Review Reports

1. Summary

Thank you very much for taking the time to review our manuscript and for providing your valuable and insightful comments to enhance the quality of our work. In accordance with your feedback, we have thoroughly and carefully revised the entire manuscript. We have submitted a version with all changes marked and highlighted in yellow for your convenient review. We look forward to receiving your acceptance.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: [Q1. The manuscript is extremely difficult to follow. The writing is riddled with incomplete sentences, missing verbs, and unclear phrasing. For example, the very first sentence of the introduction is grammatically broken. The authors must carefully reread the entire manuscript and revise it thoroughly to ensure basic readability and coherence. ]

Response 1: We sincerely appreciate your rigorous assessment regarding the language quality. We fully agree with your observation that the manuscript suffered from significant issues in expression, sentence completeness, and overall coherence. These shortcomings in the initial version seriously compromised the readability and effective communication of the scientific content. Consequently, we have conducted a thorough, word-by-word review of the manuscript, focusing specifically on correcting incomplete sentences, missing verb elements, and ambiguous phrasing to ensure every sentence is grammatically sound and clearly expressed.

Especially the first sentence of the introduction:

Against the backdrop of the intensifying global climate crisis and the deepening concept of sustainable development [1,2,3,4].

After revision:

Pressured by the global climate crisis and polluting emissions, the international community's focus is driving the crucial importance of sustainable development for businesses [1,2,3,4].

Comments 2: [Q2. Some other examples of issues with writing: What do these phrases mean: “understanding the basic situation of the data”, in Figure 5, the phrase “shows a separate data set of TQ”?]

Response 2: Thank you very much for pointing this out. After revision: Figure 5 presents the trend in Tobin's Q of listed polluting listed companies over the period 2012–2022. (Figure 5. Tobin's Q trend analysis of polluting listed companies)

Comments 3: [Q3. Table 1: The column headings are misleading. “Variable” and “Variable Name” should be merged into a single column that clearly identifies each variable. The “Explanation and Calculation Methods” column is inconsistent, some entries contain useful definitions, while others are vague or irrelevant. This column should be cleaned up to include only concise, meaningful descriptions.  “Ln” (logarithmic transformation) is incorrectly presented as an exploratory variable.]

Response 3: Thank you very much for pointing this out. Table 1 has been revised as follows:

Table 1. Variable statistics and explanations.

Comments 4: [Q4. Figure 5 needs improvement. Generally it is hard to understand this figure. The x-axis labels are unreadable, and the explanation provided for what we learn from this is vague. The sharp change around 2018 warrants deeper analysis.]

Response 4: Thank you very much for pointing this out. Figure 5 has been simplified and improved to provide a deeper analysis of the sharp changes around 2018. Figure 5 analysis has been revised as follows:

Figure 5 is a three-dimensional projection curve of the Tobin's Q dataset, displaying changes from 2012 to 2022. The horizontal axis represents the year, while the left vertical axis is labeled "872 Listed Companies," and the right axis shows "Tobin's Q." The color bar corresponds to Tobin's Q values ranging from 0.60 to 21.30. Overall, Tobin's Q demonstrates a volatile but rising trend, indicating a general enhancement in market valuation.

The point labeled 2018 EPT Policy shows noticeable fluctuations around the year. Values were relatively stable before 2018 but declined temporarily around the policy's implementation, later rebounding quickly and continuing to rise. This volatility may be linked to the EPT reform. The policy might have initially affected corporate costs and profit expectations, suppressing Tobin's Q in the short term. Over the longer term, however, the industry upgrades and green development concepts promoted by the policy likely led to a reassessment of corporate value by the market, resulting in the recovery and growth of Tobin's Q.

In summary, the long-term increase in Tobin's Q reflects market recognition of corporate value, while the short-term fluctuation around 2018 illustrates the impact and adaptation process following a policy change. This pattern of "long-term growth with short-term volatility" highlights the influence of environmental policy guidance during China's economic transformation and the resilience of listed companies when facing external policy shocks, providing next step (empirical evidence) for this study on the effects of the 2018 EPT policy.

Comments 5: [Q5. Given the apparent structural break in 2018, shown in Figure 5, why a difference-in-differences approach is not employed?]

