Review Reports - From Control to Incentive: How Market-Driven Environmental Regulation Shapes ESG Performance in Manufacturing Industries

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper examines the impact of Environmental Protection Tax (EPT) on the ESG performance of manufacturing firms, using a quasi-natural experiment approach. The topic is timely and relevant, particularly given the growing emphasis on market-driven environmental regulation and corporate sustainability. The empirical analysis is robust, and the findings contribute meaningfully to the literature on ESG performance and policy effectiveness. However, there are several areas where the manuscript could be strengthened to improve its theoretical grounding, contextualisation, and overall impact. Below are my specific comments and suggestions.

The introduction and literature review are well-structured but would benefit from a more engaged discussion with recent, high-impact studies on sustainability governance and policy. Currently, the theoretical framing feels somewhat narrow, missing opportunities to link the findings to broader debates in environmental regulation and corporate sustainability.
Expand the literature review to include more recent, influential work on market-based environmental policies and ESG performance. For example:
(1) A study like [DOI: 10.1016/j.erss.2025.104347] could help contextualise the environmental regulation and sustainable policy pathways.
(2) A sustainable governance-focused paper such as [DOI: 10.1016/j.jenvman.2024.123765] could strengthen the discussion on governance perspectives.

Clarify the novelty of this study compared to prior work on ESG determinants. Are there conflicting findings in the literature that this paper resolves? How does this study advance existing debates?

Hypothesis 1 is well-justified, but the link between financing constraints (later discussed as a mechanism) and the main hypothesis could be clearer upfront.

Some terms (e.g., market-driven environmental regulation) are used interchangeably with "market-based regulation". Consistency would improve readability.

The paper finds that the EPT’s impact varies by firm ownership and region. However, the discussion could delve deeper into why these differences exist. Are there institutional or market factors at play?

How do these findings compare with similar policies in other countries? Does the EPT’s design offer lessons for other emerging economies?

The transition between sections (e.g., from literature review to hypotheses) could be smoother. Some logical connections are assumed rather than explicitly stated.

The conclusion is somewhat brief. It could better highlight the study’s key contributions and policy recommendations.

Overall , this is a strong paper with valuable empirical findings, but it would benefit from deeper theoretical engagement and a more expansive discussion of its contributions. With moderate revisions, particularly in framing the study within broader scholarly debates, it could be suitable for publication in this journal.

Author Response

Author's Reply to the Review Report (Reviewer 1)

Response:

We sincerely appreciate the reviewer’s careful evaluation and professional guidance. We are grateful for your recognition of the study’s research design, which employs a quasi-natural experiment to examine the impact of the Environmental Protection Tax (EPT) on the ESG performance of manufacturing enterprises, as well as for acknowledging the practical relevance and timeliness of this topic under the current trend of strengthening market-driven environmental regulation and corporate sustainability.

At the same time, your comments regarding the need to further deepen the theoretical foundation, enhance the contextualization of the research setting, and improve the overall academic expression of the manuscript are highly insightful and constructive. These suggestions provide valuable direction for refining the research framework, strengthening theoretical contributions, and improving logical coherence in the manuscript. In response, we have revised and optimized the connection between the literature review and the theoretical hypothesis development, further clarified the institutional context of the EPT policy, and enhanced the clarity and consistency of the overall narrative.

We sincerely appreciate the reviewer’s thoughtful and rigorous comments, which are of great importance in improving the academic rigor, clarity, and contribution of this study. We will continue to carefully refine the manuscript in accordance with the suggestions, with the aim of meeting the publication standards of the journal. Thank you once again for your time and valuable guidance.

Question 1.1

Expand the literature review to include more recent, influential work on market-based environmental policies and ESG performance. For example:

(1) A study like [DOI: 10.1016/j.erss.2025.104347] could help contextualise the environmental regulation and sustainable policy pathways.

(2) A sustainable governance-focused paper such as [DOI: 10.1016/j.jenvman.2024.123765] could strengthen the discussion on governance perspectives.

Response:

We sincerely thank the reviewer for this valuable suggestion. Following your guidance, we have expanded the literature review to deepen the theoretical framing and better situate our study within the broader discussions on sustainability governance and market-based environmental regulation. Specifically:

We added the sustainability governance study (DOI: 10.1016/j.jenvman.123765) to strengthen the governance perspective and highlight the multi-actor coordination mechanisms in environmental policy implementation. This addition clarifies how collaborative governance and institutional evolution relate to the effects of market-based environmental regulation on ESG performance.
We incorporated additional literature on market-driven environmental policies and sustainable transformation, including work discussing how market-based regulatory frameworks create dynamic incentives for green upgrading. These references help contextualize the Environmental Protection Tax (EPT) within the broader domain of regulatory innovation and sustainable industrial development.
The relevant discussions were integrated into the literature review section (Section 2), and we also revised the introduction to improve the conceptual link between ESG enhancement, environmental governance evolution, and policy instrument design.

We believe these revisions broaden the theoretical foundation of the paper and more clearly articulate the contribution of our work to current academic debates.

We truly appreciate the reviewer’s insightful comment, which has substantially improved the clarity and academic rigor of the manuscript.

Question 1.2

Clarify the novelty of this study compared to prior work on ESG determinants. Are there conflicting findings in the literature that this paper resolves? How does this study advance existing debates?

Response:

Thank you very much for your constructive comment regarding the need to clarify the novelty of this study and its contribution to existing debates on the determinants of ESG performance. We appreciate this insightful suggestion. In response, we have substantially revised the Introduction and Literature Review sections to more clearly articulate the theoretical positioning and contribution of our work.

Specifically, we now highlight that although ESG performance has received increasing academic attention, prior research has not systematically examined how market-based environmental regulation, particularly the Environmental Protection Tax (EPT), affects the ESG performance of manufacturing firms. Moreover, we address the fact that existing literature provides conflicting conclusions regarding whether market-oriented environmental policies promote corporate sustainability—some studies emphasize their role in incentivizing green transformation, whereas others suggest that regulation may increase compliance costs and crowd out innovation-related resources.

To resolve these inconsistencies, our revision clarifies the three main contributions of this study:

(1) Causal identification: By treating the 2018 EPT implementation as a quasi-natural experiment and employing a multi-period DID model, we provide rigorous causal evidence linking market-based environmental regulation to ESG performance, contributing new empirical insights beyond prior correlational studies.

(2) Mechanism clarification: We identify and empirically validate two transmission mechanisms—alleviation of financing constraints and stimulation of green technological innovation—which helps reconcile theoretical disagreements on whether market-driven environmental regulation promotes or suppresses sustainable investment.

(3) Boundary conditions and governance implications: By examining heterogeneity across ownership structure and audit quality, we show that policy effects vary systematically with governance and resource environments, thereby advancing the literature by identifying the contextual conditions under which regulatory tools are more effective.

These revisions are now incorporated in the manuscript (see pages 3–4), and we believe they strengthen the theoretical grounding and clarify how the present study advances existing scholarly debates.

Thank you again for this valuable suggestion.

Question 1.3

Hypothesis 1 is well-justified, but the link between financing constraints (later discussed as a mechanism) and the main hypothesis could be clearer upfront.

Response:

Thank you for your valuable suggestion. In response to your comment that the theoretical connection between Hypothesis 1 and the subsequent mediation analysis of “financing constraints” should be established earlier and more clearly, we have revised the manuscript accordingly. Specifically, we have added a theoretical discussion prior to the statement of Hypothesis 1, clarifying that the implementation of the Environmental Protection Tax can strengthen firms’ environmental compliance and information transparency, thereby sending a positive “green credibility” signal to external investors. This improves investor confidence, alleviates firms’ financing constraints, and enhances their capacity for sustained investments in environmental governance, social responsibility practices, and governance improvement. This addition creates a coherent logical pathway linking EPT to ESG performance through the easing of financing constraints.

In the revised manuscript (Page 5), we inserted the following text: The implementation of the Environmental Protection Tax encourages firms to enhance environmental compliance and disclosure, which signals stronger environmental responsibility to capital markets. This helps reduce external investors’ perceived risk and alleviates financing constraints, thereby improving the availability of financial resources. The improved financing environment, in turn, supports sustained investment in green technology upgrading, social responsibility initiatives, and governance system enhancement, forming a ‘regulation–resource–sustainability investment’ transmission mechanism that promotes ESG performance

We have also added a transition statement when presenting Hypothesis 1 to explicitly indicate that financing constraints will be examined as an important mediating channel in the empirical analysis, thus ensuring logical consistency between the theoretical hypotheses and subsequent mechanism testing.

We sincerely appreciate your insightful comment, which has significantly strengthened the theoretical coherence and clarity of the manuscript.

Question 1.4

Some terms (e.g., market-driven environmental regulation) are used interchangeably with "market-driven environmental regulation". Consistency would improve readability.

