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Minimum wages in an automating economy

Eckardt, Marcel Steffen (2022):
Minimum wages in an automating economy. (Publisher's Version)
In: Journal of Public Economic Theory, 24 (1), pp. 58-91. John Wiley & Sons, e-ISSN 1467-9779,
DOI: 10.26083/tuprints-00020978,

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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Minimum wages in an automating economy
Language: English

We explore the suitability of the minimum wage as a policy instrument for reducing emerging income inequality created by new technologies. For this, we implement a binding minimum wage in a task‐based framework, in which tasks are conducted by machines, low‐skill, and high‐skill workers. In this framework, an increasing minimum wage reduces the inequality between the low‐skill wage and the other factor prices, whereas the share of income of low‐skill workers in the national income is nonincreasing. Then, we analyze the impact of an automating economy along the extensive and intensive margins. In a setting with a minimum wage, it can be shown that automation at the extensive margin and the creation of new, labor‐intensive tasks do not increase the aggregate output in general, as the displacement of low‐skill workers counteracts the positive effects of cost‐savings. Finally, we highlight a potential trade‐off between less inequality of the factor prices and greater inequality of the income distribution when a minimum wage is introduced into an automating economy.

Journal or Publication Title: Journal of Public Economic Theory
Volume of the journal: 24
Issue Number: 1
Place of Publication: Darmstadt
Publisher: John Wiley & Sons
Uncontrolled Keywords: automation, displacement effects, employment, inequality, labor demand, minimum wage, tasks, wages
Classification DDC: 300 Sozialwissenschaften > 330 Wirtschaft
Divisions: 01 Department of Law and Economics > Volkswirtschaftliche Fachgebiete > Fachgebiet Finanzwissenschaft und Wirtschaftspolitik
Date Deposited: 11 Jul 2022 13:41
Last Modified: 06 Sep 2022 10:43
DOI: 10.26083/tuprints-00020978
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-209788
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20978
PPN: 498915174
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