Working Paper: CEPR ID: DP7813
Authors: Jess Fernández-Villaverde; Pablo A. Guerrón-Quintana; Juan Francisco Rubio-Ramírez
Abstract: 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 us 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, we build a medium-scale dynamic stochastic general equilibrium (DSGE) model with both stochastic volatility and parameter drifting in the Taylor rule and we estimate it non-linearly using U.S. data and Bayesian methods. Methodologically, we 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. Our 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.
Keywords: Bayesian methods; DSGE models; parameter drifting; stochastic volatility
JEL Codes: C11; E10; E30
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Monetary policy changes (E52) | Aggregate volatility (E10) |
| Favorable shocks (E32) | Economic stability (E60) |
| Leadership (M54) | Policy effectiveness (D78) |
| Changes in monetary policy (E52) | Great Moderation (E65) |