Fixed Effects Vector Decomposition

A Magical Solution to the Problem of Time-Invariant Variables in Fixed Effects Models

Bibliographic Data

ID7971097
AuthorsWilliam Greene (0000-0003-3806-0685), William H Greene (0000-0003-0347-2604, New York University, corresponding author)
Year2011
Volume19
Issue2
Pages135-146
Publication date2011-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePolitical Analysis (JOURNAL)
Journal identifiersISSN: 1047-1987 • E-ISSN: 1476-4989
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1093/pan/mpq034
OpenAlexW2112520204
LanguageEN
Citations received37
References cited10

Plümper and Troeger (2007) propose a three-step procedure for the estimation of a fixed effects (FE) model that, it is claimed, “provides the most reliable estimates under a wide variety of specifications common to real world data.” Their fixed effects vector decomposition (FEVD) estimator is startlingly simple, involving three simple steps, each requiring nothing more than ordinary least squares (OLS). Large gains in efficiency are claimed for cases of time-invariant and slowly time-varying regressors. A subsequent literature has compared the estimator to other estimators of FE models, including the estimator of Hausman and Taylor (1981) also (apparently) with impressive gains in efficiency. The article also claims to provide an efficient estimator for parameters on time-invariant variables (TIVs) in the FE model. None of the claims are correct. The FEVD estimator simply reproduces (identically) the linear FE (dummy variable) estimator then substitutes an inappropriate covariance matrix for the correct one. The consistency result follows from the fact that OLS in the FE model is consistent. The “efficiency” gains are illusory. The claim that the estimator provides an estimator for the coefficients on TIVs in an FE model is also incorrect. That part of the parameter vector remains unidentified. The “estimator” relies upon a strong assumption that turns the FE model into a type of random effects model

Consistent estimator · Covariance · Efficient estimator · Estimator · Invariant (physics · Invariant estimator · Minimum-variance unbiased estimator · Statistics · Mathematics · Spatial and Panel Data Analysis · Statistical Methods and Bayesian Inference · Statistical Methods and Inference · Applied Mathematics

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