Managing AgriculturalProduction Risk Innovations in Developing Countries

Agriculture and Rural Development Department

REPORT NO. 32727-GLB

THE WORLD BANK

Agriculture & Rural Development DepartmentWorld Bank1818 H Street, N.W.Washington, D.C. 20433http://www.worldbank.org/rural

Managing

AgriculturalProduction

Risk

THE WORLD BANKAGRICULTURE AND RURAL DEVELOPMENT DEPARTMENT

Managing AgriculturalProduction Risk Innovations in Developing Countries

2005 The International Bank for Reconstruction and Development / The World Bank1818 H Street, NWWashington, DC 20433Telephone 202-473-1000Internet www.worldbank.org/ruralE-mail ard@worldbank.org

All rights reserved.

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iii

A C R O N Y M S A N D A B B R E V I AT I O N S vii

P R E FA C E A N D A C K N O W L E D G M E N T S ix

E X E C U T I V E S U M M A RY xi

Introduction 1

Risk and Risk Management in Agriculture 5Informal Mechanisms 6Formal Mechanisms 8

Approaches to Agricultural Risk in Developed Countries 11Crop Insurance Programs in Developed Countries 11Why the Experience of Developed Countries is not a Good Model

for Developing Countries 14

Innovation in Managing Production Risk: Index Insurance 15Index Insurance Alternatives 15Basic Characteristics of an Index 15Relative Advantages and Disadvantages of Index Insurance 17The Trade-off Between Basis Risk and Transaction Costs 17Where Index Insurance Is Inappropriate 17

0 New Approaches to Agricultural Risk Management in Developing Countries 21

Role of Government 21Policy Objectives 23Constraints in Agricultural Risk Management 24Risk Principles: Layering and the Role of Index Insurance 25Addressing the Market Insurance Risk Layer 26Market Failure Layer 29

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3

2

1

Contents

Policy Instruments 30Index Insurance as a Source of Contingent Funding

for Government Disaster Assistance and Safety Net Programs 32

From Theory to Practice: Pilot Projects for Agricultural Risk Transfer in Developing Countries 35

Nicaragua: A Seven-Year Incubation Period 36Morocco 38India: Private Sector Led Alternative Agricultural Risk

Market Development 39Ukraine 41Ethiopia: Ethiopian Insurance Corporation and Donor Led Ex Ante

Disaster Risk Management 43Malawi and SADC: Weather Risk Transfer to Strengthen Livelihoods

and Food Security 47Peru: Government Led Systemic Approach to Agricultural

Risk Management 48Mongolia: World Bank Contingent Credit for Livestock Mortality

Index Insurance 49Global Strategy: The Global Index Insurance Facility (GIIF) 51

Potential Roles for Governments and the World Bank 53Government Roles 53World Bank Roles 54

R E F E R E N C E S 59

Appendix 1: Weather Risk Management for Agriculture 63The Financial Impact of Weather 63The Weather Market 64Weather Risk and Agriculture 65Structuring a Weather Risk Management Solution 67Valuing Weather Risk 74Weather Data 79Further Reading 81References 81

Appendix 2. Case Studies of Agricultural Weather Risk Management 83Indexed-based Insurance for Farmers in Alberta, Canada:

The AFSC Case Study 83Alternative Insurance Through Weather Indices in Mexico:

The Agroasemex Case Study 85Weather Insurance for Farmers in the Developing World:

Case Studies from India and Ukraine 90Technology Application Case Studies: Grassland Index Insurance

Using Satellite Imagery 107References 108

N O T E S 111

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iv Contents

Contents v

Tables2.1 Risk Management Strategies in Agriculture 8

4.1 Advantages and Disadvantages of Index Insurance 18

5.1 Risk Transfer Strategies 28

6.1 Summary of Case Studies 36

6.2 Reasons for Buying Weather Index Insurance in India 43

A2.1 Options for CHU Contracts 85

A2.2 Total Liability Factored into the Agroasemex Business Plan for Autumn-Winter 20012002 86

A2.3 Summary of the Methodology to Calculate the Eleven FCDD Indices 87

A2.4 Comparative Analysis Between the Observed Historical Severity Indices (indemnities/total liability) and the Estimated Severity Indices for the Crops and Risks Selected 88

A2.5 Specifications of Call Option Structures Considered by Agroasemex 89

A2.6 Estimated Commercial Premium for Weather Derivative Structures (in US$) 90

A2.7 Weather Insurance Contracts Offered to Groundnut and Castor Farmers 94

A2.8 Pilot Statistics, 2003 95

A2.9 Payout Structure Per Acre for Groundnut Weather Insurance Policy for Narayanpet Mandal, Mahahbubnagar District (2004) 96

A2.10 Payout Structure Per Acre for Castor and Groundnut Excess Rainfall WeatherInsurance Policy for Narayanpet, Mahahbubnagar 97

A2.11 Relationship Between SHR and Winter Wheat Yields During the Vegetative Growth Phase of Plant Development 101

A2.12 Relationship Between SHR and Financial Losses Associated with Winter Wheat Yield Fluctuations 102

A2.13 Correlation Coefficients for the Interannual Variability of Cumulative Rainfall, Average Temperature, and the SHR Index Measured at Five UHC Weather Stations in Kherson 103

Boxes2.1 Asset-Based Risk Management 7

5.1 Reinsurance 22

6.1 India Impact Assessment 42

7.1 Examples of Potential World Bank Investment Lending Projects to Facilitate Risk Management 57

Figures2.1 Independent Versus Correlated Risk 9

3.1 Crop Insurance Premiums and Indemnities in the United States 12

4.1 Payout Structure for a Hypothetical Rainfall Contract 16

5.1 Framework for Governmental Agricultural Risk Management Policy Formulation 23

5.2 Average April to October Rainfall for Thirteen Malawi Weather Stations 26

5.3 Histogram of Simulated SADC Drought Events 29

5.4 Government-Sponsored DOC as Risk Transfer Product Between National and International Risk Markets 30

7.1 Potential Impacts of Natural Hazards 54

A1.1 Notional Value of All Weather Contracts in US$ 65

A1.2 Percentage of Total Weather Contracts by Location (excluding CME trades) 66

A1.3 Potential End User Market by Economic Sector 20032004 66

A1.4 Call Option Payout Structure and Wheat Growers Losses 72

A1.5 Collar Payout Structure and Agrochemical Companys Deviation from Budgeted Revenue 73

A1.6 Schematic of Historical Revenues of a Business and the Impact of Weather Hedging 78

A2.1 Relationship Between the Daily Rate of Development of Corn Minimum and Maximum Temperatures 84

A2.2 Comparative Accumulated Distribution Probability Function Based on a Probability of Exceedence Curve for the Historical and Modeled Results (payouts in US$) 89

A2.3 Mahahbubnagar District Groundnut Yields Versus Groundnut Rainfall Index 93

A2.4 Payout Structure of Groundnut Weather Insurance Policy Held by Farmers with Small, Medium, and Large Land Holdings 94

A2.5 Payout Structure of Groundnut Weather Insurance Policy for Narayanpet Mandal, Mahahbubnagar District, 2004 97

A2.6 An Example of the Marketing Leaflet for Groundnut (DGN), Castor (DCN), and Excess Rainfall (EN) Protection in Narayanpet Mandal, MahahbubnagarDistrict, 2004 98

A2.7 Winter Wheat Yields for Kherson Oblast, 19712001 100

A2.8 Cumulative Rainfall and Average Temperature for Behtery Weather Station for April 15 to June 30, 19732002 104

A2.9 SHR Index for Behtery Weather Station, 19732002 105

A2.10 Sample Contract for Behtery Weather Station 106

vi Contents

vii

ACP Africa-Caribbean-Pacific

APF Agricultural Policy Framework of Canada

APH actual production history

ARD Agriculture and Rural Development Department of the World Bank Group

BASIX Livelihood Promotion and Microfinance entity of Andhra Pradesh

BIP base insurance product

BSFL Bhartiya Samruddhi Finance Limited (part of BASIX)

CAIS Canadian Agricultural Income Stabilization

CAT catastrophe

COFIDE Corporacin Financiera de Desarollo S.A. (Development Finance Corporationlocated in Lima, Peru)

CRDB Cooperative and Rural Development Bank Limited, a private commercial bank

CRMG Commodity Risk Management Group (ARD, The World Bank)

DECRG Development Economics Research Group of The World Bank

DOC disaster option for CAT risk

DPPC Disaster Prevention and Preparedness Commission (Ethiopia)

DRP disaster response product

EC/ACP European Commission/Africa-Caribbean-Pacific

EIC Ethiopia Insurance Corporation

ENESA Entidad Estatal de Seguros Agrarios, the National Agricultural InsuranceAgency of Spain

ENSO El Nio southern oscillation (sea surface temperatures)

ESDVP Environmentally Sustainable Development Vice Presidency

ESSD The World Bank Environmentally and Socially Sustainable DevelopmentAdvisory Service

