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MAPLES: a general method for the estimation of age profiles from standard demographic surveys (with an application to fertility)

Author

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  • Roberto IMPICCIATORE

    ()

  • Francesco C. BILLARI

    ()

Abstract

In this paper we present MAPLES (Method for Age Profiles Longitudinal EStimation), a general method for the estimation of age profiles that uses standard micro-level demographic survey data. The aim is to estimate smoothed age profiles and relative risks for time-fixed and time-varying covariates. MAPLES is implemented through a data processing routine and a series of regressions using GAM (Generalized Additive Models). Although the approach has been developed to be applied in the field of living arrangements and fertility, MAPLES may be used for any kind of life events. In fact, it can be applied to every setting where micro-level data on transitions are available from a large-scale representative survey (e. g. , Demographic and Health Surveys; Fertility and Family Surveys; Generations and Gender Surveys). MAPLES is implemented through the R software and includes a set of commands that can be easily applied and that may constitute a useful tool box for demographers and social scientists.

Suggested Citation

  • Roberto IMPICCIATORE & Francesco C. BILLARI, 2010. "MAPLES: a general method for the estimation of age profiles from standard demographic surveys (with an application to fertility)," Departmental Working Papers 2010-40, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  • Handle: RePEc:mil:wpdepa:2010-40
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    References listed on IDEAS

    as
    1. Matsuo, Hideko & Willekens, Frans, 2003. "Event histories in the Netherlands Fertility and Family Survey 1998. A technical report," Research Reports 03-01, University of Groningen, Population Research Centre (PRC).
    2. Anna Christina D'Addio & Michael Rosholm, "undated". "Left-Censoring in Duration Data: Theory and Applications," Economics Working Papers 2002-5, Department of Economics and Business Economics, Aarhus University.
    3. Donald McNeil & T. Trullell & John Turner, 1977. "Spline interpolation of demographic oata," Demography, Springer;Population Association of America (PAA), vol. 14(2), pages 245-252, May.
    4. repec:dgr:rugprc:03-01 is not listed on IDEAS
    5. Carl Schmertmann, 2003. "A system of model fertility schedules with graphically intuitive parameters," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 9(5), pages 81-110, October.
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    Cited by:

    1. Frans Poppel & Niels Schenk & Ruben Gaalen, 2013. "Demographic Transitions and Changes in the Living Arrangements of Children: The Netherlands 1850–2010," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(2), pages 243-260, April.
    2. Nicole L. Van Der Gaag & Govert Bijwaard & Joop de Beer & Luc Bonneux, 2015. "A multistate model to project elderly disability in case of limited data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(3), pages 75-106, January.

    More about this item

    Keywords

    Age profiles; transition rates; fertility and living arrangements; general additive models; smoothing procedure.;

    JEL classification:

    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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