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In search of a modelling strategy for projecting internal migration in European countries - Demographic versus economic-geographical approaches

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  • Leo JG Van Wissen
  • Nicole Gaag
  • Phil Rees
  • John Stillwell

Abstract

Internal migration is the most volatile and difficult to predict component of regional demographic change. A pure demographic approach using age and sex-specific parameters of migration intensities cannot fully capture the migration trends over time. One of the approaches that can be used for a better description of past trends and forecasting of future trends is to use additional non-demographic information such as regional economic indicators. In this paper we compare the predictive performance of pure demographic and extended economic-geographical models using data of four European countries at the so-called NUTS 2 level. The models are nested within a GLM specification%2C that allows both demographic and extended models to be written as specific cases of loglinear models. Therefore model fit and performance can be compared directly.

Suggested Citation

  • Leo JG Van Wissen & Nicole Gaag & Phil Rees & John Stillwell, 2005. "In search of a modelling strategy for projecting internal migration in European countries - Demographic versus economic-geographical approaches," ERSA conference papers ersa05p787, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa05p787
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    2. A Stewart Fotheringham & Phil Rees & Tony Champion & Stamatis Kalogirou & Andy R Tremayne, 2004. "The Development of a Migration Model for England and Wales: Overview and Modelling Out-Migration," Environment and Planning A, , vol. 36(9), pages 1633-1672, September.
    3. Andrei Rogers, 1967. "Matrix Analysis Of Interregional Population Growth And Distribution," Papers in Regional Science, Wiley Blackwell, vol. 18(1), pages 177-196, January.
    4. P H Rees & A G Wilson, 1973. "Accounts and Models for Spatial Demographic Analysis I: Aggregate Population," Environment and Planning A, , vol. 5(1), pages 61-90, February.
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