The Impact of Government and Public Dual-Subject Environmental Concerns on Urban Haze Pollution: An Empirical Research on 279 Cities in China
Round 1
Reviewer 1 Report
The article presents quite interesting mathematical calculations based on regression. Although the calculations done are definitely overvalued, and they are irrelevant to the conclusions presented.
1) There is not enough information on what can actually be read from the model, the current conclusions (and hypothesis) are obvious, and there is no need for any research to formulate them.
2) It should be presented the hard data (charts/trends) on the pollutions in analysed years. Do not to express the admiration for the actions of the Chinese government, as they are still insufficient. Present them in relation to other countries.
3) The way of measuring environmental policy uncertainty is disputable - as changes can be insignificant or radical. The authors assume that lower number of policy updates leads to a reduction in pollution, which is absurd.
4) Similarly, it is questionable to measure government environmental concern and public environmental concern by the number of appearances of selected keywords. It is enough just to reduce the number of keywords and the pollution increases.
5) In the introduction / literature review part, the authors should relate their research process to other models presented to justify the need to assessment and compare results.
6) The presentation of the results can be limited to the final with lagged variable, best model - from which it is worth drawing the conclusions. And the research process can only be described.
7) It is good practice to describe the limitations and point the direction of future research.
Selected editorial errors:
1) Capital letter BAKER S R，BLOOM N，DAVIS S J．
2) The use of the phrases should be more professional with less emotional charge and supported by research: ‘the world's public enemy’, ‘been attacked by haze pollution’, ‘the haze pollution will be effectively controlled’
3) Unfortunate wording in the introduction, suggesting a positive value of haze pollutions. ‘Government environmental concern and public environmental concern have a significant negative impact on urban haze pollution.’
4) China Eco-Environment status Bulletin - reference is needed
5) Unify the citations
‘Wu Wenqi found that the public opinion of the new media network has a deterrent and supervisory effect on corporate pollution, so it has a significant positive impact on reducing haze pollution.[18]. Long, F et al.(2022)’
6) Some contradictory: ‘But few scholars define and analyze the government environment concern.’ ‘At present, many scholars have done a lot of research on the relationship between government environmental concern, public environmental concern, and environmental pollution.’
7) In one of the tables, it is worth explaining the abbreviations to make it easier to analyze the tables.
Author Response
Dear Reviewers:
On behalf of my co-authors, we thank you very much for giving us an opportunity to revise our manuscript. You and reviewers’ comments are all of great importance to our manuscript entitled " The impact of government and public dual-subject environmental concerns on urban haze pollution: An empirical research on 279 cities in china (1813955)". Those comments are all valuable and have contributed a lot to improve the quality of our article. Based on your suggestions, we write a point-by-point response letter to you and reviewers to acknowledge your helps and denote where we made revisions. Revised portions are marked in color with underline in the paper.We would like to express our great appreciation to you and reviewers for comments on our paper. Looking forward to hearing from you.
With regards,
Dianyuan Ma
Point: The article presents quite interesting mathematical calculations based on regression. Although the calculations done are definitely overvalued, and they are irrelevant to the conclusions presented.
Response : Thanks for your comment, it is important to improve the quality of this article, especially the description of the conclusions.We link the core results of the model to the conclusions based on your suggestions.
6.1. Research result
This paper took 279 cities in China from 2011 to 2019 as the research sample, using a fixed-effect regression model to investigate the effect of government environmental concern and public environmental concern on urban haze pollution. Overall, the main conclusions of this study are drawn as follows:
(1) Government environmental concern and public environmental concern have a significant negative impact on urban haze pollution. The results were still valid after a series of robustness tests and controlling for endogenous problems.
(2) Further research found that dual-subject environmental concerns have a stronger negative effect on urban haze pollution in areas where there is a low level of Internet development and in western regions.
(3) Through the test of the intermediary mechanism, it was observed that between government environmental concern and haze pollution, the mediating effect of environmental policy uncertainty was 0.712, and the mediating effect of capital factor mismatch was 0.015. Between public environmental concern and haze pollution, the mediating effect of environmental policy uncertainty was 0.698, and the mediating effect of capital factor mismatch was 0.017. Therefore, in terms of policy, the role of the government is greater than that of the public. In resource allocation, the role of the public is greater than that of the government. In general, the mediating role of environmental policy is greater than the allocation of capital factors. Therefore, strengthening the effective interaction between the government and the public will help China reach the standards set by the World Health Organization as soon as possible.
Point 1:There is not enough information on what can actually be read from the model, the current conclusions (and hypothesis) are obvious, and there is no need for any research to formulate them.
