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Article
Publication date: 29 April 2014

Niels Pelka, Oliver Musshoff and Robert Finger

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

China Agricultural Economic Review, vol. 6 no. 2
Type: Research Article
ISSN: 1756-137X

Keywords

Article
Publication date: 2 November 2012

Leif Erec Heimfarth, Robert Finger and Oliver Musshoff

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…

Abstract

Purpose

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.

Design/methodology/approach

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

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.

Originality/value

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.

Details

Agricultural Finance Review, vol. 72 no. 3
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 15 May 2017

Davide Castellani and Laura Viganò

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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).

Details

International Journal of Bank Marketing, vol. 35 no. 3
Type: Research Article
ISSN: 0265-2323

Keywords

Article
Publication date: 5 May 2015

Ron Weber, Wilm Fecke, Imke Moeller and Oliver Musshoff

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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

Details

Agricultural Finance Review, vol. 75 no. 1
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 6 July 2015

Niels Pelka, Oliver Musshoff and Ron Weber

Small-scale farmers in developing countries are undersupplied with capital. Although microfinance institutions (MFIs) have become well established in developing countries…

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Abstract

Purpose

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.

Design/methodology/approach

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).

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

Agricultural Finance Review, vol. 75 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 2 August 2011

Leif Erec Heimfarth and Oliver Musshoff

The purpose of this paper is to analyze the extent to which weather index‐based insurances can contribute to reducing shortfall risks of revenues of a representative…

Abstract

Purpose

The purpose of this paper is to analyze the extent to which weather index‐based insurances can contribute to reducing shortfall risks of revenues of a representative average farm that produces corn or wheat in the North China Plain (NCP). The geographical basis risk is quantified to analyze the spatial dependency of weather patterns between established weather stations in the area and locations where the local weather patterns are unknown.

Design/methodology/approach

Data are based on the Statistical Yearbook of China and the Chinese Meteorological Administration. Methods of insurance valuation are burn analysis and index value simulation. Risk reduction is measured non‐parametrically and parametrically by the change of the standard deviation and the value at risk of revenues. The geographical basis risk is quantified by setting up a decorrelation function.

Findings

Results suggest significant differences in the potential risk reduction between corn and wheat when using insurance based on a precipitation index. The spatial analysis suggests a potential to expand the insurance around a reference weather station up to community level.

Research limitations/implications

Findings are limited by a weak database in China and, in particular, by the unavailability of individual farm data. Moreover, the low density of weather stations currently limits the examination of the approach in a broader context.

Practical implications

The risk reduction potential of the proposed insurance is encouraging. From a policy point of view, the approach used here can support the adjustment of insurers towards different crops.

Originality/value

This paper is believed to be the first that investigates a weather index‐based insurance designed for an average farm in the NCP and the quantification of geographical basis risk.

Details

Agricultural Finance Review, vol. 71 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 26 July 2013

Niels Pelka and Oliver Musshoff

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

Agricultural Finance Review, vol. 73 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Book part
Publication date: 19 October 2016

Marcus Taylor

Conceptualizing development in terms of risk management has become a prominent feature of mainstream development discourse. This has led to a convergence between the…

Abstract

Conceptualizing development in terms of risk management has become a prominent feature of mainstream development discourse. This has led to a convergence between the rubrics of financial inclusion and risk management whereby improved access for poor households to private sector credit, insurance and savings products is represented as a necessary step toward building “resilience.” This convergence, however, is notable for a shallow understanding of the production and distribution of risks. By naturalizing risk as an inevitable product of complex systems, the approach fails to interrogate how risk is produced and displaced unevenly between social groups. Ignoring the structural and relational dimensions of risk production leads to an overly technical approach to risk management that is willfully blind to the intersection of risk and social power. A case study of the promotion of index-based livestock insurance in Mongolia – held as a model for innovative risk management via financial inclusion – is used to indicate the tensions and contradictions of this projected synthesis of development and risk management.

Article
Publication date: 7 July 2020

Roman Hohl, Ze Jiang, Minh Tue Vu, Srivatsan Vijayaraghavan and Shie-Yui Liong

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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).

Practical implications

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.

Originality/value

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.

Article
Publication date: 5 May 2008

Jerry R. Skees, Barry J. Barnett and Anne G. Murphy

This article considers the potential for securitizing index‐based insurance products that transfer weather and natural disaster risks from lower income countries. It…

Abstract

This article considers the potential for securitizing index‐based insurance products that transfer weather and natural disaster risks from lower income countries. It begins with a brief overview explaining why markets for natural disaster risks are important, yet often missing, in lower income countries and a review of some recent activities using index‐based weather insurance. Next, we describe how natural disaster risks are handled in higher income countries. These examples, along with the example of an innovative index‐based livestock insurance pilot project in Mongolia, illustrate how layers, or tranches, of natural disaster risk can be financed during the product development phase by creating structures similar to the Special Purpose Vehicles used in catastrophe bond, mortgage bond, and the emerging microfinance bond markets. We refer to these investment alternatives as micro‐CAT bonds since the principle amounts would be small relative to the existing CAT bond market.

Details

Agricultural Finance Review, vol. 68 no. 1
Type: Research Article
ISSN: 0002-1466

Keywords

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