Will Trade Protection Trigger a Surge in Investment-Related CO2 Emissions? Evidence from Multi-Regional Input–Output Model
Round 1
Reviewer 1 Report
Dear authors,
First of all congratulations for your work. A lot of hard work and scientific rigor is appreciated and I have enjoyed reading it. The only aspect that would improve is to enhance their contribution and the results found. I have been able to appreciate that it really brings something new, 2 contributions, but on the other hand, these are not highlighted either in the abstract or in the conclusions.
I would also try to give more details when reading the graphs. They are well explained and understandable, but they could be simplified to make them more intuitive.
I encourage you to do so and I am waiting. When I get the revision I'll give it another read to see if it can be further simplified.
Congratulations good job.
Author Response
Response to Reviewer 1 Comments
We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. Our responses (red font) to your comments (black font) are given below. The number of lines and pages indicated in the responses corresponds to the revised manuscript-highlighted version (with changes marked).
Point 1：The only aspect that would improve is to enhance their contribution and the results found. I have been able to appreciate that it really brings something new, 2 contributions, but on the other hand, these are not highlighted either in the abstract or in the conclusions.
Response 1: Thank you for your suggestion. Based on your suggestion, we have highlighted two contributions in abstract and conclusions. And the two contributions in the literature review are explained in more detail.
The contribution of this paper is mainly reflected in two aspects. Firstly, in terms of theoretical contributions，the effect of trade protection on the environment has become a research hotspot in recent years. However, the existing studies are more about the effect of transnational investment on CO2 emissions, and seldom studies the effect of trade protection on investment-related CO2 emissions. To fill this research gap, this paper constructs an accounting framework for investment-related CO2 emissions under trade freedom and trade restrictions based on the MRIO model for the first time. The effect of global trade protection on investment-related CO2 emissions is revealed from the three levels of country, section and trade links.
Secondly, in terms of practical contribution, in the process of trade globalization, the connection between economy and environment among countries is intricate, which has attracted extensive attention of scholars. What effect will the evolution of global trade patterns have on investment-related CO2 emissions? This study quantifies the effect of trade protection on investment-related CO2 emissions in order to provide a reference for policymakers to better grasp the environmental costs behind the evolution of the current trade situation. And timely adjustment of investment policies according to possible changes in the future will play an important role in reducing investment-related CO2 emissions. The research results provide a reference for measures to reduce investment-related CO2 emissions, such as promoting trade openness and reducing trade barriers to achieve a reduction in global total investment-related CO2 emissions. China and India can attract transnational investment to reduce investment-related CO2 emissions in both countries. China should focus on introducing clean technologies for transnational investment in manufacturing to reduce the sector's contribution to investment-related CO2 emissions. Strengthening China's barriers in trade of final goods or focusing on the energy efficiency of this trade link will have a favorable effect on reducing investment-related CO2 emissions in this trade link. For Russia and Japan, we should pay attention to the quality of investment and optimize the investment structure. In general, trade liberalization has a negative effect on investment-related CO2 emissions from the trade of end-stage intermediary goods. Reduce the trade barriers to investment related to intermediate products in the trade of end-stage intermediary goods on a global scale, so as to achieve the greatest possible reduction in investment-related CO2 emissions in this link.
Manuscript changes please see line 12-14 in page 1, line 30-31 in page 1, line 548-550 in page 16 and line 579-592 in page 16.
Point 2: I would also try to give more details when reading the graphs. They are well explained and understandable, but they could be simplified to make them more intuitive.
Response 2: Thank you very much for reading our manuscript carefully, we have simplified the pictures based on your comments, and removed the background shadows in Figure 1, Figure 2, and Figure 7. In order to clearly show the meaning of the columns, the position of the legend in Figure 4 has been changed. In order to express the meaning of the picture more clearly, we set a new title for Figure 6, namely "Figure 6. The distribution of investment-related CO2 emissions of countries in various sectors under a normal trade scenario (a) and under a no trade scenario (b)". The details of the pictures have been further explained in the text.
Figure 1. Trends in transnational investment-related CO2 emissions
Figure 2. Countries’ investment-related CO2 emissions in both normal trade and no trade scenarios in 2014
Figure 4. Trends in investment-related CO2 emissions under the scenario of normal trade –under the scenario of no trade for different countries
Figure 6. The distribution of investment-related CO2 emissions of countries in various sectors under a normal trade scenario (a) and under a no trade scenario (b)
Figure 7. The effect of international trade on countries' investment-related CO2 emissions in various sectors
Manuscript changes please see line 438-440 in page 11, line 456-458 in page 12, Figure 1 in page 9, Figure 2 in page 10, Figure 4 in page 13, Figure 6 in page 14, Figure 7 in page 15.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper deals with interesting issues. However, it is inconsistent, and the methods used do not provide a way to verify the claims made.
The abstract should be improved (Objective. Research Design & Methods. Hypothesis, research questions. Findings. Implications & Recommendations. Contribution & Value Added.)
In general, the introduction and literature review make many assumptions and formulate many hypotheses, that have not been proven.
There was no assessment of the appropriateness of the model used for the purpose and scope of the study.
The method of data selection in the context of the content addressed in the introduction and literature review is incorrect (the data end in 2014).
The results presented and conclusions formulated do not meet the stated objectives and were not evaluated by the reviewer.
There are also faults in the text, including the way the formulas are written (mathematical formalism). It needs to be improved.
Detailed comments (up to Chapter 3) are written below.
31. Current studies should be cited. Their reliability (whether CO2 emissions cause climate change) and conclusions (what level of CO2 emissions is acceptable) should be discussed at length. Reference to the papers from 2011 [2] and 1990 [3] is insufficient. Item [4] is not relevant to this topic.
36. Item [5] is outdated and cannot form the basis of the thesis in the paper. Current research should be pointed out and reliably discussed.
41. The use of the phrase "trade war" is not professional in an academic paper. Instead, the mechanisms used by countries in international trade should be discussed. Relevant studies should be cited and quantitatively described. You should embed considerations for successive years of the assumed period of analysis.
42. Identifying only three countries based on three causal papers is insufficient. Studies on all relevant countries should be cited. The conclusions of these studies should be discussed.
43. The changes that occurred as a result of the COVID-19 pandemic (quantitative and qualitative) should be discussed.
47-51. The literature items [10-12] are out of date (2000, 2009, 2012), and item [9] does not consider the effects of COVID. Current studies should be cited. The conclusions of the studies should be discussed.
54. Nothing comes out of quantifying relationships. Indicate what this information can be used for and how.
57. There should be a precise definition of what normal trade and no trade mean.
70. This is a strong hypothesis that needs to be proven.
74. The items [16-29] only confirm that any investment activity related to energy consumption increases CO2 emissions. Have the authors of any of these papers considered the structure of primary energy consumption and the long-term effects of the implementation of investments (their energy efficiency)? Have the authors of any of these papers considered how economic growth in the countries in question has increased the consumption of goods and services?
75. Most means which ones? Identify specific papers and discuss the conclusions of these papers.
99. What does the analysis of items [30-40] bring to the literature review?
128. Five papers [41-46] refer to the study of local and limited issues. Can these methods be applied to a worldwide analysis? Likewise, items [47-49] deal only with local issues - where else and by whom have general and broader issues been studied?
138. The description of the model should be written in the next chapter.
153. What kind of guidance does the study provide?
159. The chosen model is very simple. It is reduced to elementary transformations and the determination of a few indicators. You should describe why this model was chosen. Compare this model with other available models. You should justify whether it allows you to describe the real situation in the current period. Indicate what simplifications the model has (what it does not take into account and how this affects the research). Describe how validation of the model was carried out and what the conclusions are. Describe how different scenarios can be differentiated from the model (how to run different simulations). A sensitivity analysis should be conducted and the results should be discussed.
187, 189. Editorial faults.
227. The indicators given are very general. It is difficult to understand what conclusions can be drawn from such aggregated data.
232. The matrix should be formally defined, as how to determine all its components. Why is this matrix symmetric and non-zero only on the diagonal?
260. The reference to a 1970 article is insufficient. Are there other sources of data? If so, which ones and why were they not used (at least discussed)? Item [53] is only causal. The data end in 2014. The data are not relevant to the purpose and scope of the study.
The paper contains numerous linguistic faults that should be corrected.
Author Response
Response to Reviewer 2 Comments
We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. Our responses (red font) to your comments (black font) are given below. The number of lines and pages indicated in the responses corresponds to the revised manuscript-highlighted version (with changes marked).
The paper deals with interesting issues. However, it is inconsistent, and the methods used do not provide a way to verify the claims made.
