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Predicting Spanish emigration and immigration

Authors: Fernández-Huertas Moraga, Jesús; López Molina, Gonzalo;

Predicting Spanish emigration and immigration

Abstract

What is the future of international migration flows? The growing availability of bilateral international migration data has resulted in an improved understanding of the determinants of migration flows through the estimation of theory-based gravity models. However, the use of these models as a prediction tool has remained a mostly unexplored research area. This paper estimates simple gravity models of bilateral migration flows for the whole world and projects these models into the future. We focus on a particularly hard-to-predict country, Spain, which evolved from an emigrant-sending to an immigrant-receiving country, and compare the estimates from internationally available data to those coming from local sources. Our results show that the projections of migration flows depend more heavily on the span of the baseline dataset used to estimate the model than on the particular functional form and variables chosen for the prediction although we confirm the relevance of origin-country demographic factors.

Keywords

International migration, Gravity Model, J11, J61, F22, Prediction, O15, Economía

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green