Non-stationary Hours in a DSGE Model


  • We are thankful to Martin Eichenbaum and Robert Vigfusson, who kindly provided their data. We also thank Ken West (co-editor) and two anonymous referees for their helpful comments. Chang gratefully acknowledges the Research Grant of the School of Economics at Seoul National University. Schorfheide gratefully acknowledges financial support from the Alfred P. Sloan Foundation. GAUSS programs that implement the empirical analysis are available through the JMCB Data Archive. The views expressed herein are solely those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Kansas City or the Federal Reserve System.


The time series fit of dynamic stochastic general equilibrium (DSGE) models often suffers from restrictions on the long-run dynamics that are at odds with the data. Using Bayesian methods we estimate a stochastic growth model in which hours worked are stationary and a modified version with permanent labor supply shocks. If firms can freely adjust labor inputs, the data support the latter specification. Once we introduce frictions in terms of labor adjustment costs, the overall time series fit improves and the model specification in which labor supply shocks and hours worked are stationary is preferred.