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FEVD: Just IV or Just Mistaken?

Published online by Cambridge University Press:  04 January 2017

Trevor Breusch ,
Michael B. Ward ,
Hoa Thi Minh Nguyen  and
Tom Kompas
Trevor Breusch*
Affiliation:
Crawford School of Economics and Government, The Australian National University, Canberra, ACT 0200, Australia
Michael B. Ward
Affiliation:
Crawford School of Economics and Government, The Australian National University, Canberra, ACT 0200, Australia e-mail: michael.ward@anu.edu.au
Hoa Thi Minh Nguyen
Affiliation:
Crawford School of Economics and Government, The Australian National University, Canberra, ACT 0200, Australia e-mail: hoa.nguyen@anu.edu.au
Tom Kompas
Affiliation:
Crawford School of Economics and Government, The Australian National University, Canberra, ACT 0200, Australia e-mail: tom.kompas@anu.edu.au
*
e-mail: trevor.breusch@anu.edu.au (corresponding author)
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Abstract

Fixed effects vector decomposition (FEVD) is simply an instrumental variables (IV) estimator with a particular choice of instruments and a special case of the well-known Hausman-Taylor IV procedure. Plümper and Troeger (PT) now acknowledge this point and disown the three-stage procedure that previously defined FEVD. Their old recipe for SEs, which has regrettably been used in dozens of published research papers, produces dramatic overconfidence in the estimates. Again PT concede the point and now adopt the standard IV formula for SEs. Knowing that FEVD is an application of IV also has the benefit of focusing attention on the choice of instruments. Now it seems PT claim that the FEVD instruments are always the best choice, on the grounds that one cannot know whether any potential instrument is correlated with the unit effect. One could just as readily make the same specious claim about other estimators, such as ordinary least squares, and support it with similar Monte Carlo assumptions and evidence.

Type
Symposium on Fixed-Effects Vector Decomposition
Information
Political Analysis , Volume 19 , Issue 2 , Spring 2011 , pp. 165 - 169
Copyright
Copyright © The Author 2011. Published by Oxford University Press on behalf of the Society for Political Methodology 

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References

Greene, William. 2011. Fixed effects vector decomposition: a magical solution to the problem of time invariant variables in fixed effects models? Political Analysis 19: 135–46.Google Scholar
Murray, Michael P. 2006. Avoiding invalid instruments and coping with weak instruments. Journal of Economic Perspectives 20: 111–32.Google Scholar
Plümper, Thomas, and Troeger, Vera. 2006. Efficient estimation of time-invariant and rarely changing variables infinite sample panel analyses with unit fixed effects. Discussion paper, Department of Government, University of Essex, Version tirc_80, August 24, 2006.Google Scholar
Plümper, Thomas, and Troeger, Vera. 2007. Efficient estimation of time-invariant and rarely changing variables in finite sample panel analyses with unit fixed effects. Political Analysis 15: 124–39.Google Scholar
Plümper, Thomas, and Troeger, Vera. 2010. xtfevd.ado version 4.0 beta. http://www.polsci.org/pluemper/xtfevd.ado.Google Scholar
Plümper, Thomas, and Troeger, Vera. 2011. Fixed effects vector decomposition: properties, reliability and instruments. Political Analysis 19: 147–64.CrossRefGoogle Scholar