Predictive regressions with panel data
By: Erik Hjalmarsson
Contributors: Board of Governors of the Federal Reserve System (U.S.)
Series: International finance discussion papers -- no. 869; International finance discussion papers (Online) -- no. 869.
Publisher: Federal Reserve Board
Published: 2006
Place of publication: Washington, D.C
Language: eng
Format: [electronic resource] /
Description: "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.
Notes: Title from PDF file as viewed on 11/27/2006.

Includes bibliographical references.

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