The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Work of the Past, Work of the Future
Open accessAbstract
US cities today are vastly more educated and skill-intensive than they were five decades ago. Yet, urban non-college workers perform substantially less skilled jobs than decades earlier. This deskilling reflects the joint effects of automation and, secondarily, rising international trade, which have eliminated the bulk of non-college production, administrative support, and clerical jobs, yielding a disproportionate polarization of urban labor markets. The unwinding of the urban non-college occupational skill gradient has, I argue, abetted a secular fall in real non-college wages by: (1) shunting non-college workers out of specialized middle-skill occupations into low-wage occupations that require only generic skills; (2) diminishing the set of non-college workers that hold middle-skill jobs in high-wage cities; and (3) attenuating, to a startling degree, the steep urban wage premium for non-college workers that prevailed in earlier decades. Changes in the nature of work--many of which are technological in origin--have been more disruptive and less beneficial for non-college than college workers.
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“Some of these technologies, like personal computers, have been complementary mostly to educated workers (63, 64)”
From The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024) · cites this paper as [64]
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Cites
Changes in Relative Wages, 1963-1987: Supply and Demand Factors
Katz, L. F., & Murphy, K. M. (1992) · The Quarterly Journal of Economics · doi:10.2307/2118323 · Cited by 4,793
The China Syndrome: Local Labor Market Effects of Import Competition in the United States
Autor, D. H., Dorn, D., & Hanson, G. H. (2013) · American Economic Review · doi:10.1257/aer.103.6.2121 · Cited by 4,459
Why Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917
The growth of low-skill service jobs and the polarization of the US labor market
Autor, D. H., & Dorn, D. (2013) · American Economic Review · doi:10.1257/aer.103.5.1553 · Cited by 3,824
Acemoglu, D., & Restrepo, P. (2018) · American Economic Review · doi:10.1257/aer.20160696 · Cited by 3,121
Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach
DiNardo, J., Fortin, N. M., & Lemieux, T. (1996) · Econometrica · doi:10.2307/2171954 · Cited by 2,917
Trends in U.S. Wage Inequality: Revising the Revisionists
Autor, D., Katz, L. F., & Kearney, M. S. (2008) · The Review of Economics and Statistics · doi:10.1162/rest.90.2.300 · Cited by 2,381
Lousy and Lovely Jobs: The Rising Polarization of Work in Britain
Goos, M., & Manning, A. (2007) · The Review of Economics and Statistics · doi:10.1162/rest.89.1.118 · Cited by 2,287
Explaining Job Polarization: Routine-Biased Technological Change and Offshoring
Goos, M., Manning, A., & Salomons, A. (2014) · American Economic Review · doi:10.1257/aer.104.8.2509 · Cited by 2,111
Technical change, inequality, and the labor market
Acemoglu, D. (2002) · Journal of Economic Literature · doi:10.1257/jel.40.1.7 · Cited by 1,767
Research works printed but not linked: 3
- 10.1257/0022051026976 · DOI · Paper page
- Autor David, 2019, The Inversion of the Rural-Urban Age Gradient in the United States, 1950
- Costa Dora L, 2000, Changes in the Locational Choice of the College Educated, 1940
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Acemoglu, D., & Restrepo, P. (2018) · American Economic Review · doi:10.1257/aer.20160696 · Cited by 3,121
Artificial Intelligence and Jobs: Evidence from Online Vacancies
Acemoglu, D., Autor, D., Hazell, J., & Restrepo, P. (2022) · Journal of Labor Economics · doi:10.1086/718327 · Cited by 1,193
Self-citationToward understanding the impact of artificial intelligence on labor
Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., Feldman, M., Groh, M., Lobo, J., Moro, E., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1900949116 · Cited by 713
Tasks, automation, and the rise in U.S. wage inequality
Acemoglu, D., & Restrepo, P. (2022) · Econometrica · doi:10.3982/ecta19815 · Cited by 715
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae191 · Cited by 371
Metadata
- Authors
- Autor, D. H.
- Affiliations
- National Bureau of Economic Research (US)
- Corresponding author
- Autor, David H.
- ORCID
- Autor, David H.
- Venue
- AEA Papers and Proceedings
- Publisher
- American Economic Association
- Published
- 2019-05-01
- Volume
- 109
- Pages
- 1-32
- ISSN
- 2574-0768 (ISSN-L)
- 2574-0776
- OpenAlex
- W2917662199
- Cited by
- 435
- References
- 42
- Citations by year
- 2026: 63 · 2025: 79 · 2024: 79 · 2023: 43 · 2022: 53 · 2021: 56 · 2020: 48 · 2019: 11
- FWCI
- 52.43
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc
- Locations
- AEA Papers and Proceedings (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Agglomeration and Urban Systems
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Keywords
- deskilling, automation, international trade, urban wage premium, low-wage employment, technological change
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