A Multidimensional Impact Study of Heterogeneous Market-Based Environmental Regulations on Carbon Emissions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Several questions and remarks regarding the article by Li et al. titled “A multidimensional impact study of heterogeneous market-based environmental regulations on carbon emissions”.

"Since China’s announcement... to peak carbon emissions by 2030... the country has been steadily advancing its carbon neutrality agenda." (Lines 33-35) Here it is worth noting that the government has set two objectives with two deadlines for achieving them: to reach "peak carbon emissions" by 2030 and to become "carbon neutral" by 2060.

This study lacks a thorough discussion. There is no comparison of the authors' findings to those of research on this issue conducted in China and other countries across the world.

The Introduction and Discussion sections must be considerably revised. First, it should be enhanced by analysing additional publications published during the previous five years (2020+). Second, these sections only rely on the results of Chinese scientists to an extent of 80%. However, this article was submitted to Sustainability, an international journal. This requires a comprehensive analysis of the topic must be presented, based from on Chinese and international scientific publications.

“The data are sourced from…. “ (Lines 324-326) Please provide citations for all databases used for analysis.

The article lacks data visualisation. There are no maps or figures in this article. For example, all parameters used in the study (subsection 3.2. Data Sources and Descriptive Statistics) might be shown as maps that highlight the statistical indicators’ variations between the 30 Chinese provinces. And so on.

Add research limitations to the Discussion section.

Author Response

Response Letter to Reviewers

 

Thank you very much for the constructive feedback provided by the editor in chief, associate editor and all reviewers for this paper. Based on feedback provided by the reviewer, significant revisions have been made to this paper. The revised title in the submitted manuscript is highlighted with a yellow background. The specific response is as follows: purple font is used to answer the reviewer's questions, and blue italic font is used for the revised original text.

 

 

Several questions and remarks regarding the article by Li et al. titled “A multidimensional impact study of heterogeneous market-based environmental regulations on carbon emissions”.

 

"Since China’s announcement... to peak carbon emissions by 2030... the country has been steadily advancing its carbon neutrality agenda." (Lines 33-35) Here it is worth noting that the government has set two objectives with two deadlines for achieving them: to reach "peak carbon emissions" by 2030 and to become "carbon neutral" by 2060.

This study lacks a thorough discussion. There is no comparison of the authors' findings to those of research on this issue conducted in China and other countries across the world.

R: Your feedback is of great help in improving the quality of this article. In response to the opinions you raised, we have added literature describing this part and conducted comparative analyses among countries.The specific modifications are as follows:

Within the current global context of escalating climate concerns, governments worldwide are actively engaged in reducing carbon emissions and advancing carbon neutrality objectives[1]. As the largest developing country and carbon emitter, China explicitly announced its dual carbon goals—peaking carbon emissions by 2030 and achieving carbon neutrality by 2060—at the 75th United Nations General Assembly in 2020. This commitment has significantly accelerated the development and refinement of its domestic environmental regulation system. Unlike the European Union’s market mechanism-led approach or the United States’ emphasis on technology-driven solutions and federal-state collaboration, China’s policy framework prioritizes top-down target decomposition and coordination with industrial policies. While China has taken a global lead in areas such as renewable energy investment and electric vehicle adoption, there remains room for improvement in terms of institutional flexibility and incentives for corporate autonomous innovation—especially compared to Asian peers like South Korea and Japan, where related efforts began earlier [2-5]. As a major economy still undergoing industrialization and urbanization, China’s carbon reduction pathway is characterized by high total emissions, tight timelines, and pronounced structural challenges. Both central and local governments exert substantial influence on national carbon emission governance through the enactment and revision of environmental laws and regulations, market guidance, and public awareness campaigns.

 

The Introduction and Discussion sections must be considerably revised. First, it should be enhanced by analysing additional publications published during the previous five years (2020+). Second, these sections only rely on the results of Chinese scientists to an extent of 80%. However, this article was submitted to Sustainability, an international journal. This requires a comprehensive analysis of the topic must be presented, based from on Chinese and international scientific publications.

