IDEAS home Printed from https://ideas.repec.org/a/aen/journl/ej41-3-lien.html
   My bibliography  Save this article

Disentangling Costs of Persistent and Transient Technical Inefficiency and Input Misallocation: The Case of Norwegian Electricity Distribution Firms

Author

Listed:
  • Subal C. Kumbhakar, Orjan Mydland, Andrew Musau, and Gudbrand Lien

Abstract

Numerous studies have focused on estimating technical inefficiency in electricity distribution firms. However, most of these studies did not distinguish between persistent and transient technical inefficiency. Furthermore, almost none of the studies estimated the cost of input misallocation arising from non-optimal use of inputs. One reason is that the cost function (input distance function) typically used in the literature does not allow for the separation of technical inefficiency and allocative inefficiency. In this study, we estimate both the persistent and transient components of technical inefficiency and input misallocation of Norwegian electricity distribution firms, using panel data from 2000 to 2016. Our modeling and estimation strategy is to use a system approach, consisting of the production function and the first-order conditions of cost minimization. Input misallocation for each pair of inputs is modeled via the first-order conditions of cost minimization. We also estimate the costs of each component of technical inefficiency and input misallocation by deriving the cost function for a multi-output separable production technology. Our modeling and estimation strategy handles endogeneity of inputs. Finally, we allow for inclusion of determinants of persistent and transient technical inefficiency. Our results show that the costs of input misallocation of Norwegian electricity distribution firms are non-negligible.

Suggested Citation

  • Subal C. Kumbhakar, Orjan Mydland, Andrew Musau, and Gudbrand Lien, 2020. "Disentangling Costs of Persistent and Transient Technical Inefficiency and Input Misallocation: The Case of Norwegian Electricity Distribution Firms," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 143-160.
  • Handle: RePEc:aen:journl:ej41-3-lien
    as

    Download full text from publisher

    File URL: http://www.iaee.org/en/publications/ejarticle.aspx?id=3505
    Download Restriction: Access to full text is restricted to IAEE members and subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jiro Nemoto & Mika Goto, 2006. "Measurement of technical and allocative efficiencies using a CES cost frontier: a benchmarking study of Japanese transmission-distribution electricity," Empirical Economics, Springer, vol. 31(1), pages 31-48, March.
    2. Finn Førsund & Lennart Hjalmarsson, 2004. "Are all Scales Optimal in DEA? Theory and Empirical Evidence," Journal of Productivity Analysis, Springer, vol. 21(1), pages 25-48, January.
    3. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Endogeneity in panel data stochastic frontier model with determinants of persistent and transient inefficiency," Economics Letters, Elsevier, vol. 162(C), pages 5-9.
    4. Henderson,Daniel J. & Parmeter,Christopher F., 2015. "Applied Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521279680, September.
    5. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521012263, September.
    6. Subal Kumbhakar & Roar Amundsveen & Hilde Kvile & Gudbrand Lien, 2015. "Scale economies, technical change and efficiency in Norwegian electricity distribution, 1998–2010," Journal of Productivity Analysis, Springer, vol. 43(3), pages 295-305, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim J.S., 2024. "Can operational efficiency in the Portuguese electricity sector be improved? Yes, but..," Energy Policy, Elsevier, vol. 190(C).
    2. Liu, Tung, 2021. "Measuring cost inefficiency: A dual approach," Economic Modelling, Elsevier, vol. 99(C).
    3. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
    4. Just, Lisa & Wetzel, Heike, 2020. "Distributed Generation and Cost Efficiency of German Electricity Distribution Network Operators," EWI Working Papers 2020-9, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    5. Tommy Lundgren & Mattias Vesterberg, 2024. "Efficiency in electricity distribution in Sweden and the effects of small-scale generation, electric vehicles and dynamic tariffs," Journal of Productivity Analysis, Springer, vol. 62(2), pages 121-137, October.
    6. Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Efficiency Measurement in Norwegian Electricity Distribution: A Generalized Four-Way-Error-Component Stochastic Frontier Model," The Energy Journal, , vol. 44(2), pages 181-204, March.

    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. Liu, Xiao-Yan & Pollitt, Michael G. & Xie, Bai-Chen & Liu, Li-Qiu, 2019. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Energy Economics, Elsevier, vol. 83(C), pages 333-344.
    2. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
    3. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim J.S., 2024. "Can operational efficiency in the Portuguese electricity sector be improved? Yes, but..," Energy Policy, Elsevier, vol. 190(C).
    4. Almeida, Alexandre N. & Bravo-Ureta, Boris E., 2019. "Agricultural productivity, shadow wages and off-farm labor decisions in Nicaragua," Economic Systems, Elsevier, vol. 43(1), pages 99-110.
    5. Yashar Tarverdi, 2018. "Aspects of Governance and $$\hbox {CO}_2$$ CO 2 Emissions: A Non-linear Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 167-194, January.
    6. Almeida, Alexandre N. & Santos, Augusto S. & Halmenschlager, Vinícius & Gilio, Leandro & Diniz, Tiago B. & Ferreira, Alexandre A. S., 2016. "Flexible-fuel automobiles and CO2 emissions in Brazil: a semiparametric analysis using panel data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235733, Agricultural and Applied Economics Association.
    7. Fernando Rios-Avila, 2019. "A Semi-Parametric Approach to the Oaxaca–Blinder Decomposition with Continuous Group Variable and Self-Selection," Econometrics, MDPI, vol. 7(2), pages 1-29, June.
    8. Agrell, Per J. & Teusch, Jonas, 2020. "Predictability and strategic behavior under frontier regulation," Energy Policy, Elsevier, vol. 137(C).
    9. Førsund, Finn, 2015. "Economic Perspectives on DEA," Memorandum 10/2015, Oslo University, Department of Economics.
    10. David H. Bernstein & Christopher F. Parmeter, 2017. "Returns to Scale in Electricity Generation: Revisited and Replicated," Working Papers 2017-08, University of Miami, Department of Economics.
    11. Kumbhakar, Subal C. & Badunenko, Oleg & Willox, Michael, 2022. "Do carbon taxes affect economic and environmental efficiency? The case of British Columbia’s manufacturing plants," Energy Economics, Elsevier, vol. 115(C).
    12. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    13. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    14. Battisti, Michele & Gatto, Massimo Del & Parmeter, Christopher F., 2022. "Skill-biased technical change and labor market inefficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    15. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    16. Luis Orea, Inmaculada C. Álvarez, and Tooraj Jamasb, 2018. "A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    17. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    18. Jamasb, T. & Söderberg, M., 2009. "Yardstick and Ex-post Regulation by Norm Model: Empirical Equivalence, Pricing Effect, and Performance in Sweeden," Cambridge Working Papers in Economics 0908, Faculty of Economics, University of Cambridge.
    19. Xie, Bai-Chen & Zhang, Zhen-Jiang & Anaya, Karim L., 2021. "Has the unbundling reform improved the service efficiency of China's power grid firms?," Energy Economics, Elsevier, vol. 95(C).
    20. Friehe, Tim & Pannenberg, Markus, 2019. "Overconfidence over the lifespan: Evidence from Germany," Journal of Economic Psychology, Elsevier, vol. 74(C).

    More about this item

    JEL classification:

    • F0 - International Economics - - General

    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:aen:journl:ej41-3-lien. 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: David Williams (email available below). General contact details of provider: https://edirc.repec.org/data/iaeeeea.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.