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Cohort Measures of Internal Migration: Understanding Long-Term Trends

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  • Aude Bernard

    (The University of Queensland
    Shanghai University)

Abstract

Internal migration intensities fluctuate over time, but both migration levels and trends show great diversity. The dynamics underpinning these trends remain poorly understood because they are analyzed almost exclusively by applying period measures to cross-sectional data. This article proposes 10 cohort measures that can be applied to both prospective and retrospective data to systematically examine long-term trends. To demonstrate their benefits, the proposed measures are applied to retrospective survey data for England that provide residential histories from birth to age 50 for cohorts born between 1918 and 1957. The analysis reveals stable lifetime migration for men but increased lifetime migration for women associated with earlier ages at moving in adulthood and a compression of intervals between consecutive moves. The proposed cohort measures provide a more comprehensive picture of migration behavior and should be used to complement period measures in exploring long-term trends. Increasing availability of retrospective and longitudinal survey data means that researchers can now apply the proposed measures to a wide range of countries.

Suggested Citation

  • Aude Bernard, 2017. "Cohort Measures of Internal Migration: Understanding Long-Term Trends," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2201-2221, December.
    • Handle: RePEc:spr:demogr:v:54:y:2017:i:6:d:10.1007_s13524-017-0626-7
    DOI: 10.1007/s13524-017-0626-7
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    Cited by:

    1. Aude Bernard & Alina Pelikh, 2019. "Distinguishing tempo and ageing effects in migration," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(44), pages 1291-1322.
    2. Aude Bernard & Martin Kolk, 2020. "Are Young Swedes Moving More? A Cohort Analysis of Internal Migration by Move Order," European Journal of Population, Springer;European Association for Population Studies, vol. 36(3), pages 601-615, July.
    3. Ben Sprung-Keyser & Nathaniel Hendren & Sonya Porter, 2022. "The Radius of Economic Opportunity: Evidence from Migration and Local Labor Markets," Working Papers 22-27, Center for Economic Studies, U.S. Census Bureau.
    4. Kosec, Katrina & Mo, Cecilia Hyunjung & Schmidt, Emily & Song, Jie, 2021. "Perceptions of relative deprivation and women’s empowerment," World Development, Elsevier, vol. 138(C).
    5. Yingxia Pu & Xinyi Zhao & Guangqing Chi & Jin Zhao & Fanhua Kong, 2019. "A spatial dynamic panel approach to modelling the space-time dynamics of interprovincial migration flows in China," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(31), pages 913-948.
    6. Haiyang Lu & Ivan T. Kandilov & Rong Zhu, 2022. "Does social integration matter for cohort differences in the political participation of internal migrants in China?," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1555-1573, August.
    7. Aude Bernard & Francisco Perales, 2021. "Is Migration a Learned Behavior? Understanding the Impact of Past Migration on Future Migration," Population and Development Review, The Population Council, Inc., vol. 47(2), pages 449-474, June.
    8. Jack DeWaard & Janna Johnson & Stephan Whitaker, 2019. "Internal migration in the United States: A comprehensive comparative assessment of the Consumer Credit Panel," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(33), pages 953-1006.

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