INNOVATIVE INSTITUTIONAL RISK MANAGEMENT STRATEGIES FOR PROMOTING SMALLHOLDER AGRICULTURAL CREDIT IN

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International Seminar Catastrophic Agricultural Insurance for Development Banks Lima, Peru, 6 November 2015

INNOVATIVE INSTITUTIONAL RISK MANAGEMENT STRATEGIES FOR PROMOTING SMALLHOLDER AGRICULTURAL CREDIT IN LATIN AMERICA

Preliminary Report Submitted to the Asociaciรณn Latinoamericana de Instituciones Financieras para el Desarrollo Lima, Peru May 12, 2015

Mario J. Miranda Professor of Agricultural, Environmental, and Development Economics The Ohio State University Columbus, Ohio, USA


Introduction The ability of Development Finance Institutions (DFIs) to reach the rural poor whose livelihoods depend on agriculture is impeded by various factors that render agricultural loans less profitable and much riskier than other commercial loans. These factors include high transactions costs, lack of adequate collateral, and exposure to droughts, pestilence, low commodity prices and other systemic shocks that can exert profound financial stress on large numbers of smallholders simultaneously, leading to widespread loan defaults that can threaten the bank’s solvency. Over the past 20 years, the international development community has been gaining experience with a variety of innovative financial technologies to address the special problems of agricultural lending in developing countries, particularly lending to marginalized smallholders with limited collateral. These include joint-liability group lending, mobile banking, and aggregate financing through outgrower, processor, and cooperative marketing agreements. They also include innovative “index” insurance products to manage the risks endemic to smallholder agricultural production, most notably those associated with drought and other catastrophic weather events. The Food and Agriculture Organization of the United Nations (FAO), in collaboration with the Asociación Latinoamericana de Instituciones Financieras para el Desarrollo (ALIDE), seeks to explore how novel financial technologies based on index insurance and its variants could be used to promote smallholder agricultural credit in Latin America. As with any promising new idea, research into financial market and product development will be needed to best tailor the new technologies to the local market and regulatory contexts. The purpose of this technical report is to provide ALIDE managers with sufficient information to judge whether such research it is worth pursuing. The report focuses on how index insurance and its variants could be used to expand credit to under-collateralized smallholders. The report draws from lessons learned from agricultural credit and insurance research and pilot projects implemented throughout the developing world over the past two decades and concludes with a series of key questions that ALIDE members and other stakeholders will need to answer for FAO to conduct its assessments and generate useful recommendations. Challenges of Smallholder Credit All institutional lenders face similar decisions. They must decide who to lend to, how much to lend, what interest rates to charge, what collateral requirements to impose, and what actions to take in the event that loan is not repaid on time, including whether to restructure debt, confiscate collateral though legal action, or simply write-off the debt, absorb the loss, and discontinue lending to the delinquent borrower. In order to maximize profit and minimize risk, lenders tend to employ time-tested and generally accepted lending practices. These practices include performing due-diligence of potential borrowers to assess the profitability and riskiness of their business enterprises, and, more generally, to gauge the likelihood that they will repay their loans in a timely way. Based on these practices, lenders tend to prefer large, reputable customers with whom they can enter into long-term commercial relationships; they tend to prefer customers who possess collateral in the form of tangible assets that can be readily liquidated in the event that a loan is not repaid; and, above all else, they tend to prefer customers whose business income is relatively stable over time and not exposed to excessive risk. Loan default risk is addressed one customer at a time. However, standard lending practices can prove ineffective when applied to agricultural smallholder credit. Smallholders are relatively poor and operate on a smaller scale than other business enterprises. They tend to own few marketable assets and often possess weak legal claims on their land, rendering them incapable of offering adequate collateral; they tend to be geographically dispersed and hard to reach, implying that loan marketing, origination and 1


enforcement costs are relatively high; they tend to lack financial literacy and experience with modern financial risk management practices; and, above all else, they tend to have incomes that are highly variable, particularly if they employ traditional agricultural production practices that expose them to the vagaries of weather. Development finance banks are thus confronted with a dilemma. On the one hand, although maximizing profit may not be their overarching objective, development finance banks are still expected to remain solvent without placing excessive demands on government and donors for subsidies to achieve sustainability. This forces them to employ conservative credit practices involving proper collateralization and risk avoidance. On the other hand, development finance banks are expected to provide credit to marginal agricultural borrowers who possess limited collateral and have highly variable incomes, for whom standard credit practices tend to be ineffective, if not wholly impracticable. The two sets of objectives are fundamentally in conflict. Many development finance banks have failed to adequately resolve the dilemma of agricultural credit, particularly as it pertains to smallholder farmers. For the most part, development finance banks have tended to fall back on standard lending practices based on securing adequate collateral and avoiding, rather than managing, risk. Standard lending practices have enabled agricultural development banks to provide credit to the more commercially viable enterprises in the agricultural value chain, such as large-scale farmers, outgrowers, processors, and exporters, all of which tend to possess extensive commercial experience and adequate collateral. However, reliance on standard lending practices has effectively excluded smallholders on the peripheries of the agricultural value chain from access to affordable credit. In order to fulfill their mandates to reach the poor farmer, while observing fiscal sustainability constraints, development finance banks need to explore novel approaches to lending that deviate from standard commercial practices. Over the past two decades, a variety of promising new lending technologies have been proposed and put to the test throughout the developing world. Perhaps none has received more attention than “index” insurance. Index Insurance Index insurance is a contingent claims contract that pays an indemnity to the policyholder based, not on verifiable losses suffered by the policyholder, as with conventional insurance, but rather an objectively observable random variable or “index” that is highly correlated with losses and which cannot be influenced by the actions of the policyholder. Rainfall is the index most commonly used in the design of agricultural index insurance contracts. It is most often used to fashion insurance contracts that protect against drought. A simple rainfall index insurance contract might pay an indemnity if the total rainfall measured at a specific weather station over a specific period of time falls below a specific target. In some parts of the world, however, were excess rainfall is the greatest threat to agricultural production, the rainfall index insurance contract might be designed to pay an indemnity if the total rainfall rises above a specific target. Other indices have been used or otherwise considered in index insurance designs, including temperature, humidity, and El Niño-Southern Oscillation (ENSO) indices. Indices that are not, strictly speaking, weather variables, but which nonetheless serve as proxies for the impact of widespread shocks on agricultural production, have also been employed in index insurance designs, including average area yields, flood levels, river flows, satellite-measured vegetation indices, and regional livestock mortality rates. Compound combinations of weather indices and prices have also been fashioned to directly address variation in both production and prices (Halcrow, 1949; Miranda, 1991; Miranda and Vedenov, 2001; Bryla and Syroka, 2007). Index insurance presents an alternative to more conventional forms of agricultural insurance available in the developed world, of which the most common is multiple-peril crop insurance (MPCI). MPCI offers farmers coverage against verifiable losses arising from any one of a variety of perils, including drought, excessive rainfall, frost, hot waves, windstorms, pestilence, and crop diseases. An MPCI policyholder whose final crop yield falls below a specified target, say, 75% of their “normal” yield, submits a loss claim to the insurance company. The 2


