Essays in the Macroeconomics of Health Care
2019-06
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Essays in the Macroeconomics of Health Care
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2019-06
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This dissertation consists of three essays that study the macroeconomics of health care. The first essay studies how policies can be designed to reduce differences in life expectancy across income groups in the United States and examines what the consequences of these policies are for welfare and the macroeconomy. Using a calibrated structural life cycle model with incomplete markets, heterogeneous agents, and endogenous health, I find that a universal health insurance reform leads to higher life expectancy, lower life expectancy inequality, lower health care spending, higher GDP per capita, and higher welfare, even after controlling for the increased tax burden needed to finance the reform. The second essay develops a structural life cycle model with incomplete markets and heterogeneous agents to study how the ability to file for medical bankruptcy affects incentives to purchase health insurance. I find that the ability to file for medical bankruptcy crowds out private health insurance coverage. The majority of the population, however, is better off in the economy with medical bankruptcy because of the implicit insurance provided by this option. Finally, motivated by the considerable heterogeneity in GDP per capita across the states of the US, the third essay develops a model to quantify the welfare differences across the states as measured by the expected lifetime utility of being born in a particular state. Using a calibrated version of the model that allows for state-specific variation in mortality risk, consumption uncertainty, and educational attainment, I document large and persistent heterogeneity in welfare across the states of the US.
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University of Minnesota Ph.D. dissertation. June 2019. Major: Economics. Advisors: Manuel Amador, Timothy Kehoe. 1 computer file (PDF); xii, 148 pages.
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Nygaard, Vegard Mokleiv. (2019). Essays in the Macroeconomics of Health Care. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/206418.
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