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Talent, Labor Quality and Economic Development

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  • German Cubas
  • B Ravikumar
  • Gustavo Ventura

Abstract

We develop a quantitative theory of labor quality based on the division of the labor force between unskilled and skilled workers, and investments in the quality of skilled labor. We use the theory to quantify the importance labor quality and Total Factor Productivity for cross-country income differences. A central ingredient in our analysis is the observed achievement levels (talent) constructed from PISA scores in a sample of 59 countries. Our findings imply that the cross-country differences in the quality of labor are almost twice as large as the conventional measures using Mincer returns. Thus, the implied disparities in TFP levels are smaller. The elasticity of output per worker with respect to TFP is about 2.3. We find no support for the hypothesis of skill-biased technology differences across countries.

Suggested Citation

  • German Cubas & B Ravikumar & Gustavo Ventura, 2012. "Talent, Labor Quality and Economic Development," Documentos de trabajo 2012010, Banco Central del Uruguay.
  • Handle: RePEc:bku:doctra:2012010
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    Cited by:

    1. Córdoba, Juan Carlos & Ripoll, Marla, 2013. "What explains schooling differences across countries?," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 184-202.
    2. Nezih Guner & Andrii Parkhomenko & Gustavo Ventura, 2018. "Managers and Productivity Differences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 256-282, July.
    3. International Monetary Fund, 2015. "Chile: Selected Issues," IMF Staff Country Reports 2015/228, International Monetary Fund.
    4. Lutz Hendricks & Todd Schoellman, 2018. "Human Capital and Development Accounting: New Evidence from Wage Gains at Migration," The Quarterly Journal of Economics, Oxford University Press, vol. 133(2), pages 665-700.
    5. Yao, Yao, 2016. "Higher education expansion, economic reform and labor productivity," Working Paper Series 5357, Victoria University of Wellington, School of Economics and Finance.
    6. Tarek M Harchaouia & Murat Üngörb, 2018. "The Lion on the Move Towards the World Frontier: Catching Up or Remaining Stuck?," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 27(3), pages 366-366.
    7. Marti Mestieri & Johanna Schauer & Robert Townsend, 2017. "Human Capital Acquisition and Occupational Choice: Implications for Economic Development," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 25, pages 151-186, April.
    8. Brotherhood, Luiz & Delalibera, Bruno R., 2020. "Minding the gap between schools and universities," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    9. Marika Santoro, 2015. "Long-term Gain, Short-Term Pain: Assessing the Potential Impact of Structural Reforms in Chile," IMF Working Papers 2015/282, International Monetary Fund.
    10. Dhritman Bhattacharya & Nezih Guner & Gustavo Ventura, 2013. "Distortions, Endogenous Managerial Skills and Productivity Differences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 11-25, January.
    11. Yao, Yao, 2019. "Does higher education expansion enhance productivity?," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 169-194.
    12. Restuccia, Diego, 2014. "Barriers to capital accumulation in a model of technology adoption and schooling," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 81-91.
    13. Wei, Wei & Zhang, Wan-Li & Wen, Jun & Wang, Jun-Sheng, 2020. "TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration," Economic Modelling, Elsevier, vol. 91(C), pages 534-549.
    14. Obiols-Homs, F. & Sánchez-Marcos, V., 2018. "Education outcomes and the labor market," Labour Economics, Elsevier, vol. 54(C), pages 14-28.
    15. Yongli Zhang & Sanggyun Na & Jianguang Niu & Beichen Jiang, 2018. "The Influencing Factors, Regional Difference and Temporal Variation of Industrial Technology Innovation: Evidence with the FOA-GRNN Model," Sustainability, MDPI, Open Access Journal, vol. 10(1), pages 1-19, January.
    16. Francesc Obiols-Homs & Virginia Sánchez-Marcos, 2015. "Education, Occupation-Mismatch and Unemployment," Working Papers 807, Barcelona Graduate School of Economics.

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    More about this item

    Keywords

    PISA; Labor Quality; TFP; Economic Development;
    All these keywords.

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General

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