Risk Management Agency Research Articles

Availability of County Crop Insurance in 2014: Implications for SCO

The Supplemental Coverage Option (SCO) will be made available beginning in the 2015 crop year for those individuals who choose the Price Loss Coverage (PLC) option for receiving commodity payments under the 2014 Farm Bill. SCO is a county crop insurance product providing coverage from an 86% coverage level down to the coverage level of the Combo product (farmdoc daily, February 27, 2014; April 24, 2014). The Risk Management Agency (RMA) will administer SCO. As of yet, RMA has not released counties for which SCO will be available in 2015. Since SCO is somewhat similar to Area Risk Protection Insurance (ARPI), showing available of ARPI policies may give some guidance for SCO availability. This article shows maps of 2014 availability of ARPI polices for corn, soybeans, wheat, cotton, and grain sorghum, the five traditional program crops for which ARPI policies exist.

Livestock Gross Margin Insurance for Dairy: The Other Dairy Safety Net Solution

With all the attention on the new Margin Protection Program for Dairy Producers (MPP) let us not forget about Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy). Similar to MPP, LGM-Dairy is also a USDA risk management instrument which offers protection against declines in average dairy income-over-feed-cost (IOFC) margins. Introduced in 2008, LGM-Dairy is an insurance product overseen by USDA’s Risk Management Agency. Like crop insurance, LGM-Dairy is sold by private insurance agents and underwritten by the Federal Crop Insurance Corporation (for a complete description of LGM-Dairy rules see here).

Evaluating Crop Insurance Options for 2014

The Risk Management Agency (RMA) has now concluded its price discovery period used to determined final prices and volatility factors for federally sponsored corn and soybean crop insurance products for 2014. For the majority of the cornbelt, the approved Projected Price (PP) for corn is $4.62 and the volatility factor is .19. For soybeans, the projected price is $11.36 with a volatility factor of .13. For comparison, the 2013 prices (volatility factors) were $5.65 (.20) and $12.87 (.17) for corn and soybeans respectively. The Projected Prices are used to determine the guarantee revenue indexes based on futures prices, and do not reflect local basis. The Projected Price for corn is determined by averaging the closing December futures price during the trading days of February, and for soybeans by averaging the November Futures closing prices during February. The volatility factors are determined by an average of the most recent five trading days' implied volatility estimates, scaled for the interval of time from now until the middle of October -the month during which average prices are used to determine Harvest Prices. For both corn and soybeans, the volatility factors have trended downward, and relative to popularly interpreted measures of volatility are considered very low for soybeans in particular. The volatility factor summarizes the market’s estimates of the likelihood for price movements of various magnitudes, and has corresponding impacts on premiums paid for Revenue and Harvest Price related products. In 2014, the Projected Prices for soybeans are close to current futures market prices, while corn traded around $.14 higher than the projected price on the first sales date for crop insurance. When actual futures prices are below the projected price, there is a somewhat increased likelihood for experiencing an insured revenue shortfall, and when actual futures prices are higher than the projected price, there is an increased likelihood that products with the harvest price option embedded will have an increase in guarantee value. Beginning with the 2014 crop, the projected prices and volatilities, where relevant, are now common over both farm-level and area-revenue and area-yield policies.

Accounting for short samples and heterogeneous experience in rating crop insurance

Purpose – The purpose of this paper is to be an academic inquiry into rating issues confronted by the US Federal Crop Insurance program stemming from changes in participation rates as well as the weighting of data to reflect longer‐run weather patterns.Design/methodology/approach – The authors investigate two specific approaches that differ from those adopted by the Risk Management Agency, building upon standard maximum likelihood and Bayesian estimation techniques that consider parametric densities for the loss‐cost ratio.Findings – Both approaches indicate that incorporating weights into the priors for Bayesian estimation can inform the distribution.Originality/value – In most cases, the authors' results indicate that including weighting into priors for Bayesian estimation implied lower premium rates than found using standard methods.

A Natural Resource Theory of U.S. Crop Insurance Contract Choice

AbstractA large variety of subsidized crop insurance products are available to U.S. crop growers. Distinct and perhaps puzzling patterns in the choices of insurance products and coverage levels can be discerned. Where production conditions are better and yields are less risky then (a) higher insurance coverage levels are chosen; and (b) revenue insurance is preferred over yield insurance. Also, (c) the extent of preference for revenue insurance is stronger in more productive areas. Assuming, as many do, that growers seek to maximize subsidy transfers, point (a) can be explained by the interaction between yield technology and natural resource endowments. Points (b) and (c) can be explained by location in conjunction with the “natural hedge” and a contract design bias in how revenue insurance guarantees are computed. Empirical study of Risk Management Agency data on corn, soybean, and wheat yields, and insurance contract choices lend support to our model inferences.

