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When a random sample is not random: Bounds on the effect of migration on household members left behind

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  • Steinmayr, Andreas

Abstract

A key problem in the literature on the economics of migration is how emigration of an individual affects households left behind. Answers to this question must confront a problem I refer to as invisible sample selection: when entire households migrate, no information about them remains in their source country. Since estimation is typically based on source country data, invisible sample selection yields biased estimates if all-move households differ from households that send only a subset of their members abroad. I address this identification problem and derive nonparametric bounds within a principal stratification framework. Instrumental variables estimates are biased, even if all-move households do not differ in their potential outcomes. For this case, I derive a corrected instrumental variables estimator. I illustrate the approach using individual and household data from widely cited, recent studies. Potential bias from invisible sample selection can be large, but transparent assumptions regarding behaviors of household members and selectivity of migrants allow identification of informative bounds.

Suggested Citation

  • Steinmayr, Andreas, 2014. "When a random sample is not random: Bounds on the effect of migration on household members left behind," Kiel Working Papers 1975, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwkwp:1975
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    References listed on IDEAS

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    Cited by:

    1. Joanna M Clifton-Sprigg, 2019. "Out of sight, out of mind? The education outcomes of children with parents working abroad," Oxford Economic Papers, Oxford University Press, vol. 71(1), pages 73-94.
    2. Bertoli, Simone & Murard, Elie, 2020. "Migration and co-residence choices: Evidence from Mexico," Journal of Development Economics, Elsevier, vol. 142(C).
    3. Bertoli, Simone & Gautrain, Elsa & Murard, Elie, 2020. "Left Behind, but Not Alone: Changes in Living Arrangements and the Effects of Migration and Remittances in Mexico," IZA Discussion Papers 13917, Institute of Labor Economics (IZA).
    4. Romuald Méango, 2016. "What Makes Brain Drain More Likely? Evidence from Sub-Saharan Africa," CESifo Working Paper Series 6209, CESifo.
    5. Murard, Elie, 2019. "The Impact of Migration on Family Left Behind: Estimation in Presence of Intra-Household Selection of Migrants," IZA Discussion Papers 12094, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    sample selection; migration; selectivity; principal stratification;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • 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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