The abstract should be improved (Objective. Research Design & Methods. Hypothesis, research questions. Findings. Implications & Recommendations. Contribution & Value Added.)
In general, the introduction and literature review make many assumptions and formulate many hypotheses, that have not been proven.
There was no assessment of the appropriateness of the model used for the purpose and scope of the study.
The method of data selection in the context of the content addressed in the introduction and literature review is incorrect (the data end in 2014).
The results presented and conclusions formulated do not meet the stated objectives and were not evaluated by the reviewer.
There are also faults in the text, including the way the formulas are written (mathematical formalism). It needs to be improved.
Detailed comments (up to Chapter 3) are written below.
We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. The abstract, introduction and literature review sections have been revised according to your comments.
We have highlighted two main contributions of this study in the abstract and conclusions sections. This paper constructs an accounting framework for investment-related CO2 emissions under trade freedom and trade restrictions based on the MRIO model for the first time. This study quantifies the effect of trade protection on investment-related CO2 emissions in order to provide a reference for policymakers to better grasp the environmental costs behind the evolution of the current trade situation. For example, according to the research results, we should promote free trade to alleviate the pressure of investment -related CO2 emissions. The background description in the introduction is exemplified by citing detailed research. For the hypothesis in the introduction and literature review, we read the studies in recent years, and updated and adjusted some of the papers in this article. In the methodology, we compare the database of this study with other input-output databases, describe the reason for choosing the WIOD, and adjust the formula. The details are written below. Our responses (Red font) to your comments (black font) are given below. The number of lines and pages indicated in the responses correspond to the revised manuscript-highlighted version (with changes marked).
Point 1: Current studies should be cited. Their reliability (whether CO2 emissions cause climate change) and conclusions (what level of CO2 emissions is acceptable) should be discussed at length. Reference to the papers from 2011 [2] and 1990 [3] is insufficient. Item [4] is not relevant to this topic.
Response 1: Thank you for your careful reading of our manuscript. We will replace and improve the relevant documents according to your suggestions. Item [2] is mainly to study the effect of no-carbon greenhouse gases on global warming (Montzka, Dlugokencky, & Butler, 2011). In order to illustrate the relationship between CO2 and global warming, we replace Item [2] and add the research of Shakun et al. in 2012 and Ghommem et al. 2012 research. Item [4] is not relevant to this topic (Wu, Lu, Zhou, Chen, & Xu, 2016). We cite a study by O. Hoegh-Guldberg et al. in 2019 to replace Item [4]. We cite current research results to make a more precise statement about the relationship between CO2 and global warming.
Shakun et al. (2021) construct a record of global surface temperature from 80 proxy records and show that during the last glacier retreat, temperature correlated with and generally lagged CO2. These observations, together with transient global climate model simulations, support the conclusion that an anti-phase hemispheric temperature response to changes in ocean circulation is superimposed on an in-phase global warming driven by increasing CO2 concentrations. Lashof and Ahuja (1990) looks at the effects of CO2 and no-carbon greenhouse on global warming, he finds that CO2 emissions account for 80% of the global warming contribution from current greenhouse gas emissions. Ghommem et al. (2012) use general circulation models (GCMs) to quantify the coupling between the carbon cycle and global temperature. It is found that a very large fraction of CO2 emissions will have to be sequestered to significantly affect global warming. These studies are all illustrating the relationship between CO2 in the greenhouse gas and global warming, and they use different models to analyze the effect of CO2 on the global climate from different perspectives. O. Hoegh-Guldberg et al. (2019) construct a carbon budget model and find that if people want to have a two-thirds probability of controlling global warming at 1.5℃, then the total CO2 in the future will be about 420Gt. If they want to have a 50% probability to control global warming at 1.5 ℃, the total CO2 emissions in the future will be about 580Gt. This study estimates the amount of CO2 emissions that can be accepted to achieve the goal of limiting temperature rise in the future by building a prediction model. This provides a reference for people to take measures to reduce CO2 emissions.
Manuscript changes please see line 37-39 in page 1.
Point 2: Item [5] is outdated and cannot form the basis of the thesis in the paper. Current research should be pointed out and reliably discussed.
Response 2: Thank you for your suggestions. Because item [5] is a long time away from now, this study cannot be used as the basis for this article. We replace this study with the research of Lin and Wang in 2021. Lin and Wang (2021) use the extended log-mean Divisia index (LMDI) to investigate the effects of R&D (research and development) efficiency, R&D intensity, investment intensity, labor productivity, employment structure, urban employment rate, and population urbanization on China's CO2 emissions. It is found that during 2000-2016, the increase of investment intensity has a positive effect on the growth of CO2 emissions.
Manuscript changes please see line 42-43 in page 1.
Point 3: The use of the phrase "trade war" is not professional in an academic paper. Instead, the mechanisms used by countries in international trade should be discussed. Relevant studies should be cited and quantitatively described. You should embed considerations for successive years of the assumed period of analysis.
Response 3：We would like to thank you for careful reading of this manuscript. We are sorry for using some unprofessional terms. Based on your suggestion, we changed the word from "trade war" to "trade conflict". When a trade conflict occurs, some countries restrict the trade between the two countries through tariff or non-tariff barriers. This is the mechanism used by some countries in international trade, which is the trade protection measure mentioned in this article.
This paper supplements some studies to quantify the effect of trade protection on CO2 emissions. For example, Tian et al. (2022) study the effect of the reduction of regional tariffs among RCEP member countries on CO2 emissions, and find that the complete elimination of tariffs among RCEP members will increase the annual CO2 emissions from global fuel combustion by about 3.1%. In a globalized economy, the production of goods can be disrupted by trade disputes. Lin et al. (2019) study the effect of trade disputes on CO2 emissions and find that increasing tariffs is beneficial to reduce carbon dioxide by 6.3%. A free trade scenario will increase global CO2 emissions and air pollution due to higher levels of production, especially in developing regions with relatively high emission intensities. The article embeds significant events that occurred during the analysis period, such as the UK's reduction in engagement with EU trading partners starting in 2013. Fezzigna et al. (2019) look at the EU's foreign trade with the rest of the world over the period 2012-2015, and find that shifting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) will increase its emissions liability by 5%. A similar outcome will occur if the UK replaced its current EU partners with its main Commonwealth trading partners.
Manuscript changes please see line 49-54 in page 2, line 56-59 in page 2.
Point 4: Identifying only three countries based on three causal papers is insufficient. Studies on all relevant countries should be cited. The conclusions of these studies should be discussed.
Response 4: Thank you very much for your careful reading of our manuscript. We cite trade conflicts between China and the United States, the United States and Japan, and the United States and Russia to illustrate that some countries, such as the United States, set up trade barriers to reduce trade exchanges in order to restrain the economic development of other countries. According to your last constructive suggestion, we think that because we are not thoughtful enough, we only describe the trade conflicts between countries, which is one-sided. Therefore, we change this part to the effect of trade restriction mechanisms adopted by some countries on CO2 emissions. For example, some countries raise tariffs to reduce trade transactions. In 2013, the UK reduced trade exchanges with EU trading partners. And we cite some studies to illustrate. Fezzigna et al. (2019) look at the EU's foreign trade with the rest of the world over the period 2012-2015. find that shifting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would increase its emissions liability by 5%. A similar outcome is expected if the UK replaces its current EU partners with its main Commonwealth trading partners. Based on the effect of the US-China trade conflict on CO2 emissions, Du et al. (2020) find that the Sino-US trade conflict can’t bring win-win consequence for the economy and the environment, so trade restrictions are not the best way to manage the environment. Tian et al. (2022) study the effect of the reduction of regional tariffs among RCEP members on CO2 emissions, and find that the complete elimination of tariffs among RCEP members will increase the annual CO2 emissions from global fuel combustion by about 3.1%.
Manuscript changes see line 49-54 in page 2, line 56-59 in page 2.
Point 5: The changes that occurred as a result of the COVID-19 pandemic (quantitative and qualitative) should be discussed.
Response 5: Thank you very much for reading our manuscript carefully, which help to improve the quality of this manuscript. Based on your suggestion, we have added a study to quantify the effect of the COVID-19 on transnational investment activities. The COVID-19 has caused some countries to adopt epidemic prevention and control, which has reduced trade exchanges. Fu et al. (2021) quantify the effect of the COVID-19 on transnational investment activity. They found that globally, international mergers and acquisitions fell by 15% due to the effect of the COVID-19; the number of transnational project financing transactions fell by a quarter. de Lucio et al. (2022) combine Spanish firm-level monthly trade data with country-level COVID-19 containment measures from February to July 2020. The results show that the value of exports fell more in destinations with strict containment measures, while the value of imports was unaffected. Strict containment measures in partner countries increase the likelihood that companies will stop trading with them. Negative effects are concentrated between March and May 2020. Ando and Mukunoki (2022) estimate the gravity equation by using various variables as proxies for COVID-19 damage. They find that regardless of the measures taken to quantify the COVID-19, COVID-19 has been found to have had a significant negative effect on international trade in both exporting and importing countries.
