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The Stambaugh bias in panel predictive regressions

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Author Info
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.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 914.

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Date of creation: 2007
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Handle: RePEc:fip:fedgif:914

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Keywords: Panel analysis ; Stocks;

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  7. Polk, Christopher & Thompson, Samuel & Vuolteenaho, Tuomo, 2006. "Cross-sectional forecasts of the equity premium," Journal of Financial Economics, Elsevier, vol. 81(1), pages 101-141, July. [Downloadable!] (restricted)
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  9. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November. [Downloadable!] (restricted)
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