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Floating Population: Migration With(Out) Family and the Spatial Distribution of Economic Activity

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Abstract

This paper argues that migrants’ decision to bring their dependent family members shapes their consumption behavior, their choice of destination, and their sensitivity to migration barriers. We document that in China: (i) rural migrants disproportionately move to expensive cities; (ii) in these cities they live without their family and in poorer housing conditions; and (iii) they remit more, especially when living without their family. We then develop a quantitative general equilibrium spatial model in which migrant households choose whether, how (with or without their family), and where to migrate. We estimate the model using plausibly exogenous variation in wages, housing prices, and exposure to family migration costs. We use the model to estimate migration costs and relate them to migration policy. We find that hukou policies protect workers in large, expensive, and high income cities at the expense of rural households, who use remittances to overcome some of these costs.

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  • Clément Imbert & Joan Monras & Marlon Seror & Yanos Zylberberg, 2023. "Floating Population: Migration With(Out) Family and the Spatial Distribution of Economic Activity," Working Paper Series 2023-26, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:96924
    DOI: 10.24148/wp2023-26
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    1. Gabriel M. Ahlfeldt & Stephen J. Redding & Daniel M. Sturm & Nikolaus Wolf, 2015. "The Economics of Density: Evidence From the Berlin Wall," Econometrica, Econometric Society, vol. 83, pages 2127-2189, November.
    2. Clement Imbert & Marlon Seror & Yifan Zhang & Yanos Zylberberg, 2022. "Migrants and Firms: Evidence from China," American Economic Review, American Economic Association, vol. 112(6), pages 1885-1914, June.
    3. Treb Allen & Costas Arkolakis, 2014. "Trade and the Topography of the Spatial Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1085-1140.
    4. Trevor Tombe & Xiaodong Zhu, 2019. "Trade, Migration, and Productivity: A Quantitative Analysis of China," American Economic Review, American Economic Association, vol. 109(5), pages 1843-1872, May.
    5. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, vol. 67(2), pages 251-334, March.
    6. Chang-Tai Hsieh & Enrico Moretti, 2019. "Housing Constraints and Spatial Misallocation," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(2), pages 1-39, April.
    7. Loren Brandt & Trevor Tombe & Xiadong Zhu, 2013. "Factor Market Distortions Across Time, Space, and Sectors in China," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 39-58, January.
    8. Loren Brandt & Trevor Tombe & Xiadong Zhu, 2013. "Factor Market Distortions Across Time, Space, and Sectors in China," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 39-58, January.
    9. Song, Yang, 2014. "What should economists know about the current Chinese hukou system?," China Economic Review, Elsevier, vol. 29(C), pages 200-212.
    10. Luo, Changyuan & Si, Chunxiao & Zhang, Hongyong, 2022. "Moving out of China? Evidence from Japanese multinational firms," Economic Modelling, Elsevier, vol. 110(C).
    11. Démurger, Sylvie & Wang, Xiaoqian, 2016. "Remittances and expenditure patterns of the left behinds in rural China," China Economic Review, Elsevier, vol. 37(C), pages 177-190.
    12. Cai, Guowei & Zhang, Xuejiao & Yang, Hao, 2022. "Fiscal stress and the formation of zombie firms: Evidence from China," China Economic Review, Elsevier, vol. 71(C).
    13. Tabuchi, Takatoshi, 1998. "Urban Agglomeration and Dispersion: A Synthesis of Alonso and Krugman," Journal of Urban Economics, Elsevier, vol. 44(3), pages 333-351, November.
    14. Fan, Yunqi & Xu, Zijing, 2022. "Audit firm's Confucianism and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 79(C).
    15. Yu Bai & Linxiu Zhang & Chengfang Liu & Yaojiang Shi & Di Mo & Scott Rozelle, 2018. "Effect of Parental Migration on the Academic Performance of Left Behind Children in North Western China," Journal of Development Studies, Taylor & Francis Journals, vol. 54(7), pages 1154-1170, July.
    16. Shuai Chen & Paulina Oliva & Peng Zhang, 2017. "The Effect of Air Pollution on Migration: Evidence from China," NBER Working Papers 24036, National Bureau of Economic Research, Inc.
    17. Zhang, Jipeng & Huang, Jin & Wang, Junhui & Guo, Liang, 2020. "Return migration and Hukou registration constraints in Chinese cities," China Economic Review, Elsevier, vol. 63(C).
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    1. Bruno Conte, 2022. "Climate Change and Migration: The Case of Africa," CESifo Working Paper Series 9948, CESifo.

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    More about this item

    Keywords

    migration; remittances; economic geography; spatial equilibrium;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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