On the one hand, the global spread of the COVID-19 has caused countries to implement trade restrictions and embargoes, directly undermining the international free trade rules system under the WTO framework, which will seriously disrupt and destroy the trade of anti-epidemic materials in various countries in the short term, jeopardizing the patient life. In the medium and long term, there will be serious trade disruption effects due to damage to trade rules. On the other hand, the spread of the epidemic has caused psychological panic and magnified trade protectionism. The customs of various countries have adopted many trade restrictive measures and quarantine measures, which have increased trade costs and directly damaged the already weak global trade.
Manuscript changes please see line 61-63 in page 2.
Point 6: The literature items [10-12] are out of date (2000, 2009, 2012), and item [9] does not consider the effects of COVID. Current studies should be cited. The conclusions of the studies should be discussed.
Response 6: Thank you for your careful reading of this manuscript and your thoughtful comments and constructive suggestions. We have updated the studies in this article based on your suggestions. Replace studies by Al-mulali (2012), List (2000) and Tamazian et al. (2009) with studies by Nejati and Taleghani (2022), Kisswani and Zaitouni (2021) and Zmami and Ben-Salha (2020). Item [9] studies the study of international trade on sustainable development (Xu et al., 2020). The purpose of citing item [9] is to demonstrate that some countries transfer high-pollution industries to other countries, sacrificing the environment of other countries to achieve their own economic growth. We misunderstood you because we didn't describe it clearly enough. Below we describe the changes in detail.
For example, transnational investment increases the pollution emissions of the host country, because developed countries transfer polluting industries to developing countries, sacrificing the environment of developing countries in exchange for their own economic growth. Nejati and Taleghani (2022) study the effect of FDI on CO2 emissions using a multiregional general equilibrium model and find that FDI increases the carbon intensity of the country if it does not have technology diffusion. Xu et al. (2020) use a MRIO model to study the effect of international trade on global sustainable development, and find that compared with developing countries, long-distance trade is more conducive to the realization of sustainable development goals in developed countries.
Some studies hold the opposite view. Kisswani and Zaitouni (2021) examine how FDI affects CO2 emissions in Malaysia and Singapore between 1971 and 2014 to support the hypothesis that developed countries transmit their national advantages to developing countries through transnational investment, thereby improving energy efficiency in developing countries. They find that clean technology transfers flowing into host countries through FDI led to lower CO2 emissions in Malaysia and Singapore. Using a random-effects regression of population, wealth, and technology (STIRPAT) model and the PMG-ARDL approach, Zmami and Ben-Salha (2020) confirm that transnational investment brings host countries clean technology, energy-inefficient industries, as they find that in the short run, FDI flows are associated with less environmental pollution.
Manuscript changes please see line 69-72 in page 2, line 75-78 in page 2.
Point 7: Nothing comes out of quantifying relationships. Indicate what this information can be used for and how.
Response 7: Thank you for your careful reading of our manuscript. We answer this question in two aspects.
On the one hand, this position in the introduction explains in detail the purpose of this study to quantify the effect of trade protection on investment-related CO2 emissions, namely, to provide a reference for policy makers to better grasp the environmental costs behind the evolution of the current trade situation and timely adjust investment policies according to possible changes in the future. This is also the practical application of quantitative results.
On the other hand, in the conclusion, we summarize the quantitative results and give policy recommendations based on these results. Based on the MRIO model, this paper constructs an investment-related CO2 emission accounting framework under the conditions of trade freedom and trade restriction, and quantifies the results from the three levels of country, sector and trade. The results show that under the current trade structure, global trade protection will lead to an increase in investment-related CO2 emissions of up to 546.17 million tons. Transnational investment in final intermediate goods trade contributed 81.6% of the total effect. In terms of different countries, trade protection is quite unfavorable to China and India's CO2 emission reduction, and their CO2 emissions will increase by 105 million tons and 141.5 million tons respectively compared with normal trade. The electricity, gas and water supply sector and manufacturing are the major contributors to investment-related CO2 emissions. In short, the investment CO2 emission accounting framework proposed in this study can more comprehensively and objectively explain the effect of trade protection on investment-related CO2 emissions. The research results provide a reference for measures to reduce investment-related CO2 emissions, such as promoting trade openness and reducing trade barriers to achieve a reduction in global total investment-related CO2 emissions. China and India can attract transnational investment to reduce investment-related CO2 emissions in both countries. China should focus on introducing clean technologies for transnational investment in manufacturing to reduce the sector's contribution to investment-related CO2 emissions. Strengthening China's barriers in trade of final goods or focusing on the energy efficiency of this trade link will have a favorable effect on reducing investment-related CO2 emissions in this trade link. For Russia and Japan, we should pay attention to the quality of investment and optimize the investment structure. In general, trade liberalization has a negative effect on investment related CO2 emissions from the trade of end-stage intermediary goods. Reduce the trade barriers to investment related to intermediate products in the trade of end-stage intermediary goods on a global scale, so as to achieve the greatest possible reduction in investment-related CO2 emissions in this link. Sorry for not elaborating on this sentence, we have added the above to this sentence.
Manuscript changes see lines 78-81 in page 2, lines 579-592 in page 16.
Point 8: There should be a precise definition of what normal trade and no trade mean.
Response 8: Thanks for your thoughtful comment. This paper uses normal trade and no trade to represent trade freedom and trade restriction. Normal trade refers to free trade, which is countries will not take trade protection measures to restrict trade exchanges. No trade means that countries adopt complete trade protection measures and do not trade with each other. This paper simulates the no trade scenario using undifferentiated technology assumptions. There are two approaches in existing research to construct no trade scenarios using multiregional input-output models. The first method is based on differentiated technical assumptions. That is to cancel exports and directly add emissions implied by imports to domestic emissions. For example, Xu et al. (2020) compute global sustainability indicators under normal trade and no trade scenarios, and find that trade raises SDG scores for most advanced economies but lowers them for most developing countries. This method assumes that the technology level of the importing country is exactly the same as that of the country itself. This approach assumes that once global trade is eliminated, the imported goods a country needs are still produced using the technical conditions of the country of origin. In countries where technological differences are small, this assumption is valid. However, this assumption is highly unrealistic across countries with vast technological differences. The research object of this study is global trade, in which North-South trade accounts for a large proportion, and the technological differences between trading countries are often large. In our opinion, this assumption can’t be adopted.
The second approach is based on the assumption of undifferentiated technology. That is to cancel exports and use domestic technology to produce imported products to meet demand. For example, Ackerman et al. (2007) study the effect of Japan-US trade on CO2 emissions and find that without trade, Japan's CO2 emissions increase by 6.7 million tons, while US CO2 emissions decrease by 14.6 million tons. Global CO2 emissions increase by 7.9 million tones Dizenbach and Mukhopadhyay (2007) study the difference between India's emissions in 1992 and 1997 under the two scenarios and find that trade contributed significantly less to India's emissions. Zhang et al. (2017) examine the effect of specific trade patterns on emissions under two scenarios and find that the environmental effect of trade in final goods diminishes over time. This scenario assumes that the goods requested by the importer should be produced domestically using its own level of technology in the absence of global trade. Trade leads to the global flow of technological elements. Once the deal is cancelled, then the flow of these technical factors should also stop. We believe this assumption is more realistic, so this study tends to use this approach to simulate the no trade scenario.
Manuscript changes please see line 84-88 in page 2, line 300-302 in page 7.
Point 9: This is a strong hypothesis that needs to be proven.
Response 9: Thank you for your careful reading of our manuscript, which is very helpful to improve the quality of our research. We based on your opinion on the hypothesis "Many developed countries transfer the environmental pollution generated by their own consumption demand to developing countries through international trade, transnational investment and technology transfer, which results in global environmental pollution" to prove. Three articles were cited separately. Wiedmann and Lenzen (2018) point out that the concern about the effect of international trade on the environment and society has gradually shifted from developed countries to developing countries, and the increase in the effect of environmental pollution related to US export products on China's health is an example. Shifts in production across borders offset slowing policies in some countries. Zwab et al. (2021) address existing limitations with a novel NTS approach and further apply it to estimate the effect of trade on global economic development and greenhouse gas (GHG) emissions. Their findings suggest that current international trade is good for global economic growth, but it emits more greenhouse gases than NTS. GHG emissions from apparel and service-related products in developed countries would increase substantially under the NTS, while GHG emissions from net exporting countries (such as China or Brazil) would decrease under the NTS. Essandoh et al. (2020) consider the short-term dynamics of 52 countries from 1991 to 2014 to explore the long-term correlation between foreign direct investment and CO2 emissions. The study concludes that CO2 emissions are negatively correlated with trade in developed countries in the long run, and positively correlated with foreign direct investment inflows in developing countries in the long run.