Response 5: Thank you very much for pointing this out. Given the clear structural breakthrough in 2018 shown in Figure 5, first, based on our research objectives, we need to clearly study the impact of specific EPT rates to conduct an assessment. Secondly, we have already adopted the difference-in-differences approach in terms of methodology, but the parallel trend method is not sufficient. Looking at columns (25) and (26) of Table 10, we provide regression results for 2013-2017 and 2028-2022, respectively. The 2013-2017 period is also significantly negative, so this approach cannot be used. In addition, future research directions require further exploration of specific EPT tax rate designs and optimization strategies, so the difference-in-differences approach is ruled out.

Comments 6: [Q6.Figures 6–8 do not contribute meaningfully to the discussion and should be removed or moved to the appendix. Same rule applies to Tables 3–4, along with their associated discussions, they should be moved to the appendix. They do not add to the main narrative and distract from the core analysis.

In general, any tests or robustness checks that do not directly support the interpretation of the main results should be relocated to the appendix. The current structure overwhelms the reader with preliminary material, making it difficult to focus and understand the actual findings and their implications.]

Response 6: Thank you very much for pointing this out. We agree with you. Figures 6-8 do not contribute substantially to the discussion and have been moved to the Appendix. Similarly, Tables 3-4 and their associated discussion have been moved to the Appendix. They do not add to the main narrative and, instead, distract from the core analysis. Any tests or robustness checks that do not directly support the interpretation of the main results have been adjusted. It also includes OLS regression and benchmark regression, which retain detailed display of control variables. The rest of the empirical results simplify the display of control variables and retain the main results. The current structure has been streamlined to focus readers' attention on the actual findings and their implications.

Comments 7: [Q7. The paper lacks a clear and extended interpretation of the results. After presenting the empirical findings, the authors should put more effort to explain what these results mean.]

Response 7: Thank you very much for pointing this out. Overall, we generally concur with all of your comments and have thoroughly addressed each one in our revisions. We acknowledge that, after presenting the empirical findings, we should have made greater efforts to interpret the implications of these results. In the initial version, we overlooked the importance of in-depth analysis and interpretation, focusing instead on data processing and superficial analysis. We greatly appreciate your expert insights and suggestions.

Finally, we have comprehensively revised the manuscript based on all of your comments and look forward to your confirmation and acceptance.

3. Additional clarifications

[NO]

1. Summary

Thank you very much for taking the time to review our manuscript and for providing your valuable and insightful comments to enhance the quality of our work. In accordance with your feedback, we have thoroughly and carefully revised the entire manuscript. We have submitted a version with all changes marked and highlighted in yellow for your convenient review. We look forward to receiving your acceptance.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: [(1) Regarding the introduction, the relevant discussion lacks conciseness. The novelty of the current version remains unconvincing.]

Response 1: Thank you very much for your valuable feedback on the conciseness and novelty of the introduction. We fully agree with your comments. The original version was indeed lengthy and lacked a clear focus on the core contributions, which weakened the persuasiveness of the research. Based on your suggestions, we have made significant revisions to the introduction, including the following: Lines 32-81

Enhancing Conciseness: We have refined and consolidated the original fragmented discussion of the necessity and innovation of the research, removing repetitive and background-laden statements. This ensures that the core issues are clearly addressed at the outset, and the logical flow of the paper directly connects theoretical gaps with practical needs.

Enhancing the Persuasiveness of Novelty: We have focused on revising the statement of research innovation to be more specific and confident:

Clearly Identifying the Theoretical Breakthrough: We emphasize that this study "is the first to systematically construct an empirical transmission framework linking EPT intensity, firm behavior, and market value," rather than vaguely claiming to link the two.

Clearly Defining the Mechanistic Contribution: We clearly explain how the introduced moderators (e.g., debt-to-asset ratio, R&D investment) and mediating variables (e.g., patent quality) are used together to "reveal the boundary conditions and transmission mechanisms of the EPT effect," thereby directly "filling the theoretical gap in the micro-mechanisms of environmental regulation in emerging markets."