insurance company then sends an agent to the farm to verify the loss and pays an indemnity to the policyholder for the assessed loss. However, MPCI suffers from a variety of well-known structural problems, including moral hazard, adverse selection, and high transactions costs (Glauber, 2004). Moral hazard, also known as the “hidden action” problem, arises when farmers, after purchasing insurance, alter their production practices in a manner that increases their chances of collecting an indemnity. Adverse selection, also known as the “hidden information” problem, arises because farmers are better informed about the distribution of their own production losses than the insurer, prompting farmers who recognize their premiums are actuarially low to acquire insurance in greater numbers than those whose premiums are actuarially high. Moral hazard and adverse selection can both cause the insurer's indemnity outlays to rise in the long-run, making the insurance operation unprofitable. Both problems can be especially acute in developing countries due to higher costs of monitoring farmer actions and absence of reliable production records needed to assess farm-level risk. The structural problems associated with MPCI render it extremely expensive, with unsubsidized premium rates more than twice the expected indemnity not entirely uncommon. Few farmers are willing to pay premiums that reflect the true cost of MPCI. As a result, all major MPCI programs operating in the developed world have been sustained only through massive government financial support that can include premium subsidies for farmers, reimbursement of insurer administrative costs, and subsidized reinsurance (Hazell, 1992; Mahul and Stutley, 2010). Due to its high costs, MPCI is not practicable for developing countries with limited fiscal resources. Index insurance, in contrast, avoids many of the problems that undermine MPCI, and has been hailed by many as a potential solution to the agricultural risk management problems of the developing world. Because the insured cannot significantly influence the value of the index, and thus the indemnity paid by the contract, index insurance is essentially free of moral hazard. Because an index insurance contract's premium rate is typically based on publicly available information, not privately held information, index insurance is largely free of adverse selection. Because index insurance does not require individually-tailored terms of indemnification or separate verification of individual loss claims, index insurance is less expensive to administer. And because index insurance has simpler information requirements and exhibits greater uniformity and transparency of contract, it is easier to market and reinsure. These features of index insurance can substantially reduce its cost relative to MPCI, making it more affordable, particularly to poor agricultural producers in the developing world. Since the late 1990s, a significant number of agricultural index insurance feasibility studies and pilot projects have been undertaken throughout the developing world, including Bangladesh, Burkina Faso, China, Ethiopia, Guatemala, Honduras, India, Indonesia, Jamaica, Kenya, Malawi, Mexico, Mongolia, Morocco, Nicaragua, Peru, Senegal, Thailand, and Vietnam. These activities have been undertaken and/or financially supported by organizations as diverse as the World Bank, the United States Agency for International Development (USAID), Asian Development Bank (ADB), Inter-American Development Bank (IADB), International Livestock Research Institute (ILRI), the United Kingdom Department for International Development (DfiD), and United Nations World Food Program (UNWFP), among others. Activities undertaken by major organizations in these index insurance projects have been broad in scope, and have included: designing an actuarial rating index insurance contracts; educating farmers, lenders, insurers, government officials, regulators, and academics regarding the potential beneficial uses of index insurance; acquiring, validating, and statistically analyzing weather and agricultural production data; assessing the adequacy of weather station network density, security, and real-time reporting capabilities; evaluating the feasibility of insurance indices other than rainfall and developing new technologies for measuring them; forging functional institutional relationships among farmers, lenders, insurers, reinsurers, government agencies, and non-governmental organizations; identifying and testing

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alternative ways to incorporate index insurance into farm, firm, and governmental risk management strategies; and improving insurance marketing and delivery mechanisms. Micro Index Insurance The results of most index insurance pilot programs implemented in the developing world, however, have proved disappointing, often with limited and sometimes negative impact on credit. Early programs envisioned index insurance as a “micro insurance” product aimed at managing the individual smallholder’s risk, with the smallholder paying part or all of the insurance premium and directly receiving any indemnity it might pay. However, significant uptake of micro index insurance among smallholders in developing countries has almost universally been found to occur only when the premiums are heavily subsidized, with the demand disappearing as soon as the subsidy is eliminated (Miranda and Farrin, 2012). Moreover, even when premiums are heavily subsidized, smallholders too often use micro index insurance indemnities to finance shortfalls in consumption, rather than to repay their loans. Indeed, in some cases, micro index insurance has been found to increase loan defaults by implicitly reducing the severity of punishment associated with default (Clarke and Dercon, 2009). The failure of early micro index insurance programs to have a sustainable positive impact on smallholders and smallholder credit are now generally understood to be due to “basis risk” (Miranda, 1991; Jensen, Mude and Barrett 2014; Carter 2011; Doherty and Richter, 2002). Basis risk refers to the failure of micro index insurance to pay indemnities that perfectly match the losses of the insured. In particular, since the indemnity paid by micro index insurance is based on a broad index rather than farm-specific losses, it is possible for the smallholder to suffer a significant loss without receiving an indemnity, if the loss is attributable to factors unrelated to the index. For example, a farmer may lose his crop to a fire or a hailstorm and not receive an indemnity from his drought insurance contract because rainfalls were normal. Due to basis risk, smallholders judge the protection offered by micro index insurance to be incomplete and not worth paying premiums that reflect the full economic costs of the insurance. Smallholders will purchase micro index insurance, but only if heavily subsidized, suggesting that they acquire micro index insurance primarily to capture the subsidies it embodies, rather than to manage risk. Meso Index Insurance As a result of the disappointing experiences with micro index insurance in the developing world, development economists and insurance experts are now turning to the use of index insurance as a “meso insurance” product aimed, not at the management of the smallholder’s risk, but rather the risk faced by the institutions that lend to them, most notably agricultural banks, microfinancial institutions, agricultural input providers, and agricultural processors. The key difference between meso and micro index insurance is that, with meso index insurance, the lender, not the smallholder, receives the indemnity paid by the insurer and thus controls its use. Micro and meso index insurance play different roles in the agricultural credit chain. To understand this, consider the special risk management problems faced by agricultural lenders, for example, a development finance bank with a significant smallholder credit portfolio. Any bank assumes a risk when they extend a loan to an individual borrower. Even the best borrowers can suffer an unanticipated income shock resulting from death, illness, accident, fire, theft, or other common peril, rendering them unable to repay a loan on time, if at all. However, these shocks are mainly idiosyncratic, that is, the shocks are independent across borrowers. Idiosyncratic shocks are diversifiable when combined in sufficient number in the bank’s overall loan portfolio and thus have predictable effects on the bank’s loan portfolio. As such, idiosyncratic shocks do not pose a risk to the bank, per se. Rather, they constitute a predictable cost of business that can be recovered by charging a higher interest rate.

