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Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components

Author

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  • Carbajal-De-Nova, Carolina
  • Venegas-Martínez, Francisco

Abstract

By increasing the dimensions N or T, or both, in data panel analysis, bias can be reduced asymptotically to zero. This research deals with an econometric methodology to separate and measure bias through synthetic estimators without altering the data panel dimensions. This is done by recursively decomposing bias in systematic and random components. The methodology provides consistent synthetic estimators.

Suggested Citation

  • Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components," MPRA Paper 94405, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:94405
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    References listed on IDEAS

    as
    1. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    2. 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.
    3. Alberto Abadie & Guido W. Imbens, 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 1-11, January.
    4. 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.
    5. Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79158, University Library of Munich, Germany, revised 11 May 2017.
    6. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    panel data models; bias analysis; econometric modeling;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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