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Stochastic Population Projection for Germany

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Author Info

  • Oliver Lipps

    ()

  • Frank Betz

    ()
    (Munich Center for the Economics of Aging (MEA))

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    Abstract

    This contribution builds upon a former paper by the authors (Lipps and Betz 2004), in which a stochastic population projection for East- and West Germany is performed. Aim was to forecast relevant population parameters and their distribution in a consistent way. We now present some modifications, which have been modelled since. First, population parameters for the entire German population are modelled. In order to overcome the modelling problem of the structural break in the East during reunification, we show that the adaptation process of the relevant figures by the East can be considered to be completed by now. As a consequence, German parameters can be modelled just by using the West German historic patterns, with the start-off population of entire Germany. Second, a new model to simulate age specific fertility rates is presented, based on a quadratic spline approach. This offers a higher flexibility to model various age specific fertility curves. The simulation results are compared with the scenario based official forecasts for Germany in 2050. Exemplary for some population parameters (e.g. dependency ratio), it can be shown that the range spanned by the medium and extreme variants correspond to the s-intervals in the stochastic framework. It seems therefore more appropriate to treat this range as a s-interval covering about two thirds of the true distribution.

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    Bibliographic Info

    Paper provided by Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy in its series MEA discussion paper series with number 04059.

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    Date of creation: 22 Sep 2004
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    Handle: RePEc:mea:meawpa:04059

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    Postal: Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy, Amalienstraße 33, 80799 München, Germany
    Phone: +49/89/38602.442
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    Cited by:
    1. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    2. Fuchs, Johann & Söhnlein, Doris, 2006. "Effekte alternativer Annahmen auf die prognostizierte Erwerbsbevölkerung," IAB Discussion Paper 200619, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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