IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v60y2021i6d10.1007_s00181-020-01968-3.html
   My bibliography  Save this article

Managing power supply interruptions: a bottom-up spatial (frontier) model with an application to a Spanish electricity network

Author

Listed:
  • Pablo Argüelles

    (EDP España and University of Oviedo)

  • Luis Orea

    (University of Oviedo and Oviedo Efficiency Group)

Abstract

In December 2013, a new electricity law was approved in Spain as part of an electricity market reform including a new remuneration scheme for distribution companies. This remuneration scheme was updated in December 2019, and the new regulatory framework introduced a series of relevant modifications that aim to encourage regulated firms to reduce their power supply interruptions using a benchmarking approach. While some managerial decisions can prevent electricity power supply interruptions, other managerial decisions are more oriented toward mitigating the consequences of these interruptions. This paper examines the second type of decision using a unique dataset referring to the power supply interruptions of a Spanish distribution company network between 2013 and 2019. We focus our analysis on the effect which grid automatization has on restoration times, the relative efficiency of the maintenance staff, and the importance of its location. We estimate a bottom-up spatial model and a stochastic frontier model to examine both external and internal power supply interruptions at municipal level. While our frontier model is standard, our spatial model differs from a conventional one in that it is developed from scratch using the information of each individual power supply interruption.

Suggested Citation

  • Pablo Argüelles & Luis Orea, 2021. "Managing power supply interruptions: a bottom-up spatial (frontier) model with an application to a Spanish electricity network," Empirical Economics, Springer, vol. 60(6), pages 2867-2896, June.
  • Handle: RePEc:spr:empeco:v:60:y:2021:i:6:d:10.1007_s00181-020-01968-3
    DOI: 10.1007/s00181-020-01968-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-020-01968-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00181-020-01968-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    2. Yu, William & Jamasb, Tooraj & Pollitt, Michael, 2009. "Does weather explain cost and quality performance? An analysis of UK electricity distribution companies," Energy Policy, Elsevier, vol. 37(11), pages 4177-4188, November.
    3. Hung-pin Lai & Cliff Huang, 2010. "Likelihood ratio tests for model selection of stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 34(1), pages 3-13, August.
    4. Giannakis, Dimitrios & Jamasb, Tooraj & Pollitt, Michael, 2005. "Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks," Energy Policy, Elsevier, vol. 33(17), pages 2256-2271, November.
    5. Jamasb, Tooraj & Orea, Luis & Pollitt, Michael, 2012. "Estimating the marginal cost of quality improvements: The case of the UK electricity distribution companies," Energy Economics, Elsevier, vol. 34(5), pages 1498-1506.
    6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    7. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    8. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2013. "A zero inefficiency stochastic frontier model," Journal of Econometrics, Elsevier, vol. 172(1), pages 66-76.
    9. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
    10. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    11. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    12. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    13. Neumayer, Eric & Plümper, Thomas, 2010. "Spatial Effects in Dyadic Data," International Organization, Cambridge University Press, vol. 64(1), pages 145-166, January.
    14. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    15. Parmeter, Christopher F. & Kumbhakar, Subal C., 2014. "Efficiency Analysis: A Primer on Recent Advances," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(3-4), pages 191-385, December.
    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. Subal C. Kumbhakarⓡ & Emir Malikovⓡ & Christopher F. Parmeterⓡ, 2021. "Applications of efficiency and productivity analysis: editors’ introduction," Empirical Economics, Springer, vol. 60(6), pages 2657-2663, June.

    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. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    2. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    4. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    5. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    6. Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2019. "Model averaging estimators for the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 51(2), pages 91-103, June.
    7. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    8. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    9. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    10. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    11. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    12. Luis Orea & Jevgenijs Steinbuks, 2018. "Estimating Market Power In Homogenous Product Markets Using A Composed Error Model: Application To The California Electricity Market," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1296-1321, April.
    13. Jamasb, Tooraj & Llorca, Manuel & Khetrapal, Pavan & Thakur, Tripta, 2021. "Institutions and performance of regulated firms: Evidence from electricity distribution in India," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 68-82.
    14. Seunghwa Rho & Peter Schmidt, 2015. "Are all firms inefficient?," Journal of Productivity Analysis, Springer, vol. 43(3), pages 327-349, June.
    15. Paul, Satya & Shankar, Sriram, 2018. "On estimating efficiency effects in a stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 271(2), pages 769-774.
    16. 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.
    17. Tran, Kien C. & Tsionas, Mike G. & Prokhorov, Artem B., 2023. "Semiparametric estimation of spatial autoregressive smooth-coefficient panel stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1189-1199.
    18. Samuele Centorrino & María Pérez‐Urdiales & Boris Bravo‐Ureta & Alan Wall, 2024. "Binary endogenous treatment in stochastic frontier models with an application to soil conservation in El Salvador," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 365-382, April.
    19. Young Hoon Lee, 2009. "Frontier Models and their Application to the Sports Industry," Working Papers 0903, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    20. Taining Wang & Jinjing Tian & Feng Yao, 2021. "Does high debt ratio influence Chinese firms’ performance? A semiparametric stochastic frontier approach with zero inefficiency," Empirical Economics, Springer, vol. 61(2), pages 587-636, August.

    More about this item

    Keywords

    Electricity distribution; Power supply interruptions; Spatial econometrics; Frontier models;
    All these keywords.

    JEL classification:

    • H54 - Public Economics - - National Government Expenditures and Related Policies - - - Infrastructures
    • L97 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Utilities: General
    • L98 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Government Policy

    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:spr:empeco:v:60:y:2021:i:6:d:10.1007_s00181-020-01968-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.