How Does Green Financial Reform Impact Carbon Emission Reduction and Pollutant Mitigation in Chinese Manufacturing Enterprises?

Abstract

Manufacturing enterprises, as significant contributors to high carbon emissions, play a crucial role in effectively reducing carbon emission intensity, which is essential for China to successfully achieve its “dual carbon” goals. This study examines the period from 2010 to 2022, focusing on manufacturing enterprises listed on the Shanghai and Shenzhen A-shares to investigate the effects of green financial reform on carbon and pollutant emissions. Our findings reveal that the results from the parallel trend test and the regression analysis of the Difference-in-Differences (DID) model indicate that the implementation of green financial reform has a negative impact on the carbon and pollutant emissions of manufacturing enterprises, which is supported by a series of robustness tests. Heterogeneity analysis shows that the emission reduction effect of green financial reform on pollutants is significant only in manufacturing enterprises with low industry competitiveness, while the inhibitory effect on carbon emissions is significant only in those with high industry competitiveness. Furthermore, the emission reduction effects are significant in highly polluting industries, non-state-owned enterprises, and small-scale firms. Green technological innovation and financing constraints serve as the channels connecting green financial reform with emission reduction and carbon mitigation. The tax burden negatively moderates this process, while environmental, social, and governance (ESG) performance positively moderates it.

1. Introduction

With the rapid development of industrialization and urbanization, global environmental issues have become increasingly severe, leading to frequent extreme weather events. Problems such as rising sea levels and a significant decline in biodiversity pose serious threats to human survival and health. Therefore, various nations have adopted various environmental policies to address these challenges, aiming to improve environmental quality and promote sustainable economic development. As the largest developing country in the world, China faces significant environmental pressures. To achieve both economic development and environmental protection, China proposed in 2012 to prioritize ecological civilization construction and to strive to build a beautiful China. In 2014, ecological security was incorporated into the national security system, and the national ecological and environmental protection work conference held in 2024 also emphasized the need to promote the establishment of a green, low-carbon, and circular economic system. It is evident that China places great importance on environmental protection issues, working to improve the ecological rights and environmental well-being of its citizens through measures such as energy trading rights, the construction of new energy demonstration cities, ecological protection red lines, and industrial mechanization [1] with significant results. According to data from the Ministry of Ecology and Environment, from 2013 to 2022, the national GDP grew by 69%, while the average concentration of PM2.5 decreased by 57%, and the number of heavily polluted days dropped by 92%, essentially eliminating severe pollution days [2]. It is evident that the various environmental policies implemented in our country have effectively improved environmental quality (see Figure 1).

However, in terms of the current effectiveness of environmental governance, there are still many issues. First, compared to developed countries, the ecological and environmental quality in China is relatively lagging and at a medium to low level. Less than 60% of cities nationwide meet air quality standards. Additionally, there are prominent issues of imbalance and lack of coordination in water body management and protection, with some monitoring sections showing a rebound in water quality. Second, regarding the promotion of green production and lifestyle, the current efficiency of energy resource utilization is relatively low. The development and utilization of renewable energy face constraints, such as the power system’s inadequate adaptability to the integration and consumption of large-scale, high-proportion renewable energy. There are also significant land resource constraints, which limit the promotion of green production and lifestyle. Third, in terms of environmental governance capacity, there are still many structural issues during the process of promoting the modernization of the environmental governance system and governance capacity. For example, ecological restoration assessment capabilities are weak, and various reform measures have failed to effectively achieve the goal of collaborative efficiency. At the same time, the construction of ecological and environmental infrastructure and the enhancement of grassroots ecological and environmental governance capabilities are also urgent. The root causes of these issues lie in several factors: insufficient scientific planning and design, an imperfect supervision and assessment system, a lack of standardization and normalization in the environmental protection system, and low levels of social capital and public participation.

As a new model for promoting financial development and an important means to achieve the “dual carbon” goals, the implementation of green financial reform helps guide and optimize the allocation of financial resources. It also promotes the optimization and upgrading of industrial structures [3]. Additionally, it establishes an economic mechanism to correct negative externalities such as greenhouse gas effects and pollution emissions, internalizes environmental costs, and thereby achieves sustainable economic development. In 2015, China initiated the top-level design for green financial reform and proposed an overall plan for establishing it. In June 2017, the country decided to implement a five-year experimental program for green financial reform and innovation in eight regions across five provinces. According to the data provided by the People’s Bank of China, by the end of September 2022, the People’s Bank of China had provided a total of CNY 156.734 billion in re-lending support for the experimental zones, with green loans in these areas accounting for 12.58% of total loans [4]. Currently, China has fully leveraged the important role of green finance in promoting green development and assisting in achieving the “dual carbon” goals, resulting in a reduction of carbon dioxide emissions equivalent to over 60 million tons.

It is evident that green financial reform, as a new attempt within China’s financial system, holds significant importance for enhancing environmental governance and achieving the goal of a “Beautiful China.” This raises the following questions: Can the implementation of green financial reform effectively motivate manufacturing enterprises to participate in environmental protection and reduce both pollutant and carbon emissions? What are the mechanisms through which green financial reform influences the carbon reduction and emission mitigation efforts of manufacturing enterprises? Additionally, will this impact vary based on the characteristics of individual enterprises? To further address these questions, this paper utilizes research data from A-share listed manufacturing enterprises in China from 2012 to 2022. It employs models such as the staggered difference-in-differences model, moderation effect model, and mediation effect model for analysis. This research aims to provide empirical references for achieving coordinated economic, social, and environmental development.

The marginal contributions of this paper may be summarized as follows: First, existing studies on corporate environmental governance behaviors often overlook the relationship between carbon emissions and pollutant emissions. However, since both have similar sources, isolating the two in research may lead to one-sided policy recommendations. Therefore, this paper integrates carbon reduction and pollution control into a single study, exploring the role of green financial reform in the carbon and pollution governance of manufacturing enterprises. This integration can provide new theoretical support and practical guidance for the combined development of green finance and the real economy. Second, the paper analyzes the guiding and incentive effects of green financial reform policies on the carbon and pollution governance of manufacturing enterprises, revealing how these policies influence emissions through channels such as capital allocation and technological innovation. Third, it focuses on the adaptability and response strategies of manufacturing enterprises in the context of green financial reform, providing valuable references for the coordinated governance of carbon and pollution and low-carbon transformation in manufacturing enterprises. This not only offers practical guidance for China’s green financial reform and the carbon and pollution governance of manufacturing enterprises but also provides beneficial insights and references for policy formulation and implementation in other countries and regions.

