Forecast of China’s natural gas demand based on the double-logarithmic model with stepwise regression method

ABSTRACT

In the current world’s energy system, natural gas, as a clean energy source, is gradually becoming the main energy source. However, the volume of natural gas demand could be able to be influenced by numerous factors, in order to forecast the future trend of the requirement more precisely, it is necessary to further explore effective driving factors influencing the volume of demand and construct a brand new function model of forecasting natural gas demand. In this study, the relative gray relational degree is used to quantitatively describe the correlation among variables, diagnosing whether there are serious multicollinearity problems among these factors. According to the principle of correlation degree: first and then small, a stepwise regression analysis is adopted to refine the analysis of factors influencing natural gas demand. On the basis of statistical significance testing, in-depth studying is conducted on the effective influencing factors of natural gas demand. This helps to develop a more accurate prediction model. In this study, we find that: (1) China’s energy consumption structure and economic development influence its natural gas demand. (2) The stepwise regression double logarithmic demand function model based on the effective drivers has good forecasting performance. Researchers can use it to forecast the natural gas demand for medium- and long-term in different regions, and the forecasting results can be considered an important reference basis for scientific natural gas policy formulation. (3) Over the coming 15 years, Natural gas demand in China will continue to grow. It will reach about $6910\times {10}^8{m}^3$ by 2035. It is concluded that the development of China’s natural gas demand would be promoted in an increasing scale trend by striving to promote China’s high-quality economic development, carefully building a new pattern of high-quality energy development, and increasing the proportion of natural gas consumption.

KEYWORDS:

• Demand forecasting
• influencing factors
• double logarithmic demand function
• grey correlation analysis
• stepwise regression analysis

Acknowledgements

It is the authors’ sincere gratitude to anonymous for their helpful and constructive comments on this paper. The relevant works were supported by the Sichuan Science and Technology Program (No. 2023NSFSC1038) in China.

Disclosure statement

It is declared by the authors that the work reported in this paper is not influenced by any known competing financial interests or personal relationships.

CRediT authorship contribution statement

The original draft of the study was completed by Hongbing Li, while data collection and compilation were performed by Mi Han.

Additional information

Notes on contributors

Hongbing Li

Hongbing Li, lecturer, master's supervisor, has been teaching in Sichuan Normal University since June 2022. His main research interests are oil and gas safety and risk management.

Mi Han

Mi Han, PhD candidate of Southwest Petroleum University.