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Technical Efficiency in the Iron and Steel Industry: A Stochastic Frontier Approach


  • Jung Woo Kim

    (Samsung Economic Research Institute, Seoul, Korea)

  • Jeong Yeon Lee

    () (Graduate School of International Studies, Yonsei University)

  • Jae Yong Kim

    (Korea Institute Public Finance, Seoul Korea)

  • Hoe Kyung Lee

    (Korea Advanced Institute of Science of Science and Technology, Seoul, Korea)


In this paper we examine the technical efficiency of firms in the iron and steel industry and try to identify the factors contributing to the industry's efficiency growth, using a time-varying stochastic frontier model. Based on our findings, which pertain to 52 iron and steel firms over the period of 1978-1997, POSCO and Nippon Steel were the most efficient firms, with their production, on average, exceeding 95 percent of their potential output. Our findings also shed light on possible sources of efficiency growth in the industry. If a firm is government-owned, its privatization is likely to improve its technical efficiency to a great extent. A firm's technical efficiency also tends to be positively related to its production level as measured by a share of the total world production of crude steel. Another important source of efficiency growth identified by our empirical findings is adoption of new technologies and equipment. Our findings clearly indicate that continued efforts to update technologies and equipment are critical in pursuit of efficiency in the iron and steel industry.

Suggested Citation

  • Jung Woo Kim & Jeong Yeon Lee & Jae Yong Kim & Hoe Kyung Lee, 2005. "Technical Efficiency in the Iron and Steel Industry: A Stochastic Frontier Approach," Economics Study Area Working Papers 75, East-West Center, Economics Study Area.
  • Handle: RePEc:ewc:wpaper:wp75

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    References listed on IDEAS

    1. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. Lieberman, Marvin B. & R. Johnson, Douglas, 1999. "Comparative productivity of Japanese and U.S. steel producers, 1958-1993," Japan and the World Economy, Elsevier, vol. 11(1), pages 1-27, January.
    4. Rafael Cuesta, 2000. "A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms," Journal of Productivity Analysis, Springer, vol. 13(2), pages 139-158, March.
    5. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    6. Jefferson, Gary H., 1990. "China's iron and steel industry : Sources of enterprise efficiency and the impact of reform," Journal of Development Economics, Elsevier, vol. 33(2), pages 329-355, October.
    7. Ray, Subhash C. & Kim, Hiung Joon, 1995. "Cost efficiency in the US steel industry: A nonparametric analysis using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 80(3), pages 654-671, February.
    8. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    9. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    10. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    JEL classification:

    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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