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Environmental Hazards 7 (2007) 62–69

www.elsevier.com/locate/hazards

Papers

Innovation in risk transfer for natural hazards impacting agriculture$

Hector Ibarraa,�, Jerry Skeesb,c

aWorld Bank Commodity Risk Management Group, World Bank, USAbUniversity of Kentucky, USA

cGlobalAgRisk Inc., USA

Abstract

Agricultural income from growing crops is susceptible to a variety of risks—the price of output and the actual amount of output are

generally the largest risk variables. This article focuses on yield risk rather than price risk by reviewing innovation in risk transfer for

natural hazard risk in agriculture. While many higher-income countries have long-standing crop insurance programs, these programs are

not appropriate for lower-income countries. Lower-income countries can ill-afford the subsidies that are used in most multiple peril crop

insurance programs throughout the world. Still, lower-income countries have large numbers of small farms increasing the need for

agricultural insurance to protect against common problems that create disastrous losses for many individual farm households.

r 2007 Published by Elsevier Ltd.

Keywords: Agriculture risk management

1. Introduction

The article begins by briefly reviewing agricultural riskmanagement strategies used by farm households. Next,agricultural insurance is introduced to acquaint the readerwith some of the unique problems associated with this typeof insurance. From this vantage point, the experience ofNorth America is highlighted to make the case for whysuch approaches cannot work in lower-income countries.The article then introduces innovations that use index-based insurance products. While these products holdpromise for lower-income countries with large numbersof small farm households, the article reviews both theadvantages and disadvantages of these products—carefullypointing to situations where index insurance products arenot appropriate. The article is meant as an overview of the

e front matter r 2007 Published by Elsevier Ltd.

vhaz.2007.04.008

s would like to express their appreciation to an anonymous

e many professionals who they have worked with through

ave influenced the thinking in this paper. This paper is a

a larger document produced by CRMG of the World

ing Agricultural Production Risk: Innovations in Devel-

es’’. This document can be found online at http://

orldbank.org/INTARD/Resources/Managing_Ag_Risk_

ing author.

ess: hibarrapando@worldbank.org (H. Ibarra).

topic only. The reader is referred to Skees et al. (2005) for amore comprehensive review of this topic.

2. Agriculture risk management

The strategies farmers use to address the financialconsequences of risk generally can be categorized as riskmitigation, risk transfer, risk diversification, and manage-ment of retained risk. Risk mitigation refers to actions suchas irrigation and pest management that reduce either orboth the probability of a loss occurring and the severityresulting from a loss event. Risk transfer shifts a portion ofa producer’s risk exposure, at some cost, to another entitywilling and more able to diversify the risk. Futures andinsurance markets are the most common risk transfermechanisms. These choices are quite limited in lower-income countries.Risk diversification involves mixing several production

activities be they multiple farm enterprises of adding off-farm income into the household production function. Inlower-income countries diversification is also likely toinvolve selection of low-risk, low-returns strategies thatslow economic growth. Even more troublesome, the verydiversification strategies that are used such as ownership oflivestock can expose farm households to even more risk

ARTICLE IN PRESSH. Ibarra, J. Skees / Environmental Hazards 7 (2007) 62–69 63

during major droughts as forced sales of livestock creates amajor price decline. Dercon (2002) examines risk manage-ment strategies for the rural poor demonstrating that manyof the diversification strategies fail to smooth income forrural households. For example, the common strategy ofusing both farm and off-farm income can also fail during adrought as off-farm employment is tied to farm income.

Even if they utilize available risk mitigation and/or risk-transfer mechanisms, farmers still retain some degree ofrisk exposure and must use additional strategies forsmoothing consumption across time—cutting back anddrawing from savings when times are rough and contribut-ing to savings when times are good. Savings and borrowingcan occur using both formal (e.g., banks) and informalmechanisms (e.g., use of money lenders). While thesemechanisms may work well for low-magnitude losses, evenif they are frequent, they often prove to be inadequate forretained risk that is rare but severe. Weather risk is whollyretained in situations where existing crop-yield insurance iseither not purchased or unavailable by location or crop.Yet in cases where crop-yield insurance is utilized, the lossdeductible is retained.