2. Literature Review and Research Hypotheses

2.1. Literature Review

2.1.1. Research on Green Financial Reform

• Construction of green financial reform

To promote the establishment of a green finance system and achieve the goals of ecological and environmental protection, China has launched green financial reform pilot zones in phases. This initiative supports low-carbon and high-quality economic development. Early research on the construction of these green financial reform pilot zones primarily focused on system construction. Fan et al. categorized the policy development of green finance in China into an initial stage, rapid development stage, and differentiated development stage [5]. Subsequently, Du et al. [6] discussed the roles of the government and commercial banks in the development of green finance. Since then, domestic scholars have shifted their research focus to the exploration and practice of green financial reform, primarily concentrating on regions such as Jiangxi, Zhejiang, Shandong, Guizhou, and Guangdong [7,8]. During the implementation of green financial reform, issues such as weak governance and inadequate regulation have emerged. These problems have led to the waste of financial resources and limited effectiveness of the reforms. To address these challenges, some scholars have begun to explore regulatory practices [9] and international cooperation [10].

• The effectiveness of green financial reform

Since the inception of green financial reform, both domestic and international scholars have examined its effectiveness, with a primary focus on its impacts on supply-side structural reform [11], urban employment [12], and related fields. Specifically, research on the effectiveness of green financial reform can be mainly divided into three categories. The first is economic effects: the implementation of green financial reform not only contributes to higher levels of green consumption and improved quality of economic development, but also significantly promotes the improvement of total factor productivity and green total factor productivity [13]. At the micro level, green financial reform helps strengthen enterprises’ green investment [14], enhance energy resilience [15] and green performance, but it also increases the risk of greenwashing [16]. Regarding environmental effects, at the meso and macro levels, green financial reform can significantly promote the ecological development of regional industrial structures, facilitate the low-carbon transition of the economy, and reduce carbon emissions [17]. At the micro level, it helps enhance enterprises’ sustainability and further reduce carbon emissions. In addition, green financial reform helps improve enterprises’ ESG performance, and both external environmental law enforcement and internal managers’ environmental awareness can further enhance this positive effect [18]. The third effect is innovation [19]. Given that green finance inherently encourages enterprises to adopt environmentally friendly technologies, scholars have extensively explored its effects on innovation. There is a general consensus that green financial reform can stimulate green technological innovation at the enterprise level to some extent, with a more pronounced effect on state-owned enterprises and those in heavily polluting industries.

2.1.2. Literature Review on Carbon Reduction and Emission Mitigation

Research on the effectiveness of carbon reduction and emission mitigation can mainly be divided into three categories: carbon reduction, emission mitigation, and the synergy between carbon reduction and emission mitigation.

First, carbon reduction. With the increasing frequency of climate issues such as glacier melting and heat waves, scholars have increasingly explored measures to mitigate greenhouse gas and carbon emissions [20]. Zexing et al. expanded the research field of carbon reduction to water pollution prevention and control, arguing that deepening efforts to safeguard clean water is also a key channel for achieving carbon reduction goals [21]. With the implementation of various national environmental policies and the application of natural experiments in causal analysis within economics, a growing number of scholars have begun to use causal analysis methods to study the impact of environmental policies on carbon emissions. The relevant policies mainly include the sustainable development policy for resource-based cities [22], high-speed railway construction [23], the “Broadband China” initiative [24], the carbon emissions trading policy [25], “zero-waste city” pilot policy [26], and others. The effects of policies may vary according to characteristics such as location, city level, and type of pollution [27]. In addition, technological innovation, industrial structure, investor attention, and government supervision are important mechanisms [28].

Second, emission mitigation. Research on pollution emission mitigation can be traced back to 2001. Wang et al., based on pollution from product consumption, introduced consumer surplus and the negative externalities of product consumption, and established a differentiated pollution reduction model for international trade [29]. Subsequently, Jia et al. explored strategies for water conservation and pollution reduction [30]. Andreoni et al. further adopted an endogenous growth model to analyze the causes of the inverted U-shaped Environmental Kuznets Curve from the perspective of pollution reduction technology [31]. As environmental pollution problems have become increasingly severe, scholars have begun to shift their research focus to the effectiveness of various pollution reduction measures. From a non-policy perspective, the level of economic development [32], energy and fossil fuel use [33], and trade openness are key factors influencing pollutant emissions. From a policy perspective, the implementation of policies such as the environmental protection tax [34], green credit policies [35], the “Broadband China” strategy [36], and the construction of new energy demonstration cities [37] all have an impact on pollutant emissions. The effects of these factors on pollutant emissions are influenced by the characteristics of individual cities, industries, and enterprises, resulting in considerable heterogeneity.

Third, regarding the synergy between carbon reduction and pollutant emission mitigation, there is a wealth of research. Early studies mainly explored its fundamental concepts and implementation paths. Özkan et al., Yang et al. and Zhao et al. have explored implementation paths for carbon and pollutant emission mitigation from perspectives such as energy transition and industrial structure, and have constructed a comprehensive, process-integrated system for synergistic pollution and carbon reduction [38,39,40,41].

2.2. Research Hypothesis

2.2.1. Green Financial Reform and Corporate Carbon and Pollutant Emissions

Green financial reform, as an important tool for promoting the green transformation of the economy and society, not only facilitates the construction of green industrial and service systems and improves the ecological environment, but also brings economic benefits by optimizing the allocation of financial resources and improving the operational efficiency of financial institutions. In the context of increasingly severe global climate change and environmental issues, green financial reform provides strong financial support for manufacturing enterprises through innovative financial instruments and service models, thereby promoting their carbon reduction and emission mitigation efforts.

Firstly, green financial reform broadens the financing channels for manufacturing enterprises through innovative financial instruments and service models. It provides low-cost, long-term financial support in the form of green credit, green bonds, and green funds, significantly reducing the financing costs for manufacturing enterprises and alleviating funding shortages. These financial tools not only help companies lower their financial costs during the green transformation process but also encourage them to adopt advanced environmentally friendly technologies and equipment, thereby effectively reducing carbon emissions and pollutant discharges. Secondly, green financial reform enhances technological innovation and application in manufacturing enterprises. The establishment of green technology funds and green innovation funds is an important measure. With its implementation, financial institutions increase investment in technological innovation for manufacturing enterprises. Through the innovation of green financial products and services, such as green insurance and green leasing, enterprises are supported in developing key technologies for high-efficiency energy saving, clean production, and resource recycling. The application of these research achievements can effectively reduce energy consumption and carbon and pollutant emissions in manufacturing enterprises, forming a virtuous cycle. In light of the above, Hypothesis 1 is proposed.

Hypothesis H1:

The implementation of green financial reform contributes to the reduction of carbon emissions in manufacturing enterprises.

