Round 1

Reviewer 1 Report

This paper adopted the SBM-DEA model and ML (index to measure the green transformation at mircro-enterprise level.  The manuscript needs to be revised as follows.

(1) An overview of the rest of the paper can be added at the end of the 1. Introduction.

(2) The theoretical and practical contributions of this study need to be described.

(3) The applicability of the models and methods chosen for this study should be further explained.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear authors.

Congratulations on the effort to develop the article, it can contribute to the scientific literature, but requires substantial improvements in its structure.

1 - What is the main question addressed by the research?

The article addresses the gap by exploring the relevant mechanisms that affect sustainable transformation from a green credit policy perspective.

2 - Do you consider the theme original or relevant in the area? Does it address a specific gap in the field?

The theme is original and relevant, as it deals with a problem with real application in the environmental aspect of several countries, specifically China.

3 - What does it add to the thematic area in relation to other published materials?

The study is current in relation to the others, as it deals with sustainable green credit.

4 - What specific improvements should the authors consider in relation to the methodology? What other controls should be considered?

The methodology must explain, in addition to the research method, the entire construction of the report, which does not contain details in the file. In addition to using more robust methods of statistical analysis.

5 - Are the conclusions consistent with the evidence and arguments presented and do they address the main question posed?

The conclusions are good, for demonstrating theoretical and practical contribution. A comparative analysis with the existing literature on the subject should also be carried out.

6 - Are the references adequate?

Yes.

7 - Please include any additional comments on the tables and figures.

Not applicable.

- - - -

I suggest some points for improvement:

The abstract demonstrates in detail the conclusion of the article, but needs to better highlight the results found.

Include a larger discussion in the introduction, presenting a timeline of the theme of carbon credit and green credit. At the end of the introduction, I suggest highlighting the advances that the current study has in relation to others, in addition to performing a greater contextualization on the subject.

In the introduction, clarify the problem and the research objectives, presenting the gaps that gave rise to the problem;

It is important to add in the introduction, which methods the other studied articles used to answer the problem;

The research hypotheses are well constructed;

The literature review seems adequate, but a few more current citations are in order;

I suggest dividing the literature review into two sections: 1 - Green credit policy, 2 - Enterprises’ green transformation;

The methodology must explain, in addition to the research method, the entire construction of the report, which does not contain details in the file. In addition to using more robust methods of statistical analysis.

The main point of suggestion is that the discussion can be more robust, including deeper statistical methods, since the use of linear programming of the slack-based measurement model (SBM) does not invalidate the study, but does not demonstrate significant gains in the literature;

 

I hope I have contributed to the improvement of the study.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

 

Green Credit Policy Influencing Enterprises’ Green Transformation In China

 

Summary

 Wow. What an interesting, important and complex paper. The authors could publish this paper as it is, but I think that to do this would be a mistake. This paper is of potential importance so should be revised to strengthen the overall argument. For this reason, I am recommending publication after revision.

 I will try to keep these comments at a high level to give the authors the maximum flexibility as to how address them.

 

The major issues to my mind are as follows.

Research Question (i) - Overall Economic Framework

 There should be a more explicit, but probably very simplistic and maybe literal or notational or even diagrammatic rather than formally mathematical, model that describes the overall economic framework of Green Credit, Green Transformation and Economic Growth / Development.

This model should set out the authors view of the overall interaction between (i) overall business investment credit demand and green credit demand, (ii) overall credit supply and green credit supply, (iii) the market / innovation driven elements of changing technology within the production function (Solow’s growth residual) and (iv) the green demands for a change in the production function that include (a) market requirements and (b) regulatory driven changes. This view then provides the “steady state” background against which the 2012 Green Credit Guideline shock occurs, the impact the authors are looking to measure.

In an ideal world the steady state model would be sufficiently enunciated to provide a theoretical counterfactual to contrast the shock state to. In this case, (and in any event counterfactuals are fraught with difficulties as they never occurred) this feels impossible as the underlying dynamics of “green policy” are a rapidly changing landscape.

Conventionally, one can often infer the counterfactual by comparing some form of “adjusted” pre shock performance to post shock performance, but in green transition this is to my mind not possible, as the structural changes (technological, consumer demand, ESG investment criteria and regulations)  to this landscape are both frequent and significant in the way they impact markets.

Credit availability is one of the key variables to delivering an effective transition, but it does need to be “contexted” within shifts in consumer and industrial demand, technical change, associated conventional productivity gain opportunities and regulatory changes. Providing a simple high-level view of how this fits together feels like important background to the paper.

This overall concept should be capable of being set out in a few additional paragraphs that perhaps belong in a somewhat longer introduction by extending the text at lines 48 - 50. These become context for the research question) and results, thereby allowing the paper’s statistical work to align to an overall transition framework. The value of this to the reader is that it should help them understand that the specific shock being tested is just one (albeit important) piece in a much larger picture, and as such this provides a useful hook for suggestions for future study.

