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Do more Vibrant Rural Areas have Lower Rates of Youth Out-Migration? Evidence from Zambia

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Abstract

We use nationally representative survey data from Zambia to evaluate whether rural youth out-migration is associated with a lack of rural economic vibrancy, as often asserted in policy discussion. After controlling for distance from markets, we do find some evidence that areas with more productive and market-oriented agriculture are associated with lower rates of out-migration, particularly for those who leave explicitly to find work. However, measures of non-farm orientation of the local economy are positively associated with out-migration, indicating that the sectoral composition of the local economy has some bearing on the relationship between vibrancy and migration. When we examine more disaggregated patterns, we find that the out-migration decisions of young males are particularly responsive to rural vibrancy conditions. However, we find that the migration decisions of those who have completed secondary school are influenced less by vibrancy measures than the decisions of less educated individuals, possibly indicating that individuals who aspire to leave rural areas, and who invest in educational attainment to achieve such aspirations, may be less susceptible to influence by rural productivity changes. Our results suggest that the narrative of a stagnation-driven exodus of educated rural youth is oversimplified and, as such, is of limited policy relevance.

Resume

Nous utilisons des données d'enquête nationales représentatives de la Zambie pour évaluer dans quelle mesure la migration des jeunes issu des zones rurales est associée au manque de dynamisme de l’économie rurale, comme cela est bien souvent affirmé dans les discussions politiques. Une fois que le contrôle de la distance par rapport aux marchés est effectué, nous trouvons en effet des preuves selon lesquelles les zones où l’agriculture est plus productive et plus orientée vers le marché sont associées à des taux d'émigration moins élevé, en particulier pour les personnes qui partent explicitement pour trouver du travail. Cependant, les mesures qui orientent l'économie locale vers des activités non agricoles sont positivement associées à l'émigration, ce qui indique que la composition sectorielle de l'économie locale a une certaine influence sur la relation entre dynamisme économique et migration. Lorsque nous examinons des modèles plus désagrégés, nous constatons que les jeunes hommes et leurs décisions de migration sont particulièrement sensibles aux conditions de dynamisme rural. Cependant, chez les personnes qui ont terminé leurs études secondaires, nous constatons que les décisions de migration sont moins influencées par les mesures de dynamisme que les décisions de personnes moins instruites. Cela indique peut-être que les personnes qui aspirent à quitter les zones rurales et qui investissent dans leur niveau d'instruction pour réaliser ces aspirations sont moins susceptibles d'être influencées par les changements au niveau de la productivité rurale. Nos résultats suggèrent que l’histoire selon laquelle l’exode des jeunes instruits issus des zones rurales est provoqué par la stagnation économique est simplifiée à l'extrême et, qu’en tant que telle, elle revêt un intérêt limité en matière de politique.

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Notes

  1. As examples, see blog posts: https://www.un.org/youthenvoy/2016/04/why-are-rural-youth-leaving-farming/, https://www.helvetas.org/en/switzerland/how-you-can-help/follow-us/blog/inclusive-systems/Youth-on-agriculture-back-breaking-labour and numerous policy reports (e.g., UNDP 2012; FAO 2012, 2014, 2020; Deotti and Estruch 2016; Mercandalli et al. 2019).

  2. Although in a fundamental sense this is not new: classic ‘push–pull’ models of migration suggest that migrants are pushed by low incomes in source communities and pulled by better economic prospects in more affluent destination communities (Lee 1966; Harris and Todaro 1970; Byerlee 1974).

  3. Although all of these constraints may affect older rural people as well (Ripoll et al. 2017).

  4. See CSO et al. (2012) for additional details on the survey and sampling design.

  5. The practical motives for this definition notwithstanding, we acknowledge that this simple age-based definition does not take account of social age, level of responsibility, etc., and thus is only an imperfect identifier for young individuals (Ripoll et al. 2017).

  6. A caveat to our analysis is that we rely on data which are generally collected by a single respondent within the household, who provides information about all household members. While this may lead to some misreporting, it is a standard limitation of household survey data, and one which is shared with the vast majority of other survey-based quantitative analyses of migration.

  7. At the request of a reviewer, we also considered the potential role of social cohesion and shared social capital in conditioning out-migration decisions. Two potential variables are available to us in our data: (a) a household-level indicator of membership in a farmer cooperative, group, and/or association; and (b) a household-level indicator of membership in a local savings and loan society. Both of these are fairly common in rural Zambia, although there is considerable spatial variation in membership rates. When we summarize these variables at the community level (i.e., the mean household participation rate), and include these as community-level controls, we find that the cooperative participation variable is positively (but insignificantly) associated with out-migration, while the savings group participation variable is negatively (and only marginally significantly) associated with out-migration. Other coefficient estimates are largely unaffected.

  8. Potential components of such measures may include average farm household share of inputs which are purchased, the average share of high-value crops in the farm portfolio, the average share of household income from non-farm business, the number of local businesses involved in agricultural value-addition (e.g., millers), and the number of non-farm businesses operating in the local economy.

  9. Somewhat relatedly, it is possible that there are time-varying “vibrancy shocks” which we are unable to detect in our data. An example might be the opening or closing of a local factory which employs many local people. Unfortunately, there is nothing we can do to directly address this possibility, although it seems likely that such shocks are relatively limited within our study setting.

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Acknowledgements

We gratefully acknowledge support for this research from International Fund for Agricultural Development (IFAD), through a research grant to the Institute for Development Studies, as well as from the CGIAR Research Program MAIZE, led by the International Maize and Wheat Improvement Centre (CIMMYT), and the Policies, Institutions, and Markets (PIM) CGIAR research program lead by the International Food Policy Research Institute (IFPRI).

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  1. International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041–00621, Nairobi, Kenya

    Jordan Chamberlin

  2. Mexico City, Mexico

    Cristina Ramos

  3. International Food Policy Research Institute (IFPRI), Cairo, Egypt

    Kibrom Abay

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  1. Jordan Chamberlin
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Chamberlin, J., Ramos, C. & Abay, K. Do more Vibrant Rural Areas have Lower Rates of Youth Out-Migration? Evidence from Zambia. Eur J Dev Res 33, 951–979 (2021). https://doi.org/10.1057/s41287-021-00404-1

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