Bayesian Vector Autoregression Analysis of Chinese Coal-Fired Thermal Power Plants

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. The use of Bayesian Vector Autoregression (BVAR) by the authors to analyze carbon emissions performance represents a critical aspect. The dependence on correct model specification underlines the importance of chosen endogenous variables (carbon emissions, energy consumption, power generation) adequately representing underlying economic relationships.

2. The claim that data comes from the Chinese Statistical Yearbook and other official sources raises concerns regarding data reliability, temporal consistency, and integrity. A discussion about the potential issues related to carbon emissions and energy consumption data is necessary to validate the findings.

3. The reported simulation results (Table 1) suggest that the interpretation of specific coefficients, particularly those near zero, may be misleading. The negative coefficient for energy consumption in relation to carbon emissions indicates the potential for inconsistency that necessitates broader contextual exploration.

4. The lack of explicit discussion about the assumptions made in the BVAR approach, such as the stationarity of time series data, indicates a limitation. The non-stationarity of data may result in spurious correlations.

5. The assertion that 20,000 Monte Carlo simulations were performed raises questions about their sufficiency to achieve convergence. The provision of convergence diagnostics is critical for ensuring robust estimates.

6. The mention of using fixed and random effects to test the robustness of results shows an area for improvement. The execution of additional robustness checks, such as examining alternative model specifications and testing various subsets of data, would enhance the reliability of findings.

7. The report of credible intervals without extensive discussion of their implications represents a gap. An understanding of the significance of these intervals in relation to policy implications, such as uncertainty in emissions targets, would benefit the discussion.

8. The claim of robust identification of feedback relationships between energy consumption, economic growth, and carbon emissions suggests a need for exploration.

9. The primary focus on coal-fired power plants raises the need for further exploration of alternative energy sources and their relationship with fossil fuel usage. The dynamics of the transition to renewable energy concerning carbon emissions should be emphasized.

10. The examination of trends, cycles, and structural breaks during the significant time period (2005–2017) may yield essential insights into the evolution of China’s energy policies and their influence on emissions.

11. The suggestions for various policy recommendations imply the necessity for further exploration of potential barriers to implementing these policies. A focus on socio-economic, technical, and governance challenges would provide a realistic perspective on achieving carbon neutrality goals.

12. The issues regarding corruption and management practices in fossil-fuel electricity generation companies are significant but somewhat abruptly introduced. A more structured approach to discussing these challenges would enhance the narrative. Consider providing a distinct subsection that specifically addresses these governance issues, their implications for emissions performance, and how they can be mitigated.

13. In the literature review, while it lists various studies and their findings, a more thorough analysis of how these studies contrast or align with the current findings would be beneficial.

14. Please add section for the conclusion and future work.

 

 

 

 

 

 

 

 

 

Comments on the Quality of English Language

Extensive revisions required. 