Adjusting the tone: The original straightforward narrative has been replaced with a more persuasive assertion, highlighting the unique value of this study in connecting environmental economics and corporate finance and providing "China evidence."

These revisions have made the introduction more concise and powerful, aiming to clearly and immediately convey the core value and innovation of this study to the reader. See the introduction for details of the revisions. We believe that the revised version has effectively addressed your concerns. Thank you again for your insightful comments, which were crucial to improving the quality of the manuscript.

Comments 2: [(2) Should the research question or objectives be explicitly stated first in the introduction for greater clarity?]

Response 2: Thank you very much for pointing this out. We agree with this comment. We have now clearly stated the research question or objective in the Introduction. The revisions are as follows: Lines 54-61

Against this backdrop, this study aims to address the following core research question: Does China's EPT promote or inhibit the market value of polluting enterprises? Furthermore, what are the underlying mechanisms and boundary conditions that govern this relationship? To answer these questions, the study sets forth three primary objectives: (1) to empirically test the direct impact of EPT intensity on corporate market value (Tobin's Q); (2) to explore the moderating effects of company-specific factors on the EPT-value nexus; and (3) to examine the specific mediating pathways through which the EPT affects polluting companies market value.

Comments 3: [(3) The authors appear to have utilized non-official database sources. To enhance data credibility, it is recommended to employ more authoritative data sources to avoid unnecessary controversy.]

Response 3: We thank the reviewer for raising this important question regarding data credibility. We would like to clarify that the core data used in our study, particularly those related to the EPT, were carefully collected and cross-verified against the official annual reports released by the sample listed companies. This process ensures the authenticity and reliability of our data. Additionally, the specialized database we employed has been cited extensively in high-quality academic publications. It emphasizes the authoritativeness of data sources and transparency in data processing. Its reputation and frequency of use are comparable to widely recognized databases such as CSMAR, making it a legitimate and acceptable source for academic research. To ensure full transparency, we are fully prepared to share the original data used in our analysis upon request, though the data is limited to Chinese data. We hope this clarification addresses any concerns, and the clearly indicated data sources in our manuscript attest to the authority and usability of the data.

Comments 4: [(4) Could the authors provide the units for all variables used to facilitate readers' assessment of coefficient estimates and scale effects?]

Response 4: Thank you very much for pointing this out. The original units of calculation of all variables are provided to facilitate the reader's evaluation of coefficient estimates and scale effects; see Table 1 for details. Disclaimers in parentheses as follows: Lines 290

Comments 5: [(5) The authors are advised to elaborate on the broader economic implications behind the environmental protection tax's impact on Tobin's Q, building upon the baseline coefficient estimates.]

Response 5: Thank you very much for pointing this out. The benchmark regression results in Table 6 have been further interpreted to provide a broader economic interpretation of the impact of EPT on Tobin's Q. The revisions are as follows:

After controlling the fixed effects of individual enterprise (ID), year and classification of heavy polluting enterprises in benchmark regression Model (14), the estimated coefficient of the core explanatory variable is −0.274***, which proves that EPT has a significant negative impact on Tobin's Q. For every unit increase in EPT, the Tobin's Q value of the enterprise decreases by 0.274 units. This indicates that an increase in EPT intensity is associated with a decrease in Tobin's Q, suggesting that the market perceives higher environmental taxes as a net cost that can dampen a firm's market valuation. So we verified H1.

Economically, this negative correlation may reflect investor concerns about increased compliance costs and potential squeezes on profit margins in the short term. It underscores the direct financial burden that environmental regulations can impose on firms.

However, this initial finding should not be interpreted in isolation. The positive and significant coefficient on ROA highlights that profitability remains a primary driver of firm value. This suggests that if firms can transform environmental pressures into long-term efficiency gains or innovation (as suggested by the Porter Hypothesis [32]), the initial negative impact might be mitigated or even reversed. The results thus present a classic trade-off between regulatory costs and potential efficiency gains, a central debate in environmental economics. The deeper implication underscores a critical challenge encountered by pollution-intensive listed companies within China's green transformation: the internalization of environmental externalities exerts a direct, negative impact on their market valuation. This reflects that their prevailing business models may not have established a sustainable pathway wherein profitability is reconciled with environmental costs.

