Literaturnachweis - Detailanzeige
| Autor/in | Gans, Joshua |
|---|---|
| Institution | National Bureau of Economic Research |
| Titel | Endogenous Task Bundling, Skills and Automation. Gefälligkeitsübersetzung: Endogene Aufgabenbündelung, Qualifikationen und Automatisierung. |
| Quelle | Cambridge, Mass (2026), 48 S.
PDF als Volltext |
| Reihe | NBER working paper / National Bureau of Economic Research. 35211 |
| Sprache | englisch |
| Dokumenttyp | online; Monografie |
| Schlagwörter | Rollenwandel; Künstliche Intelligenz; Bildungsertrag; Automatisierung; Einkommenseffekt; Unternehmen; Arbeitsverteilung; Berufliche Qualifikation; Berufliche Spezialisierung; Berufsgruppe; Berufswandel; Tätigkeitsmerkmal; Tätigkeitswandel; Berufsbeschreibung; Berufsbild; Berufsrolle; Arbeitspapier; Auswirkung |
| Abstract | "Empirical measures of AI's wage effect typically hold fixed the bundle of activities a worker is paid for at its pre-AI shape. We argue that this assumption hides much of the action. When automation breaks a job apart, firms decide how to recombine the surviving activities; whether they rebundle them into one broad role or split them into specialist roles changes which surviving skills the labour market actually rewards. A skill that played no role in the pre-AI wage can become the dominant component of the post-AI wage, while a skill that anchored the pre-AI wage can disappear from the schedule. We develop an assignment model in which the priced human bundle is endogenous, and we use it to show that a fixed-bundle wage regression can mis-sign the effect of AI exposure. In general, the omitted-redesign bias has no unconditional sign: it is the residual covariance between exposure and role-specific redesign terms. Under explicit sufficient conditions, exposure-correlated unbundling loads specialist comparative-advantage premia onto the exposure coefficient, while exposure-correlated rebundling loads a different, often opposite, omitted term. The sign must therefore be measured from local post-AI partition changes rather than assumed from exposure alone." (Author's abstract, IAB-Doku). |
| Erfasst von | Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg |
| Update | 2026/4 |