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Agricultural yield and commodity prices are very sensitive to weather patterns such as drought, excessive rain, or frost. Consequently, unseasonable weather can cause major losses for players in the agricultural value chain, including input providers, farmers, commodity traders, and food processors. In this paper information recorded by PriceWaterhouseCoopers on behalf of the Weather Risk Management Association is complemented by Swiss Re’s market intelligence to examine demand patterns for weather risk transfer solutions. There is a particular focus on the evolution of demand from the energy sector compared to the agricultural sector as a means of identifying the critical success factors needed for a prospering market. Our findings show that recent growth in the weather risk transfer market is mainly related to speculative trading in the energy sector. Stakeholders in the agricultural sector around the world are growing increasingly interested in weather risk transfer products. However, the lack of exchange‐based instruments in this field, the relatively high basis risk between weather indexes and agricultural markets are still highly regulated, and inadequate information and training are all impeding the growth of this business.

Examine the usability of rainfall and temperature outputs of a regional climate model (RCM) and meteorological drought indices to develop a macro-level risk transfer product to compensate the government of Central Java, Indonesia, for drought-related disaster payments to rice farmers.

Based on 0.5° gridded rainfall and temperature data (1960–2015) and projections of the WRF-RCM (2016–2040), the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are calculated for Central Java over different time spans. The drought indices are correlated to annual and seasonal rice production, based on which a weather index insurance structure is developed.

The six-month SPI correlates best with the wet season rice production, which generates most output in Central Java. The SPI time series reveals that drought severity increases in future years (2016–2040) and leads to higher payouts from the weather index structure compared to the historical period (1960–2015).

The developed methodology in using SPI for historical and projected periods allows the development of weather index insurance in other regions which have a clear link between rainfall deficit and agricultural production volatility.

Meteorological drought indices are a viable alternative for weather index insurance, which is usually based on rainfall amounts. RCM outputs provide valuable insights into future climate variability and drought risk and prolong the time series, which should result in more robust weather index insurance products.

The purpose of this paper is to assess the losses of weather‐related insurance at different regional levels. The possibility of spatial diversification of insurance is explored by estimating the joint occurrence on unfavorable weather conditions in different locations, looking particularly at the tail behavior of the loss distribution.

Joint weather‐related losses are estimated using copulas. Copulas avoid the direct estimation of multivariate distributions but allow for much greater flexibility in modeling the dependence structure of weather risks compared with simple correlation coefficients.

Results indicate that indemnity payments based on temperature as well as on cumulative rainfall show strong stochastic dependence even at a large regional scale. Thus the possibility to reduce risk exposure by increasing the trading area of insurance is limited.

The empirical findings are limited by a rather weak database. In that case the estimation of high‐dimensional copulas leads to large estimation errors.

The paper includes implications for the quantification of systemic weather risk which is important for the rate making of crop insurance and reinsurance.

This paper's results highlight how important the choice of the statistical approach is when modeling the dependence structure of weather risks.

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 the present paper is to review studies on weather index-insurance as a tool to manage the climate change impact risk on farmers and to explore the study gaps in the currently existing literature by using a systematic literature review.

This study analyzed and reviewed the 374 articles on weather index insurance (WII) based on a systematic literature search on Web of Science and Scopus databases by using the systematic literature review method.

WII studies shifted their focus on growing and emerging areas of climate change impact risk. The finding shows that the impact of climate change risk significantly influenced the viability of WII in terms of pricing and design of WII. Therefore, the cost of WII premium increases due to the uncertainty of climate change impact that enhances the probability of losses related to insured weather risks. However, WII has emerged as a risk management tool of climate insurance for vulnerable agrarian communities. The efficacy of WII has been significantly influenced by repetitive environmental disasters and climate change phenomena.

This study will be valuable for scholars to recognize the missing and emerging themes in WII.

This study will help the policy planners to understand the influence of climate change impact on WII viability.

This study is the original work of the author. An attempt has been made in the present study to systematically examine the viability of WII for insuring the climate change risk.

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 purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed form reinsurance pricing formulas. A yield restatement approach to account for changing crop mix through time is also demonstrated.

The new crop yield forecasting model is empirically analyzed based on detailed farm-level data from Manitoba, Canada, covering 216 crop varieties from 19,238 farms from 1996 to 2011. As well, corresponding weather data from 30 stations, including daily temperature and precipitation, are considered. Algorithms that combine screening regression, cross-validation and principal component analysis are evaluated for the purpose of achieving efficient dimension reduction and model selection.

The results show that the new yield forecasting model provides significant improvements over the classical regression model, both in terms of in-sample and out-of-sample forecasting abilities.

The empirical analysis is limited to data from the province of Manitoba, Canada, and other regions may show different results.

This research is useful from a risk management perspective for insurers and reinsurers, and the framework may also be used to develop improved weather risk management strategies to help manage adverse weather events.

This is the first paper to integrate a credibility estimator for crop yield forecasting, and develop a closed form reinsurance pricing formula.

The purpose of this study is to demonstrate the use of weather derivatives to hedge firm exposure to previously unmanageable risk events caused by natural phenomenon such as excessive rainfall.Design/methodology/approach – The paper adopts a case study approach to meet the objectives above, focusing on golf courses in the Midwest USA, which provide perfect examples of businesses with seasonal cash flows.Findings – It is shown that a firm can reduce its revenue volatility by up to 80 per cent. Weather derivatives are important additions to firm portfolios of risk management tools. Purchasing weather derivatives will improve the owner's ability to forecast revenues and assure expenditure coverage, both important goals for a small business owner.Practical implications – Many firms find the uneven revenue streams associated with their industry to be difficult to manage. One of the primary risks faced by firms is exposure to weather phenomena. With the introduction of weather derivatives, firms can now hedge their exposure to climatologic events. The application for weather derivatives is quite limitless. Weather derivatives are a relatively new product, and most firms are either unaware of their existence or believe them to be complicated. It is an industry that may experience explosive growth in the coming years.Originality/value – This paper demonstrates the use of derivatives to hedge exposure to climatic events.

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.