It is highly likely that risk management strategies alsovary over time as a function of farm household experience,the regulatory environment and changing risk attitudesamong other factors. While this discussion casts riskmanagement strategies as complementary, there may alsobe instances when risk mitigation and coping mechanismsfor retained risk substitute for risk transfer, as seen in theUS crop insurance experience (Glauber, 2004). There arelikely several explanations, but in the absence of risktransfer, risk mitigation and risk coping strategies maypotentially be overwhelmed by catastrophic loss events.Building systems whereby insurance transfers highlycorrelated and catastrophic losses out of the community,and banks and non-banking institutions facilitate savingsand borrowing to assist in coping with more frequent andless severe events, is at the core of designing effectivesystems for agricultural output risk.

3. Agriculture insurance

Insurance is a commonly used risk-transfer mechanismfor property damage throughout the developed world, andin many lower-income countries. Personal liability risk isalso commonly transferred, as is the risk of illness or injuryand loss of life. When purchasing these insurance policies,individuals choose to accept a relatively small, consistentstream of losses (the insurance premiums) rather than facethe risk of a large loss that has a low probability ofoccurrence. Developed countries have many differentinsurance products available. Again, this is not true forlower-income countries. If insurance for property damageis available at all, it is likely that it is only available in theurban areas and largely absent in the rural areas. Thetransaction cost of delivering insurance products toeconomically small rural households is simply too great.

When considering the potential functionality of any risk-transfer instrument, a major consideration is the degree ofcorrelation in financial losses caused by the risk, andbuilding a diversified portfolio of insureds. Aggregatinguncorrelated risks into a single insurance pool reduces thevariance of loss as the mean of the individual variances isalways greater than the variance around the mean loss ofthe pool, a result that follows from the statistical propertyknown as the ‘‘law of large numbers.’’ Society benefitsfrom insurance markets that pool uncorrelated risks, sincethe volatility of the risk faced by the pool is less than thepre-aggregated sum of individual risks (Priest, 1996).Agricultural production losses, especially due to weather

events, tend to be characterized by some degree of positivespatial correlation, since weather patterns are generallysimilar over large geographic areas. Thus, the degree ofpositive correlation is often inversely related to the size ofthe region under consideration: relatively small (large)countries are likely characterized by more (less) positivelycorrelated agricultural losses. Positive spatial correlation oflosses limits the risk reduction that can be obtained bypooling risks from different geographical areas andincreases the variance in indemnities paid by insurers. Asa result, it also increases the cost of maintaining adequatereserves or reinsurance to fund potentially large indem-nities caused by systemic loss events. In general, whenlosses are more positively correlated, insurance is lessefficient as a risk-transfer mechanism.Other risk-transfer markets may be better suited to

highly positively correlated risks. For example, futuresexchange markets exist to transfer risks associated withcommodity prices and interest rates where the underlyingvalues are generally highly correlated. In recent years,various capital market instruments have developed fortransferring highly correlated weather risks or risksassociated with natural disasters (Doherty, 2000; Skees,1999). While growing in significance these markets aregenerally small when compared to conventional reinsur-ance markets.In general, agricultural production losses are typically

neither uncorrelated nor highly positively correlated. Theyare what have been referred to as ‘‘in-between’’ risks (Skeesand Barnett, 1999). This implies that, if used exclusively,neither insurance nor capital market instruments are wellsuited for transferring agricultural production risks. How-ever, a careful blending of these instruments can fosterfurther development of agricultural risk-transfer opportu-nities, and weather index insurance contracts lend them-selves to facilitating that blending.Besides the lack of statistical independence, agricultural

insurance is often plagued by high administrative costs,due, in part, to the risk classification and monitoringsystems that insurers must put in place to forestall theasymmetric information problems associated with moralhazard and adverse selection. Moral hazard occurs whenthe insured changes behavior after the purchase of theinsurance. The changed behavior makes the insured more

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risky than they were prior to purchasing the insurance.Adverse selection occurs when those who are more riskyare attracted to purchase the insurance and those who areless risky chose not to purchase. Obtaining more informa-tion either prior to the sale of insurance or after the sale ofinsurance can mitigate moral hazard and adverse selection.It is costly to obtain more information. Other costs includeacquiring the data needed to establish accurate premiumrates and conducting claims adjustments. As a percentageof the premium, the smaller the policy, typically, the largerthe administrative costs.