2.2.2. The Mediating Channels of the Impact of Green Financial Reform on Corporate Carbon Emissions

According to the Porter Hypothesis, appropriate environmental regulations can promote technological research and development activities. In the context of green financial reform affecting carbon emissions from manufacturing enterprises, green technological innovation is viewed as an important driving force. However, green technological innovation in the manufacturing sector often requires substantial R&D investment, longer return periods, and higher R&D risks, making it difficult for the traditional financial system to meet these demands. In this situation, green financial reform establishes environmental protection and resource efficiency as important criteria for evaluating financing activities, providing financial services that support climate change mitigation and resource conservation, thereby offering funding support for green technological innovation in manufacturing. Moreover, green financial reform encourages manufacturing enterprises to collaborate with universities, research institutions, and others, promoting deep integration of industry, academia, and research. This collaborative model helps form an innovation mechanism that shares benefits and risks, reducing R&D risks for enterprises and promoting the development and application of common technologies. Overall, the organic combination of green financial reform and green technological innovation provides dual support for carbon reduction and emissions reduction in manufacturing enterprises. On one hand, green finance encourages enterprises to increase investment in green technological innovation through financial support and policy guidance; on the other hand, green technological innovation drives the green and low-carbon transformation of manufacturing enterprises through the application and commercialization of innovative results. In light of the above, Hypothesis H2 is proposed.

Hypothesis H2:

green financial reform has the potential to achieve carbon reduction and emissions reduction targets by promoting green technological innovation in the manufacturing sector.

As global environmental issues become increasingly severe, carbon reduction and emissions reduction in manufacturing enterprises have become key to achieving sustainable development. However, the traditional financial financing system faces problems such as complex processes, high transaction costs, high financing costs and thresholds, lack of flexibility, and limited varieties of financial products. These issues severely restrict the financing channels for manufacturing enterprises, further limiting their ability to adopt green technologies and achieve low-carbon production. As an important force driving the green transformation of the economy, green financial reform has gradually evolved into an effective means to address the financing challenges faced by manufacturing enterprises and promote carbon reduction and emissions reduction. As an innovation in the financial system, green financial reform can significantly alleviate the financing constraints faced by manufacturing enterprises, mainly reflected in the following three aspects: First, green financial reform broadens financing options by providing various financial instruments such as green loans and green bonds. This reduces financing costs and transaction fees, improves access to funds, and alleviates the financial pressure on enterprises. Second, green financial reform lowers financing thresholds by encouraging the establishment of specialized green financial institutions, improving green project databases and service platforms, and streamlining approval processes. This helps small and medium-sized enterprises overcome financing difficulties and promotes their green transformation. Overall, green financial reform reduces financing costs, making it easier for manufacturing enterprises to access funds and diversify risks, thereby driving technological innovation and environmental management, and promoting carbon reduction and emission mitigation. In light of the above, Hypothesis 3 is proposed.

Hypothesis H3:

Green financial reform can facilitate carbon reduction and emission mitigation in manufacturing enterprises by alleviating financing constraints.

3. The Impact of Green Financial Reform on Carbon Emissions of Manufacturing Enterprises

3.1. Research Design

3.1.1. Model Settings

Based on relevant studies, this paper adopts a DID model to identify the impact of green financial reform on carbon reduction in manufacturing enterprises [42]. In the specific regression process, we perform two rounds of differencing: the first difference quantifies the relative relationship between the experimental group and the control group before and after the implementation of green financial reform, thereby accounting for the individual heterogeneity of carbon emissions in manufacturing enterprises. The second difference accounts for the incremental changes in carbon emissions over time between the experimental group and the control group, thus removing time dependency. It is evident that the two rounds of differencing used in the DID model effectively eliminate individual differences and time trends between the experimental group and the control group enterprises. Additionally, the binary variables employed help to address the endogeneity issue arising from mutual causality. Furthermore, the relevant analysis in this paper is conducted using a fixed effects model, with clustered robust standard errors set at the city level where the green financial reform is implemented, aiming to reduce estimation bias caused by omitted variables and thereby enhance the precision of the study. In addition, considering that China’s green financial reform is implemented gradually and in batches, and drawing on relevant studies [42,43], this paper establishes the difference-in-differences model as follows:

$$Y_{it}={\beta }_0+{\beta }_{1}Did+{\gamma Con}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(1)

In this model, $i$ and $t$ represent manufacturing enterprises and years, respectively. $Y_{it}$ denotes the carbon emissions or pollutant emissions of manufacturing enterprise $i$ in year $t$; $Did$ represents the dummy variable for the implementation of the green financial reform. We selected the eight regions approved as the first batch of green financial reform pilot zones in 2017 as the treatment group, while other regions that did not implement this policy were designated as the control group. For firms i located in the pilot zones, if their region was included in the pilot zone in 2017, then the Did variable takes the value of 1 for 2017 and subsequent years; conversely, if the firm is located in a non-pilot zone, the Did variable will always be 0. ${Con}_{it}$ denotes the control variables; ${\mu }_i$ indicates the fixed effects; ${\lambda }_t$ represents the year fixed effects; and ${\epsilon }_{it}$ denotes the random error term for enterprise $i$ in year $t$. The coefficients ${\beta }_0$, ${\beta }_1$ and $\gamma$ correspond to the regression coefficients of the respective variables. Among these, ${\beta }_1$ indicates the average effect of the implementation of green financial reform on the carbon emissions of manufacturing enterprises. To reduce issues of heteroscedasticity and autocorrelation and to improve regression accuracy, this paper employs clustered robust standard errors at the enterprise level.

3.1.2. Variable Selection

Carbon Emissions (CO₂): According to international standards, the accounting of corporate carbon emissions can be primarily divided into three scopes [44]: Scope 1 refers to direct carbon emissions generated from sources owned or controlled by the company; Scope 2 includes indirect carbon emissions resulting from the greenhouse gases produced by the electricity and heat consumed by the enterprise; Scope 3 encompasses other scattered indirect emissions. Generally, both direct and indirect carbon emissions are required to be disclosed internationally, and their sum constitutes the total carbon emissions. Furthermore, if carbon emissions are considered in isolation without accounting for the impact on economic output, research in this field may fall into the “carbon rebound effect,” leading to potentially biased conclusions. Therefore, this paper intends to calculate the carbon emissions per unit of economic activity based on the total revenue of the enterprise.

Pollutant Emissions ($Pol$): Based on relevant studies, this paper selects the emissions of sulfur dioxide, nitrogen oxides, and particulate matter from exhaust gases, as well as chemical oxygen demand, ammonia nitrogen emissions, total nitrogen, and total phosphorus from wastewater as baseline variables. Subsequently, according to the “Management Measures for the Collection of Pollutant Discharge Fees,” the selected baseline pollutant emissions undergo a standardization process. After obtaining the standardized emission equivalents, they are summed to reflect the pollution emission levels of the enterprises. To mitigate the impact of economic activities on pollutant emissions, this paper also calculates the pollutant emissions per unit of economic activity based on the total revenue of manufacturing enterprises.

3.1.3. Core Explanatory Variable

Green financial reform ($Did$): Based on the research by Tong et al. [17], the implementation of green financial reform is selected as the core explanatory variable. Specifically, if the region where firm $i$ is located is selected as an experimental zone in year $t$, then $Did$ equals 1 in the years following $t$; otherwise, it equals 0.

