Investigating the Differences in CO2 Emission in the Transport Sector Across Iranian Provinces: Evidence from a Quantile Regression Model

Improving the quality of the environment is a desired goal of any economy. In this regard, given the important role of the transportation sector in the emission of pollutants, policy makers should focus on identifying the factors affecting CO2 emissions in the transport sector. This study examines the factors affecting the differences of CO2 emissions in the transportation sector in Iranian provinces by applying the extended STIRPAT model and quantile regression and using the provincial-level data for the period 2006 to 2015. Evidence shows that the Yazd and Semnan provinces has the highest per capita logarithms of CO2 emissions equal to 0.51 and 0.5 respectively,  and Golestan province has the lowest value equal to 0.3. Evidence of estimation shows that urbanization, energy intensity and production have a positive and significant effect and the effect of population on CO2 emissions is negative and significant. Also, according to quantile regression, as we move toward a high CO2 emission level, the effect of energy intensity increases and the effect of urbanization decreases. Based on this, improving urban infrastructure to maximize the benefits of high intensity of occupancy, improving production technology and improving the quality of the transportation system are effective steps for reducing carbon dioxide emissions in the transport sector.