Literaturnachweis - Detailanzeige
| Autor/inn/en | Jurkat, Anne; Klump, Rainer; Schneider, Florian |
|---|---|
| Institution | ZBW - Leibniz-Informationszentrum Wirtschaft |
| Titel | Robots and Wages: A Meta-Analysis. Gefälligkeitsübersetzung: Roboter und Löhne: Eine Meta-Analyse. |
| Quelle | Kiel (2023), 72 S.
PDF als Volltext kostenfreie Datei |
| Reihe | EconStor Preprints. 274156 |
| Sprache | englisch |
| Dokumenttyp | online; Monographie |
| Schlagwörter | Automatisierung; Industrieroboter; Technologische Entwicklung; Entwicklungsland; Industriestaat; Beschäftigungseffekt; Einkommenseffekt; Lohnhöhe; Qualifikation; Arbeitspapier; Auswirkung; Einflussfaktor; Geschlechtsspezifik; Sektorale Verteilung; Europa; Japan; USA |
| Abstract | "The empirical evidence on how industrial robots affect employment and wages is very mixed. Our meta-study helps to uncover the potentially true effect of industrial robots on labor market outcomes and to identify drivers of the heterogeneous empirical results. By means of a systematic literature research, we collected 53 papers containing 2143 estimations for the impact of robot adoption on wages. We observe only limited evidence for a publication bias in favor of negative results. The genuine overall effect of industrial robots on wages is close to zero and both statistically and economically insignificant. With regard to the drivers of heterogeneity, we find that more positive results are obtained if primary estimations a) include more countries in their sample, b) control for ICT capital, demographic developments, or tenure, c) focus on employees that remain employed in the same sector, d) consider only non-manufacturing industries, e) are specified in long differences, and f) come from a peer-reviewed journal article. More negative effects, in turn, are reported for primary estimations that are i) weighted, ii) aggregated at country level, iii) control for trade exposure, iv) and consider only manufacturing industries. We also find some evidence for skill-biased technological change. The magnitude of that effect is albeit small and less robust than one might expect in view of skill-biased technological change. We find little evidence for data dependence." The study refers to the period 2018-2022. (Author's abstract, IAB-Doku).. |
| Erfasst von | Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg |
| Update | 2024/1 |
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