Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/314564 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 17667
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
We study how the effects of exports on earnings vary across individual workers, depending on a wide range of worker, firm, and job characteristics. To this end, we combine a generalized random forest with an instrumental variable strategy. Analyzing Germany's exports to China and Eastern Europe, we document sharp disparities: workers in the bottom quartile (ranked by the size of the effect) experience little to no earnings gains due to exports, while those in the top quartile see considerable earnings increases. As expected, the workers who benefit the most on average are employed in larger firms and have higher skill levels. Importantly, however, we also find that workers with the largest earnings gains tend to be male, younger, and more specialized in their industry. These factors have received little attention in the previous literature. Finally, we provide evidence that the contribution to overall earnings inequality is smaller than expected.
Schlagwörter: 
machine learning
earnings
inequality
exports
skills
labor market
JEL: 
C52
F14
J23
J24
J32
Dokumentart: 
Working Paper

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