Unpacking Skill Bias: Automation and New Tasks
Name
pandp.20201063.pdf
Description
Published version
Size
756.03 KB
Format
Adobe PDF
Checksum (MD5)
46fb1aba3885bc9ce3d951a6e767c09f
Author(s)
Acemoglu, K. Daron
Date Issued
May 2020
Journal
American Economic Association Papers and Proceedings
Publisher
American Economic Association
Citation
Acemoglu, K. Daron and Pascual Restrepo. “Unpacking Skill Bias: Automation and New Tasks.” American Economic Association Papers and Proceedings, 110 (May 2020): 356-361 © 2020 The Author(s)
Version
Final published version
Abstract
We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.
MIT Department
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1257/PANDP.20201063
