In the case of life insurance, if you have a terminal illness or have made lifestyle choices that increase your mortality risk, then that is likely to be private information. Because you are higher risk, you should pay a higher premium. However, because the life insurance company can't tell the high-risk and low-risk people apart, that leads to a pooling equilibrium. The life insurance company must assume that everyone is high risk, and raise premiums as a result.
So, if there is adverse selection in the life insurance market, we should expect to see that people with life insurance are more likely to die than people without life insurance. Which leads me to this recent paper in the journal Economics Letters (ungated here) by Timothy Harris and Aaron Yelowitz (both of University of Kentucky). Using data from the 1990 and 1991 panels of the Survey of Income and Program Participation in the U.S., combined with mortality data from the Social Security Administration's Master Beneficiary Record, Harris and Yelowitz find:
...no significant evidence of adverse selection. In virtually all specifications, those who have higher mortality are no more likely to hold life insurance.In fact, the authors find some evidence of advantageous selection (the opposite of adverse selection - in this case, where lower risk individuals are more likely to have life insurance). But before you think this means that this proves a lack of adverse selection, consider this. Markets, particularly insurance markets (including life insurance) can be pretty adept (and often sophisticated) in mitigating the problems of adverse selection. In the case of life insurance, simply comparing those with and without a life insurance policy in terms of mortality doesn't tell the full story about adverse selection. Insurers spend some effort in screening applicants for life insurance, including questions about medical history, incidence of disease in your parents, etc. before they make a decision about offering insurance (and what the premium will be). The most risky applicants will be eliminated during this screening phase. Indeed, the authors note this themselves:
So, if we had no underwriting or screening processes, maybe we would observe adverse selection in the life insurance market. Or maybe not. Simply looking at mortality after an insurance contract is negotiated in the absence of screening would not be enough, because of potential moral hazard problems. Moral hazard arises when, after an agreement is made, one of the parties has an incentive to change their behaviour (usually to take advantage of the terms of the agreement) in a way that harms the other party. In the case of life insurance, once a person has life insurance their incentives change slightly - they may engage in more risky behaviour safe in the knowledge that their family will be provided for in the case of a skydiving accident, for instance. So, we might expect to see higher mortality among the insured than the non-insured not because of adverse selection, but because of moral hazard.Although the empirical findings are consistent with the concept of advantageous selection, it is important to recognize the importance of underwriting in the life insurance market. All existing empirical analyses examine life insurance holdings, not applications. Insurers ask extensive questions and require medical exams prior to approval of an application. These institutional features suggest caution before claiming that applicants are advantageously selected; rather the underwriting process potentially screens out high-risk applicants who would otherwise obtain life insurance.
The authors are correct in asserting that we should look at applications for life insurance. Adverse selection is a problem of pre-contractual opportunism after all. To assess whether adverse selection exists in this market, the best approach would be to look at applications and medical histories and risk factors for life-threatening diseases of applicants, and compare with non-applicants. While looking at actual outcomes (in terms of mortality data) is somewhat appealing, it runs into issues of whether the observed difference arises because of adverse selection (the applicant was at higher risk before they obtained insurance), moral hazard (the applicant became more risky to insure after they obtained insurance), or some combination of the two.