TY - JOUR
T1 - Determination of models of simple regression and multivariate analysis for the forecast of the electricity price in Colombia at 2030
AU - Hernández Bueno, Nelson Javier
AU - Calderón, María de los Ángeles Pinto
AU - Muñoz Maldonado, Yecid Alfonso
AU - Ospino Castro, Adalberto
N1 - Publisher Copyright:
© 2018, Econjournals. All rights reserved.
PY - 2018
Y1 - 2018
N2 - The electricity price in Colombia responds to demographic, economic, climatic changes, among others, that generate uncertainty and therefore risks in the electric production. Considering that the decision-making process has a great importance in the electricity market and that the participation of generators in energy auctions is usually based on intuition and previous experience, the need to study the possible alternatives and methods that minimize the risks before deciding some important matter can be appreciate. In this article, the estimation of the behavior of electrical energy prices in Colombia at the year 2030 for different scenarios and there are propose the following scientific models: (1) Simple regression; (2) econometric model. As result are obtained forecasts for each model, identifying that the econometric model has the lowest margin of error compared to the historical data that considers the behavior of different variables for the forecast.
AB - The electricity price in Colombia responds to demographic, economic, climatic changes, among others, that generate uncertainty and therefore risks in the electric production. Considering that the decision-making process has a great importance in the electricity market and that the participation of generators in energy auctions is usually based on intuition and previous experience, the need to study the possible alternatives and methods that minimize the risks before deciding some important matter can be appreciate. In this article, the estimation of the behavior of electrical energy prices in Colombia at the year 2030 for different scenarios and there are propose the following scientific models: (1) Simple regression; (2) econometric model. As result are obtained forecasts for each model, identifying that the econometric model has the lowest margin of error compared to the historical data that considers the behavior of different variables for the forecast.
KW - Econometric modeling
KW - Electricity price
KW - Forecasting
KW - Methods of statistical simulation
UR - http://www.scopus.com/inward/record.url?scp=85053018888&partnerID=8YFLogxK
M3 - Artículo Científico
AN - SCOPUS:85053018888
SN - 2146-4553
VL - 8
SP - 202
EP - 211
JO - International Journal of Energy Economics and Policy
JF - International Journal of Energy Economics and Policy
IS - 5
ER -