As an aside I find the paragraph at line 52-61 opaque. To my mind this section should summarize in a couple of sentences exactly what the 2012 policy change was and how it was intended to impact private credit markets. As I am not familiar with the policy announcement in detail it would be very helpful to have a very simple summary, and also to perhaps link this to a comment on how this policy relates to the 2014 announcement of Green Credit Key Performance Indicators and the research being documented in this paper.

 The comments at lines 41 to 47 should be a separate paragraph, and directly relate to the model suggested at the start of this section of comments. Reading these lines, I am unconvinced by the current wording, most especially on the issue of investment risk. In a post – Covid, climate aware world, demand patterns,  technologies and regulations are all shifting very rapidly, so all industrial investment projects are technically, demand and regulatory uncertain. Why are green ones more uncertain than everything else?

I would recommend adjusting the language in this passage to perhaps highlight that there is a new category of “green transition” projects that need lending officer and lending criteria to enable them to be fairly assessed, rather than stating that they are inherently more risky than other investments which to my mind is a statement that is more difficult to support. The alternative to changing the language would be to add a couple of references that draw on the work of others to “stand up” these statements.

Research Question (ii) - The Statistical Model

 I have not checked the equations, and whilst I think I understand what they are doing I find the overall model they are testing, is at a detail level, challenging to abstract out to the “back of an envelope”. Perhaps a few words or a diagram giving a simple summary of the model could help.

Having read the paper a few times, is it really about testing the impact of the “Green Credit Guidelines” of January 29, 2012? If so, should this be mentioned in the abstract, the introduction, the research questions (I am not sure these are hypotheses, so I would suggest renaming section 3 as “research questions”) and the conclusions as it is the overall bounding assumption of the study.

Section 4 is complex to read with a great deal of detail and leaves me uncertain as to if I have understood how the implicit productivity measure in the Malmquist-Lenberger Index combines with the Slacks based efficiency measure into the Green Transformation variable.

Specifically, when I case my eye over the 2012 announcement, I am wondering if there is any carbon footprint / atmospheric pollution data that could be included into the index elements for the Malmquist-Lenberger Index? A couple of high-level sentences on why the variables selected give the constructed Green Transformation variable validity as a measure of environmental transformation would be helpful, even if these sentences add that there are some variables that the authors would have liked to include but could not because the data is not available. Could such a comment help reinforce recommendations for (i) future research  and (ii) suggest additional data regulators may want collected in the future?

Having gone to the trouble of creating the index and identifying the value of environment investment (is this at constant or actual prices?) why not add a figure graphing on against the other with no time lag and then with the time lag later added to the paper. That should help the  apriori  understanding as to whether a one period lag is the right length of time for this analysis.

There is also a question as to whether the lag is variable in relation to industry or enterprise type or if it is standard? For example, will decision making and execution apparatus in private market facing companies be faster than in less market facing large state-owned companies? It would be no surprise if this were to be the case, in which case could the results that indicate the difference between the two sectors be related to different lags associated with different decision making and execution structures. In other words – could State Owned non-Market facing enterprises obtain the same gain in Green Transformation, just it takes them longer?

I have no idea, but could a simple graph help give context? In making this comment I am not suggesting changing the statistical work, rather just to highlight the complexities of lag selection, and perhaps add a further hook for additional research.

The correlation model itself makes reasonable sense although I am not convinced that the definition of variable Green Credit Policy is sufficiently broad. It feels like there is a significant ceteris paribus “other things being equal” assumption implicit to its definition – which is fine provided that there is a paragraph explicitly acknowledging what those bounding assumptions are (see the section below).

Having said all of the above,  I don’t think the results end of the paper needs much work to handle these issues –  a few extra sentences should cover the issues. I am not suggesting a change to the statistical model.

 

Assumptions

Flowing on from expressing the framework model, could this contribution benefit by explicitly stating the underlying “bounding” assumptions, (possibly as a new section 3.2). This section can be referred to in the vectors described in 4.1 by means of identifying elements that could be included into these vectors if the assumptions were to be relaxed – thereby giving a hook for the undoubted additional research needed in this area.

Literature Review

This and the subsequent section can and probably should be substantially pruned – it is unnecessarily long winded and could be significantly shortened and include some of the missing literature which in my view is essential to context the rest of the paper. It is also confusing in places. For example, I cannot understand some of the sentence at line 92 – what is “upward surplus management” and what is “surplus quality”? I am not sure this matters as these concepts do not seem to feature elsewhere in the paper.

The paragraph between lines 93 and 106 either needs shortening into a sentence or rewriting to cat as a lead into explain why the approach on measuring Green Transition the authors is taking is different. Equally, I wonder if lines 78 to 90 could be condensed to a couple or even a single sentence. Whilst interesting to read, the feel somewhat minor when compared to the need to provide literature support to the index approach to measuring Green Transition the authors take (which I take to be one of the significant innovations in this paper).

For example, a paragraph discussing the production function, the production possibilities frontier and the Malmquist-Lenberger Index, (which is not as far as I know a single concept but rather Lenberger can be seen as an extension of Malmquist), would be helpful. This article may be of help

Boussemart, J. P., Briec, W., Kerstens, K., & Poutineau, J. C. (2003). Luenberger and Malmquist productivity indices: theoretical comparisons and empirical illustration. Bulletin of Economic Research, 55(4), 391-405.

