IDEAS home Printed from https://ideas.repec.org/p/amz/wpaper/2026-04.html

New technologies and the rise of wage inequality

Author

Listed:
  • Sebastian, Raquel
  • Salas-Rojo, Pedro

    (London School of Economics and Political Science)

  • C. Palomino, Juan
  • G. Rodríguez, Juan

Abstract

Technological change fuels economic growth, but its impact on wage inequality remains contested. This study presents a unified empirical framework that isolates the effects of new technologies such as automation and AI on the entire wage distribution. We develop a continuous and task-sensitive automation index and propose a distributional counterfactual-based method. Applying the approach to Spanish micro-data for 2000-2019 and instrumenting technology variables, we find automation to be a key driver of inequality: without task displacement the Gini coefficient would be 21.5% lower and significant wage shares would shift from the top 10% towards middle and bottom groups. Automation is found to barely affect the gender gap in the period studied, yet to widen the education premium. Like automation, AI exposure increases inequality, although the mechanisms to impact wages differ: automation tends to negatively impact wages in the middle of the distribution, while AI tends to increase wages at the top. Trade, offshorability, educational attainment, employment rates and mark-ups play secondary, period specific roles. The results can inform policies on skill formation and inclusive innovation.

Suggested Citation

  • Sebastian, Raquel & Salas-Rojo, Pedro & C. Palomino, Juan & G. Rodríguez, Juan, 2026. "New technologies and the rise of wage inequality," INET Oxford Working Papers 2026-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    • Handle: RePEc:amz:wpaper:2026-04
    as