Spatially correlated risk, moral hazard, adverse selec-tion, and high administrative costs are all importantreasons why agricultural insurance markets may fail.Furthermore, insurers must generally load premiums toreflect the possibility of ruin in the early years as thevariance of insuring a correlated risk is higher than thevariance of insuring an uncorrelated risk. If globalreinsurance markets are efficient, what is correlated riskwithin a single country can be placed into a well-diversifiedportfolio of risk globally and reduce the need for this typeof loading. Still the transaction costs of performing duediligence for small volumes of premium in lower-incomecountries make it highly unlikely that reinsurance will beavailable in these countries. Finally, cognitive failureamong potential insurance purchasers and ambiguityloading on the part of insurance suppliers are otherpossible causes of agricultural insurance market failure.1

If consumers fail to recognize and plan for low-frequency, high-consequence events, the likelihood thatan insurance market will emerge diminishes. Whenconsidering an insurance purchase, the consumer mayhave difficulty determining the value of the contract or,more specifically, the probability and magnitude of lossrelative to the premium (Kunreuther and Pauly, 2001).Many decision makers tend to underestimate their ex-posure to low-frequency, high-consequence losses. Thus,they are unwilling to pay the full costs of an insuranceproduct that protects against these losses. Low-frequencyevents, even when severe, are frequently discounted orignored altogether by producers trying to determine thevalue of an insurance contract. The evaluation of prob-ability assessments regarding future events is complex andoften entails high search costs. Many people resort tovarious simplifying heuristics, but probability estimatesbased on these heuristics may differ greatly from the trueprobability distribution (Schade et al., 2002; Morgan andHenrion, 1990). The general finding regarding subjectivecrop-yield distributions is that agricultural producersforget extreme low-yield events and tend to overestimatethe mean yield and underestimate the variance (Buzbyet al., 1994; Pease et al., 1993; Dismukes et al., 1989).

On the other hand, insurers will typically load premiumrates heavily for low-frequency, high-consequence events

1See Skees et al. (2005) background paper for more discussion of

‘‘cognitive failure’’ and ‘‘ambiguity loading.’’

where considerable ambiguity surrounds the actual like-lihood of the event (Schade et al., 2002; Kunreuther et al.,1995). Ambiguity is especially serious when consideringhighly skewed probability distributions with long tails, as istypical of crop yields. Uncertainty is further compoundedwhen the historical data used to estimate probabilitydistributions are incomplete or of poor quality, a verycommon problem in lower-income countries. Small samplesize creates large measurement error, especially when theunderlying probability distribution is heavily skewed.Kunreuther et al. (1993) demonstrate via experimentaleconomics that when risk estimates are ambiguous, loadson insurance premiums can be 1.8 times higher than wheninsuring events with well specified probability and lossestimates.Together, these effects create a wedge between the prices

that farmers are willing to pay for catastrophic agriculturalinsurance and the prices that insurers are willing to accept.Thus, functioning private-sector markets may fail tomaterialize or, if they do materialize, they may cover onlya small portion of the overall risk exposure (Pomareda,1986).

4. Approaches to agriculture insurance in developed

countries

To better understand agricultural risk managementmarkets and government policies to facilitate access torisk management instruments, it is worthwhile to analyzecritically the experiences of some developed countries. TheUnited States and Canada have long established a quitesophisticated multiple peril crop insurance programs. Inboth countries, the programs have undergone significantchanges in the past 20–30 years. In both countries, heavygovernment subsidies are used (e.g., in the US farmers payonly about 30 percent of the total costs of the agriculturalinsurance). These subsidies mask many of the underwritingproblems that are inherent in offering individual multipleperil crop insurance. If farmer premiums are subsidized, itmakes the premiums more attractive to those farmers whorepresent better risk than the pool of farmers who wouldpurchase without the subsidies. Thus, given premiumsubsidies with little attention to individual underwriting,the higher risk farmers will still end up with more transfers.Two major differences between the US and Canadian

crop insurance programs involve the delivery systems andthe role of provinces in designing alternative products inCanada. The US uses the private sector to deliver cropinsurance. The Canadians deliver crop insurance viaprovincial government entities. In the US there is oneRisk Management Agency (RMA) in the United StatesDepartment of Agriculture that is responsible for main-tenance of existing products and the development of newproducts. The RMA also sets premium rates. Unlike theUS, in Canada provinces have a degree of autonomy totailor design products that fit their region. Provinces have arelationship with Federal government in Canada to

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provide some of the subsidy and reinsurance capacityunder the broader umbrella of Canadian agricultural safetynet policy.

There are several common elements among the NorthAmerican crop insurance programs. Each of the programs:

1.

