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Determinants of Fertility - An Application of Machine Learning Techniques

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Schäfer, C., Schmitt, C. Determinants of Fertility - An Application of Machine Learning Techniques. Journal of Contextual Economics – Schmollers Jahrbuch, 127(1), 127-138. https://doi.org/10.3790/schm.127.1.127
Schäfer, Christin and Schmitt, Christian "Determinants of Fertility - An Application of Machine Learning Techniques" Journal of Contextual Economics – Schmollers Jahrbuch 127.1, 2007, 127-138. https://doi.org/10.3790/schm.127.1.127
Schäfer, Christin/Schmitt, Christian (2007): Determinants of Fertility - An Application of Machine Learning Techniques, in: Journal of Contextual Economics – Schmollers Jahrbuch, vol. 127, iss. 1, 127-138, [online] https://doi.org/10.3790/schm.127.1.127

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Determinants of Fertility - An Application of Machine Learning Techniques

Schäfer, Christin | Schmitt, Christian

Journal of Contextual Economics – Schmollers Jahrbuch, Vol. 127 (2007), Iss. 1 : pp. 127–138

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Article Details

Schäfer, Christin

Schmitt, Christian

Abstract

The paper at hand applies machine learning techniques to investigate first birth transitions. The methods do not rely an distribution assumptions and require only few preconditions for application. The results are compatible with contemporary demographic research, highlighting - among other factors - the Status of relationship, income and the distribution of labour in the farnily. Machine learning techniques may thus be used as explorative method in the social sciences as well as tool for an in-depth analysis in future research as they are especially suited to process large data sets.