Comments 6: [(6) The authors are encouraged to provide additional details regarding the design of the placebo test.]

Response 6: Thank you very much for pointing this out. Additional details regarding the placebo study design have been provided. The detailed revisions are as follows: Lines 401-424

4.4.1. Placebo test

To verify that the negative impact of EPT on Tobin's Q observed in the baseline regression was not driven by unobserved confounding factors or randomness, this study employed a rigorous placebo test. The core design follows logic similar to a double-blind clinical trial: if a placebo (in this test, a randomly generated EPT variable) that should theoretically have no effect is applied to a control group (simulated false samples in this test), and a statistically significant effect is still observed, then the genuine effect found in the baseline regression may be considered a statistical fluke.

Specifically, using Stata's permute command, the values of the core explanatory variable EPT were randomly shuffled across all observations while strictly keeping all other variables unchanged. This process was repeated 1,000 times, generating 1,000 simulated datasets. For each dataset, the identical baseline regression model was re-estimated, including all control variables, while absorbing fixed effects for firm identity, year, and whether a firm was heavily polluting, with standard errors clustered at the firm level. After each regression, the estimated coefficient (beta), standard error (se), and degrees of freedom (df) for EPT were recorded, and the corresponding t-statistic and p-value were calculated. This constructed an empirical distribution of the estimates and their statistics under the null hypothesis (EPT truly has no effect).

For visualization and evaluation, the distribution of the simulated t-statistics was plotted and compared against the real t-statistic from the actual regression. Additionally, a scatter plot of p-values against coefficients was used to intuitively display the relationship between the coefficient estimates and their statistical significance. A reference line at p=0.1 helped quickly identify instances of spurious significance in the simulations. The test results are shown in Figure 6 and Figure 7.

Comments 7: [(7) Although passing statistical tests, I remain skeptical about the appropriateness of using lagged terms as instrumental variables.]

Response 7: Thank you very much for pointing this out. We added a second instrumental variable as a supplement. The detailed revisions are as follows: Lines 471-492

Comments 8: [(8) In Table 13, what is the basis for the authors' regional classification?]

Response 8: Thank you very much for pointing this out. The basis for regional division has already been explained. Lines 501-503, Revised to Table 10

Comments 9: [(9) The authors are advised against adopting the controversial mediation effect model.]

Response 9: Thank you very much for pointing this out. We thank you for your valuable comments regarding the mediation effect model. We fully understand the concerns about potential methodological controversies and would like to clarify our analytical approach. In this study, we employed a combination of the traditional stepwise regression method (Baron & Kenny, 1986) and the improved bootstrapping method. Our core analysis is based on the bootstrapping procedure with 1,000 repetitions, which is recommended by studies such as Preacher & Hayes (2008) and Zhao et al. (2010). We consider the improved bootstrapping method advantageous as it does not rely on distributional assumptions and offers higher statistical power.

Our bootstrap test results (Lines 617, revised to Table 13) show that the 95% confidence intervals for the indirect effects of all mediation paths (M1, M2, M3) do not include zero. This provides strong statistical evidence for the existence of the mediation effects. Furthermore, our model controls for firm, year, and industry fixed effects, and we cluster standard errors at the firm level. This helps mitigate concerns regarding omitted variables and serial correlation, thereby strengthening the causal inference based on our observational data.

In summary, we believe our mediation effect analysis is built on a solid methodological foundation that effectively addresses common pitfalls. The consistent and significant results across different mediating variables further reinforce the reliability of our finding that EPT influences firm value through innovation channels.

Finally, we are very open to the reviewer's specific suggestions. Should the reviewer wish for further clarification on any particular aspect of the model or exploration of an alternative method, we would be grateful for the guidance and are willing to conduct additional analyses. If our clarification is deemed reasonable, we look forward to your acceptance of the revised manuscript.

Comments 10: [(10) What additional limitations of this study require clarification?]