3.1.4. Control Variables

Control Variables: Due to the complex factors influencing carbon and pollutant emissions, this study references the research by Xu et al. [45] and selects individual characteristics at the enterprise level as control variables. These include the following: Total Factor Productivity ($TFP$): This measures the role of pure technological progress in production according to neoclassical economic growth theory. The total factor productivity used in this analysis is calculated based on total output, capital input, labor input, and intermediate goods input, utilizing the LP method. Enterprise Size ($Size$): Generally speaking, the larger the enterprise, the higher the scale and frequency of its production activities, which in turn affects carbon and pollutant emissions. This paper measures enterprise size using the logarithm of total assets. Investment Expenditure Rate ($Invt$): Typically, investment expenditure reflects the self-accumulation capacity of an enterprise and indicates the level of self-restraint in post-tax retained earnings being directed towards consumption. This paper measures it as the ratio of cash used for purchasing or constructing fixed assets, intangible assets, and other long-term assets to total assets. Debt Ratio ($Tl$): Generally speaking, a higher debt ratio indicates that an enterprise has limited investment for environmental governance, leading to relatively higher carbon and pollutant emissions. This paper measures it as the ratio of total liabilities to total assets. Separation of Ownership and Control ($Sep$): Typically, a higher degree of separation allows managers to make more informed decisions. This paper measures it as the difference between control rights and ownership rights.

3.1.5. Data Sources

This study selects the observation period from 2010 to 2022, focusing on manufacturing enterprises listed on the Shanghai and Shenzhen stock exchanges to examine the impact of green financial reform on carbon and pollutant emissions from these enterprises. All data used in this research comes from the CSMAR database. To obtain the sample data required for the study, the carbon emissions and pollutant emissions of enterprises were matched with the independent variables, dependent variables, and control variables. Specifically, a 1:1 matching was conducted based on the listing codes of manufacturing enterprises and the corresponding years. To avoid the influence of outliers on the regression results, the following processing was applied to the matched data: companies classified as ST, *ST, or PT were excluded; companies that had been listed for less than one year, had already delisted, or had been suspended from listing were also removed. After these processing steps, a non-balanced panel dataset of 20,019 enterprise–year observations was obtained. Descriptive statistics for the relevant variables are shown in

Table 1. Descriptive statistics of variables.

VAR	Obs	Mean	Std. Dev.	Min	Max
CO2	17,257	0.1448	0.0046	0.1311	0.1529
Pol	16,928	0.0049	0.0042	0	0.3547
Did	20,019	0.0236	0.1519	0	1
TFP	20,019	11.4606	24.1847	0.2567	561.0974
Size	20,019	21.8419	1.2359	16.6380	27.6211
Invt	20,019	0.0571	0.0498	0	0.5453
Tl	20,019	0.3754	0.2491	0.0075	13.7114
Sep	17,610	5.1415	7.6803	0	59.5000

.

3.2. Baseline Regression

3.2.1. Parallel Trends

The parallel trends test is a prerequisite for conducting policy analysis using the Did model. Therefore, referencing related research [46], this study employs the event study method to conduct a parallel trends test on the impact of green financial reform on carbon and pollutant emissions from manufacturing enterprises. In the specific regression analysis, this study selects the period of policy implementation as the baseline. To avoid the influence of multicollinearity, this baseline is excluded during the regression process. Figure 2 illustrates the dynamic effect coefficients of green financial reform on carbon and pollutant emissions from manufacturing enterprises.

According to Figure 2, before the implementation of the green financial reform, the 95% confidence intervals for the regression coefficients of pollutant emissions and carbon emissions both include zero. This indicates that there were no significant differences in carbon and pollutant emissions between the treatment group and the control group prior to the reform. After the pilot implementation of the green financial reform, the confidence interval from the first period does not include zero, and the regression coefficient is negative. This result suggests that the green financial reform can effectively reduce carbon and pollutant emissions from manufacturing enterprises. Therefore, it is feasible to use the staggered difference-in-differences model to verify the impact of green financial reform on carbon and pollutant emissions from manufacturing enterprises.

3.2.2. Baseline Analysis

Based on the regression model 1 established in the previous section, this study examines the impact of green financial reform on carbon and pollutant emissions from manufacturing enterprises. The regression results are presented in

Table 2. Baseline regression results.

VAR	Pol		CO2
	(1)	(2)	(3)	(4)
Did	−0.0009 **	−0.0010 *	−0.0006 ***	−0.0005 ***
	(0.0004)	(0.0006)	(0.0002)	(0.0002)
TFP		1.24 × 10−6		1.65 × 10−5 ***
		(0.0000)		(0.0000)
Size		−3.72 × 10−5		−0.0017 ***
		(0.0000)		(0.0005)
Invt		0.0006 **		−0.0037 ***
		(0.0003)		(0.0010)
Tl		5.62 × 10−5 *		0.00394 **
		(0.0000)		(0.0016)
Sep		1.32 × 10−6		1.11 × 10−5 *
		(0.0000)		(0.0000)
Con	0.145 ***	0.145 ***	0.005 ***	0.041 ***
	(0.0000)	(0.0008)	(0.0000)	(0.0097)
Obs	16,622	14,253	16,637	16,146
R2	0.950	0.952	0.166	0.183

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, **, and * indicate significance at the 1%, 5%, and 10% confidence levels, respectively.

. Columns (1) and (2) show the results for pollutant emissions, both without and with control variables, while columns (3) and (4) display the results for carbon emissions under the same conditions.

According to columns (1) and (2), when control variables are not included, the regression coefficients of Did are significantly negative. After including control variables, both the regression coefficients and their significance decrease but remain significantly negative. This indicates that the implementation of green financial reform negatively impacts pollutant emissions from manufacturing enterprises, thereby validating H1. In other words, the implementation of green financial reform contributes to reducing pollutant emissions from manufacturing enterprises. This suggests that the establishment of green financial reform pilot zones provides comprehensive support and incentives for pollutant management in manufacturing enterprises.

According to columns (3) and (4), regardless of whether control variables are included, the regression coefficients of Did are negative, and their significance remains unchanged. This indicates that the implementation of green financial reform negatively impacts carbon emissions from manufacturing enterprises, further confirming H1. In other words, the pilot implementation of green financial reform contributes to reducing carbon emissions from manufacturing enterprises. From the perspective of financial institutions, the green financial reform pilot zones encourage their participation in research and development and the provision of specialized funding for green financial products through financial policy support and incentives. This funding aims to support low-carbon technology research and development as well as clean energy projects, lower the barriers for manufacturing enterprises to apply for green finance, and guide them toward low-carbon production models. From the perspective of manufacturing enterprises, the establishment of pilot zones helps enhance their environmental awareness and carbon emissions management capabilities. The green financial reform has established an effective incentive and constraint mechanism for manufacturing enterprises. To secure specialized funding, these enterprises are encouraged to adopt measures such as low-carbon technology research and development to monitor and reduce their carbon footprint. Additionally, the establishment of green financial reform pilot zones aids manufacturing enterprises in developing green supply chains. By encouraging stakeholders, including upstream and downstream enterprises, to use environmentally friendly materials and low-carbon production processes, the reform facilitates the green and low-carbon transformation of the entire industrial chain. Furthermore, the demonstration effects at regional and industry levels promote the application and dissemination of low-carbon technologies, ultimately creating a carbon reduction framework that involves the participation of society as a whole.

