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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Citations
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
Cited by
Sorted by citations
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
The impact of artificial intelligence on employment: the role of virtual agglomeration
Shen, Y., & Zhang, X. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-02647-9 · Cited by 270
Identity, beliefs, and political conflict
Bonomi, G., Gennaioli, N., & Tabellini, G. (2021) · The Quarterly Journal of Economics · doi:10.1093/qje/qjab034 · Cited by 213
Althoff, L., Eckert, F., Ganapati, S., & Walsh, C. (2021) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2022.103770 · Cited by 190
New Frontiers: The Origins and Content of New Work, 1940–2018
Autor, D., Chin, C., Salomons, A., & Seegmiller, B. (2022) · The Quarterly Journal of Economics · doi:10.1093/qje/qjae008 · Cited by 300
Disability, Work and Inclusion
OECD (2022) · OECD eBooks · doi:10.1787/1eaa5e9c-en · Cited by 264
Soft skills, hard skills: What matters most? Evidence from job postings
Lyu, W., & Jin, L. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.117307 · Cited by 195
Autor, D. (2022) · SSRN Electronic Journal · doi:10.3386/w30074 · Cited by 198
Randolph, G. F., & Storper, M. (2022) · Urban Studies · doi:10.1177/00420980211067926 · Cited by 162
Growing Income Inequality in the United States and Other Advanced Economies
Hoffmann, F., Lee, D. S., & Lemieux, T. (2020) · The Journal of Economic Perspectives · doi:10.1257/jep.34.4.52 · Cited by 170
Explaining the Decline in the US Employment-to-Population Ratio: A Review of the Evidence
Abraham, K. G., & Kearney, M. S. (2020) · Journal of Economic Literature · doi:10.1257/jel.20191480 · Cited by 143
Global universal basic skills: Current deficits and implications for world development
Gust, S., Hanushek, E. A., & Woessmann, L. (2023) · Journal of Development Economics · doi:10.1016/j.jdeveco.2023.103205 · Cited by 153
Labour market transitions across OECD countries: Stylised facts
Causa, O., Lưu, N., & Abendschein, M. (2021) · OECD Economics Department Working Papers · doi:10.1787/62c85872-en · Cited by 16
The dynamics of industry agglomeration: Evidence from 44 years of coagglomeration patterns
Steijn, M. P. A., Koster, H. R. A., & Oort, F. G. V. (2022) · Journal of Urban Economics · doi:10.1016/j.jue.2022.103456 · Cited by 115
Work in the 21st century: New directions for aging and adult development.
Ackerman, P. L., & Kanfer, R. (2020) · American Psychologist · doi:10.1037/amp0000615 · Cited by 109
Artificial Intelligence as a Service, Economic Growth, and Well-Being
Makridis, C. A., & Mishra, S. (2022) · Journal of Service Research · doi:10.1177/10946705221120218 · Cited by 117
Tasks, Automation, and the Rise in US Wage Inequality
Acemoğlu, D., & Restrepo, P. (2021) · National Bureau of Economic Research · doi:10.3386/w28920 · Cited by 114
On the Persistence of the China Shock
Autor, D., Dorn, D., & Hanson, G. (2022) · Brookings Papers on Economic Activity · doi:10.1353/eca.2022.0005 · Cited by 95
Labor Market Returns to Vocational Secondary Education
Silliman, M., & Virtanen, H. (2021) · American Economic Journal Applied Economics · doi:10.1257/app.20190782 · Cited by 100
Why Do Sectoral Employment Programs Work? Lessons from WorkAdvance
Katz, L. F., Roth, J., Hendra, R., & Schaberg, K. (2022) · Journal of Labor Economics · doi:10.1086/717932 · Cited by 79
The Economics of Skyscrapers: A Synthesis
Ahlfeldt, G. M., & Barr, J. M. (2020) · Journal of Urban Economics · doi:10.1016/j.jue.2021.103419 · Cited by 78
Barley, S. R. (2020) · doi:10.1093/oso/9780198795209.001.0001 · Cited by 78
Where have all the workers gone? Recalls, retirements, and reallocation in the COVID recovery
Forsythe, E. C., Kahn, L., Lange, F., & Wiczer, D. G. (2022) · Labour Economics · doi:10.1016/j.labeco.2022.102251 · Cited by 74
Automation in Latin America: Are Women at Higher Risk of Losing Their Jobs?