Accounting for short samples and heterogeneous experience in rating crop insurance

PurposeThe purpose of this paper is to be an academic inquiry into rating issues confronted by the US Federal Crop Insurance program stemming from changes in participation rates as well as the weighting of data to reflect longer‐run weather patterns.Design/methodology/approachThe authors investigate two specific approaches that differ from those adopted by the Risk Management Agency, building upon standard maximum likelihood and Bayesian estimation techniques that consider parametric densities for the loss‐cost ratio.FindingsBoth approaches indicate that incorporating weights into the priors for Bayesian estimation can inform the distribution.Originality/valueIn most cases, the authors' results indicate that including weighting into priors for Bayesian estimation implied lower premium rates than found using standard methods.

Yield Guarantees and the Producer Welfare Benefits of Crop Insurance

Crop yield and revenue insurance products with coverage based on actual production history (APH) yields dominate the U.S. Federal Crop Insurance Program. The APH yield, which plays a critical role in determining the coverage offered to producers, is based on a small sample of historical yields for the insured unit. The properties of this yield measure are critical in determining the value of the insurance to producers. Sampling error in APH yields has the potential to lead to over-insurance in some years and under-insurance in other years. Premiums, which are in part determined by the ratio of the APH yield to the county reference yield, are also affected by variations in APH yields. Congress has enacted two measures, yield substitution and yield floors, that are intended to limit the degree to which sampling error can reduce the insurance guarantee and producer welfare. We examine the impact of sampling error and related policy provisions for Texas cotton, Kansas wheat, and Illinois corn. The analysis is conducted using county level yield data from the National Agricultural Statistics Service and individual insured-unit-level yield data obtained from the Risk Management Agency’s insurance database. Our findings indicate that sampling error in APH yields has the potential to reduce producer welfare and that the magnitude of this effect differs substantially across crops. The yield substitution and yield floor provisions reduce the negative impact of sampling error but also bias guarantees upward, leading to increased government cost of the insurance programs.

Evaluation of Crop Insurance Yield Guarantees and Producer Welfare with Upward-Trending Yields

Actual Production History (APH) yields play a critical role in determining the coverage offered to producers by the Risk Management Agency's yield-based crop insurance products. Using both county and individual insured unit data, we examine the impact of APH yield trends for Texas cotton and Illinois com. Our findings indicate that biases due to using simple average APH yields when yields are trending upward reduce the expected indemnity and actuarially fair premium rate. The estimated welfare effect also varies significantly with different commonly used detrending approaches. This study demonstrates that producer welfare can be enhanced through proper treatment of yield trends in crop insurance programs.

Premium estimation inaccuracy and the actuarial performance of the US crop insurance program

PurposeThe purpose of this paper is to explore the impact of the levels of inaccuracy associated with three different premium estimation methods, one of which attempts to mimic the protocol currently used by the Risk Management Agency (RMA), on the actuarial performance of the US crop insurance program.Design/methodology/approachThe analyses are conducted using empirically‐grounded simulation and other computational methods, under various plausible assumptions about the producer's risk aversion behavior and knowledge of his/her actuarially fair premium.FindingsRegardless of the assumed producer knowledge and behavior, it is concluded that the persistently high government subsidy levels required to keep the program solvent could be solely explained by the inaccuracy in the RMA's premium estimates. In other words, the observed need for large subsidies does not necessarily imply that the program is systematically favoring less efficient farmers or particular crops or production areas. Also, contrary to the commonly accepted “adverse selection” argument, it is shown that farmers having more information about their actuarially fair premiums than the insurer is not the reason why high subsidies are needed. Actuarial performance, however, could be improved by using the more elaborate methods exemplified in the paper, as well as larger sample sizes for premium estimation.Originality/valueThe paper provides conclusions and recommendations that could substantially reduce the amount of public subsidies needed to keep the US crop insurance program solvent.

Implications of within county yield heterogeneity for modeling crop insurance premiums

PurposeFarm level data are essential to accurate setting of crop insurance premium rates, but their time series tends to be too short to allow them to be the sole data source. County level data are available in longer time series, however. The purpose of this paper is to present a methodology to make full use of the information inherent in each of these data sets.Design/methodology/approachThe paper uses a novel application of statistical tools for using farm and county level yield data to generate farm level yield densities that explicitly incorporate within county yield heterogeneity while accounting for systemic risk and other spatial or intertemporal correlations among farms within the county.FindingsThe empirical analysis shows that current approaches used by the Risk Management Agency to individualize premiums for a farm result in substantial mispricing of crop insurance premiums because they do not adequately capture farm yield variability and yield correlations between farms. The new premium setting method is empirically shown to substantially reduce government subsidies for crop insurance premiums.Originality/valueThe paper demonstrates how to extract more information from available data when setting crop insurance premiums, which allows the government to more closely tailor premiums to the farm than do current approaches.

