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Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis

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  • Hosseinzadeh, Ahmad
  • Smyth, Russell
  • Valadkhani, Abbas
  • Le, Viet

Abstract

We identify the balance of efficiency gains and losses for 33 Australian mining firms over the period 2008–2014 using bootstrap data envelopment analysis (DEA). We ascertain which companies climbed the efficiency ladder and which companies slipped back in efficiency over time. We find that mining companies involved in metal processing or mining services have been more efficient than those involved in exploration and extraction activities. Assuming variable returns to scale (VRS), on average, we find that mining firms could improve their performance between a minimum of 17% in 2010 and a maximum of 34% in 2008, relative to the best practice performers. We find that, overall, most mining companies became more efficient over time, with the top performers generally maintaining a ranking in the top third of companies in terms of efficiency throughout the period.

Suggested Citation

  • Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
  • Handle: RePEc:eee:ecmode:v:57:y:2016:i:c:p:26-35
    DOI: 10.1016/j.econmod.2016.04.008
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    References listed on IDEAS

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    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    4. Dean Parham, 2013. "Australia's Productivity: Past, Present and Future," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 46(4), pages 462-472, December.
    5. Simon Zheng & Harry Bloch, 2014. "Australia’s mining productivity decline: implications for MFP measurement," Journal of Productivity Analysis, Springer, vol. 41(2), pages 201-212, April.
    6. Stacy Eller & Peter Hartley & Kenneth Medlock, 2011. "Empirical evidence on the operational efficiency of National Oil Companies," Empirical Economics, Springer, vol. 40(3), pages 623-643, May.
    7. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    8. Wanke, Peter & Barros, Carlos Pestana, 2016. "Efficiency drivers in Brazilian insurance: A two-stage DEA meta frontier-data mining approach," Economic Modelling, Elsevier, vol. 53(C), pages 8-22.
    9. Thompson, Russell G. & Dharmapala, P. S. & Thrall, Robert M., 1995. "Linked-cone DEA profit ratios and technical efficiency with application to Illinois coal mines," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 99-115, April.
    10. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2008. "Asymptotics And Consistent Bootstraps For Dea Estimators In Nonparametric Frontier Models," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1663-1697, December.
    11. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    12. Ellis Connolly & David Orsmond, 2011. "The Mining Industry: From Bust to Boom," RBA Research Discussion Papers rdp2011-08, Reserve Bank of Australia.
    13. Arif Syed & R. Quentin Grafton & Kaliappa Kalirajan & Dean Parham, 2015. "Multifactor productivity growth and the Australian mining sector," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(4), pages 549-570, October.
    14. Fare, Rolf & Zelenyuk, Valentin, 2007. "Extending Fare and Zelenyuk (2003)," European Journal of Operational Research, Elsevier, vol. 179(2), pages 594-595, June.
    15. Ellis Connolly & Linus Gustafsson, 2013. "Australian Productivity Growth: Trends and Determinants," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 46(4), pages 473-482, December.
    16. Chen, Yu-Chuan & Chiu, Yung-Ho & Huang, Chin-Wei & Tu, Chien Heng, 2013. "The analysis of bank business performance and market risk—Applying Fuzzy DEA," Economic Modelling, Elsevier, vol. 32(C), pages 225-232.
    17. Asafu-Adjaye, J. & Mahadevan, R., 2003. "How cost efficient are Australia's mining industries?," Energy Economics, Elsevier, vol. 25(4), pages 315-329, July.
    18. Tsolas, Ioannis E., 2011. "Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA," Resources Policy, Elsevier, vol. 36(2), pages 159-167, June.
    19. Kulshreshtha, Mudit & Parikh, Jyoti K., 2002. "Study of efficiency and productivity growth in opencast and underground coal mining in India: a DEA analysis," Energy Economics, Elsevier, vol. 24(5), pages 439-453, September.
    20. Fang, Hong & Wu, Junjie & Zeng, Catherine, 2009. "Comparative study on efficiency performance of listed coal mining companies in China and the US," Energy Policy, Elsevier, vol. 37(12), pages 5140-5148, December.
    21. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    22. Léopold Simar & Valentin Zelenyuk, 2007. "Statistical inference for aggregates of Farrell-type efficiencies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1367-1394.
    23. Ellis Connolly & David Orsmond, 2011. "The Mining Industry: From Bust to Boom," RBA Annual Conference Volume,in: Hugo Gerard & Jonathan Kearns (ed.), The Australian Economy in the 2000s Reserve Bank of Australia.
    24. Fare, Rolf & Zelenyuk, Valentin, 2003. "On aggregate Farrell efficiencies," European Journal of Operational Research, Elsevier, vol. 146(3), pages 615-620, May.
    25. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to scale and damages to scale under natural and managerial disposability: Strategy, efficiency and competitiveness of petroleum firms," Energy Economics, Elsevier, vol. 34(3), pages 645-662.
    26. Charoenrat, Teerawat & Harvie, Charles, 2014. "The efficiency of SMEs in Thai manufacturing: A stochastic frontier analysis," Economic Modelling, Elsevier, vol. 43(C), pages 372-393.
    27. P. Byrnes & R. Färe & S. Grosskopf, 1984. "Measuring Productive Efficiency: An Application to Illinois Strip Mines," Management Science, INFORMS, vol. 30(6), pages 671-681, June.
    28. Wijesiri, Mahinda & Viganò, Laura & Meoli, Michele, 2015. "Efficiency of microfinance institutions in Sri Lanka: a two-stage double bootstrap DEA approach," Economic Modelling, Elsevier, vol. 47(C), pages 74-83.
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    Cited by:

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    More about this item

    Keywords

    Australia; Mining companies; Efficiency; Data envelopment analysis; Bootstrap;

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • N57 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Africa; Oceania
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)

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