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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.

The purpose of this paper is to review the most recent scientific literature on the determinants explaining the demand for index-insurance, the impact of index-insurance and the existing links between insurance and credit. In this meta-analysis, the authors identify key discoveries on the potential of index-insurance in enhancing credit supply for smallholders and thus farm productivity.

Following a systematic literature search in Scopus and Web of Science, relevant empirical articles were identified by using the following criteria search algorithm: “insurance” and (“weather” or “micro” or “area?based” or “rain*” or “livestock” or “index”), and ((“empiric*” or “experiment” or “trial” or “RCT” or “impact”) or (“credit” or “loan*” or “debt” or “finance”)). The authors identified 1,133 related papers, 110 of which were selected as closely matching the study criteria. After removing duplicates and analysing each document, 45 papers were included in the current analysis. The framework for addressing insurance and credit issues, in the paper, entails three subsequent themes, namely, adoption of insurance, impact of insurance and links between insurance and credit.

It is not confirmed yet that demand for insurance is indeed hump-shaped in risk aversion and the functional form of this relationship should be tested in more detail. This also holds for the magnitude of the effect of trust and education on actual demand. Furthermore, it is unclear to what extent other risk mitigation strategies form complements or substitutes to index-insurance. Lastly, the interaction between basis risk and price is important to the design of index-insurance products. If basis risk and price elasticity are indeed highly correlated, products that diminish basis risk are crucial in increasing demand. On the impact of bundled products, e.g. combination of insurance and credit, limited empirical research has been conducted. For example, it is unknown to what extent credit suppliers would react to the insured status of farmers or what the preferences of farmers are when it comes to a mix of financial products. In addition, several researchers have suggested that microfinance institutions or banks could insure themselves against covariate risk, yet no empirical evidence about this insurance mechanism has been conducted so far.

The authors based the research on scientific literature uploaded in Scopus and Web of Science. Other potentially insightful grey literature was not included due to lack of accessibility. Given the research findings, there is plenty of opportunity for further research particularly with regard to the effects of bundled products, e.g. insurance plus credit, on demand for index-insurance, supply of credit, loan conditions and impact on farm productivity and farmers’ well-being.

Microfinance institutions, insurance companies, NGOs, research institutions and universities, particularly in developing countries, will be interested to learn about the systematic review of scientific research done in the area of insurance and credit for agriculture and the possibilities for application in their own practice of supplying these financial products.

A rigorous understanding of the potential of index-insurance and credit is essential for identifying the right mix of financial products that help smallholder farmers to increase farm productivity and their own well-being.

The paper is valuable due to its rigorous evaluation of existing theoretical and empirical research around issues explaining the degree of adoption and impact of index-insurance and that of bundled financial products (i.e. index-insurance plus credit). The paper has the potential to become essential reading for academics, practitioners and policy-makers interested in researching and putting in practice the best options leading to greater farm productivity and well-being in developing countries.

Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the authors look at different risk aggregation levels across political regions (meso-level). The authors then design weather index insurance products able to compensate revenue losses identified and analyze their risk reduction potential.

The authors design different weather insurance products based on put-options on a cumulated precipitation index. The insurance products are modeled for different inter-regional and intra-regional risk aggregation and risk coverage scenarios. In this attempt the authors deal with the common problem of developing countries in which yield data is often only available on an aggregate level, and weather data is only accessible for a low number of weather stations.

The authors find that it is feasible to design index-based weather insurance products on the meso-level with a considerable risk reduction potential against weather-induced revenue losses in cotton production. Furthermore, the authors find that risk reduction potential increases on the national level the more subregions are considered for the insurance product design. Moreover, risk reduction potential increases if the index insurance product applied is designed to compensate extreme weather events.

The findings suggest that index-based weather insurance products bear a large risk mitigation potential on an aggregate level. Hence, meso-level insurance should be recognized by institutions with a regional exposure to cost-related weather risks as part of their risk-management strategy.

The authors are the first to investigate the potential of weather index insurance for different risk aggregation levels in developing countries.

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.

Index insurance is promising to mitigate drought-related income losses in agriculture. To reduce the basis risk of index insurance, the integration of satellite data is of growing interest in research. The objective of this study is to obtain preliminary evidence regarding farmers' perceived usefulness (PU) of satellite-based index insurance.

By modifying the transtheoretical model of change to a transtheoretical model of PU, German farmers' gradual PU of satellite-based index insurance was investigated.

The results show that the average farmer perceives satellite-based index insurance as useful. It can be particularly seen that a higher level of education in an agricultural context as well as higher trust in index insurance products increases farmers' gradual PU. Moreover, higher relative weather-related income losses increase farmers' gradual PU.

It is recommended to apply latent variables when conducting future investigations regarding farmers' PU.

To the best of the authors' knowledge, this is the first study to explore farmers' PU of upcoming satellite-based index insurance by modifying and applying the transtheoretical model in a new way.

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.

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 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.

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.

Agricultural weather index insurance (WII) has been introduced in pilot or experimental form in many countries. However, the effective demand for WII is often limited by the impact of the basis risk. Thus, the purpose of this paper is to propose a new type of double trigger product, named “supplement” type, to reduce basis risk and improve the performance of the standalone WII.

Two measures of performance are introduced by the certainty equivalent income of expected utility theory. Through the Monte Carlo experiments and empirical study, this paper compares the performance of three types of double trigger products.

The findings indicate that the supplement type can significantly improve the performance of the single weather index product. First, it covers the downside basis risk and the catastrophic basis risk when the standalone WII fails to do so, especially in case of extreme losses. Second, it is superior when the correlation between the weather index and the yield index is not so strong, and can further enhance the performance of insurance even when the weather index and the yield index are highly correlated, for which the standalone WII could perform well.

The supplement type double trigger product proposed in this paper as an enhancement version finds a more preferable way to improve the standalone WII with relative lower complexity.