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This dissertation consists of the three essays that allowed me to investigate three different economics phenomena. The discussion focuses on topics related to U.S. bank deregulation, China's resource misallocation and currency carry-trade strategy. In particularly, the aim is to study how U.S. bank deregulation is related to Great Moderation in U.S. between the mid-1980s and the start of the subprime debt crisis in 2007, what the implication of monetary policy with China's resource misallocation is and how a new carry trade method can be constructed.

The first paper models the effect of bank deregulation on the volatility of output and firms dynamics. By introducing a cost channel and bank sector into Bilbiee, Ghironi and Melitz (2007)'s model, we test the volatility change under various shocks before and after bank deregulation. Simulations show that with the bank spread decreases by 1/3, the volatility of output and number of producers decrease significantly. This can provide a potential explanation for why the Great Moderation starts from the mid-1980s to mid-2000s.

The second paper constructs a dynamic stochastic general equilibrium model of China with heterogeneous sectors and resource misallocation. Recent literature has shown that there is significant resource misallocation between state-owned firms and private firms in China. We find the presence of resource misallocation alters standard monetary policy conclusions in important ways. We show that there is an additional real effect of monetary policy--- an allocation effect. This is different from the standard New Keynesian framework, where the real effect comes from the price rigidity. Monetary policy shocks also exert heterogeneous effects on private firms and state-owned firms. Given a common shock, the output volatility of private firms is higher than that of state-owned firms. The model can easily be extended to other developing countries with similar situations.

The third paper employs two methods to construct a portfolio for carry trade strategy. The first one is the minimal variance, subject to specific return and weights constraints. The other is the maximal R square, subject to the weights constraints. Using MATLAB, we can calculate the optimal weights, returns and Sharpe ratio for these two methods. By comparing the Sharpe ratio for different time intervals, we find that the overall maximal R square strategy is relatively more accurate than the minimal variances strategy. This provides an alternative method to construct a carry trade portfolio.

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