Modeling and Analysis of Natural Gas Demand in Different Economic Sectors (An Autoregressive Distributed Lag Approach)
This study employs the Autoregressive Distributed Lag (ARDL) model to estimate the natural gas demand in six economic sectors, including household, agriculture, transportation, commercial, industrial, and power plants. The data used for this analysis spans during thr period of 2011 - 2022 and is derived from the national energy balance sheets.The modeling results indicate that the price elasticity of demand in the estimated functions is very low, meaning that the gas demand in these sectors is not highly responsive or sensitive to price changes. One reason for the low price elasticity is the regulated pricing of natural gas in these sectors. Additionally, the low price, assuming other conditions remain constant, reduces the sensitivity of consumers to price fluctuations.In most sectors, the elasticity of value-added and GDP surpasses other elasticities, highlighting that income has a more significant impact on natural gas demand. This effect is particularly pronounced in the industrial and power plant sectors. Therefore, the gas demand in these sectors is closely tied to the level of economic activity.
-
Evaluation and Ranking of Iran’s Railway Regions Using Window Data Envelopment Analysis Approach Model
Naser Zourmand Baghdar, *, Morteza Pakdaman, Amir Hajimirzajan
Journal of Transportation Research, Summer 2025 -
Providing an Integrated Model for the Sustainable Development of "Water, Energy and Food" in Iran Using a Grounded Theory Approach
Fatemeh Momeni Mahmouei, *, Narges Salehnia, Ghasem Eslami
Journal of Water and Sustainable Development, -
Designing a dynamic model of brand equity with a focus on fake news and customer knowledge at Coca-Cola
Davood Arian Nezhad, *, Hadi Bastam, Ali Hosseinzadeh
Management tomorrow, -
Financial development and environment: Evidence of consumption-based CO₂ emissions
Fariba Osmani, Aliakbar Naji*, Mahdi Cheshomi
Journal of Advanced Environmental Research and Technology, Fall 2023