FAO Food and Agriculture Organization of the United Nations

FCIP Federal Crop Insurance Program

FSE The Financial Sector Group of The World Bank

GDP gross domestic product

GIIF Global Index Insurance Facility (proposed by CRMG)

Acronyms andAbbreviations

GMO genetically modified organisms

IBLI index-based livestock insurance

ICICI A private general insurance Lombard company in India

ICRISAT International Crops Research Institute for the Semi-Arid Tropics

IFC International Finance Corporation of the World Bank Group

IFFCO-Tokio A private general insurance company in India, a joint venture between Tokio-Marine and the Indian Fertilizer Association

IFPRI International Food Policy Research Institute

IMF International Monetary Fund

INISER Instituto Nicaraguense de Seguros y Reaseguros

Nicaraguan Institute for Insurance and Reinsurance

ISMEA Istituto di Servizi per il Mercato Agricolo Alimentare (Italian Institute forServices to Agricultural Food Markets)

KBS LAB Krishna Bhima Samruddhi Local Area Bank

LIL learning and innovation loan

MAMDA Mutuelle Agricole Marocaine dAssurance

MMPI Malawi Maize Production Index

NASFAM National Smallholders Association

NDVI normalized difference vegetation index

NGO nongovernmental organization

NMSA National Meteorological Services Agency

OECD Organization for Economic Cooperation and Development

OI Opportunity International

PI production insurance

RI reinsurance

SADC Southern African Development Community

SECO State Secretariat for Economic Affairs, Swiss Trade Commission

SENAMHI Servicio Nacional de Meteorologia e Hidrologia del Peru (NationalMeteorology and Hydrology Service of Peru)

SRA Standard Reinsurance Agreement (U.S. crop insurance)

TCDAI Technical Committee for the Development of Agriculture Insurance(Peru)

UNCTAD United Nations Conference on Trade and Development

WFP World Food Program of the United Nations

viii Acronyms and Abbreviations

ix

This document was produced by Ulrich Hess, as task manager, and byJerry Skees, Andrea Stoppa, Barry Barnett, and John Nash, usingbackground papers written by Robert Townsend; Paul Siegel; andJerry Skees, Barry Barnett, and Jason Hartell. (These papers can beviewed at the Commodity Risk Management Group (CRMG) website, www.itf-commrisk.org.) Panos Varangis led the work for thisstudy during its conceptual stage. The two appendixes are shortenedversions of contributions by CRMG authors Joanna Syroka andHector Ibarra to a forthcoming ISMEA (Istituto di Servizi per ilMercato Agricolo Alimentare) publication on innovations in agri-cultural risk management.

Although motivated by the solid and growing literature on alter-native risk management techniques, this paper is ultimately drivenby empirical results that would have been impossible to obtain with-out the development communitys support and demand for action.

At The World Bank, Karen Brooks and Richard Scobey, rural sec-tor managers in the Africa Region, supported the conceptual workand instilled a sense of realism and purpose into the ideas expressedhere. Jock Anderson and Derek Byerlee in the Agriculture and RuralDevelopment department continuously refreshed our ideas in theareas of agricultural risk management and food security risk man-agement. Kevin Cleaver and Sushma Ganguly, Sector Director andSector Manager, respectively, in the Agriculture and RuralDevelopment department, gave motivational advice and guidance.Ken Newcombe, ESDVP, encouraged this work and has become achampion of the Global Index Insurance Facility (GIIF). In his IFCdays, Cesare Calari, FSE, was an early supporter of weather riskmanagement concepts, and he continues to encourage this line ofthinking in his various capacities. Rodney Lester, senior insuranceexpert in FSE, also contributed advice and support. Xavier Gine,DECRG, helped to shape our thinking on smallholder access tofinancial services. Our colleagues in the social development andsocial protection areasnotably Harold Alderman, Will Wiseman,and Elena Gallianohelped with the crossover to the social riskmanagement realm, providing a better understanding of the needs ofvulnerable populations and the relevance of insurance techniques forsafety nets.

Development partners have continuously prompted qualityleaps forward through their particular expertise. Richard Wilcoxof the UN World Food Program (WFP) pushes the weather insur-

Preface andAcknowledgments

ance idea to new limits and has shaped ourthinking at that level. Alexander Sarris, FAO,and Lamon Rutten, UNCTAD, supported CRMGin the areas of commodity risk management.

The key concepts espoused in this paper havebeen developed in the academic community aswell. Ronald Duncan and his group at the WorldBank systematically explored index insuranceideas in the early 1990s (Priovolos and Duncan1991). Also in the early 1990s, Peter Hazell,IFPRI, and Jerry Skees analyzed the shortcom-ings of traditional crop insurance and suggestedthe weather index insurance alternative.

This ESW insists on market-based insurancetechniques, the only sustainable way to transferrisk out of agriculture. At the same time, marketgaps exist, and often markets fail the poor. CRMGand its partnersby crowding in the privatesectorare building the bridges necessary to spanthese gaps. None of this would have been possiblewithout the visionary thinking of leaders in theweather risk management markets. Ravi Nathan,ACE Insurance of North America, in particular, hashelped to globalize the market beyond OECDcountries thanks to creative partnership and risk-sharing structures that include marketing partnersfrom developing countries. His vision continues toinspire the market and our work. Crucial advisorson the work and ideas of the CRMG as repre-sented here are Brian Tobben and William Dick ofPartner RE; Juerg Trueb, of Swiss RE; and RickMcConnell, formerly of the Agricultural FinancialServices Corporation, Alberta. Bruce Tozer, atRabobank, and Roy Leighton, at Carlyon, haveadvised and encouraged CRMG and the Inter-national Task Force for Commodity Risk Man-agement, throughout their existence, withwisdom and passion.

The demand for systematic techniques of agri-cultural risk management in developing countriesultimately came from the people who deal withfarmers and who partly make the farmers riskstheir own. The vision and inspiration of NachiketMor, of ICICI Bank, India, and Vijay Mahajan, ofBASIX, India, are the real motivators behind theastounding success of weather insurance tech-niques. This paper and its proposals would beunthinkable without the ICICI Lombard andBASIX weather insurance pilots and their revela-tion that farmers understand and appreciate thetransparency and timeliness of the product.Ramesh and Vasumathi in Mahahbubnagar,Ramana and Gunaranjan in Hyderabad andMumbai, Virat Divyakirti at ICICI Lombard, andBindu Ananth, also at ICICI, were the architects ofa simple innovation that promises to change Indiasrural landscape. Champions for pilot projects else-where are Rachid Guessous, MAMDA, in Morocco;Ramon Serrano, INISER, in Nicaragua; andShadreck Mapfumo, OI, in Malawi.

The authors wish to acknowledge the generoussupport of the Swiss State Secretariat for EconomicAffairs, SECO. SECO has supported CRMGs pilotprograms in innovative agricultural risk manage-ment, and major lessons from these pilots informthis report. The European Commission and, inparticular, Henny Gerner are associated with thework of CRMG and, by extension, with this ESWthrough their constructive criticism of and supportfor the idea of the Global Index Insurance Facility(GIIF).

Finally, the authors express their sincere grat-itude to World Bank reviewers Jock Andersonand Stephen Mink and to Celeste Sullivan andAnne Goes, of GlobalAgRisk, Inc., for their edi-torial assistance.

x Managing Agricultural Production Risk

xi

The creation of risk transfer markets for weather events in devel-oping and emerging economies is rapidly progressing. This docu-ment describes several sources of risk that create poverty traps forpoor households and impede the development process, focusingon low-probability, high-consequence weather risk events as theyrelate to rural households. These types of risks are highly corre-lated and require special financing and access to global markets ifthey are to be pooled, rendered diversifiable, and improved in pric-ing. Thus, a significant contribution of this paper is the introductionof index insurance, highlighting its use at the micro-, meso-, andmacrolevels for risk transfer. By using index insurance products, itis possible to organize systems that take advantage of global mar-kets to transfer the correlated risks associated with low-probability,high-consequence events out of developing countries. This docu-ment presents both a conceptual backdrop for understanding thissystem and a progress report on several World Bank efforts to assistcountries in using their limited government resources to facilitatemarket-based agricultural risk transfer when faced with naturaldisasters.

While global markets providing reinsurance for natural disastersare both large and growing, they are rarely interested in taking suchrisk from developing and emerging economies. In part, this isbecause developing countries have weak primary insurance mar-kets. Before agreeing to provide reinsurance, global reinsurersengage in due diligence investigations of primary insurers and of therisks the primary insurers wish to transfer. Compared to traditionalinsurance products, index insurance has far fewer problems withhidden information and hidden action. This reduces the reinsurersdue diligence and underwriting costs and makes accepting naturaldisaster risk from new insurance providers in developing countriesmore attractive. Nonetheless, natural disaster losses can be signifi-cant, and carefully crafted ways to finance such losses are criticalpreconditions for shifting the risk into global markets. Innovation inpooling these risks globally may also facilitate the transfer of natu-ral disaster risk from developing countries.

