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Modelling and Forecasting Residential Electricity Consumption in the U.S. Mountain Region

Author

Listed:
  • Jason B. Jorgensen

    (George Washington University)

  • Fred Joutz

    (George Washington University)

Abstract

In this paper we present an analysis of the demand for residential electricity of the U.S. mountain region. The objective is to develop two simulations analyzing how changes in electricity prices and warmer weather affect electricity consumption and greenhouse gas emissions. Electricity demand is modeled as a function of the price of electricity, real personal income, number of households, weather as a function of heating and cooling days, and the price of natural gas. A general-to-specific approach is used to develop congruent models. We are able to estimate an equilibrium correction model capturing long run electricity demand and short run or seasonal responses. We find that in the long-run, income elasticity is positive and inelastic, own-price elasticity is negative and inelastic, and cross-price elasticity is positive and inelastic. In the short-run, all price and income elasticities are perfectly inelastic and the only effects on demand for electricity are weather variables.

Suggested Citation

  • Jason B. Jorgensen & Fred Joutz, 2012. "Modelling and Forecasting Residential Electricity Consumption in the U.S. Mountain Region," Working Papers 2012-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2012-003
    as

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    File URL: https://www2.gwu.edu/~forcpgm/2012-003.pdf
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    References listed on IDEAS

    as
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    2. Rolando Gonzales Martinez, 2012. "Baysian seasonal analysis with robust priors," Investigación & Desarrollo 0312, Universidad Privada Boliviana, revised Jan 2012.

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    More about this item

    Keywords

    Time series; Econometric models; Residential electricity demand; Error correction Models; Autometrics;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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