IDEAS home Printed from https://ideas.repec.org/a/oup/oxecpp/v74y2022i1p115-135..html
   My bibliography  Save this article

Technological unemployment revisited: automation in a search and matching framework
[The future of work: meeting the global challenges of demographic change and automation]

Author

Listed:
  • Dario Cords
  • Klaus Prettner

Abstract

Will automation raise unemployment and what is the role of education in this context? To answer these questions, we propose a search and matching model of the labour market with two skill types and with industrial robots. In line with evidence to date, robots are better substitutes for low-skilled workers than for high-skilled workers. We show that robot adoption leads to rising unemployment and falling wages of low-skilled workers and falling unemployment and rising wages of high-skilled workers. In a calibration to Austrian and German data, we find that robot adoption destroys fewer low-skilled jobs than the number of high-skilled jobs it creates. For Australia and the USA, the reverse holds true. Allowing for endogenous skill acquisition of workers implies positive employment effects of automation in all four countries. Thus, the firm creation mechanism in the search and matching model and skill acquisition are alleviating the adverse effects of automation.

Suggested Citation

  • Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
  • Handle: RePEc:oup:oxecpp:v:74:y:2022:i:1:p:115-135.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/oep/gpab022
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marcus Hagedorn & Iourii Manovskii & Sergiy Stetsenko, 2016. "Taxation and Unemployment in Models with Heterogeneous Workers," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 19, pages 161-189, January.
    2. George A. Akerlof & Janet L. Yellen, 1990. "The Fair Wage-Effort Hypothesis and Unemployment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(2), pages 255-283.
    3. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2017. "Robots and the skill premium: An automation-based explanation of wage inequality," ECON WPS - Working Papers in Economic Theory and Policy 06/2017, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    4. Mortensen, Dale & Pissarides, Christopher, 2011. "Job Creation and Job Destruction in the Theory of Unemployment," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 1-19.
    5. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
    6. James Albrecht & Susan Vroman, 2002. "A Matching Model with Endogenous Skill Requirements," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(1), pages 283-305, February.
    7. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    8. David E. Bloom & Mathew McKenna & Klaus Prettner, 2018. "Demography, Unemployment, Automation, and Digitalization: Implications for the Creation of (Decent) Jobs, 2010–2030," NBER Working Papers 24835, National Bureau of Economic Research, Inc.
    9. Maya Eden & Paul Gaggl, 2018. "On the Welfare Implications of Automation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 15-43, July.
    10. Juan J. Dolado & Marcel Jansen & Juan F. Jimeno, 2009. "On‐the‐Job Search in a Matching Model with Heterogeneous Jobs and Workers," Economic Journal, Royal Economic Society, vol. 119(534), pages 200-228, January.
    11. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    12. Südekum, Jens & Dauth, Wolfgang & Findeisen, Sebastian & Woessner, Nicole, 2017. "German Robots – The Impact of Industrial Robots on Workers," CEPR Discussion Papers 12306, C.E.P.R. Discussion Papers.
    13. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    14. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 61-103.
    15. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    16. Grossmann, Volker & Steger, Thomas & Trimborn, Timo, 2013. "Dynamically optimal R&D subsidization," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 516-534.
    17. Robert E. Hall & Paul R. Milgrom, 2008. "The Limited Influence of Unemployment on the Wage Bargain," American Economic Review, American Economic Association, vol. 98(4), pages 1653-1674, September.
    18. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    19. Michele Battisti & Gabriel Felbermayr & Giovanni Peri & Panu Poutvaara, 2018. "Immigration, Search and Redistribution: A Quantitative Assessment of Native Welfare," Journal of the European Economic Association, European Economic Association, vol. 16(4), pages 1137-1188.
    20. Abeliansky, Ana L. & Martínez-Zarzoso, Imnaculada & Prettner, Klaus, 2015. "The impact of 3D printing on trade and FDI," University of Göttingen Working Papers in Economics 262, University of Goettingen, Department of Economics.
    21. Gautier, Pieter A, 2002. "Unemployment and Search Externalities in a Model with Heterogeneous Jobs and Workers," Economica, London School of Economics and Political Science, vol. 69(273), pages 21-40, February.
    22. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    23. Andri Chassambouli & Giovanni Peri, 2015. "The Labor Market Effects of Reducing the Number of Illegal Immigrants," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(4), pages 792-821, October.
    24. 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.
    25. David Cass, 1965. "Optimum Growth in an Aggregative Model of Capital Accumulation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 32(3), pages 233-240.
    26. Prettner, Klaus, 2019. "A Note On The Implications Of Automation For Economic Growth And The Labor Share," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1294-1301, April.
    27. Michael Elsby & Bart Hobijn & Ayseful Sahin, 2013. "The Decline of the U.S. Labor Share," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(2 (Fall)), pages 1-63.
    28. Prettner, Klaus & Strulik, Holger, 2017. "The lost race against the machine: Automation, education and inequality in an R&D-based growth model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    29. repec:nbr:nberch:14019 is not listed on IDEAS
    30. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    31. Gasteiger, Emanuel & Prettner, Klaus, 2017. "A note on automation, stagnation, and the implications of a robot tax," Discussion Papers 2017/17, Free University Berlin, School of Business & Economics.
    32. Belan, Pascal & Carré, Martine & Gregoir, Stéphane, 2010. "Subsidizing low-skilled jobs in a dual labor market," Labour Economics, Elsevier, vol. 17(5), pages 776-788, October.
