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Moment Estimation with Attrition

Author

Listed:
  • JM Abowd

    (Crest)

  • Bruno Crépon

    (Crest)

  • Francis Kramarz

    (Crest)

Abstract

We present a method that accommodates missing data in longitudinal datasets of the type usually encountered in economic and social applications. The technique uses various extensions of missing at random' assumptions that we customize for dynamic models. Our method, applicable to longitudinal data on persons or firms, is implemented using the Generalized Method of Moments with reweighting that appropriately corrects for the attrition bias caused by the missing data. We apply the method to the estimation of dynamic labor demand models. The results demonstrate that the correction is extremely important.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • JM Abowd & Bruno Crépon & Francis Kramarz, 1997. "Moment Estimation with Attrition," Working Papers 97-35, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:97-35
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    Cited by:

    1. Cheti Nicoletti, 2010. "Poverty analysis with missing data: alternative estimators compared," Empirical Economics, Springer, vol. 38(1), pages 1-22, February.
    2. Tor Jakob Klette & Arvid Raknerud, 2002. "How and why do Firms differ?," Discussion Papers 320, Statistics Norway, Research Department.
    3. Rob Alessie & Stefan Hochguertel & Guglielmo Weber, 2005. "Consumer Credit: Evidence From Italian Micro Data," Journal of the European Economic Association, MIT Press, vol. 3(1), pages 144-178, March.
    4. Markus Frölich & Martin Huber, 2014. "Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
    5. Cheti Nicoletti & Marco Francesconi, 2006. "Intergenerational mobility and sample selection in short panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1265-1293.
    6. Nicoletti, Cheti & Peracchi, Franco, 2002. "A cross-country comparison of survey nonparticipation in the ECHP -ISER working paper-," ISER Working Paper Series 2002-32, Institute for Social and Economic Research.
    7. Cheti Nicoletti & Franco Peracchi & Vincenzo Atella, 2005. "Survey Response and Survey Characteristics: Micro-level Evidence from the European Commission Household Panel," CEIS Research Paper 64, Tor Vergata University, CEIS.
    8. Arvid Raknerud, 2002. "Identification, Estimation and Testing in Panel Data Models with Attrition: The Role of the Missing at Random Assumption," Discussion Papers 330, Statistics Norway, Research Department.
    9. Nicoletti, Cheti & Peracchi, Franco, 2004. "Survey response and survey characteristics: Micro-level evidence from the ECHP," Economics & Statistics Discussion Papers esdp04015, University of Molise, Department of Economics.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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