Author Response

Please see the attachment. 1.The use of Bayesian Vector Autoregression (BVAR) by the authors to analyze carbon emissions performance represents a critical aspect. The dependence on correct model specification underlines the importance of chosen endogenous variables (carbon emissions, energy consumption, power generation) adequately representing underlying economic relationships. Response: Thank you very much for bringing such valuable comment back to us. We appreciate your comment and this can improve our study. The dependence underlines the importance of carbon emissions, energy consumption, power generation. 2. The claim that data comes from the Chinese Statistical Yearbook and other official sources raises concerns regarding data reliability, temporal consistency, and integrity. A discussion about the potential issues related to carbon emissions and energy consumption data is necessary to validate the findings. Response: Thank you again. We are sorry that we did not indicate the study setup clearly in the original manuscript. In this revision, we add another subsection called “Data” to illustrate your concern regarding the prices selection and data sources. Specifically, it is described as below: “To resemble the economic and environmental effects under various operations, this study accommodates different endogenous variables to examine how the changes in energy consumption and power generation may alter the performance of carbon emissions. The value from energy consumption ,power generation and emission reduction are based on the official sources. The basic calculation of such parameters can be found from our previous studies (Yu and Zhang,2022, Zhang et al.,2016). In this study the variables are further modified to reflect the potential climate-induced impacts on economic activities.” 3. The reported simulation results (Table 1) suggest that the interpretation of specific coefficients, particularly those near zero, may be misleading. The negative coefficient for energy consumption in relation to carbon emissions indicates the potential for inconsistency that necessitates broader contextual exploration. Response: Thank you for your valuable comment. According to the table, it is suggesting that the interpretation of specific coefficients which are near zero, those are wrong. The negative coefficient for energy consumption in relation to carbon emission indicates the potential for inconsistency. But the model of Bayesian vector autoregressions is able to precisely improve the discriminating power and comparability of intertemporal observations. It incorporates the prior knowledge or results of a previous model, can be used to inform the current model. That means we need to provide some proof in robust exploration to further elaborate this point. 4. The lack of explicit discussion about the assumptions made in the BVAR approach, such as the stationarity of time series data, indicates a limitation. The non-stationarity of data may result in spurious correlations. Response: Thank you very much for bringing such valuable comment back to us. The Bayesian vector autoregression model has an advantage, in that the technique incorporates informative priors, so that results of a previous model, can be used to inform the current model. The discussion about the stationarity of time series data and non-stationarity have been clearly addressed in the “Methodology” section. Thank you for your comment. 5. The assertion that 20,000 Monte Carlo simulations were performed raises questions about their sufficiency to achieve convergence. The provision of convergence diagnostics is critical for ensuring robust estimates. Response: Thank you again. 20,000 is the number of retained draws per chain. The default value is20,000.we use some value in Bayesian vector autoregression. We use diagnostics function too. These function will contain estimates of the MCMC standard error, as well as of the inefficiency factor, per parameter. The estimates indicate that these are not sufficient to achieve convergence. 6. The mention of using fixed and random effects to test the robustness of results shows an area for improvement. The execution of additional robustness checks, such as examining alternative model specifications and testing various subsets of data, would enhance the reliability of findings. Response: Thank you very much for raising these concerns. We use fixed and random effects to test the robustness of results. We have enhanced the reliability of findings by using fixed and random effects to test the robustness of results. Specifically, it is discussed as below: “We apply the fixed and random effects to test the robustness of results. In the fixed effects model, constant term is not perpendicular to the variables. In the random effects model, constant term is perpendicular to the variables. In the random-coefficients model, each coefficient is associated group effects..” 7. The report of credible intervals without extensive discussion of their implications represents a gap. An understanding of the significance of these intervals in relation to policy implications, such as uncertainty in emissions targets, would benefit the discussion. Response: Thank you for your valuable comment. According to the table, the report of credible intervals will represent an understanding of the significance of policy implications. Notice, however, that the credible intervals for each of the variables do not contain zero, suggesting that a strictly effect is very likely. This means the robust exploration is important to further elaborate this point too. 8. The claim of robust identification of feedback relationships between energy consumption, economic growth, and carbon emissions suggests a need for exploration. Response: Thank you very much. We have used some sections for the interrelationship between energy consumption, economic growth and carbon emission. The transition concerning carbon emissions have been clearly addressed in the new section. We have explained in robust identification for further exploration. 