Long Term Energy Forecasting with Econometrics in MATLAB

Dynamic energy demand forecasting using Econometrics (ARIMA/VAR/GARCH)
Updated 1 Sep 2016

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Since 2008 energy demand in Australia has started to decline. The result, traditional regression based models that were being used to forecast long term energy load were now highly inaccurate in their predictions. Energy demand has since continued to fall, however will it increase again? If so, how can this be predicted? A dynamic model to forecast long term energy demand is needed.
In this example, we’ll demonstrate how using econometrics techniques, you can create a dynamic, self-tuning model for predicting long term energy load. We will look at building ARIMA/GARCH and Vector Autoregressive (VARX) forecasting models based of historical energy and economic data sets.

Cite As

David Willingham (2024). Long Term Energy Forecasting with Econometrics in MATLAB (https://www.mathworks.com/matlabcentral/fileexchange/49279-long-term-energy-forecasting-with-econometrics-in-matlab), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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