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Agricultural banks, however, are different from other banks. When an agricultural bank extends loans to farmers, it assumes non-idiosyncratic systemic risk in the form of exposure to adverse weather or fluctuating output prices. Adverse systemic weather and agricultural price shocks affect large numbers of farmer borrowers simultaneously, and thus are not diversifiable in the bank’s agricultural loan portfolio. As such, a bank heavily invested in unsecured smallholder credit would experience aggregate default rates that can fluctuate dramatically over time, threatening the bank’s solvency. Although micro index insurance may provide limited benefits to individual farmers, meso index insurance can prove valuable as a risk management instrument for a lender that provides credit to many farmers simultaneously. A lender such as an agricultural bank effectively diversifies much of the idiosyncratic risks borne by its borrowers and thus faces lower basis risk with a meso index insurance contract than its borrowers face individually with a micro index insurance contract. That is, an index that measures systemic agricultural production shocks in a bank's geographical scope should track the bank's cash flow shortfalls more closely than those of any one individual borrower. Meso index insurance, in theory, can be used by banks to manage the risk endemic to their agricultural loan portfolios. By efficiently managing the systemic risk embodied in agricultural loan portfolios using properly designed meso index insurance, lenders can substantially reduce the risk of liquidity shortfalls that can result in insolvency or otherwise impose high external financing and other adjustment costs on the bank. This would allow banks to offer more loans to smallholders at lower interest rates (Miranda and Gonzalez-Vega, 2011; Farrin and Miranda, 2013; Guizar-Mateos, Gonzalez-Vega and Miranda 2014). However, questions remains about how best to integrate meso index insurance into bank agricultural lending and risk management practices. Arguably, the most efficient and direct method is for the bank to adopt a holistic approach to risk management, rather than relying on traditional risk avoidance. Under this approach, a bank would purchase index insurance to hedge its risk of widespread defaults among agricultural borrowers due to a droughts or other natural disasters. The optimal meso index insurance contract would be designed to provide indemnities when aggregate rates of loan defaults among the target smallholder borrower population are likely to rise due to a systemic shock. Holistic risk management of the agricultural loan portfolios, however, is not without some impediments. First, many agricultural banks lack a culture of risk management based on the use of insurance and other market instruments. For the most part, banks are content to manage agricultural risk the traditional way, by avoiding it, and can be resistant to changes in their time-tested lending policies. Second, holistic risk management is opaque with regard to the benefits received by the smallholder. Aggressive management of agricultural portfolio risk by a bank can make agricultural lending safer, allowing the bank to offer credit to more smallholders at lower interest rates. However, the benefits to smallholders are not readily obvious or immediate, exposing the bank to shortsighted political criticisms that its practices do not help the smallholder. There are, however, other ways to integrate meso index insurance into agricultural lending. One way that is currently being tested throughout the developing world is to use index insurance to fashion “contingent credit” contracts (Farrin and Miranda, 2015). Under a contingent credit contract, the borrower is not obligated to repay their loan in the event of, say, a drought. In order to compensate, the bank purchases an index insurance contract that pays the bank an indemnity equal to the loan balance in the event of a drought, which it then uses to cover the smallholder’s debt. With contingent credit, the smallholder borrower benefits in a direct and transparent way by not having to repay their loan in the event of a drought or other adverse weather event. The bank also benefits by completely eliminating the possibility of widespread defaults in the event of a drought or other adverse weather event, since all outstanding smallholder loans are automatically repaid by the insurer. However, meso index insurance is not a panacea for development finance banks seeking to expand credit services to agricultural producers in general, and smallholders in particular. Index insurance has its limitations. Index insurance, if not properly designed, can fail to 5


