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Convergence Clubs in Labor Productivity

In: Convergence Clubs in Labor Productivity and its Proximate Sources

Author

Listed:
  • Carlos Mendez

    (Nagoya University)

Abstract

This chapter studies convergence in labor productivity across developed and developing countries, respectively. Through the lens of a non-linear dynamic factor model, the cross-country dynamics of potential GDP per worker are evaluated over the 1990–2014 period. Results reject the hypothesis that all countries would eventually converge to a common steady-state growth path within their respective groups. Developed countries are characterized by three convergence clubs with largely separating trends. Developing countries are characterized by five convergence clubs. Most clubs are largely below the mean and continue diverging downwards.

Suggested Citation

  • Carlos Mendez, 2020. "Convergence Clubs in Labor Productivity," SpringerBriefs in Economics, in: Convergence Clubs in Labor Productivity and its Proximate Sources, chapter 0, pages 33-39, Springer.
    • Handle: RePEc:spr:spbchp:978-981-15-8629-3_4
    DOI: 10.1007/978-981-15-8629-3_4
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    Citations

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    Cited by:

    1. Andreas Eder & Wolfgang Koller & Bernhard Mahlberg, 2024. "The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach," Journal of Productivity Analysis, Springer, vol. 61(2), pages 157-181, April.
    2. Barbara Dañska-Borsiak, 2023. "Human capital convergence in European NUTS 2 regions," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 18(2), pages 367-392, June.
    3. Mitsuhiko Kataoka & Al-Ikram Taupan Darangina, 2023. "Imperial Manila syndrome in poverty reduction: a province-level spatial distribution analysis," Asia-Pacific Journal of Regional Science, Springer, vol. 7(1), pages 1-28, March.
    4. Uğur Ursavaş & Carlos Mendez, 2023. "Regional income convergence and conditioning factors in Turkey: revisiting the role of spatial dependence and neighbor effects," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(2), pages 363-389, October.
    5. Irving G'omez-M'endez & Chainarong Amornbunchornvej, 2024. "Regional and spatial dependence of poverty factors in Thailand, and its use into Bayesian hierarchical regression analysis," Papers 2408.09760, arXiv.org.

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