Estimating VARs with long stationary heterogeneous panels: A comparison of the fixed effect and the mean group estimators

Abstract

The most promising candidates for estimating vector autoregressive models with long, stationary, possibly heterogeneous panel data sets (panel-VARs) are the fixed effect (FE) and the mean group (MG) estimators. With a view to providing guidance to applied researchers on how to pool in a panel-VAR, this paper compares the performance of the FE and the MG estimators both asymptotically and in Monte Carlo simulations. The main results of the analysis suggest the use of both estimators in applied work. If FE and MG estimates give similar estimates, the FE estimator should be used because it is more efficient. If they differ, the MG estimator should be used only if the panel is sufficiently long -- say, twice as long as usually recommended in the dynamic panel data literature. If FE and MG estimates differ and the panel is not long enough, neither is generally a desirable alternative and other estimation techniques are needed.