Manuscript changes please see line 103-109 in page 3.
Point 10: The items [16-29] only confirm that any investment activity related to energy consumption increases CO2 emissions. Have the authors of any of these papers considered the structure of primary energy consumption and the long-term effects of the implementation of investments (their energy efficiency)? Have the authors of any of these papers considered how economic growth in the countries in question has increased the consumption of goods and services?
Response 10: We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions. We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions. Below we will explain these documents one by one.
This section mainly discusses the investigation of the relationship between investment activities and CO2 emissions in existing research. The specific content is exemplified from three aspects, namely, the effect of domestic investment activities on CO2 emissions and the effect of transnational investment activities on CO2 emissions.
(1) Demonstrate the effect of investment activities on the environment from the perspective of energy consumption and CO2 emissions
Bu et al. (2019) study the relationship between FDI and energy intensity. Based on unique panel data of firms in Jiangsu Province of China during 2005-2007, they find that FDI firms are more energy efficient than non-FDI firms. This is because local firms are linked to clean technologies through FDI, and they are able to absorb advanced green technologies transferred from foreign firms. When building the model, the author controls a group of exogenous variables to check their effect on the energy intensity of the company, including company age, company size, Process, etc. Therefore, the long-term effects of the implementation of investments and economic scale do not affect the findings.
Zhang and Zhou (2016) use the Stochastic Effects of Population, Wealth, and Technology Regression (STIRPAT) model to account for regional differences in the effect of FDI on CO2 emissions. FDI is found to help China reduce CO2 emissions. The effect of FDI on CO2 emissions decreases from the western region to the eastern and central regions. And this hypothesis is more supportive of the pollution halo hypothesis that foreign firms can export greener technologies from developed to developing countries and do business in an environmentally friendly manner. This paper comprehensively considers factors such as population, economy, technology, and geography, and studies the effect of foreign direct investment on different regions of China while controlling other variables. This study uses the panel co-integration test to test the long-term equilibrium between variables, so it also takes into account the long-term effect of investment on CO2 emissions.
Sun et al. (2017) test hypotheses using the Autoregressive Distributed Lag Cointegration (ARDL) method, integrating gross domestic product (GDP), GDP squared, energy use, foreign direct investment (FDI), economic freedom, urbanization, financial development, and trade openness is listed as the main driver of CO2 emissions. This study considers the linkages between the various drivers of CO2 emissions. The results of the bounds tests indicate that there are stable long-term relationships between the selected variables in each model. Considering the long-term nature of foreign direct investment, it is concluded that for every 1% increase in FDI inflow (as a percentage of GDP), CO2 emissions will increase by 0.058%. This study also considers the consumption of alternative energy and nuclear energy as an integral part of energy use. Considering that the development of the financial sector may also affect environmental performance, NDCt is set as an indicator of domestic financial development. This study constructs eight models with different combinations of variables based on the assumption that, in addition to foreign direct investment, several variables have a large effect on air pollution. This study considers the effect of energy consumption structure and economic development on CO2 emissions.
(2) Give examples of "the effect of domestic investment activities on CO2 emissions"
Cadarso et al. (2016) study that increased investment of Spanish tourism in 1995-2007 and find considering the CO2 emissions generated by tourism investment in Spain increases the tourism sector's carbon footprint responsibility based on a life cycle evaluation model. The analysis in this paper takes into account the investment in tourism will promote the development of tourism-related industries, and the CO2 emissions generated by these industries are taken into account in the effect of tourism investment on CO2 emissions. The author defines the system boundary of accounting as all economic activities with investment as the final demand in the whole life cycle. This result is the joint effect of technology effect, structure effect and scale effect, which also covers the influence of energy consumption structure and investment scale. This does not affect the policy significance of the research conclusions, namely, to draw policy makers' attention to the CO2 emissions generated by tourism investment.
Ganda (2019) conducts a study on the effect of national investment in innovation and technology on CO2 emissions. The study uses four indicators of innovation and technology investment, namely renewable energy consumption, number of researchers, R&D spending and number of triplet patent families. Applying a dynamic model and controlling for endogeneity, the study finds that investments in innovation and technology have different effects on CO2 emissions across countries. This mainly depends on which aspects of investment in innovation and technology. FDI, human capital, economic growth, usage of primary energy supply etc. are the control variables as part of this study. Therefore, the long-term effects of the implementation of investments and economic scale do not affect the findings.
Yang et al. analyze (2022) how investments in renewable energy affect CO2 emissions. The study considers the energy efficiency, multiplier effect and scale of investment and finds that increasing the scale of renewable energy investment can indirectly reduce CO2 emissions through technical effects and indirectly increase CO2 emissions through multiplier effects. However, the structural effect of renewable energy investment scale on CO2 emissions is not significant. In addition, the study considered the effect of investments on CO2 emissions of different energy sources. Increased proportional investment in wind energy can reduce CO2 emissions. At the same time, increasing the proportion of investment in solar energy and bioenergy will increase CO2 emissions. However, the effect of increasing investment in the proportion of renewable hydropower on CO2 emissions is not significant. The authors consider the effect of energy consumption structure and investment scale, and draws conclusions for energy investment structure and investment scale.
(3) Provide examples of the effect of transnational investment activities on CO2 emissions
The study by Zafirakis et al (2015). employs a new national power sector emissions estimation framework. Overall, different levels of energy storage are assessed for their potential to prevent electricity trade from countries with higher CO2-emitting factors to countries with lower CO2-emitting factors. We apologize for our omission in citing the Zafirakis et al. study which does not properly demonstrate the effect of transnational investment on CO2 emissions. We replace the Zafirakis et al. (2015) study with that of Zhang et al. (2020). Zhang et al. allocate the carbon footprint of multinational corporations to the investing country based on investment accounting framework. The results of the study find that during the first period (2005-2008) CO2 emissions in the supply chains of multinational corporations increase by 20.4%. The main factor responsible for this increase is the increase in the output of MNEs (scale effect), which would lead to a 27.4% increase in the carbon footprint of MNEs in the absence of other factors. The reduction in carbon intensity offsets -9.3% of the carbon footprint of MNCs (intensity effect), while changes in production technology play a relatively small role (+2.4%, technology effect). This result is the joint effect of technology effect, structure effect and scale effect, which also covers the influence of energy consumption structure and investment scale. This does not affect the practical significance of the research conclusion, namely, investors should bear more responsibility for carbon emission reduction.
Behera and Dash (2017) examine the relationship between urbanization, energy consumption, foreign direct investment (FDI), and carbon dioxide (CO2) emissions in 17 countries in the South and Southeast Asia (SSEA) region during the period 1980-2012. By incorporating fossil fuel energy consumption instead of primary energy consumption into the surrogate regression specification, results show that primary energy consumption, fossil fuel energy consumption and FDI are significantly affecting CO2 emissions in the SSEA region. In addition, empirical results show that primary energy and fossil fuel energy consumption significantly increases CO2 emissions in middle-income countries. The study assumes that in the long run, the negative effect of certain key factors will outweigh the initial positive effect of the variable. Urbanization, primary energy consumption, and FDI are direct functions of the CO2 emission rate. These results take into account the long-term effect of investment and the structure of primary energy consumption, which does not affect the authenticity of the research conclusions.
Acquaye et al. (2017) use MRIO analysis to calculate emissions and resource consumption intensities and footprints, direct and indirect effects, and net emissions flows between countries. Conduct environmental performance assessments at the sectoral level in specific countries and as part of global value chains. Since this paper does not focus too much on the effect of transnational investment on CO2 emissions, we decided to delete this paper.
Tang and Tan (2015) study the relationship between CO2 emissions, energy consumption, FDI and economic growth in Vietnam from 1976 to 2009 and find that there is a long-term equilibrium between economic growth, FDI and energy consumption. A two-way causal relationship between FDI and CO2 is found, with a negative effect on CO2 emissions. Therefore, it also emphasizes that the adoption of clean technology in foreign direct investment is conducive to reducing investment-related CO2 emissions. Co-integration analysis and Granger causality tests are used to test the relationship between variables. All variables are assumed to be endogenous. The author considers the long-term effect of investment and energy consumption, which does not affect the real rationality of the research results.
