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

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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.

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File URL: http://wp.demm.unimi.it/tl_files/wp/2010/DEMM-2010_040wp.pdf
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Bibliographic Info

Paper provided by Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano in its series Departmental Working Papers with number 2010-40.

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Date of creation: 04 Dec 2010
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Handle: RePEc:mil:wpdepa:2010-40

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Related research

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

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  1. Anna Christina D'Addio & Michael Rosholm, . "Left-Censoring in Duration Data: Theory and Applications," Economics Working Papers 2002-5, School of Economics and Management, University of Aarhus.
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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, vol. 32(2), pages 243-260, April.

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