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Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data

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  • César Alonso-Borrego
  • Manuel Arellano

Abstract

In this paper we discuss the estimation of panel data models with sequential moment restrictions using symmetrically normalized GMM estimators. These estimators are asymptotically equivalent to standard GMM but are invariant to normalization and tend to have a smaller finite sample bias. They also have a very different behaviour compared to standard GMM when the instruments are poor. We study the properties of SN-GMM estimators in relation to GMM, minimum distance and pseudo maximum likelihood estimators for various versions of the AR(1) model with individual effects by mean of simulations. The emphasis is not in assessing the value of enforcing particular restrictions in the model; rather, we wish to evaluate the effects in small samples of using alternative estimating criteria that produce asymptotically equivalent estimators for fixed T and large N. Finally, as an empírical illustration, we estimate by SN-GMM employment and wage equations using panels of UK and Spanish firms.
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Suggested Citation

  • César Alonso-Borrego & Manuel Arellano, 1996. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Working Papers wp1996_9612, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp1996_9612
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
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    11. Keller, Wouter J., 1975. "A new class of limited-information estimators for simultaneous equations systems," Journal of Econometrics, Elsevier, vol. 3(1), pages 71-92, February.
    12. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    13. Morimune, Kimio, 1983. "Approximate Distributions of k-Class Estimators When the Degree of Overidentifiability Is Large Compared with the Sample Size," Econometrica, Econometric Society, vol. 51(3), pages 821-841, May.
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