Estimating Dynamic Panel Data Models: A Practical Guide for Macroeconomists

Posted: 2 Jul 2021

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: 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.

Suggested Citation

Judson, Ruth A. and Owen, Ann L., Estimating Dynamic Panel Data Models: A Practical Guide for Macroeconomists (1997). Available at SSRN: https://ssrn.com/abstract=3877777

Ruth A. Judson (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Ann L. Owen

Hamilton College - Economics Department ( email )

198 College Hill Road
Clinton, NY 13323
United States
315-859-4419 (Phone)
303-859-4477 (Fax)

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