Assessment of the causal links between energy, technologies, and economic growth in China: An application of wavelet coherence and hybrid quantile causality approaches

Zia Ur Rahman, Yufeng Chen and Assad Ullah

Applied Energy, 2025, vol. 377, issue PA, No S030626192401852X

Abstract: It is undeniable that energy and technology play a vital role in driving the economic growth of a country. This paper's objective is to check the unexplored causal links between electricity generation and GDP growth in China by using a multivariate framework that contains technologies in the production or processing of goods, gross capital formation, labour force, financial sector development, and primary energy consumption as supplementary factors in growth model using the updated data. Applying new advances in time series data analysis, the study used wavelet coherence and hybrid non-parametric quantile causality approaches to analyze whether these factors predict GDP growth. We observed that technologies, capital formation, labor force, energy consumption, financial sector development, and electricity generation propel GDP growth in China. The quantile causality in mean and variance also corroborates that all these factors are causatives of GDP growth across their entire distribution. The Breitung-Candelon Spectral Granger-causality method further sustains the robustness of these results. Our findings provide valuable insight to policymakers to pave the way for these causative factors, mainly promoting electricity projects and adapting new technologies to propel economic growth in China.

Keywords: Energy; Economic growth; Technologies; Wavelet coherence; Hybrid quantile causality; China (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626192401852X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:377:y:2025:i:pa:s030626192401852x

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2024.124469

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().