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Abstract

Dynamisation of efficiency in data envelopment analysis may be viewed in several forms, depending on the interpretation of efficiency. Four different interpretations have been discussed in the current literature. One is the economic theory of technical efficiency and allocative (price) efficiency, where the former characterizes a production frontier and the latter the degree of correctness in adaptation of factor proportions to the ratio of factor prices. When the factor prices are observed as competitive market prices, the allocatively efficient firms follow an expansion path which is optimal in each period. This optimal expansion path may be called the expansion frontier. A second view is to consider the production function underlying the DEA models with dynamic inputs such as capital, technology and capacity variables, each of which has significant impact on output for several periods in the future. Efficiency in this framework is characterized by the capacity frontier or the technology frontier. The third form of efficiency defines an adjustment frontier as in model (3.l0c) of Chapter One, where the coefficients of the production frontier are modified due to various time lags of adjustment of inputs. This type of model allows a two-stage interpretation of efficiency, with a short and a long run view of the state space model.

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References

  • Bellman, R. (1957), Dynamic Programming, Princeton: Princeton University Press.

    Google Scholar 

  • Charnes, A., Cooper, W.W., Lewin, A. and L.M. Seiford (1994), Data Envelopment Analysis: Theory, Methodology and Applications, to be published.

    Book  Google Scholar 

  • Cooper, W.W., Huang, Z. and S.X. Li (1994), “Satisficing DEA Models Under Chance Constraints,” working paper, University of Texas at Austin.

    Google Scholar 

  • Dixit, A.K. and R.S. Pindyck (1994), Investment Under Uncertainty, Princeton, University Press.

    Google Scholar 

  • Enos, J.L. and W.H. Park (1988), The Adoption and Diffusion of Imported Technology, London: Croom Helm Publishers.

    Google Scholar 

  • Farrell, M.J. (1957), “The Measurement of Productive Efficiency,” Journal of Royal Statistical Society, Series A, Vol. 120, pp. 253–290.

    Article  Google Scholar 

  • Grosskopf, S. (1993), “Efficiency and Productivity,” in The Measurement of Productive Efficiency: Techniques and Applications, New York: Oxford University Press.

    Google Scholar 

  • Johansen, L. (1972), Production Functions, Amsterdam: North Holland.

    Google Scholar 

  • Kwon, J.K. (1986), “Capital Utilization, Economies of Scale and Technical Change in the Growth of Total Factor Productivity,” Journal of Development Economics, Vol. 24, pp. 75–89.

    Article  Google Scholar 

  • Morrison, C.J. and E.R. Berndt (1981), “Short-run Labor Productivity in a Dynamic Model,” Journal of Econometrics, Vol. 16, pp. 339–365.

    Article  Google Scholar 

  • Norsworthy, J.R. and S.L. Jang (1992), Empi ri cal Measurement and Analysis of Productivity and Technological Change, Amsterdam: North Holland.

    Google Scholar 

  • Proschan, F. (1974), “Recent Research on Classes of Life Distributions Useful in Maintenance Modeling,” FSU Statistical Report M291.

    Google Scholar 

  • Salukvadze, M.E. (1979), Vector-valued Optimization Problems in Control Theory, New York: Academic Press.

    Google Scholar 

  • Sengupta, J.K. (1987), “Efficiency Measurement in Nonmarket Systems through Data Envelopment Analysis,” International Journal of Systems Science, Vol. 18, pp. 2279–2304.

    Article  Google Scholar 

  • Sengupta, J.K. (1992), “Adjustment Costs in Production Frontier Analysis,” Economic Notes, Vol. 21, pp. 316–329.

    Google Scholar 

  • Sengupta, J.K. (1994), “Evaluating Dynamic Efficiency by Optimal Control,” International Journal of Systems Science, Vol. 25, pp. 1337–1353.

    Article  Google Scholar 

  • Treadway, A. B. (1974), “The Globally Optimal Flexible Accelerator,” Journal of Economic Theory, Vol. 7, pp. 17–39.

    Article  Google Scholar 

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© 1995 Springer Science+Business Media Dordrecht

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Sengupta, J.K. (1995). Dynamics of Efficiency. In: Dynamics of Data Envelopment Analysis. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8506-4_2

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  • DOI: https://doi.org/10.1007/978-94-015-8506-4_2

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4582-9

  • Online ISBN: 978-94-015-8506-4

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