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Duration dependence and dispersion in count - data models


Winkelmann, Rainer (1995). Duration dependence and dispersion in count - data models. Journal of Business & Economic Statistics, 13(4):467-474.

Abstract

This paper explores the relation between non-exponential waiting times between events and the distribution of the number of events in a fixed time interval. It is shown that within this framework the frequently observed phenomenon of overdispersion, i.e. a variance that exceeds the mean, is caused by a decreasing hazard function of the waiting times, while an increasing hazard function leads to underdispersion. Using the assumption of i.i.d. gamma distributed waiting times, a new count data model is derived. Its use is illustrated in two applications: the number of births, and the number of doctor consultations.

This paper explores the relation between non-exponential waiting times between events and the distribution of the number of events in a fixed time interval. It is shown that within this framework the frequently observed phenomenon of overdispersion, i.e. a variance that exceeds the mean, is caused by a decreasing hazard function of the waiting times, while an increasing hazard function leads to underdispersion. Using the assumption of i.i.d. gamma distributed waiting times, a new count data model is derived. Its use is illustrated in two applications: the number of births, and the number of doctor consultations.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:1995
Deposited On:11 Feb 2008 12:21
Last Modified:05 Apr 2016 12:17
Publisher:American Statistical Association
ISSN:0735-0015
Publisher DOI:10.2307/1392392
Related URLs:http://links.jstor.org/sici?sici=0735-0015%28199510%2913%3A4%3C467%3ADDADIC%3E2.0.CO%3B2-V
http://www.jstor.org/view/07350015/ap050052/05a00140/0
Permanent URL: http://doi.org/10.5167/uzh-1190

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