자료 1: Adverse selection (explained in The Economist's terms )
When you do business with people you would be better off avoiding. This is one of two main sorts of market failure often associated with insurance. The other is moral hazard. Adverse selection can be a problem when there is asymmetric information between the seller of insurance and the buyer; in particular, insurance will often not be profitable when buyers have better information about their risk of claiming than does the seller. Ideally, insurance premiums should be set according to the risk of a randomly selected person in the insured slice of the population (55-year-old male smokers, say). In practice, this means the average risk of that group. When there is adverse selection, people who know they have a higher risk of claiming than the average of the group will buy the insurance, whereas those who have a below-average risk may decide it is too expensive to be worth buying. In this case, premiums set according to the average risk will not be sufficient to cover the claims that eventually arise, because among the people who have bought the policy more will have above-average risk than below-average risk. Putting up the premium will not solve this problem, for as the premium rises the insurance policy will become unattractive to more of the people who know they have a lower risk of claiming. One way to reduce adverse selection is to make the purchase of insurance compulsory, so that those for whom insurance priced for average risk is unattractive are not able to opt out.
자료 2: a course material in some college:
Adverse selection, anti-selection, or negative selection is a term used in economics, insurance, statistics, and risk management. It refers to a market process in which "bad" results occur when buyers and sellers have asymmetric information (i.e. access to different information): the "bad" products or services are more likely to be selected. A bank that sets one price for all its checking 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 with signaling games and screening games.Example: insuranceThe term adverse selection was originally used in insurance. It describes a situation where an individual's demand for insurance (either the propensity to buy insurance, or the quantity purchased, or both) is positively correlated with the individual's risk of loss (e.g. higher risks buy more insurance), and the insurer is unable to allow for this correlation in the price of insurance. This may be because of private information known only to the individual (information asymmetry), or because of regulations or social norms which prevent the insurer from using certain categories of known information to set prices (e.g. the insurer may be prohibited from using information such as gender or ethnic origin or genetic test results). The latter scenario is sometimes referred to as 'regulatory adverse selection'.
The potentially 'adverse' nature of this phenomenon can be illustrated by the link between smoking status and mortality. Non-smokers, on average, are more likely to live longer, while smokers, on average, are more likely to die younger. If insurers do not vary prices for life insurance according to smoking status, life insurance will be a better buy for smokers than for non-smokers. So smokers may be more likely to buy insurance, or may tend to buy larger amounts, than non-smokers. The average mortality of the combined policyholder group will be higher than the average mortality of the general population. From the insurer's viewpoint, the higher mortality of the group which 'selects' to buy insurance is 'adverse'. The insurer raises the price of insurance accordingly. As a consequence, non-smokers may be less likely to buy insurance (or may buy smaller amounts) than if they could buy at a lower price to reflect their lower risk. The reduction in insurance purchase by non-smokers is also 'adverse' from the insurer's viewpoint, and perhaps also from a public policy viewpoint.
Furthermore, if there is a range of increasing risk categories in the population, the increase in the insurance price due to adverse selection may lead the lowest remaining risks to cancel or not renew their insurance. This leads to a further increase in price, and hence the lowest remaining risks cancel their insurance, leading to a further increase in price, and so on. Eventually this 'adverse selection spiral' might in theory lead to the collapse of the insurance market.
To counter the effects of adverse selection, insurers (to the extent that laws permit) 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. 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.
Whilst 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, auto insurance, and health insurance. On the other hand, "positive" test results for adverse selection have been reported in health insurance, long-term care insurance and annuity markets. These "positive" results tend to be based on demonstrating more subtle relationships between risk and purchasing behavior (e.g. 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.
One reason why adverse selection may be muted in practice may be that insurers' underwriting is largely effective. Another possible reason is negative correlation between risk aversion (e.g. insurance purchasers) and risk level (e.g. level of observed claims) in the population: if risk aversion is higher amongst lower risk customers, adverse selection can be reduced or even reversed, leading to 'propitious' or 'advantageous' selection. For example, there is evidence that smokers are more willing to do risky jobs than non-smokers, 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.
In studies of health insurance, an individual mandate requiring 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. Mandates, like all insurance, increase moral hazard.
Death spiral (insurance)
Market for Lemons
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