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The aim of this paper is to show how provisions of the Supplemental Revenue Assistance Payments (SURE) program impacts production practices, and empirically examine changes in crop insurance participation rates as a means of measuring producer responses to the program.

The structure of the SURE program is described and a stylized theoretical model is used to show the SURE program's effects on farm‐level crop insurance and production decisions. A county‐level cross‐sectional empirical specification with regional fixed effects is used to test the hypothesis that producers who are most likely to benefit from production practice re‐optimization are more likely to participate in crop insurance.

Results from empirical analyses of corn, soybean, and wheat production areas show that the SURE program has had substantial impacts on crop insurance participation by producers who are more likely to receive SURE indemnities and exploit moral hazard opportunities.

Because the program has only recently been introduced, empirical estimates of the program's long‐run impacts are not estimable.

Results indicate that the program can have unexpected market consequences, with increased frequency and size of SURE indemnity claims than the Congressional Budget Office anticipated and increases in aggregate tax payer subsidies for both the crop insurance and SURE program. These outcomes can have important implications on motivating a restructuring of the program in the next farm bill.

Increased tax payer expenditures on the SURE and crop insurance programs in the form of subsidies can lead to non‐trivial reductions in social welfare.

This research is the first to develop a rigorous model of the SURE program's impacts on producer responses and associated effects on crop insurance participation. The study also provides empirical evidence of these effects.

The purpose of this paper is to determine which factors are most influential to farmers' crop insurance purchasing decisions in northern Illinois.

A mail survey method was used to collect information from farmers in a 42 county region of Illinois.

Of the factors analyzed, price had the most significant effect on crop insurance purchase decisions. While acres farmed had statistically significant impact on most of the crop insurance purchase decisions, different factors played a role in purchase decisions based on types of insurance and types of crops covered.

The results of this study warrant additional research relative to crop insurance purchase decisions. Analyzing the affect of varying degrees of government subsidization across crop insurance plans and coverage levels on purchase decisions is recommended. Questions regarding the relationship between crop insurance subsidization, farm program payments, and ad hoc disaster payments would be relevant in light of World Trade Organization and federal budget discussions. Also, asking participants to indicate if they have a written grain marketing plan and if that plan leverages crop insurance coverage to support forward contracting or pre‐harvest pricing would provide additional insights in determining how crop insurance purchase decisions are made. Questions regarding the claims process should be incorporated into future studies on this topic. The timeliness of claims payments, as well as the farmer's level of satisfaction with the claims adjustor and claims process may factor into the decision‐making process.

Illinois farmers and crop insurance agencies could benefit from this study. Findings could improve the crop insurance products and services available to Illinois farmers and make the federal crop insurance program more effective in enhancing farmers' ability to manage crop production risk.

This paper identified the factors that are most influential to farmers' crop insurance purchasing decisions in northern Illinois.

Aware that “those who aren't counted don't count” in health program planning, a community coalition, called African Partnership for Health, attempts a current estimate of the African community living in Portland, Oregon, USA. This paper seeks to describe the findings.

The paper's definition of the “African community” was crucially informed by community participation in the research process. The authors drew on existing publicly available data sources to estimate the size of the target population and identified the strengths and weaknesses of each source.

Conservative estimations are of a 2010 African community population of 11,500‐15,500 for the Portland metropolitan area. No data source on its own would have resulted in this estimate.

Areas for further research include creating practical systems to collect data on country of origin and to address an existing data bias towards refugees over immigrants. In the USA, more robust data collection systems are needed to estimate the impact of secondary migration on the size and characteristics of refugee and immigrant communities.

Health program planners should be aware that existing data may include more information about some groups (refugees as opposed to immigrants) and emphasize some characteristics (race as opposed to country of origin).

Including immigrant and refugee community members in the research process can result in more relevant definition of that community, which may lead to more effective program targeting and design.

Malting barley is an important specialty crop in the Northern Plains and growers mitigate risk with federally subsidized crop insurance and production contracts. The purpose of this paper is to quantify risks growers face due to “coverage gaps” in crop insurance that result in uncertain indemnity payments when their crop does not meet contract specifications.

