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The purpose of this research is to study the weather risk management practices of agriculture producers. In particular, the authors look at the extent to which farmers use weather derivatives to complement insurance. Unlike insurance, weather derivatives mitigate risk associated with low intensity, high probability events and therefore offer the potential of a more complete hedge than insurance alone.

The authors conducted a survey of grain farmers in the province of Saskatchewan, Canada, a typical jurisdiction in which farmers tend to face weather events that are high in frequency but low in severity, to study the usage of weather derivatives compared to insurance and identify the hurdles to their usage.

The authors find that fewer than 10 percent of their respondents use weather derivatives. Consistent with previous literature in other contexts, they identify participation costs, especially lack of awareness, to be the most significant hurdle to their usage.

A limitation of this study is that the data were collected using a survey methodology and are therefore subject to the usual risks of bias associated with that approach. Moreover, because the authors' survey was delivered online, it may have favoured the participation of farmers that were more comfortable with technology and some bias may have also been introduced into the data as a result.

The authors' findings suggest that there is significant potential to improve farmers' ability to hedge weather risk and thereby improve economic outcomes if the major barriers to the usage of weather derivatives can be overcome. The study paves the way for further research to support the development of public policy strategies that could help farmers take advantage of weather derivatives as part of their inventory of risk management tools.

To the authors' knowledge this is the first study that quantifies the usage of weather derivatives by agriculture producers and identifies the hurdles.

The purpose of this paper is to explain the factors affecting farmers’ willingness to purchase weather index insurance for crops in China, in the Province of Hainan, and to also provide additional background information on weather index insurance.

A survey of 134 farmers was undertaken in Hainan, China, regarding their willingness to purchase weather index insurance. A probit regression model was used, and a number of variables were included to explain willingness of farmers to purchase weather index insurance.

In total, 11 of 15 variables in the model are found to be statistically significant in explaining farmers’ willingness to purchase weather index insurance.

First, farmers’ interest in weather index insurance may be limited due to basis risk. Second, some farmers may not sufficiently understand weather index insurance and so may not purchase it, and a considerable portion of farmers may also require a subsidy if they are to purchase weather insurance.

Weather index insurance may provide a lower cost alternative than traditional crop insurance, however, basis risk remains a main challenge.

This is the first study to quantitatively study the factors affecting the willingness of farmers to purchase weather index insurance for agriculture in the province of Hainan, China.

China frequently suffers from weather‐related natural disasters and weather risk is recognized as a source of wide‐spread systemic risk throughout large swaths of China. During these periods farmers' crops are at risk and for a largely poor population few can afford the turmoil to livelihoods that goes along with drought. The purpose of this paper is to investigate the willingness of Shaanxi and Gansu farmers to purchase weather insurance.

This paper is based on surveyed results of 890 farm households in Shaanxi and Gansu provinces. The survey was designed specifically to extract willingness to pay for weather insurance. Factor affecting willingness to pay are explained using linear regression.

The authors find strong evidence that the demand for drought insurance is downward sloping and also believe from the analysis that the demand is fairly elastic. This suggests that price matters and the results suggest that in order for wide spread adoption of weather insurance farmers will require a substantial premium, perhaps in the order of 80 per cent, as is being applied to current crop insurance initiatives. The authors find, as expected, that crop producers would be willing to pay more for insurance than livestock producers, but also find, as one would expect, that the key indicator is risk. Using a Pert distribution, the authors constructed from information gathered from farmers the expected values and standard deviations of gross revenues and yields of the most prominent crop and constructed the coefficient of variation. It was found in both cases that the higher the CV the greater the willingness to pay.

The authors believe that this is the first willingness‐to‐pay study of weather insurance uptake in China. The authors used a unique “experimental” design and investigation technique to determine weather insurance demand.

Since the 1990s, there has been a discussion about the use of weather index‐based insurance, also called weather derivatives, as a new instrument to hedge against volumetric risks in agriculture. It particularly differs from other insurance schemes by pay‐offs being related to objectively measurable weather variables. Due to the absence of individual farm yield time series, the hedging effectiveness of weather index‐based insurance is often estimated on the basis of aggregated farm data. The authors expect that there are differences in the hedging effectiveness of insurance on the aggregated level and on the individual farm‐level. The purpose of this paper is to estimate the magnitude of bias which occurs if the hedging effectiveness of weather index‐based insurance is estimated on aggregated yield data.

The study is based on yield time series from individual farms in central Germany and weather data provided by the German Meteorological Service. Insurance is structured as put‐option on a cumulated precipitation index. The analysis includes the estimation of the hedging effectiveness of insurance on aggregated level and on individual farm‐level. The hedging effectiveness is measured non‐parametrically regarding the relative reduction of the standard deviation and the value at risk of wheat revenues.

Findings indicate that the hedging effectiveness of a weather index‐based insurance estimated on aggregated level is considerably higher than the realizable hedging effectiveness on the individual farm‐level. This refers to: hedging effectiveness estimated on the aggregated level is higher than the mean of realized hedging effectiveness on the individual farm‐level and almost every evaluated individual farm in the analysis realizes a lower hedging effectiveness than estimated on the aggregated level of the study area. Nevertheless, weather index‐based insurance designed on the aggregated level can lead to a notable risk reduction for individual farms.

To the authors’ knowledge, this paper is the first that analyzes the influence of crop yield aggregation with regard to the hedging effectiveness of weather index‐based insurance.

The purpose of this paper is to investigate weather risks facing Chinese farmers, and to determine whether farmers would have a preference for weather insurance over other types of agricultural insurance.