3.3. Robustness Test

3.3.1. Placebo Test

The methodology employed in this study effectively addresses potential biases in causal inference regarding the impact of green financial reform on carbon emissions in manufacturing enterprises. By utilizing a placebo test and constructing a virtual treatment group, the study enhances the robustness of its findings. Drawing on 500 random samples further strengthens the reliability of the results by minimizing the influence of low-probability events and unobservable factors. Additionally, the kernel density distribution plots of the regression coefficients provide a clear visual representation of the data, facilitating a better understanding of the relationship between green financial reform and carbon emissions. Overall, this approach significantly contributes to the validity of the conclusions drawn from the analysis. According to Figure 3, the kernel density plot of pollutant emissions from the placebo test approximately follows a normal distribution with a mean close to zero. This indicates that the impact of green financial reform on pollutant emissions from manufacturing enterprises is not influenced by exogenous factors. In the kernel density plot of carbon emissions from the placebo test, the distribution shows a left tail and is approximately normal. Although the mean is not exactly zero, it significantly differs from the original regression coefficient of −0.0005. This suggests that while the impact of green financial reform on carbon emissions is affected by other policies or omitted variables, it does not undermine the robustness of the original research conclusions. Overall, this analysis indicates that in the randomly selected treatment group, the impact of green financial reform on both carbon and pollutant emissions from manufacturing enterprises remains significantly negative, further validating the robustness of the baseline regression results.

3.3.2. PSM-DID

To mitigate sample selection bias, this study further employs the PSM-DID model to assess the impact of green financial reform on carbon and pollutant emissions from manufacturing enterprises. Specifically, the nearest neighbor matching method is used to match the manufacturing enterprises in the treatment and control groups, eliminating any unmatched data. Based on this, the Did model regression is conducted again. The regression results are presented in

Table 3. Robustness test II: PSM-DID.

VAR	Pol		CO2
	(1)	(2)	(1)	(2)
Did	−0.0009 **	0.0100 ***	−0.0006 **	−0.0005 *
	(0.0004)	(0.0035)	(0.0003)	(0.0003)
Con	0.145 ***	0.145 ***	0.005 ***	0.041 ***
	(0.0000)	(0.0008)	(0.0000)	(0.0097)
CVs	YES	YES	YES	YES
Obs	15,696	14,441	14,871	14,373
R2	0.938	0.935	0.021	0.042

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, **, and * indicate significance at the 1%, 5%, and 10% confidence levels, respectively.

. According to Table 3, regardless of whether control variables are included, the regression coefficients of Did for carbon and pollutant emissions are significantly negative, consistent with the baseline regression results. This further validates the robustness of the baseline findings.

3.3.3. Retain Central Cities

Cities of different administrative levels have varying capacities to attract funds, talent, and other resources, which can also impact industrial development. Therefore, this study considers the differences between municipalities, provincial capital cities, and ordinary prefecture-level cities. Additionally, given that there are relatively few registered enterprises in prefecture-level cities, which may hinder a complete representation of the regression results, this paper excludes manufacturing enterprise samples registered in prefecture-level cities and conducts the regression analysis again. The results are presented in the table below. According to

Table 4. Robustness test III: retain central cities.

VAR	Pol		CO2
	(1)	(2)	(1)	(2)
Did	0.0005 ***	0.0001 ***	−0.0006 ***	−0.0005 ***
	(0.0001)	(0.0000)	(0.0000)	(0.0000)
Con	0.145 ***	0.145 ***	0.005 ***	0.033 ***
	(0.0000)	(0.0015)	(0.0000)	(0.0050)
CVs	YES	YES	YES	YES
Obs	6402	5505	6199	5991
R2	0.953	0.951	0.420	0.427

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, indicates significance at the 1%, confidence levels.

, regardless of whether control variables are included, the policy variable Did for green financial reform is significantly positive at the 1% level, indicating that the implementation of green financial reform helps reduce pollutant and carbon emissions from manufacturing enterprises in central cities, further validating the robustness of the baseline regression results.

3.3.4. High-Dimensional Fixed

Given the inherent differences among enterprises in the manufacturing industry, this paper incorporates these industry differences into the regression model to further mitigate regression bias caused by industry disparities and omitted variables, using a high-dimensional fixed effects model for re-estimation. The regression results are presented in

Table 5. Robustness test IV: high-dimensional fixed effects.

VAR	Pol		CO2
	(1)	(2)	(1)	(2)
Did	0.0005 ***	0.0001 ***	−0.0006 ***	−0.0005 ***
	(0.0001)	(0.0000)	(0.0000)	(0.0000)
Con	0.145 ***	0.145 ***	0.005 ***	0.033 ***
	(0.0000)	(0.0015)	(0.0000)	(0.0050)
CVs	YES	YES	YES	YES
Obs	6402	5505	6199	5991
R2	0.953	0.951	0.420	0.427

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, indicates significance at the 1%, confidence levels.

. According to Table 5, compared to the baseline regression in Table 2, both the regression coefficients and significance levels have not changed significantly. This indicates that even when accounting for industry differences, the impact of green financial reform on carbon reduction and emission mitigation in manufacturing enterprises remains significant, further validating Hypothesis 1.

3.4. Heterogeneity Analysis

3.4.1. Heterogeneity of Industry Competition Intensity

The social responsibility of enterprises is to generate profits, and the level of competition within the industry directly affects their profitability. To investigate whether there is heterogeneity in industry competition intensity regarding the impact of green financial reform on carbon reduction and emission mitigation in manufacturing enterprises, this paper uses the industry Herfindahl index to classify industries into high and low competition based on the median, and conducts subsample regression. The results are presented in the table below.

According to

Table 6. Heterogeneity analysis I: heterogeneity of industry competition intensity.

VAR	Pol				CO2
	High Competition Intensity		Low Competition Intensity		High Competition Intensity		Low Competition Intensity
Did	−0.0007	−0.0006	−0.0015 ***	−0.0016 ***	−0.0007 **	−0.0006 **	−0.0004	−0.0001
	(0.0009)	(0.0010)	(0.0002)	(0.0003)	(0.0003)	(0.0002)	(0.0004)	(0.0004)
Con	0.145 ***	0.144 ***	0.144 ***	0.146 ***	0.005 ***	0.055 ***	0.005 ***	0.031 ***
	(0.0000)	(0.0013)	(0.0000)	(0.0012)	(0.0000)	(0.0169)	(0.0000)	(0.0059)
CVs	NO	YES	NO	YES	NO	YES	NO	YES
Obs	8526	7101	7084	6796	8120	7928	8270	7969
R2	0.953	0.956	0.948	0.949	0.211	0.233	0.217	0.230

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; *** and ** indicate significance at the 1% and 5%, confidence levels, respectively.

