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Few issues in business ethics are as polarizing as the practice of risk classification and underwriting in the insurance industry. Theorists who approach the issue from a background in economics often start from the assumption that policy-holders should be charged a rate that reflects the expected loss that they bring to the insurance scheme. Yet theorists who approach the question from a background in philosophy or civil rights law often begin with a presumption against so-called “actuarially fair” premiums and in favor of “community rating,” in which everyone is charged the same price. This paper begins by examining and rejecting the three primary arguments that have been given to show that actuarially fair premiums are unjust. It then considers the two primary arguments that have been offered by those who wish to defend the practice of risk classification. These arguments overshoot their target, by requiring a “freedom to underwrite” that is much greater than the level of freedom enjoyed in most other commercial transactions. The paper concludes by presenting a defense of a more limited right to underwrite, one that grants the legitimacy of the central principle of risk classification, but permits specific deviations from that ideal when other important social goods are at stake.

The practice of insuring essentially involves the determination and assignment of risk to individuals. Such determinations are made almost exclusively on the basis of statistical models. As such, the determination of an individual's risk in relation to a particular form of insurance, and thus ultimately to the determination of the cost and availability of that insurance for the individual, is made in relation to her inclusion in certain statistical groups. However, a number of questions, both practical and philosophical, can be raised about the way in which an individual is assessed upon the basis of such statistical modeling. In this paper, I explore some of these issues in relation to questions of fairness. I begin by examining the basic structure of statistical risk assessment for insurance purposes. I argue that the underlying ethical concern involved with such cases involves the manner in which the attributes of the statistical groups used for insurance purposes can be said to fairly represent the individual qua individual. As such, I go on to explore the general philosophical issues involved in applying statistical models to individuals and the fairness of using such applications to make determinations about individuals for insurance purposes.

The purpose of this paper is to develop methods for inferring if crop insurance premiums imply yield distributions that are valid according to standard laws of probability and broadly consistent with observed empirical evidence. The authors also survey current premium-implied distributions both before and after conditioning on the producer’s choice of coverage level.

Under an assumption of actuarial fairness, the authors derive expressions for upper and lower bounds for premium-implied yield cumulative distribution functions (CDFs) at loss thresholds for each coverage level. When observed premiums imply a CDF that exceeds one or is not non-decreasing, the authors conclude that premiums cannot be actuarially fair. The authors additionally specify very weak conditions for premium-implied yield CDFs to be consistent with two possible reasonable parametric distributions.

The authors evaluate premiums for the year 2018 for 19,104 county-crop-type-practice combinations, both before and after conditioning on producer’s choice of coverage level. The authors find problems in roughly one-third of cases. Problems are exhibited for all crops evaluated, and are strongly associated with areas with lower expected yields and higher yield variability. At least 40m acres are currently insured under premium schedules that cannot possibly be consistent with valid probability distributions.

The authors make two primary contributions. First, the premium-implied yield CDF bounds the authors derive requires fewer assumptions than previous similar work, while simultaneously placing more stringent conditions on premiums to be consistent with actuarial fairness. Second, the authors show that current US crop insurance premiums cannot possibly be actuarially fair for many cases, reflecting tens of millions of insured acres, which implies sub-optimal producer risk mitigation and inequitable expenditures for producers and taxpayers.

Due to the low crop insurance participation by grain growers in the Pacific Northwest, the performance of insurance programs and the futures market is assessed in this area. Revenue insurance, combined with the futures and government programs, is identified as the optimal risk management portfolio. Although yield risk level, decision maker’s risk preference, and actuarial fairness of premiums can all affect farmers’ choices, the current subsidy policy is most influential. The varying subsidy levels induce farmers’ subsidy‐seeking incentive and suppress the risk‐reducing incentive. There is little diversification effect from growing two crops in the rotation instead of one.

Moral hazard is a concept that is central to risk and insurance management. It refers to change in economic behavior when individuals are protected or insured against certain risks and losses whose costs are borne by another party. It asserts that the presence of an insurance contract increases the probability of a claim and the size of a claim. Through the US Affordable Care Act (ACA) of 2010, this study seeks to examine the validity and relevance of moral hazard in health care reform and determine how welfare losses or inefficiencies could be mitigated.

This study is divided into three sections. The first contrasts conventional moral hazard from an emerging or alternative theory. The second analyzes moral hazard in terms of the evolution, organization, management, and marketing of health insurance in the USA. The third explains why and how salient reform measures under the ACA might induce health care consumption and production in ways that could either promote or restrict personal health and safety as well as social welfare maximization.

Insurance generally induces health care (over) consumption. However, not every additional consumption, with or without adverse selection, can be considered wasteful or risky, even if it might cost insurers more in the short run. Moral hazard can generate welfare and equity gains. These gains might vary depending on which ACA provisions, insured population, covered illnesses, treatments, and services, as well as health outcomes are taken into account, and because of the relative ambiguities surrounding definitions of “health.” Actuarial risk models can nonetheless benefit from incorporating welfare and equity gains into their basic assumptions and estimations.

This is the first study which examines the ACA in the context of the new or alternative theory of moral hazard. It suggests that containing inefficient moral hazard, and encouraging its desirable counterpart, are prime challenges in any health care reform initiative, especially as it adapts to the changing demographic and socio-economic characteristics of the insured population and regulatory landscape of health insurance in the USA.

The USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.

This study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.

Results indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.

This paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.

This paper investigates Chinese agricultural insurance agents willingness to offer (WTO) livestock insurance based on the variations of eight main attributes of livestock insurance.

This study implements discrete choice experiments (DCE) with actual insurance agents who design, sell and operate livestock insurance in China. The choice experiment of this study is based on the D-optimal approach, a six-block design, with 15 cards per block and two choices per card. The sample size was 211. Econometrics results are based on conditional and mixed logit models.

The authors find that the subsidy effect is enormous; a one level increase of subsidy leads to 3.166 times higher probability to offer. This subsidy effect is important as it confirms the endogenous structure between price and quantity in insurance offering, where subsidy does not only incentivize demand but also the supply. Another main factor of insurance investigated is the impact of different coverage types on agents' WTO. The authors find that agents prefer mortality insurance the most, followed by revenue insurance and profit insurance, while Index-Based Livestock Insurance (IBLI) is the least preferred to offer. Agents' knowledge about these newer types of insurance supports their WTO as well; thus, proper education is necessary to promote the more advanced types of livestock insurance.

A limitation is that in the presence of COVID 19, and administrative issues at the local level, the sample was not randomly drawn. Nonetheless, the authors believe that there is enough diversity across participants, insurers and provinces and have done sufficient robustness checks to support results and conclusions.

This study provides further validation for the DCE research method that could potentially be applied to different analyses: using choice experiments to study insurers and reveal their preferences, through combinations of various levels of core attributes for insurance products. The findings and contribution are critical to the reform and improvement of livestock insurance in China and for insurance markets more broadly. The authors find that insurers do not place equal weights or values on insurance product attributes and do not view types of insurance equally. In other words, while farmers may hold different preferences about the type of insurance they demand, the results suggest that insurers also hold preferences in the type of insurance they sell.

So far as the authors are aware, this is the first DCE designed around the supply of insurance products with the subjects being insurance agents, marketers and executives.