Abstract
We estimate whether migration can be an equilibrating force in the labour market by comparing pre- and post-crisis migration movements at the regional level in both Europe and the United States, and their association with asymmetric labour market shocks. Based on fixed-effects regressions using regional panel data, we find that Europe’s migratory response to unemployment shocks was almost identical to that recorded in the United States after the crisis. Our estimates suggest that, if all measured population changes in Europe were due to migration for employment purposes—i.e. an upper-bound estimate—up to about a quarter of the asymmetric labour market shock would be absorbed by migration within a year. However, in Europe and especially in the Eurozone, the reaction to a very large extent stems from migration of recent EU accession country citizens as well as of third-country nationals.
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Notes
The countries which joined in 2004 were Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia and Slovenia. Bulgaria and Romania joined in 2007.
Beine and Coulombe (2018) estimate different effects of temporary versus permanent immigrants on the labour market in Canada.
Note, however, that the data for Europe reported by Molloy et al. (2011) only cover the pre-crisis period up to 2007.
Croatia is excluded, because it only joined the EU in 2013.
While the minimum age of labour force entry in most European countries is 15, in a few countries and the United States it is 16.
Information on overlapping old (pre-2012) and new (2012 and after) PUMA regions is provided on the web page http://mcdc.missouri.edu/data/corrlst/puma2k_puma2010.csv
The SuperPUMA codes can be found on the following web page https://usa.ipums.org/usa/volii/2000PUMAsASCII.txt
According to the ILO definition, the unemployed comprise all persons who, during the week prior to the survey interview, were without work while both being available for work and seeking work.
By using relative measures, we assume that the decision to migrate or not is affected by the labour market situation in a given region relative to that elsewhere in the free-mobility area.
By relating a flow (migration proxied by population change) to a stock (the lagged unemployment or non-employment rate), we build on the matching function literature, which is based on an analogy to the production function where the flow of new hires is “produced” by the stock of unemployed workers and vacancies (see Petrongolo and Pissarides 2001 for a survey of this literature).
We also ran separate regressions for the youth population aged 15/16–24 (available upon request). The results indicate, not surprisingly, that this group tends to be more responsive to changes in the relative regional labour market conditions than the overall working-age population.
These estimates refer to the period 1985 to 1996. For Western Germany, Puhani (2001) reported an estimated offset of up to 30%; however, this period covered German reunification which was associated with large-scale movements from East to West Germany.
However, it is possible that part of the measured effect arises from naturalisations, i.e. immigrants with a non-EU-27/EFTA nationality taking up citizenship of their respective host countries—and this is a group that is particularly mobile.
Cadena and Kovak (2013) still demonstrate that Mexican migrants played a significant role in the absorption of labour market shocks in the United States during the crisis.
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Acknowledgements
We are very grateful to the referees and the editor for their helpful comments on an earlier draft which have greatly improved it. We also thank Franziska Braschke for helpful research assistance. The views expressed are our own and cannot be held to represent those of the institutions with which we are associated.
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Responsible editor: Klaus F. Zimmermann
Appendix. Simulations
Appendix. Simulations
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Jauer, J., Liebig, T., Martin, J.P. et al. Migration as an adjustment mechanism in the crisis? A comparison of Europe and the United States 2006–2016. J Popul Econ 32, 1–22 (2019). https://doi.org/10.1007/s00148-018-0716-x
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DOI: https://doi.org/10.1007/s00148-018-0716-x