Response 1: Thanks to your suggestion, We have added a description of the results. We provide a brief introduction here.
China is a large country with a vast territory, and cities in different locations have great differences in resource endowment, factor rationing, and policy implementation [30]. Regression analysis based on an overall city sample may mask regional differences. Therefore, this paper divided the sample into eastern cities, central cities and western cities, in order to investigate the differential impact of government environmental concern and public environmental concern regarding haze pollution. The results are shown in Table 8.
The coefficients between government environmental concerns and haze pollution were -0.230 (p<0.01), -0.359 (p<0.01), and -0.596 (p<0.01) in eastern, central, and western cities, respectively. The coefficients between public environmental concerns and haze pollution were -0.236 (p<0.01), -0.243 (p<0.01), and -0.262 (p<0.05) in eastern, central, and western cities, respectively.
The regression results showed that, in the eastern city, the coefficient between government environmental concerns and public environmental concerns regarding haze pollution was lower than midwest.
Why use a model to explain the relationship between variables, here are the reasons:
(1)In order to quantify the impact of government and public dual-subject environmental concerns on haze pollution.
(2)In order to find out the difference of dual-subject environmental concerns on haze pollution in cities with different characteristics (Different Internet Development Levels and Different Geographical Locations)
(3)To test whether the intermediary mechanism exists.
(4)In order to detect which intermediary mechanism is more effective.
Point 2: It should be presented the hard data (charts/trends) on the pollutions in analysed years. Do not to express the admiration for the actions of the Chinese government, as they are still insufficient. Present them in relation to other countries.
Response 2: Thank you for your valuable comments, this paper adds Figure 1 to the Introduction section.
Figure 1. Comparison of urban haze in China with WHO standards from 2011 to 2021
Although compared with 2011, China has made some progress in control, the haze problem is still serious (see Figure 1).
Point3: The way of measuring environmental policy uncertainty is disputable - as changes can be insignificant or radical. The authors assume that lower number of policy updates leads to a reduction in pollution, which is absurd.
Response 3: Thank you for your comment, this article makes the following description.
(1)On the Measurement of Environmental Policy Uncertainty
Baker et al[48] (2016) developed a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Considering that the explanatory variables of this paper have selected word frequency and Brandon Julio et al(2016) pointed out that new and different planning approaches and policy development can help reduce uncertainty in climate change policy. Therefore, this study uses the number of revisions and releases of environmental protection standards in the "Twelfth Five-Year Plan for National Environmental Protection Standards" and the "Thirteenth Five-Year Plan for National Environmental Protection Standards" to measure environmental policy uncertainty.
As experts say, environmental policy uncertainty is not only affected by policies, but also by changes in officials, emergencies, etc. However, some data have not been obtained for the time being. Therefore, this paper mentions the issue of environmental policy uncertainty indicators in the research shortage.
It still has the following shortcomings: (2)The measurement of environmental policy uncertainty does not take into account the policy uncertainty caused by changes in officials, etc.
(2) The conclusion that lower number of policy updates leads to a reduction in pollution is a typo.
In Table 5, the regression coefficient of environmental policy uncertainty and haze pollution is -1.552, (P<0.01). In Table 6, the regression coefficient of environmental policy uncertainty and haze pollution is -1.568, (P < 0.01). The research results all prove that with the revision and increase of the policy (the uncertainty of environmental policy is reduced), the haze pollution is decreasing. Consistent with Chunling Yu. pointed that the implementation of the New Law correlates with reduction of PM2.5, SO2 concentrations and Air Quality Comprehensive Index.
Point 4:Similarly, it is questionable to measure government environmental concern and public environmental concern by the number of appearances of selected keywords. It is enough just to reduce the number of keywords and the pollution increases.
Response 4: Thank you for your comment, this article makes the following description.
(1)Representing environmental concerns by word frequency analysis is a routine method. Chen et al. (2016)[47] used the ratio of the total number of words in five terms, including “environment”, “environmental protection”,“pollution”, “emission reduction “and “energy consumption”, to the total number of words in the full text of the government work report as a proxy variable for government environmental governance. Pan xuwen et al(2022) [48]counted the frequencies of words related to government environmental governance such as "environmental protection", "environmental governance" and "PM2.5", and calculates the ratio of the total frequency of the above words to the total word frequency of the full text of the government work report, indicating that the government environmental concern.
The key words of the government report can convey the key issues that the government is concerned about.
