Abstract
Although there is considerable research evidence showing that immigrants are at great risk of poverty, there have been few comparative analyses of the poverty gap between immigrants and natives across Europe. We examine the patterns of variation in the immigrant–native poverty gap between and within countries. We simultaneously combine characteristics of households from the European Union Statistics on Income and Living Conditions and some key country-specific factors, distinguishing among mixed and non-mixed immigrant households and natives. The main findings for 2012 reveal that immigrants, especially non-mixed immigrant households, are exposed to a higher risk of poverty than natives, though this gap varies across countries. We find evidence of significant household-level effects, but the contribution of country-level variables to explain cross-country differences in the poverty gap is substantially higher. Concerning household characteristics, employment and being young have less effect (positive and negative, respectively) on immigrants than on natives, while each additional child has a more negative effect. Education seems to have a lower effect on the likelihood of being poor for non-mixed immigrant households than for natives and owning a house reduces this likelihood more for non-mixed immigrant households. In terms of country-level factors, labour market and social benefits seem to be equally important for both natives and immigrants. We also compare the results in 2012 with those for 2007 to check for possible changes over time related to the influence of the economic cycle on the poverty gap and/or on the importance of household- and country-level factors.
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Notes
Among other explanations of why new immigrants in Canada are worse-off despite the point system, they argue economic conditions at time of entry, deteriorating outcomes for new labour market entrants, declining returns to foreign work experience, and a deterioration in the “networks” that are available to recent immigrants.
We have 27 countries in the regression analysis for 2007: EU28 except Croatia, Malta and Romania, plus Iceland and Norway. Romania is dropped due to missing data.
We are aware that treating all foreign-born adults in the same group lumps together immigrants from very different backgrounds, but the categories and sample size for some groups provided in the EU-SILC do not allow us to circumvent this problem.
We acknowledge that the introduction of the usual variables of integration, such as years since migration, would be preferable to this classification, but EU-SILC does not provide this kind of information for the two waves analyzed.
See Table 5 in Appendix for number of observations and shares of natives, mixed immigrants and non-mixed immigrants by country in 2012.
To avoid methodological problems arising from the fact that individuals living in the same household are not statistically independent observations, we switch from the individual to the household level for the regression analyses.
For a review, see Bryan and Jenkins (2013).
Bryan and Jenkins (2013) argued that a small number of countries in country datasets constrains the ability of multilevel models to provide robust conclusions about the effects of country-level characteristics on outcomes. They suggest at least 30 countries for logit multilevel models, but recognise that fewer countries are sufficient if one is content to be merely fairly “close” to these ideals. We fulfil this suggestion.
Let us recall that in the EU-SILC the educational attainment of a person is the highest level of an educational programme that the individual has successfully completed. The educational classification used is the International Standard Classification of Education (ISCED), and is coded according to the seven ISCED-97 categories.
To be consistent with the equivalence scale applied, modified OECD equivalence scale, we have defined the variable Nchildren as the number of individuals aged 13 or under.
We have also estimated the models without Romania and Bulgaria, the two countries with the lowest proportion of immigrants in the sample, and the results remain the same. Results available upon request.
Results available upon request.
This has a small effect with a low significance on mixed immigrant that vanishes in the following model when we control for household- and country-level variables simultaneously.
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Acknowledgments
Elena Bárcena-Martín and Salvador Pérez-Moreno gratefully acknowledge the useful comments and advices of Rafael Muñoz de Bustillo, José Ignacio Antón and two anonymous referees, as well as the financial support provided by the Spanish Institute for Fiscal Studies and by the University of Málaga through the III Plan Propio de Investigación. The former also thanks the financial support provided the Spanish Ministry of Education through Grant ECO2012-33993 and by the Fundación Ramón Areces, XI Concurso Nacional para la Adjudicación de Ayudas a la Investigación en Ciencias Sociales.
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Bárcena-Martín, E., Pérez-Moreno, S. Immigrant–native gap in poverty: a cross-national European perspective. Rev Econ Household 15, 1105–1136 (2017). https://doi.org/10.1007/s11150-015-9321-x
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DOI: https://doi.org/10.1007/s11150-015-9321-x