Response 10: Thank you very much for pointing this out. After a comprehensive revision, we reiterate our study limitations and revise them as follows: Lines 712-723

This study has several limitations. First, although fixed-effects models were employed, endogeneity issues between EPT and corporate value may not be fully resolved. Second, while innovative attempts were made to measure EPT intensity and patent quality, their accuracy and validity still require further improvement. Third, as the conclusions are based on a sample of Chinese listed companies, their generalizability to non-listed companies or other emerging markets should be approached with caution. Additionally, the mechanism tests primarily focus on innovation pathways and do not comprehensively incorporate other potential mediating variables such as reputation and supply chain management. Finally, the findings support the "compliance cost hypothesis" but do not validate the "Porter hypothesis," which may be constrained by the current stage of market development, its long-term dynamics warrant further investigation. These limitations provide avenues for future research.

3. Additional clarifications

[NO]

1. Summary

Thank you very much for taking the time to review our manuscript and for providing your valuable and insightful comments to enhance the quality of our work. In accordance with your feedback, we have thoroughly and carefully revised the entire manuscript. We have submitted a version with all changes marked and highlighted in yellow for your convenient review. We look forward to receiving your acceptance.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: [First, too long paper! There are so many figures and tables derived from several test analysis, that on the one hand it's good but on the other hand it's comfused! Maybe you can see how you can reduce this excellent, in any case, analysis!]

Response 1: Thank you very much for your recognition of the analytical quality of our paper and for your important suggestions regarding streamlining the length and optimizing the presentation of figures and tables. We fully concur with your view that excessive content can indeed distract readers from the core arguments.

In response to your valuable feedback, we have promptly implemented the following measures to enhance conciseness:

Streamlined Figures and Tables: We have moved a series of non-essential robustness checks and auxiliary analyses to the appendix. The main text now retains only the most critical benchmark regression results, core figures/tables for mechanism tests, and robustness checks that directly impact the conclusions.

Consolidated Text: We have refined the Discussion section by merging paragraphs with redundant explanations, making the logical argument more compact and directly focused on the research questions. Unnecessary background and explanatory text have been removed.

Sharpened Focus: We have thoroughly reviewed the entire manuscript to ensure every section directly contributes to answering the core research questions, eliminating analyses that, while related, diverted focus from the main narrative.

Through these revisions, we believe the paper's structure is now clearer and its key points more prominent, effectively guiding readers to understand the core findings and contributions of the research. We deeply appreciate your insightful comments, which have been crucial for improving the manuscript's quality. Details of the revisions can be found in the marked-up version of the manuscript, and we look forward to your further review and acceptance.

Comments 2: [Second, I would like to include a new section, called "Previous studies analysis" and also at the end of this section to present a table, with author/s, goals, methods, variables and main conclusions]

Response 2: We sincerely thank you for this constructive suggestion regarding the addition of a dedicated "Previous Research Analysis" section with a summary table. We agree that such a table could provide a clear overview of the existing literature.

Upon careful consideration, we have decided to maintain the current structure of the literature review. Our primary reason is that our article is an empirical study, and its core contribution lies in the novel evidence and mechanistic tests we present. While we have already discussed prior studies in detail within the existing literature review, adding a comprehensive summary table would significantly expand the narrative length, potentially shifting the focus away from our original empirical analysis and findings. Our goal is to keep the manuscript concise and sharply focused on its empirical contributions.

We believe that the current integrated discussion within the literature review sufficiently contextualizes our study within the broader academic conversation without creating redundancy. We hope this explanation clarifies our rationale, and we thank the reviewer again for their thoughtful input, which has helped us refine the paper's focus.

3. Additional clarifications

[NO]

1. Summary

Thank you very much for taking the time to review our manuscript and for your valuable and insightful feedback, which helped us improve it. We have resubmitted this second version, with all changes highlighted in red, distinguishing them from the first round of yellow highlights, for your convenience. We look forward to your acceptance of this second round of revisions.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: [1- Not all grammatical issues have been corrected. A thorough, complete proofread of the manuscript is still needed.]

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, based on your feedback on our first round of revisions, we did proofread and revise the entire manuscript again for issues like grammar and logic. See the red highlighted section in detail.

Comments 2: [2- Although Table 3 has improved in some respects, new problems have emerged. The version included in the manuscript does not look correct. Please ensure that headings, e.g., Explained variable, are placed in a separate row for clarity.]

