IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-01744614.html

On endogenizing direction vectors in parametric directional distance function-based models

Author

Listed:
  • Rolf Färe
  • Carl Pasurka
  • Michael Vardanyan

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Empirical studies of production technologies using directional distance functions have traditionally resorted to ad hoc ways of choosing direction vectors for these functions. Yet it is well known that the assumptions placed on the direction vector can have a non-negligible impact on the estimation results. Several recent studies have attempted to address this issue using econometric estimation and Data Envelopment Analysis. We demonstrate the use of parametric nonlinear programming to select the direction vector optimally. Data on the US electric power plants from early 2000s are used to show the difference between results obtained with endogenously determined direction vectors and ad hoc vectors.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Rolf Färe & Carl Pasurka & Michael Vardanyan, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," Post-Print hal-01744614, HAL.
    • Handle: RePEc:hal:journl:hal-01744614
    DOI: 10.1016/j.ejor.2017.03.040
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    3. Song, Yao-yao & Li, Jing-jing & Wang, Jin-li & Yang, Guo-liang & Chen, Zhenling, 2022. "Eco-efficiency of Chinese transportation industry: A DEA approach with non-discretionary input," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Rolf Färe & Giannis Karagiannis, 2023. "Translation efficiency and directionally optimal scale," Journal of Economics, Springer, vol. 140(3), pages 259-273, December.
    5. Yuan, Peng & Pu, Yuran & Liu, Chang, 2021. "Improving electricity supply reliability in China: Cost and incentive regulation," Energy, Elsevier, vol. 237(C).
    6. Walheer, Barnabé & Zhang, Linjia, 2018. "Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision making units: the case of the star-rated hotel industry in China," RIEI Working Papers 2018-06, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration.
    7. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
    8. Tsionas, Mike G., 2020. "Directional technology distance functions through duality," Economics Letters, Elsevier, vol. 190(C).
    9. Bogetoft, Peter & Ramírez-Ayerbe, Jasone & Romero Morales, Dolores, 2024. "Counterfactual analysis and target setting in benchmarking," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1083-1095.
    10. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
    11. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
    12. Arabmaldar, Aliasghar & Sahoo, Biresh K. & Ghiyasi, Mojtaba, 2023. "A generalized robust data envelopment analysis model based on directional distance function," European Journal of Operational Research, Elsevier, vol. 311(2), pages 617-632.
    13. Niu, Yiran & Boussemart, Jean-Philippe & Shen, Zhiyang & Vardanyan, Michael, 2024. "Performance evaluation using multi-stage production frameworks: Assessing the tradeoffs among the economic, environmental, and social well-being," European Journal of Operational Research, Elsevier, vol. 318(3), pages 1000-1013.
    14. Du, Limin & Lu, Yunguo & Ma, Chunbo, 2022. "Carbon efficiency and abatement cost of China's coal-fired power plants," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    15. Jindal, Abhinav & Nilakantan, Rahul & Sinha, Avik, 2024. "CO2 emissions abatement costs and drivers for Indian thermal power industry," Energy Policy, Elsevier, vol. 184(C).
    16. Flavius Badau & Nicholas Rada, 2022. "Disequilibrium effects from misallocated markets: An application to agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 592-604, July.
    17. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    18. Zhou, Yi & Zhou, Wenji & Wei, Chu, 2023. "Environmental performance of the Chinese cement enterprise: An empirical analysis using a text-based directional vector," Energy Economics, Elsevier, vol. 125(C).
    19. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
    20. Barnabé Walheer, 2019. "Dynamic directional nonparametric profit efficiency analysis for a single decision-making unit: an aggregation approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 1123-1149, December.
    21. Moriah Bostian & Rolf Färe & Shawna Grosskopf & Tommy Lundgren, 2022. "Prevention or cure? Optimal abatement mix," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(4), pages 503-531, October.
    22. Yang, Haoran & Chen, Qiu, 2025. "Material balance and correction for the measurement of green total factor productivity growth," Energy Economics, Elsevier, vol. 148(C).
    23. Rolf Färe & Xinju He & Sungko Li & Valentin Zelenyuk, 2019. "A Unifying Framework for Farrell Profit Efficiency Measurement," Operations Research, INFORMS, vol. 67(1), pages 183-197, January.
    24. Fukuyama, Hirofumi & Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2021. "Measuring the capacity utilization of the 48 largest iron and steel enterprises in China," European Journal of Operational Research, Elsevier, vol. 288(2), pages 648-665.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-01744614. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.