Document Type



Doctor of Philosophy (PhD)



First Advisor's Name

Hakan Yilmazkuday

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Cem Karayalcin

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Sheng Guo

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Zhonghua Wu

Fourth Advisor's Committee Title

Committee member


Growth, housing market, inequality

Date of Defense



This dissertation includes three essays on growth, the housing market, and inequality. In the first essay, I analyze the effects of government consumption and government debt on long-run economic growth by considering the economic characteristics of the countries investigated. Linear regressions reveal that government consumption has a much bigger negative impact on long-run growth compared with the negative (and sometimes insignificant) effects of government debt. Nonlinear analyses further show that such effects are highly impacted by the economic characteristics of the countries investigated.

In the second essay, I study time-series fluctuations in the United States housing market from 2010 to 2016 using the Gordon growth model. Using variance decomposition analysis, I find that the housing premium is the main driver of housing market fluctuations. Motivated by previous studies and using impulse response functions, I show how different components of the housing market respond over time to a shock in the interest rate in regions with different levels of income or demographics. My findings suggest that the impact of monetary policy is smaller (and less persistent) in the U.S. housing market when households have more females, more African Americans, or fewer well-educated members; a combination of these demographics and a lower income in households results in a smaller impact of monetary policy in the housing market, due to the necessity of housing for these families.

In the third essay, I use Internal Revenue Service (IRS) annual data and Zillow median housing price data, to analyze the impact of income inequality on housing price to rent ratio from 2005 to 2015 for more than 12,700 zip codes. Employing various specifications, I find a consistent positive and significant relationship between the Gini coefficient and housing affordability index. My results are robust to different methods of estimating the Gini index. Moreover, the empirical results of this study suggest a larger impact of inequality in zip codes with higher levels of income.



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