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Understanding productivity dynamics: A task taxonomy approach

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  • Fonseca, Tiago
  • Lima, Francisco
  • Pereira, Sonia C.

Abstract

As job markets have been polarizing, firms have been changing their labor inputs. By using matched employer–employee data for Portugal, we examine whether labor market polarization has occurred within or across firms and how labor input upgrades have contributed to overall productivity growth. We develop a firm taxonomy based on worker's occupational data. Firms can be focused on one task – Abstract, Manual or Routine – on a combination of tasks, or none. Results show that Abstract firms are the most productive and their share has increased over time. Manual firms, the least productive, have had a stable share throughout the period. Routine firms have seen their share decline over time. The dynamic decomposition of the estimated productivity reveals that productivity growth is propelled by increased market shares of the most productive incumbents and exiting of the least productive, especially for Abstract firms. Notwithstanding these productivity growth drivers, they fail to avert the productivity stagnation observed in Portugal between 2004 and 2009 due to the overall decline in productivity of incumbent firms, especially Routine. We discuss the policy implications of our results which are relevant to other European economies also lagging behind in terms of knowledge and innovation capabilities.

Suggested Citation

  • Fonseca, Tiago & Lima, Francisco & Pereira, Sonia C., 2018. "Understanding productivity dynamics: A task taxonomy approach," Research Policy, Elsevier, vol. 47(1), pages 289-304.
  • Handle: RePEc:eee:respol:v:47:y:2018:i:1:p:289-304
    DOI: 10.1016/j.respol.2017.11.004
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    2. Ge, Chunmian & Huang, Ke-Wei & Kankanhalli, Atreyi, 2020. "Platform skills and the value of new hires in the software industry," Research Policy, Elsevier, vol. 49(1).
    3. Fonseca, Tiago & Lagdami, Khanssa & Schröder-Hinrichs, Jens-Uwe, 2021. "Assessing innovation in transport: An application of the Technology Adoption (TechAdo) model to Maritime Autonomous Surface Ships (MASS)," Transport Policy, Elsevier, vol. 114(C), pages 182-195.
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    5. Minna Saunila & Juhani Ukko & Tero Rantala & Mina Nasiri & Hannu Rantanen, 2020. "Preceding operational capabilities as antecedents for productivity and innovation performance," Journal of Business Economics, Springer, vol. 90(4), pages 537-561, May.

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    More about this item

    Keywords

    Taxonomy; Productivity; Routinization; Technological change; Polarization;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • 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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