Modeling Environmental Kuznets Curve in the transport sector in Iran, Using Structural Time Series

In recent years¡ carbon dioxide emissions have been a significant increase in the transport sector. Therefore¡ accurate modeling of carbon dioxide emissions is important to adopt a policy by managers and policy makers in the transport sector. This study using underlying trend concept and create a state- space model¡ Kalman filter algorithms which were estimated structural model of Environmental Kuznets Curve in the transport sector. The data used in this study is the annual time series over the period 1346-1392. The nature of the underlying trend is smooth¡ rising and non-linear. According to likelihood ratio statistic¡ most appropriate structure for hyper parameters¡ were local level model with drift model. The results indicate that the structural time series models¡ according to the implicit import (technology) inverted U relationship is confirmed for the transport sector. Also¡ The transport sector is on the descending curve. Variable coefficient of energy consumption in the transport sector is based on the theory and it is positive. According to the results of the assessment¡ to reduce carbon dioxide emissions¡ policy-makers and managers can plan to increase value added in transport and investing in new technologies.