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A Study of the Socioeconomic Factors Influencing Migration in Russia

Author

Listed:
  • Li Wang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands)

  • Jixia Huang

    (Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China)

  • Hongyan Cai

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Hengzi Liu

    (University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jinmei Lu

    (Department of Engineering and Safety, The Arctic University of Norway, 9037 Tromso, Norway)

  • Linsheng Yang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Russia has experienced population decline in years and the economic development in Russia is largely restricted by labor shortage, particularly for the Far North and East region. In order to explore the migration mechanisms, six socioeconomic factors were selected to explore the influences on the net migration. Data from the 82 regions covering four time periods (2000, 2005, 2010 and 2015) was processed use spatial panel econometric analysis and the time-period fixed effects Spatial Durbin Model (SDM) was selected as the best fit model after tests. The results indicates that, unemployment and infant death rate are significantly negatively associated with net migration, while urbanization rate, urban scale and life expectancy are significantly positively associated with net migration; every 100 USD increase in per capita GRP (Gross Regional Product) is positively related with averagely 5.4 net migrates in the region; every 1 year increase in life expectancy would increase 1052 net migrates; every 1sqm increase in urban scale would increase the net migrates by 11.75 and every 1% increase in unemployment would lead to a decrease of 0.54 net migrates. Spillover effect was also found for per capita GRP and life expectancy, indicating that the increase of per capita GRP and life expectancy in neighboring regions can also increase the attractiveness in one region. It can be concluded that better job market, better economic status and health related wellbeing are all attracting factors for migrates and these factors can even make the neighborhood region more attractive for immigrates. Considering the ambitious development plan for the Russia Far North and East regions, related suggestions on attracting migrates are provided.

Suggested Citation

  • Li Wang & Jixia Huang & Hongyan Cai & Hengzi Liu & Jinmei Lu & Linsheng Yang, 2019. "A Study of the Socioeconomic Factors Influencing Migration in Russia," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1650-:d:215240
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    References listed on IDEAS

    as
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    Cited by:

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    2. Li, Baoxi & Cheng, Shixiong & Xiao, De, 2020. "The impacts of environmental pollution and brain drain on income inequality," China Economic Review, Elsevier, vol. 62(C).
    3. Amina Chanysheva & Pierre Kopp & Natalia Romasheva & Anni Nikulina, 2021. "Migration Attractiveness as a Factor in the Development of the Russian Arctic Mineral Resource Potential," Resources, MDPI, vol. 10(6), pages 1-25, June.
    4. Elena Batunova & Giovanni Perucca, 2020. "Population shrinkage and economic growth in Russian regions 1998–2012," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(4), pages 595-609, August.
    5. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    6. Elena Bogdanova & Konstantin Filant & Ekaterina Sukhova & Maria Zabolotnikova & Praskovia Filant & Dele Raheem & Olga Shaduyko & Sergei Andronov & Andrey Lobanov, 2022. "The Impact of Environmental and Anthropogenic Factors on the Migration of the Rural Arctic Population of Western Siberia," Sustainability, MDPI, vol. 14(12), pages 1-17, June.

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