Mixing both social and market-based goals. 2. Core products that involve insurance at the farm level

for multiple perils.

3. Government subsidies that are linked to premiums on a

percentage basis.

4. Government subsidies or government agencies for the

administrative cost of the program.

5. A major role for government in pooling and holding

some of the most catastrophic risk.

A fundamental challenge for any country rethinkingcurrent approaches to agricultural insurance programs orattempting to design new instruments, including indexedweather insurance, is to critically assess key features thatare common to existing government-facilitated agriculturalinsurance programs.

5. Why the experience of developed countries is not a good

model for lower-income countries

For various reasons, lower-income countries shouldavoid adopting approaches to risk management similar tothose adopted in developed countries because the oppor-tunity cost of their more limited fiscal resources may besignificantly greater than in a developed country. Thus, it iscritical for a developing country to consider carefully howmuch risk management support is appropriate and howto leverage limited government dollars to spur insurancemarkets. Governments in lower-income countries cannotafford to facilitate income transfers, given the largesegments of the population often engaged in farming.Nonetheless, since a larger percentage of the population inlower-income countries is typically involved in agriculturalproduction or related industries, catastrophic agriculturallosses will have a much greater impact on GDP than mayoccur in developed countries.

Policymakers should also carefully consider the varyingstructural characteristics of agriculture in different coun-tries. For traditional crop insurance products, the typicallysmaller farms in lower-income countries imply higheradministrative costs as a percentage of total premiumsdue to marketing and servicing (loss adjustment) insurancepolicies, lack of farm-level data, and lack of cost effectivemechanisms for controlling moral hazard.

Lower-income countries also have far less access toglobal crop reinsurance markets than do developedcountries. Reinsurance contracts typically involve hightransaction costs related to due diligence. Reinsurers mustunderstand every aspect of the specific insurance productsbeing reinsured (for example, underwriting, contract de-sign, rate making, and adverse selection and moral hazard

controls). Some minimum volume of business, or theprospect for strong future business, must be present torationalize incurring these largely fixed transaction costs,and the enabling environment must foster confidence incontract enforcement and institutional regulations. Thesecomponents are largely missing in lower-income countries.Setting rules assuring that premiums will be collected andthat indemnities will be paid is not a trivial undertaking.

6. Innovation in managing production risk: index insurance

Index insurance products offer some potential newsolutions to help mitigate several aspects of the problemsoutlined above (Skees et al., 1999). These contingent claimscontracts are less susceptible to some of the problems thatplague multiple-peril farm-level crop insurance products.Unlike traditional crop insurance that attempts to measureindividual farm yields or revenues, index insurance makesuse of variables exogenous to the individual policyholder—such as area-level yield or some objective weather event ormeasure such as temperature or rainfall—but have a strongcorrelation to farm-level losses.For most insurance products, a precondition for insur-

ability is that the loss for each exposure unit be uncor-related (Rejda, 2001). For index insurance, a preconditionis that risk be spatially correlated. When yield losses arespatially correlated, index insurance contracts can bean effective alternative to traditional farm-level cropinsurance.Index products also facilitate risk transfer into financial

markets where investors acquire index contracts as anotherinvestment in a diversified portfolio. In fact, indexcontracts may offer significant diversification benefits toinvestors, since the returns generally should be uncorre-lated with returns from traditional debt and equitymarkets.

7. Basic characteristics of an index

The underlying index used for index insurance productsmust be correlated with yield or revenue outcomes forfarms across a relatively large geographic area. In addition,the index must satisfy a number of additional propertiesaffecting the degree of confidence or trust that marketparticipants have that the index is believable, reliable, andvoid of human manipulation; that is, the measurement riskfor the index must be low (Ruck, 1999). A suitable indexrequires that the random variables measured meet thefollowing criteria:

�

Observable and easily measured; � Objective; � Transparent; � Independently verifiable; � Reportable in a timely manner (Turvey, 2002; Ramamurtie,

1999); and

� Stable and sustainable over time.

ARTICLE IN PRESS

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

0 10 20 30 40 50 60 70 80 90 100 110

Rainfall in mm

Indem

nity P

aym

ents

Fig. 1. Payout structure for a hypothetical rainfall contract. Source: Skees

(2003).

