Working Paper

Predictive regressions with panel data

Abstract: This paper analyzes panel data inference in predictive regressions with endogenous and nearly persistent regressors. The standard fixed effects estimator is shown to suffer from a second order bias; analytical results, as well as Monte Carlo evidence, show that the bias and resulting size distortions can be severe. New estimators, based on recursive demeaning as well as direct bias correction, are proposed and methods for dealing with cross sectional dependence in the form of common factors are also developed. Overall, the results show that the econometric issues associated with predictive regressions when using time-series data to a large extent also carry over to the panel case. However, practical solutions are more readily available when using panel data. The results are illustrated with an application to predictability in international stock indices.

Keywords: Financial institutions; Econometrics;

Bibliographic Information

Provider: Board of Governors of the Federal Reserve System (U.S.)

Part of Series: International Finance Discussion Papers

Publication Date: 2006

Number: 869