9. The primary focus on coal-fired power plants raises the need for further exploration of alternative energy sources and their relationship with fossil fuel usage. The dynamics of the transition to renewable energy concerning carbon emissions should be emphasized. Response: Thank you very much. We have drawn the Table 1 of the dynamics of transition to renewable energy. The transition concerning carbon emissions have been clearly addressed in the new section. Table 1 Timeline who (organization responsible for the plan) what (the transition plan ) -1978 The State Council, and Central Committee of the CPC The management and operation will not be integrated, and power plants and grids will not be affiliated units of the government. 1979-1985 The State Council, and Central Committee of the CPC Electric power companies cannot be solely invested by the central government. The proposed plans will solve the contradiction between the original vertical monopoly operation mode of the power industry and economic system reform and opening up. 1986-1997 The State Council of the People's Republic of China The reform of the investment system will stimulate the enthusiasm for power investment, and the power industry will develop rapidly. The total amount of investment outside of finance will rapidly expanding. The primary focus on alternative energy sources to further exploration of their relationship with fossil fuel usage. 1998-2007 The State Council of the People's Republic of China The relaxation of restrictions in the field of fossil-fuel electricity generation companies should activate the enthusiasm of social capital. The reform of the power investment system should greatly increase the capacity for power investment. China emphasizes the dynamics of the transition from carbon to renewable energy 2008-2010 The State Council, and local management departments According to the requirements of 2008 Beijing Olympic Games, some fossil-fuel electricity generation companies will be phased out. The plan for the reform of the electric power system will clarify the key tasks of the reform of the electric power industry. 2011-2013 The State Council, and local management departments The series of complementary transition plans are the separation of power plants and grids, separation of main and auxiliary power, separation of transmission and distribution, and bidding for grid connection. 2014-2022 National Development and Reform Commission, Energy Administration, and local organizations The important tasks for the development of the power industry: energy conservation, emission reduction, and green development. Chinese power industry will enters a stage of high-quality development. 2023- National Development and Reform Commission, Energy Administration, and local organizations Some fossil-fuel electricity generation companies can be controlled by foreign capital company. The management departments should pay attention to the development of clean energy generation such as wind power and photovoltaic power. They should promote the comprehensive development of the power industry towards digitization, and internationalization. 10. The examination of trends, cycles, and structural breaks during the significant time period (2005–2017) may yield essential insights into the evolution of China’s energy policies and their influence on emissions. Response: Thank you for your valuable comment. We have modified the manuscript to address this point more clearly. We further elaborate on the trends and cycles during 2005 to 2017. After Beijing Olympic Games (2008) and Shanxi mine disasters (2010), carbon emission, consumption and generation suddenly changed. 11. The suggestions for various policy recommendations imply the necessity for further exploration of potential barriers to implementing these policies. A focus on socio-economic, technical, and governance challenges would provide a realistic perspective on achieving carbon neutrality goals. Response: Thank you for your valuable comment. I suggest We should face the policies on the socio-economic, technical, and governance. We have modified the manuscript to address this point (socio-economic, and technical challenges) more clearly. In addition, we have written another paper about the causal relationship of the carbon emission to internal firm governance, economic scale and energy consumption. 12. The issues regarding corruption and management practices in fossil-fuel electricity generation companies are significant but somewhat abruptly introduced. A more structured approach to discussing these challenges would enhance the narrative. Consider providing a distinct subsection that specifically addresses these governance issues, their implications for emissions performance, and how they can be mitigated. Response: Thank you again. It would be better if we create a subheading specifically addressing this corruption issue. we add another subsection “2.4. Corruptions and associated challenges” to address this point more clearly. In addition, we have written some new articles about emissions performance, corruption and so on. 13. In the literature review, while it lists various studies and their findings, a more thorough analysis of how these studies contrast or align with the current findings would be beneficial. Response: Thank you again. We are sorry that we did not writes about the issue clearly in the original manuscript. we add another paragraph and this passage clearly addresses the comment. We have modified the manuscript to address this point more clearly. 14. Please add section for the conclusion and future work. Response: Thank you again. We are sorry that we did not indicate the conclusion and future work clearly in the original manuscript. In this revision, we add another paragraph to illustrate: “Further research needs to confirm and build on the conclusions reached here by improving on this research. As we used carbon emissions as the only undesirable output in the empirical analysis, firstly, the limitations of this paper suggest directions for new research of pollutants, such as PM 2.5 and SO. Secondly, future research should consider a wider range of transitional characteristics, such as government ownership or corporate governance to better assess the performance of Chinese power industries.” Thank you for your comment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Journal: Sustainability