, the impact of green financial reform on pollutant reduction is significant only in manufacturing enterprises with low industry competition intensity. This indicates that green financial reform has a notable inhibitory effect on pollutant emissions in these enterprises, while its effect on manufacturing enterprises with high competition is not significant. This may be due to the fact that in industries with lower competition, there are fewer potential competitors and producers of substitute products, resulting in lower entry barriers and market pressure. Consequently, manufacturing enterprises in such environments tend to have greater bargaining power and market concentration, allowing them more resources and opportunities for green transformation and pollutant reduction. Additionally, low competition fosters more collaboration among manufacturing enterprises, which helps establish environmental cooperation mechanisms within the industry and encourages joint participation in pollution reduction. Therefore, green financial reform can more effectively facilitate pollutant reduction in manufacturing enterprises with low industry competition. In contrast, for manufacturing enterprises facing high competition, there are relatively more competing firms, increasing the competition for access to green finance. Since these enterprises are profit-driven, they may prioritize short-term profits or neglect environmental governance and investment due to excessive price competition, resulting in less noticeable effects of green financial reform on emission mitigation.

From the perspective of carbon emissions, the inhibitory effect of green financial reform on carbon emissions is significant only in manufacturing enterprises with high industry competition intensity, while its effect on carbon emissions in manufacturing enterprises with low competition is not significant. This may be because these enterprises face greater market pressure and consumer demand. To maintain and enhance their competitiveness and attract consumers, manufacturing enterprises in highly competitive industries tend to adopt proactive environmental measures. They reduce carbon emissions through technological innovation and other means to establish their brand image and improve market competitiveness. At the same time, green finance institutions are more likely to favor manufacturing enterprises that excel in environmental governance, such as carbon emissions, when assessing loans and investments. This encourages manufacturing enterprises in highly competitive industries to increase their investments in green technologies and emission mitigation measures, ultimately achieving carbon reduction.

3.4.2. Heterogeneity of Industry Pollution Types

According to the 2012 Guidelines for the Classification of Listed Companies by Industry, this paper classifies the observed samples into heavily polluting and lightly polluting industries based on the industry codes of manufacturing enterprises. It explores the heterogeneity of industry pollution types regarding the impact of green financial reform on carbon reduction and emissions reduction in manufacturing enterprises. The regression results for each sample are shown in the table below.

According to

Table 7. Heterogeneity analysis II: heterogeneity of industry pollution types.

VAR	Pol				CO2
	High Pollution		Low Pollution		High Pollution		Low Pollution
Did	−0.0015 ***	−0.0020 ***	−0.0007	−0.0007	−0.0009 *	−0.0006 *	−0.0005	−0.0004
	(0.0000)	(0.0001)	(0.0005)	(0.0007)	−0.0006	−0.0003	(0.0005)	(0.0003)
Con	0.144 ***	0.145 ***	0.145 ***	0.145 ***	0.005 ***	0.033 ***	0.005 ***	0.047 ***
	(0.0006)	(0.0012)	(0.0000)	(0.0010)	(0.0006)	(0.0071)	(0.0000)	(0.0158)
CVs	NO	YES	NO	YES	NO	YES	NO	YES
Obs	6606	5797	10,016	8456	6472	6319	10165	9827
R2	0.953	0.951	0.951	0.949	0.174	0.187	0.162	0.185

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; *** and * indicate significance at the 1% and 10% confidence levels, respectively.

, the suppressive effect of green financial reform on carbon and pollutant emissions is significant only in manufacturing enterprises within heavily polluting industries, while it is not significant for those in lightly polluting industries. This may be because green finance guides funds toward environmental protection and low-carbon sectors, helping heavily polluting manufacturing enterprises with technological research and development and process upgrades, thereby reducing carbon and pollutant emissions. Specifically, on one hand, enterprises in heavily polluting industries typically face stricter environmental regulations and emission standards. The implementation of green financial reform can provide low-interest loans and other forms of green credit and bonds for environmental projects, which inadvertently raises the financing threshold and costs for these enterprises. This guiding role of green fund allocation encourages manufacturing enterprises to increase their environmental investments, thus reducing pollutant and carbon emissions. On the other hand, a key aspect of green financial reform is the risk assessment and investment decision-making for manufacturing projects. This compels enterprises to prioritize environmental governance and investments in environmental protection, optimize resource allocation and industrial structure, and gradually reduce their reliance on heavily polluting projects. This transition guides them toward cleaner energy production processes, ultimately lowering overall carbon and pollutant emissions. Therefore, the implementation of green financial reform can effectively drive carbon reduction and emissions reduction in heavily polluting industries, ultimately achieving a green and low-carbon transformation.

3.4.3. Heterogeneity of Corporate Ownership

To explore the heterogeneity of corporate ownership in the impact of green financial reform on carbon reduction and emissions reduction in manufacturing enterprises, this paper classifies the samples into state-owned and non-state-owned enterprises based on the nature of the actual controlling shareholders. The samples are then re-analyzed using the same model as in Model 1, with the regression results presented in

Table 8. Heterogeneity analysis III: heterogeneity of corporate ownership.

VAR	Pol				CO2
	State-Owned		Non-State-Owned		State-Owned		Non-State-Owned
Did	−0.0007	−0.0006	−0.0008 *	−0.0009 *	−0.0004	0.0002	−0.0007 ***	−0.0006 ***
	(0.0005)	(0.0010)	(0.0005)	(0.0005)	(0.0005)	(0.0007)	(0.0002)	(0.0002)
Con	0.145 ***	0.146 ***	0.144 ***	0.146 ***	0.005 ***	0.062 *	0.005 ***	0.0360 ***
	(0.0000)	(0.0013)	(0.0001)	(0.0014)	(0.0005)	(0.0359)	(0.0000)	(0.0034)
CVs	NO	YES	NO	YES	NO	YES	NO	YES
Obs	4430	4265	11,909	9953	4422	4268	12,031	11,840
R2	0.957	0.959	0.944	0.946	0.107	0.124	0.291	0.323

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; *** and * indicate significance at the 1% and 10% confidence levels, respectively.

. According to these results, regardless of whether individual characteristics at the enterprise level are considered, the Did estimated coefficient for non-state-owned enterprises is significantly negative. This indicates that the promoting effect of green financial reform on carbon reduction and emissions reduction in manufacturing enterprises is significant only for non-state-owned enterprises.