Shahbaz et al. (2018) examine the functional effect of foreign direct investment (FDI), financial development, economic growth, energy consumption, and innovation in energy research on CO2 emissions. The findings show that FDI has a positive effect on CO2 emissions in France and degrades the French environment. The study incorporates the real per capita GDP and the square term of private sector domestic credit into the carbon emission function to examine the relationship between per capita CO2 emissions and economic growth, as well as between per capita CO2 emissions and financial development. The study used CO2 emissions per capita (metric tons), real GDP per capita (constant local currency), real foreign direct investment per capita (constant local currency), energy consumption (kg oil equivalent) and real domestic Data on credit (constant LCU) are from World Development Indicators (2018). Public budget data (constant in local currency) on energy research and development expenditure are from the European Commission database. Directly use the French time series data from 1955 to 2016 to establish a quantitative economic model to analyze the effect of various variables on CO2 emissions. This does not affect reliability.
Huang et al. (2019) find that the rising level of foreign direct investment and foreign trade was the root cause of environmental pollution. These three documents prove the effect of developed countries' trade behavior on developing countries and the global environment from the perspectives of international trade, transnational investment and technology transfer. In order to determine other socioeconomic factors that affect CO2 emissions, this study uses the STIRPAT model, which takes into account factors such as population size, average wealth, and technological development that may affect the environment. Therefore, the long-term effects of the implementation of investments and economic scale did not affect the findings.
Zhu et al. (2022) construct the input-output decomposition framework and found that foreign direct investment significantly contributes to high-tech manufacturing and CO2 emissions in highly developed economies. The study takes into account the economic and technological level of the investment object. The scale and carbon intensity effects of the investment are also considered. The scale effect makes FDI produce more CO2 emissions, but the carbon intensity effect makes FDI reduce CO2 emissions. This result is the joint effect of technology effect, structure effect and scale effect, which also covers the influence of energy consumption structure and investment scale. This does not affect the practical significance of the research conclusions,
Ji et al. (2019) study the effect of China's domestic investment on energy consumption and economic growth based on the input-output model. Investment has promoted the increase of GDP and energy consumption, and the effect of investment is mainly concentrated in China's top three industries. The input-output model is a quantitative economic analysis method based on the interdependence between different economic sectors or industries. The calculation process is mainly a matrix operation, which does not involve time complexity and convergence criteria.
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Point 11: Most means which ones? Identify specific papers and discuss the conclusions of these papers.
Response 11：Thank you for your careful reading of our manuscript. We are very sorry that we did not find "most" in the position you mentioned, we think the word may be "numerous", so the following we will explain "numerous". At present, many studies are studying the effect of investment activities on the environment.
In this paper, we cite the following papers as examples. Bu et al. (2019) study the relationship between FDI and energy intensity. Based on unique panel data of firms in Jiangsu Province of China during 2005-2007, they find that FDI firms are more energy efficient than non-FDI firms. This is because local firms are linked to clean technologies through FDI, and they are able to absorb advanced green technologies transferred from foreign firms. Zhang and Zhou (2016) use the Stochastic Effects of Population, Wealth, and Technology Regression (STIRPAT) model to account for regional differences in the effect of FDI on CO2 emissions. FDI is found to help China reduce CO2 emissions. The effect of FDI on CO2 emissions decreases from the western region to the eastern and central regions. And this hypothesis is more supportive of the pollution halo hypothesis that foreign firms can export greener technologies from developed to developing countries and do business in an environmentally friendly manner. Sun et al. (2017) test hypotheses using the Autoregressive Distributed Lag Cointegration (ARDL) method, integrating gross domestic product (GDP), GDP squared, energy use, foreign direct investment (FDI), economic freedom, urbanization, financial development. They find trade openness is listed as the main driver of CO2 emissions. This study considers the linkages between the various drivers of CO2 emissions. The results of the bounds tests indicate that there are stable long-term relationships between the selected variables in each model. Considering the long-term nature of FDI, it is concluded that for every 1% increase in FDI inflow (as a percentage of GDP), CO2 emissions will increase by 0.058%.
In addition to the studies in this paper, there are other papers that study the effect of investment activities on CO2 emissions. Muhammad et al. (2020) take 56 countries on the Silk Road as the research object, and find that strengthening the voluntary disclosure of environmental information by multinational investment companies can reduce CO2 emissions. Ahmed et al. (2022) find that FDI generally increases CO2 emissions and greenhouse gases in countries on the African continent. The total amount has a significant negative effect on the environment
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Point 12: What does the analysis of items [30-40] bring to the literature review?
Response12: Thank you for your careful reading of our manuscript. We are very sorry for causing confusion to you due to our unclear description of the central idea of the two paragraphs. We will explain from the following two parts.
(1) This paper aims to explore the effect of trade protection on investment-related CO2 emissions. There are many studies on the effect of trade restrictions and trade liberalization on global environmental quality and CO2 emissions, but few studies address the effect of trade protection on investment-related CO2 emissions. This part aims to cite research related to the effect of trade restrictions and trade freedom on global environmental quality and CO2 emissions to highlight the innovation of our research, namely, the effect of trade protection on investment-related CO2 emissions.
(i) Justification for the emergence of trade protection or trade friction
Holladay et al. (2018) decompose the effect of a country's unilateral strengthening of environmental policies on pollution emissions in the rest of the world based on a double-benefit general equilibrium model. The analysis and figures show that the level of emissions leakage depends on the level of trade friction in the services sector. Increases in domestic pollution taxes reduce emissions in the rest of the world. The study assumes the effect of a country's unilateral strengthening of environmental policies on the rest of the world. The study is not strong enough for background arguments due to our oversight. In order to better prove the gradual emergence of trade protection, this paper selects the research of Voituriez and Wang (2015), which points out that the EU suppresses the price of Chinese export products through trade defense measures—anti-dumping. Use the trade conflict between China and the European Union to demonstrate the emergence of trade protection.
Fajgelbaum and Khandelwal (2022) point out that in 2018, there was a trade conflict between China and the United States, and the United States deviated from history and took the lead in integrating the global market. By the end of 2019, the U.S. had imported about $350 billion in Chinese imports, and China had retaliated against $100 billion in U.S. exports.
(ii) An illustration of the effect of trade restrictions on global environmental quality in relation to CO2 emissions.
de Melo and Solleder (2020) conclude that by reducing tariff and non-tariff barriers, developing countries can benefit from better markets for environmental goods and services. Liu et al. (2020) find that the implementation of Sino-US trade frictions reduces the environmental emissions of both parties, but increases the environmental emissions of other countries, and generally reduces global CO2 emissions and some pollutant emissions.
(iii) The effect of trade freedom on global CO2 emissions.
Zhang et al. (2021) take 52 countries along the Belt and Road as research objects and conclude that CO2 emissions are inversely linked with exports and significantly linked with imports. Alola (2019) discovers that American trade policies increase CO2 emissions in short order. Wang and Zhang (2021) come to the conclusion that free trade significantly affects the dissociation of economic growth from CO2 emissions in developed countries but inversely affects it in developing countries. This study complements a study by Wang and Wang to illustrate the effect of trade liberalization on investment-related CO2 emissions. Wang and Wang (2021) choose FDI as an intermediary variable, and explore the threshold effect of FDI on trade openness affecting CO2 emissions. The research results show that with the increase of FDI, trade openness is obviously beneficial to the reduction of carbon intensity.
(2) In recent years, with the economic globalization, the production process is distributed all over the world. Under the influence of global manufacturing fragmentation, countries are linked globally through different trades according to their technological and manufacturing characteristics. Each country's position in global production is inextricably linked to the global division of responsibilities for reducing emissions. This part aims to provide support for the division of global value chains in this study with the existing studies.
(i) Examples of the environmental effects of global production fragmentation
Liu et al. (2016) study the effect of China's accession to the WTO in 2001 and its participation in international trade on its own pollutant emissions. It is found that increasing the import of intermediate products and finished products after joining WTO can reduce or avoid domestic pollutant discharge to a certain extent. China suffers more local emissions than its trading partners after joining the WTO. Using China's multiregional input-output tables for 2007, 2010, and 2012, Feng (2020) explores the effect of production fragmentation on virtual carbon trade derived from three trade patterns, namely trade in final goods, trade in intermediate goods at the final stage of production, and value Chain related trade. The results show that the first two trade patterns help reduce CO2 emissions, while value chain-related trade leads to carbon growth. Tian et al. (2022) study the effect of international value chain integration on the carbon intensity of developing and developed countries in RCEP member countries.
