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While the demand for weather‐based agricultural insurance in developed regions is limited, there exists significant potential for the use of weather indexes in developing areas. The purpose of this paper is to address the issue of historical data availability in designing actuarially sound weather‐based instruments.

A Bayesian rainfall model utilizing spatial kriging and Markov chain Monte Carlo techniques is proposed to estimate rainfall histories from observed historical data. An example drought insurance policy is presented where the fair rates are calculated using Monte Carlo methods and a historical analysis is carried out to assess potential policy performance.

The applicability of the estimation method is validated using a rich data set from Iowa. Results from the historical analysis indicate that the systemic nature of weather risk can vary greatly over time, even in the relatively homogenous region of Iowa.

The paper shows that while the kriging method may be more complex than competing models, it also provides a richer set of results. Furthermore, while the application is specific to forage production in Iowa, the rainfall model could be generalized to other regions by incorporating additional climatic factors.

The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer.

Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined.

The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent.

By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

This article aims to examine the state of risk management in agriculture and power sector of India, evaluate the effectiveness of weather derivatives as alternative risk management tools and basic framework required to implement them.

Applications of traditional risk‐hedging tools and techniques in Indian agricultural and power sectors have proved to be costly, inadequate, and more importantly, a drag on the country's fiscal system. Mostly they offer a hedge against only the price risk. The volume related risk, which is rather more serious and highly weather‐dependent, remains practically unhedged. This study has used existing literature and empirical evidences for analyzing the various issues related to risk management in agriculture and power sector. Traditional derivative strategies have been used to construct weather derivatives contracts with different underlying weather indices.

The article suggests that how an appropriate weather‐based derivative contract system may be a more flexible, economical and sustainable way of managing the volume‐related weather risk in an economy, like India, having predominant agricultural and power sectors.

The article will be of value to all those who have some stakes in agricultural and power sectors of an economy and would like to mange the volume related risk in these sectors.

This paper outlines approaches to valuating weather‐linked bonds, mortgages, and operating lines of credit. Using historical data from weather stations in Adrmore, Oklahoma, and Ithaca, New York, indemnities and insurance premiums are computed for specific‐event rainfall insurance. The main contribution of the paper is the development of new and accurate formulae for determining the coupon rates on weather‐linked bonds and the interest rates on weather‐linked mortgages and lines of credit. The empirical aspects of the paper indicate that linking weather risk to debt may be very costly if the risks are common, but the risk premiums on rare or low‐frequency weather risks can be very manageable.

Small-scale farmers in developing countries are undersupplied with capital. Although microfinance institutions (MFIs) have become well established in developing countries, they have not significantly extended their services to farmers. It is generally believed that this is partly due to the riskiness of lending to farmers. The purpose of this paper is to combine original data from a Madagascan MFI with weather data to estimate the effect of rainfall on the repayment performance of loans granted to farmers.

The basis of the empirical analysis is a unique data set of a commercial MFI in Madagascar and weather data provided by the German Meteorological Service. The repayment performance of loans granted to small-scale farmers is estimated using a two-step estimation approach based on linear probability models (LPMs) and a sequential logit model (SLM).

The results reveal that an excessive amount of rain in the harvest period of rice increases the credit risk of loans granted to small-scale farmers in Madagascar. Furthermore, the results confirm that credit features affect the repayment performance of loans.

Since the returns from weather index-based insurance (at least as a future contract) are perfectly correlated with weather events, the authors can set the effect of weather events on the repayment performance of loans equal to the effect of the returns of weather index-based insurance on the repayment performance of loans. Thus, the results imply that weather index-based insurance might have the potential to mitigate a certain part of the risk in agricultural lending.

The focus and results of the present study are very relevant for MFIs, potential providers of weather index-based insurances as well as for farmers. The results confirm that weather events are a primary reason for the risk perception of lenders in developing countries toward small-scale farmers. Future research should, hence, concentrate on the development of index-based insurances in agricultural lending and consider interventions on different levels, e.g., insurance on the farm and the bank level.

To the knowledge, this is the first study that combines original loan repayment data from a Madagascan MFI with weather data in order to estimate the effect of weather events on the repayment performance of loans granted to farmers. Furthermore, to the knowledge, this is the first study that uses a two-step estimation approach based on LPMs and a SLM to investigate the repayment performance in agricultural lending.

