Modelling zero-inflated count data when exposure varies: With an application to sick leave

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 effect of insurance generosity on the number of absent days.

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Year of publication:	2012
Authors:	Baetschmann, Gregori ; Winkelmann, Rainer
Publisher:	Zurich : University of Zurich, Department of Economics
Subject:	Zähldatenmodell \| Stochastischer Prozess \| Regression \| Theorie \| exposure \| Poisson regression \| complementary log-log link

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Series:	Working Paper ; 61
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.5167/uzh-59265 [DOI] 746051476 [GVK] hdl:10419/77528 [Handle]
Classification:	J29 - Time Allocation; Work Behavior; Employment Determination and Creation. Other ; C25 - Discrete Regression and Qualitative Choice Models
Source:	EconStor

Persistent link: https://www.econbiz.de/10010316870