R: Your opinion is very correct, and we have added some research literature on environmental regulations by international scholars in the past five years.

 

“The data are sourced from…. “ (Lines 324-326) Please provide citations for all databases used for analysis.

R: Your opinion is very constructive，and we have provided citations for all databases used for analysis.

.

 

The article lacks data visualisation. There are no maps or figures in this article. For example, all parameters used in the study (subsection 3.2. Data Sources and Descriptive Statistics) might be shown as maps that highlight the statistical indicators’ variations between the 30 Chinese provinces. And so on.

R: Your feedback is very helpful in improving the quality of this article. We added vector maps of the core explanatory variable and the explained variable after Section 3.2.The specific modifications are as follows:

      

      

5     

 

Add research limitations to the Discussion section.

R: Your feedback is very helpful in improving the quality of this article. Based on your feedback, we have added a section on limitations and future research directions in the conclusion section.The specific modifications are as follows:

6.2 Research Limitations and Future Prospects

Although this study has made certain progress in theoretical and empirical analysis, several limitations remain. Future research could be further deepened in the following aspects:

(1) Data granularity. This study is based on provincial-level panel data and does not delve into enterprise or industry-level analysis. Future research could integrate micro-level enterprise data to further reveal the differential impact mechanisms of environmental regulations on carbon emissions behavior across heterogeneous firms.

(2) Temporal coverage of the sample. The sample in this study concludes in 2023 and does not fully encapsulate the most recent developments following the comprehensive implementation of the "Dual Carbon" policy. Future studies could track longer-term data to evaluate policy continuity and dynamic adjustment effects.

(3) Lack of international comparison. This study focuses on Chinese provincial data and lacks comparative analysis with other countries or regions. As carbon emission markets become increasingly standardized and unified globally, cross-national comparative research could be conducted to explore the similarities, differences, and applicability conditions of market-based environmental regulations under different institutional contexts.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This study focuses on the heterogeneous characteristics of market-based environmental regulations, categorizing them into investment incentive-oriented and tax supervision-oriented types. The findings reveal that heterogeneous market-based environmental regulations significantly inhibit carbon emissions, with both exhibiting nonlinear relationships. Following are my comments and suggestions:

• The abstract is well written, but it is lengthy. It is recommended to revise it in a manner to emphasize the novelty of distinguishing between investment incentive-oriented and tax supervision-oriented regulations.
• In my opinion, the introduction and literature review should be merged. It is also suggested that literature should be discussed more critically. At present, it reads like a summary.
• Although the methodology is thorough, a clearer explanation of the rationale behind the use of lagged instruments and nonlinear functional forms is needed.
• Some symbols appear later in the tables without being clearly introduced in the model specification. It is recommended to add a notation table.
• Control variables should be better justified in the model.
• The nonlinear findings are interesting but require robustness tests.
• Endogeneity is partly handled using lagged IVs, but dynamic panel methods might be more appropriate.
• The results section is thorough but a little long. It is suggested to add figures to better illustrate comparative findings.
• Conclusions should include limitations and highlight directions for future research.

Author Response

Response Letter to Reviewers

 

Thank you very much for the constructive feedback provided by the editor in chief, associate editor and all reviewers for this paper. Based on feedback provided by the reviewer, significant revisions have been made to this paper. The revised title in the submitted manuscript is highlighted with a yellow background. The specific response is as follows: purple font is used to answer the reviewer's questions, and blue italic font is used for the revised original text.

 

This study focuses on the heterogeneous characteristics of market-based environmental regulations, categorizing them into investment incentive-oriented and tax supervision-oriented types. The findings reveal that heterogeneous market-based environmental regulations significantly inhibit carbon emissions, with both exhibiting nonlinear relationships. Following are my comments and suggestions:

 

The abstract is well written, but it is lengthy. It is recommended to revise it in a manner to emphasize the novelty of distinguishing between investment incentive-oriented and tax supervision-oriented regulations.