Response 2: Thank you very much for pointing this out. We agree with you. We have, accordingly, revised to emphasize this point. The revisions are as follows:

Table 1. Variable statistics and explanations.

Comments 3: [3- The axes labels in Figure 5 remain unreadable and need to be improved.]

Response 3: Thank you very much for pointing this out. We have, accordingly, revised to emphasize this point. The revisions are as follows:

Comments 4: [4- I am not conviced by the response to my Comments 4 in the previous round.  The reply is speculative and does not provide a solid scientific justification. If addressing this comment is beyond the scope of the paper or the authors are unsure how to proceed, I recommend avoiding speculative explanations. Instead, it would be more appropriate to acknowledge this as a limitation of the paper and suggest it as an area for future research.]

Response 4: Thank you very much for pointing this out. We agree with you. We have, accordingly, revised to emphasize this point. We adopt your suggested approach, acknowledge this as a limitation of the paper, and suggest it as a direction for future research. Based on an appropriate description of the data trend, we are more precise about the specific coordinate axes. Polluting companies and the 2018 EPT are bound to be affected in the short term. This is in line with common sense and intuition. In theory, it is also consistent with compliance costs, cost pressure and expected management effects. Finally, we will take this as a direction for future in-depth research. The revisions are as follows: Lines 309-316

Figure 5 depicts the temporal distribution of Tobin's Q for polluting companies from 2012 to 2022. The X-axis represents the year, the Y-axis indicates the sample size of polluting companies in this study, and the Z-axis denotes the values of Tobin's Q. Overall, Tobin's Q exhibits a fluctuating but generally upward trend, with a pronounced decline following the implementation of the 2018 EPT policy. This trajectory reflects the initial impact of the EPT policy on the Tobin's Q of polluting companies and their subsequent adaptation process. The observed trend provides preliminary support for the documented negative impact of the 2018 EPT policy on Tobin's Q in this study.

5.4. Limitations and Future Directions

This study has several limitations. First, although fixed-effects models were employed, endogeneity issues between EPT and corporate value may not be fully resolved. Second, while innovative attempts were made to measure EPT intensity and patent quality, their accuracy and validity still require further improvement. Third, as the conclusions are based on a sample of Chinese listed companies, their generalizability to non-listed companies or other emerging markets should be approached with caution. Additionally, the mechanism tests primarily focus on innovation pathways and do not comprehensively incorporate other potential mediating variables such as reputation and supply chain management. In summary, the findings provide some support for the "compliance cost hypothesis." However, under the short-term effects of the EPT policy, the study fails to validate the innovation compensation mechanism of the "Porter Hypothesis." This hypothesis may be constrained by the current stage of market development, and its long-term dynamics warrant further investigation. Future research could explore how to optimize innovation strategies to counteract this negative impact, such as by focusing on high-value innovations or enhancing investor relations.

3. Additional clarifications

[No]

1. Summary

Thank you very much for taking the time to review our manuscript and for your valuable and insightful feedback, which helped us improve it. We have resubmitted this second version, with all changes highlighted in red, distinguishing them from the first round of yellow highlights, for your convenience. We look forward to your acceptance of this second round of revisions.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: [However, please check whether there is an editorial error in the header of column (21) in Table 8: both the dependent variable and the independent variable are labeled as Lag1.EPT? Additionally, I recommend abandoning the use of lagged terms as instrumental variables. Further clarification and justification are needed regarding the relevance and exogeneity of the instrumental variables. It is also suggested to indicate the column numbers corresponding to the results in the text for reader convenience.]

Response 1: Thank you for pointing this out. We agree with this comment. We have checked the title of column (21) in Table 8 for an editorial error (The modified version has deleted this instrumental variables). Furthermore, we agree with your suggestion and have abandoned the use of lagged terms as instrumental variables. The relevance and exogeneity of the instrumental variables have been further clarified and demonstrated. Furthermore, we have indicated the corresponding column numbers in the text for the convenience of readers. Please see the red highlighted parts in the manuscript for detailed revisions.

