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Erschienen in: Social Indicators Research 3/2010

01.07.2010

Increasing Inequality in Social Exclusion Occurrence: The Case of Sweden During 1979–2003

verfasst von: Miia Bask

Erschienen in: Social Indicators Research | Ausgabe 3/2010

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Abstract

In this paper, we examine the risk of social exclusion among the Swedish population from a longitudinal perspective. In the empirical analysis, a person is considered socially excluded if he or she suffers from at least two of the following six welfare problems: chronic unemployment, economic problems, health problems, experiences of threat or violence, crowded housing and lack of interpersonal relationships. Our three main findings are as follows: There is no evidence that immigrants have been better integrated into Swedish society over time from the perspective of social exclusion risk. Instead, there are weak signs that their situation has become worse. Further, even though men are worse off than women as regards the odds for social exclusion, there are weak signs that their relative situation has improved over time. Finally, compared to couples without children, there is clear evidence that the odds for social exclusion for singles with children have increased over time and that the odds for social exclusion for couples with children have decreased over time. We can, therefore, conclude that among these groups, the inequality has increased over time. To be able to make these conclusions, we have fitted several specifications of a logistic regression model with random effects for panel data to our data set.

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Fußnoten
1
Having an immigrant background means that the person is born abroad or that both parents are born abroad.
 
2
Being a Nordic immigrant means that the person comes from any of the countries Denmark, Finland, Iceland and Norway. In the year 2003, Nordic immigrants constituted about 26% of the stock of immigrants and about 22% of the inflow of immigrants.
 
3
See Table 9 in the Appendix for regression models fitted to each wave in the panel. Of course, we cannot statistically compare parameter estimates from different models. On the other hand, there is no need to do so since we fit several regression models in this paper that are designed for cross-sectional data with a time dimension.
 
4
This is because the first odds = exp(−5.395) × 0.996 implies the probability = odds/(1 + odds) ≈ 0.00450, and the second odds = exp(−5.395) × 0.996 × 34.392 implies the probability = odds/(1 + odds) ≈ 0.13457.
 
5
This is because the first odds = exp(−5.395) × 1.232 × 4.811 × 2.979 implies the probability = odds/(1 + odds) ≈ 0.07420, and the second odds = exp(−5.395) × 1.232 × 4.811 × 2.979 × 34.392 implies the probability = odds/(1 + odds) ≈ 0.73379.
 
6
To be more precise, that the results are not driven by characteristics among men or women is clear since virtually the same odds ratios in the two regression models are significant. See Table 10 in the Appendix.
 
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Metadaten
Titel
Increasing Inequality in Social Exclusion Occurrence: The Case of Sweden During 1979–2003
verfasst von
Miia Bask
Publikationsdatum
01.07.2010
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 3/2010
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-009-9512-z

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