Adverse selection

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Adverse selection, anti-selection, or negative selection is a term used in economics, insurance, risk management, and statistics. It refers to a market process in which undesired results occur when buyers and sellers have asymmetric information (access to different information); the "bad" customers are more likely to apply for the service. For example, a bank that sets one price for all of its checking account (current account) customers runs the risk of being adversely selected against by its low-balance, high-activity (and hence least profitable) customers. Two ways to model adverse selection are to employ signaling games and screening games.


The term "adverse selection" was originally used in insurance. It describes a situation where an individual's demand for insurance (the propensity to buy insurance and the quantity purchased) is positively correlated with the individual's risk of loss (higher risks buy more insurance), and the insurer cannot allow for this additional risk in the price of the insurance.[1] This may be because of private information known only to the individual (information asymmetry), or because of regulations, social norms or marketing considerations which prevent the insurer from using certain categories of known information to set prices (for example, the insurer may be prohibited from using such information as gender, ethnic origin, genetic test results, or pre-existing medical conditions). This is sometimes referred to as "regulatory adverse selection".[2]

This can be illustrated by the link between smoking status and mortality. Non-smokers, on average, live longer than smokers. If a life insurance company does not vary prices according to smoking status, its life insurance will be a better buy for smokers than for non-smokers. So smokers may be more likely to buy insurance from that company, or may tend to buy larger amounts than non-smokers, thereby raising the average mortality of the combined policyholder group above that of the insured population in general, and leading to losses for the company and/or higher prices for all that company's customers.

Furthermore, these higher prices may lead the "good risks" (healthy, non-smoking customers) to cancel or not renew their insurance. This promotes a further increase in price: a vicious circle, which might, in theory, lead to the collapse of the insurance market.[3]

To counter the effects of adverse selection, insurers (as far as laws permit and it is economic to do so) ask a range of questions and may request medical or other reports on individuals who apply to buy insurance, so that the price quoted can be varied accordingly, and any unreasonably high or unpredictable risks rejected altogether. This risk selection process is known as underwriting. In many countries, insurance law incorporates an "utmost good faith" or uberrima fides doctrine, which requires potential customers to answer any underwriting questions asked by the insurer fully and honestly; if they fail to do this, the insurer may later refuse to pay claims.

While adverse selection in theory seems an obvious and inevitable consequence of economic incentives, empirical evidence is mixed. Several studies investigating correlations between risk and insurance purchase have failed to show the predicted positive correlation for life insurance,[4] auto insurance,[5][6] and health insurance.[7] On the other hand, "positive" test results for adverse selection have been reported in health insurance,[8] long-term care insurance,[9] and annuity markets.[10] These "positive" results tend to be based on demonstrating more subtle relationships between risk and purchasing behavior (such as between mortality and whether the customer chooses a life annuity which is fixed or inflation-linked), rather than simple correlations of risk and quantity purchased.[citation needed]

One reason why adverse selection might be muted in practice could be that insurers' underwriting is largely effective. Another possible reason is the negative correlation between risk aversion (such as the willingness to purchase insurance) and risk level (estimated beforehand based on hindsight observation of the occurrence rate for other observed claims) in the population: if risk aversion is higher among lower risk customers, such that persons less likely to engage in risk-increasing behavior are more likely to engage in risk-decreasing behavior (to take affirmative steps to reduce risk), adverse selection can be reduced or even reversed, leading to "propitious" or "advantageous" selection.[11][12]

For example, there is evidence that smokers are more willing to do risky jobs than non-smokers,[13] and this greater willingness to accept risk might reduce insurance purchase by smokers. From a public policy viewpoint, some adverse selection can also be advantageous because it may lead to a higher fraction of total losses for the whole population being covered by insurance than if there were no adverse selection.[14]

In studies of health insurance, an individual mandate that requires people to either purchase plans or face a penalty is cited as a way out of the adverse selection problem by broadening the risk pool.[15]

See also[edit]


  1. ^ Chandler, Seth J. "Adverse Selection". The Wolfram Demonstrations Project. 
  2. ^ Polborn, M. K.; Hoy, M.; Sadanand, A. (2006). "Advantageous Effects of Regulatory Adverse Selection in the Life Insurance Market". Economic Journal 116 (508): 327–354. doi:10.1111/j.1468-0297.2006.01059.x. 
  3. ^ Cutler, David; Reber, Sarah (1998). "PAYING FOR HEALTH INSURANCE: THE TRADE-OFF BETWEEN COMPETITION AND ADVERSE SELECTION". The Quarterly Journal of Economics 113 (2): 433–466. doi:10.1162/003355398555649. 
  4. ^ Cawley, J.; Philipson, T. (1999). "An Empirical Examination of Barriers to Trade in Insurance". American Economic Review 89 (4): 827–846. doi:10.1257/aer.89.4.827. JSTOR 117161. 
  5. ^ Chiappori, P. A.; Salanie, B. (2000). "Testing for Asymmetric Information in Insurance Markets". Journal of Political Economy 108 (1): 56–78. doi:10.1086/262111. 
  6. ^ Dionne, G.; Gouriéroux, C.; Vanasse, C. (2001). "Testing for Evidence of Adverse Selection in the Automobile Insurance Market: A Comment". Journal of Political Economy 109 (2): 444–453. doi:10.1086/319557. 
  7. ^ Cardon, J. H.; Hendel, I. (2001). "Asymmetric information in health insurance: evidence from the National Medical Expenditure Survey". Rand Journal of Economics 32 (3): 408–427. JSTOR 2696362. 
  8. ^ Cutler, David M.; Zeckhauser, Richard J. (1998). "Adverse Selection in Health Insurance". Forum for Health Economics & Policy 1: Article 2. doi:10.2202/1558-9544.1056. 
  9. ^ Finkelstein, A.; McGarry, K. (2006). "Multiple dimensions of private information: evidence from the long-term care insurance market". American Economic Review 96 (4): 938–958. doi:10.1257/aer.96.4.938. JSTOR 30034325. PMC 3022330. PMID 21253439. 
  10. ^ Finkelstein, A.; Poterba, J. (2004). "Adverse selection in insurance markets: policyholder evidence from the UK annuity market". Journal of Political Economy 112 (1): 183–208. doi:10.1086/379936. 
  11. ^ Hemenway, D. (1990). "Propitious selection". Quarterly Journal of Economics 105 (4): 1063–1069. JSTOR 2937886. 
  12. ^ De Meza, D.; Webb, D. C. (2001). "Advantageous selection in insurance markets". RAND Journal of Economics 32 (2): 249–262. JSTOR 2696408. 
  13. ^ Viscusi, W. K.; Hersch, J. (2001). "Cigarette smokers as job risk takers". Review of Economics and Statistics 83 (2): 269–280. doi:10.1162/00346530151143806. 
  14. ^ Thomas, R. G. (2008). "Loss coverage as a public policy objective for risk classification schemes". Journal of Risk & Insurance 75 (4): 997–1018. doi:10.1111/j.1539-6975.2008.00294.x. 
  15. ^ Blumberg, Linda J.; Holahan, John (2009). "The Individual Mandate — An Affordable and Fair Approach to Achieving Universal Coverage". N Engl J Med 361 (1): 6–7. doi:10.1056/NEJMp0904729. PMID 19535794. 

External links[edit]

  • The Economist: Research Tools, Adverse Selection [1]

Further reading[edit]

  1. Bartram, Söhnke M.; Fehle, Frank R.; Shrider, David (May 2008). "Does Adverse Selection Affect Bid-Ask Spreads for Options?". Journal of Futures Markets 28 (5): 417–437. doi:10.1002/fut.20316.