Ebrahim Heidari

The purpose of this study is to investigate and analyze factors affecting the energy intensity in provinces of Iran with emphasis on information and communications technology (ICT) index, during the period from 2010-2015. Weighted Average Least Square (WALS) method and information criteria have been applied to select the model; so that, based on WALS method, six variables among various affective factors on energy intensity according to theoretical background and empirical studies have been chosen, and then based on information criteria, a Bayesian panel model was determined in order to evaluate the effect of each factor on energy intensity. Results from Monte Carlo simulation with Markov chains have indicated that among information and communications technology sub-indices, access to ICT equipment sub-index, reduces energy intensity, but, skill sub-index (the average years of schooling and enrollment rate in and university) has a positive effect on energy intensity. Per capita income and energy price have negative effects on energy intensity, and the share of industry sector in production and inventory of vehicles leads to an increase in energy intensity.