An Actuarial Analysis of Calibration of Crop Insurance Premiums to Heterogeneous Risks

This paper examines whether the loadings on the crop insurance premium rates for risks such as moral hazard and adverse selection are adequate. From the discrete choice (tobit) analysis conducted, we discover that the premium loadings for 75% coverage level are not adequate, resulting in losses for the Risk Management Agency.

Can Crop Insurance Premiums Be Reliably Estimated?

This paper develops and applies a methodology to assess the accuracy of historical loss-cost rating procedures, similar to those used by the U.S. Department of Agriculture's Risk Management Agency (RMA), versus alternative parametric premium estimation methods. It finds that the accuracy of loss-cost procedures leaves much to be desired, but can be markedly improved through the use of alternative methods and increased farm-level yield sample sizes. Evidence suggests that the high degree of inaccuracy in crop insurance premium estimations through historical loss-cost procedures identified in the paper might be a major factor behind the need for substantial government subsidies to keep the program solvent.

Evaluation of the reference yield calculation method in crop insurance

PurposeThis article seeks to examine the reference yield calculation method used in crop insurance rating and provides recommendations that could potentially improve actuarial performance of the Federal crop insurance program.Design/methodology/approachConceptual, numerical, and statistical analysis is utilized to evaluate the reference yield calculation method used in the US Federal crop insurance program.FindingsThe results suggest that reference yields, which at the time of this study are calculated using National Agricultural Statistics Service (NASS) data, do not accurately represent the average actual yields of the insured pool of producers in the Federal crop insurance program. In addition, it is found that not regularly updating these NASS‐based reference yields exacerbates this problem because these reference yields do not appropriately represent the current state of technological progress.Practical implicationsThe empirical analysis leads this paper to recommend a reference yield calculation procedure that utilizes county‐average yields from the risk management agency (RMA) participation database and an approach that uses spatially aggregated average yields in cases when data for a particular county are sparse.Originality/valueNo previous study has investigated the reference yield calculation method in the Federal crop insurance program using both RMA and NASS data sets. Moreover, this study contributes to the small literature that examines various aspects of the actual production history (APH) rating platform and suggests refinements to improve actuarial performance.

Near-miss event assessment in orthopedic surgery: Antimicrobial prophylaxis noncompliance

Antimicrobial prophylaxis is one of the main safety measures to be enforced when implanting any medical device; surveys of practice, however, have found poor compliance. This study is based on analysis of 153 dedicated in-depth analysis forms sent to orthopedic surgeons who had reported an antimicrobial prophylaxis-related near-miss event (NME) during the year 2008 as part of their certification report to the official organization, Orthorisq (orthopaedic Patient safety risk management agency). Antimicrobial prophylaxis guidelines exist in 95% of French centers, but in 14% are not available in the right place. 88% of orthopedic surgeons consider them well-adapted to their practice. Most declarations follow fortuitous discovery by the surgeon of an immediate peri-operative malfunction. Human causes were found in 92% of declarations, general organizational causes in 50% and material causes in 28%. Regarding corrective action, 65% of respondents reported implementing a second-order procedure, and only 20% were able to resume truly regular antimicrobial prophylaxis. The main reason for poor or non-performance of antimicrobial prophylaxis was "omission by negligence or oversight", reported in 56% of declarations. Proposals for improvement were: revised antimicrobial prophylaxis guidelines specifying "who does what"; guideline awareness checks on new, temporary and locum-tenens staff; patient involvement in personal data collection; and implementation of a check-list in line with WHO and French Health Authority recommendations. These improvement proposals were taken on board in the antimicrobial prophylaxis consensus update currently being drawn up by the French Society for Anesthesia and Intensive Care. Level IV, Decision Analyses Study.

Special Issue on Crop Insurance and Risk Management

The role of crop insurance and new risk management tools for agriculture is evolving at an almost dizzying pace. One needs only to examine recent postings on the Risk Management Agency's website to see how expansive this is. Moreover, throughout the world we are witness to a host of new programs available in both developed and developing countries that are largely based on the U.S. experience. It is necessary that academics first recognize the scope of issues facing production and market risks in agriculture and then respond with new and creative ways to address the problems. To these needs, the Crop Insurance and Risk Management Workshop—the provenance of the papers in this volume—was designed to bring academics with research and extension responsibilities together with industry to explore this ever-changing landscape and discuss research and outreach of mutual interest.