(ii) Provide a basis for the division of trade links
Wang et al. (2022) decompose the trade area triggered by domestic demand into three links, namely trade of final goods, trade of end-stage intermediary goods and trade of remaining-stage intermediary goods in accordance with the Leontief inverse matrix's decomposition findings. Zhang et al. (2017) decomposes international trade into three trade links to study the effect of trade links on global CO2 emissions. It is found that the share of implied emissions corresponding to the trade of traditional intermediate products is the largest, the share of emissions induced by the global value chain is gradually increasing, and the international net carbon transfer is mainly completed through the trade of final products.
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Point 13: Five papers [41-46] refer to the study of local and limited issues. Can these methods be applied to a worldwide analysis? Likewise, items [47-49] deal only with local issues - where else and by whom have general and broader issues been studied?
Response 13: Thank you for reading this article carefully, and for your thoughtful comments and constructive suggestions, which will help improve the quality of this article.
We have listed three methods here, namely, econometric analysis, decomposition analysis, and input-output analysis. These three methods are common methods for studying the effect of trade and investment activities on CO2 emissions, and they can be used for regional or global research. We regret that the studies we have listed ignore the characteristics of the study area, and only cover some local examples, but not global examples. Below we will introduce the characteristics (scopes) of these three methods respectively, and add some general or broader case studies.
(1) econometric analysis
The main process of econometric analysis is to build a model, estimate parameters and use the model. It can be used for variable relationship studies of macro or micro variables, and the field of study can be regional or global, depending on the availability of data. Researching the effect of trade and investment on CO2 emissions can establish a model relationship between variables and CO2 emissions. It can be used not only to analyze the effect of trade and investment on CO2 emissions of individual countries, but also to the effect of trade and investment on international CO2 emissions. For example, Kahia et al. (2019) use the latest panel vector autoregressive model to study the effect of renewable energy consumption, economic growth, foreign direct investment inflows, and trade on CO2 emissions for a panel of 12 Middle East and North African countries during the period 1980 to 2012. Wang and Zhang (2020) examine whether increasing investment in R&D can help decouple economic growth from CO2 emissions. This study uses the fully modified ordinary least squares method to empirically estimate the R&D investment and CO2 emissions of the BRICS countries from 1996 to 2014. The results show that for every 1% increase in R&D investment, CO2 emissions will decrease by 0.8122% for the BRICS as a whole, indicating that increasing R&D investment has a positive effect on the decoupling of economic growth and environmental pressure. On a country-by-country basis, this effect is most pronounced in China and weaker in Russia and India.
(2) decomposition analysis
It can be used to study the driving forces behind economic, social, and environmental flows at the global level, and is usually divided into driving forces of technological progress, driving forces of structural changes, and driving forces of scale effects. If you have a global input-output table and a list of related variables, you can use decomposition analysis to study global issues. Zhu et al. (2022) propose a cross-country input-output decomposition framework that distinguishes between domestic firms and multinational firms, and recalculates global value chain emissions, including emissions from international trade (trade-related global value chain emissions), foreign direct Investment (GVC emissions related to foreign direct investment), and both (GVC emissions related to trade and FDI). It is found that from 2005 to 2016, global FDI-related GVC emissions increased by about 704.6 million tons, mainly due to the scale effect, while the carbon intensity effect led to a decrease in FDI-related GVC emissions. Andreoni and Galmarini (2016) conduct an exponential decomposition analysis of energy-related CO2 emissions for 33 countries of the world using data from the period 1995-2007. The results show that economic growth has been the main driver of increases in energy-related CO2 emissions.
(3) input-output analysis
The input-output analysis method includes two models: MRIO model and SRIO model. MRIO model is used for describing the trade between economies, namely the economic trade between the sectors of the country where the inputs come from and the sectors of the country where they are distributed. It includes single regional input-output model (SRIO) and MRIO model. The SRIO model assumes that the rest of the world except the target country is a whole, and cannot analyze the trade between countries. The MRIO model reflects the role of countries in the global value chain, and takes into account the differences in national technology levels. When applying the multi-regional input-output model to analyze the effect of investment on CO2 emissions, the relevant CO2 emissions of each country are also calculated to calculate the global CO2 emissions. Based on the World Input-Output Database (WIOD), Deng and Xu (2017) establish a multi-regional input-output model to estimate the global embodied carbon trade from 1995 to 2009. Apply the Structural Decomposition Analysis (SDA) method to quantify the changes in the scale and structure of the implied carbon trade in China, India, Japan and the United States. The results show that the United States, China, and Japan in 1995 and the United States, China, and India in 2009 are the top three countries with the highest degree of concrete carbon trade. Using a multi-regional input-output model of the global economy and a hypothetical extraction method, Hertwich (2021) quantifies the greenhouse gas emissions in the production of materials and the carbon footprint of materials as the first user of materials and the final consumption industry. Greenhouse gas emissions from materials production alone increase by 120% from 1995 to 2015, with 11 billion tons of CO2 equivalent emitted in 2015. Materials production increase from 15% to 23% of global emissions. Hong et al. (2022) assess land-use emissions reflected in global trade from 2004 to 2017 by using new emissions estimates and a multiregional input-output model. About three-quarters of embodied emissions come from land-use change, the largest share of which is shifted from low-income countries such as Brazil, Indonesia and Argentina to more industrialized regions such as Europe, the United States and China. Therefore, reducing global land-use emissions and sustainable development may depend on improving supply chain transparency. Meng et al. (2018) use three methods (multi-regional environmental input-output analysis, bilateral trade implied emission method, and structural decomposition analysis) to evaluate the total amount of embodied carbon emissions and emission transfers in South-South trade. The results show that carbon emissions embodied in South-South trade more than doubled between 2004 and 2011, reflecting a new phase of globalization: some production activities are shifting from China and India to other developing countries, especially energy production of raw materials and intermediate goods in intensive sectors.
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Point 14: The description of the model should be written in the next chapter.
Response 14：Thank you for your careful reading of our manuscript. Based on your suggestion, we moved this sentence to methodology and described it in more detail.
Manuscript changes please see line 252-253 in page 5.
Point 15: What kind of guidance does the study provide?
Response 15：We would like to thank you for careful reading. Regarding this question, we answer this question from two aspects.
This article has two meanings. One is the theoretical aspect. The effect of trade protection on the environment has become a research hotspot in recent years. However, the existing papers are more about the effect of transnational investment on CO2 emissions, and seldom study the effect of trade protection on investment-related CO2 emissions. To fill this research gap, this paper constructs an accounting framework for investment-related CO2 emissions under trade freedom and trade restrictions based on the MRIO model for the first time. The effect of global trade protection on investment-related CO2 emissions is revealed from the three levels of country, section and trade links. effect on emissions.
Another aspect is reality. In the process of trade globalization, the connection between economy and environment among countries is intricate, which has attracted extensive attention of scholars. What effect will the evolution of global trade patterns have on investment-related CO2 emissions? This study quantifies the effect of trade protection on investment-related CO2 emissions to provide a reference for policy makers to better grasp the environmental costs behind the evolution of the current trade situation. And timely adjustment of investment policies according to possible changes in the future will play an important role in reducing investment-related CO2 emissions.
In summary, the research results provide a reference for measures to reduce investment-related CO2 emissions, such as promoting trade openness and reducing trade barriers to achieve a reduction in global total investment-related CO2 emissions. China and India can attract transnational investment to reduce investment-related CO2 emissions in both countries. China should focus on introducing clean technologies for transnational investment in manufacturing to reduce the sector's contribution to investment-related CO2 emissions. Strengthening China's barriers in trade of final goods or focusing on the energy efficiency of this trade link will have a favorable effect on reducing investment-related CO2 emissions in this trade link. For Russia and Japan, we should pay attention to the quality of investment and optimize the investment structure. In general, trade liberalization has a negative effect on investment-related CO2 emissions from the trade of end-stage intermediary goods. Reduce the trade barriers to investment related to intermediate products in the trade of end-stage intermediary goods on a global scale, so as to achieve the greatest possible reduction in investment-related CO2 emissions in this link.
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Point 16: The chosen model is very simple. It is reduced to elementary transformations and the determination of a few indicators. You should describe why this model was chosen. Compare this model with other available models. You should justify whether it allows you to describe the real situation in the current period. Indicate what simplifications the model has (what it does not take into account and how this affects the research). Describe how validation of the model was carried out and what the conclusions are. Describe how different scenarios can be differentiated from the model (how to run different simulations). A sensitivity analysis should be conducted and the results should be discussed.
Response 16: Thank you very much for your careful reading of our manuscript. We have modified the Methods section according to your suggestion. In addition, the application of other methods in this field is presented in the literature review section, and these methods are compared with multi-regional input-output model. A simplification of the method is illustrated in the Introduction and Literature Review sections. We will answer your questions from the following five aspects:
The MRIO model is the main tool for studying trade environment issues.