Egana-delSol, P. A., Bustelo, M., Ripani, L., Soler, N., & Viollaz, M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121333 · Cited by 78
Digitalization and resilience during the COVID-19 pandemic
Abidi, N., Herradi, M. E., & Sakha, S. (2023) · Telecommunications Policy · doi:10.1016/j.telpol.2023.102522 · Cited by 73
The March of the Techies: Job Polarization Within and Between Firms
Harrigan, J., Reshef, A., & Farid Toubal, B. (2020) · Research Policy · doi:10.1016/j.respol.2020.104008 · Cited by 73
New Frontiers: The Origins and Content of New Work, 1940–2018Preprint
Autor, D., Chin, C., Salomons, A., & Seegmiller, B. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4196333 · Cited by 72
Redding, S. J. (2022) · Handbook of international economics · doi:10.1016/bs.hesint.2022.02.003 · Cited by 67
The empirics of technology, employment and occupations: Lessons learned and challenges ahead
Montobbio, F., Staccioli, J., Virgillito, M. E., & Vivarelli, M. (2023) · Journal of Economic Surveys · doi:10.1111/joes.12601 · Cited by 70
Education, skill training, and lifelong learning in the era of technological revolution: a review
Kim, J., & Park, C. (2020) · Asian-Pacific Economic Literature · doi:10.1111/apel.12299 · Cited by 78
Technological Progress, Artificial Intelligence, and Inclusive Growth
Korinek, A., Schindler, M., & Stiglitz, J. E. (2021) · IMF Working Paper · doi:10.5089/9781513583280.001 · Cited by 77
Automation: Theory, Evidence, and Outlook
Restrepo, P. (2024) · Annual Review of Economics · doi:10.1146/annurev-economics-090523-113355 · Cited by 73
Digital infrastructure and economic growth: Evidence from corporate investment efficiency
Wang, Z., Peng, D., Kong, Q., & Tan, F. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.103854 · Cited by 61
Singh, A., Triulzi, G., & Magee, C. (2020) · Social Science Research Network · doi:10.1016/j.respol.2021.104294 · Cited by 55
Universal resilience patterns in labor markets
Moro, E., Frank, M. R., Pentland, A., Rutherford, A., Cebrián, M., & Rahwan, I. (2021) · Nature Communications · doi:10.1038/s41467-021-22086-3 · Cited by 58
Digitalization and Resilience: Firm-level Evidence During the COVID-19 Pandemic
Abidi, N., Herradi, M. E., & Sakha, S. (2022) · IMF Working Paper · doi:10.5089/9798400201073.001 · Cited by 57
Future jobs: analyzing the impact of artificial intelligence on employment and its mechanisms
Shen, Y. (2024) · Economic Change and Restructuring · doi:10.1007/s10644-024-09629-6 · Cited by 62
Explaining the Decline in the U.S. Employment-to-Population Ratio: a Review of the Evidence
Abraham, K., & Kearney, M. (2018) · doi:10.3386/w24333 · Cited by 55
The nature, causes, and consequences of inter-regional inequality
Bathelt, H., Buchholz, M., & Storper, M. (2024) · Journal of Economic Geography · doi:10.1093/jeg/lbae005 · Cited by 54
Scenarios for the Transition to AGI
Korinek, A., & Suh, D. (2024) · National Bureau of Economic Research · doi:10.3386/w32255 · Cited by 61
Cognitive Hubs and Spatial Redistribution
Rossi‐Hansberg, E., Sarte, P.-D. G., & Schwartzman, F. (2019) · American Economic Journal Macroeconomics · doi:10.1257/mac.20230013 · Cited by 50
Gyau, E. B., Li, Y., & Appiah, M. (2025) · Economic Change and Restructuring · doi:10.1007/s10644-024-09843-2 · Cited by 54
Occupational routine intensity and the costs of job loss: evidence from mass layoffs
Blien, U., Dauth, W., & Roth, D. H. W. (2020) · Labour Economics · doi:10.1016/j.labeco.2020.101953 · Cited by 49
Acemoğlu, D., & Johnson, S. (2024) · Annual Review of Economics · doi:10.1146/annurev-economics-091823-025129 · Cited by 62
Robot adoption and product innovation
Antonioli, D., Marzucchi, A., Rentocchini, F., & Vannuccini, S. (2024) · Research Policy · doi:10.1016/j.respol.2024.105002 · Cited by 47
Trends in US Spatial Inequality: Concentrating Affluence and a Democratization of Poverty
Gaubert, C., Kline, P., Vergara, D., & Yagan, D. (2021) · AEA Papers and Proceedings · doi:10.1257/pandp.20211075 · Cited by 46
Martin-Caughey, A. (2021) · American Sociological Review · doi:10.1177/00031224211042053 · Cited by 52
Rapid wage growth at the bottom has offset rising US inequality
Aeppli, C., & Wilmers, N. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2204305119 · Cited by 52
Workplace learning and the future of work
Beier, M. E., Saxena, M., Kraiger, K., Costanza, D. P., Rudolph, C. W., Cadiz, D. M., Petery, G. A., & Fisher, G. G. (2025) · Industrial and Organizational Psychology · doi:10.1017/iop.2024.57 · Cited by 53
Clark, S., Harper, S. B., & Weber, B. A. (2022) · RSF The Russell Sage Foundation Journal of the Social Sciences · doi:10.7758/rsf.2022.8.3.01 · Cited by 55
Regional Disparities, Growth, and Inclusiveness
