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Self-selection of Emigrants

Theory and Evidence on Stochastic Dominance in Observable and Unobservable Characteristics

Bibliographic Data

ID9718753
AuthorsGeorge J Borjas (0000-0001-8596-1705, Harvard Kennedy School, NBER and IZA), Ilkka Kauppinen (0000-0002-9175-1525, VATT Institute for Economic Research), Ilpo Kauppinen (VATT Institute for Economic Research), Panu Poutvaara (0000-0003-2070-784X, LMU Munich, ifo Institute–Leibniz Institute for Economic Research at the University of Munich, CESifo, CReAM and IZA, corresponding author)
Year2019
Volume129
Issue617
Pages143-171
Publication date2019-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Economic Journal (JOURNAL)
Journal identifiersISSN: 0013-0133 • E-ISSN: 1468-0297
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1111/ecoj.12585
OpenAlexW3124052556
LanguageEN
Citations received37
References cited34

The Roy model has more precise predictions about the self-selection of migrants than previously realised. The conditions shown to result in positive or negative selection in terms of expected earnings also imply a stochastic dominance relationship between the earnings distributions of migrants and non-migrants. We test these predictions using the Danish full population administrative data. We find strong evidence of positive self-selection of emigrants in terms of pre-emigration earnings and residual earnings: the income distribution for the migrants almost stochastically dominates the distribution for the non-migrants. Decomposing the self-selection in total earnings reveals that unobserved abilities play the dominant role

Biology · Demographic economics · Dominance (genetics · Earnings · Econometrics · Economics · Emigration · Geography · Population · Selection (genetic algorithm · Sociology · Stochastic dominance · Unobservable · Computer Science · Demography · Gender, Labor, and Family Dynamics · Labor market dynamics and wage inequality · Migration and Labor Dynamics

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Unique citing works37
Citations per year4,11
Citation span2017 - 2026 (10)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 37

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