Modelling Zero-Inflated Count Data When Exposure Varies: With an Application to Sick Leave

University of Zurich Department of Economics Working Paper No. 61

16 Pages Posted: 17 Feb 2012 Last revised: 24 Feb 2012

See all articles by Gregori Baetschmann

Gregori Baetschmann

University of Zurich

Rainer Winkelmann

University of Zurich - Statistics and Empirical Economic Research; IZA Institute of Labor Economics; Centre for Economic Policy Research (CEPR)

Date Written: February 1, 2012

Abstract

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a new zero-inflated count data model that is based on two homogeneous Poisson processes and accounts for exposure time in a theory consistent way. The new model is used in an application to the e ffect of insurance generosity on the number of absent days.

Keywords: Exposure, Poisson regression, complementary log-log link

JEL Classification: J29, C25

Suggested Citation

Baetschmann, Gregori and Winkelmann, Rainer, Modelling Zero-Inflated Count Data When Exposure Varies: With an Application to Sick Leave (February 1, 2012). University of Zurich Department of Economics Working Paper No. 61, Available at SSRN: https://ssrn.com/abstract=2005793 or http://dx.doi.org/10.2139/ssrn.2005793

Gregori Baetschmann (Contact Author)

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Rainer Winkelmann

University of Zurich - Statistics and Empirical Economic Research ( email )

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Centre for Economic Policy Research (CEPR)

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