(2)It is also common to use the Baidu Index in the measurement of public environmental concerns. Long, F et al.(2022) constructed the PEC variable by searching the Baidu Search Index of environmental terms. The search index can capture the “active” portion of public concern, that is, individuals voluntarily spending time to search for environmental information online. To measure investor attention,Mengmeng Guo et al(2020) manually collected the Baidu Index of environment-related keywords from index.baidu.com. Wenli Li(2021) choosed six keywordsd“雾霾” (haze),“灰霾” (dust-haze), “空气污染” (air pollution), “大气污染” (atmospheric pollution), PM2, 5, and PM10 dare selected as the initial seeds, to generally portray the public concern.
(3)Considering the operability of data measurement, this paper chooses word frequency analysis method. Indeed, as expert say, the use of word frequency analysis is controversial. Therefore, this paper mentions in the lack of research that the measurement of environmental attention by word frequency analysis is not rigorous enough, and hopes to establish a more scientific measurement of environmental attention in future studies.
Point 5: In the introduction / literature review part, the authors should relate their research process to other models presented to justify the need to assessment and compare results.
Response 5: Following expert advice, we have strengthened the description of the model in the literature review section.
For example, Huang, J.-T. (2018) took 30 provinces in China from 2008 to 2013 as a research sample, using the spatial Durbin model, and found that government spending on environmental protection can effectively reduce sulfur dioxide emissions [16].
Wu Wenqi et al. (2021) used a dynamic spatial econometric model to find that the public opinion of new media networks has a deterrent and supervisory effect on corporate pollution, and has a significant positive effect on reducing haze pollution [20]. Long, F et al. (2022) use a fixed-effects model to find that public environmental issues can mitigate differences in urban and rural pollution intensity by influencing government regulatory behavior [21].
Drawing on the research of Long, F et al. (2022) [21], based on theoretical mechanisms and research hypotheses, to study the effects of government and public dual-subject environmental concerns on haze pollution in China, the following panel data model is constructed.
Point 6: The presentation of the results can be limited to the final with lagged variable, best model - from which it is worth drawing the conclusions. And the research process can only be described.
Response 6: Thank you for your comment, this article makes the following description.
- The lag item of adding variables in the article is to demonstrate the robustness of the results.
There may be a time lag effect between the government and the public starting to pay attention to haze and affecting haze pollution. Therefore, this paper used the core explanatory variables government environmental concern and public environmental concern lagging by one period to introduce into the regression model. The results are shown in the columns (3) and (4) of Table 3. The regression results were still significantly negative at the 1% level. This is consistent with the main results, which further supports the robustness of the core conclusions of the article.
- Section 5 of the article has a dedicated discussion of the results.
5.Discussion
5.1. Analysis of the direct effect
First, there was a significant negative correlation between government environmental concerns and urban haze pollution during the study period. On the one hand, the government will actively take measures to control haze pollution due to its responsibilities and assessment needs [23]. On the other hand, the government has an authoritative influence on environmental governance.
Second, public environmental concerns can significantly reduce urban haze. On the one hand, haze pollution is highly visible and harmful, and it is easy to attract public attention. On the other hand, the development of Internet technology has also become an important basis for public participation in environmental governance, enabling the public to quickly respond to behaviors that damage the environment [20]. Therefore, the government should actively carry out environmental education and training activities, and establish environmentally friendly schools and communities to enhance the public's awareness of the environment and green consumption, as well as to cultivate environmental protection professionals.
Third, in places with a low level of Internet development, the dual-subject environmental concerns of the government and the public have a more significant impact on urban haze pollution. This shows that the development of the Internet has provided technical support for the government and the public to pay attention to the environment and environmental supervision, but the main cause of environmental concern is environmental pollution itself. In places with a high number of households with Internet access, Internet development can promote the industrial green total factor ratio through industrial structure upgrading and technological innovation [57], which will help reduce haze pollution. Therefore, the development of the Internet has weakened the role of environmental concerns.
Fourth, in the western region, the dual-subject environmental concerns of the government and the public have a stronger impact on haze pollution. On the one hand, the eastern region has a high level of development and environmental regulation, and at the same time, local governments can speed up urban economic transformation through technological innovation [58], which can effectively solve environmental problems. Therefore, the impact of environmental concerns on haze pollution has been weakened to a certain extent. On the other hand, the resource curse effect mainly occurs in inland cities in the Midwest [59]. In addition, compared with the eastern region, the central and western regions have weaker environmental regulations, and polluting enterprises will choose the central region or the western region as the destination of migration. If this situation continues, the central and western regions will likely become a "sanctuary for pollution" for companies [60]. The transfer of polluting enterprises has caused serious environmental problems in the central and western regions and is more likely to cause environmental concerns. Therefore, the suppression levels of the two environmental concerns on haze pollution show the phenomenon of western region > central region > eastern region. The government should implement a strict enterprise access system for less developed regions, raise the entry threshold for highly polluting, high-emission, and high-energy-consumption enterprises; eliminate the existence of "pollution shelters"; and encourage enterprises to adopt technology, transformation, and other positive ways to achieve the decoupling of the economy and environmental pollution.