This is mainly because state-owned enterprises have an implicit connection with the government and bear political, economic, and social responsibilities. Compared to their political and economic responsibilities, state-owned enterprises have relatively weak environmental governance responsibilities and enjoy more relaxed financing channels, resulting in lower dependence on the special funds provided by green financial reform. Therefore, the impact of green financial reform on their carbon reduction and emissions reduction is not significant. In contrast, non-state-owned enterprises often face stricter financing constraints and more intense market competition, making them more sensitive to cost-effectiveness and market changes. The innovative practices of green financial reform have introduced new financial tools, such as green credit and green bonds, which provide non-state-owned enterprises with diversified financing channels and lower their financing costs. This also reduces the costs associated with participating in environmental governance and process upgrades, further promoting their carbon reduction and emissions reduction efforts. Additionally, compared to state-owned enterprises, non-state-owned enterprises are generally more open and advanced in terms of technological innovation and management models. They are better able to accept and apply the new concepts, technologies, and channels brought about by green financial reform and can promptly adjust their production methods and business strategies according to the requirements of green finance. This helps non-state-owned enterprises attract more green investments, creating a virtuous cycle that ultimately leads to greater breakthroughs and achievements in their carbon reduction and emissions reduction efforts.

3.4.4. Scale Heterogeneity

Generally, the scale of a company directly affects its carbon emissions. To investigate whether the obstructive effect of green financial reform on carbon emissions in manufacturing enterprises varies by company size, this paper divides the research sample into large-scale and small-scale enterprises based on the median of total assets at the end of the year and conducts a subsample regression analysis. The regression results are presented in the table below. According to

Table 9. Heterogeneity analysis IV: heterogeneity by firm size.

VAR	Pol				CO2
	Large-Scale		Small-Scale		Large-Scale		Small-Scale
Did	−0.0006	−0.0007	−0.0012 ***	−0.0015 ***	−0.0003	−0.0002	−0.0011 ***	−0.0009 *
	(0.0008)	(0.0009)	(0.0002)	(0.0003)	(0.0003)	(0.0003)	(0.0002)	(0.0005)
Con	0.145 ***	0.146 ***	0.144 ***	0.146 ***	0.005 ***	0.0205 *	0.0052 ***	0.0718 ***
	(0.0000)	(0.0013)	(0.0001)	(0.0014)	(0.0002)	(0.0108)	(0.0000)	(0.0055)
CVs	NO	YES	NO	YES	NO	YES	NO	YES
Obs	9377	7985	6982	6048	8461	8159	7890	7701
R2	0.947	0.949	0.955	0.958	0.200	0.204	0.418	0.441

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; *** and * indicate significance at the 1% and 10% confidence levels, respectively.

, regardless of whether control variables are included, green financial reform can drive carbon reduction and emissions reduction in small-scale manufacturing enterprises.

This may be because, unlike traditional financial institutions that tend to invest in large enterprises and mature projects, green finance expands financing channels for small-scale manufacturing enterprises by providing specialized tools such as green bonds. This offers policy guidance and incentives for small enterprises, encouraging them to improve their processes by adopting clean energy, upgrading production equipment, and ultimately reducing carbon emissions and pollutants through lower energy consumption. Additionally, when financial institutions assess green loans for manufacturing enterprises, they incorporate environmental risks and sustainability into their evaluation criteria. This means that companies must disclose their environmental information, which increases market transparency and reduces information asymmetry. As a result, small-scale manufacturing enterprises are more likely to prioritize environmental protection and lower carbon emissions to mitigate potential environmental risks and secure more green financing. Furthermore, green financial reform is accompanied by incentive policies such as government subsidies and tax benefits, as well as policy consulting services and technical support. These policy supports encourage manufacturing enterprises to engage in green technology research and development, improve the application conversion rate of innovative results, and promote low-carbon technologies. Ultimately, this effectively drives carbon reduction and emissions reduction in small-scale manufacturing enterprises, enhancing their sustainable development capabilities.

4. The Mechanism Through Which Green Financial Reform Influences Carbon Emissions in Manufacturing Enterprises

4.1. Mediation Channel Test

4.1.1. Mediation Effect Model

Referring to Baron & Kenny (1986) [47], this paper employs a stepwise regression mediation effect model to explore the channels through which green financial reform influences carbon emissions in manufacturing enterprises. Building on the baseline regression model 1, this section further constructs models 2 and 3, conducting regressions sequentially. The regression models are set up as follows:

$$M_{it}={\alpha }_0+{\alpha }_{1}Did+{\gamma Con}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(2)

$$Y_{it}={\gamma }_0+{\gamma }_1{M_{it}+\gamma }_{2}Did+{\gamma Con}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(3)

where $M_{it}$ represents the mediating variable, and the explanations for the other variables are the same as in model (1).

4.1.2. Variables and Data

This paper selects tax liabilities and ESG scores as moderating variables to explore how these factors influence the impact of green financial reform on carbon reduction and emission mitigation in manufacturing enterprises. ① Tax Burden: Referring to the study by Wang et al. [48], tax liabilities are chosen as the representative variable for corporate tax burden. The data for this variable primarily comes from the Guotai An database. ② ESG Scores: Based on the research by Guo et al. [49], this paper selects the ESG scores from Huazheng as the representative variable. The data for this indicator mainly comes from the Huatai official website and is matched according to the listing codes and years of manufacturing enterprises, ultimately yielding the data required for analysis.

4.1.3. Results of the Moderation Effect Test

The previous section confirmed the mediating roles of financing constraints and green technological innovation in the process of green financial reform driving carbon reduction and emission mitigation in manufacturing enterprises. However, it remains uncertain whether external environmental factors will influence the impact of green financial reform on carbon and pollutant emissions in these enterprises. Therefore, this section will test the roles of tax burden and ESG scores in this process based on research hypotheses 4 and 5, using a moderation effect model. The regression results are presented in

Table 10. Moderating test I: tax burden.

VAR	Pol	CO2
	(1)	(2)
Did	−0.0011 *	−0.0005 ***
	(0.0006)	(0.0002)
Tax	−0.0000	0.0000 **
	(0.0000)	(0.0000)
Did × Tax	0.0001 ***	0.0000 **
	(0.0000)	(0.0000)
Con	0.145 ***	0.0411 ***
	(0.0008)	(0.0101)
CVs	YES	YES
ObS	14,253	15,615
R2	0.950	0.182

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, **, and * indicate significance at the 1%, 5%, and 10% confidence levels, respectively.

and

Table 11. Moderating test II: tax burden.

VAR	Pol	CO2
	(1)	(2)
Did	−0.0014 ***	−0.0011 ***
	(0.0004)	(0.0003)
ESG	0.0000	0.0001
	(0.0000)	(0.0001)
Did × ESG	−0.0004 ***	−0.0002 **
	(0.0001)	(0.0001)
Con	0.145 ***	0.020 *
	(0.0009)	(0.0117)
CVs	YES	YES
ObS	14,175	14,860
R2	0.950	0.127

Note: (1) The values in parentheses represent robust standard errors clustered at the firm level; ***, **, and * indicate significance at the 1%, 5%, and 10% confidence levels, respectively.

below.

• Taxation

According to Table 10, regardless of whether considering pollutants or carbon emissions, the regression coefficients of the main effects remain significantly negative after incorporating the moderating variables and interaction terms. In contrast, the regression coefficients of the interaction terms are significantly positive. This indicates that taxation has a negative moderating effect in this context. Specifically, an increase in the tax burden significantly diminishes the impact of green financial reforms on the pollution and carbon emissions of manufacturing enterprises. Furthermore, tax incentive policies can enhance the effectiveness of green finance in reducing carbon emissions for these enterprises.

