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Firm Size And Efficiency In The South African Motor Vehicle Industry




The South African motor vehicle industry has historically been considered a critical industry in the South African economy and the target of numerous government policies designed to protect it and/or increase its international competitiveness. This study examines the cost performance of firms in this industry according to their size, using data categorised by output level. The results are consistent with statistically significant economies of scale at the lowest output levels and a cost inefficiency averaging from about seven to nine per cent for all firms. The findings also suggest that all else equal, the smallest firms and the largest firms have lower unit costs than mid-sized firms. While this work suggests that policies that would give incentives for the smallest firms to increase their scale of operations might help to reduce their unit costs, further investigation needs to be done with respect to why firms in the mid-level size categories appear to be less efficient. Copyright 2009 The Authors. Journal compilation 2009 Blackwell Publishing Ltd/University of Adelaide and Flinders University.

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  • Lila J. Truett & Dale B. Truett, 2009. "Firm Size And Efficiency In The South African Motor Vehicle Industry ," Australian Economic Papers, Wiley Blackwell, vol. 48(4), pages 333-341, December.
  • Handle: RePEc:bla:ausecp:v:48:y:2009:i:4:p:333-341

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    References listed on IDEAS

    1. Anthony Black, 2001. "Globalization and restructuring in the South African automotive industry," Journal of International Development, John Wiley & Sons, Ltd., vol. 13(6), pages 779-796.
    2. Vitaliano, Donald F. & Toren, Mark, 1994. "Cost and efficiency in nursing homes: a stochastic frontier approach," Journal of Health Economics, Elsevier, vol. 13(3), pages 281-300, October.
    3. Justin Barnes, 2000. "Changing lanes: The political economy of the South African automotive value chain," Development Southern Africa, Taylor & Francis Journals, vol. 17(3), pages 401-415.
    4. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    5. 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.
    6. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, March.
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