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Migration as an Adaptation Strategy to Weather Variability: An Instrumental Variables Probit Analysis

Author

Listed:
  • Yonas Alem

    (GU - Göteborgs Universitet = University of Gothenburg)

  • Mathilde Maurel

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Katrin Millock

    (PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

There is solid scientific evidence predicting that a large part of the developing world will suffer a greater incidence of extreme weather events, which may increase displacement migration. We draw on the new economics of migration to model migration decisions of smallholder and rain-dependent farm households in rural Ethiopia and investigate both the ex-ante and ex-post impacts of climate variables. Using detailed household survey panel data matched with rainfall data, we show that weather variability - measured by the coefficient of variation of rainfall - has a strong positive impact on the probability of sending a migrant. This implies that households engage in migration to cope with risk ex-ante. We also find evidence suggesting that rainfall shocks have ex-post impact on households' likelihood of migration, but the effect is not significant at the conventional levels. Instrumental variables probit regression results also show that controlling for endogeneity of income using a credible instrument is important to identify its impact on the decision to migrate. Our findings have important implications for policies aiming to improve the capacity of vulnerable households to adapt to climate change.

Suggested Citation

  • Yonas Alem & Mathilde Maurel & Katrin Millock, 2018. "Migration as an Adaptation Strategy to Weather Variability: An Instrumental Variables Probit Analysis," PSE-Ecole d'économie de Paris (Postprint) halshs-01885449, HAL.
  • Handle: RePEc:hal:pseptp:halshs-01885449
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    Cited by:

    1. Olper, A. & Falco, C. & Galeotti, M., 2018. "Climate Change, Agriculture and Migration: Is there a Causal Relationship ?," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277488, International Association of Agricultural Economists.
    2. Kuhnt, Jana, 2019. "Literature review: drivers of migration. Why do people leave their homes? Is there an easy answer? A structured overview of migratory determinants," IDOS Discussion Papers 9/2019, German Institute of Development and Sustainability (IDOS).
    3. Chiara Falco & Franco Donzelli & Alessandro Olper, 2018. "Climate Change, Agriculture and Migration: A Survey," Sustainability, MDPI, vol. 10(5), pages 1-21, May.

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    More about this item

    Keywords

    climate change; drought; Ethiopia; household survey; migration; rainfall;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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