One global innovation currently being prepared by the WorldBank and the European Commission involves a Global IndexInsurance Facility (GIIF). The GIIF will have three functions targetedat helping insurance providers in developing countries build capac-ity: (1) supporting the technical assistance and infrastructure needed

Executive Summary

to develop index insurance based on quality data;(2) aggregating and pooling risk from differentdeveloping countries to improve pricing and risktransfer into the global reinsurance and capitalmarkets; and (3) cofinancing certain insuranceproducts on a bilateral basis from donor to develop-ing country. Importantly, the third function will beseparate from the commercial activity representedin the first and second functions. A global effortto facilitate these three functions could representa major breakthrough for those developing coun-tries exposed to extreme natural disaster risk.

Another promising realm of innovation is thedevelopment of improved technology both to mea-sure weather and to link it to farming systems toforecast crop yields. Improved and less costly sys-tems for measuring weather events in developingcountries will play a significant role in the potentialsuccess of many of the ideas presented here. Secureand accurate measurement will influence both thepricing of index insurance and the demand fromend users. Improvements in developing countriesfirst in measuring the vegetative cover using satel-lite images and then in forecasting the value of thatvegetation in terms of crop yields or grazing valuecould lead to the availability of enhanced types ofindex insurance products. Additionally, moresophisticated crop models linking weather, man-agement systems, and soil condition can be used toprovide insurance products that protect against thedominant random variable affecting productionthe weather.

Transferring risk out of developing countries isimportant for a number of reasons. Natural dis-asters impede development, push households intopoverty, and drain fiscal resources. Many naturaldisasters are directly tied to extreme weather eventsthat can have devastating impacts on agriculture.Nearly three-fourths of the 1.3 billion people world-wide living on less than US$1 per day depend onagriculture for their livelihoods. In many countriesaround the world, agricultural development clearsthe way for overall economic development in thebroader economy, forging a strong link betweenweather, the livelihoods of the poor, and develop-ment. Yet, no effective ex ante solutions for deal-ing with weather risks in developing countriesexist. Rather, developing countries, the WorldBank, and the donor community are currentlyheavily exposed to natural disaster risk via expost responses such as financial bailouts, debt for-giveness, and emergency response.1 None of these

responses are optimal. They fail to provide an effec-tive safety net for the poor; they can be inequitableand untimely; and they create a dependency thathas dire consequences.

If the planning for and financing of extremeweather events were to occur ex ante, access toboth formal and informal lending should improve.As broader financial services become more acces-sible to the rural poor, newer technologies willbe used, and improvements in productivity andincomes should follow.

Farmers around the world utilize various riskcoping and risk management strategies, but manyof these strategies are inefficient. The economicdevelopment literature is full of cases illustratinghow poor, risk-averse farmers often forego poten-tially higher incomes to reduce their risk exposure.Both individual households and the larger societyincur costs for smoothing consumption acrossincome shocks. In many cases, following majorincome shocks, the poor must resort to high inter-est rate loans. Many argue that the poor cannotafford to purchase ex ante insurance protectionagainst extreme weather events, but the wide-spread use of ex post loans suggests otherwise.

The challenge remains of how to make insur-ance against extreme weather events both moreeffective and more affordable. Two major consid-erations inhibit the development of risk transfermarkets for agricultural losses caused by extremeweather events: First, organizing ex ante financingfor highly correlated losses can result in ex-tremely large financial exposure; and, second,asymmetric information problems, such as moralhazard and adverse selection, lead to high trans-action costs. The latter also makes it nearly impos-sible to provide traditional agricultural insurancefor small farmers, because the large fixed transac-tion costs greatly increase the average cost, permonetary unit, of insurance protection for small-holder agriculture. Unfortunately, there are fewsuccessful examples to consider; the heavily sub-sidized crop insurance provided by governmentsin developed countries is both costly and ques-tionable in terms of net social welfare.

Researchers frequently find that economic deci-sion makers underestimate the likelihood and/ormagnitude of low-probability, high-consequenceloss events, leading to a reduced willingness topay for insurance to protect against these events.At the same time, because insurers have littleempirical information about the likelihood and/or

xii Managing Agricultural Production Risk

Executive Summary xiii

magnitude of extreme events, they tend to addlarge extra costs to premium rates for insuranceproducts protecting against them. This diver-gence between what potential purchasers will payand what insurers will accept results in agricul-tural insurance markets that clear less thansocially optimal quantities of risk transfer.

New conceptual models are being developedto facilitate the transfer of extreme weather riskout of developing countries. This documentreports on the progress of several ongoing effortsby the Commodity Risk Management Group(CRMG) at the World Bank that have been moti-vated by these models. All of these efforts are builton the premise that index-based insurance prod-ucts can effectively address the challenges of theex ante financing of highly correlated losses andhigh transaction costs. Index insurance productspay indemnities based on an independent meas-ure highly correlated with realized losses. Unliketraditional crop insurance, which attempts tomeasure individual farm yields, index insurancemakes use of variables largely exogenous to theindividual policyholder, including area yield orweather events such as temperature or rainfall.This feature greatly reduces the need fordeductibles and copayments, since it results invery little exposure to asymmetric informationproblems, such as moral hazard and adverse selec-tion. By eliminating farm-level loss adjustment,index insurance products achieve lower transactioncosts than are possible with traditional agricul-tural insurance products.

Purchasers of index insurance products areexposed to basis risk. Since index insuranceindemnities are triggered not by farm-level lossesbut rather by the value of an independent measure(the index), a policyholder can experience a lossand yet receive no indemnity. Conversely, thepolicyholder may not experience a loss and yetnonetheless receive an indemnity. The effective-ness of index insurance as a risk managementtool depends on how positively correlated farm-level losses are with the underlying index.Importantly, since farmers have incentives to con-tinue to produce or to try to save their crops andlivestock even in the face of bad weather events,index insurance should provide for a more effi-cient allocation of resources.

Since they are standardized and transparent,index insurance products can also function as re-insurance instruments that transfer the risk of

widespread, correlated agricultural productionlosses. To the extent that institutions can be createdto aggregate and pool the low-probability, high-consequence tail risk that results from writinginsurance on these events, the divergence betweeninsurers willingness to accept and potential pur-chasers willingness to pay should decrease, caus-ing the market to clear at high quantities of risktransfer.

This paper was written to inform a broad rangeof decision makers about the progress being madein risk transfer for natural disaster risk. While thefocus here is on agriculture, many of the same con-cepts can clearly also be used for other sectorsexposed to natural disaster risk. Two basic innova-tions dominate the conceptual framework: (1) useof index-based insurance; and (2) layering risk tofacilitate risk transfer. In many cases, individualswill self-insure against the layer of risk com-posed of high-probability, low-consequencelosses. Some form of government interventionmay be required to achieve higher levels of risktransfer in the layer of risk composed of low-prob-ability, high-consequence losses. Between thesetwo extremes lies a layer of risk that, with appro-priate risk transfer and pooling structures, can betransferred using market mechanisms.

Since catastrophe risks (CAT risks) are one ofthe impediments to market development, aframework has been developed for governmentaction in the management of agricultural risk thatincludes models for government intermediationof catastrophic risk through government disasteroptions for CAT risk, or DOC. This framework pro-poses that governments buy index-based cata-strophic risk coverage in international marketsand offer them at rates lower than global marketrates to local insurers, who then pass the savingson to end users in developing countries. This sys-tem would mitigate large-loss/infrequent risksthat are usually difficult and expensive to reinsurein traditional reinsurance markets and would ulti-mately allow local insurers to cover more peopleagainst the extreme risks in an ex ante fashion.

This paper includes several case studies illustrat-ing the application of these concepts in countriesaround the world. While the specifics vary based oneach countrys needs, all of the cases involve the useof index insurance and/or the layering of risk tofacilitate risk transfer. The final chapter of this doc-ument describes potential future roles for the WorldBank in the area of agricultural risk management.

1

This document presents innovations in agricultural risk managementfor natural disaster risk, with the focus on defining practical roles forgovernments of developing countries and the World Bank in devel-oping risk management strategies.2 Recent success stories demon-strate that the World Bank can play a role in assisting countries intaking actions that effectively use limited government resources tofacilitate market-based agricultural risk transfer. This is important, asdeveloping countries, the World Bank, and the donor community arecurrently heavily exposed to natural disaster risk without the benefitof ex ante structures to finance losses. Instead, at each big drought orother natural disaster, those affected must appeal for financial sup-port, leaving them vulnerable to the mercy of ad hoc responses fromgovernment, the international financial institutions, and donors. In most developing countries, livelihoods are not insured by inter-national insurance/reinsurance providers, capital markets, or evengovernment budgets. In addition, natural disasters and price risk inagriculture also impede development of both formal and informalbanking. Without access to credit, risk-averse poor farmers are lockedin poverty, burdened with old technology, and faced with an ineffi-cient allocation of resources.