A stochastic dominance model is developed to evaluate alternative strategies for growers with differing risk attitudes and production practices (irrigation vs dryland).

The results illustrate how alternative crop insurance provisions affect efficient choice sets for growers. Risk premiums for irrigated growers all point to valuations favoring more coverage, contracts, and malting option B. As the crop insurance industry matures in the functions it performs, it will become increasingly more important to address quality attributes.

This paper addresses quality issues and coverage gaps in crop insurance provisions.

An economic analysis is presented of the Standard Reinsurance Agreement (SRA), the contract governing the relationship between the Federal Crop Insurance Corporation and the private insurance companies that deliver crop insurance products to farmers. The paper outlines provisions of the SRA and describes the modeling methodology behind the SRA simulator, a computer program developed to assist crop insurers and policy makers in assessing the economic impact of the Agreement. The simulator is then used to analyze how the SRA affects returns from underwriting crop insurance. The results are presented in aggregate and also at the regional and individual company levels.

At the beginning of the production year producers face a complex risk management decision environment given by risks specific to their operation, multiple crop insurance contracts and hedging opportunities. The purpose of this paper is to provide a producer-level framework for risk management decision making, focusing on the interaction between crop insurance and hedging.

The authors develop a Monte Carlo simulation model that generates a producer’s net income (NI) distribution that incorporates historical producer risk, price-yield correlation via a copula, price risk, and production costs. The authors evaluate the NI distribution through a modified Modern Portfolio Theory (MPT) decision framework. The authors use the modified MPT decision framework to explore tradeoffs between expected NI and farm ruin (defined as 1 or 5 percent expected shortfall) from different crop insurance contracts and pre-harvest hedging options.

Only revenue protection and the highest two levels of coverage level exist on the efficient frontier. The level of hedging on the efficient frontier ranges from 0 to 55 percent of Actual Production History. The authors find that increasing coverage level 5 percent (from 80 to 85 percent) negatively impacts the optimal hedging amount by 26 percentage points (from 35 to 9 percent).

The model provides the precise identification of financial benefits from different risk management strategies by incorporating producer-level historical yield data, using a copula to capture yield-price dependency structure and producer production cost in generating the NI distribution. This model can be applied to any producer’s characteristics and data.

Federal crop insurance programs are the primary risk management programs of the US farm programs. Currently, these programs have been criticized for being disproportionally in favor of the riskier areas. Despite previous researchers having widely speculated its existence, a formal study of the scale, spatial pattern and fiscal impacts of such misrating phenomenon is still missing in the literature.

This paper first purposes an empirically testable definition of misrating, and then detects the scale of the misrating phenomenon by using over two million actuarial records collected by United States Department of Agriculture (USDA's) risk management agency since 1989. Furthermore, multiple spatial statistics methods have been adopted to study the spatial patterns of the misrating statuses. Finally, the paper builds a simple theoretical model to study the potential fiscal impacts of any policy attempts to mitigate the misrating issue.

The result reveals that roughly 40% of the counties display some degree of misrating. Furthermore, the distribution of misrating displays a significant pattern of positive global spatial autocorrelation, which reflects the existence of regional clusters of premium rate mispricing. Last but not least, the paper concludes that whether an attempt toward fair rating decreases the total program outlay or not relies on the demand elasticity of crop insurance in both overrated and underrated regions.

This paper offers the first attempt to quantify the scale, identify the spatial pattern and evaluate the fiscal impact of the premium misrating in federal crop insurance programs.

In the Netherlands, as in England, concerns exist about the extent of and frequency with which freedom-restricting measures are applied. The view is that use of these measures needs to decrease. The purpose of this paper is to outline new legislation that is expected to come into force in the Netherlands in 2020.

This paper provides a description of legislation entering into force on 1 January 2020.

Many of the new legislation’s practical implications remain unclear, including the definition of involuntary care.

The new legislation will start being monitored directly after coming into force, and only then the authors will make out what works well and what does not.

Introducing new legislation on coercion is not sufficient. Careful implementation of the legislation is important, including the way it defines involuntary care.

In 2020, the Netherlands is introducing new legislation on involuntary care for people with an intellectual disability. This includes a definition of involuntary care.

The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.

The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.

Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.

The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.