquidity requirements to support

(potential) daily margin calls .

Options • Provides ability to lock in maximum (minimum) prices while still providing hedger with ability to take advantage of positive price movements that may occur in the future .

• Has an upfront cost, which is market-driven and volatile but can range from 5–12% of the value of the underlying price for a 6–18 month coverage .

Swaps • No upfront costs .• Can be used to create similar price protection as with

futures contracts• Provides ability to manage two commodity exposures, or

financial flows, at the same time .

• Creates unknown and unpredictable future liability .• Requires financing of a credit line or credit guarantee .• Requires managing cash flow requirements to support (poten-

tial) daily margin calls .

Commodity-linked bonds or loans

• Could be used on more macro level to connect borrowing or financing programs to the performance of a specific commodity index .

• Can be more complex to structure .• May not be effective as a hedge for specific commercial

exposures .

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