5.2. Analysis of the intermediary effect
First, dual-subject environmental concerns can affect urban haze pollution by reducing environmental policy uncertainty. The government’s role is more influential than the public role. The main reason for this is that the government is the main body in formulating policies and has absolute authority and credibility in formulating policies. The public reduces the asymmetry of information by means of petitions, complaints, etc., and also contributes to the formulation of environmental policies, but mainly plays an auxiliary role. The revision of environmental policy can help to control air pollution [61]. The government should broaden and optimize the channels for the public to give feedback on environmental information; strengthen the effective screening of public feedback information with the help of Internet technology; conduct on-the-spot verification, timely response, and accurate monitoring; punish violations as required; and quickly revise relevant regulations or introduce new corresponding regulations to ensure the comprehensiveness and accuracy of regulations [62].
Second, dual-subject environmental concerns can affect urban haze pollution by reducing environmental resource allocation. The role of the public is greater than that of the government. A possible reason for this is that the main body of enterprises is profit oriented. In order to gain a larger market share, they will cater to the public's green consumption preferences and actively carry out green and environmental protection behaviors to enhance the corporate image. Additionally, the way the public votes regarding money makes it easier for money to be allocated to environmental protection projects [24][45].
Point 7: It is good practice to describe the limitations and point the direction of future research.
Response 7: Methods for measuring environmental concerns and environmental policy uncertainty illustrate deficiencies
Based on existing research, we will consider enriching measurement methods for environmental concerns, and environmental policy uncertainty. And the spatial effect of environmental concerns on environmental pollution in future research to improve the comprehensiveness and reliability of the estimated results.
Selected editorial errors:
Point 1: Capital letter BAKER S R，BLOOM N，DAVIS S J．
Response 1: This question has been revised as follows:
Baker et al.(2016) developed a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency [50]
Point 2: The use of the phrases should be more professional with less emotional charge and supported by research: ‘the world's public enemy’, ‘been attacked by haze pollution’, ‘the haze pollution will be effectively controlled’
Response 2: This question has been revised as follows:
The introduction part has been reorganized. We cut down on emotional vocabulary and got professionals to proofread our English.
Point 3: Unfortunate wording in the introduction, suggesting a positive value of haze pollutions. ‘Government environmental concern and public environmental concern have a significant negative impact on urban haze pollution.’
Response 3: The introduction part has been reorganized.
Point 4: China Eco-Environment status Bulletin - reference is needed
Response 4: This question has been revised as follows:
Endnotes added at the end of the article. See more details at: https://www.mee.gov.cn/hjzl/sthjzk/zghjzkgb/
Point 5: Unify the citations ‘Wu Wenqi found that the public opinion of the new media network has a deterrent and supervisory effect on corporate pollution, so it has a significant positive impact on reducing haze pollution.[18]. Long, F et al.(2022)’
Response 5: As suggested, we have unified the application.
Long, F et al. (2022) use a fixed-effects model to find that public environmental issues can mitigate differences in urban and rural pollution intensity by influencing government regulatory behavior [21]. The second view is that public environmental concerns cannot impact environmental pollution. Chao, H et al. (2016) used the number of letters and visits to express public appeals. The study found that public requests will not lead to an increase in environmental regulation investment, so environmental pollution cannot be reduced [22].
Point 6: Some contradictory: ‘But few scholars define and analyze the government environment concern.’ ‘At present, many scholars have done a lot of research on the relationship between government environmental concern, public environmental concern, and environmental pollution.’
Response 6: We have made a logical unification, deleted ‘ ‘But few scholars define and analyze the government environment concern.’
Point 7: In one of the tables, it is worth explaining the abbreviations to make it easier to analyze the tables.
