The Stambaugh bias in panel predictive regressions
AbstractThis 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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Bibliographic InfoPaper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 914.
Date of creation: 2007
Date of revision:
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- Hjalmarsson, Erik, 2008. "The Stambaugh bias in panel predictive regressions," Finance Research Letters, Elsevier, vol. 5(1), pages 47-58, March.
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