Floerkemeier, H., & Spatafora, N. L. (2021) · IMF Working Paper · doi:10.5089/9781513569505.001 · Cited by 43
Why is the rent so darn high? The role of growing demand to live in housing-supply-inelastic cities
Howard, G., & Liebersohn, J. (2021) · Journal of Urban Economics · doi:10.1016/j.jue.2021.103369 · Cited by 42
The interplay between location and strategy in a turbulent age
Bathelt, H., & Li, P. (2022) · Global Strategy Journal · doi:10.1002/gsj.1432 · Cited by 44
Risk Sharing Within the Firm: A Primer
Pagano, M. (2020) · Foundations and Trends® in Finance · doi:10.1561/0500000059 · Cited by 41
Why Do Sectoral Employment Programs Work? Lessons from WorkAdvance
Katz, L. F., Roth, J., Hendra, R., & Schaberg, K. (2020) · National Bureau of Economic Research · doi:10.3386/w28248 · Cited by 43
Implications of emerging technologies on the future of work
Jain, A., & Ranjan, S. (2020) · IIMB Management Review · doi:10.1016/j.iimb.2020.11.004 · Cited by 37
Critical Commentary: The city and the virus
Nathan, M. (2021) · Urban Studies · doi:10.1177/00420980211058383 · Cited by 38
Employment Impacts of the Covid-19 Pandemic Across Metropolitan Status and Size
Cho, S. J., Lee, J. Y., & Winters, J. V. (2020) · Growth and Change · doi:10.1111/grow.12540 · Cited by 32
To them that hath: economic complexity and local industrial strategy in the UK
Mealy, P., & Coyle, D. (2021) · International Tax and Public Finance · doi:10.1007/s10797-021-09667-0 · Cited by 32
Building Bridges and Widening Gaps
Bütikofer, A., Løken, K. V., & Willén, A. (2022) · The Review of Economics and Statistics · doi:10.1162/rest_a_01183 · Cited by 31
Goujon, A., Natale, F., Ghio, D., & Alessandra, C. (2021) · Journal of Population Research · doi:10.1007/s12546-021-09263-3 · Cited by 30
Liu, S., & Yang, X. (2020) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2020.103620 · Cited by 29
Lukauskas, M., Šarkauskaitė, V., Pilinkienė, V., Stundžienė, A., Grybauskas, A., & Bruneckienė, J. (2023) · Applied Sciences · doi:10.3390/app13106119 · Cited by 42
Koster, H., & Ozgen, C. (2021) · Journal of Urban Economics · doi:10.1016/j.jue.2021.103386 · Cited by 26
Fidrmuc, J., Hulényi, M., & Tunalı, Ç. B. (2019) · European Journal of Political Economy · doi:10.1016/j.ejpoleco.2019.07.002 · Cited by 25
Has U.S. employment really polarized? A critical reappraisal
Hunt, J., & Nunn, R. (2022) · Labour Economics · doi:10.1016/j.labeco.2022.102117 · Cited by 26
Urbanization favors high wage earners
Shutters, S. T., Applegate, J. M., Wentz, E. A., & Batty, M. (2022) · npj Urban Sustainability · doi:10.1038/s42949-022-00049-x · Cited by 28
Cavalleri, M., Luu, N., & Causa, O. (2021) · OECD Economics Department working papers · doi:10.1787/421bf4aa-en · Cited by 26
Alam, M. F., Lentsch, A., Yu, N., Barmack, S., Kim, S., Acemoğlu, D., Hart, A. J., Johnson, S., & Ahmed, F. (2024) · doi:10.21428/e4baedd9.e39b392d · Cited by 31
To Them That Hath: Economic Complexity and Local Industrial Strategy in the UKPreprint
Mealy, P., & Coyle, D. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3491153 · Cited by 24
Education, Skill Training, and Lifelong Learning in the Era of Technological RevolutionPreprint
Park, C., & Kim, J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3590922 · Cited by 27
Card, D., Rothstein, J. M., & Yi, M. (2023) · National Bureau of Economic Research · doi:10.3386/w31587 · Cited by 24
The paradox of the unhappy, growing city: Reconciling evidence
Carlsen, F., & Leknes, S. (2022) · Cities · doi:10.1016/j.cities.2022.103648 · Cited by 22
Does urbanization increase inequality? Race, gender, and the urban wage premium
Buchholz, M. (2023) · Journal of Urban Affairs · doi:10.1080/07352166.2023.2252538 · Cited by 22
Cognitive Hubs and Spatial Redistribution
Rossi‐Hansberg, E., Sarte, P.-D. G., Richmond, F. R. B. O., Schwartzman, F., & Richmond, F. R. B. O. (2019) · Federal Reserve Bank of Richmond Working Papers · doi:10.21144/wp19-16 · Cited by 22
Identity, Beliefs, and Political ConflictPreprint
Gennaioli, N., & Tabellini, G. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3300726 · Cited by 23
Searching for STARs: Work Experience as a Job Market Signal for Workers without Bachelor's Degrees
Blair, P. Q., Castagnino, T., Groshen, E. L., Debroy, P., Auguste, B., Ahmed, S., Diaz, F. G., & Bonavida, C. (2020) · National Bureau of Economic Research · doi:10.3386/w26844 · Cited by 22
The impact of generative artificial intelligence on socioeconomic inequalities and policy makingPreprint
Capraro, V., Lentsch, A., Acemoğlu, D., Akgün, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas‐Garza, P., Butera, L., Douglas, K. M., et al. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/6fd2y · Cited by 47
Risk of Job Automation and Participation in Adult Education and Training: Do Welfare Regimes Matter?