The construction of a Green Transition Index that is capable of sub setting across types of enterprise and industry feels to me like a very significant contribution, although I am not convinced the authors have all the elements needed to make it truly representative. Repeating my comments from above, I suspect it should also include carbon footprint / atmospheric pollution data that could be included into the index elements, even if their inclusion could be flagged for future research.

In that context I wonder if the authors approach could be contrasted with that set out with others. Here are a couple of examples.

Liu, X., & Chen, S. (2022). Has environmental regulation facilitated the green transformation of the marine industry?. Marine Policy, 144, 105238.

Wu, C., Li, Y., & Qi, L. (2022). Assessing the Impact of Green Transformation on Ecological Well-Being Performance: A Case Study of 78 Cities in Western China. International Journal of Environmental Research and Public Health, 19(18), 11200.

To reiterate a comment already made, I would like to suggest a figure giving a longitudinal view of the evolution of the Malmquist-Lenberger Index they calculate that is annotated to describe how this is changing in relation to green innovation / investment as a opposed to how it is evolving in relation to changes in non-green Total Factor Productivity. If the authors feel this is too ambitious for this paper and belongs in a “further research category”; then I would encourage the authors to include a table to show how the index has evolved.

The Porter hypothesis is conceptually important and seems highly relevant to the research question, so perhaps a paragraph summarizing some of the threads in the extensive literature regarding this would be helpful.

Equally, issues regarding credit constraints and information asymmetry deserve more space in the paper than they currently have. At a minimum shouldn’t reference be made to the foundational Stiglitz and Weiss 1981 paper on this?

The implicit assumption that overall credit availability is not constrained may hold for the size of companies in this analysis but is almost certainly untrue when one looks at smaller firms that also need to execute a Green Transformation. For that reason, a few words on credit availability, if only to say that this paper is looking at relative credit allocation (rather than total credit volume) between green and non-green projects may help. Would some data (a simple table?) to show how overall credit to the sample changed over the period and in turn how the allocation of this changed between green and non-green projects be helpful? Wouldn’t this data back up and demonstrate the practical impact of the 2012 “Green Credit Guidelines”?

Also, some of the literature review seems to be in the section on “Research Hypothesis”. Lines 120 to 168 feel like they could be condensed into 4 or 5 lines to support the statement that green credit policy supports green transformation.

The sentence at lines 177 – 178 feels like it is too strong. Regulation can be a spur to transform technology, replace capital stock and thereby transform productivity. The sentence should either be removed, reworded or referenced to a supporting study that underpins the claim being made. The following sentence makes the point I have just made, so one sentence is not compatible with the other.

The wording between 180 – 190 is suspect, many global investors now have green “gating” investment criteria, so I suspect the information in Li et al. that is cited may probably slightly out of date. This section should be revisited by the authors.

The rest of the text in this section from 191 to 272 is very wordy and could probably be shortened to 4 or 5 lines whilst still supporting the statement at line 273. The same can be said of the text from lines 275 to 308.

Reducing the length of these sections should then give space in the article to include other issues that this note highlights as needing to be discussed. It is of course for the authors to determine what to do, but these comments are intended as a pointer as to possibilities if article length is a concern.

TobinQ

I don’t see the relevance of this. How does the relationship between the book and replacement value of assets come into this? Isn’t the relevant commercial variable the potential asset write down required to change technology? If this is the case this is a standalone variable not related to the replacement cost – a balance sheet write down is a balance sheet write down irrespective of the replacement cost of the assets; and an investing firm, especially a private sector market facing one will need to take this into account in any investment appraisal.

Given that the model is fully calculated, I would not change the model at this late stage, but rather I would suggest reviewing the wording as to why TobinQ is used.

Rate Of Interest

Even if mentioned in a sentence or two, doesn’t the relationship between the rate of return and the cost of the green credit ( the rate of interest) need mentioning (perhaps in the introduction). This is a complex area, as the selected rate of interest rate needs to be risk adjusted and the potential financial returns depend upon an expectational framework that may in turn relate to existing and anticipated regulatory burdens. For this reason, I would suggest keeping any sentence on this at a very high level, perhaps taking a “theoretical economics escape hatch” through alluding to the comparison of Keynes Marginal Efficiency of Capital with Wicksell’s Natural Rate of Interest and thereby avoiding discussing the necessary bounding assumptions to making such a comparison valid.

Finally

If the authors agree with them, these comments should all be capable of being handled as changes to the text and so rapid to include. I have deliberately not commented on the empirical results, as I think this is the “meat” of the authors work and should be presented as is.

Myself, I like this paper and think the approach on constructing the index (even if it may not have all the necessary elements in it) is making an important contribution in an emerging and active area.

Assessing how policy pronouncements in the ESG area impact behavior is to my mind very important as it helps us understand the balance between prescriptive changes in formal regulations and the role of “softer measures” in changing firm level and lender behavior.

 

Thank for an interesting read and I hope these comments help you as authors to finalize what I personally believe should be an important contribution in the area.

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Dear authors.

Congratulations on the changes to the article.