Research on the Relation between Foreign Trade and Green Economic Efficiency in Subdeveloped Region: Based on Data from Central China
Round 1
Reviewer 1 Report
Environmental degradation is currently a serious problem, and it is the development of international trade that is making a significant contribution to this. The paper deals with the problem of the impact of foreign trade on economic growth in the context of sustainability on the example of a selected region. China has experienced rapid economic growth since 1978, but there are differences in economic development between regions. The authors examine the impact of foreign trade on the economic development of the selected region based on available data. They declare their research at the end of the paper. They used relevant resources in the research. However, in the introductory part of the article, they could focus more on the positives or negatives of the impact of economic growth on the environment.
Author Response
Part of the introduction describes the status of foreign trade in Central China has been removed, so the introduction focuses more on the contradictory relationship between economic growth and environment. At beginning, we wanted to detail the whole development prosses of foreign trade in Central China, including why the region had chosen such a development path, whether external environment was pleasant for expanding foreign trade scale, so these contents might have reduced the focus on our main topic unintentionally. Also, English writing has been moderated of our article.
Reviewer 2 Report
This article addresses a critical issue for not only ecologists and environmentalists, but for the entire population of central China and possibly even for all those in the general global vicinity.
The author’s findings, specifically those related to differences in green economic efficiency
(ENE) related to capital city status, rivers, city size, and level of manufacturing, provide valuable insight into predictors of environmental problems. Further, the authors’ suggestions, in the article’s conclusion, demonstrate their genuine intentions in applying their findings to benefit the locale.
Despite these impressive qualities, a potential major flaw in reasoning made by the authors
necessitates reconsideration of the natures of the relationships between the variables analyzed.
The authors seem to have ignored the methodological rule that “correlation does not equal
causation.” Throughout the article, and even in its title, they use the expressions “cause,”
“effect,” “affect,” “impacts,” “results from,” and similar terms that imply causation. It is clear,
therefore, that the authors presume that a relationship between two variables means that the
independent variable causes the dependent variable. In fact, that MAY be the case, but one
cannot discount the possibility of explanations other than direct causation for the relationships.
For example, in lines 224 and 225, the authors state that an increase in economic growth causes an increase in pollution. They do not, however, consider the possibility of a spurious correlation.
Perhaps a third, intervening, variable such as population growth explains both the economic
growth (as residents bring business to local establishments) and pollution (as residents litter and corrupt the natural landscape). In this case, although economic growth and pollution may
increase simultaneously, it is not the first that causes the second; instead it is the intervening
variable that causes them both. The authors need to address such possibilities throughout the
article, as they consistently assert that changes in environmental factors are caused by various
independent variable factors. They can do so in either of two ways. The more complicated, but more impressive, approach involves using partial or part correlations to estimate the correlations between the independent and dependent variables independent of all plausible intervening variables. (Although the authors do discuss control variables, this discussion simply identifies these factors. It does not describe the approach to accounting for them.) The alternative approach simply requires the authors to acknowledge that the relationships they describe do not necessarily imply causality. Replacing the terms that imply causation with terms such as “relates to,” “is associated with,” and “predicts” can accomplish this task.
Other concerns, although none as critical as the one described in the previous paragraph, appear in the following list.
1. The authors are clearly not native English speakers. In general, they did an impressive job
explaining their points in English. However, as any individual not intimately familiar with
the language would do, they made many errors related to fine points of the language.
Because these errors are so numerous and specific, I have noted them on the manuscript
itself.
2. The use of the terms “significant” in line 74 and “significantly” in line 80 does not seem to refer to the statistical concept of significance. Perhaps the terms, “substantial” and
“substantially” can be used instead.
3. Hypothesis I and Hypothesis II should specify the directions of the relationship (positive or negative) between the variables involved. Similarly, could the authors include + signs (to
represent direct/positive relationships) and – signs (to represent inverse/negative
relationships) along the paths between variables presented in Figure 2?
4. The authors should clarify what they mean by “unnecessarily do good to reducing…” in
lines 156-157.