R: Your feedback is of great help in improving the quality of this article.we have revised the abstract, highlighting the novelty of investment incentive and tax supervision regulations.The specific modifications are as follows:

Within the context of global climate change and China’s commitment to the "Dual Carbon" goals (carbon peak and carbon neutrality), this study proposes a novel taxonomy of market-based environmental regulations, dividing them into investment-driven and tax-based supervisory mechanisms. Using panel data from 30 Chinese provinces between 2010 and 2023, we empirically investigate their differential effects on carbon emissions. Results indicate that both regulatory approaches significantly curb carbon emissions, each exhibiting distinct nonlinear patterns: an inverted-U curve for investment-oriented measures and a U-shaped trajectory for tax-oriented policies, implying that excessively stringent tax supervision may lead to a rebound in emissions due to effects such as the "resource curse" and "innovation crowding-out." Industrial structure transformation functions as a common mediating channel, while green innovation efficiency exerts a distinct moderating influence. Both policy types demonstrate adverse spatial spillover effects, with no support found for the "pollution haven" or "race to the bottom" hypotheses. This study offers new empirical insights into how environmental regulations facilitate green and low-carbon transition through market mechanisms, providing valuable implications for designing ecological policy systems that harmonize emission reduction efficiency with sustainability in China and other emerging economies.

 

In my opinion, the introduction and literature review should be merged. It is also suggested that literature should be discussed more critically. At present, it reads like a summary.

R: Your opinion is very constructive.However, considering the length of the paper and the clarity of the problem statement comprehensively, we did not combine the introduction and the literature review. But we believe that critical discussion is very necessary. Therefore, we added some comparative studies in the literature review and made some targeted comments on them, making this literature review more logical.

Although the methodology is thorough, a clearer explanation of the rationale behind the use of lagged instruments and nonlinear functional forms is needed.

R: Your feedback is very helpful in improving the quality of this article. We have taken your opinions into consideration and chosen to use the GMM method for endogeneity testing. We have also reinterpreted the nonlinear function to make its expression clearer.The specific modifications are as follows:

Regarding the "inverted U-shaped" relationship observed in investment incentive-oriented regulations, the mechanism lies in the changing marginal effects of regulatory intensity at different stages. In the initial phase of low intensity, policies such as environmental investment subsidies significantly reduce the marginal cost of green technological innovation for enterprises, effectively stimulating their innovative vitality. The resulting "innovation compensation" effect dominates the reduction in carbon emissions. However, when the incentive intensity exceeds a certain threshold, it may trigger resource misallocation in the market: on one hand, firms with low innovation efficiency may engage in "strategic innovation" or even expand high-carbon production capacity to obtain subsidies, leading to a "green paradox"; on the other hand, highly efficient innovators may allocate excess subsidy funds to expanding production scale rather than deepening innovation, where the carbon increment from output expansion could offset or even exceed the carbon reduction from technological progress, thus activating the "Jevons paradox." Consequently, excessively high incentive intensity may instead undermine emission reduction efficiency.

Regarding the "U-shaped" relationship observed in tax supervision-oriented regulations, this finding appears inconsistent with previous studies that reported either U-shaped patterns or promoting effects. At moderate intensity levels, policies such as environmental taxes and pollution discharge fees effectively force enterprises to adopt short-term emission reduction measures—including end-of-pipe treatment, energy efficiency improvements, or fuel substitution—by increasing the marginal cost of carbon emissions. During this stage, the "cost constraint" effect dominates, leading to a continuous decline in carbon emissions.

