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.…
Verfasserangaben: | 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 |
Titel des übergeordneten Werks (Englisch): | Multivariate Behavioral Research |
Verlag: | Routledge, Taylor & Francis Group |
Verlagsort: | Abingdon |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 07.02.2022 |
Erscheinungsjahr: | 2022 |
Datum der Freischaltung: | 14.12.2023 |
Freies Schlagwort / Tag: | Dynamic Structural Equation Modeling (DSEM); autoregressive wage growth; cumulative advantage (CA); human capital theory; wage dynamics |
Band: | 58 |
Ausgabe: | 3 |
Seitenanzahl: | 22 |
Erste Seite: | 504 |
Letzte Seite: | 525 |
Organisationseinheiten: | Humanwissenschaftliche Fakultät / Strukturbereich Bildungswissenschaften / Department Erziehungswissenschaft |
DDC-Klassifikation: | 3 Sozialwissenschaften / 37 Bildung und Erziehung / 370 Bildung und Erziehung |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Hybrid Open-Access |
Lizenz (Deutsch): | ![]() |