5. Descriptions of non-linear data may need modification.
a. Throughout the article, the authors refer to FX2. This notation is first introduced in line
182, where the authors mention that variables may have a quadratic, rather than a linear
relationship. Should the notation of FX2, then, really be (FX)2, as the squared term is
characteristic of quadratic functions? If so, then FX2 should be changed to (FX)2
throughout the article.
b. Also throughout the article, the authors refer to a U-shaped relationship. If this pattern
reflects the quadratic relationship between variable, then the authors should refer to the
shape formally as a parabola (or inverted parabola when relevant), which is the graph of a
quadratic equation.
6. Figure 5 does, as the authors state in line 241, suggest that a negative relationship exists.
Could the authors provide the actual correlation coefficient as well?
7. In line 333, the authors should replace the phrase, “proven to be true,” with “supported.”
According to standards of social research, no hypothesis is ever unequivocally proven;
hypotheses receive support.
8. Please clarify, in line 297, whether trade is an advantage of price or price is an advantage of trade. These points, as well as the earlier comments on the topic of causality, should be regarded as constructive criticism, meant to help authors improve what seems to be a promising analysis of environmental conditions in central China. Successfully addressing these matters, I believe, will make “How Will Foreign Trade Affect Green Economic Efficiency in Sub-developed Region? An Empirical Research Based on the Data from Central China” suitable for publication in Sustainability
Author Response
(1) Based on the theories of environmental economics and regional economics, this paper puts forward foreign trade can have an impact on ecological environment. Our regression analysis is intended to confirm the existence of this effect. However, there might be omission of important variables in the econometric models or improper setting of the model, causing ‘pseudo regression’ and endogenous problems. As has been pointed out，‘significant correlation in our article does not equal causation’, so we have conducted fixed effect IV regression and difference GMM regression to solve these problems. But we can neither include all impact factors or find a perfect instrumental variable for foreign trade in our article. As a result, these problems cannot be completely solved. To make our results more convincing, we adopted your advice to change our title as ‘Research on the Relation Between Foreign Trade and Green Economic Efficiency in Sub-developed Region: Based on the Data from Central China’. Expressions such as ‘have negative impact or effect’ have been replaced with ‘we confirmed the negative relation or parabolic relation’ in our article except for theoretical analysis part, for we have drawn the conclusion from economic theories and existing literatures that 'causation' exists at least at the theoretical level. (2) English writing has been moderated. (3) “significant” in line 74 and “significantly” in line 80 have been replaced with “substantial” and “substantially”. (4) From the theoretical analysis, it can be seen that the impact of foreign trade on green economic efficiency is different under different circumstances. We can only propose the hypothesis that foreign trade does correlate with green economic efficiency. Empirically testing the relation between foreign trade and green economic efficiency in Central China and figure out the characteristic of the relation are also the most important job in our article. Therefore, it is difficult to predict whether the relationship is positive or negative before empirical test is completed. (5) FX2 has be changed to (FX)2. (6) ‘U-shaped relationship’ has been changed to ‘parabolic relation’. (7) Stata 14.0 doesn’t provide such correlation coefficient in ‘twoway’ command. Achieving this needs a formal regression step, that’s what we have done in the empirical test part. Figure 5. is just to preliminarily illustrate that the relationship could be negative, and correlation coefficient alone here is not robust enough, so it is omitted in the figure. (8) “proven to be true” has been changed as “support the hypothesis.” (9) We have re-written the sentence of line 333, that is “For cities newly engaged in foreign trade, only lower price can help products of these cities take up a large market share quickly”.
Reviewer 3 Report
The review is attached.
Comments for author File: 
Comments.pdf
Author Response
(1) Coefficients of formulas (1)-(3) have been change to be different. (2) We have identified the meanings of each important coefficient. (3) In 2018, president Xi conducted an investigation on the protection of the Yangtze River by himself and intensified the concept of ‘high standard protection’. Then local governments of cities along the Yangtze River forced a large number of polluting enterprises to close, move or transform under the environmental protection pressure from the central government, effectively reduced the pollution emission of the region. (4) We have normalized CRE, RIC, FDI, and FANJR through performing logarithmic processing on them. (5) Policy implications have been enriched by adding some specific suggestions.