However, when regulatory intensity exceeds a certain threshold, excessively high compliance costs crowd out productive investments and innovation resources, resulting in an "innovation crowding-out effect." Faced with substantial cost pressures, enterprises rationally shift their strategies away from long-term green technology innovation toward paying fines or taxes to maintain existing high-carbon production, or they reduce R&D budgets and adhere to conventional high-carbon technological pathways. When firms are compelled to allocate significant resources to compliance expenditures due to pollution discharge fees, these non-productive investments divert funds that could otherwise be used for low-carbon technology R&D or process upgrades, creating a "resource curse of environmental policy." Ultimately, this leads to stagnation in technological advancement and may even trigger a rebound in carbon emissions.

 

Some symbols appear later in the tables without being clearly introduced in the model specification. It is recommended to add a notation table.

R: Your feedback is very helpful in improving the quality of this article.We have provided more detailed explanations of some variables in the table to facilitate readers' understanding of the model.We have provided more detailed explanations of some variables in the table to facilitate readers' understanding of the model. For example:

Among them, GE*MER_I and GE*MER_R represent the interaction terms between the core explanatory variable and the moderating variable.(In Tbale7)

 

Control variables should be better justified in the model.

R: Your opinion is very correct, and we have provided a more detailed explanation of the control variables in the paper.The specific modifications are as follows:

(1) Production Scale: Carbon emissions are inherently a byproduct of economic activities.   Following the scale effect theory, the expansion of economic scale is typically accompanied by increased energy consumption and carbon emissions.   To control for the fundamental impact of the overall scale of economic activity on carbon emissions at the provincial level, this study selects provincial employment numbers as a proxy variable.   Labor, as a core input factor in the production function, directly determines the level of economic activity and the corresponding total energy demand.   Differences in provincial employment numbers reflect the spatial distribution characteristics of economic activity density and serve as an important structural factor influencing regional total carbon emissions.

(2) Infrastructure Level: Infrastructure construction constitutes a vital component of capital stock, and its scale and structure profoundly shape a region's energy consumption patterns and carbon emission pathways through the "lock-in effect."  Large-scale infrastructure development, particularly the expansion of energy-intensive industries, directly drives up contemporaneous carbon emissions.  This study selects the proportion of provincial secondary industry value-added to GDP as a proxy for infrastructure level, primarily based on the following considerations: the secondary industry serves as the main carrier of infrastructure and the primary sector of energy consumption.  Its scale largely reflects a region's industrialization-oriented infrastructure development level, which aligns with China's current developmental stage.  This indicator effectively captures the rigid demand for energy consumption and helps control for carbon emission disparities arising from differences in developmental stages.

(3) Energy Consumption Level: Final energy consumption, particularly fossil fuel combustion, constitutes the most direct source of carbon dioxide emissions.  Controlling for the total scale of energy consumption is crucial for accurately identifying the emission reduction effects of environmental regulations.  This study selects electricity consumption per hour as a proxy variable.  This indicator directly measures the scale of final energy inputs required for the operation of the economic system.  Given that electricity accounts for a significant and continuously growing share of China's energy consumption, it effectively represents the overall energy consumption level. 

(4) Birth Rate: Demographic factors represent one of the fundamental long-term drivers influencing carbon emissions.  This study introduces the birth rate to control for the long-term environmental impacts of demographic structure changes.  The birth rate not only affects long-term total energy demand by altering the scale of future consumer populations (population scale effect) but also indirectly shapes long-term carbon emission trajectories by modifying current population age structures (e.g., youth dependency ratio), which influence societal consumption-saving patterns, labor supply, and energy consumption preferences.  Controlling for this variable helps distinguish between the effects of environmental regulations and potential demographic transition effects.

 

The nonlinear findings are interesting but require robustness tests.

R: Your opinion is very constructive，we added nonlinear robustness tests in the paper.The specific modifications are as follows:

This study assesses the robustness of the model by incorporating additional control variables. The baseline regression results of the model are reported in Columns (1) and (2) of Table 3, indicating that market-based environmental regulations curb carbon emissions, which is consistent with the OLS regression findings, thereby further substantiating the model's robustness. Furthermore, robustness tests were performed to examine the nonlinear relationship between environmental regulations and carbon emissions. As illustrated in Columns (3) and (4) of Table 3, the results are largely aligned with the OLS results, reinforcing the model's stability.

