To Pool or Not to Pool: What Is a Good Strategy for Parameter Estimation and Forecasting in Panel Regressions?
35 Pages Posted: 24 Feb 2018 Last revised: 25 Nov 2018
Date Written: March 24, 2015
This paper considers estimating the slope parameters and forecasting in potentially heterogeneous panel data regressions with a long time dimension. We propose a novel optimal pooling averaging estimator that makes an explicit trade-off between efficiency gains from pooling and bias due to heterogeneity. By theoretically and numerically comparing various estimators, we find that a uniformly best estimator does not exist and that our new estimator is superior in non-extreme cases and robust in extreme cases. Our results provide practical guidance for the best estimator and forecast depending on features of data and models. We apply our method to examine the determinants of sovereign credit default swap spreads and forecast future spreads.
Keywords: Credit default swap spreads; Heterogeneous panel; Model screening; Panel data forecasting; Pooling averaging
JEL Classification: C23, C52, G15
Suggested Citation: Suggested Citation