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Moment Conditions and Neglected Endogeneity in Panel Data Models

Author

Listed:
  • Giorgio Calzolari

    () (University of Florence)

  • Laura Magazzini

    () (Department of Economics (University of Verona))

Abstract

This paper develops a new moment condition for estimation of linear panel data models. When added to the set of instruments devised by Anderson, Hsiao (1981, 1982) for the dynamic model, the proposed approach can outperform the GMM methods customarily employed for estimation. The proposal builds on the properties of the iterated GLS, that, contrary to conventional wisdom, can lead to a consistent estimator in particular cases where endogeneity of the explanatory variables is neglected. The targets achieved are a reduction in the number of moment conditions and a better performance over the most widely adopted techniques.

Suggested Citation

  • Giorgio Calzolari & Laura Magazzini, 2011. "Moment Conditions and Neglected Endogeneity in Panel Data Models," Working Papers 02/2011, University of Verona, Department of Economics.
  • Handle: RePEc:ver:wpaper:02/2011
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    File URL: http://dse.univr.it//workingpapers/WP_02_2011.pdf
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    References listed on IDEAS

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    1. Alok Bhargava & J. D. Sargan, 2006. "Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods," World Scientific Book Chapters,in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 1, pages 3-27 World Scientific Publishing Co. Pte. Ltd..
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Han, Chirok & Phillips, Peter C. B., 2010. "Gmm Estimation For Dynamic Panels With Fixed Effects And Strong Instruments At Unity," Econometric Theory, Cambridge University Press, vol. 26(01), pages 119-151, February.
    4. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    5. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    6. Calzolari, Giorgio & Sampoli, Letizia, 1993. "A Curious Result on Exact FIML and Instrumental Variables," Econometric Theory, Cambridge University Press, vol. 9(02), pages 296-309, April.
    7. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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    Citations

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    Cited by:

    1. Laura Magazzini & Giorgio Calzolari, 2012. "Identification of linear panel data models when instruments are not available," Working Papers 06/2012, University of Verona, Department of Economics.
    2. Giorgio Calzolari & Laura Magazzini, 2013. "A powerful test of mean stationarity in dynamic models for panel data: Monte Carlo evidence," Working Papers 14/2013, University of Verona, Department of Economics.

    More about this item

    Keywords

    panel data; dynamic model; GMM estimation; endogeneity;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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