Estimating Dynamic Panel Data Models: A Practical Guide Fo Macroeconomists

Board of Governors of the Federal Reserve System Finance and Econ. Disc. Series #97-3

22 Pages Posted: 6 May 1997

See all articles by Ruth Judson

Ruth Judson

Board of Governors of the Federal Reserve System

Ann L. Owen

Hamilton College - Economics Department

Date Written: January 16, 1997

Abstract

We use a Monte Carlo approach to investigate the performance of several different methods designed to reduce the bias of the estimated coefficients for dynamic panel data models estimated with the longer, narrower panels typical of macro data. We find that the bias of the least squares dummy variable approach can be significant, even when the time dimension of the panel is as large as 30. For panels with small time dimensions, we find a corrected least squares dummy variable estimator to be the best choice. However, as the time dimension of the panel increases, the computationally simpler Anderson-Hsiao estimator performs equally well.

JEL Classification: C23, O11, E00

Suggested Citation

Judson, Ruth A. and Owen, Ann L., Estimating Dynamic Panel Data Models: A Practical Guide Fo Macroeconomists (January 16, 1997). Board of Governors of the Federal Reserve System Finance and Econ. Disc. Series #97-3, Available at SSRN: https://ssrn.com/abstract=1904 or http://dx.doi.org/10.2139/ssrn.1904

Ruth A. Judson (Contact Author)

Board of Governors of the Federal Reserve System ( email )

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Ann L. Owen

Hamilton College - Economics Department ( email )

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Clinton, NY 13323
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