To Pool or Not to Pool: What Is a Good Strategy for Parameter Estimation and Forecasting in Panel Regressions?
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.
|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)|
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 http://hdl.handle.net/1765/109088