The nexus of renewable energy - sustainable development - environmental quality in Iran: Bayesian VAR approach

Abstract

The use of renewable energy reduces environmental pollution and leads to achievement of sustainable development. The current study investigates the dynamic interrelationship between sustainable development, renewable and non-renewable energies and environment nexus by applying Bayesian vector autoregression (BVAR) and impulse response functions in Iran with an annual data frequency for the time span of 1980-2013. In this study, genuine savings (GS) were particularly examined to indicate sustainable development. The empirical results confirm the existence of cointegration long-run relationship among the variables. Based on BVAR analysis, SSVS-full and normal-Wishart functions were used as optimal prior functions to estimate renewable and non-renewable energies models, respectively. Results of impulse response functions indicate a positive impact of renewable and non-renewable energies consumption on sustainable development. Also, renewable and non-renewable energies consumption shocks positively affect CO2 emissions, but the effect of non-renewable energy consumption on air pollution is more than that of renewable energy consumption. Moreover, the results reveal positive impact of sustainable development shock on renewable energy consumption and negative impact on non-renewable energy consumption.

Keywords

• Renewable Energy
• Environmental Quality
• sustainable development
• Bayesian Vector Auto Regression (BVAR)