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Timing, sequencing and quantum of life course events: a machine learning approach

  • Francesco C. Billari

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Johannes Fürnkranz
  • Alexia Prskawetz

    (Max Planck Institute for Demographic Research, Rostock, Germany)

In this methodological paper we discuss and apply machine learning tech-niques, a core research area in the artificial intelligence literature, to analyse simultaneously timing, sequencing, and quantum of life course events from a comparative perspective. We outline the need for techniques which allow the adoption of a holistic approach to the analysis of life courses, illustrating the specific case of the transition to adulthood. We briefly introduce machine learning algorithms to build decision trees and rule sets and then apply such algorithms to delineate the key features which distinguish Austrian and Ital-ian pathways to adulthood, using Fertility and Family Survey data. The key role of sequencing and synchronisation between events emerges clearly from the methodology used. [AUTHORS]

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File URL: http://www.demogr.mpg.de/Papers/Working/wp-2000-010.pdf
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File URL: http://www.ofai.at/cgi-bin/tr-online?number+2000-30
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Paper provided by Max Planck Institute for Demographic Research, Rostock, Germany in its series MPIDR Working Papers with number WP-2000-010.

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Length: - pages
Date of creation: Oct 2000
Date of revision:
Handle: RePEc:dem:wpaper:wp-2000-010
Contact details of provider: Web page: http://www.demogr.mpg.de/

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  1. Courgeau, Daniel & Lelievre, Eva, 1993. "Event History Analysis in Demography," OUP Catalogue, Oxford University Press, number 9780198287384.
  2. Lillard, Lee A., 1993. "Simultaneous equations for hazards : Marriage duration and fertility timing," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 189-217, March.
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