H. Ibarra, J. Skees / Environmental Hazards 7 (2007) 62–6966

Publicly available measures of weather variables gene-rally satisfy these properties.2

3Basis risk also exists with traditional farm-level, multiple-peril crop

yield insurance. Typically, a small sample size is used to develop estimates

of the central tendency in farm-level yields (for example, 4–10 years in the

United States). Given simple statistics about the error of small sample

estimates, it can be demonstrated that these procedures can generate large

mistakes when estimating expected farm-level yield. This makes it possible

for farmers to receive insurance payments when yield losses have not

occurred and to fail to receive payments when yields are indeed below

normal. Thus, basis risk occurs not only in index insurance but also in

farm-level yield insurance. Another type of basis risk results from the

For weather indexes, the units of measurement shouldconvey meaningful information about the state of theweather variable during the contract period, and they areoften shaped by the needs and conventions of marketparticipants. Indexes are frequently cumulative measures ofprecipitation or temperature during a specified time. Insome applications, average precipitation or temperaturemeasures are used instead of cumulative measures.

Innovations in technology, including the availabilityof low-cost weather monitoring stations that can beplaced in many locations and sophisticated satelliteimagery, will expand the number of areas in which weathervariables can be measured as well as of the types ofmeasurable variables. Measurement redundancy and auto-mated instrument calibration further increase the credi-bility of an index.

The terminology used to describe features of indexinsurance contracts resembles that used for futures andoptions contracts rather than for other insurance contracts.Rather than referring to the point at which payments beginas a trigger, for example, index contracts typically refer toit as a strike. They also pay in increments called ticks.

Consider a contract being written to protect againstdeficient cumulative rainfall during a cropping season.Fig. 1 maps the payout structure for a hypothetical $50,000rainfall contract with a strike of 100mm and a limit of50mm.

The writer of the contract may choose to make afixed payment for every 1mm of rainfall below the strike.If an individual purchases a contract where the strike is100mm of rain and the limit is 50mm, the amount ofpayment for each tick would be a function of how muchliability is purchased. There are 50 ticks betweenthe 100mm strike and 50mm limit. Thus, if $50,000 ofliability were purchased, the payment for each 1mmbelow 100mm would be equal to $50,000/(100�50), or$1000. Once the tick and the payment for each tick are

2By contrast, area-yield indexes in developing countries often are not

measured in a reliable and timely manner.

known, the indemnity payments are easy to calculate.A realized rainfall of 90mm, for example, results in tenpayment ticks of $1000 each, for an indemnity paymentof $10,000.In developed countries, index contracts that protect

against unfavorable weather events are now sufficientlywell developed that some standardized contracts are tradedin exchange markets. These exchange-traded contracts areused primarily by firms in the energy sector, although therange of weather phenomena that might potentially beinsured using index contracts appears to be limited only byimagination and the ability to parameterize the event.A few examples include excess or deficient precipitationduring different times of the year, insufficient or damagingwind, tropical weather events such as typhoons, variousmeasures of air temperature, measures of sea surfacetemperature, the El Nino southern oscillation (ENSO)tied to El Nino and La Nina, and even celestialweather events such as disruptive geomagnetic radiationfrom solar flare activity. Contracts are also designed forcombinations of weather events, such as snow andtemperature (Dischel, 2001; Ruck, 1999). The potentialfor the use of index insurance products in agriculture issignificant (Skees, 2001). In the US, weather derivativeswitnessed a dramatic 4-fold growth from 2004–2005 to2005–2006 of roughly $10 billion to a forecast in excess of$40 billion of notional risk (Weather Risk ManagementAssociation).A major challenge in designing an index insurance

product is minimizing basis risk. Since index-insuranceindemnities are triggered by exogenous random variables,such as area yields or weather events, an index-insurancepolicyholder can experience a yield or revenue loss and notreceive an indemnity or may experience no yield or revenueloss and receive an indemnity. The effectiveness of indexinsurance as a risk management tool depends on howpositively correlated farm yield losses are with the under-lying index. In general, the more homogeneous the area,the lower the basis risk and the more effective area-yieldinsurance will be as a farm-level risk managementtool. Similarly, the more closely a given weather indexactually represents weather events on the farm, the moreeffective the index will be as a farm-level risk managementtool.3

estimate of realized yield. Even with careful farm-level loss adjustment

procedures, it is impossible to avoid errors in estimating the true realized

yield. These errors can also result in under- and overpayments.

