Graduating the age-specific fertility pattern using Support Vector Machines

Anastasia Kostaki, Javier Moguerza, Alberto Olivares and Stelios Psarakis
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Anastasia Kostaki: Athens University of Economics and Business
Javier Moguerza: Universidad Rey Juan Carlos
Alberto Olivares: Universidad Rey Juan Carlos
Stelios Psarakis: Athens University of Economics and Business

Demographic Research, 2009, vol. 20, issue 25, 599-622

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.

Keywords: age patterns of fertility; graduation techniques; support vector machines; parametric models of fertility (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:dem:demres:v:20:y:2009:i:25

DOI: 10.4054/DemRes.2009.20.25

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