Douglas Clement has an \”Interview with Amy Finkelstein\” in the September 2015 issue of The Region, which is published by the Minneapolis Federal Reserve. Finkelstein has done a lot of her most prominent work looking at issues of insurance and risk: especially health insurance, but also long-term care insurance, annuities, and others. She\’s a theory-tester: that is, an empirical researcher who works with a keen awareness of what the previous accepted underlying theories might seem to imply. Back in 2012, Finkelstein was awarded the very prestigious John Bates Clark medal, given annually to an \”American economist under the age of forty who is judged to have made the most significant contribution to economic thought and knowledge.\” In the Fall 2012 issue of the Journal of Economic Perspectives (where I labor in the fields as Managing Editor), Jonathan Levin and James Poterba offered an overview of Finkelstein\’s earlier career.
For example, standard models of the economics of insurance suggest that people who know that they are more likely to receive the insurance payout (more likely to get sick, for example) are more likely to seek out generous insurance policies. Sellers of Insurance need to beware this \”adverse selection\” dynamic, as it is called, or they can end up pricing their insurance as if it was for the average person, and then ending up with much higher payouts than expected. But does the evidence support the theory? Finkelstein points out that in a number of studies, those who get the insurance often do not end up receiving greater payouts. A possible reason is that some people are pretty safe risks in part because they are quite risk-averse, so they are more likely to purchase insurance and less likely to use it. Here are some comments from Finkelstein:
Suppose you have people—in health insurance we often refer to them as the “worried well”—who are healthy, so a low-risk type for an insurer, but also risk averse: They’re worried that if something happens, they want coverage. … As a result, people who are low risk, but risk averse, will also demand insurance, just as high-risk people will. And it’s not obvious whether, on net, those with insurance will be higher risk than those without. … We looked at long-term care insurance—which covers nursing homes—and rates of nursing home use. We found that individuals with long-term care insurance were not more likely to go into a nursing home than those without it, as standard adverse selection theory would predict. In fact, they often looked less likely to go into a nursing home. These results held even after controlling for what the insurance company likely knew about the individual, and priced insurance on. … [O]our data gave us a way to detect private information: people’s self-reported beliefs about their chance of going into a nursing home. And we showed that people who think they have a higher chance of going into a nursing home are both more likely to buy long-term care insurance and more likely to go into a nursing home. … That certainly sounds like the standard adverse selection models! … Then we found some examples in the data that we broadly interpreted as proxies for preferences such as risk aversion, and we found that individuals who report being more likely to, for example, get flu shots, or more likely to wear seatbelts, were both more likely to buy long-term care insurance and less likely to subsequently go into a nursing home.
In another prominent line of work. Finkelstein and several co-authors looked at the question of geographic variation in health care costs–that is, the well-known fact that health care utilization and spending per person is much higher in some urban areas and states than in others. They asked the question: What happens if a person relocates from a high-utilization, high-cost area to a low-cost, low utilization area? If one believes that health care decisions are determined by a mixture of patient expectations and what local health care providers think of as \”best practice,\” one might expect the health care usage of those who relocate to gradually trend toward the patterns of their new geographic location. But that\’s not what happens. Finkelstein explains:
\”We … look at people who moved geographically across areas with different patterns of health care utilization (i.e., high-utilization versus low-utilization areas) and whether their health care utilization changed. Originally, we were very focused on this issue of habit formation, which would suggest a very specific conceptual model and econometric specification. … So you would expect, in a model with habit formation, that maybe initially there wouldn’t be much change in your health care utilization. But over time—whether it’s because doctors would be urging you to do less or the people around you were like, “Why go to the doctor when you have a minor pain?”—you would gradually change your behavior toward the new norm.But that’s just not what we see at all. We have about 11 years of data on Medicare beneficiaries and about 500,000 of them who move across geographic areas. When they do, we see a clear, on-impact change: When you move from a high-spending to a low-spending place, or vice versa, you jump about 50 percent of the way to the spending patterns of the new place. But then your behavior doesn’t change any further. … We estimate that about half of the geographic variation in health care utilization reflects something “fixed” about the patient that stays with them when they move, such as their health or their preferences for medical care. And about half of the geographic variation in health care utilization reflects something about the place, such as the beliefs and styles of the doctors there, or the availability of various medical technologies. This gives you a very different perspective on how to think about the geographic variation in health care spending than the prior conventional wisdom that most of the geographic variation in the health care system was due to the supply side—that is, something about the place rather than the patient.
In the last few years, some of Finkelstein\’s most prominent research has been an analysis of data generated by an experiment in the state of Oregon. Back in 2008, the state of Oregon wanted to expand Medicaid coverage to low-income people who wouldn\’t have otherwise been eligible for Medicaid. The state realized that it didn\’t have enough money to offer the expanded health insurance to everyone, so it held a lottery. From an academic research point of view, this decision was a dream come true, because it becomes possible to compare health and life outcomes for two very similar groups–one randomly chosen to receive additional health insurance and one not. Finkelstein and a team of co-authors were on the job. Finkelstein describes some of their findings:
For health care use, we found across the board that Medicaid increases health care use: Hospitalizations, doctor visits, prescription drugs and emergency room use all increased. On the one hand, this is economics 101. Demand curves slope down: When you make something less expensive, people buy more of it. And what health insurance does, by design, is lower the price of health care for the patient. … On the other hand, there were ways in which these results were surprising. For Medicaid, in particular, there’s been a lot of conjecture that while in general, health insurance would increase use of health care, that because Medicaid reimbursement rates to providers are so low, providers wouldn’t want to treat Medicaid patients. … Our findings reject this view. We find compelling evidence from a randomized evaluation that relative to being uninsured, Medicaid does increase use of health care. Another result that some found surprising was on use of the emergency room. There had been claims in policy circles that covering the uninsured with Medicaid might get them out of the emergency room … The hope that ER use would go down comes from the belief that doctor visits are substitutes for the ER, so when the doctor also becomes free, you go to the doctor instead of the emergency room. Maybe this is the case (or maybe it isn’t), but on net, our results show any substitution for the doctor that may exist is just not outweighed by the direct effect of making the emergency room free. On net, Medicaid increases use of the emergency room, at least in the first one to two years of coverage we are able to look at.
A variety of other findings have emerged from this research, which is ongoing. In the Oregon data, the additional health insurance reduced financial risk for households, and perhaps not coincidentally, also led to improvements in mental health status (measured both by self-reported mental health and by the proportion diagnosed with depression). In terms of measures of physical health, Finkelstein reports, \”we did not detect statistically significant effects on the physical health measures we studied: blood sugar, cholesterol and blood pressure.\”
The expansion of Medicaid in Oregon clearly brought at least some benefits to the previously uninsured. But what the cost to the state worth the benefits to the individuals? Finkelstein and a couple of co-authors tried to model what the insurance was worth to those receiving it. They found:
[O]ur central estimate is that the value of Medicaid to a recipient is about 20 to 40 cents per dollar of government expenditures. … The other key finding is that the nominally “uninsured” are not really completely uninsured. We find that, on average, the uninsured pay only about 20 cents on the dollar for their medical care. This has two important implications. First, it’s a huge force working directly to lower the value of Medicaid to recipients; they already have substantial implicit insurance. … Second and, crucially, the fact that the uninsured have a large amount of implicit insurance is also a force saying that a lot of spending on Medicaid is not going directly to the recipients; it’s going to a set of people who, for want of a better term, we refer to as “external parties.” They’re whoever was paying for that other 80 cents on the dollar.