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Regional migration and the dimension of distance in empirical analysis

Author

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  • Lucie Kurekova

    (Cevro Institut, Center for Economic Studies)

Abstract

The phenomenon of migration is addressed by several disciplines, such as demography, sociology, economics, political science and history. Therefore, a wide range of analytical tools can be used to analyse this phenomenon. This study focuses primarily on regional migration and capturing the dimension of distance in empirical analysis. Cartograms can be used to analyse regional migration, and Webb diagrams that capture the evolution of net international and internal migration over time. It is also appropriate to use the efficiency matrix of migration indices and nodal graphs to analyse migration flows between different regions. Spatial econometrics is then important for migration analysis to test the validity of theoretical concepts of migration. However, it is often not possible to track the exact distance of migration flows in the data. Therefore, it is necessary to resort to proxy methods to determine the distance. Tracking internal migration plays a crucial role in regional development and is vital in assessing political, economic and social change. Therefore, appropriate analytical tools must be used to analyse it at the regional level.

Suggested Citation

  • Lucie Kurekova, 2022. "Regional migration and the dimension of distance in empirical analysis," International Journal of Economic Sciences, European Research Center, vol. 11(2), pages 80-91, November.
    • Handle: RePEc:aop:jijoes:v:11:y:2022:i:2:p:80-91
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    References listed on IDEAS

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    1. Jonathan Azose & Adrian Raftery, 2015. "Bayesian Probabilistic Projection of International Migration," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1627-1650, October.
    2. Lucie Kurekova & Pavlina Hejdukova, 2021. "Multilevel research of migration with a focus on internal migration," International Journal of Economic Sciences, European Research Center, vol. 10(2), pages 86-102, December.
    3. Jacob L. Vigdor, 2002. "Locations, Outcomes, and Selective Migration," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 751-755, November.
    4. Lucie Kurekova & Pavlina Hejdukova, 2021. "Multilevel research of migration with a focus on internal migration," International Journal of Economic Sciences, European Research Center, vol. 10(2), pages 87-103, December.
    5. Michael P. Cameron & Jacques Poot, 2019. "The estimation and interpretation of coefficients in panel gravity models of migration," Letters in Spatial and Resource Sciences, Springer, vol. 12(1), pages 9-15, April.
    6. Grogger, Jeffrey & Hanson, Gordon H., 2011. "Income maximization and the selection and sorting of international migrants," Journal of Development Economics, Elsevier, vol. 95(1), pages 42-57, May.
    7. Arbia, Giuseppe, 2016. "Spatial Econometrics: A Broad View," Foundations and Trends(R) in Econometrics, now publishers, vol. 8(3-4), pages 145-265, November.
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    Cited by:

    1. Jun He & Yongxiang Xie, 2024. "Health Bonus of Migrating to Higher Tier Cities: Evidence From China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(1), pages 71-88, October.

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    More about this item

    Keywords

    Migration; labor market; statistical indicators; model;
    All these keywords.

    JEL classification:

    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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