This article presents a categorical model of fertility based on the statistical theory of the Generalised Linear Model (GLM). Focussing on the individual probability of giving birth to a child, we derive distributions which can be embedded in a GLM framework. A major advance of that methodology is the knowledge of the distribution of the random variable, which leads to a Maximum Likelihood estimation procedure. The approach takes into account the smooth shapes of parameter development over the age of the mother as well as over time. The estimation of this semi-parametric approach is done using the Local-Likelihood-method. The presented method provides stable results of the fertility, especially for smaller populations. This is illustrated by using a data set which consists of less than 100,000 inhabitants.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Length: Date of creation: 30 Jun 2006 Date of revision: Handle: RePEc:bay:rdwiwi:677
Note: This paper is part of http://www.opus-bayern.de/uni-regensburg/schriftenreihen_ebene2.php?sr_id=3 Contact details of provider: Postal: D-93040 Regensburg Phone: +49 941 943-2392 Fax: +49 941 943-4752 Email: Web page: http://www.wiwi.uni-regensburg.de/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Marc Reymann) The email address of this maintainer does not seem to be valid anymore. Please ask Marc Reymann to update the entry or send us the correct address..
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.: