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Sobre Los Fundamentales Del Precio De La Energía Eléctrica: Evidencia Empírica Para Colombia

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Listed:
  • Jorge Barrientos Marín

    (Universidad de Antioquia)

  • Mónica Toro Martínez

    (Universidad de Antioquia)

Abstract

in this paper we are interested in investigating the market fundamentals that influences energy prices formation in Colombia and evaluating the impact of the some market variables on the behavior of energy price by estimating the impulse-response function. To this end we estimate VAR specification. In addition, we carried out an exploratory analysis for forecasting the future energy prices in the next 10 years. Our main conclusion is that the set of variables which most affects the evolution of the energy prices is the hydrology and the declared availability. About the forecasting, we found that the energy prices going to increase for the next years with a kind of fall around 2018 just for recovery ahead.

Suggested Citation

  • Jorge Barrientos Marín & Mónica Toro Martínez, 2016. "Sobre Los Fundamentales Del Precio De La Energía Eléctrica: Evidencia Empírica Para Colombia," Grupo Microeconomía Aplicada 74, Universidad de Antioquia, Departamento de Economía.
    • Handle: RePEc:lde:grupom:074
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    References listed on IDEAS

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    1. Haldrup, Niels & Nielsen, Frank S. & Orregaard Nielsen, Morten, 2009. "A vector autoregressive model for electricity prices subject to long memory and regime switching," Queen's Economics Department Working Papers 273697, Queen's University - Department of Economics.
    2. Haldrup, Niels & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2010. "A vector autoregressive model for electricity prices subject to long memory and regime switching," Energy Economics, Elsevier, vol. 32(5), pages 1044-1058, September.
    3. Sergio Botero Botero & Jovan Alfonso Cano Cano, 2008. "Análisis de series de tiempo para la predicción de los precios de la energía en la bolsa de Colombia," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID.
    4. Hickey, Emily & Loomis, David G. & Mohammadi, Hassan, 2012. "Forecasting hourly electricity prices using ARMAX–GARCH models: An application to MISO hubs," Energy Economics, Elsevier, vol. 34(1), pages 307-315.
    5. Jorge Barrientos Marín & Edwin Rodas & Esteban Velilla & Mauricio Lopera, 2012. "Modelo para el pronóstico del precio de la energía eléctrica en Colombia," Revista Lecturas de Economía, Universidad de Antioquia, CIE.
    6. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    7. 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.
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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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