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DEA and endogenous technological change

Author

Listed:
  • Färe, R.
  • Grosskopf, S.
  • Fukuyama, H.
  • Margaritis, D.

Abstract

In this paper we report on our initial approach to introduce technical change into a DEA model endogenously, through optimization.

Suggested Citation

  • Färe, R. & Grosskopf, S. & Fukuyama, H. & Margaritis, D., 2011. "DEA and endogenous technological change," European Journal of Operational Research, Elsevier, vol. 210(2), pages 457-458, April.
    • Handle: RePEc:eee:ejores:v:210:y:2011:i:2:p:457-458
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    References listed on IDEAS

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    1. 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.
    2. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
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    Cited by:

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    2. Shuai Chen & Jiameng Yang & Xinyi Kang, 2023. "Effect of Fiscal Expenditure for Supporting Agriculture on Agricultural Economic Efficiency in Central China—A Case Study of Henan Province," Agriculture, MDPI, vol. 13(4), pages 1-22, April.
    3. Hsiao-Yin Chen & Chin-wei Huang & Yung-Ho Chiu, 2017. "An intertemporal efficiency and technology measurement for tourist hotel," Journal of Productivity Analysis, Springer, vol. 48(1), pages 85-96, August.
    4. Shuai Chen & Jiameng Yang & Xue Chen, 2024. "Impact of Foreign Direct Investment on Green Total Factor Productivity: New Evidence from Yangtze River Delta in China," Sustainability, MDPI, vol. 16(18), pages 1-24, September.

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