Myth and Measurement — The Case of Medical Bankruptcies (with Carlos Dobkin, Amy Finkelstein, and Matthew Notowidigdo) New England Journal of Medicine 378(12), March 2018: 1076-1078.
Press: New York Times, Associated Press, Newsweek, Washington Post
The Economic Consequences of Hospital Admissions (with Carlos Dobkin, Amy Finkelstein, and Matthew Notowidigdo) American Economic Review 108(2), February 2018: 308–352. Online Appendix.
Abstract: We use an event study approach to examine the economic consequences of hospital admissions for adults in two datasets: survey data from the Health and Retirement Study, and hospitalization data linked to credit reports. For non-elderly adults with health insurance, hospital admissions increase out-of-pocket medical spending, unpaid medical bills, and bankruptcy, and reduce earnings, income, access to credit, and consumer borrowing. The earnings decline is substantial compared to the out-of-pocket spending increase, and is minimally insured prior to age-eligibility for Social Security Retirement Income. Relative to the insured non-elderly, the uninsured non-elderly experience much larger increases in unpaid medical bills and bankruptcy rates following a hospital admission. Hospital admissions trigger fewer than 5 percent of all bankruptcies in our sample.
Press: Washington Post (Wonkblog), New York Times
Beyond Statistics: The Economic Content of Risk Scores (with Liran Einav, Amy Finkelstein, and Paul Schrimpf) American Economic Journal: Applied Economics 8(2), April 2016: 195-224.
Abstract: In recent years, the increased use of “big data” and statistical techniques to score potential transactions has transformed the operation of insurance and credit markets. In this paper, we observe that these widely-used scores are statistical objects that constitute a one-dimensional summary of a potentially much richer heterogeneity, some of which may be endogenous to the specific context in which they are applied. We demonstrate this point empirically using rich data from the Medicare Part D prescription drug insurance program. We show that the “risk scores,” which are designed to predict an individual's drug spending and are used by Medicare to customize reimbursement rates to private insurers, do not distinguish between two different sources of spending: underlying health, and responsiveness of drug spending to the insurance contract. Naturally, however, these two determinants of spending have very different implications when trying to predict counterfactual spending under alternative contracts. As a result, we illustrate that once we enrich the theoretical framework to allow individuals to have heterogeneous behavioral responses to the contract, strategic incentives for cream skimming still exist, even in the presence of “perfect” risk scoring under a given contract.