closely track the lender’s agricultural credit portfolio cashflows. It can also be expensive, typically demanding premiums that well exceed expected indemnities if offered on a commercially viable basis. The optimal index insurance design and the best strategy for incorporating it into bank lending practices will vary by country, region, agricultural practices, regulatory constraints, and established lender practices. Thus, introduction of index insurance to support smallholder credit requires a careful assessment of local conditions, informed by local experience with agricultural credit and insurance. Index Insurance in Latin America Many valuable lessons have been learned through the numerous pilot programs and academic studies of index insurance throughout the developing world. The number of pilot programs and studies that have been implemented in the developing world is too large to permit discussion of all of them. We have, however, selected three index insurance projects undertaken in Latin America in recent years for more detailed discussion. Each of these projects evolved past the stage of conceptualization, implying that a contract was designed and rated, a marketing framework was developed, and the insurance product was “marketed”, leading to some uptake of the product, however modest. The projects also generated important lessons, both positive and negative, regarding proper index insurance contract design, marketing, financing, regulation, and education. Peru The risk of severe El Niño events, which can cause torrential rains and catastrophic flooding, significantly constrains access to agricultural credit in northwest Peru. In an attempt to improve credit availability in rural areas, USAID initiated a project in 2004 to develop an index insurance contract to insure agricultural credit portfolios based on the El Niño-Southern Oscillation (ENSO) index (GlobalAgRisk, Inc., 2006, 2010; Skees and Murphy, 2009). The ENSO index measures sea surface temperatures off the coast of Peru, where higher temperatures are associated with severe El Niño events and subsequent flooding. Khalil et al., 2007, designed an ENSO index insurance product for purchase by banks in the Piura region of Peru. The insurance product was approved by the Peruvian banking and insurance regulator, but, in 2006, due to a government subsidization of traditional agricultural insurance, the index insurance project went on hiatus. The product, however, was subsequently refined and its sale resumed. For a time, area-yield insurance also was offered by the government to rural banks in Peru’s eight poorest regions (Carter, Boucher, and Trivelli, 2007; Lybbert et al., 2010). The goal was to protect subsistence farmers with fewer than 3 hectares of land against excessive crop loss. The area-yield insurance indemnifies farmers with payments of 400 to 750 soles per hectare when yields fall below 40% of the historical average. Sales of the insurance product reached $17 million in liability in 2009-2010 and $19 million in 2010-2011. However, the premium paid by farmers was roughly only 14% of the value insured, with the remainder paid by regional government or the national agricultural bank. However, both index insurance programs proved unsustainable and were abandoned. At present, the only agricultural insurance available in Peru is a highly subsidized MPCI insurance offered by Agrobanco that is purchased by no more than 25% of borrowers. Central America In 2004, the Inter-American Development Bank (IADB) and the Central American Bank for Economic Integration (CABEI) financed a $3.5 million project to strengthen public and private sector capacities to manage agricultural financial risk in Guatemala, Nicaragua, and Honduras. The project was implemented in collaboration with the Latin American Federation of Insurers (FIDES), with technical assistance from the World Bank and the International Research Institute for Climate and Society (IRI) of Columbia University. IRI developed and actuarially rated rainfall insurance contracts based on remote sensing satellite technology for rice, soybeans, and sorghum in Nicaragua and for sorghum, soybeans, and maize in Guatemala. The project also aimed to transfer capacity in agriculture index insurance product 6


design and development to the Tropical Agricultural Research and Higher Education Center (CATIE), a highly-regarded Nicaraguan academic research and teaching institution. The pilot study found that there is an extremely strong link between rainfall index insurance contract payouts and El NiĂąo cycles in Central America. As a result, most of the contracts designed by IRI tended to provide pay outs mostly, if not exclusively, during El NiĂąo years. The pilot program also uncovered significant climatic trends that in the long run are sure to impact agriculture in Central America, most notably increased precipitation along the Caribbean coast and decreased precipitation along the Pacific coast. As such, index insurance contract structures and pricing would need to be regularly revised in response to climate change. Nicaragua Nicaragua represents one of the earliest efforts to implement index insurance in Latin America. In 1998, the World Bank explored the feasibility of introducing weather index insurance to Nicaragua and recommended the establishment of a rainfall index insurance pilot program for major cereal producers in Northwest Nicaragua. Plans to initiate the pilot program were underway when Hurricane Mitch devastated the country in October of 1998. After this event, attention shifted to the development of an index insurance product that would provide disaster financing to the government of Nicaragua during severe events. An index insurance contract was designed and priced on the global reinsurance market. However, in the end, the Government of Nicaragua dropped plans to purchase catastrophic weather index insurance on the grounds they could reliably depend on the global community for assistance when major catastrophes occurred. Work on index insurance in Nicaragua resumed in 2004, at which time the World Bank entered into a collaboration with the Nicaraguan Institute of Insurance and Reinsurance (INISER), the publicly owned national insurer, to developing index insurance market for agriculture. In 2005, the World Bank and INISER, with complementary efforts by the IADB, launched a pilot weather index insurance program aimed at strengthening credit for groundnut producers in western Nicaragua, with the expressed objective of testing whether weather index insurance could lead to a reduction interest rates charged by lenders to farmers. The operational phase of the project began in 2007 when INISER began selling weather index insurance designed to protect medium- and large-scale groundnut and rice farmers against drought during the growing periods and excess moisture during the sowing and harvest periods. The leadership provided by INISER in Nicaragua served as an effective catalyst to weather index insurance market development in various ways, not least of which is by helping to establish essential institutional working partnerships among local banks, private insurers, agricultural universities, reinsurers, government agricultural and weather agencies, and government regulators. Other Index Insurance Initiatives in Latin America There are various other examples of agricultural index insurance pilot programs in Latin America (Carter, de Janvry, Sadoulet, and Sarris, 2014; Fuchs and Wolff, 2010; Hellmuth et al., 2009; Vargas-Hill and Torero, 2009; Burke, de Janvry and Quintero, 2010). For example, in 2001, AgroBrasil introduced an area-yield insurance product to participants in a government seed program, which, at its height, reached 15,000 farmers; the product, however, was largely financed by the federal government, which paid over 90% of the premiums. In 2007, the governments of 16 Caribbean countries established the Caribbean Catastrophe Risk Insurance Facility, which provided insurance indexed to hurricanes and earthquakes. In 2005, the World Bank established a contingency line of credit for the Government of Colombia to access funding in the event of earthquakes. And in 2003, Agroasemex, the Mexican state reinsurance company, introduced free drought insurance to local communities, benefiting 800,000 poor rural dwellers. Market Development In order to effect lasting changes in the agricultural credit system so as to promote smallholder financial inclusion, Development Finance Banks must commit to developing new lending 7


