This paper considers estimating the slope parameters in potentially heterogeneous panel data regressions for explaining and forecasting cross-country sovereign credit risk. We propose a novel optimal pooling averaging estimator that makes an explicit tradeoff 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. The results provide practical guidance for the best estimator depending on features of data and models.

Additional Metadata
Keywords Credit default swap spreads, Heterogeneous panel, Mean squared error, Model screening, Pooling averaging
JEL Models with Panel Data (jel C23), Model Evaluation and Testing (jel C52), International Financial Markets (jel G15)
Persistent URL
Wang, W, Zhang, X, & Paap, R. (2018). To Pool or Not to Pool: What Is a Good Strategy for Parameter Estimation and Forecasting in Panel Regressions?. Retrieved from