A zero-inflated ordered probit model, with an application to modelling tobacco consumption

Data for discrete ordered dependent variables are often characterised by "excessive" zero observations which may relate to two distinct data generating processes. Traditional ordered probit models have limited capacity in explaining this preponderance of zero observations. We propose a zer...

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Main Authors: Harris, Mark, Zhao, X.
Format: Journal Article
Language:English
Published: Elsevier 2007
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/81800
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author Harris, Mark
Zhao, X.
author_facet Harris, Mark
Zhao, X.
author_sort Harris, Mark
building Curtin Institutional Repository
collection Online Access
description Data for discrete ordered dependent variables are often characterised by "excessive" zero observations which may relate to two distinct data generating processes. Traditional ordered probit models have limited capacity in explaining this preponderance of zero observations. We propose a zero-inflated ordered probit model using a double-hurdle combination of a split probit model and an ordered probit model. Monte Carlo results show favourable performance in finite samples. The model is applied to a consumer choice problem of tobacco consumption indicating that policy recommendations could be misleading if the splitting process is ignored. © 2007 Elsevier B.V. All rights reserved.
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spelling curtin-20.500.11937-818002021-03-25T02:27:22Z A zero-inflated ordered probit model, with an application to modelling tobacco consumption Harris, Mark Zhao, X. Social Sciences Science & Technology Physical Sciences Economics Mathematics, Interdisciplinary Applications Social Sciences, Mathematical Methods Business & Economics Mathematics Mathematical Methods In Social Sciences ordered outcomes discrete data tobacco consumption zero-inflated responses COUNT DATA MODELS SPECIFICATION TESTS DEPENDENT VARIABLES DEMAND MARIJUANA SELECTION ALCOHOL Data for discrete ordered dependent variables are often characterised by "excessive" zero observations which may relate to two distinct data generating processes. Traditional ordered probit models have limited capacity in explaining this preponderance of zero observations. We propose a zero-inflated ordered probit model using a double-hurdle combination of a split probit model and an ordered probit model. Monte Carlo results show favourable performance in finite samples. The model is applied to a consumer choice problem of tobacco consumption indicating that policy recommendations could be misleading if the splitting process is ignored. © 2007 Elsevier B.V. All rights reserved. 2007 Journal Article http://hdl.handle.net/20.500.11937/81800 10.1016/j.jeconom.2007.01.002 English Elsevier restricted
spellingShingle Social Sciences
Science & Technology
Physical Sciences
Economics
Mathematics, Interdisciplinary Applications
Social Sciences, Mathematical Methods
Business & Economics
Mathematics
Mathematical Methods In Social Sciences
ordered outcomes
discrete data
tobacco consumption
zero-inflated responses
COUNT DATA MODELS
SPECIFICATION TESTS
DEPENDENT VARIABLES
DEMAND
MARIJUANA
SELECTION
ALCOHOL
Harris, Mark
Zhao, X.
A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title_full A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title_fullStr A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title_full_unstemmed A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title_short A zero-inflated ordered probit model, with an application to modelling tobacco consumption
title_sort zero-inflated ordered probit model, with an application to modelling tobacco consumption
topic Social Sciences
Science & Technology
Physical Sciences
Economics
Mathematics, Interdisciplinary Applications
Social Sciences, Mathematical Methods
Business & Economics
Mathematics
Mathematical Methods In Social Sciences
ordered outcomes
discrete data
tobacco consumption
zero-inflated responses
COUNT DATA MODELS
SPECIFICATION TESTS
DEPENDENT VARIABLES
DEMAND
MARIJUANA
SELECTION
ALCOHOL
url http://hdl.handle.net/20.500.11937/81800