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Differences in Job De-Routinization in OECD Countries: Evidence from PIAAC

Author

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  • de la Rica, Sara

    (University of the Basque Country)

  • Gortazar, Lucas

    (World Bank)

Abstract

The aim of the paper is threefold. First, we compute differences on the degree of de-routinization of job contents across a harmonized and hence comparable sample of Anglo-Saxon, many European and even Asian advanced countries. We do so by using very precise information on job contents at the worker level, which allows for job task heterogeneity within occupations. Second we assess the extent to which computer adoption leads to the observed difference in the degree of de-routinization of job contents. Third, we test whether higher degrees of technology adoption are associated to higher wage inequality. Our results show remarkable differences in the degree of de-routinization of job contents across countries, being computer adoption at work a key significant driver of such differences. In particular, ICT use at work explains 13.4% (6.3%) of the cross-country unconditional (conditional) differences in de-routinization of job contents. Regarding the impact of adoption technology on wage inequality, our results indicate that although differences in ICT adoption explain an important and significant part of wage differentials, the effect is homogeneous for all the wage distribution, implying that we cannot find a significant association between wage inequality and technology adoption.

Suggested Citation

  • de la Rica, Sara & Gortazar, Lucas, 2016. "Differences in Job De-Routinization in OECD Countries: Evidence from PIAAC," IZA Discussion Papers 9736, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp9736
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    Cited by:

    1. Agnieszka Piasna & Jan Drahokoupil, 2017. "Gender inequalities in the new world of work," Transfer: European Review of Labour and Research, , vol. 23(3), pages 313-332, August.
    2. Maximilian Longmuir & Carsten Schröde & Matteo Targa, 2020. "De-Routinization of Jobs and Polarization of Earnings: Evidence from 35 Countries," Working Papers 1397, Economic Research Forum, revised 20 Jun 2020.
    3. Pankaj Vashisht & Nisha Rani, 0. "Automation and the Future of Garment Sector Jobs in India," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 0, pages 1-22.
    4. Okubo, Toshihiro, 2022. "Traveling and eating out during the COVID-19 pandemic: The Go To campaign policies in Japan," Japan and the World Economy, Elsevier, vol. 64(C).
    5. Piotr Lewandowski & Albert Park & Wojciech Hardy & Yang Du & Saier Wu, 2022. "Technology, Skills, and Globalization: Explaining International Differences in Routine and Nonroutine Work Using Survey Data," The World Bank Economic Review, World Bank, vol. 36(3), pages 687-708.
    6. Wojciech Hardy & Roma Keister & Piotr Lewandowski, 2016. "Technology or Upskilling? Trends in the Task Composition of Jobs in Central and Eastern Europe," HKUST IEMS Working Paper Series 2016-40, HKUST Institute for Emerging Market Studies, revised Dec 2016.
    7. van der Velde, Lucas, 2022. "Phasing out: Routine tasks and retirement," Journal of Comparative Economics, Elsevier, vol. 50(3), pages 784-803.
    8. Okubo, Toshihiro, 2022. "Telework in the spread of COVID-19," Information Economics and Policy, Elsevier, vol. 60(C).
    9. Mariya Brussevich & Ms. Era Dabla-Norris & Salma Khalid, 2019. "Is Technology Widening the Gender Gap? Automation and the Future of Female Employment," IMF Working Papers 2019/091, International Monetary Fund.
    10. Pankaj Vashisht & Nisha Rani, 2020. "Automation and the Future of Garment Sector Jobs in India," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 63(2), pages 225-246, June.
    11. Toshihiro Okubo, 2024. "Non‐routine tasks and ICT tools in telework," LABOUR, CEIS, vol. 38(2), pages 177-202, June.
    12. Peter Haiss & Bernhard Mahlberg & Daniel Michlits, 2021. "Industry 4.0–the future of Austrian jobs," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 5-36, February.
    13. Martina Bisello & Eleonora Peruffo & Enrique Fernandez-Macias & Riccardo Rinaldi, 2019. "How computerisation is transforming jobs: Evidence from the European Working Conditions Survey," JRC Working Papers on Labour, Education and Technology 2019-02, Joint Research Centre.
    14. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    15. Lewandowski, Piotr & Keister, Roma & Hardy, Wojciech & Górka, Szymon, 2017. "Routine and Ageing? The Intergenerational Divide in the Deroutinisation of Jobs in Europe," IZA Discussion Papers 10732, Institute of Labor Economics (IZA).
    16. Wojciech Hardy & Roma Keister & Piotr Lewandowski, 2018. "Educational upgrading, structural change and the task composition of jobs in Europe," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(2), pages 201-231, April.

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    More about this item

    Keywords

    routine-biased technological change; de-routinization; polarization; PIACC; RIF-Regressions; wage decomposition;
    All these keywords.

    JEL classification:

    • 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
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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