How Does Critical Peak Pricing Boost Urban Green Total Factor Energy Efficiency? Evidence from a Double Machine Learning Model

Da Gao, Qingshuo Wang and Qingjiang Han ()
Additional contact information
Da Gao: School of Law and Business, Wuhan Institute of Technology, Wuhan 430205, China
Qingshuo Wang: School of Law and Business, Wuhan Institute of Technology, Wuhan 430205, China
Qingjiang Han: School of Law and Business, Wuhan Institute of Technology, Wuhan 430205, China

Energies, 2025, vol. 18, issue 18, 1-21

Abstract: Green and low-carbon development constitutes an essential pathway toward high-quality socioeconomic transformation, with improving urban green total factor energy efficiency (GTFEE) critical to achieving this objective. Based on the sample data of Chinese cities from 2013 to 2022, this study systematically investigated the impact and mechanism of critical peak pricing on urban GTFEE by using the double machine learning method, effectively supplementing the existing literature. This study finds that this policy significantly enhances urban GTFEE. Mechanism analysis indicates that critical peak pricing generates a dual effect by increasing the price difference between peak and off-peak hours and enhancing energy efficiency through two important channels: market expansion and technology-driven innovation. Heterogeneity analysis indicates that the critical peak pricing policy has a more significant promotion effect on non-resource-based, strong government administrative power, as well as central and eastern regions. These findings advance the power marketization reform framework and provide new theoretical support for promoting low-carbon energy transformation.

Keywords: critical peak pricing; urban GTFEE; double machine learning method; mechanism analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/18/4970/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/18/4970/ (text/html)

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:gam:jeners:v:18:y:2025:i:18:p:4970-:d:1752827

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().