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Predictive regressions with panel data
| Content Provider | Library of Congress - Books/Printed Material |
|---|---|
| Author | Hjalmarsson, Erik. |
| Temporal Coverage | 2006 |
| 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"--Federal Reserve Board web site. |
| Language | English |
| Publisher | Federal Reserve Board, |
| Publisher Place | Washington, D.C. |
| Part of Series | Catalog |
| Requires | HTML5 supported browser |
| Access Restriction | Open |
| Subject Keyword | Cross-sectional Dependence Panel Data Pooled Regression Predictive Regression Stock Return Predictability |
| Subject Domain (in LCSH) | Cross-sectional dependence; |
| Subject Domain (in LCSH) | panel data; |
| Subject Domain (in LCSH) | pooled regression; |
| Subject Domain (in LCSH) | predictive regression; |
| Subject Domain (in LCSH) | stock return predictability |
| Subject Domain (in LCC) | HG3879 |
| Content Type | Text |
| Resource Type | Book |
