Comparing Efficiency Across Various Groups of Firms: A Meta-Frontier Approach

  • Mainak Mazumdar
Part of the Contributions to Economics book series (CE)


In this chapter we have classified firms according to their strategies and structures and compared the efficiency at two different levels viz., the global and local frontiers. The global frontier is constructed by taking into consideration all the firms in the sample and the local frontier by considering only the firms from the group. A cross comparison of the efficiency at two different levels enable us to examine whether the inefficiency arises due to firm specific intrinsic factors or due to its strategies or structure. The analysis reveals that firms undertaking R&D are gradually catching up with the global frontier. We also notice that firms producing only finished products or formulation are by themselves efficient; however, by integrating with the downstream raw-material industry additional efficiency gain is also possible. Similarly for firms selling their product only in the domestic market an additional efficiency gain is possible by changing their strategy and selling their product in the international market.


Efficiency Score Efficiency Level Production Possibility Efficient Firm Bulk Drug 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Assaf A (2009) Accounting for size in efficiency comparisons of airports. Journal of Air Transport Management 15(5):256–258CrossRefGoogle Scholar
  2. Assaf A, Matawie KM (2008) A bootstrapped metafrontier model. Appl Econ Lett 1466–4291Google Scholar
  3. Battese GE, Rao DSP (2002) Technology gap, efficiency and a stochastic metafrontier function. International Journal of Business and Economics 1:87–93Google Scholar
  4. Battese GE, Rao DSP, O’Donnell CJ (2004) A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis 21:91–103CrossRefGoogle Scholar
  5. Bhandari AK, Ray SC (2007) Technical efficiency in the Indian textiles industry: a nonparametric analysis of firm-level data. University of Connecticut Department of Economics Working Paper Series 2007–49Google Scholar
  6. Biman JN, Gockowski J, Nkamleu GB (2008) Technical efficiency and productivity potential of cocoa farmers in West African countries. The Developing Economies 46(3):242–263CrossRefGoogle Scholar
  7. Bos J, Schmiedel H (2007) Comparing efficiency in European banking: a meta-frontier approach. Journal of Banking & Finance 31(7):2081–2102CrossRefGoogle Scholar
  8. Chaudhuri S (2005) The WTO and the India’s pharmaceuticals industry. Oxford University Press, New DelhiGoogle Scholar
  9. Chen KHM (2007) The impact of agglomerative industrial dynamic externalities on regional technology gaps: a case of the ICT industry in Taiwan. Australasian Journal of Regional Studies 13(3):261–287Google Scholar
  10. Coelli T (1996) A guide to Frontier version 4.1: a computer program for stochastic frontier production and cost function estimation. CEPA Working Paper 96/07, Centre for Efficiency and Productivity Analysis, University of New England, ArmidaleGoogle Scholar
  11. Das A, Ray SC, Nag A (2007) Labor-use efficiency in Indian banking: a branch level analysis. Omega 37(2):411–425CrossRefGoogle Scholar
  12. Farrell MJ (1957) The measurement of productive efficiency. J Roy Stat Soc Ser A Gen 120(3):253–281CrossRefGoogle Scholar
  13. Gunaratne LH, Leung PS (2001) Asian black tiger shrimp industry: a productivity analysis. In: Economics and management of shrimp and carp farming in Asia: a collection of research papers based on the ADB/NACA farm performance surveyGoogle Scholar
  14. Hayami Y (1969) Sources of agricultural productivity gap among selected countries. American Journal of Agricultural Economics 51(3):564–575CrossRefGoogle Scholar
  15. Hayami Y, Ruttan VW (1970) Agricultural productivity differences among countries. American Economic Review 60(5):895–911Google Scholar
  16. Hayami Y, Ruttan VW (1971) Agricultural development: an international perspective. Johns Hopkins University Press, Baltimore, p 82Google Scholar
  17. Iyer K, Rambaldi A, Tang KK (2006) Globalisation and the technology gap: regional and time evidence. In: Leading economic and managerial issues involving globalisation. Chapter 15. Nova Scotia, New YorkGoogle Scholar
  18. Kudaligama VP, Yanagida JF (2000) A Comparison of Intercountry Agricultural Production Functions: A Frontier Function Approach. Journal of Economic Development 25(1):57–74Google Scholar
  19. Kuosmanen, T. (2008) Representation theorem for convex nonparametric least squares. The Econometric Journal (to appear).Google Scholar
  20. Kuosmanen, T. 2006. Stochastic nonparametric envelopment of data: Combining virtues of SFA and DEA in unified framework. MTT Discussion Paper 3: 51 s.Google Scholar
  21. Lau LT, Yotopoulos PA (1989) The Metaproduction Function Approach toTechnological Change in World Agriculture. Journal of Development Economics 31:241–269CrossRefGoogle Scholar
  22. Rao DSP, O'Donnell CJ, Battese GE (2003) “Meta-frontier Functions for the Study of Inter-Regional Productivity Differences”, CEPA Working Papers Series, WP012003. University of Queensland, Australia, School of EconomicsGoogle Scholar
  23. Ruttan, V.W., Binswanger, H.P., Hayami, Y., Wade, W.W., & Weber, A. (1978) ‘Factor productivity and growth: A historical interpretation’ in Induced Innovation: Technology, Institution, and Developments, Binswanger, H.P., et V.W. Ruttan, eds., Baltimore: John Hopkins University Press.Google Scholar
  24. Sharma KR, Leung PS (2000) Technical efficiency of carp pond culture in South Asia: An application of stochastic Metaproduction frontier function model. Aquaculture Economics and Management 4:169–189CrossRefGoogle Scholar
  25. Sipilainen, T. & Kuosmanen, T. & Kumbhakar, S.C., (2008) "Measuring productivityError! Bookmark not defined.," 2008 International Congress, August 26–29, 2008, Ghent, Belgium 44277, European Association of Agricultural EconomistsGoogle Scholar
  26. Tybout, J. (2000) ‘Manufacturing firms in developing countries: How well do they do and why ?’ Journal of Economic Literature Vol XXXVIII pp 11–44.Google Scholar
  27. Kawagoe T, Hayami Y (1985) An intercountry comparison of agricultural production efficiency. Am J Agric Econ 67:87–92CrossRefGoogle Scholar
  28. Boshrabadi HM, Villano R, Fleming E (2007) Technical efficiency and environmental-technological gaps in wheat production in Kerman province of Iran. Agric Econ 38(1):67–76CrossRefGoogle Scholar
  29. Chen Z, Shunfeng S (2008) Efficiency and technology gap in China’s agriculture: a regional meta-frontier analysis. China Econ Rev 19(2):287–296CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Centre De Sciences Humaines (CSH)New DelhiIndia

Personalised recommendations