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Un indice synthétique de fécondité enrichi à partir des données de panel

Author

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  • Gustavo De Santis
  • Sven Drefahl
  • Daniele Vignoli

Abstract

Hoem and Mure?an (2011a) have recently shown that the most widely used macro-level indicator of fertility, the total fertility rate (TFR), can be reconciled with fertility estimates that derive from applications of event history analysis (EHA) to micro-data. The purpose of this paper is to extend their ideas and show that they can be usefully applied to short panels, i.e. when the same people are interviewed in two or more successive rounds over a very limited number of years. This method can also be applied to data collected for general purposes and not strictly for demographic research, including data of an economic nature (employment, income, geographic or professional mobility, etc.). Despite the absence of questions on fertility, group-specific fertility estimates can be obtained that are not otherwise available (e.g. fertility by income level before the birth of the child), which are not biased by memory or selection of respondents and can be made consistent with the TFR observed in that period for the entire population. An application to Italian EU-SILC data in the years 2004-2007 highlights the advantages and the limitations of the method.

Suggested Citation

  • Gustavo De Santis & Sven Drefahl & Daniele Vignoli, 2014. "Un indice synthétique de fécondité enrichi à partir des données de panel," Population (french edition), Institut National d'Études Démographiques (INED), vol. 69(3), pages 463-476.
    • Handle: RePEc:cai:popine:popu_1403_0463
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    Citations

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    Cited by:

    1. Angela Greulich & Aurélien Dasre, 2017. "The quality of periodic fertility measures in EU-SILC," Post-Print hal-01726581, HAL.
    2. Angela Greulich & Aurélien Dasré, 2017. "The quality of periodic fertility measures in EU-SILC," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(17), pages 525-556.
    3. Angela Greulich & Aurélien Dasré, 2017. "Fertility Analysis with EU-SILC: A Quantification of Measurement Bias," Documents de travail du Centre d'Economie de la Sorbonne 17002, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Angela Greulich & Aurélien Dasre, 2017. "Fertility Analysis with EU-SILC: A Quantification of Measurement Bias," Post-Print halshs-01440519, HAL.
    5. Angela Greulich & Aurélien Dasre, 2017. "The quality of periodic fertility measures in EU-SILC," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01726581, HAL.

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