Comments 2: [Regarding the mediation effect section, I strongly recommend that the authors use theoretical arguments to substantiate the latter part of the mediation effect. This suggestion is provided for the authors' consideration.]

Response 1: Thank you for pointing this out. We agree with this comment. Regarding the mediation effect section, we accept your strong suggestion and return to the second half of the paper, which uses theoretical arguments to confirm the mediation effect. The detailed revisions are as follows:

Lines 455-486

4.4.4. Endogeneity test

In order to ensure the consistency of estimation, avoid pseudo-regression, and identify and correct data problems, this study uses the instrumental variable method (IV-2SLS) for endogeneity test. Referring to Cai et al. [71], we construct an interaction term as an instrumental variable: the product of the river density in the city where a company is located and the water pollution intensity index of its industry (RLP). The validity of this instrumental variable is based on the following logic: cities with dense river networks are more sensitive to water pollution, and this sensitivity disproportionately falls on industries that are inherently high in water pollution intensity. Consequently, this interaction term strongly predicts the actual environmental tax burden faced by companies. Meanwhile, river density is a natural geographical feature, and industry pollution intensity is an exogenous technological characteristic; their interaction term is unlikely to affect the market value of individual companies through any causal channel other than influencing the environmental tax burden. Therefore, this meets the selection criteria for instrumental variables. The regression results are shown in Table 8.

Table 8. IV-2SLS regression results.

Notes: We report robust standard errors in parentheses and cluster robust standard errors at the individual level. *** p<0.01, ** p<0.05, * p<0.1

Source: calculated by the authors

In column (21) of Table 8, the regression coefficient of the instrumental variable RLP on EPT is 0.218***, indicating a statistically significant positive effect of RLP on EPT and confirming a strong correlation. The Kleibergen-Paap Wald F-statistic of 29.766*** significantly exceeds the Stock-Yogo critical value (16.38 at the 10% level), while the CD Wald F-statistic of 96.226 also surpasses the critical threshold. These results strongly reject the null hypothesis of weak identification, further validating the strength of the instrumental variable. Additionally, the LM test yields a statistic of 42.24***, indicating the presence of endogeneity and justifying the use of the instrumental variable approach. In the second-stage regression presented in column (22), the coefficient of EPT on Tobin's Q is −1.531***, which remains significantly negative at the 1% level. Therefore, this study passes the endogeneity test, proves the effectiveness of the instrumental variables, and demonstrated the robustness of the benchmark regression results.

Lines 673-700

Finally, this study found that the innovation compensation mechanism of Porter's hypothesis was not fully supported in this study. This is in stark similarity to the conclusion of the innovation path proposed by [83], so we reject H4. Under the regulation of China's 2018 EPT, polluting companies significantly increase R&D investment and strive to enhance the quality of patent applications and grants to meet compliance standards and ensure operational continuity. However, in the short term, such externally pressured innovation acts as a negative mediating channel, where innovation costs dominate, thereby suppressing corporate market value. The core theoretical mechanism is as follows: First, EPT-induced innovation exhibits a defensive nature and cost attribute, as resources are heavily allocated to end-of-pipe treatments or process improvements. While such investments improve innovation quality, they directly crowd out short-term profits and are perceived by investors as financial burdens due to their inability to swiftly translate into market revenue. Second, market expectations and information asymmetry exacerbate this effect. When investors observe surging R&D expenditures, they are more likely to interpret them as indicators of severe compliance costs and operational risks rather than assurances of future competitiveness, leading to valuation downgrades. Thus, although the EPT successfully stimulates both stages of innovation input and output, the accompanying high costs, resource crowding-out, and negative market signals collectively contribute to a negative relationship between innovation activities and corporate market value, revealing the potential short-term pains in the realization of the innovation compensation effect posited by the Porter Hypothesis. In summary, the negative impact of the EPT on Tobin’s Q through innovation mediation reflects the combined effects of cost pressure, market expectations, and innovation lag. This underscores the importance of designing environmental policies that account for polluting companies’ financial capacity and innovation types to avoid excessive short-term costs. Simultaneously, polluting companies should communicate the long-term value of their innovations to improve market expectations.

3. Additional clarifications

[No]