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 with firm size.
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Valuable comments by John London-Lane, Siddharta Chib and two anonymous referees are gratefully acknowledged.
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Winkelmann, R. Markov chain Monte Carlo analysis of underreported count data with an application to worker absenteeism. Empirical Economics 21, 575–587 (1996). https://doi.org/10.1007/BF01180702
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DOI: https://doi.org/10.1007/BF01180702