Search results

The purpose of this paper is to provide an evaluation method for agricultural catastrophic risk.

Data on agricultural disaster loss are collected based on hectares covered by natural disasters, hectares affected by natural disasters, and hectares destroyed by natural disasters using the standard process. Peak over threshold (POT) approach based on the extreme value theory is used to model the distribution of agricultural catastrophic loss, and value at risk (VaR) is used to assess agricultural catastrophic risk.

This paper provides an approach for collecting agricultural loss data and modelling probability distribution of agricultural catastrophic loss, which is promising for agricultural catastrophic risk evaluating. As the quantified measurement of agricultural catastrophic risk, VaR is observed to be appropriate and feasible. Results of empirical research demonstrate that drought catastrophe negatively affects grain‐production in the northeast region of China; in particular, the drought catastrophic risk is severe within a 100‐year scenario and thus is expected to recur.

To provide an accurate agricultural catastrophic risk assessment, data collection based on disaster occurrence instead of crop yield, and VaR is used in this paper.

The purpose of this paper is to investigate changes proposed in 2012 to commodity programs for the new Farm Bill. Both the Senate and House Agriculture Committee versions of the new Farm Bill eliminate current commodity programs including direct payments, create new revenue‐based commodity program options designed to cover “shallow” revenue losses, and also introduce supplemental crop insurance coverage for shallow revenue losses.

This paper documents the payment functions for the new revenue programs proposed in both the Senate and House Ag Committee Farm Bills, and also estimates expected payments for each using a model based on historical county yield data, farmer‐level risk rates from RMA, and commodity price levels from the March 2012 CBO baseline projections.

The authors find significant variation in expected per acre payment across programs, crops, and regions. In general, the Senate's bill would be expected to be preferred over the House's bill for corn and soybean producers, particularly those in the Midwest. Also, the RLC program in the House's Bill typically would be projected to pay much less than the Senate's SCO or ARC programs for most producers in the Midwest.

This study develops an extensive nationwide model of county and farm yield and price risks for the five major US crops and employs the model to evaluate expected payment rates and the distribution of payments under the House and Senate Farm Bill proposals. These analyses are important for program evaluation and should be of great interest to producers and policymakers.

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.

Revenue insurance is the most popular form of insurance available in the US federal crop insurance program. The majority of crop revenue policies are sold with a harvest price replacement feature that pays out on lost crop yields at the maximum of a realized or projected harvest price. The authors introduce a novel actuarial and statistical approach to rate revenue insurance policies with exotic price coverage: the payout depends on an order statistic or average of prices. The authors examine the price implications of different dependence models and demonstrate the feasibility of policies of this type.

Hierarchical Archimedean copulas and vine copulas are used to model dependence between prices and yields and serial dependence of prices. The authors construct several synthetic exotic price coverage insurance policies and evaluate the impact of copula models on policies covering different types of risk.

The authors’ findings show that the price of exotic price coverage policies is sensitive to the choice of dependence model. Serial dependence varies across the growing season. It is possible to accurately price exotic coverage policies and we suggest these add-ons as a possible avenue for developing private crop insurance markets.

The authors apply hierarchical Archimedean copulas and vine copulas that allow for flexibility in the modeling of multivariate dependence. Unlike previous research, which has primarily considered dependence across space, the form of exotic price coverage requires modeling serial dependence in relative prices. Results are important for this segment of the agricultural insurance market: one of the main areas that insurers can develop private products around the federal program.

Community supported agriculture (CSA) programs allow consumers to buy a share of a farm’s production while providing working capital and risk management benefits for farmers. Several different types of CSA arrangements have emerged in the market with terms varying in the degree to which consumers share in the farm’s risk. No-arbitrage principles of futures and options pricing suggest that CSA shares should be priced to reflect the degree of risk transfer. The paper aims to discuss these issues.

