A novel benchmark methodology for estimating industrial electricity demand considering unsteady socio-economic conditions

Ali Azadeh, Ruholla Jafari-Marandi, Mohammad Abdollahi and Elahe Roudi

International Journal of Business Performance Management, 2017, vol. 18, issue 2, 196-215

Abstract: The aim of this paper is to propose a benchmark methodology for forecasting industrial electricity demand in unsteady socio-economic environments such as developing countries using various aspects of socio-economic parameters. Iran's industrial electricity demand after cutting off subsidies is analysed as our case study. The study uses data of 19 countries for the years 1993-2008 for benchmarking due to their similarities to Iran. Moreover, nine indexes of life expectancy rate, human population density, literacy rate, human development index, total healthcare expenditure, gender equality index, R%D spending rate, motor vehicle rate, and CO₂ emission rate are considered in our study as benchmarking indicators. The essence of the benchmark methodology is based on log-log equilibrium of industrial electricity consumption versus price of electricity, population of users and value added. Regression is applied to all the data and proper coefficients are calculated for each of the selected countries to be used in the benchmark model. Subsequently, price elasticity and other coefficients to be used in electricity demand prediction of Iran is estimated from the viewpoint of each benchmarking index using the results obtained for the 19 countries. Lastly, an equation is presented for forecasting future electricity demand.

Keywords: industrial energy demand; benchmarking; regression; equilibrium; time series; demand estimation; socio-economic parameters; forecasting; developing countries; Iran; case study; energy consumption; electricity prices; value added; life expectancy; human population density; literacy rate; human development index; healthcare expenditure; gender equality; R%D expenditure; research and development; motor vehicles; CO2; carbon dioxide; carbon emissions; price elasticity. (search for similar items in EconPapers)
Date: 2017
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