The data are based on 1,564 farm households surveyed in Shaanxi, Henan, and Gansu provinces in Central China between October 2007 and 2008.

Results suggest that the greater risk for farmers is drought followed by excessive rain. Heat is less critical as a risk but more significant than cool weather. Results suggest a strong interest in precipitation insurance with 50 and 44 percent of respondents indicating strong interest in the product. Supplementary results indicate that interest is equal between planting, cultivating, and harvesting. Furthermore, results suggest that farmers are willing to adopt new ideas, and where possible action has already been taken to self‐insure through diversification and other means.

This research is based on primary data gathered in China. However, the authors are limited in the access to Chinese weather station data to illustrate how weather insurance operates. Instead, the authors use weather data from the weather station in Ashland, Kansas which has similarities to the wheat growing regions of China. While the example is for illustrative purposes only, the authors cannot claim that it actually represents premiums that might actually be found in China.

The Chinese Government has within the past year authorized an investigation into agricultural insurance. The burst of research and applications of weather insurance in both developed and developing countries suggest that a wide array of applications could be feasible in China. The results are encouraging because they suggest that farmers in China would have an interest in purchasing weather insurance.

The authors believe that this is the first study conducted on weather insurance in China. The survey instrument is designed to specifically determine what weather risks are important to Chinese farmers and the interest that farmers would have in using such a product.

The purpose of this paper is to investigate the role that weather shocks can play in the livestock mortality microinsurance take-up when the insured risk has a prevalent covariant component.

The sample consists of 360 rural Ethiopian households. Data were collected in a panel-structure at the end of three agricultural seasons (2011-2013). In the questionnaire, a specific section on insurance was meant to collect information on the farmer’s willingness-to-pay (WTP) for a set of insurance products, including livestock mortality insurance. Two OLS regression models and a quantile regression model were employed to estimate the impact of weather anomalies on the WTP for the insurance product.

The authors find that weather anomalies contribute to changes in the WTP to a large extent. Negative (positive) changes in precipitation (temperature) anomalies can lead to more than a 30 percent reduction in the WTP. This general finding is complemented with the analysis of the conditional distribution of the WTP, which shows that other elements can prevail for low values of the conditional distribution. In this case, the WTP seems to be represented more by the interviewee’s age and basic knowledge of insurance, and village fixed-effects. Basic knowledge of insurance, in particular, can increase WTP by about 60 percent.

This paper has straightforward implications from a policy perspective. It suggests that farmers would prefer an insurance premium that follows the changes in the systemic component. On the contrary, insurance as well as reinsurance companies are usually reluctant to frequently revise their premiums. Financial education programs, farmer-driven design, trust building, and bundling insurance with other financial and non-financial products can increase the value proposition perceived by the farmers. From a marketing perspective, the overall findings suggest that continuous fine-tuning of the contract, transparency, and targeted information campaigns can contribute to increase and stabilize potential customers’ WTP.

To the best of the authors’ knowledge, this is the first paper that considers the impact of weather shocks on the WTP for a livestock mortality insurance product. Livestock is one of the most strategic assets of poor rural households in Africa. This study contributes to the theoretical and empirical literature on the determinants of weather insurance take-up in developing countries and, in particular, the role of spatiotemporal adverse selection and basis risk (e.g. Jensen et al., 2016).

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.

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

The purpose of this paper is to empirically investigate the impact of weather index insurance on agricultural technology adoption in rural China.

A field experiment was conducted with 344 rural households/farmers in Heilongjiang and Jiangsu Provinces, China. DID model was used to evaluate farmers’ technology adoption with and without index insurance.

The results show that weather index insurance has a significant effect on the technology adoption of rural households; there is a regional difference in this effect between Heilongjiang and Jiangsu. Weather index insurance promotes technology adoption of rural households in Heilongjiang, while has limited impact on those in Jiangsu. Weather, planting scale and risk preference are also important factors influencing the technology adoption of rural households.

This research is subject to some limitations. First, the experimental parameters are designed according to the actual situation to simulate reality, but the willingness in the experiment does not mean it will be put into action in reality. Second, due to the diversity of China’s climate, geography and economic environment, rural households are heterogeneous in rural China. Whether the conclusion can be generalized beyond the study area is naturally questionable. A study with more diverse samples is needed to gain a fuller understanding of index insurance’s effects on farmers in China.

This research provides a rigorous empirical analysis on the impact of weather index insurance on farmers’ agricultural technology adoption through a carefully designed field experiment.

The paper analyzes the hedging efficiency of weather-indexed insurance for corn production in Northeast of China. The purpose of this paper is to identify the potential weather variables that impact corn yields and to analyze the efficiency of weather-indexed insurance under varying thresholds for payouts (strike values).

Statistical relationships between climate variables and crop yields are used to construct weather-indexed insurance that enable a farmer to hedge against adverse precipitation outcomes. Mean root square loss is used to compare the efficiency of various weather products.

Based on efficiency comparisons, it turns out that in some, but not all circumstances, cumulative rainfall (CR) insurance can be used to hedge weather risk. When CR explains one-third or more of the variation in corn yields, a hedge can offset the revenue loss caused by the corresponding weather risk; but when it explains much less of the yield variation, it is inefficient for hedgers to buy weather insurance. If CR explains variation in crop yields, it is increasingly efficient to employ CR-indexed insurance as strike values decline for put options or increase for call options.

The paper provides a method for calculating the premium for an insurance product that provides a payout if CR in a growing season is too low.

This research is important because it illustrates the potential benefits of using weather insurance as an agricultural risk management strategy in China.