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Assessing the Impacts of an Aging Population on Rising Healthcare and Pharmaceutical Expenditures within the United States
By Rahul Sharma
This paper studies the impact of aging on rising healthcare and pharmaceutical expenditures in the United States with the goal of contextualizing the future burden of public health insurance on the government. Precedent literature has focused on international panels of multiple countries and hasn’t identified significant correlation between age and healthcare expenditures. This paper presents a novel approach of identifying this correlation by using a US sample population to determine if age impacts an individual’s consumption of healthcare services and goods. Results suggest that age has a significant impact on healthcare and pharmaceutical expenditures across private and public insurance.
Advisors: Gilliam D. Saunders-Schmidler and Grace Kim | JEL Codes: H51, H53, I12, I13, I18, I38
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.
Advisor: Frank Sloan | JEL Codes: I11, I13, I18, L11, L80 | Tagged: