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Comparing Internal Migration Between Countries Using Courgeau’s k

  • Martin BellEmail author
  • Salut Muhidin
Chapter
Part of the Understanding Population Trends and Processes book series (UPTA, volume 4)

Abstract

Building on recent work for the 2009 UN Human Development Report, this chapter aims to explore one of the measures identified in a recent review by Bell et al. (Journal of the Royal Statistical Society A 165(3):435–464, 2002), as originally proposed by Courgeau (Population 28:511–537, 1973a). The particular appeal of Courgeau’s ‘k’ statistic is that it purports to provide a single summary index of migration intensity which transcends the differences in zonal systems that commonly confound cross-national comparisons. Courgeau’s k is applied to examine differences in mobility between 27 countries, using census data drawn primarily from the Integrated Public Use Microdata Series (IPUMS) database maintained by the University of Minnesota. Our goals of the chapter are threefold: first, to establish the strengths and limitations of Courgeau’s k as a summary measure of internal migration; second, to identify the extent of international differences in mobility; and third, to determine the general trajectory of internal migration over time.

Keywords

Internal Migration Population Mobility Modifiable Areal Unit Problem Zonal System Migration Intensity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This chapter draws on work undertaken for the United Nations Development Programme 2009 Human Development Report Overcoming Barriers: Human Mobility and Development (see http://hdr.undp.org/en/). We are grateful for permission to utilise here some of the material assembled for that project. The majority of the data utilised here are drawn from the Integrated Public Use Microdata Series (IPUMS) maintained by the Minnesota Population Center at the University of Minnesota: we are grateful to the IPUMS team for facilitating access to these data. We also thank colleagues at the United Nations Development Programme for facilitating access to data for China and India.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.School of Geography, Planning and Environmental Management, University of QueenslandQueenslandAustralia
  2. 2.Demography Program at Department of BusinessMacquarie UniversityNorth Ryde-SydneyAustralia

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