The Welfare Cost of Asymmetric Information: Evidence from the U.K. Annuity Market

Abstract

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.

Contract Pricing in Consumer Credit Markets

“…This market is attractive for studying pricing and contract design in the presence of informational 1 See also Einav, Finkelstein and Schrimpf (2007) for a related application to annuity demand, and Chiappori and Salanie (2000) and Finkelstein and McGarry (2006) as representative of a closely-related literature on "testing for asymmetric information. "…”

Estimating Risk Preferences in the Field

“…Another approach has been to exogenously impose risk preferences, as opposed to estimating risk preferences within a larger model. See, for example, Einav, Finkelstein, and Schrimpf (2010), who use external data to calibrate the values for risk aversion (as well as other parameters that would only be identified via functional form assumptions in their model).…”

Evidence of adverse selection in automobile insurance market: A seemingly unrelated probit modelling

“…The impact of adverse selection on welfare has been discussed sufficiently by Rothschild and Stiglitz (1976). These two original studies have been extensively discussed and extended, See, for example, Wilson (1977), Salanié (1997), Spence (1978), Dionne, Doherty, and Fombaron (2001), and more recently, Einav, Finkelstein, and Levin (2010), Einav, Finkelstein, and Schrimpf (2010), and Handel (2013).…”