1- Tarbiat Modares University 2- Tarbiat Modares University , samortazavi@modares.ac.ir
Abstract: (22 Views)
Environmental protection is one of the key pillars of sustainable development. The agricultural sector, on the one hand, plays a vital role due to its responsibility in meeting the basic needs of society; on the other hand, it significantly contributes to pollutant emissions because it relies on energy as a production input. Accordingly, in order to reduce the negative externalities of agricultural development, the present study investigates the factors affecting carbon dioxide emissions in the agricultural sector using statistical evidence from Iranian provinces over the period 2007–2021 and applying a spatial econometric approach. The data reveal that Yazd Province has the highest energy intensity in agriculture, equivalent to 190 barrels of crude oil per thousand billion rials of output, and the highest per capita carbon dioxide emissions, amounting to 565 tons per thousand people. Estimation results indicate that agricultural output does not have a statistically significant effect on CO₂ emissions; however, energy intensity has a positive and significant impact, reflecting a high degree of inefficiency in energy consumption. Additionally, the effects of population and urbanization on per capita CO₂ emissions are found to be negative and statistically significant. Therefore, improving production technologies in the agricultural sector to reduce energy intensity and increase crop productivity, along with developing other economic sectors to phase out highly polluting machinery particularly considering the roles of population and urbanization are among the most important policy recommendations for enhancing environmental quality associated with agricultural activities. JEL Classification: O13، C21، P28. Keywords: CO2 emission, Energy intensity, Spatial Econometric.
Jahed T, Mortazavi S A, Vakilpoor M H. Examining the effect of energy intensity and value added on CO2 Emission in the Agricultural Sector (A Spatial Econometric Approach). QEER 2026; 23 (89) :73-97 URL: http://iiesj.ir/article-1-1713-en.html