UZH-Logo

Maintenance Infos

Count data models for demographic data.


Winkelmann, Rainer; Zimmermann, Klaus F (1994). Count data models for demographic data. Mathematical Population Studies, 4(3):205-221.

Abstract

Key demographic variables, such as the number of children and the number of marriages or divorces, can only take integer values. This papers deals with the estimation of single equation models in which the counts are regressed on a set of observed individual characteristics such as age, gender, or nationality. Most empirical work in population economics has neglected the fact that the dependent variable is a nonnegative integer. In the few cases where this feature was recognized, the authors advocated the use of the Poisson regression model. The Poisson model imposes, however, the equality of conditional mean and variance, a restriction which is often rejected by the data. We propose a generalized event count model to simultaneously allow for a wide class of count data models and account for over- and underdispersion. This model is successfully applied to German data on fertility, divorces and mobility.

Key demographic variables, such as the number of children and the number of marriages or divorces, can only take integer values. This papers deals with the estimation of single equation models in which the counts are regressed on a set of observed individual characteristics such as age, gender, or nationality. Most empirical work in population economics has neglected the fact that the dependent variable is a nonnegative integer. In the few cases where this feature was recognized, the authors advocated the use of the Poisson regression model. The Poisson model imposes, however, the equality of conditional mean and variance, a restriction which is often rejected by the data. We propose a generalized event count model to simultaneously allow for a wide class of count data models and account for over- and underdispersion. This model is successfully applied to German data on fertility, divorces and mobility.

Citations

Altmetrics

Downloads

309 downloads since deposited on 11 Feb 2008
30 downloads since 12 months
Detailed statistics

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:1 February 1994
Deposited On:11 Feb 2008 12:21
Last Modified:05 Apr 2016 12:17
Publisher:Taylor & Francis
ISSN:0889-8480
Additional Information:This is an electronic version of an article published in Math Popul Stud 1994, 4(3):205-21, 223. Math Popul Stud is available online at http://www.informaworld.com/smpp/title~content=t713644738~db=all
Publisher DOI:10.1080/08898489409525374
PubMed ID:12287090
Permanent URL: http://doi.org/10.5167/uzh-1191

Download

[img]
Preview
Content: Accepted Version
Filetype: PDF
Size: 287kB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations