Estimating of Electricity Demand of Agricultural Sector in Iran by Cointegration Method

Abstract

Using time-series data and cointegration techniques in econometrics, particularly Autoregressive Distributed Lag (ARDL) and error correction mechanism (ECM), the study estimated the long-term and short-term relationships of the electricity demand model in Iran's agricultural sector. According to the results obtained, the inelasticity of electricity demand relative to price, obtained in other studies in Iran and other countries, was confirmed in this study too. The absolute value of price elasticity of agricultural demand was 0.521 stating that one percent increase in the price of electricity, its demand decreases by 0.521%. Thus, electricity in the agricultural sector in Iran is a less elastic commodity, as electricity is cheaper than other petroleum products with high economic efficiency and it is less possible to replace it with other products. With the increase in the price of this carrier, the demand for it does not decrease significantly, which shows that the agricultural sector depends on electricity. Moreover, other energy sources cannot be a suitable alternative to it. The findings indicate that all coefficients are significant at the level of five and ten percent. Using time-series data and electricity consumption statistics from 1976 to 2016 and cointegration techniques in econometrics, especially ARDL and ECM, the study estimated the long-term and short-term relationships model of electricity demand in the agricultural sector until 2025.