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Count Data Models With Variance Of Unknown Form: An Application To A Hedonic Model Of Worker Absenteeism

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Miguel A. Delgado
Thomas J. Kniesner

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Abstract

We examine an econometric model of counts of worker absences due to illness in a sluggishly adjusting hedonic labor market. We compare three estimators that parameterize the conditional variance-least squares, Poisson, and negative binomial pseudo maximum likelihood-to generalized least squares (GLS) using nonparametric estimates of the conditional variance. Our data support the hedonic absenteeism model. Semiparametric GLS coefficients are similar in sign, magnitude, and statistical significance to coefficients where the mean and variance of the errors are specified ex ante. In our data, coefficient estimates are sensitive to a regressor list but not to the econometric technique, including correcting for possible heteroskedasticity of unknown form. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technolog

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Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 79 (1997)
Issue (Month): 1 (February)
Pages: 41-49
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Handle: RePEc:tpr:restat:v:79:y:1997:i:1:p:41-49

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  1. Stefan Boes, 2004. "Empirical Likelihood in Count Data Models: The Case of Endogenous Regressors," Working Papers 0404, University of Zurich, Socioeconomic Institute. [Downloadable!]
  2. Dionne, Georges & Dostie, Benoit, 2008. "Correlated Poisson Processes with Unobserved Heterogeneity: Estimating the Determinants of Paid and Unpaid Leave," IZA Discussion Papers 3642, Institute for the Study of Labor (IZA). [Downloadable!]
    Other versions:
  3. Begoña Álvarez, 2001. "La demanda atendida de consultas médicas y servicios urgentes en España," Investigaciones Economicas, Fundación SEPI, vol. 25(1), pages 93-138, January. [Downloadable!]
  4. Georges Dionne & Benoit Dostie, 2005. "New Evidence on the Determinants of Absenteeism Using Linked Employer-Employee Data," Cahiers de recherche 0521, CIRPEE. [Downloadable!]
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  5. Steve Bradley & Colin Green & Gareth Leeves, 2004. "Worker absence and shirking: evidence from matched teacher-school data," Working Papers 000271, Lancaster University Management School, Economics Department. [Downloadable!]
    Other versions:
  6. Stefan Boes, 2007. "Count Data Models with Unobserved Heterogeneity: An Empirical Likelihood Approach," Working Papers 0704, University of Zurich, Socioeconomic Institute. [Downloadable!]
  7. Bharati Basu & Felix Famoye, 2004. "Domestic violence against women, and their economic dependence: a count data analysis," Review of Political Economy, Taylor and Francis Journals, vol. 16(4), pages 457-472, October. [Downloadable!] (restricted)
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