Response:

Thank you for your helpful comment regarding terminology consistency. We agree that the interchangeable use of the terms “market-driven environmental regulation” and “market-based environmental regulation” may reduce textual coherence. In the revision, we have carefully reviewed the entire manuscript and standardized the terminology, uniformly adopting the term “market-driven environmental regulation” throughout the paper to ensure conceptual clarity and improve overall readability. We sincerely appreciate the reviewer’s suggestion, which has contributed to enhancing the precision and consistency of the manuscript.

Question 1.5

Response:

Thank you for this thoughtful suggestion. We have substantially expanded the discussion to address the institutional and market mechanisms underlying the heterogeneous effects. Specifically, we added a dedicated subsection—“5.2.4 Discussion of Heterogeneity Results” (revised manuscript, pp. 20)—which now provides a structured explanation along two dimensions:

1.Ownership-based heterogeneity (institutional mandates vs. market incentives). We explain that SOEs face relatively “hard” policy mandates and rigid expectations on environmental and social responsibilities, which limit the marginal improvements attributable to the EPT. By contrast, non-SOEs operate under stronger market discipline and external monitoring; the EPT increases the economic cost of pollution and strengthens oversight, thereby encouraging non-SOEs to improve ESG in order to reduce compliance costs, enhance reputation, attract capital, and strengthen competitiveness. In short, the EPT works primarily as a behavioral incentive mechanism in non-SOEs, but functions more as a compliance reinforcement mechanism in SOEs.

Regional heterogeneity (institutional transmission frictions and market capacity).We discuss how eastern regions—characterized by more mature market governance, richer green finance, stronger technological absorption, and higher social oversight—enable a fuller transmission from regulatory pressure to reputational improvement, better financing access, greater sustainability-oriented investment, and ultimately stronger ESG outcomes. In contrast, central and western regions may face weaker regulatory capacity, limited green financial support, and potential misalignment between environmental objectives and local fiscal/growth incentives, which can dampen or distort policy transmission.

Drawing on these arguments, the new subsection concludes with a broader implication: the effectiveness of environmental regulation depends not only on the design of the instrument itself, but also on its alignment with regional governance capacity, financial resource conditions, and firms’ internal governance foundations. This directly responds to your request for a deeper, mechanism-based discussion of why heterogeneity arises (including local fiscal incentives, financing environment gaps, and differences in governance capacity).

We appreciate your guidance; it has helped us clarify the institutional economics behind the heterogeneous effects and strengthen the policy relevance of our findings.

Question 1.6

How do these findings compare with similar policies in other countries? Does the EPT’s design offer lessons for other emerging economies?

Response:

Thank you very much for this constructive suggestion. We fully agree that situating the EPT within a broader international comparative context can enhance the policy relevance of the study. In response, we have added a dedicated discussion at the end of Section 5.2.4 (Discussion of Heterogeneity Results) (see revised manuscript, pp. 21). The new content compares China’s EPT with environmental tax and pollution pricing schemes adopted in other economies—for example, carbon taxes and emission trading systems in European countries—and highlights how differences in governance capacity, green finance availability, and regulatory enforcement strength can lead to variation in policy transmission and effectiveness.

In addition, we emphasize that the Chinese EPT features flexible tax rate adjustment mechanisms, clearer pollutant classifications, and stronger integration with local environmental monitoring and information disclosure systems. These institutional arrangements may offer practical lessons for other emerging economies seeking to design environmental taxation instruments that balance regulatory enforcement with market-based incentives. The revised discussion underscores that the effectiveness of environmental taxes depends not only on tax rate and tax base design, but also on the degree of alignment with local governance capacity, financial support infrastructure, and firms’ internal governance frameworks.

We believe that this added content significantly strengthens the international relevance and policy implications of our findings. Thank you again for your valuable suggestion, which has helped improve the depth and completeness of the manuscript.

Question 1.7

The transition between sections (e.g., from literature review to hypotheses) could be smoother. Some logical connections are assumed rather than explicitly stated.

Response:

Thank you very much for your constructive suggestion. We appreciate your point that the transition from the literature review to the theoretical hypothesis section was somewhat abrupt. In response, we have carefully revised the manuscript to enhance the logical coherence of the argument. Specifically:

We added a concluding subsection at the end of the literature review to summarize existing findings and clearly highlight the research gap that motivates this study.
We introduced transition sentences at the beginning of the theoretical analysis section, which serve to naturally bridge prior literature with the development of our conceptual framework.
Before presenting each hypothesis, we added additional explanatory text to elaborate the underlying logic and ensure that the progression from theory to hypothesis is smooth and coherent.

These revisions have significantly improved the structural clarity and strengthened the logical flow between sections. We sincerely appreciate your insightful comments, which have contributed meaningfully to improving the quality and readability of the paper.

Question 1.8

The conclusion is somewhat brief. It could better highlight the study’s key contributions and policy recommendations.

Response:

Thank you very much for your constructive suggestion. You pointed out that “the conclusion section is relatively brief, and the key contributions and policy implications should be further highlighted to enhance the overall impact of the paper.” We fully agree with this valuable comment.

In response, we have revised the conclusion section accordingly. Specifically:

We added a dedicated paragraph summarizing the core contributions of the study. This highlights the research innovation in terms of empirical identification strategy, mechanism analysis, and heterogeneity examination, making the academic contributions clearer and more prominent.

We refined and expanded the policy implications to ensure that they are more closely aligned with the empirical findings and provide clearer guidance for practical implementation. This enhancement strengthens the relevance and applicability of the study’s conclusions.

These revisions have been incorporated into the manuscript in the Conclusion section and Policy Implications subsection, which we believe significantly improve the coherence and impact of the paper.

We sincerely appreciate your thoughtful and constructive feedback, which has greatly contributed to improving the quality of our manuscript.

Question 1.9

Response:

We sincerely appreciate the reviewer’s thoughtful and constructive feedback. We are grateful for your positive recognition of the empirical value and policy relevance of this study, as well as your insightful suggestion that the theoretical depth and framework integration could be further enhanced. Your comments accurately highlight an important direction for improvement, especially the need to embed the research more firmly within the broader academic discourse on environmental regulation and corporate sustainability. In response, we have carefully revised the manuscript by strengthening the theoretical underpinnings, refining the logic of the mechanism and hypothesis development, and enhancing the linkage between the literature review and conceptual framework. We have also expanded the conclusion section to more clearly emphasize the core contributions and to provide more targeted and actionable policy implications. We sincerely thank you again for your valuable guidance, which has played a crucial role in improving the rigor and clarity of our study. We will continue to refine the manuscript to better meet the publication standards of the journal.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Please refer to my comments and suggestions. I urge the authors to incorporate all the comments outlined in the report, in order to improve the scholarly quality of the paper.

Referee Report: From Control to Incentive: How Market-Driven Environmental Regulation Shapes ESG Performance in Manufacturing Industries

Overall assessment. This paper sheds light on a very important question. Critically, it not only has the potential to provide a meaningful contribution to the academic literature, but also may inform major policy debates.

Altogether, these factors justify a request to revise and resubmit the manuscript.

That said, while the outlook is positive, there are important issues about the present version of the manuscript that makes it fall short of the scholarly rigor expected for publication in an academic journal. Critically, the paper comes across as suggesting that market incentives to promote environmental policies indeed improve firms' ESG performance. Differently stated, at a first glance, the paper comes across as a tautology, making the reader wonder what is the scholarly contribution of the study. Consequently, the reader questions the scope of the analysis-that is, the reader questions whether the results documented are not just mechanical correlations rather than evidence of an economic channel.

While these are major concerns, I believe they can be properly addressed if the authors are willing to spend sincere efforts to incorporate all the comments I raise in my report. I cannot emphasize enough how important it is to implement all the expositional and empirical modifications I outline below.

Endogeneity and confounding factors. The main reservation I have about the present version of the manuscript is that both independent and dependent variables of the study seem to be mechanically related. In other words, the increasing global need to bolster environmental policy led to the implementation of the EPT, as well as to firms' increasing investments in ESG. Differently put, an omitted correlated variable proxying for how investors,policy makers and regulators care about environmental policy is driving both dependent and independent variables of the study. This is well justified in face of the massive increase in ESG investing. While the authors include time-fixed effects, this is not enough to account for the gamut of macro factors at play during the sample period because those factors can have heterogeneous dynamic effects (i.e., effects that vary at the time-firm dimension). These factors include

The rise in policy uncertainty in developed markets, which led to massive increases in ESG funds to Chinese firms.
The COVID-19 pandemic and its disruptions, which likely affected perceptions of ESG by Chinese corporations.
The anti-ESG wave in the US, which likely made investments in China more attractive to ESG-friendly institutional investors.

