Next Article in Journal
Process-Based Source Apportionment and Radiological Baseline of Multi-Radionuclides in Soils of a Tourism-Oriented Island
Previous Article in Journal
Green Skills in Finance for a Sustainable Bioeconomy: Systematic Literature Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Do Low-Carbon and New Energy Demonstration City Pilots Generate Synergy? Evaluating the Dual-Pilot Policy on Carbon Emission Performance with Double Machine Learning

1
School of Economics and Management, Changchun University of Technology, Changchun 130012, China
2
Collaborative Innovation Center for Green and Low Carbon Development, Changchun University of Technology, Changchun 130012, China
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(11), 5734; https://doi.org/10.3390/su18115734 (registering DOI)
Submission received: 28 April 2026 / Revised: 30 May 2026 / Accepted: 1 June 2026 / Published: 4 June 2026
(This article belongs to the Section Energy Sustainability)

Abstract

To advance sustainable development, China has introduced low-carbon city pilots (LCCP) and new energy demonstration city pilots (NEDC) as important institutional innovations. Using 2006–2023 panel data for 274 Chinese cities, we treat the dual-pilot policy of LCCP and NEDC as a quasi-natural experiment. We measure carbon emission performance (CEP) via a super-efficiency SBM-GML index incorporating social welfare and undesirable outputs, and use double machine learning (DML) to estimate the policy’s impact on CEP. We find the dual-pilot policy is associated with significantly improved urban CEP, with a stronger effect than either single pilot alone. Mechanism tests suggest the policy may contribute to improved CEP by promoting green technology innovation, industrial structure upgrading, and energy efficiency. Heterogeneity test results demonstrate that the dual-pilot policy yields more pronounced impacts in cities characterized by higher economic development, weaker path dependence, and more stringent environmental governance. Additionally, negative cross-regional spatial spillovers are identified. Different from the existing literature, this study integrates social welfare dimensions into CEP’s measurement framework and further validates that the dual-pilot policy generates more outstanding efficiency benefits compared with separate LCCP and NEDC pilots
Keywords: carbon emission performance; dual-pilot policy; super-efficiency SBM-GML; low-carbon cities; new energy demonstration cities; double machine learning carbon emission performance; dual-pilot policy; super-efficiency SBM-GML; low-carbon cities; new energy demonstration cities; double machine learning

Share and Cite

MDPI and ACS Style

Li, M.; Jiang, Q. Do Low-Carbon and New Energy Demonstration City Pilots Generate Synergy? Evaluating the Dual-Pilot Policy on Carbon Emission Performance with Double Machine Learning. Sustainability 2026, 18, 5734. https://doi.org/10.3390/su18115734

AMA Style

Li M, Jiang Q. Do Low-Carbon and New Energy Demonstration City Pilots Generate Synergy? Evaluating the Dual-Pilot Policy on Carbon Emission Performance with Double Machine Learning. Sustainability. 2026; 18(11):5734. https://doi.org/10.3390/su18115734

Chicago/Turabian Style

Li, Mingyang, and Qiancheng Jiang. 2026. "Do Low-Carbon and New Energy Demonstration City Pilots Generate Synergy? Evaluating the Dual-Pilot Policy on Carbon Emission Performance with Double Machine Learning" Sustainability 18, no. 11: 5734. https://doi.org/10.3390/su18115734

APA Style

Li, M., & Jiang, Q. (2026). Do Low-Carbon and New Energy Demonstration City Pilots Generate Synergy? Evaluating the Dual-Pilot Policy on Carbon Emission Performance with Double Machine Learning. Sustainability, 18(11), 5734. https://doi.org/10.3390/su18115734

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop