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The use of weather derivatives is impaired with a basis risk which diminishes the hedging effectiveness and hinders the distribution of these risk management instruments in the agricultural sector. A frequently suggested approach to reduce the basis risk is the use of mixed indices composed of several weather variables. The purpose of this paper is to compare the hedging effectiveness of a simple temperature‐based and a simple precipitation‐based weather derivative with that of a derivative based on a mixed index of two weather variables.

The basis of this comparison are empirical yield time series of the winter wheat production of 32 farms located in central Germany, as well as daily temperature and precipitation data collected by selected weather stations over several years. Insurance is structured as an option on an accumulated weather index and priced by index‐value simulation. In addition, the bootstrapping method is used to improve statistical reliability. The hedging effectiveness is measured non‐parametrically regarding the relative reduction of the standard deviation of winter wheat revenues caused by using weather derivatives.

The results reveal that mixed index‐based weather derivatives have a significantly higher potential to reduce the risk of winter wheat revenues than simple index‐based weather derivatives. However, using mixed index‐based weather derivatives does not lead to a significantly higher hedging effectiveness than the simultaneous use of several simple index‐based weather derivatives. Moreover, simple index‐based weather derivatives may more easily raise the interest of other industries which could serve as potential trading partners for the agricultural sector.

The authors analyzed the hedging effectiveness of weather derivatives based on simple and mixed indices with regard to the production of winter wheat in Central Germany. To confirm that the present results are generalizable, further research is required for other types of production apart from winter wheat cultivation and with respect to other regions besides Germany.

The focus and results of the present study are very relevant for farmers as well as for potential providers of weather derivatives. The results reconfirm that weather derivative providers should better offer different weather derivatives based on a simple index than complex derivatives that are based on a mixed index.

To the best of the authors' knowledge, this paper is the first that provides a comparative impact analysis of simple and mixed index‐based weather derivatives conducted for real individual farms with regard to their hedging effectiveness.

Maize production in China is exposed to pronounced yield risks, in particular weather risk, which is one of the most important and least controllable sources of risk in agriculture. The purpose of this paper is to analyze the extent to which weather index-based insurance can contribute to reducing the revenue risk in maize production caused by yield variations. An average farm producing maize is analyzed for each of eight Chinese provinces, six of which are part of the Northern Plains of China.

Data are based on the Statistical Yearbook of China and the Chinese Meteorological Administration. The used method of insurance pricing is burn analysis. Hedging effectiveness of precipitation index-based insurance is measured by the relative reduction of the standard deviation (SD) and the Value at Risk of maize revenues.

Results reveal that precipitation index-based insurance can cause a reduction of up to 15.2 percent of the SD and 38.7 percent of the Value at Risk with a 90 percent confidence level of maize revenues in the study area. However, there are big differences in the hedging efficiencies of precipitation index-based insurance measured at different weather stations in the various provinces. Therefore, it is recommended for insurance providers to analyze the hedging effectiveness of weather index-based insurance with regard to the geographical location of their reference weather station if they would like to offer weather index-based insurance products.

The absence of individual, long-term yield data in the study area prevents the evaluation of risk on individual farms. Thus, the hedging effectiveness can only be analyzed on an aggregated level of yield data and can rather be modeled for an average farm of a particular province.

To the author's knowledge, this paper is the first that investigates the hedging effectiveness of precipitation index-based insurance designed for reducing revenue risk of maize production in eight Chinese provinces.

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.