Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
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.