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Metafrontier Functions for the Study of Inter-regional Productivity Differences

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The paper uses the concept of metafrontier functions to study regional differences in production technologies. The paper has three components. The first deals with the analytical framework necessary for the definition of metafrontier functions. The second component studies the properties of the metafrontier estimated using nonparametric data envelopment analysis (DEA). The third component focuses on the estimation of metafrontiers within the parametric framework of stochastic frontier analysis (SFA). The empirical application of the models uses cross-country agricultural sector data. The DEA and SFA metafrontiers are presented and discussed.

Suggested Citation

  • D.S. Prasada Rao & Christopher J. O'Donnell & George E. Battese, 2003. "Metafrontier Functions for the Study of Inter-regional Productivity Differences," CEPA Working Papers Series WP012003, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uqcepa:01
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    File URL: http://www.uq.edu.au/economics/cepa/docs/WP/WP012003.pdf
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    References listed on IDEAS

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    1. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    2. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    3. 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.
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    Cited by:

    1. Mfon Akpan & Peter Wanke & Jorge Junio Moreira Antunes & Rangan Gupta, 2018. "Unveiling the Endogenous Relationship between Technical Efficiency and Value Creation in Mergers and Acquisitions in Nigeria," Working Papers 201821, University of Pretoria, Department of Economics.
    2. Anup Kumar Bhandari & Subhash C. Ray, 2012. "Technical Efficiency In The Indian Textiles Industry: A Non‐Parametric Analysis Of Firm‐Level Data," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 109-124, January.
    3. Duygun, Meryem & Sena, Vania & Shaban, Mohamed, 2016. "Trademarking activities and total factor productivity: Some evidence for British commercial banks using a metafrontier approach," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 70-80.
    4. Misra, J. & Misra, S.R., 2014. "Technical Efficiency of Fish Farms in West Bengal: Nature, Extent and Implications," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 27(2).
    5. Huang, Yi-Ju & Chen, Ku-Hsieh & Yang, Chih-Hai, 2010. "Cost efficiency and optimal scale of electricity distribution firms in Taiwan: An application of metafrontier analysis," Energy Economics, Elsevier, vol. 32(1), pages 15-23, January.
    6. Nkamleu, Guy Blaise & Sylla, Kalilou & Zonon, Abdoulaye, 2008. "What accounts for growth in African agriculture," MPRA Paper 11102, University Library of Munich, Germany, revised 2008.
    7. 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.
    8. Astrid Cullmann & Christian Hirschhausen, 2008. "Efficiency analysis of East European electricity distribution in transition: legacy of the past?," Journal of Productivity Analysis, Springer, vol. 29(2), pages 155-167, April.
    9. Nkamleu, Guy Blaise, 2007. "Religious faith and agricultural growth: exploring some correlations in Africa," MPRA Paper 11131, University Library of Munich, Germany, revised 2007.
    10. Barros, Carlos Pestana & Wanke, Peter, 2015. "An analysis of African airlines efficiency with two-stage TOPSIS and neural networks," Journal of Air Transport Management, Elsevier, vol. 44, pages 90-102.
    11. Kounetas, Konstantinos & Mourtos, Ioannis & Tsekouras, Konstantinos, 2009. "Efficiency decompositions for heterogeneous technologies," European Journal of Operational Research, Elsevier, vol. 199(1), pages 209-218, November.
    12. Nkamleu, Guy Blaise & Nyemeck, Joachim & Sanogo, Diakalia, 2006. "Metafrontier Analysis of Technology Gap and Productivity Difference in African Agriculture," MPRA Paper 15103, University Library of Munich, Germany.
    13. Nadia BELHAJ HASSINE, 2007. "Technical Efficiency In The Mediterranean Countries’ Agricultural Sector," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 25, pages 27-44.
    14. Gulati, Rachita & Kumar, Sunil, 2016. "Assessing the impact of the global financial crisis on the profit efficiency of Indian banks," Economic Modelling, Elsevier, vol. 58(C), pages 167-181.
    15. Saeid Hajihassaniasl & Recep Kök, 2016. "Scale effect in Turkish manufacturing industry: stochastic metafrontier analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-17, December.
    16. Sahoo, Biresh K. & Singh, Ramadhar & Mishra, Bineet & Sankaran, Krithiga, 2017. "Research productivity in management schools of India during 1968-2015: A directional benefit-of-doubt model analysis," Omega, Elsevier, vol. 66(PA), pages 118-139.
    17. Chiu, Yung-ho & Luo, Zhengying & Chen, Yu-Chuan & Wang, Zebin & Tsai, Min-Pei, 2013. "A comparison of operating performance management between Taiwan banks and foreign banks based on the Meta-Hybrid DEA model," Economic Modelling, Elsevier, vol. 33(C), pages 433-439.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L6 - Industrial Organization - - Industry Studies: Manufacturing

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