This is critically important because one of the arguments provided by the authors is that the regulation eases financial constraints. In this case, financial constraints could have been mitigated because of the ESG capital flows or because of the excess liquidity due to monetary expansions over the decade.

While the existence of these macro factors at play do not necessarily deem this study invalid, they create an additional burden on the authors' side to (1) discuss the factors at play (as I outlined above) and (2) conduct additional tests to attest to the robustness of the main findings.

To discuss these hidden factors, I encourage the authors to add a subsection in the manuscript titled "endogeneity and caveats."

Accounting for omitted variables. To account for the effects of omitted correlated factors (or, critically, the effects of a third variable driving both independent and dependent variables of the study), the authors can estimate parametric bounds through an approach akin to the one of Dantas et al. (2023), which relies on the parametric bound estimation put forth by Oster (2019). See Table 11 and Table 12 of Dantas et al. (2023). Critically, the authors can proceed as follows:

Estimate a regression without fixed effects and obtain the EPT coefficient estimate β and the R-squared R².
Then, consider a model with year and industry fixed effects to obtain the DID coefficient estimate and the R-squared R².
The authors can use a safety factor II = 1.3 or a more conservative II = 2.0 to obtain R²_max= min{1, II x R²} and then estimate the parametric bounds β.

Critically, if the parametric bounds preserve the positive sign of the coefficient estimate of EPT, then the authors can claim that even if omitted correlated factors are driving the effects on the dependent variable and the mediators, they would not change the direction of the inferences.

References

Dantas, M., K. J. Merkley, and F. B. G. Silva (2023). Government Guarantees and Banks' Income Smoothing. Journal of Financial Services Research 63(2), 123-173. DOI: https://doi.org/10.1007/s10693-023-00398-3.

Oster, E. (2019). Unobservable Selection and Coefficient Stability: Theory and Evidence. Journal of Business & Economic Statisties 37(2), 187-204. DOI: https://doi.org/10.1080/07350015.2016.1227711.

Verner, E. and G. Gyöngyösi (2020). Household Debt Revaluation and the Real Economy: Evidence From a Foreign Currency Debt Crisis. American Economic Review 110(9), 2667–2702. DOI: http://dx.doi.org/10.1257/aer.20181585.

Author Response

Author's Reply to the Review Report (Reviewer 2)

Please refer to my comments and suggestions. I urge the authors to incorporate all the comments outlined in the report, in order to improve the scholarly quality of the paper.

Referee Report: From Control to Incentive: How Market-Driven Environmental Regulation Shapes ESG Performance in Manufacturing Industries

Overall assessment. This paper sheds light on a very important question. Critically, it not only has the potential to provide a meaningful contribution to the academic literature, but also may inform major policy debates. Altogether, these factors justify a request to revise and resubmit the manuscript. That said, while the outlook is positive, there are important issues about the present version of the manuscript that makes it fall short of the scholarly rigor expected for publication in an academic journal. Critically, the paper comes across as suggesting that market incentives to promote environmental policies indeed improve firms' ESG performance. Differently stated, at a first glance, the paper comes across as a tautology, making the reader wonder what is the scholarly contribution of the study. Consequently, the reader questions the scope of the analysis-that is, the reader questions whether the results documented are not just mechanical correlations rather than evidence of an economic channel. While these are major concerns, I believe they can be properly addressed if the authors are willing to spend sincere efforts to incorporate all the comments I raise in my report. I cannot emphasize enough how important it is to implement all the expositional and empirical modifications I outline below.

Response:

We sincerely appreciate the reviewer’s high recognition of the importance of this study’s topic and its potential to make a meaningful contribution to both the academic literature and important policy discussions. We are deeply grateful for the reviewer’s thorough and constructive feedback, which points out the key issues in the current version of the manuscript. Specifically, we acknowledge the reviewer’s concerns regarding the apparent redundancy of the proposition "market-based environmental policies will improve corporate ESG performance," which could lead to the perception of the paper as a tautology. This, in turn, raises questions about the academic contribution and analytical depth of the study and makes readers skeptical about whether the findings are simply mechanical correlations rather than genuine evidence of economic mechanisms. We fully understand and accept these points and have already taken action to address the concerns raised.

We are committed to thoroughly revising the manuscript by addressing all the comments provided. Specifically, we will enhance the motivation and contribution of the study by compressing the background, sharpening the identification of the research gap, and clearly defining the novelty and contextual boundaries of the research to avoid presenting the proposition as self-evident. In terms of identification strategy, we will emphasize the logic of the quasi-natural experiment and multi-period DID design, clearly stating the identification assumptions and potential threats. Additionally, we will incorporate an event-study figure, mark the omitted baseline period, and include pre-trend joint significance and anticipation-window tests in the manuscript. For robustness, we will use more saturated fixed effects (such as industry × year and province × year fixed effects), alternative clustering methods, sample exclusions (e.g., excluding pandemic years), and alternative outcome measures (such as E/S/G sub-scores and alternative ESG indicators) to address macro trends and dynamic heterogeneity shocks. In the mechanism section, we will moderate the language around "single causal chains," highlighting that financing constraints and green innovation act as “conditional” transmission channels, and we will provide more intuitive economic significance using standard deviation/percentage effect and typical firm ESG ranking changes to enhance interpretability. We will also refine the academic positioning by situating the paper at the intersection of “market-based environmental regulation,” “corporate sustainability,” and “China-specific contexts,” clearly defining the boundaries for extrapolation and addressing concerns about the study’s novelty and testable implications. Lastly, we will standardize terminology, formatting, and references, refining and restructuring paragraphs to improve the logical density and readability of the manuscript.

In summary, we sincerely thank the reviewer for providing a high-level, actionable revision roadmap. These suggestions not only pinpoint the issues but also illuminate the direction for improvement. We will address each point in detail and work to transform what may seem to be an obvious proposition into an empirically testable claim backed by rigorous evidence, clearer mechanisms, and more measured wording. Once again, we deeply appreciate the reviewer’s patience and thoughtful guidance. We value this revise-and-resubmit opportunity and will submit a substantially revised manuscript that fully responds to all the comments.

Question 2.1

Endogeneity and confounding factors. The main reservation I have about the present version of the manuscript is that both independent and dependent variables of the study seem to be mechanically related. In other words, the increasing global need to bolster environmental policy led to the implementation of the EPT, as well as to firms' increasing investments in ESG. Differently put, an omitted correlated variable proxying for how investors,policy makers and regulators care about environmental policy is driving both dependent and independent variables of the study. This is well justified in face of the massive increase in ESG investing. While the authors include time-fixed effects, this is not enough to account for the gamut of macro factors at play during the sample period because those factors can have heterogeneous dynamic effects (i.e., effects that vary at the time-firm dimension). These factors include

The rise in policy uncertainty in developed markets, which led to massive increases in ESG funds to Chinese firms.

The COVID-19 pandemic and its disruptions, which likely affected perceptions of ESG by Chinese corporations.

The anti-ESG wave in the US, which likely made investments in China more attractive to ESG-friendly institutional investors.

To discuss these hidden factors, I encourage the authors to add a subsection in the manuscript titled "endogeneity and caveats."

Response:

We sincerely appreciate the reviewer’s insightful comments regarding the potential endogeneity and confounding factors in this study. In response, we have substantially strengthened the identification strategy and robustness discussion, and have added a dedicated subsection entitled “4.3.7 Endogeneity and Caveats.” In this section, we explicitly address the concern that global increases in environmental policy awareness, rising ESG-oriented capital flows, the impacts of the COVID-19 pandemic, and the emergence of anti-ESG discourse in certain markets may simultaneously influence both the implementation of the Environmental Protection Tax (EPT) and firms’ ESG performance, thereby creating a risk of mechanical correlation between the independent and dependent variables.

First, in terms of empirical strategy, beyond the original firm and year fixed effects, we additionally incorporate industry-by-year and province-by-year saturated fixed effects in the robustness specifications to absorb heterogeneous macro-level shocks that vary across regions and industries over time. We also estimate alternative specifications including firm-specific linear time trends to further mitigate concerns regarding slow-moving, unobserved factors at the firm level.

Second, within the event-study framework, we present the full set of dynamic treatment effects alongside their 95% confidence intervals and clearly indicate the omitted baseline period. The results show that pre-treatment coefficients are statistically indistinguishable from zero; the joint pre-trend test fails to reject the parallel trends assumption, and the anticipation window test indicates no evidence of firms adjusting behavior in advance of the policy. These findings provide direct support for the validity of the DID identification strategy.

Third, we conduct multiple robustness checks addressing macro-level confounding influences: (i) Sample exclusion—re-estimating the model after removing the years most affected by COVID-19 yields consistent results; (ii) Alternative fixed effects—results remain stable when using only industry-by-year or only province-by-year fixed effects; (iii) Clustering adjustments—standard errors clustered at the province level or two-way clustered at the firm and province levels do not change inference; (iv) Outcome variable substitution—re-estimations using the E, S, and G sub-scores and an alternative ESG indicator from the same data provider yield qualitatively consistent effects.

