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Markov Chain Monte Carlo analysis of underreported count data with an application to worker absenteeism


Winkelmann, Rainer (1996). Markov Chain Monte Carlo analysis of underreported count data with an application to worker absenteeism. Empirical Economics, 21(4):575-587.

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.

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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:1996
Deposited On:11 Feb 2008 12:21
Last Modified:05 Apr 2016 12:17
Publisher:Springer
ISSN:0377-7332
Publisher DOI:10.1007/BF01180702
Related URLs:http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=6759568&loginpage=Login.asp&site=ehost-live

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