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IV Estimation of Panels with Factor Residuals

  • Donald Robertson
  • Vasilis Sarafidis

This paper proposes a new instrumental variables approach for consistent and asymptotically efficient estimation of panel data models with weakly exogenous or endogenous regressors and residuals generated by a multifactor error structure. In this case, the standard dynamic panel estimators fail to provide consistent estimates of the parameters. The novelty of our approach is that we introduce new parameters to represent the unobserved covariances between the instruments and the factor component of the residual; these parameters are estimable when N is large. Some important estimation and identification issues are studied in detail. The finite sample performance of the proposed estimators is investigated using simulated data. The results show that the method produces reliable estimates of the parameters over several parametrisations.

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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1321.

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Date of creation: 04 Jun 2013
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Handle: RePEc:cam:camdae:1321
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  22. Arturas Juodis & Sarafidis, V., 2014. "Fixed T Dynamic Panel Data Estimators with Multi-Factor Errors," UvA-Econometrics Working Papers 14-07, Universiteit van Amsterdam, Dept. of Econometrics.
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  28. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
  29. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
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