Advances in risk transfer in developed countries are leading theway to solutions to many social problems. Shiller (2003) documentsprogress and charts a course for far more innovation as the democra-tization of finance and technology spur global risk pooling. Financialand reinsurance markets in developed countries are rapidly devisingindex-based instruments that allow for the transfer of systemic risksand even of livelihood risks. Innovations in risk transfer for naturaldisasters have been well documented (Doherty 1997; Skees 1999b).The challenge is to make these innovations relevant in developingcountries and to facilitate knowledge and access.

Is the absence of formal transfers of natural disaster risk inevitablein developing countries? Clearly not; formal global markets for off-setting natural disaster risks and weather risks are widely used indeveloped countries.3 This document demonstrates how these mar-kets can be used to insure natural disaster risk in developing coun-tries. Agricultural sectors in developing countries are much moreexposed to the vagaries of weather than are those of richer countries,so this protection would be even more valuable to them.

Is it a luxury to offer insurance to poor people who lack properroads or even safe drinking water? Every government must set its

Introduction1

own priorities. Careful consideration of the bene-fits and costs of different interventions is critical.Still, the poor are forced to make production deci-sions using the objective of minimizing risk, ratherthan maximizing profits, and thus they must foregomore remunerative activities that could providemeans of escape from their poverty. An effective andtimely insurance mechanism might allow people toengage in higher risk, higher return activities with-out putting their livelihoods at risk. Spurring devel-opment via improved financial markets is importantfor developing countries.

Are there any effective precedents for agricul-tural insurance mechanisms in developing coun-tries? While these innovations are just taking hold,progress has been made with weather insurancefor farmers in India, Ukraine, Nicaragua, Malawi,Ethiopia, and Mexico. Several other experimentsare also documented in this work. Weather insuredfarmers in India say they either have a good cropin which case it does not matter if they do not recoupthe insurance premiumor they have a monsoonfailure, in which case they receive an insurance pay-out. This payout will at least cover the farmers cashoutlay and perhaps provide them with enough extramoney to keep their children in school and to pre-serve assets they would otherwise be forced to liqui-date, often at greatly reduced prices. These farmerswill be likely to invest a little more in the right seedsand fertilizer at the right time. Quantifying thisimpact is difficult right now, but a large impact assessment will soon provide more informationon the effectiveness of this program. It is clear already, however, that when offered the choice,many farmers in India will pay for fully pricedweather insurance. Even farmers with access tothe government-subsidized crop insurance prod-uct choose to buy the market-priced weather in-surance product. They say they like the objectivenature of the weather index; they can check theweather station measurements themselves. Theyalso like the timely payout. Indeed, on this count,the new rainfall index insurance, which pays on atimely basis, compares favorably to the nationalcrop insurance product, which might pay only afteras much as eighteen months.

Is this insurance only suitable for large commer-cial farmers? One true advantage of weather insur-ance is that it can be targeted to small farmers, as nomonitoring is needed to verify farm-level losses.The Indian experience clearly demonstrates thatsmall farmers find value in weather insurance.

BASIX (a microfinance entity in Andhra Pradesh)estimates that all of the 427 farmers who boughtweather insurance policies in 2003 have small- tomedium-sized farms of between two and ten acres,providing an average yearly income of 15,000 to30,000 Rupees, or between US$1 and US$2 per day.Currently, many farmers buying weather insur-ance in India are repeat customers. Clearly, thesefarmers were not too poor to buy the product. Earlysurvey results demonstrate that more than half ofthose purchasing the insurance list managing riskas their primary reason. Some farmers might havechosen this new insurance option over the prospectof paying high interest to moneylenders when cashis needed after a harvest failure.

Is Indias insurance program sustainable? Withthe pilot program now in its third year and otherinsurance companies replicating and selling theproduct, BASIX has mainstreamed the weather in-surance product and automated delivery to an ex-pected 8,000 clients for the 2005 season. Countriesin sub-Saharan Africa and Latin America are start-ing their own weather insurance projects at micro-and macrolevels. Ethiopia is piloting a weather-insurance-based drought emergency response, forexample. Furthermore, weather insurance seems tobe a good business. The Indian weather insuranceprogram has emerged without the support of gov-ernment subsidies. The Commodity Risk Manage-ment Group (CRMG) of the World Bank has advisedthose who were ready to try these new approachesto agricultural risk management.

How can this process be operationalized in theWorld Bank and elsewhere? Task managers andpractitioners may want to follow this work withpotential projects, but how do they get started?This document presents ideas on how to structurea solid framework of action. Among the importantpublic goods that governments and the World Bankmight provide are, for example, weather stationsand risk financing for catastrophic protection.

Governments in drought-prone countries anddonors and relief agencies should also be aware ofother kinds of projects that use risk managementmarkets to improve the response to weather-relatedshocks. This document explores how current adhoc disaster relief mechanisms can be modified andcomplemented by a more systematic response torecurrent droughts.

When assessing proper roles for government,the first factors to consider are the economic bene-fits that can be created by risk management tools,

2 Managing Agricultural Production Risk

Introduction 3

the characteristics of the risks faced by farmers ina specific area, and the challenges associated withcreating and maintaining risk management toolssuch as insurance. In general, agricultural riskmanagement presents no one-size-fits-all policyrecommendation for the role of government. Mostgovernments consider at least four criteria whenconsidering alternatives for addressing agricul-tural risk management needs: (1) fiscal constraint;(2) growth; (3) market-oriented risk-transfer; and(4) social goals of reducing poverty and vulnerabil-ity in rural areas.

Chapter 2 of this document begins with anoverview of risk in agriculture, focusing on howdecision makers currently cope with and managerisk in developing countries and on the impedi-ments to developing effective risk transfer markets.High transaction costs, problems with correlatedrisk, and the classic problems of moral hazard andadverse selection clearly increase the cost of tradi-tional insurance. Chapter 3 reviews in detail the ex-periences of some developed countries withagricultural risk transfer. A clear message emergesabout the costs to governments and the inefficien-cies of these systems, supporting the need to searchfor new solutions appropriate for developing coun-tries. The stark contrast between what is possible ina developed country versus what is possible in adeveloping country further motivates a continuing

search for new solutions. Chapter 4 explores alter-nate solutions based on the concept of weatherindex insurance that covers farmers against weatherevents leading to serious agricultural losses, high-lighting the advantages of such systems for devel-oping countries. Chapter 5 brings together two coreinnovations: first, the use of index insurance to in-sure against detrimental weather events, a formwith significantly lower monitoring costs; and sec-ond, the layering of insurance products to segmentrisk more efficiently, thus allowing for transfer ofcorrelated risk. These innovations provide a richframework for introducing new approaches to risksharing and risk transfer in developing countries.Chapter 5 outlines an effective role for the WorldBank and other donors in this important domain ofnatural hazard risk management. Chapter 6 pro-vides an overview of a number of ongoing agricul-tural risk pilot programs and case studies for invarious countries. Finally, Chapter 7 makes rec-ommendations for the role of the World Bank andcountry governments in facilitating the develop-ment of innovation in agricultural risk manage-ment. Following the core chapters, the reportincludes two detailed appendixes: the first explainshow to structure and price weather index insur-ance; the second provides more background to risktransfer programs and experiences in Ukraine,Mexico, Canada, and India.

5

Agricultural risk is associated with negative outcomes stemmingfrom imperfectly predictable biological, climatic, and price variables.These variables include natural adversities (for example, pests anddiseases), climatic factors not within the control of agricultural pro-ducers, and adverse changes in both input and output prices. To setthe stage for the discussion on how to deal with risk in agriculture,we classify the different sources of that risk.4

Agriculture is often characterized by high variability of productionoutcomes, that is, by production risk. Unlike most other entrepreneurs,agricultural producers cannot predict with certainty the amount ofoutput their production process will yield, due to external factorssuch as weather, pests, and diseases. Agricultural producers can alsobe hindered by adverse events during harvesting or collecting thatmay result in production losses.

Both input and output price volatility are important sources ofmarket risk in agriculture. Prices of agricultural commodities areextremely volatile. Output price variability originates from bothendogenous and exogenous market shocks. Segmented agriculturalmarkets will be influenced mainly by local supply and demand con-ditions, while more globally integrated markets will be significantlyaffected by international production dynamics. In local markets, pricerisk is sometimes mitigated by the natural hedge effect, in which anincrease (decrease) in annual production tends to decrease (increase)output price (though not necessarily farmers revenues). In integratedmarkets, a reduction in prices is generally not correlated with localsupply conditions, and therefore price shocks may affect producersin a more significant way. Another kind of market risk arises in theprocess of delivering production to the marketplace. The inabilityto deliver perishable products to the right market at the right timecan impair producers efforts. The lack of infrastructure and of well-developed markets makes this a significant source of risk in manydeveloping countries.

The ways businesses finance their activities is a major concern formany economic enterprises. In this respect, agriculture has its ownpeculiarities. Many agricultural production cycles stretch over longperiods, and farmers must anticipate expenses they will only be ableto recuperate after marketing their product. This leads to potentialcash flow problems, which are often exacerbated by lack of access tocredit and the high cost of borrowing. These problems can be classi-fied as financial risk.

