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Labor Market Laws and Intra-European Migration: The Role of the State in Shaping Destination Choices

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Abstract

This article investigates the relationship between migrants’ destination choices and the formal labor market access afforded by multiple potential host countries in the context of the EU’s eastward enlargement. We use an index of labor market access laws combined with data on migration from new EU member states into the existing states of the EU and EFTA from 2004 through 2010 to test whether (1) migrants are attracted to destinations that give them greater formal labor market access, (2) migration flows to any given destination are influenced by the labor market policies of competing destinations, and (3) the influence of labor market laws on migrant flows is mediated by social networks, language ability, and educational level. Our data support the first two propositions and partly support the third: Migration between origin/destination pairs was positively associated with the loosening of destination labor market restrictions, while negatively associated with the loosening of competing destinations’ labor market restrictions. In addition, the influence of destination labor market access appears to be weaker for destinations in which migrants have larger existing co-national networks, and for migrants from countries with languages that are more similar to the destination language, although we do not discern a clear mediating effect of education level. Our models also include variables for a set of economic indicators, social welfare spending, geographic distance, and historical relationships, and the estimated coefficients on these variables are largely in line with theoretical predictions. By combining rich EU data with a unique approach to evaluating competing legal regimes, the analysis helps us better understand how law shapes migration in a multi-destination world.

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Notes

  1. We use this term in the sense of Ostrom et al. (1961) to connote multiple centers of decision making that are formally independent but may end up in competitive or cooperative relationships. This is related to the notion of polycentric problems, discussed in the context of adjudication by Fuller (1978), Henderson (1975), and others.

  2. All of these theories are discussed in detail in Massey et al. (2002).

  3. Theoretical models are also often simplified in this respect to avoid the mathematical complications introduced by multiple origins and destinations (Borjas 1989).

  4. For instance, the employer may need to prove that there is no native or unrestricted EU-national worker available on the labor market for the position.

  5. Treaty of Accession to the European Union 2003, Annexes V-XIV, O.J. L 236 (Sept. 23, 2003).

  6. European Parliament and Council Directive 2004/38/EC of 29 April 2004, O.J. L 158 (Apr. 30, 2004).

  7. The UK put in place a mandatory workers registration scheme for monitoring purposes, but did not restrict access in substantive ways (European Commission 2009).

  8. This dataset is an updated and expanded version of that used in Pedersen and Pytliková (2008) and Pedersen et al (2008).

  9. The OECD International Migration Database is the source for data on migration to Chile, Israel, Korea, Mexico, the Russian Federation, and Turkey, and Eurostat is the source for migration to Bulgaria, Croatia, Cyprus, Estonia, Latvia, Lithuania, Malta, Romania, and Slovenia.

  10. As with other existing datasets of this type, we measure only migration events that have been recorded in official documents. This is a drawback in that increases in documented migration may be related to simultaneous decreases in clandestine migration. We are not able to disentangle such dynamics due to the difficulty of measuring clandestine migration.

  11. See http://www.cepii.fr/anglaisgraph/bdd/distances.htm. The distance measurements are from the dist variable, which is constructed as the geodesic distance between each state’s most populous city (Mayer and Zignago 2011).

  12. We lack data on stocks for 39 (4 %) of the total of 994 country-pair-years, but we have tested the robustness of our results by fitting all models using imputed data in addition to dropping records with missing stocks.

  13. Note, however, that stocks depend also on outmigration and death rates, which are likely to be uncorrelated with current inflows, making the potential existence of endogeneity not at all a straightforward issue.

  14. The consistency of the GMM estimator depends on the validity of the moment conditions being exploited and therefore we check the validity by the Sargan (1958)/Hansen (1982) test of over-identifying restrictions. Furthermore, Arellano and Bond (1991) propose two tests for first-order and second-order serial correlation for the disturbances of the first-differenced equation (A–B tests). In our models, the Sargan test is rejecting the null, whereas the Hansen test is failing to reject. We suspect that since, in contrast to the Hansen test, the Sargan test is not distributed as Chi square under heteroskedasticity, the existing heteroskedasticity could cause the Sargan test to incorrectly reject the null. From our A–B tests, we can see that we have no serial correlation in the first-order errors, but second-order GMM residual serial correlation.

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Acknowledgments

Special thanks to Marta Tienda, Rafaela Dancygier, Alicia Adsera, Kate Choi, Julia Gelatt, Melissa Martinson, Fernanda Nicola, Anna Ginés, and the participants in the 2011 Emerging Immigration Law Scholars and Teachers Conference at American University and the II Annual Conference of the Spanish Association of Law and Economics at Pompeu Fabra University for their advice and comments on earlier drafts. Palmer’s work on this project was supported at Princeton University by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (No. 5R24HD047879) and the National Institutes of Health (No. 5T32HD007163). Pytliková’s research was funded in part by the NORFACE research programme on Migration in Europe—Social, Economic, Cultural and Policy Dynamics (MI3-Migration: Integration, Impact and Interaction), from the Operational Programme Education for Competitiveness (No. CZ.1.07/2.3.00/20.0296), by a Czech Science Foundation grant (No. GA15-23177S) and by an SGS Research grant (No. SP2015/120). The map of Europe reproduced in Fig. 1 relies, for the administrative boundaries, on copyrighted data from EuroGeographics, permission for which has been granted by the European Commission.

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Correspondence to John R. B. Palmer.

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Palmer, J.R.B., Pytliková, M. Labor Market Laws and Intra-European Migration: The Role of the State in Shaping Destination Choices. Eur J Population 31, 127–153 (2015). https://doi.org/10.1007/s10680-015-9341-5

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