Literaturnachweis - Detailanzeige
Autor/in | Michaud, Amanda M. |
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Titel | A quantitative theory of information, worker flows, and wage dispersion. Gefälligkeitsübersetzung: Eine quantitative Theorie der Information, Arbeitskräfteumschlag und Lohnspreizung. |
Quelle | In: American economic journal. Macroeconomics, 10 (2018) 2, S. 154-183
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | online; Zeitschriftenaufsatz |
ISSN | 1945-7707; 1945-7715 |
DOI | 10.1257/mac.20160136 |
Schlagwörter | Lernen; Lohnentwicklung; Zwischenbetriebliche Mobilität; Arbeitsloser; Arbeitsplatzwechsel; Arbeitsproduktivität; Beschäftigungsdauer; Job turnover; Betriebszugehörigkeit; Arbeitgeber; Information; USA |
Abstract | "Employer learning provides a link between wage and employment dynamics. Workers who are selectively terminated when their low productivity is revealed subsequently earn lower wages. If learning is asymmetric across employers, randomly separated high-productivity workers are treated similarly when hired from unemployment, but recover as their next employer learns their type. I provide empirical evidence supporting this link, then study whether employer learning is an empirically important factor in wage and employment dynamics. In a calibrated structural model, learning accounts for 78 percent of wage losses after unemployment, 24 percent of life-cycle wage growth, and 13 percent of cross-sectional dispersion observed in data." (Author's abstract, IAB-Doku). |
Erfasst von | Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg |
Update | 2018/3 |