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

Markus Jochmann

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

Markus Jochmann

Economics

Research output: Working paper › Discussion paper

19 Downloads (Pure)

Abstract

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.

Original language	English
Place of Publication	Glasgow
Publisher	University of Strathclyde
Number of pages	21
Publication status	Published - 31 Oct 2009

Publication series

Name	Strathclyde Discussion Papers in Economics
Publisher	University of Strathclyde
Volume	09-23

Keywords

bayesian
model selection
model averaging
count data
zero-inflation
demand for health care

Access to Document

Jochmann-2009-Zero-inflated-count-models-with-an-application-to-the-demand-for-health-careFinal published version, 258 KB

Cite this

@techreport{132f2ca027254d1093e84320b83c1a98,

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

abstract = "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.",

keywords = "bayesian, model selection, model averaging, count data, zero-inflation, demand for health care",

author = "Markus Jochmann",

note = "Published as a paper within the Discussion Papers in Economics, No. 09-23 (2009)",

year = "2009",

month = oct,

day = "31",

language = "English",

series = "Strathclyde Discussion Papers in Economics",

publisher = "University of Strathclyde",

type = "WorkingPaper",

institution = "University of Strathclyde",

}

TY - UNPB

T1 - What Belongs Where? Variable Selection for Zero-Inflated Count Models with an Application to the Demand for Health Care

AU - Jochmann, Markus

N1 - Published as a paper within the Discussion Papers in Economics, No. 09-23 (2009)

PY - 2009/10/31

Y1 - 2009/10/31

N2 - 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.

AB - 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.

KW - bayesian

KW - model selection

KW - model averaging

KW - count data

KW - zero-inflation

KW - demand for health care

UR - https://www.strath.ac.uk/business/economics/research/discussionpapers/

M3 - Discussion paper

T3 - Strathclyde Discussion Papers in Economics

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

PB - University of Strathclyde

CY - Glasgow

ER -

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

Abstract

Publication series

Keywords

Access to Document

Other files and links

Fingerprint

Cite this