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Metropolitan Econometric Electric Utility Forecast Accuracy

Author

Listed:
  • Thomas M. Fullerton

    (Department of Economics & Finance, University of Texas at El Paso, El Paso, TX 79968-0543, USA,)

  • George Novela

    (Load Forecast and Planning Unit, El Paso Electric Company, P.O. Box 982, El Paso, TX 79960 USA,)

  • David Torres

    (Department of Research and Planning, El Paso Water Utilities, 1154 Hawkins Boulevard, El Paso, TX 79925, USA,)

  • Adam G. Walke

    (Department of Economics & Finance, University of Texas at El Paso, El Paso, TX 79968-0543, USA.)

Abstract

El Paso Electric Company (EPEC) is the sole commercial electricity provider for two metropolitan economies in the southwestern desert region of the United States: El Paso, Texas and Las Cruces, New Mexico. A publicly traded corporation, EPEC employs a structural econometric system of equations model to forecast energy sales for various customer classes. Although the modeling system has provided reliable inputs to annual corporate planning efforts at EPEC, its historical track record has not previously been formally assessed for forecast accuracy. Both descriptive and inferential statistics are used to evaluate the EPEC model s forecasting performance. Results indicate that accurate prediction of electricity usage in this service area is an elusive target. Those results are similar to what has been documented for other regional economic variables.

Suggested Citation

  • Thomas M. Fullerton & George Novela & David Torres & Adam G. Walke, 2015. "Metropolitan Econometric Electric Utility Forecast Accuracy," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 738-745.
    • Handle: RePEc:eco:journ2:2015-03-13
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    References listed on IDEAS

    as
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    Cited by:

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    More about this item

    Keywords

    Energy Forecasting; Statistical Tests; Forecast Accuracy Evaluation;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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