Response 7: All variables mentioned in the table are fully described in Table 1. As follows:
Table 1. Statistical description of variables.
|
|
Variable |
Definition |
Obs |
Mean |
Std. Dev. |
Min |
Max |
|
Dependent variable |
Haze |
Urban haze pollution concentration |
2415 |
6.180 |
6.260 |
0.220 |
71.000 |
|
Independent variable |
GEC |
Government environment concern |
2415 |
4.110 |
1.100 |
0.000 |
7.340 |
|
PEC |
Public environment concern |
2415 |
3.430 |
0.490 |
0.000 |
4.710 |
|
|
Intermediary variable |
EPU |
Environmental policy uncertainty |
2415 |
7.079 |
0.315 |
6.800 |
7.440 |
|
CM |
Capital misallocation |
2415 |
0.700 |
0.240 |
0.010 |
2.880 |
|
|
Control variable |
PCEC |
Per capita energy consumption |
2415 |
0.510 |
3.750 |
0.010 |
166.630 |
|
IS |
Industrial structure |
2415 |
0.450 |
0.140 |
0.040 |
0.990 |
|
|
Dust |
Emission of industrial flue dust |
2415 |
9.720 |
1.160 |
4.030 |
15.460 |
|
|
Green |
Greening level |
2415 |
39.940 |
10.100 |
0.360 |
376.580 |
|
|
Traffic |
Traffic condition |
2415 |
1614.920 |
3101.620 |
29.000 |
35809.000 |
|
|
ID |
Level of industrial development |
2415 |
1272.260 |
1505.400 |
20.000 |
11042.000 |
|
|
Edu |
Education level |
2415 |
9.770 |
17.010 |
0.020 |
120.000 |
|
|
STR |
Sewage treatment rate |
2415 |
90.000 |
10.540 |
24.000 |
100.000 |
Author Response File: 
Author Response.pdf
Reviewer 2 Report
I can not judge about english language and style. please recheck the english language.
Author Response
Dear Reviewers:
On behalf of my co-authors,we thank you very much for giving us an opportunity to revise our manuscript. You and reviewers’ comments are all of great importance to our manuscript entitled "The impact of government and public dual-subject environmental concerns on urban haze pollution: An empirical research on 279 cities in china (1813955)". Those comments are all valuable and have contributed a lot to improve the quality of our article. Based on your suggestions, We have invited professionals to proofread and polish the English.We would like to express our great appreciation to you and reviewers for comments on our paper. Looking forward to hearing from you.
With regards,
Dianyuan Ma
Point 1: I can not judge about english language and style. please recheck the english language.
Response 1: Thank you for your comment, we have invited professional people to proofread and polish the English.
Reviewer 3 Report
Comments of Article - The impact of government and public dual-subject environmental concerns on urban haze pollution: An empirical research on 279 cities in china
Minor comments:
1. Year of reference missing – like
Line 223: Guo, M.et al. found that the higher
Line 271-272: the research of 271 van Donkelaar Aaron et al.[44]
2. Capitalize first alphabet (Line 260) sample selection and data processing
3. Decimals to third places may be avoided (Table 1)
4. Line 318: Year must be mentioned for – ‘public data from Dalhousie University in Canada’
Author Response
Dear Reviewers:
On behalf of my co-authors, we thank you very much for giving us an opportunity to revise our manuscript. You and reviewers’ comments are all of great importance to our manuscript entitled " The impact of government and public dual-subject environmental concerns on urban haze pollution: An empirical research on 279 cities in china (1813955)". Those comments are all valuable and have contributed a lot to improve the quality of our article. Based on your suggestions, we write a point-by-point response letter to you and reviewers to acknowledge your helps and denote where we made revisions. Revised portions are marked in color with underline in the paper.We would like to express our great appreciation to you and reviewers for comments on our paper. Looking forward to hearing from you.
With regards,
Dianyuan Ma
Point 1.Year of reference missing – like
Line 223: Guo, M.et al. found that the higher
Line 271-272: the research of 271 van Donkelaar Aaron et al.[44]
Response 1: Thank you for your comment, the modifications are as follows:
Guo, M.et al.(2020) found that the higher the public environmental concern, the lower the return on the stock of polluting companies [45].
referred to the research of van Donkelaar Aaron et al. (2019) [46],
Point 2. Capitalize first alphabet (Line 260) sample selection and data processing
Response 2: This question has been revised as follows:
3.2. Sample selection and data processing
Point 3: Decimals to third places may be avoided (Table 1)
Response 3: Thank you for your comment, this article makes the following description.
Thank you for your comment, this article makes the following description.
Point 4: Line 318: Year must be mentioned for – ‘public data from Dalhousie University in Canada’
Response 4: This question has been revised as follows:
public data from Dalhousie University in Canada (2011~2019)
Author Response File: Author Response.pdf