Table 3. Robustness Test Results.

	(1)	(2)	(3)	(4)
MER_I	-3.874***		2.070
	(1.110)		(2.158)
MER_R		-0.004*		-0.016***
		(0.002)		(0.004)
MER_I2			-265.509***
			(83.030)
MER_R2				0.001***
				(0.001)
Employed	0.051***	0.056***	0.053***	0.062***
	(0.018)	(0.018)	(0.018)	(0.018)
Iva	-0.008***	-0.008***	-0.008***	-0.009***
	(0.002)	(0.002)	(0.002)	(0.002)
Elec	0.062***	0.063***	0.061***	0.063***
	(0.010)	(0.010)	(0.010)	(0.010)
bornr	0.146	0.228	0.090	0.239
	(0.267)	(0.272)	(0.265)	(0.269)
consu	-0.109***	-0.108***	-0.113***	-0.102***
	(0.199)	(0.021)	(0.197)	(0.021)
GDP	0.106***	0.103***	0.110***	0.097***
	(0.022)	(0.103)	(0.022)	(0.022)
_cons	17.188***	17.205***	17.158***	17.266***

Standard errors in parentheses；* p<0.1, ** p<0.05, *** p<0.01.

 

Endogeneity is partly handled using lagged IVs, but dynamic panel methods might be more appropriate.

R: Your feedback is very helpful in improving the quality of this article.Based on your suggestion, we use GMM for endogeneity testing.The specific modifications are as follows:

 

Although this investigation controlled for potential confounding variables during model specification and strengthened the reliability of the conclusions through a series of robustness tests, concerns persist regarding potential reverse causality between the intensity of market-based environmental regulations and carbon emission intensity, which could compromise the validity of the findings. To tackle this endogeneity issue, this paper applies a Generalized Method of Moments (GMM) model. The specific outcomes are presented in Table 4.

Table 4. Endogeneity Tests.

	(1)	(3)
CE(L1)	0.528***	0.144***
	(0.029)	(0.018)
MER_I	-2.937***
	(0.373)
MER_R		-0.006***
		(0.001)
Employed	0.049	-0.025***
	(0.007)	(0.028)
Iva	-0.024***	-0.005***
	(0.004)	(0.002)
Elec	0.166***	0.141***
	(0.019)	(0.015)
bornr	-0.782***	-0.106
	(0.095)	(0.111)
AR(2)	0.73	1.54
Hansen test	29.11	28.93
obs	420	420
ID	Yes	Yes
YEAR	Yes	Yes

Standard errors in parentheses；* p<0.1, ** p<0.05, *** p<0.01.

The GMM (Generalized Method of Moments) method is particularly effective in verifying and addressing endogeneity issues, as it minimizes the deviation between sample moments and population moments by constructing moment conditions, and uses instrumental variables to isolate the correlation between explanatory variables and perturbation terms, thereby obtaining consistent estimates. Specifically, GMM assumes the existence of an exogenous instrumental variable Z that satisfies E [Z 'ε]=0, which can handle omitted variables, simultaneity, or dynamic endogeneity (such as lagged dependent variables in panel data), especially in dynamic panel models where internal lag tools automatically generate moments to improve estimation efficiency. When verifying endogeneity, the Hausman test can be used to compare OLS and GMM estimates , and internal diagnostics such as AR (1)/AR (2)  and Hansen/Sargan can be used to indirectly confirm whether endogeneity has been alleviated. If the diagnosis is successful, it indicates that GMM has successfully corrected the bias. This method is more robust than Simple IV and is suitable for heteroscedastic or small sample scenarios. It is widely used for causal identification of endogeneity problems in empirical economic research. Therefore, this article added the GMM method for endogeneity testing, as shown in Table 12 (GMM). In the dynamic panel GMM estimation, the AR (2) test statistic is -1.480 and not significant, which supports the null hypothesis. This indicates that the exogeneity of lagged second-order and above variables as instrumental variables holds and satisfies the basic assumption of the Arellano Bond model. At the same time, the Hansen test statistic of 11.42 is not significant, which cannot reject the null hypothesis that all instrumental variables are valid. This indicates that the selected instrumental variables overall meet the exogeneity requirements, and the model estimates are consistent and have no significant bias. This result jointly verifies the robustness of GMM setting and avoids potential endogeneity bias.

