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Integrated Modelling of European Migration: Background, specification and results

Author

Listed:
  • James Raymer

    () (University of Southampton)

  • Jonathan J. Forster

    (University of Southampton)

  • Peter W.F Smith

    (University of Southampton)

  • Jakub Bijak

    (University of Southampton)

  • Arkadiusz Wiśniowski

    (University of Southampton)

Abstract

The aims of this paper are to present the background and specification of the Integrated Modelling of European Migration (IMEM) model. Currently, international migration data are collected by individual countries with separate collection systems and designs. This creates problems when attempting to understand or predict population movements between countries as the reported data are inconsistent in terms of their availability, definitions and quality. Rather than wait for countries to harmonise their migration data collection and reporting systems, we propose a model to overcome the limitations of the various data sources. In particular, we propose a Bayesian model for harmonising and correcting the inadequacies in the available data and for estimating the completely missing flows. The focus is on estimating recent international migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA) from 2002 to 2008, using data collected by Eurostat and other national and international institutions. We also include additional information provided by experts on the effects of undercount, measurement and accuracy. The methodology is integrated and capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Suggested Citation

  • James Raymer & Jonathan J. Forster & Peter W.F Smith & Jakub Bijak & Arkadiusz Wiśniowski, 2012. "Integrated Modelling of European Migration: Background, specification and results," Norface Discussion Paper Series 2012004, Norface Research Programme on Migration, Department of Economics, University College London.
  • Handle: RePEc:nor:wpaper:2012004
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    Cited by:

    1. Cate Arie ten, 2014. "The Identification of Reporting Accuracies from Mirror Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(1), pages 70-84, February.

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