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Debunking the Cost-Shifting Myth: An Analysis of Dnamic Price Discrimination in California Hospitals

By Omar Nazzal

Cost-shifting, a dynamic form of price discrimination, is a phenomenon in which hospitals shift the burden of decreases in government-sponsored healthcare reimbursement rates to private health insurers. In this paper, I construct a data set spanning 2007 – 2011 that matches financial metrics of California hospitals to hospital- and market-specific characteristics with theoretical implications in price discrimination. The subsequent analysis is split into three stages. In the first and second stages, I use a fixed-effects OLS model to derive a point estimate of the inverse correlation between private revenue and government revenue that is consistent with recent empirical work in cost-shifting, a body of literature almost entirely reliant upon fixed-effects and difference-in-difference OLS. These types of models are encumbered by the inherent causality loop connecting public and private payment sources. I address this endogeneity problem in the third stage by specifying a fixed-effects 2SLS model based on an instrument for government revenue constructed with data from the California Department of Health Care Services and the U.S. Census. This instrument performed well in canonical tests for relevance and validity. I find that an increase in government payments causes an increase in private payments, and that the relationship is statistically-significant at all reasonable levels. In addition, I comment on properties of the data set that suggest that the original inverse correlation was due to inadequate measurements of market power. I conclude with policy implications and suggestions for future research.

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Advisor: Frank Sloan | JEL Codes: I11, I13, I18, L11, L80 | Tagged: Health Insurance, Market Structure, Medicaid, Medicare, Price Discrimination

Health Care Utilization and Health Status of NCMS Elderly Enrollees in China: Evidence from CHARLS Data

By Pengpeng Wang

This study explores the effect of benefit designs and demographic factors on health care utilization and health status of elderly rural enrollees in the New Cooperative Medical Scheme, a rural health insurance program implemented by the Chinese government in 2003. Using the new data from CHARLS pilot study, we find that immediate reimbursement does not have a statistically significant effect on health utilization as suggested in a previous study, but instead on health status. Other policy-related factors neither have a significant effect due to limited data and large standard deviation nor display a consistent effect.

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Advisor: Frank Sloan | JEL Codes: I13, I18 | Tagged: Health Care Utilization, Health Insurance, Health Status, New Cooperative Medical Scheme, Reimbusement Method, Rural China

Possibility of Cost Offset in Expanding Health Insurance Coverage: Using Medical Expenditure Panel Survey 2008

By Catherine Moon

The Patient Protection and Affordable Care Act aims to substantially reduce the number of the
uninsured over time and asserts that the financial burden of extending insurance coverage to the
previously uninsured will be offset by the benefit of the attendant improvement in their health.
Motivated by this policy, I explore whether health-insurance status and type affect one’s likelihood of
improving or maintaining health using the Medical Expenditure Panel Survey data. I build a set of
ordered regression models for health-status transitions under the first-order Markov assumption and
estimate it using maximum likelihood estimation. I perform a series of likelihood ratio tests for pooling to determine whether the latent propensity index is the same between adjacent initial health-status groups. Empirical results imply that expanding health care to the unwillingly uninsured due to severe
economic constraints and extending the scope of public insurance to that of private insurance will lead to improvement or maintenance of health for the relatively healthy population, implying the possibility of cost off-set in the expansion of coverage and the extension of scope.

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Advisor: Frank Sloan, Michelle Connolly | JEL Codes: C12, C25, I12, I13, I18 | Tagged: Health Insurance, Health Transition, Ordered Regression Model, Patient Protection and Affordable Care Act (PPACA), Self-Assessed Health Status, Test for Pooling Adjacent Ordinal Categories


Undergraduate Program Assistant
Jennifer Becker

Director of the Honors Program
Michelle P. Connolly