Fourth, in the mechanism analysis section, we more carefully frame the interpretation of the financing constraint and green innovation channels as conditional mediation pathways under the specified empirical setting, rather than implying a singular or universal causal mechanism. This avoids attributing potential effects of global liquidity conditions or ESG capital flows solely to the policy intervention.

Overall, these revisions substantially enhance the transparency and credibility of the empirical findings. At the same time, we explicitly acknowledge that fully eliminating all unobservable macro-level influences is inherently challenging. Therefore, the estimated effects should be interpreted as conditional causal effects under the presented identification framework. We further suggest that future research may benefit from longer observation windows, cross-institutional comparisons, or alternative external shocks to further validate and extend the findings. We sincerely thank the reviewer again for this constructive and valuable guidance, which significantly improved the rigor and clarity of the manuscript.

Question 2.2

Accounting for omitted variables. To account for the effects of omitted correlated factors (or, critically, the effects of a third variable driving both independent and dependent variables of the study), the authors can estimate parametric bounds through an approach akin to the one of Dantas et al. (2023), which relies on the parametric bound estimation put forth by Oster (2019). See Table 11 and Table 12 of Dantas et al. (2023). Critically, the authors can proceed as follows:

Estimate a regression without fixed effects and obtain the EPT coefficient estimate β and the R-squared R2.

Then, consider a model with year and industry fixed effects to obtain the DID coefficient estimate and the R-squared R2.

The authors can use a safety factor II = 1.3 or a more conservative II = 2.0 to obtain R2max = min{1, II x R2} and then estimate the parametric bounds β.

Response:

We sincerely thank the reviewer for this insightful suggestion. Following the recommendation, we have added a new subsection in the robustness analysis to explicitly address the potential influence of omitted correlated factors. Specifically, we employ the parametric bounds approach proposed by Oster (2019), as applied in Dantas et al. (2023), to examine whether unobserved confounders could jointly drive the implementation of the EPT and firms’ ESG performance.

In this analysis, we first estimate a baseline regression without fixed effects to obtain the initial coefficient and R², and then compare it with the full DID specification including year and industry fixed effects. Based on these results, we calculate the identification bounds under two commonly used upper limits for the attainable R² (i.e.,Rmax=1.3×R2 and Rmax=2×R2). The parametric bounds show that the estimated coefficient of EPT remains positive under both settings, with δ values exceeding 2, indicating that unobserved factors would need to be more than twice as influential as the observed controls to overturn our conclusions. These findings confirm that the positive effect of the EPT on corporate ESG performance is robust to concerns regarding omitted variable bias.

We have incorporated the estimation results and detailed discussion into the revised manuscript (see Section X.X “Endogeneity and Omitted Variable Concerns”). We sincerely appreciate the reviewer’s guidance, which has significantly strengthened the causal credibility of the study.

References

Oster, E. (2019). Unobservable Selection and Coefficient Stability: Theory and Evidence. Journal of Business & Economic Statisties 37(2), 187-204. DOI: https://doi.org/10.1080/07350015.2016.1227711.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The paper studies China’s 2018 Environmental Protection Tax (EPT) as a quasi-natural experiment and finds that market-based environmental regulation improves manufacturing firms’ ESG scores, with channels via eased financing constraints and green innovation; effects are stronger for non-SOEs, non-Big-Four-audited firms, and firms in the East. The question is timely and the empirical toolkit (DID, event study, placebo, PSM-DID, alternative measures) is broadly appropriate.

The manuscript alternates among (i) provinces/municipalities that raised water pollutant EPT rates (treatment) vs those that did not (control), (ii) a “city EPT pilot,” and (iii) a Post dummy that is 1 “if EPT was officially implemented for firm i in year t.” Please unify to a single definition, describe timing explicitly, and explain how firms are linked to policy exposure (registered HQ city/province? production location?). Also align Table 1’s “city pilot” wording with your actual treatment (rate increase).

Section 3.1 says you control for individual (firm) and time fixed effects, but Table 3 reports only Year and Industry FE. Please re-estimate with firm and year FE (and, ideally, province-year FE to net out regional shocks tied to rate setting) and make the table notes match the model.

T-statistics are reported, but the clustering level is not stated. Given a province-level policy shock, cluster at least at the province (or city) level; two-way clustering by firm and region-year is even better. Update table notes accordingly.

The event-study plot is referenced; please display coefficient estimates with 95% CIs, label the omitted base period, and report (i) a joint pre-trend test and (ii) an anticipation window. This will strengthen the DID identification.

Table 6 shows EPT→WW (–) and EPT→GI (+), but the mediator → MFESG (controlling for EPT) step is not reported; a Sobel Z alone is not sufficient. Please add the full set of regressions and consider modern causal-mediation (e.g., Imai–Keele–Tingley with bootstrap) for inference.

ESG scores. Specify the “Listed Company ESG Rating Database” provider and methodology (scale, coverage, rescaling), and confirm that the E/S/G sub-scores come from the same provider. The Huazheng robustness is helpful—keep both in text/tables.

Define the taxonomy/source used to label “green” (e.g., IPC Green Inventory, CNRDS, CNIPA list) and whether you use grants or applications.

The label says “Dual-Class Share Structure,” but the definition is CEO–chair duality. Please rename to “CEO duality.”

Table 1 defines FA as “years since establishment,” yet Table 2’s mean ≈2.88 suggests a log transformation. Clarify the construction.

The minimum (–33.97) looks anomalous relative to typical WW distributions and your stated 5–95% winsorization. Please verify computation, scaling, and winsorization order.

The Big Four / ownership / region splits are informative; report sample sizes (already shown in Table 8) and consider adjusting for multiple comparisons or, at minimum, discuss the family-wise error rate. A compact figure with coefficients and CIs would aid interpretation.

Provide economic significance: translate coefficients (e.g., 0.73 on EPT) into % of a SD of MFESG, or movement within the ESG distribution, and illustrate with a representative firm.

The abstract is a bit long and rhetorical; tightening will improve readability (e.g., condense policy background to one sentence, foreground identification and main effect sizes).

Soften “pioneers/comprehensive” type language in the contribution section. Keep the strong results but avoid overstatement.

Add a Data Availability and Code Availability statement (sources listed for ESG/CSMAR/EPT are good, but reproducibility would be strengthened by sharing codebooks).

Unify journal capitalization and styles (several entries show inconsistent casing/formatting).

Author Response

Author's Reply to the Review Report (Reviewer 3)

Response:

We would like to sincerely thank the reviewer for their thoughtful and encouraging feedback. We are grateful for your recognition of the relevance and timeliness of the research question, as well as your positive evaluation of the empirical methods we employed. We greatly appreciate your acknowledgment of the robustness of our empirical toolkit, which includes techniques such as Difference-in-Differences (DID), event studies, placebo tests, Propensity Score Matching-DID (PSM-DID), and alternative measures. These methods were chosen to ensure that the findings are both rigorous and credible, and we are pleased that you found them broadly appropriate for the research objectives.

Your feedback reassures us that the core focus of the paper—investigating the impact of market-based environmental regulation, specifically China’s 2018 Environmental Protection Tax (EPT), on corporate ESG performance—addresses a timely and important issue. We are also grateful for your acknowledgment of the specific channels through which these effects occur, namely eased financing constraints and enhanced green innovation, as well as the recognition that the effects are particularly pronounced for non-state-owned enterprises (non-SOEs), firms not audited by the Big Four, and those located in China’s Eastern regions. This feedback not only validates our research direction but also encourages us to continue refining our analysis to enhance both the academic contribution and policy relevance of the study.

Once again, we sincerely thank you for your detailed and constructive feedback. It has been invaluable in improving the clarity and depth of the manuscript, and we are committed to addressing any further concerns or suggestions you may have as we continue to enhance the quality of our work.

Question 3.1

Response:

Thank you very much for your constructive suggestion regarding the consistency of the policy shock variable. We fully acknowledge that the manuscript previously involved three different operationalizations of the EPT treatment variable, which may lead to ambiguity in understanding the policy identification strategy.

In the revised manuscript, we have unified the definition of the treatment variable. Specifically, we now consistently define the policy shock variable as: “The variable takes the value 1 if the applicable tax rate on water pollutants under the Environmental Protection Tax is increased in the firm’s registered location, and 0 otherwise.”

This adjustment ensures conceptual and empirical coherence across all models. Regarding the linkage between firms and policy exposure, we clarify that: The treatment assignment is based on the firm's registered location. If a firm is registered in a province where the water pollutant tax rate was increased, the firm is considered to be exposed to the policy shock. This approach aligns with the regulatory jurisdiction under which the EPT is administered.