Title:  Bayesian VAR analysis of Chinese coal-fired thermal power plants

 

The authors have investigated the orthogonalized response of the carbon emission to energy consumption and power generation by using the Bayesian vector auto regressions and feedback solutions for impulse control technology. The authors have discussed the implications of the findings.

 

Below are some comments and suggestions for improvement:

·       Line 27 – no need to give full website address. Please use proper referencing style of the journal.

·       Line 46 – replace In with in

·       Line 50 – “In 2022, manufacturing industries consumed 65% of China's total energy.” Please give reference for this line. Also, it would be good to show the share of other sectors’ energy consumption in the overall total energy consumption of China.

·        Lines 53-57 – please check where the full stop is and where a new sentence begins.

·       Line 100 – check spacing between words and after full stops. Please check this throughout the manuscript.

·       Lines 132-147 : the proposed a series of complementary transition plans to Phase out fossil-fuel electricity generation companies can be presented in a Table that has information on who (organisation/institution responsible for the plan), what (what does the plan entail) and when (timeline of the plan).

 

 

 

General comments:

·       In section 2.1 – please show graphs of how the energy consumption, generation and emissions have been changing for the electricity sector over the years (eg 2005-2022). On the same graph, mark timelines where major change or policy was introduced in china that led to the shift in trend.

·       Section 2.3 – last paragraph – I think for journal articles, this can be written generally without the mention of specific names but references to articles can be made.

·       Please refrain from plenty use of quotes “”. Please rephrase and write – especially in sections 2.2, 2.3 and 3.1

 

·       Authors need to discuss the limitations of the present work.

Author Response

Please see the attachment.

Below are some comments and suggestions for improvement:

Line 27 – no need to give full website address. Please use proper referencing style of the journal.

Response: Thank you. We have deleted the full website address. We have studied referencing style carefully. To cite an article from an academic journal, we need an in-text citation and a corresponding reference. The in-text citation lists the authors and publication year. Different citation styles present this information differently.

Line 46 – replace In with in

Response: Thank you. We have replaced In with in. We have modified the entire manuscript to ensure the readability.

Line 50 – “In 2022, manufacturing industries consumed 65% of China's total energy.” Please give reference for this line. Also, it would be good to show the share of other sectors’ energy consumption in the overall total energy consumption of China.

Response: Thank you for your valuable comment.

According to your request, we searched for  “In 2022, manufacturing industries consumed 65% of China's total energy” on the website. We found on Chinese website that, manufacturing industries consumed about  65% of China's total energy ( Spaceicloud).But  we can no longer find the ENGLISH website and URL, so we will replace the previous one with a new reference: In 2022,  The industrial sector accounts for 65 to 72% of China’s total energy consumption( Deng et al., 2023) .

Lines 53-57 – please check where the full stop is and where a new sentence begins.

Response: Thank you very much. The Lines 53-57 has been checked . I check where the full stop is, and spelling are double checked to avoid confusion.

Line 100 – check spacing between words and after full stops. Please check this throughout the manuscript.

Response: Thank you very much. The spacing between words and after full stops have been checked .We have modified the entire manuscript and double checked the spelling and grammars to ensure the readability of this manuscript is improved significantly.

Lines 132-147 : the proposed a series of complementary transition plans to Phase out fossil-fuel electricity generation companies can be presented in a Table that has information on who (organization/institution responsible for the plan), what (what does the plan entail) and when (timeline of the plan).

Response: Thank you very much.

We have drawn the Table 1 of the transition plans to Phase out fossil-fuel electricity generation companies.

 

Table 1

Timeline	who (organization responsible for the plan)	what (the transition plan )
-1978	The State Council, and Central Committee of the CPC	The management and operation will not be integrated, and power plants and grids will not be affiliated units of the government.
1979-1985	The State Council, and Central Committee of the CPC	Electric power companies cannot be solely invested by the central government. The proposed plans will solve the contradiction between the original vertical monopoly operation mode of the power industry and economic system reform and opening up.
1986-1997	The State Council of the People's Republic of China	The reform of the investment system will stimulate the enthusiasm for power investment, and the power industry will develop rapidly. The total amount of investment outside of finance will rapidly expanding. The primary focus on alternative energy sources to further exploration of their relationship with fossil fuel usage.
1998-2007	The State Council of the People's Republic of China	The relaxation of restrictions in the field of fossil-fuel electricity generation companies should activate the enthusiasm of social capital. The reform of the power investment system should greatly increase the capacity for power investment. China emphasizes the dynamics of the transition from carbon to renewable energy
2008-2010	The State Council, and local management departments	According to the requirements of 2008 Beijing Olympic Games, some fossil-fuel electricity generation companies will be phased out. The plan for the reform of the electric power system will clarify the key tasks of the reform of the electric power industry.
2011-2013	The State Council, and local management departments	The series of complementary transition plans are the separation of power plants and grids, separation of main and auxiliary power, separation of transmission and distribution, and bidding for grid connection.
2014-2022	National Development and Reform Commission, Energy Administration, and local organizations	The important tasks for the development of the power industry: energy conservation, emission reduction, and green development. Chinese power industry will enters a stage of high-quality development.
2023-	National Development and Reform Commission, Energy Administration, and local organizations	Some fossil-fuel electricity generation companies can be controlled by foreign capital company. The management departments should pay attention to the development of clean energy generation such as wind power and photovoltaic power. They should promote the comprehensive development of the power industry towards digitization, and internationalization.