Risk and Risk Managementin Agriculture2

Institutional risk, that is, risk generated by un-expected changes in regulations that affect produc-ers activities, constitutes another important sourceof uncertainty for agricultural producers. Changesin regulations can have significant impact on theprofitability of farming activities. This is particularlytrue for import/export regimes and for dedicatedsupport schemes, but sanitary and phytosanitaryregulations too can restrict producers activities andimpose costs on households.

Like most other entrepreneurs, agricultural pro-ducers are responsible for all the consequences oftheir activities. Growing concern over the impact ofagriculture on the environment, however, includ-ing the introduction of genetically modified organ-isms (GMO), may cause an increase in producerliability risk. Finally, agricultural households, alongwith other economic enterprises, are exposed topersonal risks to the well-being of people who workon the farm and asset risks, including possible dam-age or theft of production equipment and assets.(See Box 2.1.)

In discussing how to design appropriate riskmanagement policies, it is useful to understandstrategies and mechanisms employed by producersto deal with risk, including the distinction betweeninformal and formal risk management mechanismsand between ex ante and ex post strategies.5 Ashighlighted in the 2000/2001 World DevelopmentReport (World Bank, 2001), informal strategiesare identified as arrangements that involve indi-viduals or households or such groups as commu-nities or villages, while formal arrangements aremarket-based activities and publicly providedmechanisms. The ex ante or ex post classificationfocuses on the point at which the reaction to risktakes place: ex ante responses take place before thepotential harming event; ex post responses takeplace after the event. Ex ante reactions can be furtherdivided into on-farm strategies and risk-sharingstrategies (Anderson, 2001). Table 2.1 summarizesthese classifications.

INFORMAL MECHANISMS6

Ex ante informal strategies are characterized bydiversification of income sources and choice of agri-cultural production strategy. One strategy producerscan employ is simply to avoid risk. In many cases,extreme poverty makes people very risk averse;producers facing these circumstances often avoidactivities that entail significant risk, even though

the income gains might be larger than for less riskychoices. This inability to accept and manage risk andaccumulate and retain wealth is sometimes referredto as the the poverty trap (World Bank 2001).

Once producers have decided to engage in farm-ing activities, the production strategy selected be-comes an important means of mitigating the risk ofcrop failure. Traditional cropping systems in manyplaces rely on crop and plot diversification. Cropdiversification and intercropping systems reducethe risk of crop failure due to adverse weatherevents, crop pests, or insect attacks. Morduch (1995)presents evidence that households whose con-sumption levels are close to subsistence (and whichare therefore highly vulnerable to income shocks)devote a larger share of land to safer, traditionalvarieties such as rice and castor than to riskier,high-yielding varieties. Morduch also finds thatnear-subsistence households diversify their plotsspatially to reduce the impact of weather shocksthat vary by location.

Apart from altering agricultural productionstrategies, households also smooth income by diver-sifying income sources, thus minimizing the effectof a negative shock to any one of them. Accordingto Walker and Ryan (1990), most rural householdsin villages of semi-arid India surveyed by the Inter-national Crops Research Institute for the Semi-AridTropics (ICRISAT) generate income from at leasttwo different sources; typically, crop income is ac-companied by some livestock or dairy income. Off-farm seasonal labor, trade, and sale of handicraftsare also common income sources. The importanceto risk management of income source diversifica-tion is emphasized by the Rosenzweig and Stark(1989), who find that households with high farmprofit volatility are more likely to have a householdmember engaged in steady wage employment.

Buffer stock accumulation of crops or liquid as-sets and the use of credit present obvious means bywhich households can smooth consumption. Limand Townsend (1998) show that currency and cropinventories function as buffers or precautionarysavings.

Crop-sharing arrangements in renting land andhiring labor can also provide an effective meansof sharing risk among individuals, thus reducingproducer risk exposure (Hazell 1992). Other risksharing mechanisms, such as community-levelrisk pooling, occur in specific communities or ex-tended households where group members transferresources among themselves to rebalance marginal

6 Managing Agricultural Production Risk

Risk and Risk Management in Agriculture 7

utilities (World Bank 2001). These arrangements,however, while effective for counterbalancing theconsequences of events affecting only some mem-bers of the community, do not work well in casesof covariate income shocks (Hazell 1992).

Typical ex post informal income-smoothingmechanisms include the sale of assets, such as landor livestock (Rosenzweig and Wolpin 1993), or thereallocation of labor resources to off-farm laboractivities. Gadgil, et al. (2002), argue that southern

Box 2.1 Asset-Based Risk Management

Siegel (2005) broadens the risk discussion into anasset-based risk management framework. This compre-hensive approach considers the dynamics of riskswithin a given context. The asset-based approach usesa livelihood focus, recognizing that rural householdshold a portfolio of assets that they allocate among arange of welfare generating activities and that the par-ticular livelihood activities pursued reflect explicit (orimplicit) multidimensional objectives that include eco-nomic, social, cultural, and environmental outcomes(Chambers and Conway 1992; Carney et al. 1999).The asset-based approach helps clarify why and howhouseholds manage assets and risks to select certainlivelihood strategies for achieving welfare outcomesgiven specific asset-context interface conditions.

The asset-based risk management approach focuseson the long-term implications of short-term decisionsabout the allocation of assets. Coping strategies usedby poor rural households can lead to the degradationor decapitalization of assets, as when, for example,trees are cut down or children are removed fromschool, and these actions can contribute to a cycle ofpoverty. Alternatively, livelihood strategies that leadto improved asset portfolios, for example, invest-ments in improved technology, training programs,and empowerment through social and political net-works, can foster a virtuous cycle of sustainablegrowth. Asset accumulation and changes in liveli-hood strategies are thus important for sustained improvements in household well-being.

Improved management of rural risk is critical toachieve rural growth and reduce poverty. It is critical,however, to move beyond a narrow risk managementfocus to a more holistic rural development approachthat focuses attention on building, enhancing, main-taining, and protecting household assets. The develop-ment of new rural risk management instruments offers

the potential to improve household livelihood options,yet their ultimate success will depend on the linkagesamong assets, context, behavior, and outcomes. Thus,the real question to be asked is what optimal risk man-agement instruments will allow households to maxi-mize their objectives in terms of expected income andvariability of income?

The relationship between assets and productivityexplains the poverty cycle and the difficulty the poorhave in improving their livelihoods. A householdsportfolio of assets influences their risk attitude andtheir ability to respond to risk. Assets also determinethe types of activities that can be undertaken. Moreproductive activities are typically associated withgreater risk, so how assets are utilized will impactproductivity as a function of both expected incomeand variability of income. At the household level,agricultural risk management instruments reduce thevariability of household incomes. The expectation isthat by reducing risk and uncertainty, households willbe able to accumulate assets and undertake moreproductive investments.

In the design of risk management instruments, it isimportant to account for the unique context pre-sented in different situations. Risk management in-struments must be tailored to specific constraints andobjectives within the country, community, andhousehold context.

In considering the potential applications of indexinsurance in developing countries, it is important toremember that index insurance is not necessarily ap-plicable or replicable for every situation. Nor should itbe inferred that index insurance is a substitute forother risk management strategies. Index insurancecan, however, provide a starting point and, ideally, aspringboard for the development of a variety of riskmanagement mechanisms.

Note: A more detailed discussion of these issues can be found in Looking at Rural Risk Management Using an Asset-Based Approach, abackground paper for this report by Paul Siegel. In particular, the reader is directed to Figure 1, which depicts the relationships among assets,context, behavior, and outcomes.

Source: Siegel 2005.

Indian farmers who expect poor monsoon rainscan quickly shift from 100 percent on-farm laboractivities to mainly off-farm activities. Fafchamps(1993), in his analysis of rain-fed agriculture amongWest African farmers, emphasizes the importanceof building labor flexibility into the productionstrategy.

As reported by Townsend (2005), in analyzingthe cost of risk on ex ante agricultural productionstrategies, Rosenzweig and Binswanger (1993),Morduch (1995), and Kurosaki and Fafchamps(2002) all find considerable efficiency losses associ-ated with risk mitigation, typically due to lack ofspecializationin other words, farmers trade offincome variability with profitability.

The need to smooth consumption not only againstidiosyncratic shocks but also against correlatedshocks comes at a serious cost in terms of productionefficiency and reduced profits, thus lowering theoverall level of household consumption. A majorconsideration for innovation would be to shift cor-related risk from rural households (Skees 2003).One obvious solution would be for rural householdsto share risk with households or institutions fromareas largely uncorrelated with the local risk condi-

tions. Examples of such extra-regional risk sharingsystems are found in the literature, including, creditand transfers between distant relatives (Rosenzweig,1988; Miller and Paulson 2000); migration and mar-riages (Rosenzweig and Stark 1989); or ethnic net-works (Deaton and Grimard 1992). Although thesestudies find some degree of risk sharing and thusof insurance against weather, use of such systemsis not so widespread as to cover all households, nordo they come even close to providing a fully efficientinsurance mechanism. Most households are there-fore still left with no insurance against correlatedrisks, the main source of which is weather.

