April 29, 2024
Ebrahim Heidari

Ebrahim Heidari

Academic Rank: Associate professor
Address:
Degree: Ph.D in Economics
Phone: 09173712463
Faculty: School of Business and Economics

Research

Title
Estimation and Forecast of Demand for Natural Gas in Bushehr Province Using Dynamic Partial Adjustment and ARIMA Models
Type Thesis
Keywords
تخمين و پيش بيني، تقاضاي گاز طبيعي، مدل ARIMA، مدل تعديل جزئي ، استان بوشهر
Researchers mahbobeh rezaei (Student) , Ebrahim Heidari (Primary advisor) , Hadi Keshavarz (Primary advisor)

Abstract

Background: Considering the importance of the role of energy resources, especially natural gas, in economic development and social welfare, in order to reduce possible shocks and crises in the future, as well as to improve and optimize the consumption pattern in the present and future, the need for proper management of energy supply and demand is very important. It is essential. Aim: The main purpose of the research is to investigate and understand the behavior of natural gas consumers in the three residential, commercial and industrial sectors of Bushehr province in order to properly manage and plan the natural gas demand. Therefore, the present study intends to estimate and forecast the demand of all three sectors for natural gas using partial adjustment dynamic models and ARIMA. Also, price and income elasticity of natural gas demand will be examined. Methodology: In order to estimate the demand using the ARIMA model in all three sectors, the monthly time series data of natural gas consumption in all three residential, commercial and industrial sectors have been used in the period of 2012-2020. Demand estimation using partial adjustment model in all three sectors, from seasonal time series data (each sector) of natural gas consumption, number of subscribers, income index, natural gas price, electricity price as substitute energy for residential and commercial sector, oil price Crude has been used as a substitute energy for the industrial sector and the average temperature in the time range of 2012-2020 Conclusions: The estimated ARIMA model for residential, commercial and industrial sectors are respectively: ARIMA(4,1,6), ARIMA(0,0,3) and ARIMA(3,1,2). The estimated price elasticity of the mentioned sectors is -0.57, -0.57 and -0.02 respectively. Estimated income elasticity of the mentioned sectors: -0.68, -0.84 and 0.47 respectively. The estimated dynamic adjustment rate is 0.17% in the residential sector, 0.30% in the commercial sector, and 0.34% in the industr