 

 

General comments:

In section 2.1 – please show graphs of how the energy consumption, generation and emissions have been changing for the electricity sector over the years (eg 2005-2022). On the same graph, mark timelines where major change or policy was introduced in china that led to the shift in trend.

Response: Thank you very much. We have drawn the graph of how the energy consumption, generation and emissions have been changing over the years. After Beijing Olympic Games (2008) and Shanxi mine disasters (2010), carbon emission, consumption and generation suddenly changed .The major change that led to the shift in trend are also addressed in it.

 

 

 

Section 2.3 – last paragraph – I think for journal articles, this can be written generally without the mention of specific names but references to articles can be made.

Response: Thank you very much. We are sorry that we used the mention of specific names. The entire Section 2.3 has been modified. Readability of the revised manuscript is improved. Thank you very much for raising these concerns.

 

Please refrain from plenty use of quotes “”. Please rephrase and write – especially in sections 2.2, 2.3 and 3.1

Response: Thank you very much again. We are sorry that we used so many quotations. The entire manuscript has been modified. Readability of the revised manuscript is improved and tense and spelling are double checked to avoid confusion.

 

Authors need to discuss the limitations of the present work.

Response: Thank you again. We are sorry that we did not indicate the limitations of the present work clearly in the original manuscript. In this revision, we add another paragraph to illustrate the limitations:

“Further research needs to confirm and build on the conclusions reached here by improving on this research. As we used carbon emissions as the only undesirable output in the empirical analysis, firstly, the limitations of this paper suggest directions for new research of pollutants, such as PM 2.5 and SO. Secondly, future research should consider a wider range of transitional characteristics, such as government ownership or corporate governance to better assess the performance of Chinese power industries.”

 

Thank you for your comment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thanks for updating the document after the comment, but the comments given for now does not satisfy the question. I recommend accepting the paper after minor revisions. There are areas that require further practical discussion and better linking of the results discussion together.

1. The quality of the paper is weak in the technical discussion, and the explanatory results have been discussed before. Both the discussion and practical application and the technical sense are missing.

2. The results require further elaboration, comprehensive comparison, and thorough examination, aiming to highlight the improved results, system superiority, and proposed methods in the paper.

3. The lack of clarification regarding the inclusion of regional variations in coal usage and emissions is a limitation that could have affected the generalizability of the findings. The justification for the choice of a Bayesian VAR model is insufficiently detailed, raising questions regarding the specific advantages of using this model compared to standard VAR or structural equation modeling in this context.

4. The conclusion indicating that the effects of energy consumption and power generation on carbon emissions were not significant warrants deeper exploration, highlighting a concern regarding the possible reasons for this finding. The potential existence of confounding variables not accounted for in the analysis is also troubling. The lack of a nuanced discussion regarding feedback mechanisms and their implications presents a weakness in the manuscript.

5. The lack of additional details regarding the calibration of the Bayesian VAR parameters for replication purposes raises concerns. Specifically, information about the prior distributions used and how the hyperparameters were determined is necessary.

6. Please specify and highlight in any color the new changes in the research to emphasize the modifications.

 

Comments on the Quality of English Language

Minor editing required. 

Author Response

Please see the attachment.

1. The quality of the paper is weak in the technical discussion, and the explanatory results have been discussed before. Both the discussion and practical application and the technical sense are missing.

Response: Thank you for your valuable comment.

We have emphasized that Bayesian vector autoregression model could estimate the carbon emissions performance of Chinese fossil-fuel generation companies accurately. We have modified the technical discussion. We have emphasized the advantage, in that the technique incorporates informative priors, so that prior knowledge, or results of a previous model, can be used to inform the current model. Thank you for raising this concern and we have modified the manuscript to address the technical sense, discussion and practical application clearly.

