|dc.description.abstract||In the first chapter, I analyze the US banking industry in order to explain two facts. First, larger banks have lower but less volatile returns on loans compared to smaller banks over the years. Second, larger borrowers have better financial records, i.e. verifiable "hard" information, and they are more likely to match with larger banks, as documented by Berger et al.(2005).
I show that these two facts can be explained using a segmented loan markets model with loan contracts between banks and borrowers. Moreover, I show that the difference between the banks returns is not due to diversification advantage of larger banks. Instead, it is because of the fact that larger banks can operate in both large and small loan markets, whereas small banks can only operate in small loans market. Therefore large banks are able to match with larger and less risky borrowers more frequently, which are less likely to default. Moreover, I take the model to infinite horizon allowing bank size to be endogenous to answer multiple policy questions about the future of small business finance and consolidation. I use the data set from the Consolidated Reports of Condition and Income provided by FDIC for 1984-2010 to motivate our research question and to estimate the model.
My second chapter revisits the welfare cost of anticipated inflation in an incomplete markets environment where agents can substitute time for money by increasing their shopping frequency. Shopping activity provides an insurance channel to individuals against changes in the return on nominal balances through inflation as documented by Aguiar and Hurst (2007) and McKenzie and Schargrodsky (2011). In my model economy, a higher level of inflation affects people through two channels. First, it distorts the portfolio decision between real and nominal balances, second it redistributes wealth from those who hold more money to those who hold less. People, on average, respond to a higher level of inflation by increasing their price search activity, as they relative return on nominal balances goes down. I find that a 5 percent increase in inflation causes the welfare level go down by 2 percent if people are allowed to substitute time for money, and by 10 percent if we take this channel away from the model.
Finally, in the third chapter, I compare the indirect measure of inflation expectations derived by Ireland (1996b) to the direct measures obtained from expectations surveys in multiple countries. Our results show that the inflation bounds calculated for US and UK data are more volatile than survey results, and are too narrow to contain them due to low standard errors in consumption growth series stemming from high persistence. For Chilean and Turkish cases, however, computed bound for inflation expectations seems to fit the survey results better. Out of three different surveys on inflation expectations in Turkey compared with the bounds computed using Turkish data, expectations obtained by the Consumer Tendency Survey fall within these bounds throughout the whole sample period. The success in the Turkish and Chilean cases can be attributed to the fact that volatility in the consumption series, whereas the failure in US and UK cases are most probably stemming from the fact that the current theoretical model is missing a risk-premium component.||en