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This chapter summarizes the major determinants of health insurance coverage rates among young adults. Socioeconomic status, demographics, actual and perceived health status, perceived value, and perceived need are all examined in order to determine what the literature reveals regarding each variable and how each variable impacts a young adult's decision to purchase health insurance. Results indicate that socioeconomic status, demographics, perceived value, and perceived need were the most significant determinates of health insurance status of young adults. A conceptual framework is also examined and used to illustrate theoretical implications. Managerial implications for marketing health plans to young adults are also addressed. Finally, policy implications concerning the new Patient Protection and Affordable Care Act are addressed.

This chapter describes how to do variable-based analysis of cases of two-person conversations. The chapter makes use of the same data that Chapter 9 describes. Here, the study examines 40 transactions between actual insurance salespersons (n = 3) and prospective clients (n = 57) interacting in field settings. The study describes conversations among purchase behavior and the frequency of key orientation and bargaining statements made by the salespersons and customers. The findings support the high value in studying social factors, influence attempts, and situation variables in constructing a general conceptualization of exchange relationships.

Purpose – To examine the effects of health insurance types on the use of prescribed medication that treat patients with hypertension, diabetes, and asthma. The study distinguishes between individuals with private health maintenance organization (HMO) plans and private non-HMO plans. The study also distinguishes between people with health insurance and drug coverage and people with health insurance and no drug coverage.

Methods – Joint discrete factor models are estimated to control for endogeneity of each type of coverage.

Findings – The main findings suggest that the effect of health insurance varies across patients with different conditions. The strongest and most significant effect is evident among patients with hypertension while the weakest and least significant is among patients with asthma. These findings suggest that patients with asymptomatic conditions are more likely to exhibit moral hazard than patients with conditions that impose immediate impairment. Additional results suggest that, relative to the uninsured and people with health insurance but no drug coverage, patients with drug coverage are more likely to initiate drug therapy and to consume more medications.

Originality – The results of the study indicate that moral hazard of drug utilization is condition specific. The variation in “silence” of conditions’ symptoms could be a key reason for difference in insurance effects among patients with hypertension, diabetes, and asthma.

This paper analyzes the effect of dental insurance on utilization of general dentist services by adult US population aged from 25 to 64 years using the ordered probit model with endogenous selection. Our econometric framework accommodates endogeneity of insurance and the ordered nature of the measure of dental utilization. The study finds strong evidence of endogeneity of dental insurance to utilization and identifies interesting patterns of nonlinear dependencies between the dental insurance status and individual's age and income. The calculated average treatment effect supports the claim of adverse selection into the treated (insured) state and indicates a strong positive incentives effect of dental insurance.

Employer-provided benefits are a large and growing share of compensation costs. In this paper, I consider three factors that can affect the value created by employer-sponsored benefits. First, firms have a comparative advantage (e.g., due to scale economies or tax treatment) in purchasing relative to employees. This advantage can vary across firms based on size and other differences in cost structure. Second, employees differ in their valuations of benefits and it is costly for workers to match with firms that offer the benefits they value. Finally, some benefits can reduce the marginal cost to an employee of extra working time. I develop a simple model that integrates these factors. I then generate empirical implications of the model and use data from the National Longitudinal Survey of Youth to test these implications. I examine access to employer-provided meals, child care, dental insurance, and health insurance. I also study how benefits are grouped together and differences between benefits packages at for-profit, not-for-profit, and government employers. The empirical analysis provides evidence consistent with all three factors in the model contributing to firms’ decisions about which benefits to offer.

One of the fundamental tasks in optimal insurance design is mitigating the moral hazard effects inherent in insurance mechanisms. Empirically, relatively little is known about how individual-level time preferences affect selection of insurance options. We use several waves of the Health and Retirement Survey to explore the relationship between revealed time preferences at the individual level and the selection of insurance options for both the under-age-65 population and the Medicare-eligible population. Our results suggest that time preferences are not likely to be fixed across the life cycle, and that they appear to be important predictors of health insurance decisions.

Purpose: To analyse the insurance market breakthroughs through ‘Big Data’ and the possibility of new techniques of services provided, creating access for information gathering and fraud detection. This can contribute to improved risk management processes and mitigation strategies referred to as ‘InsurTech’.

Methodology: We catalogue the technique which is especially useful and being evaluated as having the ability to bring innovations to the insurance business. In doing this, we reveal which marketplaces actively participate in start-ups and how insurers engage in them and present them, highlighting the impact of blockchain technology, ride services, robo-advice, and data analysis on the insurance industry.

Findings: Findings show that because emerging economies have fewer organisation needs to ensure the distribution model, technology and research may significantly influence such areas. Nonetheless, whether industrialised or emergent, relevant legislative inspections should be carried out to protect subscribers’ welfare.

Practical implication: Since ‘Big Data’ impacts insurers’ constant monitoring of business risks and corporate governance, an overview of how information is harnessed should be carefully studied. Moreover, it is essential to study the handling of algorithms to guarantee that the expectations are reasonable and that unforeseen effects are avoided to the greatest extent feasible, and regulators have a mechanism for engaging in this review.

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.

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

Purpose – Long-term care (LTC) services assist people with limitations in the ability to perform activities of daily living (ADLs) as a result of chronic illness or disabilities. We discuss possible behavioral explanations for the under-purchasing of LTC insurance, as well as the current state of knowledge on the neural mechanisms behind these behavioral factors.

Findings/approach – Ideas from behavioral economics are discussed, including risk-seeking over losses, ambiguity-preferring over losses, hyperbolic discounting, and the effect of the aging process on the underlying neural mechanisms supporting these decisions. We further emphasize the role of age, as aging is a highly heterogeneous process. It is associated with changes in both brain tissue as well as cognitive abilities, and both are characterized by large individual differences. Therefore, understanding the neural mechanisms is vital to understanding this heterogeneity and identifying possible methods of interventions.

Research implications – LTC financing and insurance is a looming issue in the next 10–20 years. It is important to understand the process by which people make decisions about LTC insurance, heterogeneity in decision processes across individuals, and how these decisions interact with changes in policy and private LTC insurance markets.

Originality/value of the chapter – By providing an overview of the current state of knowledge in behavioral economics of LTC insurance and the neuroscience of aging, this chapter provides some new directions in the emerging area of neuroeconomics of aging.