FORMAL MECHANISMSFormal risk management mechanisms can be classi-fied as publicly provided or market based (Table 2.1).Government action plays an important role in agri-cultural risk management, both ex ante and ex post.Ex ante education and services provided by agri-cultural extension help familiarize producers withthe consequences of risk and help them adoptstrategies to deal with it. Governments also reducethe impacts of risk by developing relevant infra-

8 Managing Agricultural Production Risk

Table 2.1 Risk Management Strategies in Agriculture

Formal Mechanisms

Informal Mechanisms Market Based Publicly Provided

Avoiding exposure to riskCrop diversification and intercroppingPlot diversificationDiversification of incomesourceBuffer stock accumulationof crops or liquid assetsAdoption of advancedcropping techniques (fertilization, irrigation, resistant varieties)

Crop sharingInformal risk pool

Sale of assetsReallocation of laborMutual aid

Contract marketingand futures contractsInsurance

Credit

Agricultural extensionPest management systemsInfrastructures (roads, dams,irrigation systems)

Social assistanceSocial fundsCash transfer

Source: Anderson 2001; Townsend 2005; World Bank 2001.

On-farm

Sharing riskwith others

Coping withshocks

EXPO

STEX

AN

TEST

RATE

GIE

SST

RATE

GIE

S

Risk and Risk Management in Agriculture 9

structure and by adopting social schemes and cashtransfers for relief after shocks have occurred.7

As mentioned in the section on informal mech-anisms, production and market risks are probablythose with the largest impact on agricultural pro-ducers. Various market-based risk managementsolutions have been developed to address thesesources of risk.

Price Risk Management

One way producers have traditionally managedprice variability is by entering into preharvest agree-ments that set a specific price for future delivery.These arrangements, known as forward contracts,allow producers to lock in a certain price, thus re-ducing risk but also foregoing the possible benefitsof positive price deviations. In specific markets,and for specific products, these arrangements haveevolved into futures contracts, traded on regulatedexchanges on the basis of specific trading rules andfor specific standardized products. This reducessome of the risks associated with forward contract-ing (for example, default). A further evolution inhedging opportunities for agricultural producershas been the development of price options, a priceguarantee that allows producers to benefit from afloor price while also allowing them to take advan-tage of positive price changes. With price options,agents pay a premium to purchase a contract thatgives them the right (but not the obligation) to sellfutures contracts at a specified price. Price optionsfor commodities are regularly traded on exchanges,but they can also be traded in over-the-countermarkets. Futures and options contacts can be ef-fective price risk management tools as well as im-

portant price discovery devices and market trendindicators.

For agricultural producers in developing coun-tries, access to futures and options contracts is prob-ably the exception rather than the rule. Futures andoptions markets in developed countries representimportant price discovery references for inter-national commodity markets, however, and indirectaccess to these exchange-traded instruments maybe granted through the intermediation of collectiveaction by producer groups such as farmer cooper-atives or national authorities.8 While an importantreality for some commodities, futures and optionsare not available for all agricultural products.

Production/Weather Risk Management

Insurance is another formal mechanism used inmany countries to share production risks. Insurancedoes not as efficiently manage production risk,however, as derivative markets do price risks. Pricerisk is highly spatially correlated and, as illus-trated in Figure 2.1, futures and options are ap-propriate instruments for dealing with spatiallycorrelated risks. In contrast, insurance is an ap-propriate risk management solution for indepen-dent risks. Agricultural production risks typicallylack sufficient spatial correlation to be effectivelyhedged using only exchange-traded futures or op-tions instruments. At the same time, agriculturalproduction risks are generally not perfectly spatiallyindependent; therefore, insurance markets do notwork at their best. Skees and Barnett (1999) refer tothese risks as in-between risks. According toAhsan, et al. (1982), good or bad weather may havesimilar effects on all farmers in adjoining areas,

Figure 2.1 Independent Versus Correlated Risk

Auto, life,

fire

Crop

yields

Prices,

interest rates

Perfectly

correlated

(systemic)

Perfectly

independent

Insurance

markets

Options and futures

markets

Source: Miranda and Glauber 1997.

and, consequently, the law of large numbers, onwhich premium and indemnity calculations arebased, breaks down. In fact, positive spatial corre-lation in losses limits the risk reduction obtainableby pooling risks from different geographical areas.This increases the variance in indemnities paid byinsurers. In general, the more the losses are posi-tively correlated, the less efficient traditional insur-ance is as a risk-transfer mechanism. For many ideaspresented in this document, a precondition for suc-cess is a high degree of positive correlation of losses.

The lack of statistical independence is not theonly problem with providing insurance in agricul-ture. Another set of problems relates to asymmetricinformation, the situation in which the insured hasmore knowledge about his or her own risk profilethan does the insurer. Asymmetric informationcauses two problems: adverse selection and moralhazard. In the case of adverse selection, farmershave better knowledge than do the insurers aboutthe probability distribution of losses. The farmersthus occupy the privileged situation of knowingwhether or not the insurance premium accuratelyreflects the risk they face. Consequently, only farm-ers bearing greater risks will purchase the cover-age, generating an imbalance between indemnitiespaid and premiums collected. Moral hazard simi-larly affects the incentive structure of the relation-ship between insurer and insured. After enteringthe contract, the farmers incentive to take propercare of the crop diminishes, while the insurer haslimited effective means to monitor what may provehazardous behavior by the farmer. Insurers maythus incur greater than anticipated losses.

Agricultural insurance is often characterized byhigh administrative costs, due, in part, to the riskclassification and monitoring systems that insurersmust put in place to forestall asymmetric informa-tion problems. Other costs include acquiring thedata needed to establish accurate premium rates andconducting claims adjustments. As a percentage ofthe premium, the smaller the policy, typically, thelarger the administrative costs.

Spatially correlated risk, moral hazard, adverseselection, and high administrative costs are all im-portant reasons why agricultural insurance marketsmay fail. Cognitive failure among potential insur-ance purchasers and ambiguity loading on the partof insurance suppliers are other possible causes ofagricultural insurance market failure.9

If consumers fail to recognize and plan for low-frequency, high-consequence events, the likelihood

that an insurance market will emerge diminishes.When considering an insurance purchase, the con-sumer may have difficulty determining the valueof the contract or, more specifically, the probabil-ity and magnitude of loss relative to the premium(Kunreuther and Pauly 2001). Many decision mak-ers tend to underestimate their exposure to low-frequency, high-consequence losses. Thus, theyare unwilling to pay the full costs of an insuranceproduct that protects against these losses. Low-frequency events, even when severe, are frequentlydiscounted or ignored altogether by producers try-ing to determine the value of an insurance contract.This happens because the evaluation of probabilityassessments regarding future events is complexand often entails high search costs. Many peopleresort to various simplifying heuristics, but proba-bility estimates based on these heuristics may dif-fer greatly from the true probability distribution(Schade et al. 2002; Morgan and Henrion 1990).Evidence indicates that agricultural producers for-get extreme low-yield events. The general findingregarding subjective crop-yield distributions is thatagricultural producers tend to overestimate themean yield and underestimate the variance (Buzbyet al. 1994; Pease et al. 1993; Dismukes et al. 1989).

On the other side, insurers will typically loadpremium rates heavily for low-frequency, high-consequence events where considerable ambiguitysurrounds the actual likelihood of the event (Schadeet al. 2002; Kunreuther et al. 1995). Ambiguity isespecially serious when considering highly skewedprobability distributions with long tails, as is typicalof crop yields. Uncertainty is further compoundedwhen the historical data used to estimate probabil-ity distributions are incomplete or of poor quality,a very common problem in developing countries.Small sample size creates large measurement error,especially when the underlying probability distrib-ution is heavily skewed. Kunreuther et al. (1993)demonstrate via experimental economics that whenrisk estimates are ambiguous, loads on insurancepremiums can be 1.8 times higher than when insur-ing events with well specified probability and lossestimates.

Together, these effects create a wedge betweenthe prices that farmers are willing to pay for cata-strophic agricultural insurance and the prices thatinsurers are willing to accept. Thus, functioningprivate-sector markets may fail to materialize or,if they do materialize, they may cover only a smallportion of the overall risk exposure (Pomareda 1986).

10 Managing Agricultural Production Risk

11

To better understand agricultural risk management markets andgovernment policies to facilitate access to risk management instru-ments, it is worthwhile to analyze critically the experiences of somedeveloped countries. The experiences of the United States, Canada,and Spain are thus described for reference, but it is important to con-sider that these systems may not be replicable in or suitable for mostdeveloping countries. In addition, many developed countries haveinvolved market support and income transfer programs that extendwell beyond crop insurance. To the extent they are based on farmincome, these programs involve levels of protection against severecrop failures. The European community has extensive policies focus-ing on income protection.

