Research

Research Papers

"Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care" (Job Market Paper) NBER Working Paper 15085, under review [PDF]

Abstract: The extent to which consumers with varying medical expenditures respond to marginal prices for medical care is important for policy. Using a new censored quantile instrumental variable (CQIV) estimator, I estimate the price elasticity of expenditure on medical care. The CQIV estimator allows the estimates to vary across the skewed expenditure distribution, it handles censoring at zero expenditure nonparametrically, and it allows for the insurance-induced endogenous relationship between price and expenditure. For identification, I rely on cost sharing provisions that generate differences in marginal prices between individuals who have injured family members and individuals who do not. I estimate the price elasticity of expenditure on medical care to be stable at -2.3 across the .65 to .95 conditional quantiles of the expenditure distribution. These quantile estimates are an order of magnitude larger than previous mean estimates. I consider several explanations for why price responsiveness is larger than previous estimates would suggest.

"Estimating Marginal Returns to Medical Care: Evidence from At-risk Newborns" NBER Working Paper 14522 (with Douglas Almond, Joseph J. Doyle, and Heidi Williams) forthcoming, Quarterly Journal of Economics [PDF]

Abstract: We estimate marginal returns to medical care for at-risk newborns by comparing health outcomes and medical treatment provision on either side of common risk classifications, most notably the "very low birth weight" threshold at 1500 grams. First, using data on the census of US births in available years from 1983-2002, we find evidence that newborns with birth weights just below 1500 grams have lower one-year mortality rates than do newborns with birth weights just above this cutoff, even though mortality risk tends to decrease with birth weight. One-year mortality falls by approximately one percentage point as birth weight crosses 1500 grams from above, which is large relative to mean one-year mortality of 5.5% just above 1500 grams. Second, using hospital discharge records for births in five states in available years from 1991-2006, we find evidence that newborns with birth weights just below 1500 grams have discontinuously higher costs and frequencies of specific medical inputs. We estimate a $4,000 increase in hospital costs as birth weight approaches 1500 grams from above, relative to mean hospital costs of $40,000 just above 1500 grams. Taken together, these estimates suggest that the cost of saving a statistical life of a newborn with birth weight near 1500 grams is on the order of $550,000 in 2006 dollars.

"Censored Quantile Instrumental Variable Estimation via Control Functions" (with Victor Chernozhukov and Ivan Fernandez-Val) [PDF]

Abstract: In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator handles censoring semi-parametrically in the tradition of Powell (1986), and it generalizes standard censored quantile regression (CQR) methods to incorporate endogenous regressors in a manner that is computationally tractable. Our computational algorithm combines a control function approach with the CQR estimator developed by Chernozhukov and Hong (2002). Through Monte-Carlo simulation, we show that CQIV performs well relative to Tobit IV in terms of median bias and interquartile range in a model that satisfies the parametric assumptions required for Tobit IV to be efficient. Given the strong parametric assumptions required by Tobit IV, the gains to CQIV relative to Tobit IV are likely to be large in empirical applications. We present results from an empirical application of CQIV to the estimation of Engel curves for alcohol. This empirical application demonstrates the importance of accounting for censoring and endogeneity with CQIV.

Research in Progress

"A Nonlinear Budget Set Model of Medical Care, With Applied Estimates of Moral Hazard, Adverse Selection, and the Optimal Nonlinear Structure of Health Insurance"

Abstract: Using the theory of utility maximization subject to a nonlinear constraint, I develop a structural model to estimate the price elasticity of expenditure on medical care among people with traditional health insurance policies. Deductibles, coinsurance rates, and stoplosses play an important role in the model because they generate nonlinearities in consumer budget sets. Identification relies on shocks to consumer demand for medical care that are uncorrelated with observed demand determinants. Relative to reduced form demand models, the model describes behavior consistent with the functional form of the demand function, and it allows for the direct calculation of welfare effects. Furthermore, it incorporates censoring in a manner that is consistent with a corner solution decision to consume zero care. The model generalizes existing nonlinear budget set models by allowing for more than one nonconvex kink. Relative to other nonlinear budget set applications, the medical care application allows for a particularly tight link between the agent's actual budget set, the model, and the estimation strategy. Using data on individuals with employer-sponsored health insurance, I estimate the price elasticity. I then perform counterfactual simulations with the estimated structural coefficients to examine adverse selection, moral hazard, and the optimal nonlinear design of health insurance policies.

"Estimates of the Risk-Reducing Benefits of Health Insurance for the Uninsured" (with Jonathan Kolstad)

Abstract: Economists have long recognized a fundamental tradeoff in the provision of insurance: more generous insurance has the undesired effect of increasing expenditure and the desired effect of decreasing exposure to financial risk. Although there are credible estimates of the increased expenditure associated with health insurance in the US, there is much less evidence on the magnitude of decreased financial risk associated with health insurance in the US. Furthermore, much academic work examines the costs of uninsurance in the aggregate and identifies uninsured populations as the residual obtained by subtracting the insured population from the overall population. In our research, using new data, we can directly examine the demographic characteristics, medical claims, and credit scores of uninsured (as well as insured) individuals. We aim to characterize the value of reduced medical financial risk in terms of medical and non-medical consumption behavior. With the value of the reduced medical financial risk, we can estimate the social welfare implications of extending coverage to the uninsured.

"Quantile Duration Models: An Application to Elderly Survival After Cardiac Catheterization" (with Victor Chernozhukov)

Abstract: Using quantile duration models, we revisit the McClellan, McNeil, and Newhouse (1994) model of the effect of cardiac catheterization on elderly mortality, which uses differential distance to a cardiac catheterization facility as an instrument. Specifically, we reproduce and extend the Cutler (2007) reexamination of the original analysis using 1984-2005 Medicare claims data. Unlike the original econometric model, our model accounts for the serious econometric issues that arise in the analysis of binary endogenous variables on binary outcomes such as mortality. We demonstrate the magnitude of the bias that arises when these issues are not taken into account, and we present updated estimates of the effect of cardiac catheterization on elderly mortality.

Publication

Amanda E. Kowalski, William J. Congdon, and Mark H. Showalter (2008) "State Health Insurance Regulations and the Price of High-Deductible Policies," Forum for Health Economics & Policy: Vol. 11: Iss. 2 (Health Care Reform), Article 8. [PDF]