(1) The MRIO model is a major tool for studying trade environment issues. Method 3.1 presents the rationale for the model:
MRIO model is used for describing the trade between economies, namely the economic trade between the sectors of the country where the inputs come from and the sectors of the country where they are distributed. It includes single regional in-put-output model (SRIO) and MRIO model. The SRIO model assumes that the rest of the world except the target country is a whole, and cannot analyze the trade between countries. The MRIO model reflects the role of countries in the global value chain, and takes into account the differences in national technology levels. In this paper, MRIO model is used to analyze the effect of transnational investment on global CO2 emissions.
(2) We supplement the literature review section with a comparison of other methods with multi-regional input-output models, pointing out the limitations of other methods.
In the literature review part, this paper proposes three methods for studying the relationship between trade and environment, which are econometric analysis, decomposition analysis and input-output analysis. Econometric analysis needs to consider whether the existing data are reliable, whether the model and the research object are suitable, and whether the results are robust. It is necessary to have high economic analysis ability and master mathematical analysis skills at the same time, and the analysis cost is relatively high. Decomposition analysis will lead to different decomposition results due to the non-unique change path, and may even obtain a decomposition result that deviates greatly from reality due to the wrong identification of the sequence of changes. Input-output models are widely used to track the environmental footprint and social footprint caused by global supply chain economic activities. Input-output analysis takes the entire economic system as the boundary, and calculates the direct and indirect effect of economic changes on the environment. It is comprehensive, and if the model is selected properly, it can save time and manpower. Input-output model is a static structural model that provides high resolution of sectoral and structural economic composition. This makes input-output model a useful tool for supply chain effect assessment. Although there is a certain lag in the input-output table due to the large amount of data contained in it. However, a country's industrial structure and technological level will not undergo major changes in a short period of time, and the input-output table is very accurate and comprehensive in describing the operation of the social and economic system. Therefore, this model has been widely used in trade-related research for a long time, and its research results still have good reference value.
(3) Simplification of the model
Based on the multi-regional input-output model, this paper constructs an accounting framework for investment-related CO2 emissions under trade freedom and trade restrictions, and replaces trade freedom and trade restrictions with normal trade and no trade. Based on the undifferentiated technology assumption, that is, to cancel exports and use domestic technology to produce imported products to meet demand. This scenario assumes that, in the absence of global trade, the goods requested by the importer should be produced domestically using its own level of technology. Trade has led to the flow of technological elements on a global scale. Once the deal is cancelled, then the flow of these technical factors should also stop. We believe this assumption is more realistic.
(4) The model does not require validation and sensitivity analysis.
The multi-regional input-output model is a quantitative economic analysis method based on the interdependence between different economic sectors or industries. The calculation process is mainly a matrix operation, which does not involve time complexity and convergence criteria.
(5) This article divides the international trade into three trade links, namely trade of final goods, trade of end-stage intermediary goods and trade of remaining-stage intermediary goods. Investment partners directly absorb transnational investment products in the trade of final goods. The trade of end-stage intermediary goods needs further reproduction by the investment partner before it can be fully absorbed by the investor. Investment related to remaining-stage intermediary goods crosses more than once and requires direct or indirect investment between sectors in countries other than the home country.
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Point 17: Editorial faults.
Response 17: We would like to thank you for careful reading of this manuscript. We've made adjustments to the format based on your comments.
Manuscript changes please see line 290-291 in page 6.
Point 18: The indicators given are very general. It is difficult to understand what conclusions can be drawn from such aggregated data.
Response 18: We would like to thank you for careful reading of this manuscript and We will answer your questions from the following two aspects.
(1) The main databases in this paper are MRIO table and WIOD's Environmental Accounting Database. We use the sum of total fixed asset formation (in millions of national currencies) and changes in inventories and other valuables (in millions of national currencies) in the final demand of the MRIO table as actual investment capital. The WIOD's Environmental Accounting Database was utilized to obtain CO2 emissions data by section and country from 2000 to 2014 to calculate the carbon intensity. Using MRIO table and carbon intensity, the effect of trade protection on investment-related CO2 emissions is quantified through a multi-regional input-output model.
(2) Use these aggregated indicators with a multiregional input-output model to draw conclusions for this study. As follows: global trade protection would lead to an increase of up to 546.17 million tons in investment-related CO2 emissions under current trade structures. Transnational investment in the trade of end-stage intermediary goods contributed 81.6% of the total effect. In terms of countries, trade protection is quite disadvantageous to CO2 emissions reduction in China and India, and their CO2 emissions will respectively increase by 105 million tons and 141.5 million tons compared to normal trade. The electricity, gas, and water supply sectors and the manufacturing sector are the main sectors to investment-related CO2 emissions.
Point 19: The matrix should be formally defined, as how to determine all its components. Why is this matrix symmetric and non-zero only on the diagonal?
Response 19: We would like to thank you for careful reading of this manuscript and for the thoughtful comments. We define the carbon intensity of sector s in country n as, typifies the CO2 emission of the sector s of economy n, and typifies the total output of the sector s of economy n. The matrix F is a diagonal matrix consisting of. The multi-regional input-output model is a quantitative economic analysis method based on the interdependence between different economic sectors or industries. The calculation process is mainly a matrix operation. According to the matrix operation, F should be a symmetrical and non-zero matrix on the diagonal.
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Point 20: The reference to a 1970 article is insufficient. Are there other sources of data? If so, which ones and why were they not used (at least discussed)? Item [53] is only causal. The data end in 2014. The data are not relevant to the purpose and scope of the study.
Response 20: We would like to thank you for careful reading of this manuscript and for the thoughtful comments. We have further supported the characterization of the input-output table based on your suggestion. The WIOD in this paper is compared with other databases. And explain the feasibility of using the data period in this paper. We will answer from the following three points.
(1) The MRIO tables are derived from the World input-output databases (WIOD), which provides researchers with detailed data on global structural change and economic growth. Since item [52] is relatively old and item [53] is only causal, we decided to replace item [52] and item [53] with the research of Long (2020) and Rocco (2016). Long et al. (2020) point out that the carbon footprint can be analyzed by using MRIO tables including emissions consumption, investment and exports included in the final demand. Rocco and Colombo (2016) point out that MRIO tables provide a standard, massively available and continuously updated data source for simulating supply chains to assess environmental pressures associated with goods and services.
(2) At present, several mature teams around the world have completed the compilation of multi-regional input-output tables by integrating trade data between countries, which facilitates researchers to directly use these well-compiled data to carry out their own research. Multi-regional input-output table databases include EORA, GTAP, WIOD, etc. By comparing and analyzing various multi-regional input-output table databases, this study decided to use the WIOD database.
The EORA global supply chain database consists of a multi-regional input-output table model, which contains a complete time series from 1990-2021. However, compared with the 56 departments in the WIOD, the EORA database has only 26 departments. The WIOD provides a more detailed description of sectoral transfers between countries.
The GATP database describes domestic transactions, global bilateral trade patterns, international transportation costs, and trade protection matrices connecting various countries and regions. The eleventh edition of the GTAP database (the latest edition) provides only five reference years (2004, 2007, 2011, 2014 and 2017). The GTAP database does not have a complete time series, which is very unfavorable for studying the trade rules of continuous years.
WIOD has time-series data tables specifically designed to track growth over time, using national accounts data on output, value added, trade, and consumption as standard. The economic transactions in the multi-regional input-output table are all calculated at the basic price, so as to better represent the production technology structure. The latest multiregional input-output tables describe trade flows between countries and sectors from 2000 to 2014, covering 43 countries and 56 sectors. The period 2000-2014 also contains large-scale events in global trade (see (3) for details). In summary, after weighing, the WIOD database was selected.
(3) Feasibility of using data from 2000-2014
(i) The research time interval selected in this study is 2000-2014, which is very representative. It covers some of the large-scale shifting events in the global trade landscape.
The year 2000 was chosen as the starting point for the study. This is because the structure of global trade has undergone profound changes since the early 2000s, especially since China's accession to the World Trade Organization in 2001, as emerging developing economies have continued to participate in international trade. Trade has led to changes in the source structure of goods, which in turn has an effect on the economy, resources and environment of various countries. The World Trade Organization (WTO), the European Free Trade Association (EFTA) and China's "One Belt, One Road" strategy have all promoted the liberalization and facilitation of trade between regions or countries to varying degrees. With a large number of third world countries participating in global trade, the world trade center began to shift to large emerging developing economies, and the proportion of developed countries in international trade declined sharply. This has also led to developing economies such as China and India becoming the "world's factory". The hidden pollutants in the export trade have greatly increased their environmental pressure.
