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Parametric Decomposition of the Input-Oriented Malmquist Productivity Index: With an Application to Greek Aquaculture

  • Christos Pantzios
  • Vangelis Tzouvelekas

    ()

    (Department of Economics, University of Crete, Greece)

  • Giannis Karagiannis

    ()

    (Department of Economics, University of Macedonia, Greece)

Using a stochastic frontier approach and a tranlog input distance function, this paper implements the input-oriented Malmquist productivity index to a sample of Greek aquaculture farms. It is decomposed into the effects of technical efficiency change, scale efficiency change, input-mix and, technical change, which is further attributed to neutral, output- and input-induced shifts of the frontier. Implementable expressions for the aforementioned components are obtained using a discrete changes-approach that is consistent with the usual discrete-form data. Empirical findings indicate that the productivity of the farms in the sample increased during the period 1995-99 at a moderate rate of about two percent, and it was shaped up primarily by the input mix-effect and technical change.

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Paper provided by University of Crete, Department of Economics in its series Working Papers with number 0518.

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Length: 27 pages
Date of creation: 00 2005
Date of revision:
Handle: RePEc:crt:wpaper:0518
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  1. Luis Orea, 2002. "Parametric Decomposition of a Generalized Malmquist Productivity Index," Journal of Productivity Analysis, Springer, vol. 18(1), pages 5-22, July.
  2. Rossi, Martín, 2000. "Technical Change and Efficiency Measures: The Post-privatisation in the Gas Distribution Sector in Argentina," UADE Working Papers 7_2000, Instituto de Economía, Universidad Argentina de la Empresa.
  3. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
  4. Fare, Rolf, et al, 1997. " Biased Technical Change and the Malmquist Productivity Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 99(1), pages 119-27, March.
  5. Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
  6. Shawna Grosskopf, 2003. "Some Remarks on Productivity and its Decompositions," Journal of Productivity Analysis, Springer, vol. 20(3), pages 459-474, November.
  7. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
  8. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  9. C. Lovell, 2003. "The Decomposition of Malmquist Productivity Indexes," Journal of Productivity Analysis, Springer, vol. 20(3), pages 437-458, November.
  10. Chambers Robert G. & Fare Rolf, 1994. "Hicks' Neutrality and Trade Biased Growth: A Taxonomy," Journal of Economic Theory, Elsevier, vol. 64(2), pages 554-567, December.
  11. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-39, December.
  12. Nishimizu, Mieko & Page, John M, Jr, 1982. "Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, 1965-78," Economic Journal, Royal Economic Society, vol. 92(368), pages 920-36, December.
  13. Bert Balk, 2001. "Scale Efficiency and Productivity Change," Journal of Productivity Analysis, Springer, vol. 15(3), pages 159-183, May.
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