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On the fixed-effects vector decomposition

  • Breusch, Trevor
  • Ward, Michael B
  • Nguyen, Hoa
  • Kompas, Tom

This paper analyses the properties of the fixed-effects vector decomposition estimator, an emerging and popular technique for estimating time-invariant variables in panel data models with unit effects. This estimator was initially motivated on heuristic grounds, and advocated on the strength of favorable Monte Carlo results, but with no formal analysis. We show that the three-stage procedure of this decomposition is equivalent to a standard instrumental variables approach, for a specific set of instruments. The instrumental variables representation facilitates the present formal analysis which finds: (1) The estimator reproduces exactly classical fixed-effects estimates for time-varying variables. (2) The standard errors recommended for this estimator are too small for both time-varying and time-invariant variables. (3) The estimator is inconsistent when the time-invariant variables are endogenous. (4) The reported sampling properties in the original Monte Carlo evidence are incorrect. (5) We recommend an alternative shrinkage estimator that has superior risk properties to the decomposition estimator, unless the endogeneity problem is known to be small or no relevant instruments exist.

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File URL: https://mpra.ub.uni-muenchen.de/26767/2/MPRA_paper_26767.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21452.

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Date of creation: Mar 2010
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Handle: RePEc:pra:mprapa:21452
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  1. Signe Krogstrup & Sébastien Wälti, 2008. "Do fiscal rules cause budgetary outcomes?," Public Choice, Springer, vol. 136(1), pages 123-138, July.
  2. Guglielmo Maria Caporale & Christophe Rault & Robert Sova & Ana Maria Sova, 2008. "On the Bilateral Trade Effects of Free Trade Agreements between the EU-15 and the CEEC-4 Countries," CESifo Working Paper Series 2419, CESifo Group Munich.
  3. Hausman, Jerry A. & Taylor, William E., 1981. "Panel data and unobservable individual effects," Journal of Econometrics, Elsevier, vol. 16(1), pages 155-155, May.
  4. Wong, Ka-fu, 1997. "Effects on inference of pretesting the exogeneity of a regressor," Economics Letters, Elsevier, vol. 56(3), pages 267-271, November.
  5. Belke, Ansgar H. & Spies, Julia, 2008. "Enlarging the EMU to the East: What Effects on Trade?," IZA Discussion Papers 3647, Institute for the Study of Labor (IZA).
  6. Kazimi, Camilla & Brownstone, David, 1999. "Bootstrap confidence bands for shrinkage estimators," Journal of Econometrics, Elsevier, vol. 90(1), pages 99-127, May.
  7. Mittelhammer, Ron C. & Judge, George G., 2005. "Combining estimators to improve structural model estimation and inference under quadratic loss," Journal of Econometrics, Elsevier, vol. 128(1), pages 1-29, September.
  8. Han, Chirok & Schmidt, Peter, 2001. "The asymptotic distribution of the instrumental variable estimators when the instruments are not correlated with the regressors," Economics Letters, Elsevier, vol. 74(1), pages 61-66, December.
  9. Mitze, Timo, 2009. "Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or not IV?," Ruhr Economic Papers 83, Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI), Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  10. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2003. "Fixed effects, random effects or Hausman-Taylor?: A pretest estimator," Economics Letters, Elsevier, vol. 79(3), pages 361-369, June.
  11. Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989. "Efficient Estimation Using Panel Data," Econometrica, Econometric Society, vol. 57(3), pages 695-700, May.
  12. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
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