ARTICLE IN PRESSH. Ibarra, J. Skees / Environmental Hazards 7 (2007) 62–69 67

8. Relative advantages and disadvantages of index insurance

Index insurance can sometimes offer superior risk pro-tection compared to traditional farm-level, multiple-perilcrop insurance. Asymmetric information problems aremuch lower with index insurance because, first, a producerhas about the same information as the insurer regardingthe index value, and second, individual producers aregenerally unable to influence the index value. Thischaracteristic of index insurance means that there is lessneed for deductibles and co-payments. Similarly, unliketraditional insurance, few restrictions need be placed on theamount of coverage an individual purchases. As long asthe individual farmer cannot influence the realized value ofthe index, liability need not be restricted. An exceptionoccurs when governments offer premium subsidies as apercentage of total premiums. In this case, the governmentmay want to restrict liability (and thus, premium) to limitthe amount of subsidy paid to a given policyholder. Keyadvantages and challenges are summarized in Table 1.

As more sophisticated systems (such as satellite imageryand accompanying models) are developed to measureevents causing widespread losses, indexing major eventsshould become more straightforward and quite acceptableto international capital markets. Under these conditions,traditional reinsurers and primary providers may beginoffering insurance in countries they would never previouslyhave considered. New risk management opportunities can

Table 1

Advantages and disadvantages of index insurance

Advantages Challeng

Less moral hazard Basis risk

The indemnity does not depend on the individual producer’s

realized yield

Without

is not an

smaller b

insurers;

extreme e

Less adverse selection

The indemnity is based on widely available information, so

there are few informational asymmetries to be exploited

Lower administrative costs Precise a

Underwriting and inspections of individual farms are not

required

Insurers

Education

Standardized and transparent structure Users mu

managem

Contracts can be uniformly structured Market s

Availability and negotiability The mark

Standardized and transparent, the contracts may be traded in

secondary markets

Reinsurance function Weather

Index insurance can be used to transfer the risk of widespread

correlated agricultural production losses more easily

Actuarial

change th

Versatility

Index contracts can be easily bundled with other financial

services, mitigating basis risk problems via savings and lending

Microclim

These pro

for freque

Forecasts

Asymmet

the poten

Source: Authors. Please note that nearly all of the challenges listed above are

develop if relevant, reliable, and trustworthy indexes can beconstructed.

9. The trade-off between basis risk and transaction costs

Among the most significant issues for any insuranceproduct is the question of how much monitoring andadministration is needed to keep moral hazard and adverseselection to a minimum. To accomplish this goal,coinsurance and deductibles are used so that the insuredshares the risk and any mistakes in offering too generouscoverage are mitigated. Considerable information is neededto tailor insurance products and to minimize the basis riskeven for individual insurance contracts. Increased informa-tion gathering and monitoring involve higher transactioncosts, which convert directly into the higher premiumsneeded to cover them. Index insurance significantly reducesthese transaction costs and can be written with lowerdeductibles and without introducing coinsurance. Whenfarm yields are highly correlated with the index being usedto provide insurance, offering higher levels of protectioncan result in risk transfer superior even to individualmultiple-peril crop insurance (Barnett et al., 2005).The direct trade-off between basis risk and transaction

costs has implications for achieving sustainable productdesigns and for outlining the role of governments andmarkets. These concepts also greatly depend on under-standing the trade-off between basis risk and transaction

es

sufficient correlation between the index and actual losses, index insurance

effective risk management tool. This is mitigated by self-insurance of

asis risk by the farmer; supplemental products underwritten by private

blending index insurance and rural finance; and offering coverage only for

vents

ctuarial modeling

must understand the statistical properties of the underlying index

st be able to assess whether index insurance will provide effective risk

ent

ize

et is still in its infancy in lower-income countries and has some start-up costs

cycles

soundness of the premium could be undermined by weather cycles that

e probability of the insured events, such as El Nino, for example

ates

duction conditions make rainfall or area-yield index based contracts difficult

nt and localized events

ric information about the likelihood of an event in the near future creates

tial for intertemporal adverse selection

challenges for any insurance products.

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costs. At every level of risk transfer, someone must accept acertain degree of basis risk if the products are to be bothsustainable and affordable. In short, extremely hightransaction costs must be paid for. The social cost ofhaving products with some basis risk may be significantlylower than the social cost associated with the hightransaction cost entailed in attempting to design productsthat have no basis risk. Additionally, to the extent that thebasis risk is relatively small, diversification can be used tomanage basis risk.

