Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Influence of the Premium Subsidy on Farmers’ Crop Insurance Coverage Decisions, April 2005

The Agricultural Risk Protection Act greatly increased the expected marginal net benefit of farmers buying high-coverage crop insurance policies by coupling premium subsidies to coverage level. This policy change, combined with cross-sectional variations in expected marginal net benefits of high-coverage policies, is used to estimate the role that premium subsidies play in farmers’ crop insurance decisions. We use county data for corn, soybeans, and wheat to estimate regression equations that are then used to obtain insight into two policy scenarios. We first estimate that eventual adoption of actuarially fair incremental premiums, combined with current coupled subsidies, would increase farmers’ purchase of high-coverage policies by almost 400 percent from 1998 levels across the three crops and two plans of insurance included in the analysis. We then estimate that a return to decoupled subsidies would decrease farmers’ high-coverage purchase decisions by an average of 36 percent.

Get a GRIP: Should Area Revenue Coverage Be Offered through the Farm Bill or as a Crop Insurance Program? 2007

The successful expansion of the U.S. crop insurance program has not eliminated ad hoc disaster assistance. An alternative currently being explored by members of Congress and others in preparation of the 2007 farm bill is to simply remove the “ad hoc” part of disaster assistance programs by creating a standing program that would automatically funnel aid to hard-hit regions and crops. One form such a program could take can be found in the area yield and area revenue insurance programs currently offered by the U.S. crop insurance program. The Group Risk Plan (GRP) and Group Risk Income Protection (GRIP) programs automatically trigger payments when county yields or revenues, respectively, fall below a producer-elected coverage level. The per-acre taxpayer costs of offering GRIP in Indiana, Illinois, and Iowa for corn and soybeans through the crop insurance program are estimated. These results are used to determine the amount of area revenue coverage that could be offered to farmers as part of a standing farm bill disaster program. Approximately 55% of taxpayer support for GRIP flows to the crop insurance industry. A significant portion of this support comes in the form of net underwriting gains. The expected rate of return on money put at risk by private crop insurance companies under the current Standard Reinsurance Agreement is approximately 100%. Taking this industry support and adding in the taxpayer support for GRIP that flows to producers would fund a county target revenue program at the 93% coverage level.

Resolución 12: Precios agrícolas y otras medidas = Resolution 12: Agricultural prices and crop insurance = Résolution 12: Prix agricoles et assurance des récoltes

El símbolo E/840/Rev.1 corresponde a la edición bilingüe inglés/francés publicada en 1953

All risk crop insurance.

Cover title.

Recommendations and findings to improve the federal crop insurance program : principal report of the Commission for the Improvement of the Federal Crop Insurance Program.

Mode of access: Internet.

Review of the federal crop insurance system : hearings before the Subcommittee on General Farm Commodities and Risk Management of the Committee on Agriculture, House of Representatives, One Hundred Ninth Congress, second session, March 15, April 26, 2006.

"Serial no. 109-27."

Hearing to review the federal crop insurance program : hearing before the Subcommittee on General Farm Commodities and Risk Management of the Committee on Agriculture, House of Representatives, One Hundred Tenth Congress, first session, May 14, 2007.

"Serial no. 110-22."

Hearing to review the state of the crop insurance industry : hearing before the Subcommittee on General Farm Commodities and Risk Management of the Committee on Agriculture, House of Representatives, One Hundred Tenth Congress, first session, Tuesday, May 1, 2007.

"Serial no. 110-15."

Federal all-risk crop insurance : why?

Mode of access: Internet.

Compilation of statutes relating to soil conservation, marketing quotas and allotments, soil bank, Commodity Credit Corporation, price support, export and surplus removal, crop insurance, sugar payments and quotas, marketing agreements and orders, and related statutes.

Issued Jan. l, 1953- as U.S. Dept. of Agriculture. Agriculture handbook, no. 49, 79, 113, 192, 242, 281, 317, etc.

Federal Crop Insurance Program Expands in 2016 and 2017 to Cover More Organic Crops

Organic agriculture represents one of the fastest growing segments of U.S. agriculture (USDA-RMA). With this in mind, the USDA’s Risk Management Agency (RMA) continues to expand crop insurance options for organic growers. In 2016 and 2017, organic producers in Maryland will see additional crops with organic crop insurance options. Increasing crop insurance options will allow this segment of producers new opportunities to manage their risks.

Crop Insurance For Maryland Field Crops And Livestock

Multi-peril crop insurance is a valuable risk management tool which allows you to insure against losses on your farm due to adverse weather conditions, price fluctuations, and unavoidable pests and diseases. It shifts unavoidable production risks to an insurance company for the payment of a fixed amount of premium per acre. This publication assists readers in understanding the basics of the federal crop insurance program.