The purpose of this paper is to suggest an integrated risk management service for agriculture, by identifying different risk management practices that may be offered in conjunction with crop insurance, to address the various problems and challenges being faced by farmers and by insurance companies.

The research is based on an inductive approach of developing theory from case studies using within‐case and cross‐case analysis. However, apart from exploring different elements from case studies, some of the existing concepts have been reviewed from the literature for their application in agricultural risk management.

An integrated framework for risk management in agriculture has been developed by inductively exploring the various elements that may be successfully interlinked with the crop insurance to tackle the various agricultural risks more efficiently and effectively.

This paper can act as a basis for new product development in agricultural risk management through the use of this integrated approach of risk management and the different elements that have been identified to improve the effectiveness of crop insurance.

This paper fulfils the identified need to develop a framework for an integrated risk management in agriculture.

The purpose of this paper is to check which role-bounded rationality might play as an explanation for farmers’ missing willingness to adopt weather index insurance (WII). WII is an innovative risk management instrument that causes low administration and regulation costs. Moreover, index insurance is plagued neither by moral hazard nor by adverse selection. Nonetheless, WII has been little used to date in agriculture.

An extra-laboratory experiment in the form of a multi-period, single-person business simulation game is conducted with farmers as experimental subjects to investigate the reasons for the low willingness to adopt WII.

First, the demand for WII decreases as the premium loading increases. Second, a transparent communication of the loading reduces demand, indicating that farmers refrain from transactions if they feel that the other party earns (too) much money. Third, communicating to farmers that the index insurance has been subsidized raises demand even though insurance costs in terms of loading are kept constant. This can be taken as an indication that farmers interpret subsidies as a signal for profitable action.

Using an experimental approach and going beyond observational research, this study investigates the prominent question of farmers’ risk management and innovation adoption behavior, and, in particular, the behavioral effect of subsidies. Using a randomized controlled trial, the real behavior of real subjects with real incentives is studied under controlled experimental conditions. Compared to prior studies, the external validity of the experiment is improved by recruiting farmers instead of a convenience group of students.

The purpose of this paper is to examine factors affecting the use of forage index insurance. Forage is a difficult crop to insure, and index insurance may be well suited for forage insurance and has been implemented in several countries, including Canada, the USA and France. Despite being a promising risk management tool, forage index insurance participation rates in Canada, and other countries are low relative to crop insurance participation rates for grain and oilseed producers.

A survey was conducted with 87 beef and cattle producers from Alberta and Saskatchewan, Canada. A probit regression model was used, and a number of variables were included to examine the use of forage index insurance.

In total, 6 of 11 variables in the model are found to be statistically significant in explaining forage producers’ use of forage index insurance. Results suggest that producers who maintain lower feed reserves are more likely to purchase forage index insurance. Also, producers with higher levels of knowledge of crop insurance and a more positive attitude toward forage insurance are more likely to use forage index insurance. Furthermore, producers are more likely to use forage index insurance if they perceive drought and weather risk as being of greater importance, and if they are younger. The importance of the variable forage index insurance premium price was statistically insignificant. This could be due to the effect of subsidization, reducing the importance of price for the decision to purchase. Similarly, the use of other subsidized risk management policies, including a whole-farm margin policy (e.g. the government program and AgriStability), did not reduce forage index insurance use. A possible explanation for this is that the subsidization of the policies may make it profitable to purchase both, despite the overlapping coverage.

These results may be useful for policy makers interested in increasing forage index insurance participation rates, as forage index insurance participation rates have historically been low relative to grain and oilseed producers.

This study is believed to be one of the first studies regarding the use of forage index insurance by forage producers. Producers can be exposed to catastrophic risks such as drought or other extreme weather events, and forage index insurance may be an effective means to manage these risks. Index insurance determines payments using an index that is correlated to producers’ actual yields. A downside of this method is basis risk, which is the mismatch between the insured index and the producer’s actual yield. Research has focused on basis risk and developing improved methods to reduce basis risk. However, less research has investigated the other important factors that may contribute to forage index insurance use. Producers may have a different risk management environment regarding forage production compared to other farm activities, and these differences have largely not been examined.