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Markov Chain Monte Carlo Analysis of Underreported Count Data with an Application to Worker Absenteeism

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  • Winkelmann, Rainer

Abstract

A new approach for modeling under-reported Poisson counts is developed. The parameters of the model are estimated by Markov Chain Monte Carlo simulation. An application to workers absenteeism data from the German Socio-Economic Panel illustrates the fruitfulness of the approach. Worker absenteeism and the level of pay are unrelated, but absence rates increase the firm size.

Suggested Citation

  • Winkelmann, Rainer, 1996. "Markov Chain Monte Carlo Analysis of Underreported Count Data with an Application to Worker Absenteeism," Empirical Economics, Springer, vol. 21(4), pages 575-587.
  • Handle: RePEc:spr:empeco:v:21:y:1996:i:4:p:575-87
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    Cited by:

    1. Riphahn Regina T. & Thalmaier Anja, 2001. "Behavioral Effects of Probation Periods: An Analysis of Worker Absenteeism / Anreizeffekte der Probezeit: Eine Untersuchung von Fehlzeiten bei Arbeitnehmern," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(2), pages 179-201, April.
    2. William H. Greene & Mark N. Harris & Bruce Hollingsworth, 2015. "Inflated Responses in Measures of Self-Assessed Health," American Journal of Health Economics, MIT Press, vol. 1(4), pages 461-493, Fall.
    3. Regina T. Riphahn & Anja Thalmaier, 1999. "Absenteeism and Employment Probation: A Panel Study for Germany," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 68(2), pages 230-236.
    4. Peter Fader & Bruce Hardie, 2000. "A note on modelling underreported Poisson counts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 953-964.
    5. Sha Yang & Yi Zhao & Ravi Dhar, 2010. "Modeling the Underreporting Bias in Panel Survey Data," Marketing Science, INFORMS, vol. 29(3), pages 525-539, 05-06.

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