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EXTENSIONS OF HURDLE MODELS FOR OVERDISPERSED COUNT DATA
Author(s) -
Farbmacher Helmut
Publication year - 2013
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.2892
Subject(s) - count data , econometrics , computer science , relevance (law) , parametric model , parametric statistics , economics , statistics , mathematics , poisson distribution , political science , law
ABSTRACT Hurdle models are frequently used to model count data. Recent developments in the count data literature make it possible to relax commonly imposed assumptions of these models. On the basis of these findings, two extensions of hurdle models that make popular specifications more flexible are developed. Both extensions nest the models that have been used so far, so they can be tested by appropriate parametric restrictions. An example from health economics illustrates the relevance of both model extensions. Copyright © 2012 John Wiley & Sons, Ltd.

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