Evaluation of the Policy Effects of Low-Carbon City Pilot Projects Based on the PSM-DID Model

Yu-yin Lin; Qing-juan Xu; Chun-ran Jiang

doi:10.30560/sdr.v7n1p136

Yu-yin Lin School of Mathematics and Statistics, Nanning Normal University, Guangxi, China
Qing-juan Xu School of Mathematics and Statistics, Nanning Normal University, Guangxi, China
Chun-ran Jiang School of Mathematics and Statistics, Nanning Normal University, Guangxi, China

DOI: https://doi.org/10.30560/sdr.v7n1p136

Keywords: carbon emissions, policy evaluation, PSM-DID, heterogeneity

Abstract

In the context of the dual-carbon policy, evaluating the implementation effects of low-carbon city pilot policies is of great significance. Based on panel data from 284 prefecture-level cities in China between 2004 and 2020, this paper integrates the Propensity Score Matching (PSM) method with the Difference-in-Differences (DID) method, referred to as the PSM-DID model. By employing parallel trend tests, placebo tests, robustness checks, and heterogeneity analyses, the implementation effects of the low-carbon city pilot policies are evaluated and compared with those from the traditional DID model. The results indicate that: (1) The low-carbon city pilot policies significantly curb carbon emissions in eastern China, while the effects in central and western regions are relatively weak; (2) Factors influencing carbon emissions differ significantly across regions. In particular, clean energy structure and per capita affluence have a greater impact on the eastern region, while the effect is weaker in the central and western regions; (3) The timing, scope, and regional factors of implementation significantly affect the policy outcomes. Policies implemented early yield more significant results than those implemented later, with regional development levels and scope of implementation playing key roles in shaping policy outcomes; (4) The PSM-DID model yields more reliable results than the DID model.

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