Efficient Estimation of Rarely Changing Variables in Fixed Effects Models

25 Pages Posted: 26 Nov 2004

See all articles by Thomas Pluemper

Thomas Pluemper

Vienna University of Economics and Business - Department of Socioeconomics; University of Essex - Department of Government

Vera E. Troeger

University of Essex - Department of Government

Abstract

The estimation of slowly and rarely changing variables in panel data with unobserved unit effects suffers from inefficiency of the fixed effects estimator. Point estimates lack reliability when the within variance (the variation across time) remains small. The estimate's efficiency can be enhanced if the between variance (the variation across space) increases. However, this comes at the cost of increasing potential omitted variable bias. We describe a three-stage estimator (called xtfevd) that allows to maintain the between variance of cross-sectionally dominant variables while estimating the variables with sufficient within variation by fixed effects. Monte Carlo simulations show that this procedure performs better than the fixed effects model in cases where the between variance exceeds the within variance by at least factor 2.5. Thus, xtfevd outperforms the standard fixed effects model if the within variance is small and the between variance significantly larger.

Keywords: Unit heterogeneity, fixed effects, panel data, re-analysis

JEL Classification: C23, C15

Suggested Citation

Plümper, Thomas and Troeger, Vera E., Efficient Estimation of Rarely Changing Variables in Fixed Effects Models. Available at SSRN: https://ssrn.com/abstract=622581 or http://dx.doi.org/10.2139/ssrn.622581

Thomas Plümper (Contact Author)

Vienna University of Economics and Business - Department of Socioeconomics ( email )

Vienna
Austria

University of Essex - Department of Government ( email )

Wivenhoe Park
Colchester, Essex CO4 3SQ
United Kingdom

HOME PAGE: http://www.polsci.org/pluemper

Vera E. Troeger

University of Essex - Department of Government ( email )

Wivenhoe Park
Colchester CO4 3SQ, CO4 3SQ
United Kingdom

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