 

The results section is thorough but a little long. It is suggested to add figures to better illustrate comparative findings.

Conclusions should include limitations and highlight directions for future research.

R: Your opinion is very constructive，we streamlined the conclusion section of the paper to make it seem less lengthy, and added the shortcomings of the research as well as the prospects for future studies.The specific modifications are as follows:

6. Conclusion

This study investigates the impact of heterogeneous market-based environmental regulations—categorized as investment incentive-oriented and tax supervision-oriented—on carbon emissions using panel data from 30 Chinese provinces (2010–2023) analyzed via OLS and spatial effect models. The results indicate that both types generally suppress emissions, albeit through distinct nonlinear pathways: an inverted U-shaped relationship for investment-oriented regulation, attributed to the "green paradox" from resource misallocation, and a U-shaped curve for tax-oriented regulation, due to innovation crowding-out effects. Industrial structure advancement serves as a significant mediator—exhibiting complete mediation for tax-oriented measures and partial mediation for investment-oriented ones, reflecting the former’s structural rigidity. Moreover, green innovation efficiency moderates these relationships, with Jevons Paradox providing explanatory insight into their nonlinearity. Importantly, both regulation types demonstrate negative spatial spillover effects, countering the "race to the bottom" hypothesis and underscoring the efficacy of market-based instruments within China’s unified market framework.

6.1 Policy Recommendations

Building upon the above research conclusions, the following recommendations are proposed:

(1) Focus on the emission reduction effects of heterogeneous market-based environmental regulations and improve the toolkit of market-oriented environmental regulatory policies. This study finds that while both types of heterogeneous market-based environmental regulations can effectively reduce carbon emissions, nonlinear relationships exist between these regulations and carbon emissions due to institutional imperfections that may lead to outcomes contrary to expectations. Therefore, authorities should strengthen the service function of policies toward market mechanisms, enhance the green financial system, unify credit evaluation standards, innovate financial products and services. By assembling a comprehensive policy toolkit, the decisive role of market mechanisms in resource allocation can be fully harnessed.

(2) Refine the "Buffer-Compensation-Orientation" logical framework of environmental regulations to leverage the synergistic effects of industrial transformation and green emission reduction. First, implement a tiered carbon pricing mechanism to provide a transition window for high-carbon enterprises, alleviating the impact of sunk costs caused by asset specificity and avoiding the "pay-to-pollute rather than transform" lock-in trap. Simultaneously, introduce innovation-oriented supplementary policies, such as R&D tax credits and industrialization subsidies for disruptive low-carbon technologies, to correct the distortion of technological direction by purely price-based tools. This will incentivize enterprises to shift resources from passive compliance to active innovation, ensuring both the efficiency of industrial structure upgrading in emission reduction and fostering endogenous momentum for long-term deep decarbonization.

(3) Strengthen the green innovation protection mechanism to ensure innovation efficiency. Research shows that the efficiency of green innovation has heterogeneous effects on different environmental regulations. Therefore, it is suggested to improve the market innovation protection mechanism, ensure the allocation efficiency of innovation resources, supervise the flow of innovation funds, prevent the "greenwashing" behavior in the market, and implement differentiated policies for enterprises with different innovation capabilities.

