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Long-Term Impact of Interregional Migrants on Population Prediction

Author

Listed:
  • Sebal Oo

    (Department of Civil and Environmental Engineering, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan)

  • Makoto Tsukai

    (Department of Civil and Environmental Engineering, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan)

Abstract

Japan is becoming depopulated, with declining fertility rates and massive urban agglomeration due to emigrations from rural areas, which results in rural–urban disparities. As demographic and social divisions between rural and urban areas increase, maintenance of infrastructure and social facilities becomes much more difficult. For social and demographic sustainability, accurate predictions of long-term population distributions are needed. This study improves the Cohort Component Analysis (CCA) into two aspects of “dependent structure” in the model system. The migration sub-model is expanded to include related structures between available job opportunities and the available workforce in each region, which are specified using the spatial autoregressive model. The advantage of the improved CCA to provides rational future projections by considering the longitudinal changes in the spatial distribution of the workforce. The simulation of the proposed model gives an alternative long-term impact of population distribution in Japan, which is compared with the conventional CCA. The results show that the future Japanese populations will become more concentrated in urban areas, with a lower fertility rate. Furthermore, the manufacturing employees will be attracted to metropolitan areas or to regions with industrial zones, and that the number of retailers will undergo changes over time, even in urbanized areas.

Suggested Citation

  • Sebal Oo & Makoto Tsukai, 2022. "Long-Term Impact of Interregional Migrants on Population Prediction," Sustainability, MDPI, vol. 14(11), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6580-:d:825808
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