technologies in collaboration with smallholders, insurers, financial regulators, and government policy makers. This can best be carried out with support from an experienced institution, such as the Food and Agricultural Organization, which can provide the technical assistance needed to design the new insurance and financial products and help forge the institutional collaboration required for market development. Market development should begin with a pilot program involving a well-defined and representative “test market” of underserved smallholders who are representative of the population the bank ultimately wishes to reach. In order to keep the pilot program manageable and control costs, the test market should exhibit some uniformity with regard to location and production and marketing practices. For example, the test market might consist of underserved smallholders residing in a few selected provinces who grow a common dominant crop. In order to implement the pilot program, the bank must then commit to experimenting with new lending practices with this test market for an extended period, say, three years. A reasonable size test market might include on the order of 5,000 farmers, though this is only a suggestion. Implementation of the pilot program will require cooperation from a variety of stakeholders. Farmer based organizations that represent the interests of marginal smallholders in the test market must be involved in order to ensure that smallholders will embrace the new technologies once developed. Government agencies, most notably the agricultural ministry and meteorological agencies, must also be approached to obtain the agronomic and weather data needed to perform a risk assessment and design effective index insurance products. Financial and insurance regulators must be informed to ensure that the new insurance products and their incorporation into credit policies observe established banking and insurance regulations. And government policymakers must be included in the dialog, in order to ensure pilot project objectives are consistent with government agricultural sector development policies, and perhaps to enlist the support of the government in the form of a governmentbacked reinsurance insurance. The most important partnership to be forged by the bank, however, is with an insurer, who will ultimately rate, market, and underwrite the index insurance products and assume the underlying risks. The bank and the insurer must work closely to design an index insurance contract that provides the greatest possible protection against high aggregate rates of default due to drought or other systemic events, relative to the premiums charged. Ideally, the insurer participating in the pilot program should possess established marketing channels to the target population in the target area, even it is currently limited to the sale of health, life, named peril or other conventional form of insurance. The insurer should also have an established relationship with a reinsurer, either local or international, who would need to be consulted to address issues pertaining to reinsurance coverage and pricing. Below, we identify major steps that must be taken to develop such a framework though a carefully designed pilot program. Risk Assessment A proper risk assessment begins with gaining a clear understanding of the bank’s institutional mission and operational objectives, which, we assume includes a desire to expand lending to currently underserved smallholders. In performing a risk assessment, we need to understand the bank’s mix of agricultural loans and the key characteristics of their agricultural borrowers. We also need to assess the bank’s current risk management practices, including those that might employ insurance, reinsurance, or insurance-like arrangements with larger banks or the government. The underserved smallholders to which credit will be introduced or otherwise expanded must then be identified and their commercial characteristics and risk exposures must be assessed. One needs to understand where the smallholders reside, what crops they grow, their dominant production and marketing practices, and their experience with micro-financial credit technologies. One must then identify the major systemic risks facing the smallholders, such as drought, excess rain, floods, hot waves, frost, windstorms, pestilence, crop diseases, and 8


price fluctuations. Essential data would have to be compiled from a variety of sources, including the bank, the agricultural ministry, and the meteorological service, among others. Armed with proper weather, crop production, commodity price and bank financial data, experienced financial and risk management consultants enlisted by FAO can apply well-tested actuarial and statistical methods to assess the risk that would be borne by the bank wishing to expand its credit portfolio to include previously unserved smallholders. Product Development Having identified the target smallholder population and the systemic risks endemic to lending to them, the next step is to design and rate an appropriate index insurance contract. The contract must be designed and integrated into bank lending practices so as to minimize the bank’s portfolio risk at the lowest possible cost. In designing an index insurance contract, various decisions must be made. First and foremost is the selection of an index. For example, an appropriate index might be a weather variable such as rainfall, temperature, ENSO, or satellite-based vegetation index. However, a nonweather variable, such as area-yields or price-adjusted area-revenues might be feasible and more appropriate. A time frame for the measurement of the index must also be specified, including start and end times for coverage and appropriate closing date for sales. Whatever index and time frame is selected, the index must be objectively and reliably observable in a timely way by the bank, the smallholder, and the insurer in order to allow undisputed settlement of indemnity payments. Next, the indemnity schedule, which specifies how much the insurer will pay the bank as a function of the value of the index, must be fashioned so as to provide the greatest possible risk protection, while remaining simple and transparent and commanding an affordable premium rate. The principal challenge in designing the index insurance contract indemnity schedule is to minimize basis risk. In order to achieve this goal, the terms of the contract should be sufficiently flexible to allow for geographical variation in climatic patterns and production practices among the smallholder target population. As a practical matter, geographical regions, across which terms will be allowed to vary, but within which terms will be uniform, must be identified. The boundaries of these regions might be based on established political administrative units, such as provinces, counties, and communities; they could be based on proximity to meteorological stations; or they could be based on the geographic grids on which satellite data are available. A higher geographical resolution implies more subdivisions among which contract terms may vary, allowing contract terms to be better tailored to the risks faced by smallholders and the bank. However, more subdivisions also raises product development and administrative costs. Thus, a balance must be struck. It is during the product development phase that the product must be actuarially rated to determine an appropriate premium to charge for the product. This begins with the computation of the expected indemnity, also known as the “fair premium”, a task that can be performed by an experienced actuary provided with adequate data. Next, the fair premium must be “loaded” by adding the administrative costs borne by the insurer and a reasonable rate of return on capital. Thus, selection of an index, the design of the indemnity schedule, and the rating of the insurance contract depend on the quantity, quality, and resolution of meteorological, price, and production data available from the agricultural ministry, meteorological service, and other sources. Accurate pricing and efficient design of weather index insurance products require long, clean, internally consistent historical data records. The rule of thumb most often cited for adequacy of rainfall data is that at least 30 years of daily, weekly or monthly data with less than 3% missing observations should be available. Given sufficient data, experienced actuaries and risk management professionals can apply well-tested actuarial and statistical methods to design a viable insurance product. Another essential task in product development is securing approval from government and its regulatory agencies. Index insurance is difficult to classify as a financial product, as it 9


possesses qualities of a financial derivative (such as an option, futures, and swap) and qualities of conventional insurance, without strictly satisfying all the conditions that ideally define either type of product. In many countries there is no clear precedent for classifying index insurance contracts within existing laws or regulatory framework. Multiple regulatory agencies therefore often need to cooperate to design appropriate oversight provisions for index insurance products. Education, Training and Evaluation Education, training, and evaluation become important elements of the pilot program. To this end, a qualified set of consultants should be retained to develop educational and training program, including the development of proper training materials. Smallholders, bankers, and insurers must all be properly informed of how index insurance works and how it should be integrated into farm and bank risk management practices. For example, if the index insurance contract is to be combined with the credit contract to create a contingent credit loan, the smallholder must be made to understand that while the loan need not be repaid on occurrence of the indexed event, the loans must be repaid otherwise, even the smallholder perceives he/she has suffered losses for any cause other than the contingency stipulated in the credit contract. Loan officers and bank managers must also be educated regarding the proper uses of index insurance. Managers, especially, must learn how to employ holistic portfolio risk management strategies, which requires a deeper understanding of bank cash-flows. Although lenders arguably are more sophisticated than farmers and thus better able to implement complex risk management practices, it is also true that many rural lenders in developing countries lack a culture of active risk management practices that employ insurance, reinsurance, and derivative products. Operational cash-flow models and risk management practices can be intricate and opaque, and can vary from one lender to the next. Efforts to develop lender portfolio risk management strategies that incorporate index insurance can encounter difficulties if lenders are reluctant to openly discuss their trade and internal cash-flow management practices with index insurance specialists. Transfer of technical knowledge to insurers pertaining to the design of weather index insurance products is also essential. Virtually all insurers employ actuaries with sound analytical skills. However, most of these skills have evolved from their application to conventional insurance, and are based largely on experience and loss rating methods that assume independence among losses of the insured. The design and rating of weather index insurance products, however, present unique problems and require certain special skills that are not part of traditional actuarial training. To properly design index insurance contracts, it is important to understand the basic agronomic relationships that exist between weather indices and agricultural production. The design of such contracts, moreover, must rely on basic weather and production data, rather than the experiential loss data most commonly the object of analysis in conventional actuarial analysis. Furthermore, correlated risk and basis risk, which are relatively minor concerns with conventional forms of insurance, become major issues in designing weather index insurance contracts. Finally, in order to learn proper lessons from a pilot program, the programs must be monitored and evaluated, to include formal impact assessments of smallholders, bankers, insurers, and other relevant players in the credit value chain. To the extent possible, a benefits and cost analysis should be performed that assesses, not only the direct benefits to banks and smallholders, but to the agricultural value chain and rural community in general. Feasibility Study FAO and ALIDE propose to conduct a series of feasibility studies to assess the potential benefits and costs to ALIDE member banks of incorporating index insurance into their lending practices. The feasibility studies will be conducted in collaboration with four ALIDE member banks committed to expanding credit to previously underserved smallholders.

