Volume 20 - Article 25 | Pages 599–622
Graduating the age-specific fertility pattern using Support Vector Machines
| Date received: | 22 May 2008 |
| Date published: | 03 Jun 2009 |
| Word count: | 2980 |
| Keywords: | age patterns of fertility, graduation techniques, parametric models of fertility, support vector machines |
| DOI: | 10.4054/DemRes.2009.20.25 |
Abstract
A topic of interest in demographic literature is the graduation of the age-specific fertility pattern. A standard graduation technique extensively used by demographers is to fit parametric models that accurately reproduce it. Non-parametric statistical methodology might be alternatively used for this graduation purpose. Support Vector Machines (SVM) is a non-parametric methodology that could be utilized for fertility graduation purposes. This paper evaluates the SVM techniques as tools for graduating fertility rates In that we apply these techniques to empirical age specific fertility rates from a variety of populations, time period, and cohorts. Additionally, for comparison reasons we also fit known parametric models to the same empirical data sets.
Author's Affiliation
Anastasia Kostaki - Athens University of Economics and Business, Greece
Javier Moguerza - Universidad Rey Juan Carlos, Spain
Alberto Olivares - Universidad Rey Juan Carlos, Spain
Stelios Psarakis - Athens University of Economics and Business, Greece
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