Initial conditions and moment restrictions in dynamic panel data models

Initial conditions and moment restrictions in dynamic panel data models Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard first-differenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in performance of the proposed estimators compared to the usual first-differenced GMM estimator, and compared to non-linear GMM. The importance of these results is illustrated in an application to the estimation of a labour demand model using company panel data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Econometrics Elsevier

Initial conditions and moment restrictions in dynamic panel data models

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Publisher
Elsevier
Copyright
Copyright © 1998 Elsevier Science B.V.
ISSN
0304-4076
eISSN
1872-6895
D.O.I.
10.1016/S0304-4076(98)00009-8
Publisher site
See Article on Publisher Site

Abstract

Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard first-differenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in performance of the proposed estimators compared to the usual first-differenced GMM estimator, and compared to non-linear GMM. The importance of these results is illustrated in an application to the estimation of a labour demand model using company panel data.

Journal

Journal of EconometricsElsevier

Published: Nov 1, 1998

References

  • Another look at the instrumental-variable estimation of error-components models
    Arellano, M.; Bover, O.

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