Thank you.

 

2. The results require further elaboration, comprehensive comparison, and thorough examination, aiming to highlight the improved results, system superiority, and proposed methods in the paper.

Response: Thank you for raising this concern.

 In this revision, we add some sentences to illustrate your concern regarding the improved results, system superiority, and proposed methods. Specifically, it is described as below:

“We also follow standard empirical convention to conduct the statistic test. The statistic’s calculated with coefficient , standard error and credible intervals of the coefficient estimate. The results demonstrate that the effects of energy consumption and power generation on carbon emissions are significant at 5% critical level. From the economy perspective, the panel of the result shows that the effects of energy consumption and power generation on carbon emissions are significant. ”

We are sorry that we did not elaborate the results clearly in the original manuscript. We have modified the manuscript in sections 5.2, 6 and7.

 

3. The lack of clarification regarding the inclusion of regional variations in coal usage and emissions is a limitation that could have affected the generalizability of the findings. The justification for the choice of a Bayesian VAR model is insufficiently detailed, raising questions regarding the specific advantages of using this model compared to standard VAR or structural equation modeling in this context.

Response: Thank you for your comment.

 We have also conducted the  clarification regarding the inclusion of regional variations. Firstly, we treated the variable of regional differences as a dummy variable. the differences were basically unchanged. their economic idea is not significant. secondly,  it wais significant if we consider that the panel is classified under regional variations (the main control factor).

Our research shows BVAR model is different from the traditional model to link the preceding factors with the following factors. The main purpose of the model is to improve the accuracy of the estimation by separating the effects from heterogeneity. It is different from the traditional effects which assumes that all units share exactly the same firms variations which is in contrast to frequentist inference. In addition, it obeys the likelihood principle. Bayesian inference is consistent with the philosophy of knowledge regarding epistemology, where examination cannot be built entirely through experimentation, but requires prior factors.

 

4. The conclusion indicating that the effects of energy consumption and power generation on carbon emissions were not significant warrants deeper exploration, highlighting a concern regarding the possible reasons for this finding. The potential existence of confounding variables not accounted for in the analysis is also troubling. The lack of a nuanced discussion regarding feedback mechanisms and their implications presents a weakness in the manuscript.

Response: Thank you for your valuable comment.

 We are sorry that we did not indicate the effects clearly in the original manuscript. The conclusion indicating that the effects of energy consumption and power generation on carbon emissions were significant.

According to the Sd.dev. and credible intervals, I  estimated the critical values  and found the impacts were significant. I  estimated the feedback by  IRF which give the response when the system is shocked by a one-standard-deviation shock too. We have modified the manuscript clearly in ABSTRACT, sections 5.2, 6 and7. In fact, we should investigate the Table 3 and 4 followed by Table 2. In addition, we also conducted study on the confounding variables and feedback mechanism, but the workload was relatively large. Due to a limited number of pages allowed, we did not provide specific details of the feedback mechanisms and their implications.

Thank you.         

 

5. lack of additional details regarding the calibration of the BVAR parameters for replication purposes raises concerns. Specifically, information about the prior distributions used and how the hyperparameters were determined is necessary.

Response: Thank you for your valuable comment.

 We have added additional details regarding the calibration of Bayesian VAR parameters. BVAR model is different from the traditional model which assumes that there are some hierarchy differences between firms. I  choose the priors for parameters as flat. The general priors for the model  are normal, Inverted Wishart or gamma distribution. I  estimated the conditional posterior values of each model parameter and used the Windows program to calculate the equation from the conditional model in sections 4 and 5.2. The prior distribution used and estimation for its hyperparameters have been described.

 

6. Please specify and highlight in any color the new changes in the research to emphasize the modifications.

Response: Thank you.  We've highlighted the important changes in red. The amendments are marked in the revised manuscript, to make it easier to see. I have specified  the work we have already done. All references are relevant to the content of the manuscript. We hope that the revision is acceptable.

 

 

 Thank you for raising the comment.

 

Author Response File: Author Response.doc