Modeling Determinants of Renewable Electricity Consumption in Iran

Document Type : Research Paper


1 Department of Health and Environmental Eonomics, University of Mohaghegh Ardabili, Ardabil, Iran

2 Department of Economics and Management, Baskent University, Ankara, Turkey



Rising concerns about global warming and energy security signal an increasing reliance on renewable energy sources in the future. Recently, renewable energy sources have emerged as a significant component of global energy consumption. However, less information is available addressing the renewable energy consumption’s determinants. Considering the contribution of renewable energy to future sustainable and reliable energy, its primary factors must be comprehended in order to derive energy policy consequences. Using Auto Regressive Distributed Lag (ARDL) bounds testing cointegration strategy and the Vector Error Correction Model (VECM) Granger causality test method over the period 2011-2019, the objective of this study is to empirically model the determinants of renewable electricity consumption in Iran. The primary predictors of renewable electricity consumption are combined pollution, per capita Gross Domestic Product (GDP), oil price, and urbanization, according to the results of the investigation. Long-term and short-term consumption of renewable electricity is positively and negatively affected by combined pollution, oil price, and urbanization, respectively, according to the empirical findings. In the short-term, the per capita GDP has a negative and significant effect on renewable electricity consumption, while in the long-term, the opposite is true. Finally, the results of Granger causality analysis utilizing the vector error correction model reveal a bidirectional short-term and long-term Granger causality flowing in a positive direction from combined pollution, per capita GDP, and oil price to renewable power usage. Moreover, the positive bilateral short-term Granger causation between the oil price and per capita GDP is verified.