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SOR models and ethnicity data in LIS and LES: country by country report

Lambert, Paul; & Penn, Roger. (2001). SOR models and ethnicity data in LIS and LES: country by country report. Luxembourg Income Study Working Paper No. 260.

Lambert, Paul; & Penn, Roger. (2001). SOR models and ethnicity data in LIS and LES: country by country report. Luxembourg Income Study Working Paper No. 260.

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This research considers the idea that a single metric expressing distance between social groups may be an adequate tool for investigating the relationship between ethnic /nationality minority group membership and social stratification. A Stereotyped Ordered Regression (SOR) model is proposed as a methodology for deriving this metric1, and this paper considers the role of SOR models for the variety of countries with appropriate data made available by the Luxembourg Income and Employment studies (LIS and LES). In particular, by making the referents of this metric relatively consistent between different countries, it is suggested that a cross-nationally comparable representation of ethnic / nationality group membership can be derived which reduces the difficulties of international comparative research on ethnicity. Section one of this paper deals with three introductory issues : the clarification of the proposed methodology; the possibilities for ethnicity analyses as available from the LIS / LES datasets; and the theoretical framework used to draw substantive cross-national comparisons. Section two comprises a summary of the descriptive patterns observed for selected indicators of social stratification by ethnic / nationality groups for each country, and the presentation of the SOR orderings derived from them. In section three, the possibilities for using those SOR orderings in analytical human capital style models of social stratification are considered. Lastly in section four some of the more prominent conclusions are drawn together.




RPRT

Luxembourg Income Study Working Paper No. 260


Lambert, Paul
Penn, Roger



2001




260











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