Konferenzbeitrag
Robots, Reshoring, and the Lot of Low-Skilled Workers
We propose a theoretical framework to analyze the offshoring and reshoring decisions of firms in the age of automation. Our theory suggests that increasing productivity in automation leads to a relocation of previously offshored production back to the home economy but without improving low-skilled wages and without creating jobs for low-skilled workers. Since it leads also to increasing wages for high-skilled workers, automation induced reshoring is associated with an increasing skill premium and increasing inequality. We develop a measure for reshoring activity at the macro-level and, using data from the world input output table, we provide evidence for automation-driven reshoring. On aver- age, within manufacturing sectors, an increase by one robot per 1000 workers is associated with a 3.5% increase of reshoring activity. We also provide the first cross-country evidence that reshoring is positively associated with wages and employment for high-skilled labor but not for low-skilled labor.
- Sprache
-
Englisch
- Erschienen in
-
Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2019: 30 Jahre Mauerfall - Demokratie und Marktwirtschaft - Session: International Trade and Trade Reforms III ; No. E08-V1
- Klassifikation
-
Wirtschaft
Trade Policy; International Trade Organizations
Economic Impacts of Globalization: Macroeconomic Impacts
Wage Level and Structure; Wage Differentials
Technological Change: Choices and Consequences; Diffusion Processes
- Thema
-
Automation
Reshoring
Employment
Wages
Inequality
Tariffs
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Krenz, Astrid
Strulik, Holger
Prettner, Klaus
- Ereignis
-
Veröffentlichung
- (wer)
-
ZBW - Leibniz-Informationszentrum Wirtschaft
- (wo)
-
Kiel, Hamburg
- (wann)
-
2019
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Krenz, Astrid
- Strulik, Holger
- Prettner, Klaus
- ZBW - Leibniz-Informationszentrum Wirtschaft
Entstanden
- 2019