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Individual Ability and Selection into Migration in Kenya

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  • Miguel, Edward
  • Hamory, Joan

Abstract

This study exploits a new longitudinal dataset to examine selective migration among 1,500 Kenyan youth originally living in rural areas. We examine whether migration rates are related to individual “ability”, broadly defined to include cognitive aptitude as well as health, and then use these estimates to determine how much of the urban-rural wage gap in Kenya is due to selection versus actual productivity differences. Whereas previous empirical work has focused on schooling attainment as a proxy for cognitive ability, we employ an arguably preferable measure, a pre-migration primary school academic test score. Pre-migration randomized assignment to a deworming treatment program provides variation in health status. We find a positive relationship between both measures of human capital (cognitive ability and deworming) and subsequent migration, though only the former is robust at standard statistical significance levels. Specifically, an increase of two standard deviations in academic test score increases the likelihood of rural-urban migration by 17%. Accounting for migration selection due to both cognitive ability and schooling attainment does not explain more than a small fraction of the sizeable urban-rural wage gap in Kenya, suggesting that productivity differences across sectors remain large.

Suggested Citation

  • Miguel, Edward & Hamory, Joan, 2009. "Individual Ability and Selection into Migration in Kenya," MPRA Paper 19228, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:19228
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    References listed on IDEAS

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    4. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    5. International Monetary Fund, 2005. "Kenya: Report on the Observance of Standards and Codes (ROSC) Data Module," IMF Staff Country Reports 2005/388, International Monetary Fund.
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    Cited by:

    1. Douglas Gollin & David Lagakos & Michael E. Waugh, 2011. "The Agricultural Productivity Gap in Developing Countries," Working Papers 11-14, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Eric Kramon & Sarah Baird & Joan Hamory & Edward Miguel, 2021. "Deepening or Diminishing Ethnic Divides? The Impact of Urban Migration in Kenya," Working Papers 2021-08, The George Washington University, Institute for International Economic Policy.
    3. Kempe Ronald Hope Sr., 2012. "Urbanisation in Kenya," African Journal of Economic and Sustainable Development, Inderscience Enterprises Ltd, vol. 1(1), pages 4-26.
    4. Wim Naudé, 2016. "Entrepreneurship and the Reallocation of African Farmers," Agrekon, Taylor & Francis Journals, vol. 55(1-2), pages 1-33, June.
    5. Maurice Schiff, 2017. "Ability drain: size, impact, and comparison with brain drain under alternative immigration policies," Journal of Population Economics, Springer;European Society for Population Economics, vol. 30(4), pages 1337-1354, October.
    6. Douglas Gollin & David Lagakos & Michael E. Waugh, 2014. "The Agricultural Productivity Gap," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(2), pages 939-993.
    7. Jonathan Colmer, 2021. "Temperature, Labor Reallocation, and Industrial Production: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 13(4), pages 101-124, October.
    8. Mike Waugh & Ahmed Mobarak & David Lagakos, 2016. "Urban-Rural Wage Gaps in Developing Countries: Spatial Misallocation or Efficient Sorting?," 2016 Meeting Papers 1032, Society for Economic Dynamics.
    9. Colmer, Jonathan, 2018. "Weather, labor reallocation and industrial production: evidence from India," LSE Research Online Documents on Economics 88695, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    Migration; selection; human capital; ability; urban-rural wage gap; productivity;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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