    33. 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.
    34. Chassamboulli, Andri & Palivos, Theodore, 2013. "The impact of immigration on the employment and wages of native workers," Journal of Macroeconomics, Elsevier, vol. 38(PA), pages 19-34.
    35. Christopher A. Pissarides, 2000. "Equilibrium Unemployment Theory, 2nd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161877, December.
    36. Mortensen, Dale T & Pissarides, Christopher A, 1999. "Unemployment Responses to 'Skill-Biased' Technology Shocks: The Role of Labour Market Policy," Economic Journal, Royal Economic Society, vol. 109(455), pages 242-265, April.
    37. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    38. Per Krusell & Anthony A. Smith Jr., 2015. "Is Piketty's "Second Law of Capitalism" Fundamental?," Journal of Political Economy, University of Chicago Press, vol. 123(4), pages 725-748.
    39. Harald Fadinger & Karin Mayr, 2014. "Skill-Biased Technological Change, Unemployment, And Brain Drain," Journal of the European Economic Association, European Economic Association, vol. 12(2), pages 397-431, April.
    40. Jeffrey D. Sachs & Laurence J. Kotlikoff, 2012. "Smart Machines and Long-Term Misery," NBER Working Papers 18629, National Bureau of Economic Research, Inc.
    41. Prettner, Klaus, 2016. "The implications of automation for economic growth and the labor share," Hohenheim Discussion Papers in Business, Economics and Social Sciences 18-2016, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    42. Pieter A. Gautier & Coen N. Teulings & Aico Van Vuuren, 2010. "On-the-Job Search, Mismatch and Efficiency ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(1), pages 245-272.
    43. Pei Kuang & Tong Wang, 2017. "Labor Market Dynamics With Search Frictions And Fair Wage Considerations," Economic Inquiry, Western Economic Association International, vol. 55(3), pages 1336-1349, July.
    44. Daron Acemoglu & Pascual Restrepo, 2016. "The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment," NBER Working Papers 22252, National Bureau of Economic Research, Inc.
    45. Andri Chassamboulli & Theodore Palivos, 2014. "A Search‐Equilibrium Approach To The Effects Of Immigration On Labor Market Outcomes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55, pages 111-129, February.
    46. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, Oxford University Press, vol. 113(4), pages 1169-1213.
    47. Jeffrey D. Sachs & Seth G. Benzell & Guillermo LaGarda, 2015. "Robots: Curse or Blessing? A Basic Framework," NBER Working Papers 21091, National Bureau of Economic Research, Inc.
    48. repec:bin:bpeajo:v:49:y:2019:i:2018-01:p:1-87 is not listed on IDEAS
    49. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    50. Arthur J. Hosios, 1990. "On The Efficiency of Matching and Related Models of Search and Unemployment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(2), pages 279-298.
    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. Abeliansky, Ana Lucia & Prettner, Klaus, 2017. "Automation and demographic change," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168215, Verein für Socialpolitik / German Economic Association.
    2. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    3. Prettner, Klaus & Strulik, Holger, 2017. "The lost race against the machine: Automation, education and inequality in an R&D-based growth model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    4. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    5. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    6. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    7. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. Gasteiger, Emanuel & Prettner, Klaus, 2017. "A note on automation, stagnation, and the implications of a robot tax," Discussion Papers 2017/17, Free University Berlin, School of Business & Economics.
    9. Xiangbo Liu & Theodore Palivos & Xiaomeng Zhang, 2017. "Immigration, Skill Heterogeneity, And Qualification Mismatch," Economic Inquiry, Western Economic Association International, vol. 55(3), pages 1231-1264, July.
    10. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2017. "Robots and the skill premium: An automation-based explanation of wage inequality," Hohenheim Discussion Papers in Business, Economics and Social Sciences 29-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    11. Pablo Casas & José L. Torres, 2023. "Automation, automatic capital returns, and the functional income distribution," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(1), pages 113-135, January.
    12. Ana Lucia Abeliansky & Klaus Prettner, 2021. "Population Growth and Automation Density: Theory and CrossCountry Evidence," VID Working Papers 2102, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    13. Abeliansky, Ana & Algur, Eda & Bloom, David E. & Prettner, Klaus, 2020. "The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation," IZA Discussion Papers 12962, Institute of Labor Economics (IZA).
    14. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Explaining the Labor Share: Automation Vs Labor Market Institutions," Labour Economics, Elsevier, vol. 75(C).
    15. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    16. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Looking ahead at the effects of automation in an economy with matching frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    17. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    18. Cords, Dario, 2017. "Endogenous technology, matching, and labor unions: Does low-skilled immigration affect the technological alignment of the host country?," Hohenheim Discussion Papers in Business, Economics and Social Sciences 20-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    19. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    20. Maciej Cieślukowski & Przemysław Garsztka & Beata Zyznarska-Dworczak, 2022. "The Impact of Robotification on the Financial Situation of Microenterprises: Evidence from the Financial Services Sector in Poland," Risks, MDPI, vol. 10(2), pages 1-20, February.

    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

    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:oup:oxecpp:v:74:y:2022:i:1:p:115-135.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/oep .

    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.