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The feasibility studies will be carried out by Emilio Hernandez of FAO and Romy Calderón from ALIDE supported by selected local consultants, in collaboration with Mario Miranda, an international consultant with extensive experience in index insurance product and market development in developing countries. For each of the four participating ALIDE banks, a local consultant lead by Hernandez and Calderón will undertake an in-country field mission to perform interviews with stakeholders and to secure essential data needed to generate concrete recommendations for the implementation of a pilot program. Local consultants selected to work on the feasibility study will be required to have significant experience with the financial and insurance sectors in their countries, possess a graduate degree in economics or business, and be able to write in both English and Spanish; they will be guided by several publications that provide guidelines for index insurance pilot program development including World Bank Agriculture and Rural Development Department, 2011; United Nations, 2007; Hellmuth et al., 2009; and GlobalAgRisk, 2009. Prior to the start of the consulting team’s in-country assessment, the local collaborating bank should identify the population of underserved smallholders to whom they wish expand credit services in the future. Ideally, the bank should also identify a well-defined and representative subset of these smallholders to serve as a “test market” for the future conduct of a wellplanned pilot program. The bank should also propose an insurer to underwrite the index insurance product, ideally one that has a history of business dealings with the bank. During its field mission, the consulting team must gain a clear understanding of the bank’s institutional mission and operational objectives and must also obtain critical data from insurers, smallholders, and government agencies to perform its risk assessment and formulate sound recommendations for a future pilot program. More specifically, during its field missions, the consulting team will need to consult with: • • • • •

Bank – agricultural lending decision makers and chief risk manager, if one exists. Insurer – chief market development officers and chief actuary Farmer Organization – respected representatives of smallholder interests Agricultural Ministry – finance and risk management specialist, data specialists Meteorological Service – catastrophic risk specialist, weather data specialists

Below, we provide a list of key questions the mission teams must address and data it should obtain in order to allow completion of the feasibility study. In many cases, the same questions will put to more than one stakeholder to check for inconsistency in perceptions among the groups. Bank 1. What are the bank’s institutional vision and mission, particularly as they pertain to the provision of credit to agricultural sector generally, and smallholder farmers in particular? 2. What is the nature of the bank’s current credit portfolio; that is, what clients does it currently serve? In particular, what is the bank’s mix of nonagricultural and agricultural loans in their credit portfolios? 3. What is the nature of the bank’s current agricultural credit portfolio; that is, what clients in the agricultural value chain does it currently serve and what are their key characteristics. In particular, what is the bank’s mix of loans to commercial agriculture (input providers, processors, exporters, large-scale farmers and outgrower enterprises) versus less commercially established smallholder farmers. 4. What is the nature of the bank’s current smallholder credit portfolio; that is, what are the defining characteristics of the bank’s smallholder clients, if any. Where do the smallholders reside, what crops do they grow, what are their dominant production practices, and what is the state of their financial literacy? Also, what are their primary

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marketing strategies; do they sell on the open market or participate in outgrower or other marketing contract arrangements? 5. How does the bank’s credit policies toward smallholders differ from those applied to the bank’s best commercial agricultural borrowers? Are the interest rates appreciably higher for smallholders? Do collateral requirements differ? What are the characteristics of the lending model(s) used by the bank to reaching smallholder households (e.g. does the bank employ joint-liability group lending, use mobile banking, or partner with value chain agents in order to reach smallholders? 6. Can the bank provide several years of hard data on the total loan volume and rates of loan default and delinquency for non-agricultural commercial loans, agricultural commercial loans, and smallholder loans? Do repayment rates decline in response to droughts or sudden decline in output prices. 7. How does the bank deal with cash-flow problems or otherwise manage portfolio risk? Does it employ risk management strategies such as insurance, reinsurance, or derivative hedging with futures and options? Does the bank carry a line of credit with larger bank or the government that it can use to address cash shortfalls? 8. What are the major impediments that currently limit the volume of loans the bank offers to smallholders, particularly the smallholders that comprise test market? What roles to transactions costs and risk play in the decision to limit lending to this group? To what extent is drought or other systemic shock a concern in lending to this group of smallholders? 9. What standing or ad-hoc government policies and programs affect the bank’s decision to lend to smallholder farmers? Does the government offer credit guarantees to banks to support smallholder credit or subsidize smallholder credit in any way? Has the government ever mandated that the bank forgive smallholder loans in response to a major drought or other natural catastrophe? Insurer 1. What are the insurer’s primary product lines? Does it offer primarily business insurance, or does it carry more conventional lines such as life, health, home, and vehicle insurance? What portion of the insurer’s book of business is in the agricultural sector? What is the total liability of agriculture-related insurance contracts written by the insurer and what is the volume of premiums collected annually? 2. What business clients in the agricultural sector does the insurer currently serve? Does the insurer offer business insurance exclusively to large commercial agricultural enterprises (large farmers, processors, exporters, etc.), or does it also offer business insurance to small farmers and smallholders? Is the insurer’s commercial agricultural book of business concentrated in any one particular geographical area or limited to one or two major commodity value chains? Does the insurer maintain a network of field offices in rural areas to serve rural dwellers? 3. What types of insurance does the insurer currently offer to agricultural business clients? Is the insurance mostly for protection against losses of business assets such as structures and capital equipment, or does the insurer also offer crop insurance that covers loses in production from weather or other natural perils? 4. Does the insurer have experience in writing any form of index insurance? If so, what type of index insurance was offered and to whom? Was the experience positive or negative? What are the reinsurance arrangements?

