Degree Name

Doctor of Philosophy


School of Economics


The objective of this thesis is to estimate the main determinants of electricity demand in Iran for various subsectors (residential, industrial, agricultural and public) using appropriate econometric models. The thesis also aims to study the influence of new electricity pricing in Iran and forecast electricity demand up to 2020.

One of the main concerns pertaining to the Iranian power industry is the high growth rate of domestic demand, coupled with the inefficient use of electricity in different sectors. A limited number of studies have focused on disaggregated electricity demand in Iran, but suffer from disregarding some important influencing factors and from some methodological drawbacks. The methodology adopted in the current study is based on unit root tests with multiple structural breaks and application of the cointegration technique. A simulation approach is applied to forecast electricity demand for the future. The employed data are annual time series from 1967 to 2009 (43 years).

The results show that the agricultural sector is the only sector that has an income and price elasticity greater than unity in the long run. Weather conditions play an important role in all sectors. Technology changes or economic progress influence electricity demand in all sectors except the agricultural sector. In the short run, weather conditions are one of the main factors affecting the industrial, residential and agricultural sectors, while in the public sector electricity price has the highest elasticity. Weather conditions are the main factor contributing to changes in aggregate electricity demand, while change in GDP is the second most influential factor. The speed of correction of deviations from long-run electricity consumption is low in all Iranian electricity subsectors and at the aggregate level.

Based on the influential factors affecting electricity demand in each sector, it can be concluded that electricity pricing needs to be restructured in Iran. Moreover, electricity consumption could feasibly be reduced by weatherproofing buildings and replacing old air conditioners and industrial ventilating systems and chillers. In addition, it is necessary to plan for long-run electricity supply and expansion of current capacity in conjunction with the country’s economic progress.

The forecast results show that the impact of government electricity pricing on electricity demand will be significant. Nine scenarios have been defined for each sector. The forecasts reveal that by 2014, under the most feasible scenarios, electricity demand in the industrial, public and residential sectors will increase; therefore, despite a forecast decrease in the agricultural sector, aggregate electricity demand in 2014 will increase compared with 2009. Considering the improvement of power-plant efficiency and the reduction of transmission and distribution network loss, under the most probable scenarios, the current supply would be sufficient to cover future demand for electricity in the Iranian economy. However, by 2020 the Iranian economy will need over 225 TWh, which is 28.1% greater than total electricity demand in 2009. That is, new capacities need to be installed by 2020 to meet anticipated electricity demand.

FoR codes (2008)

140302 Econometric and Statistical Methods, 140303 Economic Models and Forecasting, 140305 Time-Series Analysis



Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.