• ESG

According to Table 11, overall, both the regression coefficients of the main effects and the interaction terms are significantly positive, indicating that ESG performance plays a positive moderating role in this process. Specifically, ESG can enhance the carbon reduction and emission mitigation effects of green financial reforms.

5. Conclusions and Policy Recommendations

5.1. Conclusions

This paper examines the impact of green financial reforms on carbon emissions in manufacturing enterprises and its transmission mechanisms, grounded in sustainable development theory, corporate social responsibility theory, and the Porter hypothesis. Utilizing the Difference-in-Differences (DID) model, it assesses the net effect of green financial reforms on carbon emissions in manufacturing enterprises and explores the heterogeneity of this impact based on industry and enterprise characteristics. The study identifies green technological innovation, financing constraints, taxation, and ESG as transmission mechanisms derived from the internal and external environments of enterprises. Furthermore, it analyzes the specific effects of these selected variables in the driving process using mediation and moderation effect models. The main conclusions are as follows:

First, the parallel trend test indicates that the implementation of green financial reforms significantly impacts carbon and pollutant emissions in manufacturing enterprises. The regression results from the DID model reveal that these reforms have a negative impact on carbon and pollutant emissions. The results from placebo tests, PSM-DID, retaining core cities, and high-dimensional fixed effects all confirm the robustness of the baseline regression results. The analysis of heterogeneity in industry competition shows that the emission mitigation effect of green financial reforms is significant only in manufacturing enterprises with low industry competition, while the suppression effect on carbon emissions is significant only in those with high industry competition. The analysis of heterogeneity in pollution types indicates that the suppression effect of green financial reforms on carbon and pollutant emissions is significant only in high-pollution industries, whereas it is not significant in low-pollution manufacturing enterprises. Furthermore, the analysis of ownership heterogeneity reveals that the promotion effect of green financial reforms on carbon reduction and emission mitigation is significant only in non-state-owned enterprises. Lastly, the analysis of size heterogeneity demonstrates that these reforms can drive carbon reduction and emission mitigation only in small-scale manufacturing enterprises.

Second, the study finds that the implementation of green financial reforms facilitates green technological innovation in manufacturing enterprises, enabling carbon reduction and emission mitigation through this innovation. Additionally, these reforms help alleviate financing constraints for manufacturing enterprises, which also contributes to carbon reduction and emission mitigation. Tax burdens play a negative moderating role in this process, indicating that tax incentive policies can enhance the effectiveness of green finance in reducing carbon emissions in manufacturing enterprises. Conversely, ESG has a positive moderating effect, as it promotes the outcomes of carbon reduction and emission mitigation associated with green financial reforms.

5.2. Policy Recommendations

This paper provides important management insights for improving the green financial reform system and enhancing the effectiveness of carbon reduction and emission mitigation in manufacturing enterprises.

First, it is essential to systematically expand the pilot scope of green financial reforms and gradually implement them nationwide. Research indicates that these reforms contribute to carbon and emission reductions in manufacturing enterprises. Therefore, the pilot scope can be expanded in a structured manner to explore effective pathways for green finance, summarize successful reform experiences, and promote them across the country. Additionally, by innovating financial products and services, a comprehensive system of green finance standards, risk assessment, and regulatory mechanisms can be established to provide funding support and policy backing for environmental projects in manufacturing enterprises, thereby promoting the overall development of the green finance market. Furthermore, through policy guidance and incentive mechanisms related to green financial reforms, more financial institutions and investment organizations can be attracted to participate in green finance practices. This will drive the green transformation of the manufacturing industry and facilitate the upgrading and transformation of related industrial chains, ultimately enhancing the capacity for sustainable economic development.

Second, it is essential to establish mechanisms for technological innovation and patent protection to leverage the intermediary role of green technological innovation. Green technological innovation is the core driving force behind carbon reduction and emission reduction in the manufacturing industry. Green financial reforms can provide funding support and market guidance for these innovation activities, thereby promoting the application and transformation of innovative outcomes. To this end, implementing incentive mechanisms for technological innovation can create a supportive and dynamic environment for manufacturing enterprises, encouraging them to increase R&D investment and explore new fields and pathways in green technology. Patent protection is crucial for ensuring the effective utilization and transformation of innovative results by manufacturing enterprises. Since green technology research and development often requires substantial investments in R&D capital and labor, a lack of effective patent protection can leave innovative results vulnerable to imitation or theft by competitors. By establishing patent protection mechanisms, the ownership of innovative results can be clearly defined, effectively safeguarding the achievements of enterprises and enhancing their motivation to innovate. In summary, as green financial reforms progress, the establishment of mechanisms for technological innovation and patent protection will help accelerate the transformation of green technologies and promote their widespread application in manufacturing enterprises, thereby achieving the goals of carbon reduction and emission reduction.

Third, it is essential to implement various tax incentive policies to maximize the regulatory role of government taxation. Tax incentive policies are a crucial means of leveraging green financial reforms to drive carbon reduction and emission reduction in manufacturing enterprises. To this end, several tax incentive policies can be introduced, such as increasing the deductible ratio for R&D expenses related to low-carbon products to encourage greater R&D investment; allowing pre-tax deductions for investments made in energy-efficient and low-carbon equipment, thereby reducing equipment renewal costs; providing tax reductions or exemptions for companies that meet environmental protection standards to incentivize improvements in their environmental performance; establishing a green tax credit system that offers additional tax incentives to companies with strong environmental management practices; and enhancing cooperation between tax authorities and environmental protection and industrial departments to jointly supervise the environmental practices of manufacturing enterprises, ensuring the effective implementation of tax incentive policies.

6. Research Limitations and Future Directions

However, our study still has several limitations. First, although the models and methods we employed provide valuable insights into corporate environmental performance, their applicability is constrained by significant differences between countries and regions. Variations in political systems, economic structures, industrial foundations, and governance capabilities may limit the generalizability of our findings, particularly in comparisons between developing and developed countries.

Second, the successful implementation of complex environmental policy frameworks requires substantial administrative capacity and long-term policy continuity, which may not be easily achievable in many countries. This contextual disparity highlights the limitations of our research and indicates that any policy recommendations must be carefully tailored to the specific circumstances of each country or region.

Additionally, due to data availability constraints, this paper primarily focuses on the environmental performance of publicly listed companies in China, neglecting the significant role of non-listed enterprises. Non-listed companies also play an important role in digitalization and green transformation, and future research could consider including these firms in the analysis for a more comprehensive perspective.

Finally, future studies could expand the scope by incorporating companies from different countries and regions, enabling cross-national or contextual policy comparisons. This would contribute to a deeper understanding of the effectiveness and applicability of various environmental policies in different contexts.

In summary, while this study provides certain theoretical and empirical support, further exploration and overcoming these limitations in future research are necessary to enhance the comprehensiveness and applicability of the findings.