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5. Can the insurer provide several years of hard data on its volume of business, including liability, premiums, and indemnities for its agricultural insurance lines? 6. Does the government provide premium subsidies for any form of agricultural insurance sold by the insurer and, if so, what percentage of the premium is subsidized? Does the government run a potentially competing agricultural insurance program? What role do the private insurers play in this program, if any? Do they serve as marketing agents for the government insurance? Do they retain any portion of the risk? 7. Prior to the arrival of the consulting team, the bank will be asked to identify a representative sub-group of smallholders that might serve as a “test market� for the future conduct of a pilot program. What major impediments does the insurer perceive in marketing insurance to this population? That is, what factors are likely to increase costs of offering such insurance? What regulatory constraints must the insurer observe if it is to develop a new line of index insurance products aimed at agricultural lenders? Is the regulatory authority to offer such products already in place? 8. Does the insurer have experience with credit insurance, that is, insurance offered to a bank or other lending institution to cover losses from loan defaults? Do credit insurance indemnities paid to banks increase when there is a drought or sudden decline in agricultural prices? 9. Does the insurer employ actuaries that are experienced with the design and rating of index insurance products? More generally, does it employ experts in agricultural sector and catastrophic risk? Smallholders 1. Prior to the arrival of the consulting team, a group of smallholders should have been identified to serve as the test market for any future pilot project. What do these smallholders produce and what production practices do they employ: rain-fed versus irrigated cultivation, traditional or hybrid seeds, monoculture or multiculture, integrated livestock operations? 2. Where do the smallholders reside? On average, how big are their farms and how many household members contribute to agricultural production activities? What proportion of food produced on the farm destined for auto-consumption, and how much is destined for market sale or delivery to processors? 3. How do the smallholders market their output: open market or marketing agreements with processor, outgrower, or other aggregator? If they employ marketing agreements, do aggregators provide seeds or fertilizer at planting in return for guaranteeing a prescribed price at harvest? 4. What do the smallholder representatives perceive as the major reasons banks will not lend to them? To what ends would smallholders use loans if they received them? Would they use loans to purchase better seeds, fertilizer inputs, or capital equipment in their operations, or would they use them for other purposes? 5. What are the major risks faced by the smallholder: drought, excess rain, untimely rains, frost, heat waves, windstorm? What was the cause of the most profound production shortfall experienced by the smallholders over the past twenty years? 6. Do the smallholders currently employ any form of crop insurance? If so, what perils are covered by the insurance and who sells it to them? Have the smallholders heard of drought insurance or other form of index insurance? Do the smallholders currently purchase other forms insurance (e.g., life, health, burial, business insurance, etc.)? If so, who sells it to them and for what purposes? 13


Agricultural Ministry 1. What do the test-market smallholders produce and what production practices do they employ; on average, how big are their farms and how many household members contribute to agricultural production activities; how do they market their output? 2. What are the major risks faced by the smallholder: drought, excess rain, untimely rains, frost, heat waves, and windstorm? What was the cause of the most profound production shortfall experienced by the smallholders over the past twenty years? 3. Does the government offer any form of insurance to smallholders? If so, what perils are covered by the insurance and who sells it to them? What percentage of the premium, if any, is subsidized by the government? 4. What government risk management and catastrophe response programs currently benefit smallholders? Do smallholders enjoy any form of government price guarantees? Do they have access to extension services? Do they usually receive or otherwise expect to receive government disaster assistance in the event of a major natural catastrophe? 5. Can the agricultural ministry provide 20 to 30 years of yield and harvest price data for the main crops grown by the target smallholders in digital form? The yield data should be geographically disaggregated to the greatest extent possible; national average yields are not useful. 6. Does the agricultural ministry maintain a reliable agronomic simulation model that accurately predicts the impact of rainfall on yields of the main crops grown by the target smallholders? Meteorological Service 1. What are the major weather risks faced by agricultural producers and how do they vary geographically? How prevalent are drought, excess rains, untimely rains, frost, heat waves, and windstorm? What single weather event most adversely affected agricultural output over the past twenty years? 2. Are weather patterns in the country subject to well-known climatic cycles, such as the El Niùo phenomenon? Are there any discernible trends in weather patterns arising from global climate change? 3. Where are the country’s World Meteorological Organization compliant weather stations located? Can the meteorological service provide us with 20 to 30 years of rainfall and related weather data from these stations in digital form? Ideally, the weather data should be temporally disaggregated to monthly, decadal (10 day), weekly observations; annual or quarterly weather data is not useful for index insurance contract design. 4. Does the meteorological agency maintain synthetic weather sets constructed from remotely sensed (i.e., satellite) data? At what geographical and temporal resolution are these data available? Can the meteorological service provide us with 20 to 30 years of this data? Other Potential Consultations New insurance contracts and significant changes in bank credit policies are often subject to oversight from, and may require formal approval from, government insurance, banking, and securities regulators. Index insurance is difficult to classify as a financial product, as it possesses qualities of a financial derivative and qualities of conventional insurance, without strictly satisfying all the conditions that ideally define either type of product. In many countries 14


