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Bias Reduction by Imputation for Linear Panel Data Models with Nonrandom Missing

Author

Listed:
  • Goeun Lee

    () (Department of Economics, Korea University, Seoul, Republic of Korea)

  • Chirok Han

    () (Department of Economics, Korea University, Seoul, Republic of Korea)

Abstract

When no variables are observed for endogenous non-respondents of panel data, bias correction is available only for a limited class of instrumental variable estimators, which require strong conditions for consistency and often suffer from substantial efficiency loss. In this paper we introduce a convenient alternative method of imputing the missing explanatory variables and then using standard bias-correction procedures for sample selection. Various bias-corrected estimators are derived and their performances are compared by Monte Carlo experiments. Results verify efficiency loss by the instrumental variable estimators and suggest that the imputation method is practically useful if it is applied to first-difference regression.

Suggested Citation

  • Goeun Lee & Chirok Han, 2018. "Bias Reduction by Imputation for Linear Panel Data Models with Nonrandom Missing," Discussion Paper Series 1801, Institute of Economic Research, Korea University.
  • Handle: RePEc:iek:wpaper:1801
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    File URL: http://econ.korea.ac.kr/~ri/WorkingPapers/w1801.pdf
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    References listed on IDEAS

    as
    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, May.
    3. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Attrition; missing; nonresponse; bias-correction; panel data; imputation;

    JEL classification:

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

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