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Much of the extensive empirical literature on insurance markets has focused on whether adverse selection can be detected. Once detected, however, there has been little attempt to quantify its importance. We start by showing theoretically that the efficiency cost of adverse selection cannot be inferred from reduced form evidence of how "adversely selected" an insurance market appears to be. Instead, an explicit model of insurance contract choice is required. We develop and estimate such a model in the context of the U.K. annuity market. The model allows for private information about risk type (mortality) as well as heterogeneity in preferences over different contract options. We focus on the choice of length of guarantee among individuals who are required to buy annuities. The results suggest that asymmetric information along the guarantee margin reduces welfare relative to a first-best, symmetric information benchmark by about £127 million per year, or about 2 percent of annual premiums. We also find that government mandates, the canonical solution to adverse selection problems, do not necessarily improve on the asymmetric information equilibrium. Depending on the contract mandated, mandates could reduce welfare by as much as £107 million annually, or increase it by as much as £127 million. Since determining which mandates would be welfare improving is empirically difficult, our findings suggest that achieving welfare gains through mandatory social insurance may be harder in practice than simple theory may suggest.

The observed seasonality of box‐office revenues reflects both seasonality in underlying demand for movies and seasonality in the number and quality of available movies. I separately identify these aspects by estimating weekly demand for movies, using movie fixed effects, a long panel of movies' weekly revenues, and restrictions on their decay pattern. I find that the estimated seasonality in underlying demand is much smaller and slightly different from the observed seasonality of sales. The biggest movies are released at times when demand is highest, amplifying the underlying seasonality. Price rigidities in the industry may facilitate this amplification effect.

Government intervention in insurance markets is ubiquitous and the theoretical basis for such intervention, based on classic work from the 1970s, has been the problem of adverse selection. Over the last decade, empirical work on selection in insurance markets has gained considerable momentum. This research finds that adverse selection exists in some insurance markets but not in others. And it has uncovered examples of markets that exhibit "advantageous selection"—a phenomenon not considered by the original theory, and one that has different consequences for equilibrium insurance allocation and optimal public policy than the classical case of adverse selection. Advantageous selection arises when the individuals who are willing to pay the most for insurance are those who are the most risk averse (and so have the lowest expected cost). Indeed, it is natural to think that in many instances individuals who value insurance more may also take action to lower their expected costs: drive more carefully, invest in preventive health care, and so on. Researchers have taken steps toward estimating the welfare consequences of detected selection and of potential public policy interventions. In this essay, we present a graphical framework for analyzing both theoretical and empirical work on selection in insurance markets. This graphical approach provides both a useful and intuitive depiction of the basic theory of selection and its implications for welfare and public policy, as well as a lens through which one can understand the ideas and limitations of existing empirical work on this topic.

We analyze a dynamic model of quantity competition, where firms continuously adjust their quantity targets, but incur convex adjustment costs when they do so. Quantity targets serve as a partial commitment device and, in equilibrium, follow a hump‐shaped pattern. The final equilibrium is more competitive than in the static analog. We then use data on monthly production targets of the Big Three U.S. auto manufacturers and show a similar empirical hump‐shaped dynamic pattern. Taken together, this suggests that strategic considerations may play a role in setting auto production schedules, and that static models may misestimate the industry's competitiveness.

We develop a structural econometric model to estimate risk preferences from data on deductible choices in auto insurance contracts. We account for adverse selection by modeling unobserved heterogeneity in both risk (claim rate) and risk aversion. We find large and skewed heterogeneity in risk attitudes. In addition, women are more risk averse than men, risk aversion exhibits a U-shape with respect to age, and proxies for income and wealth are positively associated with absolute risk aversion. Finally, unobserved heterogeneity in risk aversion is greater than that of risk, and, as we illustrate, has important implications for insurance pricing. (JEL D81, G22)