Explaining Local Swedish Refugee Policy

Abstract

In the Swedish migration system, the local level plays a crucial role since the municipalities have full autonomy to accept or decline refugees. This has created a considerable variation in numbers of immigrants among municipalities, and there is a large variation in local societies' willingness to receive refugees. In this study, we focus on all the Swedish municipalities for a time span of several years and derive from economic, demographic, socio-cultural, and explanatory factors that have been put forward in earlier research. Through quantitative analysis, we can show how income, the unemployment rate, population, and support for the right-wing party negatively vary with the willingness to receive refugees. Moreover, the distribution of income results in the opposite significant direction. These results, partly contradicting theory, show the importance of a nuanced and holistic theoretical base in further research.

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Fig. 1

Notes

  1. 1.

    By this we mean refugees including for instance quota refugees and former asylum seekers given residence. However, this group can settle in other municipalities after admission, as can asylum seekers. This situation has placed a particularly heavy burden on some municipalities, especially in metropolitan areas that have received many immigrants through their subsequent location (Åslund 2005). Our main focus, though, is on the variation in the agreed reception of refugees, since this is determined by the municipalities.

  2. 2.

    The average number of accepted refugees per 1,000 inhabitants varies from 2.65 (2006) to 2.32 (2010) per municipality, but the variation is not significant. The number of municipalities has increased from 233 in 2006 to 271 municipalities in 2010.

  3. 3.

    Means calculated for regions gives the following numbers—2.30 (southern Sweden), 2.34 (central Sweden), and 3.91 (northern Sweden). Analysis of variance indicates that there is a significant difference between the regions, and the effect is 0.093 (eta squared).

  4. 4.

    The spatial variation between municipalities differs significantly, while the temporal variation between years does not differ significantly.

  5. 5.

    Gilljam et al. (2010, 26) find that politicians representing the Left Party are most positive toward immigration, while politicians representing the Sweden Democrats and the Moderate Party are most sceptical. Therefore, voting shares for these three parties will be included.

  6. 6.

    Here, we follow Beck’s (2001) definition of time-series cross-section data as repeated observations of fixed units. Our data are characterized by a quite large N but a smaller T (N > T). However, two arguments make it possible to regard the data as time-series cross-section. First, the units are not sampled, and the total population is included in the dataset. Second, the units are of importance since they reflect specific political units.

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Acknowledgments

An earlier draft of this manuscprit was presented at the annual meeting of the Swedish Political Science Association in Växjö 2012. We would like to thank Svante Ersson and the three anonymous reviewers for their comments on earlier drafts of this manuscpript.

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Data Appendix

Data Appendix

Dependent variable: number of accepted refugees per 1,000 citizens from the Swedish Migration Board (2010), data for 2006–2010. Municipalities that lack agreement are coded with the value 0. A few municipalities have an agreement without specification of the number of places, and these are treated as missing values. Independent variables: unemployment rate, calculated for the population aged 16–64 years from the Swedish Public Employment Service (2010), data for 2006–2009; average income, calculated for the population older than 20 years, from Statistics Sweden (2010), data for 2006–2009; sickness rate, calculated for the population aged 16–64 years, from the Swedish Social Insurance Agency (2010), data for 2006–2009; financial solidity, from the Database for Local and County Councils (2010), data for 2006–2009; Gini coefficient, based on income distribution, from Statistics Sweden (2010), data for 2006–2009; population with post-secondary education, from the Confederation of Swedish Enterprise (2010), data for 2006–2009; population, from Statistics Sweden (2010), data for 2006–2010; population density, from Statistics Sweden (2010), data for 2006–2009; average age, from Statistics Sweden (2010), data for 2006–2009; share of votes for left-wing party, votes for the Left Party in National Parliament election, from the Election Authority (2010), data from elections 2002 and 2006; share of votes for conservative party, votes for the Moderate Party in National Parliament election, from the Election Authority (2010), data from elections 2002 and 2006; share of votes for right-wing party, votes for the Swedish Democrats in National Parliament election, from the Election Authority (2010), data from elections 2002 and 2006; population with foreign background, from Statistics Sweden (2010), data for 2006–2009; share of free apartments, based on statistics from public housing companies, from Statistics Sweden (2010), data for 2006–2009.

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Lidén, G., Nyhlén, J. Explaining Local Swedish Refugee Policy. Int. Migration & Integration 15, 547–565 (2014). https://doi.org/10.1007/s12134-013-0294-4

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Keywords

  • Refugee policy
  • Migration
  • Local government
  • Sweden