A dynamic structural equation approach to modeling wage dynamics and cumulative advantage across the lifespan
- Wages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes andWages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes and related developmental dynamics, and we highlight the extensions and limitations of the DSEM framework.…
Author details: | Andrea HaslORCiDGND, Manuel VoelkleORCiDGND, Julia KretschmannORCiDGND, Dirk RichterORCiDGND, Martin BrunnerORCiD |
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DOI: | https://doi.org/10.1080/00273171.2022.2029339 |
ISSN: | 0027-3171 |
ISSN: | 1532-7906 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/35129003 |
Title of parent work (English): | Multivariate Behavioral Research |
Publisher: | Routledge, Taylor & Francis Group |
Place of publishing: | Abingdon |
Publication type: | Article |
Language: | English |
Date of first publication: | 2022/02/07 |
Publication year: | 2022 |
Release date: | 2023/12/14 |
Tag: | Dynamic Structural Equation Modeling (DSEM); autoregressive wage growth; cumulative advantage (CA); human capital theory; wage dynamics |
Volume: | 58 |
Issue: | 3 |
Number of pages: | 22 |
First page: | 504 |
Last Page: | 525 |
Organizational units: | Humanwissenschaftliche Fakultät / Strukturbereich Bildungswissenschaften / Department Erziehungswissenschaft |
DDC classification: | 3 Sozialwissenschaften / 37 Bildung und Erziehung / 370 Bildung und Erziehung |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |