IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v84y2022i1p130-157.html

Automatability of Work and Preferences for Redistribution

Author

Listed:
  • AndrÉ van Hoorn

Abstract

Although the importance of technological change for increasing prosperity is undisputed and economists typically deem it unlikely that labour‐saving technology causes long‐term employment or income losses, people’s anxiety about automation and its distributive consequences can be an important shaper of economic and social policies. This paper considers the political economy of automation, proposing that individuals in occupations more at risk of job loss due to automation have stronger preferences for government redistribution. I analyse individual‐level cross‐national data from the European Social Survey and other sources, covering up to 32 countries and more than 170,000 individuals. I find a robust positive association between occupational automation risk and preferences for redistribution. As long as the conditional (mean) independence assumption is satisfied, my estimates suggest that a one standard deviation increase in automatability increases preferences for redistribution with roughly 0.05 standard deviations, which is comparable to the difference in preferences for redistribution between women and men.

Suggested Citation

  • AndrÉ van Hoorn, 2022. "Automatability of Work and Preferences for Redistribution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 130-157, February.
  • Handle: RePEc:bla:obuest:v:84:y:2022:i:1:p:130-157
    DOI: 10.1111/obes.12460
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/obes.12460
    Download Restriction: no

    File URL: https://libkey.io/10.1111/obes.12460?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Emily Oster, 2019. "Unobservable Selection and Coefficient Stability: Theory and Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 187-204, April.
    2. Petra E. Todd & Weilong Zhang, 2020. "A dynamic model of personality, schooling, and occupational choice," Quantitative Economics, Econometric Society, vol. 11(1), pages 231-275, January.
    3. Ilyana Kuziemko & Michael I. Norton & Emmanuel Saez & Stefanie Stantcheva, 2015. "How Elastic Are Preferences for Redistribution? Evidence from Randomized Survey Experiments," American Economic Review, American Economic Association, vol. 105(4), pages 1478-1508, April.
    4. 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.
    5. Haaland, Ingar & Roth, Christopher, 2020. "Labor market concerns and support for immigration," Journal of Public Economics, Elsevier, vol. 191(C).
    6. Climent Quintana‐Domeque, 2011. "Preferences, Comparative Advantage, and Compensating Wage Differentials for Job Routinization," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 207-229, April.
    7. Roth, Christopher & Wohlfart, Johannes, 2018. "Experienced inequality and preferences for redistribution," Journal of Public Economics, Elsevier, vol. 167(C), pages 251-262.
    8. Gärtner, Manja & Mollerstrom, Johanna & Seim, David, 2017. "Individual risk preferences and the demand for redistribution," Journal of Public Economics, Elsevier, vol. 153(C), pages 49-55.
    9. Erzo F. P. Luttmer & Monica Singhal, 2011. "Culture, Context, and the Taste for Redistribution," American Economic Journal: Economic Policy, American Economic Association, vol. 3(1), pages 157-179, February.
    10. Meltzer, Allan H & Richard, Scott F, 1981. "A Rational Theory of the Size of Government," Journal of Political Economy, University of Chicago Press, vol. 89(5), pages 914-927, October.
    11. David Autor & David Dorn & Gordon Hanson & Kaveh Majlesi, 2020. "Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure," American Economic Review, American Economic Association, vol. 110(10), pages 3139-3183, October.
    12. Vahagn Jerbashian, 2019. "Automation and Job Polarization: On the Decline of Middling Occupations in Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 1095-1116, October.
    13. 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.
    14. Massimo Anelli & Italo Colantone & Piero Stanig, 2019. "We Were the Robots: Automation and Voting Behavior in Western Europe," CESifo Working Paper Series 7758, CESifo.
    15. 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.
    16. 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.
    17. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    18. Alberto Alesina & Stefanie Stantcheva & Edoardo Teso, 2018. "Intergenerational Mobility and Preferences for Redistribution," American Economic Review, American Economic Association, vol. 108(2), pages 521-554, February.
    19. Hans Peter Gruner & Giacomo Corneo, 2000. "Social Limits to Redistribution," American Economic Review, American Economic Association, vol. 90(5), pages 1491-1507, December.
    20. 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.
    21. Ravallion, Martin & Lokshin, Michael, 2000. "Who wants to redistribute?: The tunnel effect in 1990s Russia," Journal of Public Economics, Elsevier, vol. 76(1), pages 87-104, April.
    22. Maria Grazia Pittau & Riccardo Massari & Roberto Zelli, 2013. "Hierarchical Modelling of Disparities in Preferences for Redistribution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 556-584, August.
    23. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LLC, vol. 19(1), pages 4-60, March.
    24. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nakatani, Ryota, 2024. "Optimal Taxation in the Automated Era," MPRA Paper 121347, University Library of Munich, Germany.
    2. Claudio Costanzo, 2022. "Robots, Jobs, and Optimal Fertility Timing," Working Papers ECARES 2022-36, ULB -- Universite Libre de Bruxelles.

