Adverse Selection

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Many individuals are uninsureable. Their pre-existing conditions indicate that they are so risky either: i) no insurance company would cover them or ii) the premiums would be so high that the individual could not afford them. To insure some of these people, many states have set up high-risk health insurance pools (HRP). Currently, all these pools operate at a loss. This is not surprising; if states could profit from insuring high-risk individuals, than the private market could certainly as well and thus there would be no need for HRPs.

Today I will review some HRP statistics from a 2009 GAO report.

Spending

  • Total claims paid by HRPs in 2008 were about $1.9 billion, accounting for almost 95 percent of total HRP expenditures. The average claims per enrolled individual totaled $9,437 in 2008, an increase of about 39 percent since 2003.

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In Germany, poor and middle class individuals must use public insurance, but well-off Germans can choose between using public and private insurance.

“In Germany, about 90% of the population is publicly insured (Colombo & Tapay, 2004). Buying public insurance is mandatory for dependent employees with a regular employment contract as long as their income does not exceed the so-called compulsory insurance threshold. The public insurance premium equals a certain percentage (nowadays about 15% that are equally shared between the employer and the employee) of gross income up to the so-called contribution ceiling, and equal to it thereafter.

Why would someone want private insurance? Coverage is universal in the public system and the deductibles and co-payments are limited. Here’s why”

Contributions for private health insurance are mainly based on health and age, so buying private insurance is especially attractive for young individuals. As a consequence of this, and because of the fact that private insurers are allowed to reject individuals, the risk pool of the private insurers is much better than in the public system…Privately insured individuals can buy better care, e.g. treatment by the head doctor in a hospital or a single room in a hospital, but this comes at a higher price.  Deductibles and co-payments are much more common, and many insurers offer a rebate if an individual did not use medical services in the past calendar year.”

In fact, a paper by Hullegie and Klein (2011) finds that individuals with private insurance are much less likely visit a doctor. This is likely due to adverse selection although moral hazard may also play a role since private insurance plans have higher copayments and deductibles.

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Deciding whether to get tested for genetic diseases is a choice many people will face in the coming years.  By knowing whether or not you are more likely to develop a given disease, you may be able to change your health habits or seek earlier medical treatment.  In addition, genetic testing provides additional knowledge useful in deciding whether or not to purchase long term care insurance.  A paper on Genetic Adverse Selection reveals the following:

…the long-term care insurance ownership rate among those at genetic risk for developing [Huntingon's Disease] (50 percent) is five times the rate of ownership in the general population (10 percent). Furthermore, among individuals whose genetic testing shows that they are 100 percent at risk to develop HD, 50 to 75 percent own insurance…

As more individuals gain private information about the likelihood that they will require costly long-term care, adverse selection may threaten the viability of private long-term care insurance, at least in its present form.

Emily Oster, Ira Shoulson, Kimberly Quaid, E. Ray Dorsey (2009) “Genetic Adverse Selection: Evidence from Long-Term Care Insurance and Huntington Disease,” NBER Working Paper 15326.

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Cohen and Siegelman (2009) document empirical research on adverse selection in 5 markets: i) automobile insurance, ii) annuities and life insurance, iii) long term care, iv) crop insurance, and v) health insurance.  The presence of adverse selection varies not only across markets, but also within markets depending on the product sold and the type of individuals who buy the product.

Detailed Summary

Adverse selection occurs when high risk individuals are the ones more likely to purchase insurance.  However, measuring adverse selection may not be asstraightforward empirically as it seems.  Typically, economists conclude that there is adverse selection in a market if a correlation exists between risk levels and whether or not the individual buys insurance.

If adverse selection is at work, however, this correlation may not necessarily show up in the data.  For instance, high risk individuals may be risk loving while low risk individuals are risk averse.  Thus, adverse selection may be occurring, but due to the correlation of risk preferences, this may not be born out in the data.  Further, a correlation between risk and insurance status does not necessarily imply the existence of adverse selection.  In health insurance markets, insured individuals may incur more cost due to moral hazard.  If the insured and uninsured have equal risk levels, the person with health insurance may still incur more medical costs, because these services are generally free to them.

