Skills, Earnings, and Employment: Exploring Causality in the Estimation of Returns to Skills

Autor/inn/en	Hampf, Franziska; Wiederhold, Simon; Woessmann, Ludger
Titel	Skills, Earnings, and Employment: Exploring Causality in the Estimation of Returns to Skills
Quelle	In: Large-scale Assessments in Education, 5 (2017), Artikel 12 (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Wiederhold, Simon)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2196-0739
DOI	10.1186/s40536-017-0045-7
Schlagwörter	Outcomes of Education; Human Capital; Labor Market; Income; International Assessment; Surveys; Adult Literacy; Employment; Wages; Employment Potential; Error of Measurement; Educational Attainment; Least Squares Statistics; Cognitive Ability; Job Skills; Statistical Bias; Foreign Countries; Regression (Statistics); Statistical Analysis; Australia; Austria; Belgium; Canada; Chile; Cyprus; Czech Republic; France; Germany; Greece; Indonesia; Ireland; Israel; Italy; Japan; New Zealand; Norway; Poland; Singapore; Slovakia; Slovenia; Spain; Sweden; United States + Suchen Sie Ihr Suchwort? Lernleistung; Schulerfolg; Humankapital; Labour market; Arbeitsmarkt; Einkommen; Survey; Umfrage; Befragung; Dienstverhältnis; Wage; Löhne; Arbeitsmarktbezogene Qualifikation; Beschäftigungsfähigkeit; Messfehler; Bildungsabschluss; Bildungsgut; Denkfähigkeit; Produktive Fertigkeit; Ausland; Regression; Regressionsanalyse; Statistische Analyse; Australien; Österreich; Belgien; Kanada; Zypern; Tschechische Republik; Frankreich; Deutschland; Griechenland; Indonesien; Irland; Italien; Neuseeland; Norwegen; Polen; Singapur; Slowakei; Slowenien; Spanien; Schweden; USA
Abstract	Ample evidence indicates that a person's human capital is important for success on the labor market in terms of both wages and employment prospects. However, unlike the efforts to identify the impact of school attainment on labor-market outcomes, the literature on returns to cognitive skills has not yet provided convincing evidence that the estimated returns can be causally interpreted. Using the PIAAC Survey of Adult Skills, this paper explores several approaches that aim to address potential threats to causal identification of returns to skills, in terms of both higher wages and better employment chances. We address measurement error by exploiting the fact that PIAAC measures skills in several domains. Furthermore, we estimate instrumental-variable models that use skill variation stemming from school attainment and parental education to circumvent reverse causation. Results show a strikingly similar pattern across the diverse set of countries in our sample. In fact, the instrumental-variable estimates are consistently larger than those found in standard least-squares estimations. The same is true in two "natural experiments," one of which exploits variation in skills from changes in compulsory-schooling laws across U.S. states. The other one identifies technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across German municipalities. Together, the results suggest that least-squares estimates may provide a lower bound of the true returns to skills in the labor market. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01