Additionally, in response to your suggestion, we have revised Table 1 to ensure that the terminology aligns with the unified variable definition. The previous description of “city EPT pilot” has been replaced with the standardized wording: “The variable takes the value 1 if the applicable tax rate on water pollutants under the Environmental Protection Tax is increased in the firm’s registered location, and 0 otherwise.” These revisions strengthen the clarity and internal consistency of the empirical strategy.

We sincerely appreciate your insightful comment, which helped improve the methodological rigor and presentation of the paper.

Question 3.2

Response:

Thank you very much for your careful review and constructive suggestions. In response to your comment regarding the inconsistency between the description in Section 3.1 and the fixed effects reported in Table 3, we have made the following revisions:

Consistent Model Specification: Following your advice, we now explicitly include firm fixed effects and year fixed effects in all regressions. In addition, we incorporate province–year fixed effects in the core model specifications to further net out regional macro shocks associated with the adjustment of EPT tax rates.

Re-estimation of All Models: Based on the revised fixed effects structure, we re-estimated all main regressions as well as robustness checks, including mechanism analyses and heterogeneity analyses. The results remain robust, with coefficient signs and significance largely consistent with or more solid than those in the previous version.

Synchronized Revision of Text and Table Notes: We have updated the description in Section 3.1 and revised the notes in Table 3 (and related tables) to clearly indicate the inclusion of firm fixed effects, year fixed effects, and province–year fixed effects, ensuring that the model specification and its presentation are now fully aligned.

Clarification of Standard Error Adjustment (Additional Revision): Given that the policy variation occurs at the regional level, we now cluster standard errors at the province level, and we additionally report robustness results using two-way clustering in the Appendix.

Once again, we sincerely appreciate your insightful comments. Your suggestions have significantly improved the rigor and clarity of our empirical strategy and the overall presentation of the manuscript.

Question 3.3

Response:

Thank you very much for your insightful comment. Following your suggestion, we have revised our empirical specification regarding the treatment of standard errors. Specifically, given that the EPT policy shock occurs at the provincial level, we now adopt two-way clustered standard errors at the firm level and the province–year level in the core regression models, in order to address potential correlation in both the cross-sectional and temporal dimensions and to ensure robust statistical inference. In addition, we have explicitly indicated the clustering method in the notes of Table 3 and all other regression tables to maintain clarity and consistency in the presentation. We sincerely appreciate your valuable feedback, which has significantly improved the econometric rigor and overall quality of the manuscript.

Question 3.4

Response:

Thank you very much for this constructive suggestion. In the revised manuscript, we have incorporated an event-study analysis to strengthen the credibility of the DID identification strategy. Specifically, we now present the dynamic event-time coefficients with their corresponding 95% confidence intervals in Figure 2, where the year immediately preceding the policy implementation (t = −1) is explicitly designated as the omitted baseline period. The pre-policy coefficients are all statistically insignificant, and a joint significance test confirms that the pre-treatment coefficients are jointly insignificant (F = 1.27, p = 0.269 > 0.10), supporting the parallel trends assumption. Furthermore, to rule out the possibility of firms adjusting behavior in anticipation of the EPT, we conduct an anticipation window test, which likewise indicates no statistically significant effects in the periods immediately prior to the policy implementation (p = 0.312 > 0.10), suggesting the absence of anticipatory responses. Following the implementation of the EPT, the dynamic coefficients become significantly positive and exhibit a clear upward trajectory, indicating a sustained and progressively strengthening policy effect. These revisions have been added to Section 4.2 (Page 14) and the updated Figure 2, thereby enhancing the rigor and credibility of the DID estimation results.

Question 3.5

Response:

Thank you very much for this constructive suggestion. In response to the concern that the mediation analysis was incomplete and relied solely on the Sobel test, we have made the following revisions: First, we have supplemented Table 6 by explicitly presenting the regression results of the mediators (WW and GI) on ESG while controlling for EPT, thereby completing the full mediation regression chain. The results show that financing constraints significantly weaken ESG performance, whereas green innovation significantly enhances it, which is consistent with the proposed theoretical mechanisms. Second, to strengthen the credibility of the mediation analysis, we further adopt the modern causal mediation analysis framework proposed by Imai–Keele–Tingley and conduct inference using 2,000 bootstrap replications. The newly added results are reported in Table 7, which shows that both financing constraints and green innovation serve as statistically significant mediating channels, with green innovation exhibiting greater economic significance. These findings are consistent with the regression results in Table 6 and provide robust support for the mechanism that EPT improves ESG performance indirectly via financing improvement and innovation upgrading. These revisions make the mediation analysis more complete and rigorous, thereby enhancing the robustness and credibility of our conclusions. The corresponding content has been updated in the “Mechanism Analysis” section of the manuscript.

Question 3.6

Response:

We sincerely appreciate the reviewer’s careful reading and valuable comments, which greatly help improve the clarity and credibility of this study. In response to the concern regarding the ESG variable, we have now provided a more explicit description in the “Data and Variables” section. Specifically, the ESG composite score and the E, S, and G sub-dimension scores used in this paper are all obtained from the Wind–Sino-Securities Index (CSI) ESG Rating Database, which is compiled by Sino-Securities Index Co., Ltd. under a unified evaluation framework. The ratings are based on listed firms’ annual reports, CSR or sustainability reports, environmental information disclosures, and authoritative third-party data sources. The scoring adopts a 0–100 scale, and industry-level standardization is applied to reduce systematic differences arising from variations in industry characteristics, ensuring consistency and comparability across firms. Moreover, following the reviewer’s constructive suggestion, we have retained the CSI ESG rating as an alternative indicator for robustness checks in both the main text and the corresponding tables. The results remain consistent with the baseline findings, which further strengthens the robustness and reliability of our conclusions. We are sincerely grateful to the reviewer for this insightful recommendation.

Question 3.7

Define the taxonomy/source used to label “green” (e.g., IPC Green Inventory, CNRDS, CNIPA list) and whether you use grants or applications.

Response:

We sincerely appreciate the reviewer’s careful and constructive suggestion. We have now clarified the definition and measurement of green technological innovation in the “Data and Variables” section. Specifically, the identification of “green” patents in this study is based on the IPC Green Inventory issued by the World Intellectual Property Organization (WIPO), which links specific IPC codes to technologies with environmental benefits. Using this classification, green patent data are matched from the China National Intellectual Property Administration (CNIPA) database, ensuring consistency with international standards while maintaining applicability to the Chinese context.

Furthermore, to reflect the actual realization of innovation outcomes rather than strategic patent filing behavior, this study adopts the granted-patent measure rather than the application-based measure. Green innovation is therefore measured as the total number of granted green invention patents and granted green utility model patents obtained by each firm in a given year, and the indicator is defined as ln(1+total granted green patents) to address distributional skewness. We have also added a brief robustness discussion indicating that using alternative specifications (e.g., application counts or alternative classification mappings) does not materially affect the core empirical conclusions.

We thank the reviewer again for this insightful suggestion, which has improved the transparency and replicability of our variable construction.

Question 3.8

The label says “Dual-Class Share Structure,” but the definition is CEO–chair duality. Please rename to “CEO duality.”

Response:

Thank you very much for the reviewer’s correction. We have replaced the original variable name “Dual-Class Share Structure” with “CEO Duality”, and clarified its definition as follows: the variable equals 1 if the CEO also serves as the Chair of the Board, and 0 otherwise. This modification has been consistently updated in the main text, tables, and variable definitions.

Question 3.9

Table 1 defines FA as “years since establishment,” yet Table 2’s mean ≈2.88 suggests a log transformation. Clarify the construction.

Response:

We sincerely appreciate the reviewer’s careful and constructive comment. To clarify, the variable FA is defined as the number of years since the firm’s establishment; however, to reduce scale differences and address right-skewness in its distribution, the variable is transformed using the natural logarithm as follows: FA=ln(1+Firm Age). This log transformation explains why the mean of FA in Table 2 is approximately 2.88. We have now explicitly stated this variable construction in the “Data and Variables” section as well as in the variable definition note in Table 1, and ensured consistency in wording across the manuscript. We sincerely thank the reviewer for helping us improve the clarity and precision of our variable definitions.

Question 3.10

The minimum (–33.97) looks anomalous relative to typical WW distributions and your stated 5–95% winsorization. Please verify computation, scaling, and winsorization order.