CROP INSURANCE PROGRAMS INDEVELOPED COUNTRIESThis section presents overviews of agricultural risk managementprograms in three developed countries: the United States, Canada,and Spain. These countries have been able to implement substantialprograms to reduce yield and revenue risk for agricultural produc-ers. While these programs offer a variety of risk management prod-ucts for farmers, the programs require levels of government supportunfeasible for most countries.

The United States

In the United States, multiple peril yield and revenue insurance prod-ucts are offered through the Federal Crop Insurance Program (FCIP),a public/private partnership between the federal government andvarious private sector insurance companies.10 The program seeks toaddress both social welfare and economic efficiency objectives. Withregard to social welfare, private companies selling federal crop in-surance policies may not refuse to sell to any eligible farmer, regard-less of past loss history. At the same time, the program aims to beactuarially sound.

Policies are available for over one hundred commodities but in2004 just four cropscorn, soybeans, wheat, and cottonaccountedfor approximately 79 percent of the US$4 billion in total premiums.Excluding pasture, rangeland, and forage, approximately 72 percentof the national crop acreage is currently insured under the FCIP.

Approaches to Agricultural Risk in

Developed Countries

3

About 73 percent of total premiums are for revenueinsurance policies, while 25 percent are for yield in-surance policies.11

Most FCIP policies trigger indemnities at the farm(or even subfarm) level.12 Yield insurance offers arebased on a rolling four-to-ten-year average yield,known as the actual production history (APH) yield.The federal government provides farmers with abase catastrophic yield insurance policy, free of anypremium costs.13 Farmers may then choose to pur-chase, at federally subsidized prices, additionalinsurance coverage beyond the catastrophic level.This additional coverage, often called buy-upcoverage, may be either yield or revenue insurance.Farm-level revenue insurance offers are based onthe product of the APH yield and a price index thatreflects national price movements for the particularcommodity.

For some crops and regions, defined alongcounty barriers, area yield and/or area revenuebuy-up insurance policies are offered through FCIP.On a per acre insured basis, area-level insuranceproducts tend to be less expensive than farm-levelinsurance products. Thus, in 2004, area yield andarea revenue policies accounted for 7.4 percent oftotal acreage insured but less than 3 percent of totalpremiums.

The federal government also provides a rein-surance mechanism that allows insurance compa-nies to determine (within certain bounds) whichpolicies they will retain and which they will cedeto the government. This arrangement is referred to

as the standard reinsurance agreement (SRA). TheSRA is quite complex, with both quota share rein-surance and stop losses by state and insurance pool;however, in essence, it allows the private insurancecompanies to adversely select against the govern-ment. This is considered necessary since the compa-nies do not establish premium rates or underwritingguidelines but are required to sell policies to alleligible farmers.

The federal costs associated with the U.S. pro-gram have four components:

Federal premium subsidies range from 100 per-cent of total premium for catastrophic (CAT)policies to 38 percent of premium for buy-uppolicies at the highest coverage levels. Acrossall FCIP products and coverage levels, theaverage premium subsidy in 2004 was 59 per-cent of total premiums.

The federal government reimburses adminis-trative and operating expenses for private in-surance companies that sell and service FCIPpolicies. This reimbursement is approximately22 percent of total premiums.

The SRA has an embedded federal subsidywith an expected value of about 14 percentof total premiums.

The program, by law, can be considered ac-tuarially sound at a loss ratio of 1.075. Thisimplies an additional federal subsidy of 7.5 percent of total premiums.

On average, the federal government pays approx-imately 70 percent of the total cost for the FCIP.Farmer-paid premiums account for only about 30 percent of the total cost. While the direct farmersubsidy varies by coverage level, the United Stateshas consistently passed legislation increasing thesubsidy level to farmers for crop and revenue insur-ance products. The rate of subsidy is one componentthat has influenced the growth in overall premium.Figure 3.1 clearly shows that the growth in premiumsubsidy is greater than the growth in farmer-paidpremiums. The rate of subsidy increased in 1995and 2001.

Canada14

In 2003, Canada revised its agricultural risk manage-ment programs. The Business Risk Managementelement of the new Agricultural Policy Framework(APF) is composed of two main schemes: ProductionInsurance and Income Stabilization.

12 Managing Agricultural Production Risk

Figure 3.1 Crop Insurance Premiums and Indemnities in the United States

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2003200119991997199519931991

U.S

.bill

ion

dolla

rs

Crop Year

Producer-paidPremium subsidy

Source: Babcock et al. 2004.

Approaches to Agricultural Risk in Developed Countries 13

The Production Insurance (PI) scheme offersproducers a variety of multiple peril production orproduction value loss products similar to many ofthose sold in the United States. One major distinc-tion, however, is that the Canadian program is mar-keted, delivered, and serviced entirely and jointlyby federal and provincial government entities, although it is the provincial authorities who areultimately responsible for insurance provision. Thisallows provinces some leeway to tailor products tofit their regions and to offer additional products.

Production insurance plans are offered for overone hundred different crops, and provisions havebeen made to include plans covering livestock lossesas well. Crop insurance plans are available based oneither individual yields (or production value in thecase of certain items, such as stone-fruits) or areabased yields. Unlike the U.S. program, Canadianproducers are not allowed to separately insure dif-ferent parcels but rather must insure together allparcels of a given crop type. This means that lowyields on one parcel may be offset by high yields onanother parcel when determining whether or notan overall production loss has occurred. Insurancecan also be purchased for loss of quality, unseededacreage, replanting, spot loss, and emergency works.The latter coverage is a loss mitigation benefit meantto encourage producers to take actions that reducethe magnitude of crop damage caused by an in-sured peril.

Cost sharing between the federal governmentand each province for the entire insurance programis to be fixed at 60:40, respectively, by 2006. Federalsubsidies as a percentage of premium costs vary,however, from 60 percent for catastrophic losspolicies to 20 percent for low deductible produc-tion coverage. Combined, the federal and provin-cial governments cover approximately 66 percentof program costs, including administrative costs.This is roughly equivalent to the percentage of totalprogram costs borne by the federal governmentin the U.S. program. Provincial authorities are responsible for the solvency of their insurance port-folio. In Canada, the federal government competeswith private reinsurance firms in offering deficitfinancing agreements to provincial authorities.

Beginning in 2004, the Canadian AgriculturalIncome Stabilization (CAIS) scheme replaced andintegrated former income stabilization programs.CAIS is based on the producer production margin,where a margin is allowable farm income, includ-ing proceeds from production insurance minusallowable (direct production) expenses. The pro-

gram generates a payment when a producerscurrent year production margin falls below thatproducers reference margin, which is based on anaverage of the programs previous five-year mar-gins, less the highest and lowest. One importantfeature of CAIS is that producers must participatein the program with their own resources. In partic-ular, a producer is required to open a CAIS accountat a participating financial institution and depositan amount based on the level of protection chosen(coverage levels range from 70 percent to 100 per-cent of the reference margin). Once producersfile their income tax returns, the CAIS program ad-ministration uses the tax information to calculatethe producers program year production margin.If the program year margin has declined belowthe reference margin, some of the funds from theproducers CAIS accounts will be available forwithdrawal. Governments match the producerswithdrawals in different proportions for differentcoverage levels.

The total investment by federal and provincialgovernments for the business risk managementprograms is CAN$1.8 billion per year. In 2004, approximately CAN$600 million was provided bygovernments as insurance premium subsidies.

Spain

The Spanish agricultural insurance system isstructured around an established public/privatepartnership. On the public side is the NationalAgricultural Insurance Agency (ENESA), whichcoordinates the system and manages resources forsubsidizing insurance premiums, and the InsuranceCompensation Agency (Consorcio de Compensacinde Seguros) that, together with private reinsurers,provides reinsurance for the agricultural insurancemarket. Local governments are involved only tothe extent that they are allowed to augment pre-mium subsidies offered at the national level. Onthe private side, insurance contracts are sold byAgroseguro, a coinsurance pool of companies thataggregates all insurance companies active in agri-culture. Farmers, insurers, and institutional rep-resentatives are all part of a general commissionhosted by ENESA that functions as the managingboard of the Spanish agricultural insurance system.

Similar to programs in the United States andCanada, Spains combined program offers insur-ance policies covering multiple perils. Policies areavailable for crops, livestock, and aquaculture activ-ities, with risks being pooled across the country by

Approaches to Agricultural Risk in Developed Countries 13

Agroseguro. Compared to the United States andCanada, however, farmers associations are moreactively involved in implementation and develop-ment of agricultural insurance. The governmenthas reserves to cover extreme losses, and, as a finalresort, the government treasury covers losses thatoccur beyond these reserves.

Total premiums for agriculture insurance poli-cies purchased reached around US$550 million( 490 million) in 2003, of which approximatelyUS$225 million ( 200 million) have been providedby the government (Burgaz 2004). The rationale be-hind subsidizing agricultural insurance is that thisoutlay serves as a disincentive for the governmentto also provide free ad hoc disaster assistance. Toreinforce the point, Spanish producers are ineligi-ble for disaster payments for perils for which in-surance is offered. For noncovered perils, ad hocdisaster payments are available, but only if the pro-ducer had already purchased agricultural insur-ance for covered perils.

