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Strategic interactions for carbon emissions in Chinese cities are influenced by mayors

Nature Cities volume 1, pages 370–377 (2024)Cite this article

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Abstract

City-related mitigation measures are crucial for reducing carbon emissions, but most studies on this issue treat cities as independent entities and neglect their interactions. This is especially relevant in the Chinese context, where peers influence policy decisions. Here we offer a novel perspective about mayors’ strategic interactions to explain cities’ carbon intensity reduction. We use a spatial Durbin model to investigate the effects and patterns of interaction on carbon intensity among Chinese cities from 2000 to 2019. We found that mayors’ interaction impacted cities’ carbon intensity, resulting in a 0.792% reduction in reference cities for every 1% decrease in neighboring cities. Mayors with higher education, younger ages, science-related majors and working in their hometowns had better performance. Additionally, we revealed an ‘imitation competition’ pattern (emulating the practices of the neighboring cities). This study offers new insights into city emissions policies and introduces new recommendations.

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Fig. 1: Heterogeneity analysis of spatio-temporal interaction effects.
Fig. 2: Heterogeneity analysis of strategic interaction between different cities.
Fig. 3: Histogram of the strategic interaction patterns in carbon regulations.

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Data availability

Most of the data in this study are sourced from publicly available data sources. Datasets that are allowed to be shared are available through GitHub at https://github.com/2020000927/-Dynamical-Systems-Laboratory-Strategic-interaction-.git (ref. 48).

Code availability

Analysis was performed using custom-made scripts coded in Stata (Version 16) and MATLAB (Version R2023a). The do file includes the code of baseline model, robust test and temporal and spatial heterogeneity analysis. The m file includes the code of strategic interaction pattern, heterogeneity analysis pilot, rank and turnover). Scripts used for this study are available through GitHub at https://github.com/2020000927/-Dynamical-Systems-Laboratory-Strategic-interaction-.git (ref. 48).

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Acknowledgements

This work is supported by the National Natural Science Foundation of China under grant no. 72261147760 (C.W.) and the Outstanding Innovative Talents Cultivation Funded Programs 2023 of School of Applied Economics, Renmin University of China (B.Z.). We are grateful to T. Nakaishi of the Faculty of Economics, Kyushu University, for providing some writing suggestions.

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  1. School of Applied Economics, Renmin University of China, Beijing, P. R. China

    Bei Zhu & Chu Wei

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  1. Bei Zhu
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  2. Chu Wei
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Contributions

B.Z.: formal analysis, methodology, data curation, writing—original draft, and visualization. C.W.: conceptualization, writing—review and editing, and project administration.

Corresponding author

Correspondence to Chu Wei.

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Nature Cities thanks the anonymous reviewers for their contribution to the peer review of this work.

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Supplementary Information

It includes seven sections. Stylized fact and research hypotheses, China’s low-carbon city pilot policy and literature review of strategic interaction sections supplement the research background. Additional method, additional results and data description sections detail the calculation process and robustness tests of the study’s baseline results.

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Zhu, B., Wei, C. Strategic interactions for carbon emissions in Chinese cities are influenced by mayors. Nat Cities 1, 370–377 (2024). https://doi.org/10.1038/s44284-024-00059-z

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