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Time substitution with application to data envelopment analysis

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  • Färe, R.
  • Grosskopf, S.
  • Margaritis, D.

Abstract

In this paper we analyze resource allocation distinguishing between the decision of when to begin allocation and over how many periods to apply the resources. We present analytical results for specific production technologies under different returns to scale assumptions, under capacity constraints and for production with technical change. Using a dynamic activity analysis framework we show how to compute in general optimal solutions for resource intensity use.

Suggested Citation

  • Färe, R. & Grosskopf, S. & Margaritis, D., 2010. "Time substitution with application to data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 206(3), pages 686-690, November.
    • Handle: RePEc:eee:ejores:v:206:y:2010:i:3:p:686-690
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    References listed on IDEAS

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    1. 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.
    2. Peter Bogetoft & Dexiang Wang, 2005. "Estimating the Potential Gains from Mergers," Journal of Productivity Analysis, Springer, vol. 23(2), pages 145-171, May.
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    Cited by:

    1. Cherchye, Laurens & De Rock, Bram & Kerstens, Pieter Jan, 2018. "Production with storable and durable inputs: Nonparametric analysis of intertemporal efficiency," European Journal of Operational Research, Elsevier, vol. 270(2), pages 498-513.
    2. Shixiong Cheng & Wei Liu & Kai Lu, 2018. "Economic Growth Effect and Optimal Carbon Emissions under China’s Carbon Emissions Reduction Policy: A Time Substitution DEA Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
    3. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    4. Fukuyama, Hirofumi & Weber, William L. & Xia, Yin, 2016. "Time substitution and network effects with an application to nanobiotechnology policy for US universities," Omega, Elsevier, vol. 60(C), pages 34-44.
    5. Han, Rong & Yu, Bi-Ying & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2017. "Carbon emissions quotas in the Chinese road transport sector: A carbon trading perspective," Energy Policy, Elsevier, vol. 106(C), pages 298-309.
    6. Antonio Peyrache & Maria C. A. Silva, 2023. "Efficiency decomposition for multi-level multi-components production technologies," Journal of Productivity Analysis, Springer, vol. 60(3), pages 273-294, December.
    7. Rolf Färe & Shawna Grosskopf & Dimitris Margaritis, 2012. "Introduction," Journal of Productivity Analysis, Springer, vol. 37(3), pages 203-204, June.
    8. Rasmus Bøgh Holmen & Timo Kuosmanen & Jaan Masso & Per Botolf Maurseth & Kenneth Løvold Rødseth, 2024. "Optimal Intertemporal Broadband Investments To Promote Regional Economic Development," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 149, Faculty of Economics and Business Administration, University of Tartu (Estonia).

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    More about this item

    Keywords

    C61 D92 Time substitution Intertemporal optimization Data envelopment analysis;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing

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