The research question centers on whether China's carbon trading policy (CTP), a market-based mechanism for climate change mitigation, can effectively promote industrial structure upgrading (UIS) and optimization (OIS). The study's context is China's expanding carbon trading market and the growing interest in its impact on industrial restructuring. UIS is defined as the advancement of industrial structure from lower to higher levels (e.g., labor-intensive to knowledge-intensive), while OIS refers to the rational allocation of resources and coordination between industries. The importance of the study lies in understanding how environmental policies can contribute to high-quality economic development and inform policymaking. The current industrial structure in China is characterized by high pollution and extensive development, which necessitates UIS and OIS for sustained economic growth. CTP, while directly aimed at environmental improvement, may indirectly promote UIS and OIS through mechanisms like cost constraints, innovation incentives, factor substitution, and consumption upgrading. However, the effect of CTP on industrial structure is not universally understood; there are counterarguments suggesting that increased costs may hinder UIS and OIS, or that pollution-intensive industries might simply relocate to areas with less stringent regulations. This paper aims to provide empirical evidence to address these uncertainties.

The literature review covers three main areas: carbon trading mechanisms, the emission reduction effects of CTP, and the impact of CTP on the economy and industrial structure. Regarding carbon trading mechanisms, the review examines different quota allocation schemes (based on current emissions, historical emissions, or carbon capital stock) and the importance of auction-paid allocations to avoid adverse selection. Studies on emission reduction effects show mixed results, with some finding significant emission reductions and regional heterogeneity while others suggest a more limited impact due to market imperfections. The review of the economic impacts of CTP reveals both positive effects (promoting high-quality economic development and technological innovation) and negative effects (weak economic effect and lack of impact on total factor productivity). Finally, the literature on the impact of CTP on industrial structure explores three theoretical perspectives: the compliance cost hypothesis, the pollution refuge hypothesis, and the Porter hypothesis. Empirical studies have shown mixed results on these hypotheses, highlighting the need for further research specifically focusing on China's CTP and its effects on industrial structure at the prefecture-level.

This study employs a difference-in-differences (DID) model using panel data from 201 prefecture-level cities in China from 2004 to 2018. The sample includes 33 pilot cities participating in the CTP and 168 control cities. The dependent variables are UIS (measured by the advancement of industrial structure, SA) and OIS (measured by the rationalization of industrial structure, SR). SA is calculated as the product of the output share and labor productivity in each industrial sector, while SR is calculated using a modified Theil index to account for structural deviations. The explanatory variable is a dummy variable representing the implementation of CTP in 2011. Control variables include human capital, government expenditure, per capita GDP, urbanization level, foreign direct investment, and infrastructure. A mediation effect model is used to analyze the role of technological innovation (measured by the number of patent applications) in the relationship between CTP and UIS/OIS. Regional heterogeneity analysis is performed by dividing cities into eastern and central/western regions. Urban characteristic heterogeneity analysis is conducted by categorizing cities based on levels of human capital, government expenditure, foreign investment, and infrastructure. Robustness checks include a placebo test and propensity score matching-DID.

The benchmark DID model results show that CTP significantly promotes UIS (positive and statistically significant coefficient for the interaction term of treatment and post-policy period). The impact on OIS is less pronounced but also statistically significant. The dynamic effect analysis reveals a time lag, with the effects of CTP on UIS becoming significant from 2013 onwards and on OIS becoming statistically significant after 2014. Robustness checks, including placebo tests and propensity score matching-DID, confirm the main findings. The mediation effect analysis demonstrates that technological innovation plays a significant mediating role in the relationship between CTP and both UIS and OIS. Heterogeneity analysis reveals significant regional differences. CTP is more effective in promoting UIS in eastern cities and OIS in central and western cities. Urban characteristic heterogeneity analysis shows that the effect of CTP is stronger in cities with high human capital and infrastructure, and that the impact varies depending on the levels of government expenditure and foreign investment. Table 2 summarizes the benchmark model estimation, Table 3 shows robustness tests results, Table 4 presents mediation effect test results, Table 5 presents the results of the regional heterogeneity test, Table 6 shows heterogeneity test results for SA, and Table 7 shows heterogeneity test results for SR.

The findings confirm that CTP can boost UIS and OIS in China, but the impact varies across regions and urban characteristics. The mediating role of technological innovation supports the Porter hypothesis, suggesting that appropriate environmental regulations can incentivize innovation and enhance competitiveness. The regional heterogeneity underscores the need for tailored policies considering the different developmental stages and resource endowments. The urban characteristic heterogeneity highlights the importance of human capital, infrastructure development, and strategic foreign investment attraction in maximizing the benefits of CTP. These findings contribute significantly to the literature by providing empirical evidence of the effects of CTP on industrial structure in China and revealing its underlying mechanisms and heterogeneous impacts.

This paper provides empirical evidence supporting the positive impact of China's CTP on both industrial structure upgrading and optimization, although the effect is stronger on upgrading. Technological innovation is identified as a key mediating mechanism. Significant regional and urban characteristic heterogeneities are also observed, implying the need for differentiated policy approaches. Future research could explore alternative measures of industrial structure, examine additional mediating factors beyond technological innovation, and conduct cross-country comparative studies.

The study's limitations include the reliance on a specific set of variables to measure UIS and OIS, the potential for omitted variable bias despite the inclusion of control variables, and the focus on China's specific context, limiting generalizability to other countries with different economic and policy settings. The time frame of the study may also limit the ability to assess the long-term effects of CTP.