What Belongs Where? Variable Selection for Zero-Inflated Count Models with an Application to the Demand for Health Care

This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided.

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Year of publication:	2009
Authors:	Jochmann, Markus
Institutions:	Scottish Institute for Research in Economics (SIRE)
Subject:	Bayesian \| model selection \| model averaging \| count data \| zero-in ation \| demand for health care

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Series:	SIRE Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series SIRE-DP-2009-54 Number 2009-54
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010550824