    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. van Hoorn, Andre, 2018. "The Political Economy of Automation: Occupational Automatability and Preferences for Redistribution," MPRA Paper 86460, University Library of Munich, Germany.
    2. Jeffrey, Karen, 2021. "Automation and the future of work: How rhetoric shapes the response in policy preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 417-433.
    3. Heyman, Fredrik, 2016. "Job polarization, job tasks and the role of firms," Economics Letters, Elsevier, vol. 145(C), pages 246-251.
    4. 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).
    5. David Kunst, 2019. "Deskilling among Manufacturing Production Workers," Tinbergen Institute Discussion Papers 19-050/VI, Tinbergen Institute, revised 30 Dec 2020.
    6. Zhou, Yuwen & Shi, Xin, 2025. "How does digital technology adoption affect corporate employment? Evidence from China," Economic Modelling, Elsevier, vol. 147(C).
    7. Oussama Chemlal & Wafaa Benomar, 2024. "The Technological Impact on Employment in Spain between 2023 and 2035," Forecasting, MDPI, vol. 6(2), pages 1-30, April.
    8. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, IZA Network @ LISER.
    9. Genz Sabrina & Janser Markus & Lehmer Florian, 2019. "The Impact of Investments in New Digital Technologies on Wages – Worker-Level Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(3), pages 483-521, June.
    10. Terry Gregory & A.M. Salomons & Ulrich Zierahn, 2016. "Racing With or Against the Machine? Evidence from Europe," Working Papers 16-05, Utrecht School of Economics.
    11. 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.
    12. Chuan, Amanda & Zhang, Weilong, 2023. "Non-college Occupations, Workplace Routinization, and the Gender Gap in College Enrollment," IZA Discussion Papers 16089, IZA Network @ LISER.
    13. Michael J. Böhm & Hans-Martin von Gaudecker & Felix Schran, 2024. "Occupation Growth, Skill Prices, and Wage Inequality," Journal of Labor Economics, University of Chicago Press, vol. 42(1), pages 201-243.
    14. Huajie Jiang & Qiguo Gong, 2022. "Does Skill Polarization Affect Wage Polarization? U.S. Evidence 2009–2021," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    15. 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).
    16. Stephany, Fabian & Teutloff, Ole, 2024. "What is the price of a skill? The value of complementarity," Research Policy, Elsevier, vol. 53(1).
    17. 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).
    18. 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.
    19. Andreas Beerli & Ronald Indergand & Johannes S. Kunz, 2023. "The supply of foreign talent: how skill-biased technology drives the location choice and skills of new immigrants," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 681-718, April.
    20. Georg Graetz, 2019. "Labor Demand in the Past, Present, and Future," European Economy - Discussion Papers 114, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    More about this item

    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:bla:obuest:v:84:y:2022:i:1:p:130-157. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/sfeixuk.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.