Forecasting Residential electricity demand in the Philippines using an Error Correction Model

Angelo Gabrielle Santos



 This study uses an Error Correction Model (ECM) to forecast residential electricity demand in the Philippines using household final consumption expenditure, residential electricity price, and temperature as explanatory variables. Results show that there is a long-run relationship between household final consumption expenditure and residential electricity demand. Estimates from the ECM are consistent with economic theory, and the model passed standard diagnostic and parameter stability tests. Forecast performance based on within-sample and out-of-sample forecasts of the ECM is also shown to be superior, relative to a benchmark Autoregressive Distributed Lag (ARDL) model. Simulations show that by 2040, residential electricity consumption will range from 42,500 gigawatthours (GWh) based on a weak income growth scenario and 62,000 GWh based on a combined changes scenario. 

JEL classification: C22, C53, Q47


electricity consumption, forecasting, error correction model

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