IDEAS home Printed from https://ideas.repec.org/a/ief/reveye/v51y2013i1p85-118.html
   My bibliography  Save this article

La Distribución Eléctrica en Argentina y su Eficiencia Técnica:Una Aplicación del Análisis de Fronteras Estocásticas (SFA) Utilizando Funciones Distancia

Author

Listed:
  • Darío Ezequiel Díaz

    (Universidad Autónoma de Encarnación, Facultad de Ciencias Empresariales (Encarnación, Paraguay))

Abstract

La tarifa es la variable más relevante en la compleja organización de la regulación del sistema eléctrico, y particularmente, de la actividad de distribución. La crisis financiera del año 2009 y la experiencia negativa de algunas privatizaciones a nivel internacional, conjuntamente con una literatura económica endeble respecto a la relación titularidad/eficiencia, revitalizaron el debate en analizar la relación entre la propiedad pública/privada de la empresa y su eficiencia técnica; la medición de esta última y el esquema de regulación adecuado para la distribución eléctrica. El objetivo del presente paper es medir la eficiencia técnica de las empresas distribuidoras eléctricas de la República Argentina utilizando la técnica de funciones distancia bajo el marco del análisis de fronteras estocásticas, con el objeto de construir un ranking de eficiencia entre las empresas privadas y públicas. / The rate is the most important variable in the complex organization of the regulation of the electricity system, and particularly of the distribution activity. The financial crisis of 2009 and the negative experience of some privatizations internationally together with weak economic literature regarding the ownership / efficiency ratio, revived the debate on analyzing the relationship between public / private ownership of the company and its efficiency technique; measurement of the latter and appropriate regulatory scheme for power distribution. The aim of this paper is to measure the technical efficiency of power distribution companies of Argentina using techniques of distance functions under the framework of stochastic frontier analysis, in order to build a ranking of efficiency between private and public companies.

Suggested Citation

  • Darío Ezequiel Díaz, 2013. "La Distribución Eléctrica en Argentina y su Eficiencia Técnica:Una Aplicación del Análisis de Fronteras Estocásticas (SFA) Utilizando Funciones Distancia," Revista de Economía y Estadística, Universidad Nacional de Córdoba, Facultad de Ciencias Económicas, Instituto de Economía y Finanzas, vol. 51(1), pages 85-118, Diciembre.
    • Handle: RePEc:ief:reveye:v:51:y:2013:i:1:p:85-118
    DOI: 10.55444/2451.7321.2013.v51.n1.11877
    as

    Download full text from publisher

    File URL: http://revistas.unc.edu.ar/index.php/REyE/article/download/11877/12229
    Download Restriction: no
    File URL: https://libkey.io/10.55444/2451.7321.2013.v51.n1.11877?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
    ---><---