(4) Accelerate the construction of a unified market to leverage market advantages. This study demonstrates that market-based environmental regulations have positive spatial spillover effects on carbon reduction in neighboring regions, as market entities in a unified market with free factor mobility are more inclined to choose innovation and upgrading rather than locational arbitrage. Therefore, it is recommended to expand the coverage of carbon markets, improve price formation mechanisms, diversify trading products, and accelerate the refinement of the carbon emission trading system to ensure the uniformity and consistency of market policies.

6.2 Research Limitations and Future Prospects

Although this study has made certain progress in theoretical and empirical analysis, several limitations remain. Future research could be further deepened in the following aspects:

(1) Data granularity. This study is based on provincial-level panel data and does not delve into enterprise or industry-level analysis. Future research could integrate micro-level enterprise data to further reveal the differential impact mechanisms of environmental regulations on carbon emissions behavior across heterogeneous firms.

(2) Temporal coverage of the sample. The sample in this study concludes in 2023 and does not fully encapsulate the most recent developments following the comprehensive implementation of the "Dual Carbon" policy. Future studies could track longer-term data to evaluate policy continuity and dynamic adjustment effects.

(3) Lack of international comparison. This study focuses on Chinese provincial data and lacks comparative analysis with other countries or regions. As carbon emission markets become increasingly standardized and unified globally, cross-national comparative research could be conducted to explore the similarities, differences, and applicability conditions of market-based environmental regulations under different institutional contexts.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The research material is presented logically and is well structured. The criteria selected for the developed models are adequate. I understand that the authors focus on studying green innovations and technological transformations for China. However, in my opinion, the literature review lacks a comparison with the approaches, control mechanisms, and policies for reducing emissions that are applied in the EU or the US. This would allow for a more complete assessment of the situation with regard to the regulation and control of carbon dioxide emissions.

As a side note, I would suggest that the literature review and information on hypotheses be better structured and presented in tabular form to improve readability. In section 3.2.1, the formula number should be added.

 

Author Response

Response Letter to Reviewers

 

Thank you very much for the constructive feedback provided by the editor in chief, associate editor and all reviewers for this paper. Based on feedback provided by the reviewer, significant revisions have been made to this paper. The revised title in the submitted manuscript is highlighted with a yellow background. The specific response is as follows: purple font is used to answer the reviewer's questions, and blue italic font is used for the revised original text.

 

The research material is presented logically and is well structured. The criteria selected for the developed models are adequate. I understand that the authors focus on studying green innovations and technological transformations for China. However, in my opinion, the literature review lacks a comparison with the approaches, control mechanisms, and policies for reducing emissions that are applied in the EU or the US. This would allow for a more complete assessment of the situation with regard to the regulation and control of carbon dioxide emissions.

R: Your feedback is of great help in improving the quality of this article.In the introduction, literature review and hypothesis presentation sections of our article, comparisons of environmental policies and emission reduction effects between China and other regions have been added.

 

As a side note, I would suggest that the literature review and information on hypotheses be better structured and presented in tabular form to improve readability. In section 3.2.1, the formula number should be added.

R: Your feedback is very helpful in improving the quality of this article. According to the suggestions you put forward, we reorganized and streamlined the literature review. We organized the table of hypotheses in the appendix at the end of the article for easy reading and added numbers to the formula of 3.2.1.The specific modifications are as follows:

Hypothesis

Hypothesis 1	Market-based environmental regulations inhibit carbon emissions, and a nonlinear relationship may exist between market-based environmental regulations and carbon emissions.
Hypothesis 2	Market-based environmental regulations modulate the carbon emission effect through industrial structure upgrading.
Hypothesis 3(a)	Investment incentive-oriented market environmental regulation exerts a negative moderating effect on carbon emissions through the influence of green innovation efficiency.
Hypothesis 3(b)	Tax supervision-oriented market environmental regulation exerts a positive moderating effect on carbon emissions through the influence of green innovation efficiency.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

All the issues I cared about were addressed by the authors. The manuscript has been carefully revised.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript has been improved.