    Download full text from publisher

    File URL: https://oms-inet.files.svdcdn.com/production/files/New_Technologies_And_The_Rise_Of_Wage_Inequality_WP_Feb_26.pdf?dm=1770737796
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sala-i-Martin, Xavier X, 1996. "The Classical Approach to Convergence Analysis," Economic Journal, Royal Economic Society, vol. 106(437), pages 1019-1036, July.
    2. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
    3. Jurkat Anne & Klump Rainer & Schneider Florian, 2022. "Tracking the Rise of Robots: The IFR Database," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 242(5-6), pages 669-689, December.
    4. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    5. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    6. Frank A. Cowell, 1980. "On the Structure of Additive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(3), pages 521-531.
    7. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    8. Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-1381, September.
    9. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    10. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    11. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    12. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    13. Maarten Goos & Alan Manning, 2007. "Lousy and Lovely Jobs: The Rising Polarization of Work in Britain," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 118-133, February.
    14. Stefania Albanesi & António Dias da Silva & Juan F Jimeno & Ana Lamo & Alena Wabitsch, 2025. "New technologies and jobs in Europe," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 71-139.
    15. Carlos Cinelli & Chad Hazlett, 2020. "Making sense of sensitivity: extending omitted variable bias," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(1), pages 39-67, February.
    16. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    17. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    18. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    19. Anthony F. Shorrocks & James E. Foster, 1987. "Transfer Sensitive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 54(3), pages 485-497.
    20. Luis Ayala & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The impact of different data sources on the level and structure of income inequality," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(3), pages 583-611, September.
    21. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    22. Alan S. Blinder, 2009. "How Many US Jobs Might be Offshorable?," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 10(2), pages 41-78, April.
    23. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    24. Josep Pijoan-Mas & Virginia Sanchez-Marcos, 2010. "Spain is Different: Falling Trends of Inequality," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(1), pages 154-178, January.
    25. Rodríguez, Juan Gabriel & Salas, Rafael, 2014. "The Gini coefficient: Majority voting and social welfare," Journal of Economic Theory, Elsevier, vol. 152(C), pages 214-223.
    26. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    27. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    28. Alan S. Blinder & Alan B. Krueger, 2013. "Alternative Measures of Offshorability: A Survey Approach," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 97-128.
    29. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
    30. David Card & Francis Kramarz & Thomas Lemieux, 1999. "Changes in the Relative Structure of Wages and Employment: A Comparison of the United States, Canada, and France," Canadian Journal of Economics, Canadian Economics Association, vol. 32(4), pages 843-877, August.
    31. Benjamin Ferri, 2022. "Novel Shift-Share Instruments and Their Applications," Boston College Working Papers in Economics 1053, Boston College Department of Economics.
    32. James E. Foster & Efe A. Ok, 1999. "Lorenz Dominance and the Variance of Logarithms," Econometrica, Econometric Society, vol. 67(4), pages 901-908, July.
    33. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    34. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    35. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    36. Foster, James E. & Shneyerov, Artyom A., 2000. "Path Independent Inequality Measures," Journal of Economic Theory, Elsevier, vol. 91(2), pages 199-222, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefania Albanesi & António Dias da Silva & Juan F Jimeno & Ana Lamo & Alena Wabitsch, 2025. "New technologies and jobs in Europe," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 71-139.
    2. Łukasz Arendt & Eugeniusz Kwiatkowski, 2023. "Kontrowersje wokół wpływu nowoczesnych technologii na zatrudnienie i bezrobocie," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 195-216.
    3. Parteka, Aleksandra & Wolszczak-Derlacz, Joanna & Nikulin, Dagmara, 2024. "How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. Florencia Jaccoud, 2025. "Robots & AI exposure and wage inequality: a within occupation approach," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(4), pages 1035-1090, December.
    5. Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational Tasks and Wage Inequality in Germany: A Decomposition Analysis," IZA Discussion Papers 15702, IZA Network @ LISER.
    6. Britta Matthes & Bernhard Christoph & Florian Janik & Michael Ruland, 2014. "Collecting information on job tasks—an instrument to measure tasks required at the workplace in a multi-topic survey [Die Erfassung von Job-Tasks in persönlichen Befragungen. Ein neues Instrument zur Erhebung von Anforderungen am Arbeitsplatz]," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 47(4), pages 273-297, December.
    7. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    8. Salverda, Wiemer & Checchi, Daniele, 2014. "Labour-Market Institutions and the Dispersion of Wage Earnings," IZA Discussion Papers 8220, IZA Network @ LISER.
    9. Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational tasks and wage inequality in West Germany: A decomposition analysis," Labour Economics, Elsevier, vol. 79(C).
    10. Fonseca, Tiago & Lima, Francisco & Pereira, Sonia C., 2018. "Job polarization, technological change and routinization: Evidence for Portugal," Labour Economics, Elsevier, vol. 51(C), pages 317-339.
    11. Caitlin Allen Whitehead & Haroon Bhorat & Robert Hill & Tim Köhler & François Steenkamp, 2021. "The Potential Employment Implications of the Fourth Industrial Revolution Technologies: The Case of the Manufacturing, Engineering and Related Services Sector," Working Papers 202106, University of Cape Town, Development Policy Research Unit.
    12. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.
    13. Edouard Ribes, 2021. "Scoping the transformation of the professional services industry," Working Papers hal-01889350, HAL.
    14. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    15. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    16. Martin Lábaj & Tomáš Oleš & Gabriel Procházka, 2025. "Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(4), pages 953-1001, December.
    17. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the digital divide: Workers' exposure to digitalization and its consequences for individual employment," Discussion Papers 118, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    18. Włoch, Renata & Śledziewska, Katarzyna & Rożynek, Satia, 2025. "Who's afraid of automation? Examining determinants of fear of automation in six European countries," Technology in Society, Elsevier, vol. 81(C).
    19. Nikolaos Terzidis & Raquel Ortega‐Argilés, 2021. "Employment polarization in regional labor markets: Evidence from the Netherlands," Journal of Regional Science, Wiley Blackwell, vol. 61(5), pages 971-1001, November.
    20. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:amz:wpaper:2026-04. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: INET Oxford admin team (email available below). General contact details of provider: https://edirc.repec.org/data/inoxfuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.