Analyzing Electricity Demand in Colombia: A Functional Time Series Approach

Jorge Barrientos Marin, Laura Marquez Marulanda and Fernando Villada Duque
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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.

International Journal of Energy Economics and Policy, 2023, vol. 13, issue 1, 75-84

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.

Keywords: functional data; functional time series; data smoothing; energy demand (search for similar items in EconPapers)
JEL-codes: C32 C50 C55 L94 Q41 Q47 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2023-01-11

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