    References listed on IDEAS

    as
    1. Antonio Estache & MartÌn A. Rossi & Christian A. Ruzzier, 2004. "The Case for International Coordination of Electricity Regulation: Evidence from the Measurement of Efficiency in South America," Journal of Regulatory Economics, Springer, vol. 25(3), pages 271-295, May.
    2. Ligia Melo & Néstor Espinosa, 2005. "Ineficiencia en la distribución de energía eléctrica: una aplicación de las funciones de distancia estocástica," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 23(49), pages 88-132, December.
    3. 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.
    4. Rafael Cuesta, 2000. "A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms," Journal of Productivity Analysis, Springer, vol. 13(2), pages 139-158, March.
    5. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    6. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    7. repec:bdr:ensayo:v::y:2005:i:49:p:88-132 is not listed on IDEAS
    8. K. Kalirajan, 1981. "An Econometric Analysis of Yield Variability in Paddy Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 29(3), pages 283-294, November.
    9. 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.
    10. Battese, George E. & Coelli, Tim J. & Colby, T.C., 1989. "Estimation of Frontier Production Functions and the Efficiencies of Indian Farms Using Panel Data from ICRISAT's Village Level Studies," 1989 Conference (33rd), February 7-9, 1989, Christchurch, New Zealand 144383, Australian Agricultural and Resource Economics Society.
    11. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    12. Hussain, Muhammad Sajid & Coelli, Tim J. & Simmons, Phil, 1999. "An Analysis of the Technical Efficiency of Cotton Farmers in the Punjab province in Pakistan," 1999 Conference (43th), January 20-22, 1999, Christchurch, New Zealand 123815, Australian Agricultural and Resource Economics Society.
    13. Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
    14. 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.
    15. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    16. Loza, Andrés & Margaretic, Paula & Romero, Carlos, 2003. "Consistencia de medidas de eficiencia basadas en funciones de distancia paramétricas y no paramétricas: una aplicación al sector de distribuidoras de electricidad en la Argentina [Consistency of ef," MPRA Paper 15269, University Library of Munich, Germany.
    17. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    18. Leland Gerson Neuberg, 1977. "Two Issues in the Municipal Ownership of Electric Power Distribution," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 303-323, Spring.
    19. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    20. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    21. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    22. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    23. Omar O. Chisari (ed.), 2007. "Regulatory Economics and Quantitative Methods," Books, Edward Elgar Publishing, number 12517.
    24. Burns, Philip & Weyman-Jones, Thomas G, 1996. "Cost Functions and Cost Efficiency in Electricity Distribution: A Stochastic Frontier Approach," Bulletin of Economic Research, Wiley Blackwell, vol. 48(1), pages 41-64, January.
    25. 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.
    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. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    2. Martín Rossi, 2015. "The Econometrics Approach to the Measurement of Efficiency: A Survey," Working Papers 117, Universidad de San Andres, Departamento de Economia, revised Feb 2015.
    3. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    4. Yeinni Andrea Patino Moya & Gustavo Adolfo Gómez Flórez & Emma Osorio Medina, 2010. "Evaluación del desempeno del sector de distribución de electricidad en Colombia: una aplicación del análisis de frontera estocástica," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 28(62), pages 70-123, June.
    5. Reddy, Mahendra, 2002. "Implication of Tenancy Status on Productivity and Efficiency: Evidence from Fiji," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 4, pages 1-20.
    6. Sedik, David & Trueblood, Michael & Arnade, Carlos, 1999. "Corporate Farm Performance in Russia, 1991-1995: An Efficiency Analysis," Journal of Comparative Economics, Elsevier, vol. 27(3), pages 514-533, September.
    7. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    8. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    9. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    10. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    11. Belloumi, Mounir & Matoussi, Mohamed Salah, 2006. "A Stochastic Frontier Approach for Measuring Technical Efficiencies of Date Farms in Southern Tunisia," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 35(2), pages 1-14, October.
    12. Blazek, David & Sickles, Robin C., 2010. "The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: The case of U. S. shipbuilding during WWII," Economic Modelling, Elsevier, vol. 27(6), pages 1484-1497, November.
    13. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    14. Raghbendra Jha & Hari K. Nagarajan & Subbarayan Prasanna, 2005. "Land Fragmentation and its Implications for Productivity: Evidence from Southern India," ASARC Working Papers 2005-01, The Australian National University, Australia South Asia Research Centre.
    15. Massimiliano Piacenza, 2002. "Regulatory Constraints and Cost Efficiency of the Italian Public Transit Systems: An Exploratory Stochastic Frontier Model," CERIS Working Paper 200202, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    16. Hasan Dudu & Erol H. Cakmak & Nadir Ocal, 2015. "Drivers of Farm Efficiency in Turkey: A Stochastic Frontier Analysis," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 1(1), pages 45-63, June.
    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. 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.
    19. Gian Carlo Scarsi, 1999. "Local Electricity Distribution in Italy: Comparative Efficiency Analysis and Methodological Cross-Checking," Working Papers 1999.16, Fondazione Eni Enrico Mattei.
    20. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.

    More about this item

    Keywords

    Distribución eléctrica; eficiencia técnica; función distancia; frontera estocástica;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - 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:ief:reveye:v:51:y:2013:i:1:p:85-118. 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: Ivan Iturralde (email available below). General contact details of provider: https://edirc.repec.org/data/ieuncar.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.