Working Paper

The Stambaugh bias in panel predictive regressions

Abstract: This paper analyzes predictive regressions in a panel data setting. The standard fixed effects estimator suffers from a small sample bias, which is the analogue of the Stambaugh bias in time-series predictive regressions. Monte Carlo evidence shows that the bias and resulting size distortions can be severe. A new bias-corrected estimator is proposed, which is shown to work well in finite samples and to lead to approximately normally distributed t-statistics. 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. The results are illustrated with an application to predictability in international stock indices.

Keywords: Panel analysis; Stocks;

Bibliographic Information

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

Part of Series: International Finance Discussion Papers

Publication Date: 2007

Number: 914