Date

5-20-2026

Department

Helms School of Government

Degree

Doctor of Philosophy in Public Policy (PhD)

Chair

Andrew Light

Keywords

activity-based costing, hospital costs, hospital property tax exemption, property tax abatement, property tax, X-Efficiency, hospital financial incentives

Disciplines

Economics | Public Affairs, Public Policy and Public Administration

Abstract

This dissertation analyzes the effects of property tax exemptions on real estate utilization by hospitals in the production of medical services. Economic theory suggests that differential taxing creates inefficiencies causing destruction of wealth from deadweight loss. Property taxation is done by state and local governments. State and local governments spend 4.5 trillion dollars annually in the United States (Pustejovsky & Little, 2023, p. 2). Although only spending on services using real estate has efficiency effects due to real estate taxes, every 1% gain in overall efficiency is 45 billion dollars saved annually if the results can be generalized to all tax-exempt organizations including state and local governments. This currently lost value due to economic inefficiency could be regained for the benefit of taxpayers. The actual amount of savings needs to be analyzed in a future study. The hospital cost data is available from the National Institutes of Health. Samples of hospitals’ 2019 data collection are selected for analysis. County tax data is used to determine the property tax exemption status of each hospital. A quotient of the value of real estate used divided by total annual expenses for each hospital is computed and identified as the real estate ratio, RealRatio. The hospitals are classified by rural or urban setting and by ownership type. These, as well as tax status, are independent variables. If any of the independent variables change within a data year, then the hospital is invalid for this analysis because the correct values of the independent variables for this analysis will be undeterminable. A non-parametric test is done to determine whether tax status, urban location, and type of ownership are significantly correlated with RealRatio. Preliminary analysis with sub-samples is used to hone the model by eliminating variables with no explanatory power. Proprietary ownership status and tax-exempt status are negatively correlated, which could make measuring their effects difficult due to multicollinearity if there is not enough variation between the two effects to allow them to be independently evaluated. Parametric analysis is then done to estimate the magnitude of the changes in the values of the independent variables on the RealRatio and possibly confirm the significance results of the non-parametric tests.

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