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Measuring cross-country technological catch-up through variable-parameter FDH

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  • Sergio Destefanis

    (Università degli Studi di Salerno)

  • Giuseppe Storti

    (Università degli Studi di Salerno)

Abstract

In this paper, we estimate indices of technological catch-up for a sample of 52 countries through the FDH approach with variable scaling parameters proposed in Kerstens and Vanden Eeckaut (1999). We show that this technique has significant advantages for the international comparisons of productivity and, more generally, wherever the assumption of convexity for the production set is not likely to be appropriate.

Suggested Citation

  • Sergio Destefanis & Giuseppe Storti, 2002. "Measuring cross-country technological catch-up through variable-parameter FDH," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 109-125, February.
    • Handle: RePEc:spr:stmapp:v:11:y:2002:i:1:d:10.1007_bf02511449
    DOI: 10.1007/BF02511449
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    References listed on IDEAS

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    1. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    2. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 407-443.
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    Cited by:

    1. Walter Briec & Kristiaan Kerstens, 2006. "Input, output and graph technical efficiency measures on non-convex FDH models with various scaling laws: An integrated approach based upon implicit enumeration algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 135-166, June.
    2. J. Vakili & R. Sadighi Dizaji, 2021. "The closest strong efficient targets in the FDH technology: an enumeration method," Journal of Productivity Analysis, Springer, vol. 55(2), pages 91-105, April.
    3. Kristof Witte & Rui Marques, 2011. "Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies," Journal of Productivity Analysis, Springer, vol. 35(3), pages 213-226, June.
    4. Antonella Basso & Stefania Funari, 2017. "The role of fund size in the performance of mutual funds assessed with DEA models," The European Journal of Finance, Taylor & Francis Journals, vol. 23(6), pages 457-473, May.
    5. Destefanis, Sergio & Storti, Giuseppe, 2005. "Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data," MPRA Paper 62336, University Library of Munich, Germany.
    6. Sergio Destefanis & Vania Sena, 2005. "Public capital and total factor productivity: New evidence from the Italian regions, 1970-98," Regional Studies, Taylor & Francis Journals, vol. 39(5), pages 603-617.

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