Further, detecting adverse selection econometrically, is not simple as well.  The researcher must have full access to the insurer’s information to reliably estimate the level of private information in a market.  Further, all accidents do not result in claims.  Individuals with high deductible health insurance may fall ill, but not go to the doctor.  Drivers who get in fender benders may not report the incident.  There may also be unobservable differences among policyholders.  Finally, one may use a variety of econometric techniques to estimate the presence of adverse selection.  Many researchers use a simple OLS structures as follows:
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“…individuals who carry the [Huntington Disease] genetic mutation are up to 5 times as likely as the general population to own long-term care insurance…relatively limited increases in genetic information may threaten the viability of private long-term care insurance.”

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Adverse Selection.

The firm wants to attract healthy individuals at all ages.  Gym membership may be observable, but it is difficult to observe frequency of gym visits.  By advertising at 24-hour Fitness, Kaiser Permanente’s ads have the strongest effect on those who go to the gym most frequently.  If  fitness enthusiasts decide to enroll at Kaiser, the average costs per member will decrease.  The cost decrease is not due to a more efficient health care system, but because of the healthier insured population.  Thus, Kaiser will be able to either 1) reduce premiums to increase market share or 2) increase profits.

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Why do people change health plans? Of course, the most obvious reasons are moving, changing jobs, or qualifying for Medicare. However, some people change health plans even when they remain in the same job. Why is this? A working paper by Cutler, Lincoln and Zeckhauser (2009) give the following explanations:

  • Adverse selection, the movement of the less healthy to more generous plans;
  • Adverse retention, the tendency for people to stay where they are when they get sick;
  • Aging in place, where lack of all movement makes plans with initially older enrollees increase in cost over time.

The authors use data 1994-2004 data from Massachusetts state workers and from workers enrolled in the state’s health insurance system, the Group Insurance Commission. They find that aging in place and adverse selection are both quantitatively important.

Miller-McCune also has a nice article on this research.

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Can Markets cure healthcare?

Is adverse selection a problem?

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For individuals who have recently lost their job, Carolyn’s Blog advises them how to get health insurance coverage.

Unless you have a pre-existing condition you should only stick with COBRA until you find a private health insurance plan.  Believe it or not, if you go with a High Deductible Health Care Plan (HDHP) for a middle aged guy of 35, private health insurance can be around $75 a month — even with such well known companies as Humana and Blue Cross Blue Sheild when you live in the city of Chicago (very expensive health insurance here!)

Healthy people sort to the less generous HDHP, sick people choose to the more generous COBRA.

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One of the biggest news stories this year is the collapse of the subprime mortgage lending market. Why did this happen? How much do we really know about subprime lending?

A working paper by William Adams, Liran Einav and Jonathan Levin examines the subprime market for automobile loans. The authors find that liquidity constraints are a major force in shaping the subprime loan market. They find that car loans spike in January through March. Why is this? Poor individuals often take out a loan against their tax rebates. These rebates can be very high–up to $4500–and these individuals will use these rebates to help finance a car purchase.

Finance charges for these loans are very high. Interest rates usually surpass 20% and often at the state-mandated 30% interest cap. A $11,000 loan paid off over 42 months would incur $6000 of finance charges.

Yet it seems that loan demand within the subprime market is not very responsive to interest rates. It is, however, much more responsive to the amount of the down payment.

We estimate that a 100 dollar increase in the minimum down payment reduces the probability that an applicant will purchase by 0.0301, while a 100 dollar increase in the car price reduces the purchase probability by only 0.0034. That is, a 100 dollar increase in the minimum down payment has the same e¤ect as a 900 dollar increase in car price. This can still be explained in the absence of liquidity constraints, but it requires a much higher annual discount rate of 427 percent.

The authors found evidence of both moral hazard and adverse selection in the subprime market. Moral Hazard means that individuals are more likely to default on large loans. Adverse selection occurs when high risk borrowers desire large loans. The authors find that when a loan amount increases $1000, the default rate increases 24%. Sixteen percentage points is due to moral hazard and the rest is due to adverse selection.

Are there any ways to mitigate these market failure problems? The authors find that “risk-based minimum payments play a substantial role in mitigating adverse selection in financing choices.” These factors lead to the observation that “in practice, observably risky buyers end up with smaller rather than larger loans because they face higher down payment requirements.” Modern credit scores give the lender more information regarding the credit-worthiness of the borrower and help to match high-risk borrowers with smaller loans.

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