Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an emerging economy

Rabia Akram, Qiyuan Li, Mohit Srivastava, Yulu Zheng and Muhammad Irfan

Technological Forecasting and Social Change, 2024, vol. 209, issue C

Abstract: With the continuous evolution of the new technological revolution and industrial transformation, industrial robots' widespread application of artificial intelligence has profoundly influenced the economic growth model. The improvement of natural resource utilization efficiency is an essential indicator for measuring the high-quality development of the economy (HQED). This paper empirically analyzes the impact of artificial intelligence on the HQED using data from 275 cities in China from 2011 to 2020. The research results of this paper show that artificial intelligence significantly promotes the HQED, which is still maintained after a series of robustness tests. The mechanism analysis of this paper indicates that artificial intelligence promotes the HQED by enhancing energy transition, fostering green technology innovation, and mitigating climate policy uncertainty. Heterogeneity analysis shows that in non-old industrial base cities, non-resource-based cities, cities with more robust intellectual property protection, and cities with abundant human capital, the promoting effect of artificial intelligence on high-quality economic development is more substantial.

Keywords: Artificial intelligence; Industrial robots; High-quality economic development; Climate change; Technological innovation; Natural resource efficiency (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524006188
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:tefoso:v:209:y:2024:i:c:s0040162524006188

DOI: 10.1016/j.techfore.2024.123820

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().