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Parametric decomposition of the input-oriented Malmquist productivity index: with an application to Greek aquaculture

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  • Christos Pantzios
  • Giannis Karagiannis
  • Vangelis Tzouvelekas

    ()

Abstract

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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File URL: http://hdl.handle.net/10.1007/s11123-010-0202-2
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Bibliographic Info

Article provided by Springer in its journal Journal of Productivity Analysis.

Volume (Year): 36 (2011)
Issue (Month): 1 (August)
Pages: 21-31

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Handle: RePEc:kap:jproda:v:36:y:2011:i:1:p:21-31

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Web page: http://www.springerlink.com/link.asp?id=100296

Related research

Keywords: Malmquist productivity index; Stochastic input distance function; Greek aquaculture farms; C23; D24; Q22;

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References

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  1. 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.
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  3. Rossi, Martin A., 2001. "Technical change and efficiency measures: the post-privatisation in the gas distribution sector in Argentina," Energy Economics, Elsevier, vol. 23(3), pages 295-304, May.
  4. 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.
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  6. 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.
  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. C. Lovell, 2003. "The Decomposition of Malmquist Productivity Indexes," Journal of Productivity Analysis, Springer, vol. 20(3), pages 437-458, November.
  9. 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.
  10. 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.
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Cited by:
  1. Pierrick Jan & Markus Lips & Michel Dumondel, 2012. "Total factor productivity change of Swiss dairy farms in the mountain region in the period 1999 to 2008," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 93(3), pages 273-298.
  2. Yu, Bingxin & Liao, Xiyuan & Shen, Hongfang, 2013. "Parametric decomposition of the malmquist index in an output-oriented distance function: Productivity in Chinese agriculture," IFPRI discussion papers 1244, International Food Policy Research Institute (IFPRI).

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