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Comparing Firm Performance Using Transitive Productivity Index Numbers in a Meta-frontier Framework

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The meta-frontier framework has been used extensively for evaluating the technical efficiency of heterogeneous production units that can be classified into different groups. This paper shows how the framework can also be used to make total factor productivity (TFP) comparisons within and across groups. The paper develops a new measure of the distance between a group frontier and the meta-frontier (the so-called ‘technology gap’). It then shows how a spatially- and temporally-transitive TFP index can be decomposed into measures of global technical change (measuring movements in the metafrontier), local technical change (measuring movements in the group frontiers) and efficiency change (measuring movements towards or around the group frontiers). To illustrate the methodology, the paper examines the productive performance of road authorities responsible for maintaining interstate highways in the US state of Virginia.

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  • C.J. O'Donnell & S. Fallah-Fini & K, Triantis, 2011. "Comparing Firm Performance Using Transitive Productivity Index Numbers in a Meta-frontier Framework," CEPA Working Papers Series WP082011, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:68
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    File URL: https://economics.uq.edu.au/files/5196/WP082011.pdf
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    1. Christopher J. O'Donnell, 2010. "Measuring and decomposing agricultural productivity and profitability change ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 527-560, October.
    2. Christopher J. O’Donnell, 2016. "Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 515-541, Springer.
    3. Worthington, Andrew C. & Lee, Boon L., 2008. "Efficiency, technology and productivity change in Australian universities, 1998-2003," Economics of Education Review, Elsevier, vol. 27(3), pages 285-298, June.
    4. Laurenceson, James & O'Donnell, Christopher, 2014. "New estimates and a decomposition of provincial productivity change in China," China Economic Review, Elsevier, vol. 30(C), pages 86-97.
    5. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    6. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    7. C.J. O'Donnell, 2008. "An aggregate quantity-price framework for measuring and Decomposing productivity and profitability change," CEPA Working Papers Series WP072008, School of Economics, University of Queensland, Australia.
    8. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    9. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    10. Melville McMillan & Wing Chan, 2006. "University Efficiency: A Comparison and Consolidation of Results from Stochastic and Non-stochastic Methods," Education Economics, Taylor & Francis Journals, vol. 14(1), pages 1-30.
    11. Kontolaimou, Alexandra & Tsekouras, Kostas, 2010. "Are cooperatives the weakest link in European banking? A non-parametric metafrontier approach," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1946-1957, August.
    12. C.J. O'Donnell, 2011. "The Sources of Productivity Change in the Manufacturing Sectors of the U.S. Economy," CEPA Working Papers Series WP072011, School of Economics, University of Queensland, Australia.
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    Cited by:

    1. Dakpo, K Hervé & Desjeux, Yann & Jeanneaux, Philippe & Latruffe, Laure, 2016. "Productivity, efficiency and technological change in French agriculture during 2002-2014: A Färe-Primont index decomposition," 149th Seminar, October 27-28, 2016, Rennes, France 244793, European Association of Agricultural Economists.
    2. Dakpo, K Hervé & Desjeux, Yann & Jeanneaux, Philippe & Latruffe , Laure, 2017. "Productivity, technical efficiency and technological change in French agriculture during 2002-2014: A Färe-Primont index decomposition," Working Papers 263010, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    3. Mitropoulos, Panagiotis & Talias, Μichael A. & Mitropoulos, Ioannis, 2015. "Combining stochastic DEA with Bayesian analysis to obtain statistical properties of the efficiency scores: An application to Greek public hospitals," European Journal of Operational Research, Elsevier, vol. 243(1), pages 302-311.
    4. Nin-Pratt, Alejandro, 2018. "Agricultural growth, efficiency and family agriculture in Paraguay," IFPRI discussion papers 1747, International Food Policy Research Institute (IFPRI).

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