there is no clear precedent for classifying index insurance contracts within existing laws or regulatory framework. For this reason, the consulting team may wish to consider meeting with appropriate government regulatory agencies if they foresee potential major impediments to the adoption of the new products and the implementation of a future pilot program. Summary and Conclusions If development finance banks are to increase agricultural lending in general, and lending to smallholders in particular, they will have to experiment with innovative lending technologies. Adopting a holistic approach to risk management employing meso index insurance, rather than relying on risk avoidance, offers a way forward and can prove especially effective if combined with other lending technologies such as group credit and mobile banking. In conducting its proposed research, the FAO consulting team will strive to develop recommendations for the adoption of index insurance by development finance banks so to allow expansion of their smallholder loan portfolios. FAO’s efforts, in collaboration with ALIDE banks, has the potential to revolutionize agricultural credit and risk management practices in Latin America, with wide-ranging positive social impacts, including: i) increased smallholder access to agricultural production loans at reduced rates; ii) increased smallholder adoption of improved production technologies; iii) increased smallholder income, consumption, and savings and reduction in livelihood risk; iv) reduced aggregate rates of default on agricultural loans; and v) increased profitability and reduced risk for banks lending to smallholder agriculture. References Bryla, E. and J. Syroka. 2007. Developing Index-Based Insurance for Agriculture in Developing Countries. Innovation Brief, United Nations, Department of Economic and Social Affairs, New York. Carter, M.R., S.R. Boucher, and C. Trivelli. 2007. Area-Based Yield Insurance Pilot Project For Peruvian Coastal Agriculture. Concept note, BASIS Research Program, University of Wisconsin-Madison, Madison, WI. Carter, Michael. 2011. Innovations for Managing Basis Risk under Index Insurance for Small Farm Agriculture. Policy Brief Number 41, Fondation pour Les Etudes et Recherches Sur le Developpement International. Jensen, Nathaniel D., Andrew G. Mude and Christopher B. Barrett. 2014. How Basis Risk and Spatiotemporal Adverse Selection Influence Demand for Index Insurance: Evidence from Northern Kenya. Working Paper, Cornell University, Ithaca, New York. Carter, Michael, Alain de Janvry, Elisabeth Sadoulet, and Alexander Sarris. 2014. IndexBased Weather Insurance for Developing Countries: A Review of Evidence and a Set of Propositions for Up-Scaling. Background document for the workshop “Microfinance Products for Weather Risk Management in Developing Countries”, Paris, June 25, 2014. Clarke, D. and S. Dercon. 2009. Insurance, Credit and Safety Nets for the Poor in a World of Risk. DESA Working Paper 81, University of Oxford, Department of Economics, Oxford, UK. Doherty, N.A. and A. Richter. 2002. Moral Hazard, Basis Risk, and Gap Insurance. Journal of Risk and Insurance 69(1):9–24. Farrin, Katie and Mario J. Miranda. 2015. A Heterogeneous Agent Model of Credit-Linked Index Insurance and Farm Technology Adoption. Forthcoming, Journal of Development Economics. Fuchs, Alan and Hendrik Wolff.

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Fuchs, Alan and Lourdes Rodriguéz-Chamussy. 2011. Voters Response to Natural Disasters Aid: Quasi-Experimental Evidence from Drought Relief Payment in Mexico. University of California at Berkeley. Glauber, Joseph. 2004. Crop Insurance Reconsidered. American Journal of Agricultural Economics 86(5): 1179-95. GlobalAgRisk, Inc. 2010. GlobalAgRisk Projects in Vietnam, Peru, and Mongolia: Four Case Studies. Technical report, GlobalAgRisk, Inc., Lexington, KY. GlobalAgRisk, Inc. 2009. Designing Agricultural Index Insurance in Developing Countries: A GlobalAgRisk Market Development Model Handbook for Policy and Decision Makers. Technical report, GlobalAgRisk, Inc., Lexington, KY. GlobalAgRisk, Inc. 2006. Hedging Weather Risk for Microfinance Institutions in Peru: Comprehensive Report. Report to the United States Agency for International Development, GlobalAgRisk, Inc., Lexington, KY. Guizar-Mateos, Isai, Mario J. Miranda, and Claudio Gonzalez-Vega. 2014. The Role of Credit and Savings in the Dynamics of Technology Decisions and Poverty Traps. Working Paper, Department of Agricultural, Environmental & Development Economics, The Ohio State University. Halcrow, H.G. 1949. Actuarial Structures for Crop Insurance. Journal of Farm Economics 31(3):418 – 443. Hazell, Peter. 1992. The Appropriate Role of Agricultural Insurance in Developing Countries. Journal of International Development 4(6):567 – 581. Hellmuth M.E., Osgood D.E., Hess U., Moorhead A. and Bhojwani H. (eds). 2009. Index Insurance and Climate Risk: Prospects for Development and Disaster Management. Climate and Society No. 2. International Research Institute for Climate and Society (IRI), Columbia University, New York, USA. Khalil, Abedalrazq F., Hyun-Han Kwon, Upmanu Lall, Mario J. Miranda, and Jerry R. Skees. 2007. El Niño-Southern Oscillation-Based Index Insurance for Floods: Statistical Risk Analyses and Application to Peru. Water Resources Research 43(10):W10416. Lybbert, T. J, F. B Galarza, J. McPeak, C. B Barrett, S. R Boucher, M. R Carter, S. Chantarat, A. Fadlaoui, and A. Mude. 2010. Dynamic Field Experiments in Development Economics: Risk Valuation in Morocco, Kenya and Peru. Agricultural and Resource Economics Review 39(2):176–192. Mahul, O., and C.J. Stutley. 2010. Government Support to Agricultural Insurance: Challenges and Options for Developing Countries. Technical Report, World Bank, Private Sector Development Vice Presidency, Global Capital Markets Development Department, Washington, DC. Miranda, Mario J. 1991. Area-Yield Crop Insurance Reconsidered. Agricultural Economics 73(2):233–242.

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Miranda, Mario J. and Claudio Gonzalez-Vega. 2011. Systemic Risk, Index Insurance, and Optimal Management of Agricultural Loan Portfolios in Developing Countries. American Journal of Agricultural Economics 93(2):399–406. Miranda, Mario J. and Dmitry V. Vedenov. 2001. Innovations in Agricultural and Natural Disaster Insurance. American Journal of Agricultural Economics 83(3):650–655. Miranda, Mario J. and Katie Farrin. 2012. Index Insurance for Developing Countries. Applied Economic Perspectives and Policy 34(3):391-427. 16


Skees, J.R. and A.G. Murphy. 2009. ENSO Business Interruption Index Insurance for Catastrophic Flooding in Piura, Peru. Technical report, GlobalAgRisk, Inc., Lexington, KY. United Nations. 2007. Developing Index-Based Insurance for Agriculture in Developing Countries. Sustainable Development Innovation Brief, Issue 2, March 2007. World Bank Agriculture and Rural Development Department. 2011. Weather Index Insurance for Agriculture: Guidance for Development Practitioners. Discussion Paper 50.

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