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Developing a Cross-National Comparative Framework for Studying Labour Market Segmentation: Measurement Equivalence with Latent Class Analysis
Author(s) -
Martin Lukac,
Nadja Doerflinger,
Valeria Pulignano
Publication year - 2019
Publication title -
social indicators research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 107
eISSN - 1573-0921
pISSN - 0303-8300
DOI - 10.1007/s11205-019-02101-3
Subject(s) - segmentation , categorical variable , market segmentation , equivalence (formal languages) , quality of life research , econometrics , human geography , latent class model , computer science , economics , artificial intelligence , machine learning , mathematics , microeconomics , economic geography , medicine , nursing , public health , discrete mathematics
This article proposes a novel measurement model of labour market segmentation in Europe for cross-national comparisons, tackling three drawbacks of current approaches: First, as segmentation is a multi-dimensional concept, it necessitates a complex measurement approach combining several indicators. Second, to date, we lack methodological evidence that earlier used measures are comparable across countries. Third, as any measure of social phenomena contains measurement error, segmentation research may be confounded by misclassification error. To overcome these drawbacks, we argue for modelling segmentation as a latent categorical concept by means of characteristics of the employment relationship. Our analysis shows that accounting for measurement non-equivalence in cross-national labour market segmentation research is crucial to arrive at reliable and unbiased comparative conclusions. The results demonstrate the importance of increased complexity in measuring labour market segmentation. Overall, this article serves as a methodological cross-national comparative framework for future quantitative analysis of labour market segmentation.

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