Total Electricity Demand Modeling: An Application of Spatial Panel Econometric Method

This paper aims to model total electricity demand (incremental) in order to estimate price and income elasticities using provincial data and the spatial panel data method. Electricity demand at the province level is influenced by climatic zones, which can be divided into temperate, cold and sub-tropical. This paper uses time series data for electricity demand in Iran’s 28 provinces, taking into account climatic factors as well as income and price elasticities.  We use Elhorst methodology and likelihood-ratio test to compare spatial patterns in order to select the best method compatible with the theoretical model. The results indicate a  price elasticity of electricity demand (-0.08), cross elasticity of electricity demand (-0.6565), income elasticity (0.11) and elasticity of demand to temperature changes (1.9). In other words, electricity demand is minimally sensitive to changes in electricity prices and natural gas prices and income, but sensitive to changes in temperature (elastic). Our cross elasticities and income elasticity indicate that electricity and natural gas are substitutes for each other and can be considered essential goods based on their income elasticity.