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Analyzing Electricity Demand in Colombia: A Functional Time Series Approach

Author

Listed:
  • Jorge Barrientos Marin

    (Departamento de Econom a, Universidad de Antioquia, Colombia; & Facultad de Econom a, Universidad Aut noma Latino Americana - UNAULA, Colombia,)

  • Laura Marquez Marulanda

    (Escuela de Ciencias Econ micas y Administrativas, Universidad EIA, Colombia,)

  • Fernando Villada Duque

    (Departamento de Ingenier a El ctrica, Universidad de Antioquia, Colombia.)

Abstract

In this work we are interested in analyzing the energy demand in Colombia for a short-term horizon, from a functional data approach. First, we make an exhaustive review of the literature on functional spaces as a potential source of statistical information. It is, of course, a theoretical reinterpretation since in practice the data are elements of a finite-dimensional space; however, very high-frequency data, properly treated, can be viewed as elements of a space of continuous functions. Second, we put such a reinterpretation into practice, by performing a spline-type smoothing of commercial energy demand, based on hourly-daily data. As a result, a function or smooth curve is obtained for each day. Finally, we expose the usefulness of this new approach for statistical analysis, modeling, and projection (or forecasting) of stochastic processes that generate high-frequency random variables.

Suggested Citation

  • Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.
    • Handle: RePEc:eco:journ2:2023-01-11
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    functional data; functional time series; data smoothing; energy demand;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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