Date of Award

May 2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Economics

Committee Member

Paul Wilson

Committee Member

Matthew Lewis

Committee Member

Babur De los Santos

Committee Member

Howard Bodenhorn

Abstract

In the first chapter, we examine the performance of Chinese commercial banks before, during, and after the 2008 global financial crisis and the 2008--2010 China's 4 trillion Renminbi stimulus plan. Fully nonparametric methods are used to estimate technical efficiencies. Recently-developed statistical results are used to test for changes in efficiencies as well as productivity over time, and to test for changes in technology over time. We also test for differences in efficiency and productivity between big and small banks, and between domestic and foreign banks. We find evidence of the non-convexity of banks' production set. The data reveal that technical efficiency declined at the start of the global financial crisis (2007--2008) and after the China's stimulus plan (2010--2011), but recovered in the years later (2011--2013), and declined again from 2013 to 2014, ending lower in 2014 than in 2007. We find that productivity declined during and just after the China's stimulus plan (2009--2011), but recovered in the years later (2013--2014), ending lower in 2014 than in 2007. We also find that the technology shifted downward from 2012 to 2013, and then shifted upward from 2013 to 2014. Over the period 2007--2014, technology shifted upward. We provide evidence that in general big banks were more efficient and productive than small banks. Finally, domestic banks had higher efficiency and productivity than foreign banks over this period except in 2008.

In the second chapter, I estimate shadow price of equity for U.S. commercial banks over 2001--2018 using nonparametric estimators of the underlying cost frontier and tests the existence of ``Too-Big-to-Fail'' (TBTF) banks. Evidence on the existence of TBTF banks are found. Specifically, I find that a negative correlation exists between the shadow price of equity and the size of banks in each year, suggesting that big banks pay less in equity than small banks. In addition, in each year there are more banks with a negative shadow price of equity in the fourth quartile based on total assets than in the other three quartiles. The data also reveal that for each year, the estimated mean shadow price of equity for the top $100$ largest banks is smaller than the mean price of deposits, even though equity is commonly viewed as a riskier asset than deposits. Finally, I find that the top $10$ largest banks are willing to pay much more at the start of the global financial crisis and after the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 than the other periods. These results imply that these regulations are effective in reducing the implicit subsidy, at least for the top $10$ largest banks. However, it is also evident that the recapitalization has imposed significant equity funding costs for the top $10$ largest banks.

In the third chapter, we examine the performance of 144 countries in the world before, during, and after the 2007--2012 global financial crisis. Fully nonparametric methods are used to estimate technical efficiencies. Recently-developed statistical results are used to test for changes in efficiencies as well as productivity over time, and to test for changes in technology over time. We also test for these differences between developing and developed countries. We find evidence of the non-convexity of countries' production set. The data revealed that technical efficiency declined at the start of the global financial crisis (2006--2008), but recovered in the years later (2008--2014), ending higher in 2014 than in 2004. We also find that mean productivity continued decreasing from 2004 to 2010. Moreover, productivity in 2004 stochastic dominants in the first order that in 2014. Statistical tests indicate that the frontier continued shifting downward from 2004 to 2010, and then continued shifting upward from 2010 to 2014. Overall, the technology has shifted downward from 2004 to 2014. Finally, we provide evidence that developing economies have lower technical efficiency but higher productivity than developed economies over this period.

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