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Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities

Listed author(s):
  • Jorge E. Galán
  • Michael G. Pollitt

The electricity reform in Colombia has exhibited gains in terms of reliability but its effects on firms efficiency and service quality have not been clear. Previous studies evaluating the performance of distribution companies after the reform have not found evidence of improvements, although large differences in efficiency have been found among firms. This suggests high inefficiency persistence and heterogeneity in the Colombian distribution sector. In this paper, we propose an extension of dynamic stochastic frontier models that accounts for unobserved heterogeneity in the inefficiency persistence and in the technology. The model incorporates total expenses, service quality and energy losses in an efficiency analysis of Colombian distributors over fifteen years after the reform. We identify the presence of high inefficiency persistence in the sector, and important differences between firms. In particular, rural companies and firms with small customers present low persistence and evidence the largest gains in efficiency during the period. However, increases in efficiency are only manifested during the last five years when the main improvements in service quality and energy losses are presented. Overall, inefficiency persistence, customer density and consumption density are found to be important criteria to be considered for regulatory purposes.

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File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1423.pdf
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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1423.

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Date of creation: 04 Aug 2014
Handle: RePEc:cam:camdae:1423
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Contact details of provider: Web page: http://www.econ.cam.ac.uk/

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  1. Christian Growitsch & Tooraj Jamasb & Michael Pollitt, 2009. "Quality of service, efficiency and scale in network industries: an analysis of European electricity distribution," Applied Economics, Taylor & Francis Journals, vol. 41(20), pages 2555-2570.
  2. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
  3. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.
  4. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
  5. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
  6. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676.
  7. Pollitt, Michael, 2008. "Electricity reform in Argentina: Lessons for developing countries," Energy Economics, Elsevier, vol. 30(4), pages 1536-1567, July.
  8. Christian von Hirschhausen & Astrid Cullmann & Andreas Kappeler, 2006. "Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2553-2566.
  9. Larsen, Erik R. & Dyner, Isaac & Bedoya V., Leonardo & Franco, Carlos Jaime, 2004. "Lessons from deregulation in Colombia: successes, failures and the way ahead," Energy Policy, Elsevier, vol. 32(15), pages 1767-1780, October.
  10. Huang, Tai-Hsin & Chen, Ying-Hsiu, 2009. "A study on long-run inefficiency levels of a panel dynamic cost frontier under the framework of forward-looking rational expectations," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 842-849, May.
  11. M. Pollitt, 2004. "Electricity reform in Chile. Lessons for developing countries," Competition and Regulation in Network Industries, Intersentia, vol. 5(3), pages 221-263, September.
  12. Ligia Melo & Néstor Espinosa, 2005. "Ineficiencia en la distribución de energía eléctrica: una aplicación de las funciones de distancia estocástica," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE, vol. 23(49), pages 88-132, December.
  13. Pombo, Carlos & Taborda, Rodrigo, 2006. "Performance and efficiency in Colombia's power distribution system: Effects of the 1994 reform," Energy Economics, Elsevier, vol. 28(3), pages 339-369, May.
  14. Jim Griffin & Mark Steel, 2007. "Bayesian stochastic frontier analysis using WinBUGS," Journal of Productivity Analysis, Springer, vol. 27(3), pages 163-176, June.
  15. Rahmatallah Poudineh & Grigorios Emvalomatis & Tooraj Jamasb, 2014. "Dynamic Efficiency and Incentive Regulation: An Application to Electricity Distribution Networks," Cambridge Working Papers in Economics 1422, Faculty of Economics, University of Cambridge.
  16. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
  17. Kopsakangas-Savolainen, Maria & Svento, Rauli, 2011. "Observed and unobserved heterogeneity in stochastic frontier models: An application to the electricity distribution industry," Energy Economics, Elsevier, vol. 33(2), pages 304-310, March.
  18. Mota, R.L., 2003. "The Restructuring and Privatisation of Electricity Distribution and Supply Business in Brazil: A Social Cost-Benefit Analysis," Cambridge Working Papers in Economics 0309, Faculty of Economics, University of Cambridge.
  19. 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.
  20. Seung Ahn & Robin Sickles, 2000. "Estimation of long-run inefficiency levels: a dynamic frontier approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 461-492.
  21. Grigorios Emvalomatis & Spiro E. Stefanou & Alfons Oude Lansink, 2010. "A Reduced-Form Model for Dynamic Efficiency Measurement: Application to Dairy Farms in Germany and The Netherlands," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 161-174.
  22. Anna Ter-Martirosyan & John Kwoka, 2010. "Incentive regulation, service quality, and standards in U.S. electricity distribution," Journal of Regulatory Economics, Springer, vol. 38(3), pages 258-273, December.
  23. Growitsch, Christian & Jamasb, Tooraj & Wetzel, Heike, 2012. "Efficiency effects of observed and unobserved heterogeneity: Evidence from Norwegian electricity distribution networks," Energy Economics, Elsevier, vol. 34(2), pages 542-548.
  24. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
  25. Toru Hattori, 2002. "Relative Performance of U.S. and Japanese Electricity Distribution: An Application of Stochastic Frontier Analysis," Journal of Productivity Analysis, Springer, vol. 18(3), pages 269-284, November.
  26. Goto, Mika & Tsutsui, Miki, 2008. "Technical efficiency and impacts of deregulation: An analysis of three functions in U.S. electric power utilities during the period from 1992 through 2000," Energy Economics, Elsevier, vol. 30(1), pages 15-38, January.
  27. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  28. Pérez-Reyes, Raúl & Tovar, Beatriz, 2009. "Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms," Energy Policy, Elsevier, vol. 37(6), pages 2249-2261, June.
  29. William Yu & Tooraj Jamasb & Michael Pollitt, 2009. "Willingness-to-Pay for Quality of Service: An Application to Efficiency Analysis of the UK Electricity Distribution Utilities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-48.
  30. 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.
  31. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
  32. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
  33. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  34. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
  35. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
  36. 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.
  37. Wiper, Michael Peter & Lopes Moreira Da Veiga, María Helena & Galán Camacho, Jorge Eduardo, 2013. "Bayesian analysis of dynamic effects in inefficiency : evidence from the Colombian banking sector," DES - Working Papers. Statistics and Econometrics. WS ws131918, Universidad Carlos III de Madrid. Departamento de Estadística.
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