WHY THE EXPERIENCE OFDEVELOPED COUNTRIES IS NOT A GOOD MODEL FORDEVELOPING COUNTRIESFor various reasons, developing countries shouldavoid adopting approaches to risk managementsimilar those adopted in developed countries.Clearly, developing countries have more limitedfiscal resources than do developed countries. Evenmore importantly, the opportunity cost of thoselimited fiscal resources may be significantly greaterthan in a developed country. Thus, it is critical for adeveloping country to consider carefully how muchrisk management support is appropriate and howto leverage limited government dollars to spur in-surance markets. In developed countries, govern-ment risk management programs are as muchabout income transfers as they are about risk man-agement. Developing countries cannot afford to

facilitate similar income transfers, given the largesegments of the population often engaged in farm-ing. Nonetheless, since a larger percentage of thepopulation in developing countries is typically in-volved in agricultural production or related in-dustries, catastrophic agricultural losses will havea much greater impact on GDP than may occur indeveloped countries.

Policymakers should also carefully consider thevarying structural characteristics of agriculture indifferent countries. In general, farms in developingcountries are significantly smaller than are farmsin countries like the United States and Canada. Fortraditional crop insurance products, smaller farmstypically imply higher administrative costs as a per-centage of total premiums. A portion of these costsare related to marketing and servicing (loss adjust-ment) insurance policies. Another portion is relatedto the lack of farm-level data and cost effectivemechanisms for controlling moral hazard.

Developing countries also have far less accessto global crop reinsurance markets than do devel-oped countries. Reinsurance contracts typicallyinvolve high transaction costs related to due dili-gence. Reinsurers must understand every aspect ofthe specific insurance products being reinsured (forexample, underwriting, contract design, rate mak-ing, and adverse selection and moral hazard con-trols). Some minimum volume of business, or theprospect for strong future business, must be presentto rationalize incurring these largely fixed transac-tion costs. For a global reinsurer to be willing toenter a market, the enabling environment must fos-ter confidence in contract enforcement and institu-tional regulations. An enabling environment is, infact, a prerequisite for effective and efficient insur-ance markets, and these components are largelymissing in developing countries. Setting rules assur-ing that premiums will be collected and that indem-nities will be paid is not a trivial undertaking. Thealternative risk management products discussed inChapter 5 are structured to overcome many of theseproblems.

14 Managing Agricultural Production Risk

15

INDEX INSURANCE ALTERNATIVES16

Given the problems with some traditional crop insurance programsin developed countries, finding new solutions to help mitigate sev-eral aspects of the problems outlined above has become critical. Indexinsurance products offer some potential in this regard (Skees et al.1999). These contingent claims contracts are less susceptible to someof the problems that plague multiple-peril farm-level crop insuranceproducts. With index insurance products, payments are based on anindependent measure highly correlated with farm-level yield orrevenue outcomes. Unlike traditional crop insurance that attemptsto measure individual farm yields or revenues, index insurancemakes use of variables exogenous to the individual policyholdersuch as area-level yield or some objective weather event or measuresuch as temperature or rainfallbut have a strong correlation tofarm-level losses.

For most insurance products, a precondition for insurability is thatthe loss for each exposure unit be uncorrelated (Rejda 2001). For indexinsurance, a precondition is that risk be spatially correlated. Whenyield losses are spatially correlated, index insurance contracts can bean effective alternative to traditional farm-level crop insurance.

Index products also facilitate risk transfer into financial marketswhere investors acquire index contracts as another investment in adiversified portfolio. In fact, index contracts may offer significantdiversification benefits, since the returns generally should be un-correlated with returns from traditional debt and equity markets.

BASIC CHARACTERISTICS OF AN INDEXThe underlying index used for index insurance products must be cor-related with yield or revenue outcomes for farms across a large geo-graphic area. In addition, the index must satisfy a number of additionalproperties affecting the degree of confidence or trust that market par-ticipants have that the index is believable, reliable, and void of humanmanipulation; that is, the measurement risk for the index must be low(Ruck 1999). A suitable index required that the random variable mea-sured meet the following criteria:

observable and easily measured; objective; transparent;

Innovation in ManagingProduction Risk

Index Insurance15

4

independently verifiable; reportable in a timely manner (Turvey 2002;

Ramamurtie 1999); and stable and sustainable over time.

Publicly available measures of weather variablesgenerally satisfy these properties.17

For weather indexes, the units of measurementshould convey meaningful information about thestate of the weather variable during the contractperiod, and they are often shaped by the needsand conventions of market participants. Indexesare frequently cumulative measures of precipita-tion or temperature during a specified time. Insome applications, average precipitation or tem-perature measures are used instead of cumulativemeasures.

New innovations in technology, including theavailability of low-cost weather monitoring sta-tions that can be placed in many locations and sophisticated satellite imagery, will expand thenumber of areas in which weather variables canbe measured as well as of the types of measurablevariables. Measurement redundancy and auto-mated instrument calibration further increase thecredibility of an index.

The terminology used to describe features ofindex insurance contracts resembles that used for fu-tures and options contracts rather than for other in-surance contracts. Rather than referring to the pointat which payments begin as a trigger, for example,index contracts typically refer to it as a strike. Theyalso pay in increments called ticks.

Consider a contract being written to protectagainst deficient cumulative rainfall during a crop-ping season (for example, see Figure 4.1). The writerof the contract may choose to make a fixed paymentfor every one millimeter of rainfall below the strike.If an individual purchases a contract where thestrike is one hundred millimeters of rain and thelimit is fifty millimeters, the amount of payment foreach tick would be a function of how much liabil-ity is purchased. There are fifty ticks between theone hundred millimeter strike and fifty millimeterlimit. Thus, if $50,000 of liability were purchased,the payment for each one millimeter below onehundred millimeters would be equal to $50,000/(100 50), or $1,000.

Once the tick and the payment for each tick areknown, the indemnity payments are easy to calcu-late. A realized rainfall of ninety millimeters, for ex-ample, results in ten payment ticks of $1,000 each,for an indemnity payment of $10,000. Figure 4.1maps the payout structure for a hypothetical $50,000rainfall contract with a strike of one hundred mil-limeters and a limit of fifty millimeters.

In developed countries, index contracts that pro-tect against unfavorable weather events are nowsufficiently well developed that some standardizedcontracts are traded in exchange markets. Theseexchange-traded contracts are used primarily byfirms in the energy sector, although the range ofweather phenomena that might potentially be in-sured using index contracts appears to be limitedonly by imagination and the ability to parameterizethe event. A few examples include excess or defi-cient precipitation during different times of the year,insufficient or damaging wind, tropical weatherevents such as typhoons, various measures of airtemperature, measures of sea surface temperature,the El Nio southern oscillation (ENSO) tied to ElNio and La Nia, and even celestial weather eventssuch as disruptive geomagnetic radiation from solarflare activity. Contracts are also designed for com-binations of weather events, such as snow and tem-perature (Dischel 2001; Ruck 1999). The potentialfor the use of index insurance products in agricul-ture is significant (Skees 2001).

A major challenge in designing an index insur-ance product is minimizing basis risk. Basis riskrefers to the potential mismatch between index-triggered payouts and actual losses. It occurs whenan insured has a loss and does not receive an in-surance payment sufficient to cover the loss (minusany deductible) or when an insured has a loss andreceives a payment that exceeds the amount of loss.

16 Managing Agricultural Production Risk

Figure 4.1 Payout Structure for a Hypothetical Rainfall Contract

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

0 20 40 60 80 100 120

Rainfall in mm

Inde

mni

typa

ymen

t

Source: Skees 2003.

Innovation in Managing Production Risk 17

Since index-insurance indemnities are triggeredby exogenous random variables, such as area yieldsor weather events, an index-insurance policyholdercan experience a yield or revenue loss and not re-ceive an indemnity. The policyholder may also ex-perience no yield or revenue loss and still receivean indemnity. The effectiveness of index insuranceas a risk management tool depends on how posi-tively correlated farm yield losses are with theunderlying index. In general, the more homoge-neous the area, the lower the basis risk and the moreeffective area-yield insurance will be as a farm-levelrisk management tool. Similarly, the more closelya given weather index actually represents weatherevents on the farm, the more effective the indexwill be as a farm-level risk management tool.18

RELATIVE ADVANTAGES AND DISADVANTAGES OF INDEX INSURANCEIndex insurance can sometimes offer superior riskprotection compared to traditional farm-level,multiple- peril crop insurance. Deductibles, co-payments, or other partial payments for loss arecommonly used by farm-level, multiple-peril in-surance providers to mitigate asymmetric informa-tion problems such as adverse selection and moralhazard. Asymmetric information problems aremuch lower with index insurance because, first, aproducer has little more information than the in-surer regarding the index value, and second, indi-vidual producers are generally unable to influencethe index value. This characteristic of index insur-ance means that there is less need for deductiblesand copayments. Similarly, un