Modelling zero-inflated count data when exposure varies: With an application to sick leave - Gregori Baetschmann; Rainer Winkelmann (University of Zurich, Department of Economics, 2012)
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.
Keywords: J29; C25; 330; exposure; Poisson regression; complementary log-log link; Zähldatenmodell; Stochastischer Prozess; Regression; Theorie