Response:

We are grateful to the reviewer for pointing this out. After carefully re-checking the preprocessing of the WW indicator, we confirm there was an error: in the version underlying Table 2 we did not apply winsorization, which led to the anomalous minimum (–33.97) inconsistent with the stated trimming rule. We have now corrected the pipeline as follows: (i) compute the WW index, (ii) apply the planned scale transformation (log adjustment), and then (iii) perform winsorization at the 1st and 99th percentiles. We have re-computed the descriptive statistics under this corrected procedure; the WW distribution now falls within a reasonable range and no longer exhibits the previously abnormal minimum. The text has been updated to reflect the 1–99% winsorization (replacing the earlier 5–95% statement), and the revised summary statistics are reported in the manuscript (Table 1/2). We also re-estimated all regressions using the corrected WW series; the sign and statistical significance of the results remain unchanged, leaving our conclusions intact. We thank the reviewer again for helping us improve the transparency and rigor of our data processing.

Question 3.11

Response:

We sincerely appreciate the reviewer’s valuable suggestions. In response, we have added the subgroup sample sizes to the heterogeneity tables to improve transparency. We also acknowledge the potential concern regarding multiple comparisons; therefore, we have included a brief discussion on the possible family-wise error rate (FWER) in the heterogeneity analysis section. In addition, following the reviewer’s recommendation, we now provide a concise coefficient plot with 95% confidence intervals (Figure 5), which visually summarizes the subgroup estimation results and enhances readability. These revisions improve both the clarity and interpretability of the heterogeneity analysis. We thank the reviewer again for the constructive guidance.

Question 3.12

Provide economic significance: translate coefficients (e.g., 0.73 on EPT) into % of a SD of MFESG, or movement within the ESG distribution, and illustrate with a representative firm.

Response:

We appreciate the reviewer’s valuable suggestion. We have added the economic significance interpretation in the revised manuscript. In the baseline specification (Column (4)), the coefficient of EPT is 0.6549. Given that the standard deviation of MFESG in the sample is 4.573, this effect corresponds to an increase of approximately 0.143 standard deviations (0.6549 ÷ 4.573 ≈ 0.143), indicating that the policy effect is economically meaningful in magnitude. Moreover, considering that the ESG score ranges from 0 to 100, and the sample mean of MFESG is 73.19, the implementation of the EPT results in an approximately 0.9% improvement in ESG performance (0.6549 ÷ 73.19 ≈ 0.009). Therefore, the effect is not only statistically significant but also substantively meaningful in economic terms. The relevant interpretation has been incorporated into the corresponding section of the manuscript.

Question 3.13

The abstract is a bit long and rhetorical; tightening will improve readability (e.g., condense policy background to one sentence, foreground identification and main effect sizes).

Response:

We sincerely appreciate the reviewer’s constructive comments. In accordance with the suggestion, we have streamlined and refined the abstract by condensing the previously lengthy policy background into a single sentence to enhance conciseness. Additionally, we now more clearly emphasize the study’s identification strategy (i.e., treating the 2018 implementation of the Environmental Protection Tax as a quasi-natural experiment and employing a difference-in-differences framework) to improve the clarity of the research design and key findings. These revisions help to strengthen the focus and readability of the abstract. We once again thank the reviewer for the valuable guidance that has contributed to improving the quality of the manuscript.

Question 3.14

Soften “pioneers/comprehensive” type language in the contribution section. Keep the strong results but avoid overstatement.

Response:

We appreciate the reviewer’s thoughtful suggestion. Accordingly, we have revised the contribution section by removing expressions that may imply “pioneering” or “comprehensive” claims. The revised text places greater emphasis on the incremental and context-specific nature of our contributions, using more cautious wording such as “provides relatively robust evidence,” “offers suggestive mechanism-based explanations,” and “may inform differentiated policy design,” rather than overstating the scope or significance of the findings. These adjustments help ensure that the conclusions remain well-supported and appropriately measured. We sincerely thank the reviewer for the guidance in improving the clarity and tone of the manuscript.

Question 3.15

Add a Data Availability and Code Availability statement (sources listed for ESG/CSMAR/EPT are good, but reproducibility would be strengthened by sharing codebooks).

Response:

We sincerely appreciate the reviewer’s helpful suggestion. In the revised manuscript, we have added a “Data and Code Availability Statement” section to further clarify the data sources, variable construction procedures, and data processing steps. As the CSMAR database and the Wind–Sino-Securities ESG rating data are subject to commercial licensing restrictions, the raw data cannot be publicly released. However, we have compiled a complete variable dictionary and the core Stata code used for data cleaning and empirical analysis. Upon acceptance of the manuscript, we will upload these materials to the data repository required or recommended by the journal to ensure the transparency and reproducibility of our research. We again thank the reviewer for the valuable suggestion, which has helped us improve the rigor and replicability of the paper.

Question 3.16

Unify journal capitalization and styles (several entries show inconsistent casing/formatting).

Response:

We sincerely thank the reviewer for this helpful suggestion. In accordance with the recommendation, we have thoroughly standardized the reference list throughout the manuscript. Specifically, we (1) unified the capitalization format of journal titles, (2) adjusted author names, publication years, volume/issue numbers, page ranges, and DOIs according to the Sustainability journal citation style, and (3) removed formatting inconsistencies to ensure complete uniformity across all entries. The revised, fully standardized reference list has now been incorporated into the updated manuscript. We appreciate the reviewer’s valuable guidance in improving the clarity and professionalism of the paper.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

After carefully reviewing the authors' revisions, I confirm that they have adequately addressed all the concerns and suggestions raised in my initial review. The manuscript has been significantly improved, with clarifications added to methodological details, strengthened data interpretation, and discussion. I recommend acceptance of the manuscript in its current form.

Author Response

Author's Reply to the Review Report (Reviewer 1)

Response:

We sincerely thank the reviewer for the careful re-evaluation of our manuscript and for the positive recommendation. We are truly grateful for the reviewer’s constructive comments and thoughtful guidance throughout the review process, which have helped us further clarify the methodological design, strengthen the empirical interpretation, and improve the overall rigor and presentation of the paper. We deeply appreciate the reviewer’s recognition of the revisions and the recommendation for acceptance. Thank you again for your time, expertise, and valuable contribution to the improvement of our work.

Reviewer 2 Report

Comments and Suggestions for Authors

N/A

Author Response

Author's Reply to the Review Report (Reviewer 2)

Response:

We sincerely appreciate the reviewer’s patience and professional guidance throughout the review process. The reviewer’s insightful comments not only helped us identify and address the shortcomings in the earlier version of the manuscript, but also encouraged us to further refine the research design, improve the model specification, and enhance the discussion of the findings. We are honored to receive the reviewer’s recognition, and we truly value this affirmation from a fellow scholar. Thank you again for devoting your time and expertise to reviewing our work. Your careful and constructive feedback has played an important role in shaping the final version of this study.

Reviewer 3 Report

Comments and Suggestions for Authors

The paper studies whether China’s Environmental Protection Tax (EPT)—as a market-based regulation—improves listed manufacturing firms’ ESG performance. Using a DID design where treatment is defined by provinces that raised water-pollutant tax rates, the authors find a positive average effect (~0.655 points on a 0–100 ESG scale; ≈0.14 SD given SD≈4.57) and present an event-study with flat pretrends. They explore mechanisms (financing constraints and green innovation) and heterogeneity by ownership, audit, and region.

Please provide a transparent “first stage”: a table/map listing each province’s chosen EPT rate (and change) and the effective year(s). This makes treatment assignment auditable and allows intensity tests based on magnitude of the rate increase (continuous DID). Also clarify whether municipalities within a province can set different rates (the text suggests province-level uniformity).

Results state two-way clustering at the firm level and the province-year level—a nonstandard choice when the policy varies at the province level. Re-report with clustering by firm and province (or province alone), and consider wild-cluster bootstrap at the province level to guard against over-rejection with ≈31 clusters. Please align the clustering choice with the policy assignment level.

Wind–Sino-Securities ratings are suitable for China, but please discuss coverage over 2010–2012 (early-years missingness?) and the implications of industry-standardization for interpreting level changes. A data-availability note is included; append a short historical coverage summary and a robustness check using z-scores within-industry-year to ensure findings aren’t artifacts of scaling.

Typo: “winsorization at the 1th and 99th percentiles” → “1st and 99th percentiles.”

Author Response

Author's Reply to the Review Report (Reviewer 3)

Response:

We sincerely thank the reviewer for the careful reading and highly accurate summary of our study. We truly appreciate your clear articulation that this paper examines whether the Environmental Protection Tax (EPT), as a market-based environmental regulation, improves the ESG performance of listed manufacturing firms in China. Your summary precisely reflects our empirical design, in which provinces that raised water-pollutant tax rates are defined as the treatment group, and a Difference-in-Differences framework is employed. We are also grateful for your acknowledgment of our empirical findings, including the positive average treatment effect (approximately 0.655 points on a 0–100 ESG scale, corresponding to about 0.14 standard deviations given SD≈4.57), as well as the event-study evidence that supports the parallel trend assumption prior to the implementation of the EPT.