Extension Programs in Crop Insurance: A Maryland Case Study

Many states have crop insurance extension programs. This activity has been stimulated with the availability of funds to support extension from the Risk Management Agency (RMA) of the U.S. Department of Agriculture. Several new RMA programs were established under the Agricultural Risk Protection Act of 2000. The Targeted States Program is quite important for the Northeast. This program serves states that were traditionally underserved by crop insurance. It is available in all 12 northeastern states, plus Nevada, Utah, and Wyoming. The Targeted States Program funds one program in each state. A total of $4.5 million in funding is available each year. Amounts for state programs range from $157,000 in Rhode Island to $754,000 in Pennsylvania, which is a considerable amount of funding.

Regionalizing Agent Training with the Greenhouse Tomato Short Course

The protocol for agent training has always been for extension specialists to train agents within the same state in each aspect of agriculture. However, with ubiquitous cutbacks among universities, and extension in particular, it is no longer feasible for every state to provide expertise in each field. Consequently, agents cannot receive training in some specialized fields. With a partnership agreement from the USDA Risk Management Agency, the Greenhouse Tomato Short Course in Jackson, Miss., provided training for five to seven agents from each state in the region: Louisiana, Tennessee, Kentucky, and Mississippi. Funding was made available to cover travel expenses, registration, and a resource notebook for 25 agents. As a result, these agents took part in 3 days of intensive training seminars, as well as a 1-day tour of greenhouses. Invited speakers from around the United States spoke to these agents, as well as current and prospective commercial growers from all over the United States. Topics included basics of producing a commercial crop of hydroponic greenhouse tomatoes, budget for establishing and operating a greenhouse business, marketing and promotion, principles of risk management, pest and disease identification and management, grower's point of view, heating, cooling, and ventilation of greenhouses, new technologies, diagnostics, recent research in greenhouse production, and alternative crops (lettuce, peppers, mini-cucumbers, galia melons, baby squash) for the greenhouse. With this training, agents from throughout the south-central region returned to their offices with the skills to assist growers in their counties to succeed in the hydroponic greenhouse tomato business. Complete information on the short course can be found at www.greenhousetomatosc.com.

FOOD SAFETY TRAIN-THE-TRAINER PROGRAM

This paper summarizes the results of a multi-state, multi-institutional partnership delivering a targeted train-the-trainer program. The program provided good agricultural practices (GAPs) and good manufacturing practices (GMPs) based training to southeastern U.S. fresh fruit and vegetable (produce) growers and packers. Twelve southern U.S. states cooperated in this project between 2001 and 2004. In the work 150 trainers introduced nearly 20,000 persons to GAPs principles, including over 2,000 Spanish-speaking workers and a similar number of limited resource/specialty crop/grower/packer/buyer audience members. Actual numbers of persons reached was nearly 20,000, a number arrived at by counting signed-in registrations for events. Cost per person for outreach was about $6.00 per person, including travel expenses. In cooperation with the federal Risk Management Agency, a training component about risk in fresh produce operations was developed. This unit was delivered to historically underserved audiences, small farms and roadside markets, and other non-traditional audiences. This training continues today.

Extending Federal Crop Insurance Programs to Commercial Fisheries: The Case of Bristol Bay, Alaska, Sockeye Salmon

AbstractThis paper analyzes the feasibility of extending the U.S. Department of Agriculture's crop insurance program to the Bristol Bay, Alaska, capture fishery for sockeye salmon Oncorhynchus nerka. The impetus for this program has been a string of poor sockeye salmon fishing seasons followed by a series of disaster declarations in western Alaska. The mission of the Risk Management Agency, for whom this analysis was prepared, is to help stabilize the agricultural sector, not to provide disaster payments that offset permanent industry shifts by assuring producers some historical (but no longer attainable) production or revenue levels. Without a contemporaneous effort to restructure and rationalize the program of limited entry, the proposed crop insurance program for Bristol Bay cannot provide meaningful relief to a maladaptive industry that is beleaguered by excessive costs and increased competition.

Systemic risk in U.S. crop reinsurance programs

This study develops a method to estimate the probability density function of the Federal Risk Management Agency’s (RMA’s) net income from reinsuring crop insurance for corn, wheat, and soybeans. When calibrated using 1997 data, results from the advocated method show that in 1997 there was a 5% probability RMA would have had to reimburse at least $1 billion to insurance companies, and the fair value of RMA’s insurance services to insurance firms in 1997 was $78.7 million.