IDEAS home Printed from https://ideas.repec.org/p/foi/wpaper/2014_04.html
   My bibliography  Save this paper

The Development of Environmental Productivity: the Case of Danish Energy Plants

Author

Listed:
  • Geraldine Henningsen

    (Department of Management Engineering, Technical University of Denmark)

  • Arne Henningsen

    (Department of Food and Resource Economics, University of Copenhagen)

  • Sascha T. Schröder

    (Department of Management Engineering, Technical University of Denmark)

  • Simon Bolwig

    (Department of Management Engineering, Technical University of Denmark)

Abstract

The Danish “Klima 2020” plan sets an ambitious target for the complete phasing-out of fossil fuels by 2050. The Danish energy sector currently accounts for 40% of national CO2 emissions. Based on an extended Farrell input distance function that accounts for CO2 as an undesirable output, we estimate the environmental productivity of individual generator units based on a panel data set for the period 1998 to 2011 that includes virtually all fuel-fired generator units in Denmark. We further decompose total productivity into technical efficiency, best practice ratio, and scale efficiency and use a global Malmquist index to calculate the yearly changes. By applying time series clustering, we can identify high, middle, and low performance groups of generator units in a dynamic setting. Our results indicate that the sectoral productivity only slightly increased over the fourteen years. Furthermore, we find that there is no overall high achiever group, but that the ranking, although time consistent, varies between the different productivity measures. However, we identify steam turbines and combustion engines for combined heat and power production as potential high performers, while combustion engines that only produce electricity are clearly low performers.

Suggested Citation

  • Geraldine Henningsen & Arne Henningsen & Sascha T. Schröder & Simon Bolwig, 2014. "The Development of Environmental Productivity: the Case of Danish Energy Plants," IFRO Working Paper 2014/04, University of Copenhagen, Department of Food and Resource Economics.
  • Handle: RePEc:foi:wpaper:2014_04
    as

    Download full text from publisher

    File URL: http://okonomi.foi.dk/workingpapers/WPpdf/WP2014/IFRO_WP_2014_04.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    3. Bert Balk, 2001. "Scale Efficiency and Productivity Change," Journal of Productivity Analysis, Springer, vol. 15(3), pages 159-183, May.
    4. Agrell, Per J. & Bogetoft, Peter, 2005. "Economic and environmental efficiency of district heating plants," Energy Policy, Elsevier, vol. 33(10), pages 1351-1362, July.
    5. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    6. Yang, Mian & Yang, Fu-Xia & Chen, Xing-Peng, 2011. "Effects of substituting energy with capital on China's aggregated energy and environmental efficiency," Energy Policy, Elsevier, vol. 39(10), pages 6065-6072, October.
    7. Tovar, Beatriz & Javier Ramos-Real, Francisco & de Almeida, Edmar Fagundes, 2011. "Firm size and productivity. Evidence from the electricity distribution industry in Brazil," Energy Policy, Elsevier, vol. 39(2), pages 826-833, February.
    8. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    10. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, December.
    11. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    2. Jradi, Samah & Bouzdine Chameeva, Tatiana & Aparicio, Juan, 2019. "The measurement of revenue inefficiency over time: An additive perspective," Omega, Elsevier, vol. 83(C), pages 167-180.
    3. Chen, Weidong & Geng, Wenxin, 2017. "Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input," Energy, Elsevier, vol. 120(C), pages 283-292.
    4. Andreas Eder & Bernhard Mahlberg & Bernhard Stürmer, 2021. "Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 37-63, February.
    5. Aparicio, Juan & Ortiz, Lidia & Santín, Daniel, 2021. "Comparing group performance over time through the Luenberger productivity indicator: An application to school ownership in European countries," European Journal of Operational Research, Elsevier, vol. 294(2), pages 651-672.
    6. Varun Mahajan & D. K. Nauriyal & S. P. Singh, 2020. "Domestic market competitiveness of Indian drug and pharmaceutical industry," Review of Managerial Science, Springer, vol. 14(3), pages 519-559, June.
    7. Zabala-Iturriagagoitia, Jon Mikel & Aparicio, Juan & Ortiz, Lidia & Carayannis, Elias G. & Grigoroudis, Evangelos, 2021. "The productivity of national innovation systems in Europe: Catching up or falling behind?," Technovation, Elsevier, vol. 102(C).
    8. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    9. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    10. Zarrin, Mansour & Brunner, Jens O., 2023. "Analyzing the accuracy of variable returns to scale data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1286-1301.
    11. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    12. Demiral, Elif E. & Sağlam, Ümit, 2021. "Eco-efficiency and Eco-productivity assessments of the states in the United States: A two-stage Non-parametric analysis," Applied Energy, Elsevier, vol. 303(C).
    13. Shixiong Cheng & Jiahui Xie & De Xiao & Yun Zhang, 2019. "Measuring the Environmental Efficiency and Technology Gap of PM 2.5 in China’s Ten City Groups: An Empirical Analysis Using the EBM Meta-Frontier Model," IJERPH, MDPI, vol. 16(4), pages 1-22, February.
    14. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    15. Giménez, Víctor & Prieto, William & Prior, Diego & Tortosa-Ausina, Emili, 2019. "Evaluation of efficiency in Colombian hospitals: An analysis for the post-reform period," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 20-35.
    16. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    17. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    18. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
    19. 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.
    20. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.

    More about this item

    Keywords

    Environmental productivity; energy sector; productivity analysis; CO2 mitigation; renewable energy; transition;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:foi:wpaper:2014_04. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Geir Tveit (email available below). General contact details of provider: https://edirc.repec.org/data/foikudk.html .

    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.