We appreciate that you further recognized our exploration of the underlying mechanisms—namely the mitigation of financing constraints and the enhancement of green innovation—as well as the heterogeneity analyses across ownership type, audit characteristics, and regional differences. Your summary accurately captures the central contributions of this work and will help future readers quickly grasp the motivation, identification strategy, and empirical results of the paper.

In response to your insightful overview, we have also taken the opportunity to refine the exposition of the manuscript. Specifically, we have: (1) clarified and presented the effect size alongside its standardized interpretation in the Abstract and Results sections to improve readability; (2) reiterated the definition of treatment assignment and the basis for tax-rate differentiation in the Research Design section for greater transparency; and (3) provided a more concise economic interpretation of the financing-constraint and green-innovation mechanisms, while also adding sample-size information and robustness notes in the heterogeneity analysis section. We believe these improvements—motivated by your accurate and constructive summary—further enhance the clarity, internal consistency, and replicability of the paper.

Once again, we sincerely thank you for your thoughtful and encouraging comments.

Question 1

Response:

We sincerely appreciate the reviewer’s valuable suggestion, and we have revised the manuscript accordingly. Specifically, we have added Appendix Table A1, which reports for each province the statutory water-pollutant Environmental Protection Tax (EPT) rates, the corresponding changes relative to the former sewage-fee regime, and the effective year of implementation. This addition strengthens the transparency and auditability of treatment assignment and helps readers clearly understand the source of cross-provincial policy variation.

Regarding the reviewer’s suggestion to construct a continuous intensity-based DID using the magnitude of the tax-rate increase, after careful examination, we find that such an approach is not feasible under the institutional structure of the EPT. The reason is that the EPT adopts multi-tier statutory tax schedules within the same province, with tax rates differentiated by pollutant category. As a result, multiple concurrent statutory rates exist within a single province and year. For example, in Hebei, the benchmark sewage fee before the EPT was 2.4, whereas under the EPT the applicable water-pollutant tax schedule became: 9.6 for primary pollutants (and 4.8 for other primary pollutants), 6.0 for secondary pollutants (and 4.8 for other secondary pollutants), and 4.8 for tertiary pollutants. Constructing a single scalar “rate increase” would therefore require an artificial weighting rule, yet provinces differ in pollutant composition, industrial structure, and enforcement categorization. Any such aggregation would inevitably introduce measurement error and comparability distortions across provinces.

To ensure the interpretability and robustness of the identification strategy, we therefore retain the binary treatment definition based on whether a province increased its applicable water-pollutant statutory rates under the EPT. At the same time, we have clarified in the manuscript that EPT tax rates are uniformly set at the provincial level and applied consistently within the province, and that municipalities do not have independent authority to adjust statutory rates.

We believe these revisions enhance the transparency, verifiability, and econometric rigor of the study. Once again, we sincerely thank the reviewer for the insightful and constructive comments.

Appendix 1 Comparison of sewage fee and environmental tax by province in China

Province	Atmospheric pollutants		Water pollutants
Province	Sewage fee	Environmental protection tax	Sewage fee	Environmental protection tax
Beijing	Sulphur dioxide, nitrogen oxides 10	12	COD 10, ammonia nitrogen 12	14
Tianjin	Sulphur dioxide 6.30, nitrogen oxides 8.50	10	COD 7.50, ammonia nitrogen 9.50	12
Hebei	2.4	Primary pollutant 9.6 and other pollutants 4.8; Secondary pollutant 6 and other pollutants 4.8; Tertiary pollutant 4.8	2.8	Primary pollutant 9.6 and other pollutants 4.8; Secondary pollutant 6 and other pollutants 4.8; Tertiary pollutant 4.8
Shanghai	Sulphur dioxide, nitrogen oxides 4	2018: sulphur dioxide 6.65, nitrogen oxides 7.6, other pollutants 1.2; 2019:	COD, ammonia 3	COD, ammonia nitrogen 4.8, Class I water pollutants 1.4, others 1.4
Shandong	Sulphur dioxide, nitrogen oxides 6, other 1.2	Sulphur dioxide, nitrogen oxides 6, other pollutants 1.2	COD, ammonia nitrogen and five heavy metals 1.4	COD, ammonia nitrogen and five heavy metals3, other pollutants 1.4
Jiangsu	3.6	Nanjing 8.4, Wuxi, Changzhou, Suzhou, Zhenjiang 6, other areas 4.8	4.2	Nanjing 8.4, Wuxi, Changzhou, Suzhou, Zhenjiang 7, other areas 5.6
Zhejiang	1.2	Four heavy metal pollutants 1.8, other pollutants 1.2	1.4	Five heavy metals, COD and ammonia nitrogen 1.8, other pollutants 1.4
Sichuan	1.2	3.9	1.4	2.8
Shanxi	1.2	1.8	1.4	2.1
Hunan	1.2	2.4	1.4	3
Henan	1.2	4.8	1.4	5.6
Guizhou, Hainan	1.2	2.4	1.4	2.8
Guangdong, Guangxi	1.2	1.8	1.4	2.8
Tibet	0.6	1.2	0.7	1.4
Chongqing	1.2	2018–2020: 2.4,2021: 3.5	1.4	2018–2020: 3,2021: 3
Fujian	1.2	1.2	1.4	Five heavy metals, COD and ammonia nitrogen 1.5, other pollutants 1.4
Hubei	2.4	Sulphur dioxide, nitrogen oxides 2.4, other pollutants 1.2	2.8	Five heavy metals, COD, total phosphorus, ammonia nitrogen 2.8, other pollutants 1.4
Anhui	1.2	1.2	Five heavy metals, COD and ammonia nitrogen 1.4	1.4
Heilongjiang, Liaoning, Jilin, Jiangxi, Gansu, Qinghai, Shaanxi, Ningxia, Xinjiang	1.2	1.2	1.4	1.4
Yunnan	1.2	2018: 1.2，2019: 2.8	1.4	2018: 1.4, 2019: 3.5
Inner Mongolia	Sulphur dioxide, nitrogen oxides 1.2	2018: 1.2, 2019: 1.8, 2020: 2.4	1.4	2018: 1.4, 2019: 3.5

Note: The data comes from the official websites of local governments.

Question 2

Response:

We sincerely appreciate the reviewer’s insightful comment regarding the clustering strategy. Following your recommendation, we have carefully revised the empirical analysis to ensure that the standard error clustering aligns with the level at which the policy varies. Specifically, we have replaced the previous firm-level and province-year clustering with two-way clustering at the firm level and the province level, which is consistent with the fact that the Environmental Protection Tax is implemented at the provincial level. Furthermore, to address the concern that the number of clusters at the province level (approximately 31) may lead to over-rejection, we have additionally conducted inference using the wild-cluster bootstrap procedure with clustering at the province level. The results remain robust and consistent with the main findings, confirming that our conclusions are not sensitive to the method of inference. We have clearly indicated these revisions in the empirical methodology section and report the wild-cluster bootstrap results in the robustness section of the manuscript. We are grateful for the reviewer’s valuable suggestion, which has substantially improved the econometric rigor and credibility of our findings.

Question 3

Response:

We sincerely appreciate the reviewer’s valuable and insightful suggestion. In response, we have added an explanation in the manuscript regarding the historical coverage of the Wind–Sino-Securities ESG rating system, clarifying that the rating system was gradually established and improved over the sample period and reached a relatively stable coverage pattern in later years. This addition helps ensure the transparency and rationality of the ESG measure used in the study.

Furthermore, to address the reviewer’s concern regarding the potential impact of industry-based normalization on the interpretation of ESG level changes, we conduct a robustness test using an industry–year standardized ESG measure. The results, reported in Column (4) of Table 5, show that the key coefficient remains positive and statistically significant, and the economic interpretation remains consistent with the baseline findings. This confirms that the core conclusions are robust and are not driven by the normalization mechanism inherent in the rating system.

We sincerely thank the reviewer once again for the constructive comments, which have helped improve the clarity and rigor of the manuscript.

Question 4

Typo: “winsorization at the 1th and 99th percentiles” → “1st and 99th percentiles.”

Response:

We sincerely thank the reviewer for pointing out this typographical error. We have corrected the expression in the manuscript accordingly. The revised sentence now reads: “all continuous variables were subjected to two-sided winsorization at the 1st and 99th percentiles.” We appreciate the reviewer’s careful reading and helpful suggestion.

Author Response File: Author Response.pdf

Round 3

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript examines how China’s Environmental Protection Tax (EPT), as a market-based environmental regulation, affects the ESG performance of listed manufacturing firms. Using an unbalanced panel of 2,677 firms from 2010–2022 and a multi-period DID design, the authors find that (i) EPT implementation improves firms’ composite ESG scores; (ii) financing constraints (WW index) and green innovation (green patents) act as mediating channels; and (iii) effects are stronger for non-SOEs, firms not audited by the Big Four, and firms located in eastern regions. A wide range of robustness checks is provided. Overall, the topic is timely and relevant for Sustainability and the empirical analysis is carefully implemented.

