Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting in U.S. Data
University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)
Federal Reserve Banks - Federal Reserve Bank of Philadelphia
Juan Francisco Rubio-Ramirez
Duke University - Department of Economics; Federal Reserve Bank of Atlanta - Research Department
April 29, 2010
FRB of Philadelphia Working Paper No. 10-14
This paper compares the role of stochastic volatility versus changes in monetary policy rules in accounting for the time-varying volatility of U.S. aggregate data. Of special interest to the authors is understanding the sources of the great moderation of business cycle fluctuations that the U.S. economy experienced between 1984 and 2007. To explore this issue, the authors build a medium-scale dynamic stochastic general equilibrium (DSGE) model with both stochastic volatility and parameter drifting in the Taylor rule and they estimate it non-linearly using U.S. data and Bayesian methods.
Methodologically, the authors show how to confront such a rich model with the data by exploiting the structure of the high-order approximation to the decision rules that characterize the equilibrium of the economy. Their main empirical findings are: 1) even after controlling for stochastic volatility (and there is a fair amount of it), there is overwhelming evidence of changes in monetary policy during the analyzed period; 2) however, these changes in monetary policy mattered little for the great moderation; 3) most of the great performance of the U.S. economy during the 1990s was a result of good shocks; and 4) the response of monetary policy to inflation under Burns, Miller, and Greenspan was similar, while it was much higher under Volcker.
Number of Pages in PDF File: 73
Keywords: DSGE models, Stochastic volatility, Parameter drifting, Bayesian methods
JEL Classification: E10, E30, C11working papers series
Date posted: May 6, 2010
© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo8 in 0.343 seconds