International Finance Discussion Papers (IFDP)
November 2007
The Stambaugh Bias in Panel Predictive Regressions
Erik Hjalmarsson
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.
Full paper (screen reader version)Keywords: Panel data, pooled regression, predictive regression, stock return predictability
PDF: Full Paper
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