10. Where index insurance is inappropriate

Index insurance contracts will not work well for allagricultural producers. Many agricultural commodities aregrown in microclimates—areas with very large differencesin weather patterns within only a few miles. In highlyspatially heterogeneous production areas, basis risk willlikely be so high that index insurance will not work. Underthese conditions, index insurance will work only if it ishighly localized4 and/or can be written to protect onlyagainst the most extreme loss events. Even in these cases, itmay be critical to tie index insurance to lending, since loansare one method of mitigating basis risk. Again, diversifica-tion can be the other mechanism for mitigating basis risk.Finally, it should be noted that microinsurance couldpotentially work for areas where the weather risk is largelyindependent.

Overfitting the data is another concern with indexinsurance. If one has a limited amount of crop yield data,fitting the statistical relationship between the index andthat limited data can become problematic. Small samplesizes and fitting regressions within the sample can lead tocomplex contract designs that may or may not be effectivehedging mechanisms for individual farmers. Standardprocedures that assume linear relationships between theindex and realized farm-level losses may be inappropriate.While scientists are tempted to fit complex relationships tocrop patterns, interviews with farmers may reveal moreabout the types of weather events of most concern. Whendesigning a weather index contract, one may be tempted tofocus on the relationship between weather events and asingle crop. When it fails to rain for an extended period oftime, however, many crops will be adversely affected.Likewise, when it rains for an extended period of time,resulting in significant cloud cover during critical photo-synthesis periods, a number of crops may suffer. Part of thedevelopment of index insurance for weather risk in Indiahas involved offering insurance that is tied to differentperiods within the growing season so as to protect against acommon problem that impacts a number of crops.

Finally, when designing index insurance contracts,significant care must be taken to assure that the insuredhas no better information about the likelihood and

4Temperature, for example, can be measured with field lodged

temperature gauges that automatically transmit data to a central server.

magnitude of loss than does the insurer. Farmers’ weatherforecasts are quite often highly accurate. Potato farmers inPeru, using celestial observations and other indicators innature, are able to forecast El Nino at least as well as manyclimate experts (Orlove et al., 2002).In 1988, an insurer offered drought insurance in the US

Midwest. As the sales closing date neared, the companynoted that farmers were significantly increasing theirpurchases of these contracts. Rather than recognize thatthese farmers had already made a conditional forecast thatthe summer was going to be very dry, the companyextended the sales closing date and sold even more rainfallinsurance contracts. The company experienced very highlosses and was unable to meet the full commitment of thecontracts. Rainfall insurance for agriculture in the UnitedStates suffered a significant setback. The lesson learned isthat when writing insurance based on weather events, it iscrucial to be diligent in following and understandingweather forecasts and any relevant information availableto farmers.Farmers have a vested interest in understanding the

weather and climate. Insurance providers who venture intoweather index insurance must know at least as much asfarmers do about conditional weather forecasts. If not,intertemporal adverse selection will render the indexinsurance product unsustainable. These issues can beaddressed; typically, the sales closing date must beestablished in advance of any potential forecastinginformation that would change the probability of a lossbeyond the norm. But beyond simply setting a sales closingdate, the insurance provider must have the discipline andthe systems in place to ensure that no policies are soldbeyond that date.

11. Summary and conclusions

This article provides an overview of why traditionalapproaches to agricultural insurance are not appropriatefor many lower-income countries that are dominated by alarge number of small farms. By framing the problem asone of high transaction costs and correlated risk due tocommon weather events, scholars have argued that use ofweather index insurance may offer more appropriateapproaches. Still these products are in their early stagesof development and are not without their own problems—basis risk and data constraints in lower-income countriesare among the largest problems.Some progress is being made in the implementation of

index-based agricultural insurance products. India hasadopted a number of weather-based insurance productsin recent years. Both the government agricultural insurerand private insurers are offering index insurance forweather risk in India. The World Bank and others areinvolved in a large number of feasibility studies todetermine how such innovations can be introduced to easethe suffering and losses associated with weather relatedcrop failure (Hess et al., 2005). A critical aspect of all of

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this thinking is the explicit recognition that many weatherevents impacted a large number of individuals at the sametime creating larges losses. The need to transfer this type ofcorrelated risk out of local communities is large. Index-based weather insurance products can be a key ingredientin meeting that need. Nonetheless, in every case theadoption of these innovations must be put into a localcontext that explicitly recognizes the nature of the risk, thecurrent risk-coping and risk management strategies of ruralhouseholds, and the markets and institutions within thecountry.

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Review 54, 15–23.

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