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Understanding productivity dynamics:a task taxonomy approach

Tiago Fonseca (), Francisco Lima () and Sonia C. Pereira
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Sonia C. Pereira: Barnard College, Columbia University and Columbia School of Social Work

No 80, GEE Papers from Gabinete de Estratégia e Estudos, Ministério da Economia

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 reveal 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.

Keywords: Taxonomy; productivity; routinization; technological change; polarization (search for similar items in EconPapers)
JEL-codes: D24 L23 O33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cta, nep-eff, nep-ent, nep-eur, nep-ino, nep-sbm and nep-tid
Date: 2017-09, Revised 2017-09
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http://www.gee.gov.pt/RePEc/WorkingPapers/GEE_PAPERS_80.pdf First version, 2017 (application/pdf)

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