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AUTOMATION, PARTIAL AND FULL

Published online by Cambridge University Press:  15 February 2021

Jakub Growiec Open the ORCID record for Jakub Growiec [Opens in a new window]
Jakub Growiec*
Affiliation:
SGH Warsaw School of Economics
*
Address correspondence to: Jakub Growiec, Szkoła Główna Handlowa w Warszawie, Katedra Ekonomii Ilościowej, al. Niepodległości 162, 02-554 Warszawa, Poland. Phone/Fax: (+48) 225649326. e-mail: jakub.growiec@sgh.waw.pl.
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Abstract

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When some steps of a complex, multi-step task are automated, the demand for human work in the remaining complementary sub-tasks goes up. In contrast, when the task is fully automated, the demand for human work declines. Upon aggregation to the macroeconomic scale, partial automatability of complex tasks creates a bottleneck of development, where further growth is constrained by the scarcity of essential human work. This bottleneck is removed once the tasks become fully automatable. Theoretical analysis using a two-level nested constant elasticity of substitution production function specification demonstrates that the shift from partial to full automation generates a non-convexity: humans and machines switch from complementary to substitutable, and the share of output accruing to human workers switches from an upward to a downward trend. This process has implications for inequality, the risk of technological unemployment, and the likelihood of a secular stagnation.

Keywords

AutomationTaskComplementarityEconomic Growth
Type
Articles
Information
Macroeconomic Dynamics , Volume 26 , Issue 7 , October 2022 , pp. 1731 - 1755
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© Cambridge University Press 2021

Footnotes

Financial support from the Polish National Science Center (Narodowe Centrum Nauki) under grant OPUS 14 No. 2017/27/B/HS4/00189 is gratefully acknowledged. The author thanks two anonymous Referees as well as Michał Gradzewicz and Jakub Mućk for their useful comments which helped substantially improve the paper. The author declares that he has no relevant or material financial interests that relate to the research described in this paper.

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