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Technical Efficiency And Its Dynamics In Indian Manufacturing: An Inter State Analysis

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  • Kankana Mukherjee

    (Department of Management ,Worcester Polytechnic Institute)

  • Subhash C. Ray

    (Department of Economics, University of Connecticut)

Abstract

This paper analyzes state level data from the manufacturing sector in India for the period 1986-87 to 1999-00 to study the efficiency dynamics of a ‘typical’ firm in individual states during the pre- and post reform years. Using the non-parametric method of Data Envelopment Analysis we utilize super-efficiency models to rank the states in terms of their performance and investigate the dynamics of the efficiency rankings over time. We find no major change in the efficiency ranking of states after the reforms. Nor is there any evidence of convergence in the distribution of efficiency in the post-reform period.

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Bibliographic Info

Article provided by Department of Economics, Delhi School of Economics in its journal Indian Economic Review.

Volume (Year): 40 (2005)
Issue (Month): 2 (December)
Pages: 101-125

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Handle: RePEc:dse:indecr:v:40:y:2005:i:2:p:101-125

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Related research

Keywords: super efficiency; convergence; Markov chains.;

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References

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  1. Robert J. Barro & Xavier Sala-i-Martin, 1991. "Convergence across States and Regions," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(1), pages 107-182.
  2. Mitra, Arup & Varoudakis, Aristomene & Veganzones-Varoudakis, Marie-Ange, 2002. "Productivity and Technical Efficiency in Indian States' Manufacturing: The Role of Infrastructure," Economic Development and Cultural Change, University of Chicago Press, vol. 50(2), pages 395-426, January.
  3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
  4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
  5. Lichtenberg, Frank R, 1994. "Testing the Convergence Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 576-79, August.
  6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
  7. Quah, Danny, 1993. " Galton's Fallacy and Tests of the Convergence Hypothesis," Scandinavian Journal of Economics, Wiley Blackwell, vol. 95(4), pages 427-43, December.
  8. Sala-i-Martin, Xavier, 1994. "Cross-sectional regressions and the empirics of economic growth," European Economic Review, Elsevier, vol. 38(3-4), pages 739-747, April.
  9. Barro, Robert J & Sala-i-Martin, Xavier, 1992. "Convergence," Journal of Political Economy, University of Chicago Press, vol. 100(2), pages 223-51, April.
  10. Varian, Hal R, 1984. "The Nonparametric Approach to Production Analysis," Econometrica, Econometric Society, vol. 52(3), pages 579-97, May.
  11. Mei Xue & Patrick T. Harker, 2002. "Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models," Management Science, INFORMS, vol. 48(5), pages 705-710, May.
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Cited by:
  1. Anup Kumar Bhandari, 2010. "Global Crisis, Environment Volatility and Expansion of Tthe Indian Leather Industry," Working Papers id:2500, eSocialSciences.
  2. Mainak Mazumdar & Meenakshi Rajeev & Subhash Ray, 2011. "Sources of Heterogeneity in the Efficiency of Indian Pharmaceutical Firms," Working papers 2011-22, University of Connecticut, Department of Economics.

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