The authors evaluate the three most common share types using a cross-sectional data set of 226 CSA farms from New England to determine if there is empirical evidence in support of the theoretical price relationship between share types.

The degree of risk transfer from farmers to consumers has a significant effect on the share price. There are statistically significant returns to scale and higher prices for organics. Farm characteristics and product offerings predict which type of shares is offered for sale.

The data set does not contain information pertaining to actual deliveries, expected deliveries, variance of expected deliveries, or covariance information; thus differences in share prices could be due to differences in these uncontrolled factors.

This paper provides empirical evidence that CSA share prices reflect the degree of risk transferred from the producer to the consumer. It also highlights challenges in conducting empirical work pertaining to CSA contracting.

The purpose of this paper is to assess the production risk for winter wheat producers in Beijing, China, particularly in its 13 districts.

A parametric approach is used to model wheat‐yield distribution for samples and the Kolmogorov‐Smirnov test is used to choose the most appropriate yield distribution. Parameters of the special yield distribution are estimated through the maximum likelihood estimation approach.

The Burr distribution is found to be the most appropriate parametric distribution to model winter wheat‐production risks for the districts of Beijing, except in the districts of Fengtai and Shunyi. Findings also show that the Johnson family distribution is the most appropriate model for these two districts (SB for the Fengtai District and SU for the Shunyi District). The wheat‐production loss ratios of the Beijing districts are between 6 and 15 percent, which is considered medium range in most regions. The highest production risks are located in the Western regions of Beijing (Mentougou and Fengtai) while the lowest production risk is located in the Southeastern region of Beijing (Daxing District).

To generate an objective yield trend and an accurate production risk assessment, linear moving average, instead of linear (or quadratic) regression, is used in this paper.

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.

A simulation methodology is applied to the loan loss reserve process of an agricultural lender. Weaknesses of the point‐estimate approach to estimating loan loss reserves are addressed with a “bottom‐up” model. Modeling includes consideration of the producer’s and the lender’s diversification efforts. Implementation of this model will provide the lender a better understanding of the institution’s portfolio risk, as well as the credit risk associated with each loan. This study compares the lender’s loan loss estimates to a distribution of losses with associated probabilities. The comparative results could provide the lender a basis for setting probability levels for determining the regulatory required level of loan loss reserve.

This paper is based on a crop insurance implementation currently undergoing in Haiti. The purpose of this paper is to present the development of a program tailored to rice production in the Artibonite Valley, the challenges and opportunities that are arising from the exercise as well as pitfalls and ways to avoid them.

The Système de Financement et d’Assurances Agricoles en Haïti’s approach for the development of crop insurance is in accordance with 13 concepts considered essential in the implementation of agricultural insurance programs. The case study is presented through each of these 13 fundamental concepts.

The paper provides an insight on challenges any organization will face when implementing crop insurance for smallholder farmers. It points out notably that close collaboration of executing agencies with local partners is essential from data collection through insurance development and delivery and that all participants should receive a specific training tailored to their level of education and understanding.

Haiti is one of the poorest countries on the planet. Smallholder farmers could benefit a lot from crop insurance. It could help them stabilize their income when facing crop losses due to natural hazards or uncontrollable natural events.

This paper fulfills an identified need to share real case studies exposing challenges faced when implementing crop insurance for smallholder farmers.

Since 1980, the principal form of crop loss assistance in the United States has been provided through the Federal Crop Insurance Program. The Federal Crop Insurance Act of 1980 was intended to replace disaster programs with a subsidized insurance program that farmers could depend on in the event of crop losses. Crop insurance was seen as preferable to disaster assistance because it was less costly and hence could be provided to more producers, was less likely to encourage moral hazard, and less likely to encourage producers to plant crops on marginal lands. Despite substantial growth in the program, the crop insurance program has failed to replace other disaster programs as the sole form of assistance. Over the past 20 years, producers received an estimated $15 billion in supplemental disaster payments in addition to $22 billion in crop insurance indemnities.