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Asymptotic distribution of quasi-maximum likelihood estimation of dynamic panels using long difference transformation when both N and T are large

Author

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  • Cheng Hsiao

    (University of Southern California
    National Tsing Hua University
    Xiamen University)

  • Qiankun Zhou

    (State University of New York at Binghamton)

Abstract

This note shows that the asymptotic properties of the quasi-maximum likelihood estimation for dynamic panel models can be easily derived by following the approach of Grassetti (Stat Methods Appl 20:221–240, 2011) to take the long difference to remove the time-invariant individual specific effects.

Suggested Citation

  • Cheng Hsiao & Qiankun Zhou, 2016. "Asymptotic distribution of quasi-maximum likelihood estimation of dynamic panels using long difference transformation when both N and T are large," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 675-683, November.
    • Handle: RePEc:spr:stmapp:v:25:y:2016:i:4:d:10.1007_s10260-016-0355-x
    DOI: 10.1007/s10260-016-0355-x
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    References listed on IDEAS

    as
    1. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, 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.
    3. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    4. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    5. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    6. Luca Grassetti, 2011. "A note on transformed likelihood approach in linear dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 221-240, June.
    7. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    8. Hsiao, Cheng & Zhang, Junwei, 2015. "IV, GMM or likelihood approach to estimate dynamic panel models when either N or T or both are large," Journal of Econometrics, Elsevier, vol. 187(1), pages 312-322.
    9. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Hsiao, Cheng & Zhou, Qiankun, 2018. "Incidental parameters, initial conditions and sample size in statistical inference for dynamic panel data models," Journal of Econometrics, Elsevier, vol. 207(1), pages 114-128.

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    More about this item

    Keywords

    Dynamic panel model; Maximum likelihood estimation; Long difference;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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