Strengthening Social Protection to Pave the Way for Technological Innovation: Evidence from the U.S.

May 3, 2024

Preview Citation

Format: Chicago

Fernanda Brollo. Strengthening Social Protection to Pave the Way for Technological Innovation: Evidence from the U.S., (USA: International Monetary Fund, 2024) accessed December 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

This paper investigates the impact of automation on the U.S. labor market from 2000 to 2007, specifically examining whether more generous social protection programs can mitigate negative effects. Following Acemoglu and Restrepo (2020), the study finds that areas with higher robot adoption reduced employment and wages, in particular for workers without collegue degree. Notably, the paper exploits differences in social protection generosity across states and finds that areas with more generous unemployment insurance (UI) alleviated the negative effects on wages, especially for less-skilled workers. The results suggest that UI allowed displaced workers to find better matches The findings emphasize the importance of robust social protection policies in addressing the challenges posed by automation, contributing valuable insights for policymakers.

Subject: Economic sectors, Employment, Expenditure, Financial crises, Labor, Labor markets, Robotics, Technology, Unemployment benefits, Wages

Keywords: Automation, Employment, Employment polarization, Europe, Gen-AI, IMF working paper 24/95, Innovation, Job searching, Labor Market, Labor market program, Labor markets, Protection policy, Robotics, Social Assistance, Social Protection, Social Safety Nets, Unemployment benefits, Unemployment Insurance, Wage measure, Wages

Publication Details

Pages:

21
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2024/095
Stock No:

WPIEA2024095
ISBN:

9798400274596
ISSN:

1018-5941

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