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:	2009-01
Authors:	Jochmann, Markus
Institutions:	Rimini Centre for Economic Analysis (RCEA)
Subject:	Bayesian \| model selection \| model averaging \| count data \| zero-inflation \| demand for health care

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Series:	Working Paper Series.
Type of publication:	Book / Working Paper
Language:	English
Classification:	C11 - Bayesian Analysis ; C25 - Discrete Regression and Qualitative Choice Models ; I11 - Analysis of Health Care Markets
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008469825