Please provide a stronger theoretical justification for treating GI as a mediator distinct from the ESG outcome itself. Alternatively, the authors could reframe this analysis to test whether the EPT’s primary impact on the ‘E’ pillar is driven by patentable green innovation, rather than presenting it as a mediator for the composite ESG score.

The analysis would be far more convincing if the authors employed a continuous or dose-response DID model. Using the actual tax rate (or its log) or the percentage change in the tax rate as the treatment variable would allow for an estimation of the elasticity of ESG performance with respect to the tax burden. This would also provide a more robust test of the underlying "cost pressure" mechanism.

Please discuss alternative interpretations. For instance:
(Baseline Effects) Do non-Big Four firms have significantly lower pre-policy ESG scores, thus offering more "room to improve"? (A test of pre-treatment baseline differences would be helpful).
(Monitoring vs. Reporting) Is it possible that Big Four firms are already adept at ESG reporting (which is what ratings measure), while the EPT forces operational changes in non-Big Four firms that are then newly captured in their ratings?
(Resource Allocation) Conversely, do Big Four firms have superior resources to "manage" the tax liability through complex financial or legal means rather than operational green investments?

Please provide a more robust theoretical linkage for this spillover effect. Is this a substantive change, or is it a reporting artifact (i.e., firms, now under scrutiny for 'E', simply increase their disclosure on 'S' topics as well)?

Author Response

Author's Reply to the Review Report (Reviewer 3)

Response:

Thank you very much for reviewing our manuscript and providing valuable feedback. We are pleased that you found our research topic and empirical analysis methods to be positively evaluated. Regarding the impact of China’s Environmental Protection Tax (EPT) on the ESG performance of listed manufacturing firms, our study indeed utilizes unbalanced panel data from 2,677 firms from 2010 to 2022, and employs a multi-period difference-in-differences (DID) design to analyze its effects. Your comments have affirmed our efforts in providing robust checks, which are greatly appreciated.

We also appreciate your recognition of the key findings of the paper, especially the roles of financing constraints (WW index) and green innovation (green patents) as mediating channels. We believe these insights are crucial for understanding how market-based environmental policies influence corporate sustainability. Your feedback encourages us to further refine our analysis of these mechanisms and ensure that our results are supported by both solid theoretical grounding and empirical evidence.

Once again, thank you for your thoughtful review. We will carefully consider your suggestions and make the necessary revisions to improve the quality and impact of the paper.

Question 1

Response:

Thank you for this constructive suggestion. In response, we have revised our analysis framework, particularly focusing on the "Environmental" (E) dimension. In the revised version, we reconsidered our research design and concentrated on examining whether the primary impact of the Environmental Protection Tax (EPT) on the "Environmental" (E) pillar is driven by green innovation (e.g., green patents), rather than through the composite ESG score as a mediator.

Specifically, we analyzed the impact of the EPT on the "Environmental" (E) dimension by looking at indicators of green innovation, such as the number of green patents. We found that the implementation of the EPT significantly promoted green innovation, particularly in terms of green patent applications and acquisitions. This increase in green innovation, in turn, drove improvements in corporate performance in the environmental (E) dimension. This result indicates that green innovation is the core driver of the EPT's impact on the "Environmental" (E) pillar, rather than merely reflecting a change in the overall ESG score.

Through this new analysis framework, we are able to clearly establish that green innovation is the primary mechanism through which the Environmental Protection Tax improves corporate performance in the environmental (E) dimension. This finding further supports the theoretical foundation of green innovation as an independent mediator in the policy's implementation.

Question 2

Response:

Thank you for the valuable feedback provided on our paper. We greatly appreciate your suggestion to use a continuous or dose-response DID model, and to use the actual tax rate (or its logarithm) or percentage changes in tax rates as the treatment variable to estimate the elasticity of ESG performance with respect to tax burden. We have carefully considered this suggestion and would like to address the feasibility of its implementation.

However, since the Environmental Protection Tax (EPT) implemented in 2018 sets different tax rates for various pollutants, it makes it difficult to apply a single actual tax rate or percentage change in tax rate as a treatment variable. For example, in Hebei province, while the overall sewage fee for atmospheric pollutants increased after the introduction of the Environmental Protection Tax, the tax rates differ for different pollutants: primary pollutants are taxed at 9.6, secondary pollutants at 6, and other pollutants at 4.8. These discrepancies in tax rates make it challenging to analyze using a unified tax rate or its percentage change as a treatment variable.

Nonetheless, we appreciate the reviewer’s insightful suggestion and will explore other methods in the revision to better quantify the impact of tax burden changes on ESG performance. We will also consider how to integrate changes in tax rates for different pollutants to improve the robustness of the model and ensure the reliability of the analysis.

Once again, we thank the reviewer for the valuable suggestions and will continue to improve our study accordingly.

Question 3

Please discuss alternative interpretations. For instance:

(Baseline Effects) Do non-Big Four firms have significantly lower pre-policy ESG scores, thus offering more "room to improve"? (A test of pre-treatment baseline differences would be helpful).

(Monitoring vs. Reporting) Is it possible that Big Four firms are already adept at ESG reporting (which is what ratings measure), while the EPT forces operational changes in non-Big Four firms that are then newly captured in their ratings?

(Resource Allocation) Conversely, do Big Four firms have superior resources to "manage" the tax liability through complex financial or legal means rather than operational green investments?

Response:

We would like to thank the reviewer for their thorough review and valuable suggestions. We greatly appreciate your feedback and have decided to include a discussion of the "monitoring and reporting" alternative explanation in the revised version of the paper.

In the revised version, we further explored the issue of whether firms audited by the Big Four accounting firms are already proficient in ESG reporting. We believe that firms audited by the Big Four typically possess strong capabilities in ESG reporting and information disclosure, meaning that they already have high transparency and well-established reporting systems in the rating process. As a result, their ESG scores may have already been relatively stable before and after the implementation of the Environmental Protection Tax (EPT), and the impact of the policy may be smaller for them.

In contrast, firms not audited by the Big Four often lack sufficient reporting and transparency, and the EPT may force these firms to make operational changes, such as improving environmental management and enhancing social responsibility. These changes are more likely to be reflected in their ESG ratings after the policy is implemented. Therefore, firms not audited by the Big Four may exhibit a stronger response to the EPT, as they are less prepared in terms of reporting and governance.

Regarding other alternative explanations, such as baseline effects and resource allocation, we acknowledge that they are also worth further exploration. However, the focus of this study is on analyzing the heterogeneity between Big Four audited and non-audited firms and their response mechanisms. We will consider further testing these factors in future research.

Once again, we thank the reviewer for their insightful comments, which have helped us better understand and clarify the potential mechanisms in our study. If you have any further suggestions or questions, we would be happy to continue improving and refining our work.

Question 4

Response:

We would like to sincerely thank the reviewer for their constructive feedback. In the revised version, we have further strengthened the theoretical explanation of the spillover effect and explored whether it represents a substantive change or simply a reporting artifact.

Specifically, we have made the following additions:

We acknowledge that the Environmental Protection Tax (EPT) may lead to improvements in corporate social responsibility and governance. However, these improvements may arise from two different mechanisms: On the one hand, firms may respond to environmental policies through actual operational changes, such as improving employee welfare, enhancing social responsibility practices, and improving governance structures. On the other hand, firms may merely increase their disclosures in these areas to enhance their ESG scores, even if these disclosures are not accompanied by substantial operational changes. Therefore, we clearly distinguish between these two possibilities and suggest that future research could further validate whether the observed spillover effect truly reflects changes in corporate behavior or whether it is simply an increase in disclosures to improve ESG scores.

We emphasize that improvements in the Social (S) and Governance (G) dimensions may not solely be due to increased reporting. In fact, after improving their environmental performance, firms may have made substantial investments and improvements in social responsibility and governance. However, if these improvements are only reflected in disclosures and not accompanied by real operational changes, then the spillover effect may simply be a reporting artifact. To verify this, we suggest that future research examine the specific investments made by firms in the areas of social responsibility and governance (such as funding, projects, etc.) to determine whether these improvements reflect substantive changes in corporate behavior.

We further discuss the gradual nature of improvements in the Governance (G) dimension. Governance improvements typically occur over a long period, involving changes in management practices, improvements in disclosure mechanisms, and long-term strategic alignment with sustainability goals. These changes usually require deeper organizational commitment, and compared to the Environmental and Social dimensions, improvements in governance are more gradual. Therefore, the impact on the Governance (G) dimension is smaller and takes longer to materialize.

Once again, we thank the reviewer for their valuable suggestions. If the reviewer has any further recommendations or questions, we would be more than happy to continue improving and refining our work.

Author Response File: Author Response.docx