Essays on monetary policy and asset prices

The recent financial and economic turmoil driven by the housing market has led economists to refocus on monetary policy and asset price, including housing prices. The various relationships between monetary policy and asset prices in the U.S. economy are investigated through steady state Bayesian VAR (SS BVAR) and revised Taylor-rule (Forward-looking rule) based on the Generalized Method of Moments (GMM).;The multi-step ahead forecasts using steady state Bayesian VAR (SS BVAR), standard BVAR, and conventional VAR are executed. Equal predictive ability tests following Giacomini and White (2006) verify that the SS BVAR is superior in forecasting performance especially in the long-horizons when compared to the cases of standard BVAR and conventional VAR.;Alternative identifications involving the housing sector are explored in two different ways: an economic theory-based approach and algorithms of inductive causations. The impulse response of housing price and investment to Federal Funds Rates (FFRs) in all alternative identifications illustrate that the magnitudes are relatively smaller, less significant, and shorter when compared to the Choleski case. Also, this finding can be fortified by historical decomposition and conditional forecast analyses which confirm that the recent high peak in housing prices cannot be well accounted for except by the housing price shock itself. With all these estimation results, it is hard to agree with the argument that the considerable responsibility of the current housing boom and fallout is due to monetary policy shocks. Rather, it can be said that there is still enormous uncertainty between monetary policy and housing prices. Institutional shocks such as fundamental change of mortgage markets including the mobilizing the mortgage debts could probably compose the "uncertainty".;How does the Fed respond to stock price and inflation movements differently across high and low inflation sub-periods? The replicated linear estimation results of Dupor and Conley (2004)'s indicate that the Fed raises its target interest rate responding to stock price gap with statistical significance. The linear estimation results, however, are not statistically robust to small changes in the breakpoint especially in the inflation coefficient. Thus, a nonlinear model is constructed as an alternative way to relax this problem. Upon the nonlinear framework, the identification of the dominant cause of apparent change in the Fed behavior, between structural change and nonlinearity, is explored. Consequently, both nonlinearity and structural changes matter in an explanation of the Fed's behavior. Given a structural change, the inflation coefficients' movements show that the Fed has responded nonlinearly to the expected inflation pressure across the high and low inflation sub-periods, while the stock price gap coefficients show an explicit break around the early 1990s in line with Dupor and Conley (2004)'s finding.