Ιωαννίδου, Α., & Parma, A. (2021) · Adult Education Quarterly · doi:10.1177/07417136211026635 · Cited by 21
Priced out? Household migration out of “superstar” US city-regions
Buchholz, M. (2022) · Environment and Planning A Economy and Space · doi:10.1177/0308518x221118912 · Cited by 21
Deskilling among Manufacturing Production WorkersPreprint
Kunst, D. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3429711 · Cited by 21
Torrent‐Sellens, J. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102739 · Cited by 25
Enhancing regional convergence in the European Union
Piña, Á., & Sicari, P. (2021) · OECD Economics Department working papers · doi:10.1787/253dd6ee-en · Cited by 19
Technological Disruption in the Labor Market
Deming, D., Ong, C., & Summers, L. H. (2025) · National Bureau of Economic Research · doi:10.3386/w33323 · Cited by 19
Regional diversification and intra-regional wage inequality in the Netherlands
Cortinovis, N., Zhang, D., & Boschma, R. A. (2024) · Regional Studies · doi:10.1080/00343404.2024.2319339 · Cited by 18
For whom are cities good places to live?
Carlsen, F., & Leknes, S. (2022) · Regional Studies · doi:10.1080/00343404.2022.2046724 · Cited by 18
What to do when the robots come? Non-formal education in jobs affected by automation
Koster, S., & Brunori, C. (2021) · International Journal of Manpower · doi:10.1108/ijm-06-2020-0314 · Cited by 17
Allen, J. P., Belfi, B., & Borghans, L. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01710 · Cited by 18
Who on Earth can Work from Home ?
Sánchez, D. G., Gómez‐Parra, N., Özden, Ç., Rijkers, B., Viollaz, M., & Winkler, H. (2020) · World Bank, Washington, DC eBooks · doi:10.1596/1813-9450-9347 · Cited by 18
Global Universal Basic Skills: Current Deficits and Implications for World Development
Gust, S., Hanushek, E. A., & Woessmann, L. (2022) · National Bureau of Economic Research · doi:10.3386/w30566 · Cited by 18
Bauluz, L., Bukowski, P., Fransham, M., Lee, A., Forero, M. L., Novokmet, F., Breau, S., Lee, N., Malgouyres, C., Schularick, M., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4957463 · Cited by 18
Frontier workers and the seedbeds of inequality and prosperity
Connor, D. S., Kemeny, T., & Storper, M. (2023) · Journal of Economic Geography · doi:10.1093/jeg/lbad018 · Cited by 19
Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity
Acemoğlu, D., & Restrepo, P. (2026) · The Quarterly Journal of Economics · doi:10.1093/qje/qjag006 · Cited by 18
Developing an innovator’s thinking in engineering education
Solodikhina, А., & Solodikhina, М. (2022) · Education and Information Technologies · doi:10.1007/s10639-021-10709-7 · Cited by 16
Tasks, occupations and slowbalisation: on the limits of fragmentation
Brakman, S., & van Marrewijk, C. (2022) · Cambridge Journal of Regions Economy and Society · doi:10.1093/cjres/rsac014 · Cited by 19
A task-based approach to inequality
Acemoğlu, D., & Restrepo, P. (2024) · Oxford Open Economics · doi:10.1093/ooec/odad082 · Cited by 18
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review