However, the financial crisis in 2008 swept the world, and the global free trade system was greatly affected, which exacerbated the uncertainty of the global economic recovery. At the same time, global trade has been severely affected, and trade protectionism continues to heat up. In 2013, the United States and the European Union officially launched negotiations on the Transatlantic Trade and Investment Partnership. Global bilateral and regional trade rules are gradually emerging as tariff levels continue to increase. The effect of trade on the global environment has also created additional uncertainty.
Therefore, with the support of limited data sources, we believe that choosing 2000-2014 as the research interval is more representative.
(ii) The database used in this study is the World Input-Output Database (WIOD). The November 2016 release of WIOD includes input-output tables for the period 2000-2014. Since the compilation of input-output tables involves complex and cumbersome economic statistics in various economic and social systems, it requires a lot of manpower and material resources, as well as a lot of time, so there is often a certain lag in the release time of input-output tables. The problem of data lag is also a common problem faced by researchers in the field of input-output analysis. But in general, a country's industrial structure and production technology level will not change significantly in a short period of time, and the input-output table is very accurate and comprehensive in describing the operation process of the social and economic system. Therefore, this model has been widely used in trade-related research, and its research results still have a good reference value for grasping the current global trade pattern and its environmental effect.
Manuscript changes please see line 363-368 in page 7, line 358-360 in page 9.
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Author Response File: Author Response.pdf
Reviewer 3 Report
The article addresses an interesting topic with useful tools: the effect of global trade protection on investment related CO2 emissions thorough a MRIO. The paper presents some weak points that should be overcome:
- The introduction section is well motivated and structurated.
- In the literature section, the references about works on the effect of trade protection on investment-related CO2 emission are scarce. The text indicates that they are few, but they are not detailed. It is important to state their work in the context of the recent literature about the scope ( see recent works of Qiang Wang) and the contribution with previous works.
- Authors should established the interested of the MRIO for the analysis of this work and the applicability degree in the regional science.
- The methodology section doesn´t defined the terms clearly. For example, the terms IEin, IEfn, IEgn must previosusly crearly. References to other works that have used this methodology have been pointed out. Mention to the authors of this technique must be included. The authors assume two scenarios: normal trade scenario for free trade scenario and no trade scenario for protection scenario. Do other works employ these scenarios? What limitations they have?
- In the data source, the authors must justify the used databased. In the conclusion, section mention other sources, but they don´t justify the use of WIOD. EORA include more recent data..
- In the results section, acronyms for the countries and sectors (see figures) should be established. Maybe in an appendix. Does the literature countersing the results?
Author Response
Response to Reviewer 3 Comments
Response:
We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. Our responses (red font) to your comments (black font) are given below. The number of lines and pages indicated in the responses corresponds to the revised manuscript-highlighted version (with changes marked).
Point 1: In the literature section, the references about works on the effect of trade protection on investment-related CO2 emission are scarce. The text indicates that they are few, but they are not detailed. It is important to state their work in the context of the recent literature about the scope (see recent works of Qiang Wang) and the contribution with previous works.
Response 1: We would like to thank you for your careful reading of this manuscript and your thoughtful comments. Based on your suggestion, we elaborate the existing studies and cite some of Mr. Wang Qiang's research to illustrate the effect of trade openness on CO2 emissions. There are currently few papers on the effect of trade protection on investment-related CO2 emissions. In order to study the effect of trade openness on CO2 emissions, Wang and Wang (2021) choose FDI as an intermediary variable to explore the threshold effect of FDI on trade openness affecting CO2 emissions. The results show that trade openness and FDI have significant asymmetric effects on carbon intensity. With FDI as the threshold variable, the effect of trade openness on carbon intensity is negatively correlated. With the increase of FDI, trade openness is obviously conducive to the reduction of carbon intensity. Therefore, it is very important to gradually increase the degree of economic openness and realize the positive effect of FDI on carbon intensity reduction. In order to study the decoupling effect of trade on CO2 emissions, and under what circumstances trade contributes to the decoupling of CO2 emissions. Wang et al. (2023) develop a combination of the Tapio decoupling model and the structural threshold model to study and quantify the effects. The results show that the dominant state of the relationship between trade openness, economic growth, and CO2 emissions is weak decoupling. In addition, it is found that there are two breakpoints in the effect of trade openness on CO2 emissions; once the structural breakpoint is broken, trade openness will suppress CO2 emissions and help achieve global carbon neutrality, which runs counter to the claims of trade protectionists. Wang and Wang (2020) explore the long-term effects of changes in CO2 emissions by disaggregating the CO2 emissions of the world and different income groups from 1990 to 2014. The results show that trade openness contributes to carbon reduction globally and by income groups in the long run emissions, although trade openness will lead to higher CO2 emissions in developing countries in the short run. Wang and Zhang (2021) explore the effect of protectionism (by measuring trade openness based on available data) on decoupling CO2 emissions from economic growth. Using data from 182 countries from 1990 to 2015, this paper examines the heterogeneous effect of trade openness on CO2 emissions. The results show that trade openness has a positive effect on the decoupling of economic growth and CO2 emissions in rich countries, but a negative effect on poor countries.
Existing research mainly focuses on the effect of investment on CO2 emissions under normal trade conditions. Shahbaz et al. (2018) study the effect of FDI on CO2 emissions using French time series data from 1955 to 2016. The empirical results emphasize the existence of time series cointegration, and the research results show that foreign direct investment has a positive effect on French CO2 emissions. Zhang and Zhou (2016) use the STIRPAT model to study that foreign direct investment is beneficial to the reduction of investment-related CO2 emissions in China. But these studies don’t involve to the effect of trade openness on investment-related CO2 emissions.
Based on the existing studies, this paper studies the effect of trade protection on investment-related CO2 emissions. For the first time, this paper constructs an accounting framework for investment-related CO2 emissions under the conditions of trade freedom and trade restriction based on the MRIO model. Based on undifferentiated technology assumptions, namely, to cancel exports, use domestic technology to produce imported products to meet demand, and replace trade restriction scenarios with no trade scenarios. Investment-related CO2 emissions are determined for 16 economies under two scenarios of free trade and restricted trade. On the basis of comparing the two scenarios, it reveals the effect of global trade protection on investment-related CO2 emissions from the three levels of country, sector and trade links.
Manuscript changes please see line 160-161 in page 4, line 164-165 in page 4, line 169-171 in page 4.
Point 2: Authors should established the interested of the MRIO for the analysis of this work and the applicability degree in the regional science.
Response 2: We would like to thank you for careful reading of this manuscript and for the thoughtful comments and constructive suggestions. We complement the strengths of MRIO models in our literature review and methodology. The MRIO model is the main tool for studying trade environment issues.
(1) The MRIO model is the main tool for studying trade environment issues. Method 3.1 presents the rationale for the model:
MRIO model is used for describing the trade between economies, namely the economic trade between the sectors of the country where the inputs come from and the sectors of the country where they are distributed. It includes single regional input-output model (SRIO) and MRIO model. The SRIO model assumes that the rest of the world except the target country is a whole, and cannot analyze the trade between countries. The MRIO model reflects the role of countries in the global value chain, and takes into account the differences in national technology levels. In this paper, MRIO model is used to analyze the effect of transnational investment on global CO2 emissions.
(2) We supplement the comparison of other methods with the multi-regional input-output model in the literature review section, pointing out the limitations of other methods.
In the literature review part, this paper proposes three methods for studying the relationship between trade and environment, which are econometric analysis, decomposition analysis and input-output analysis. Econometric analysis needs to consider whether the existing data are reliable, whether the model and the research object are suitable, and whether the results are robust. It is necessary to have high economic analysis ability and master mathematical analysis skills at the same time, and the analysis cost is relatively high. Decomposition analysis will lead to different decomposition results due to the non-unique change path, and may even obtain a decomposition result that deviates greatly from reality due to the wrong identification of the sequence of changes. Input-output models are widely used to track the environmental footprint and social footprint caused by global supply chain economic activities. Input-output analysis takes the entire economic system as the boundary, and calculates the direct and indirect effect of economic changes on the environment. It is comprehensive, and if the model is selected properly, it can save time and manpower. Although there is a certain lag in the input-output table due to the large amount of data contained. However, a country's industrial structure and technological level will not undergo major changes in a short period of time, and the input-output table is very accurate and comprehensive in describing the operation of the social and economic system. Therefore, this model has been widely used in trade-related research for a long time, and its research results still have good reference value.
Manuscript changes please see line 223-224 in page 5, line 252-258 in page 5.
Point 3: The methodology section doesn´t defined the terms clearly. For example, the terms IEin, IEfn, IEgn must previosusly crearly. References to other works that have used this methodology have been pointed out. Mention to the authors of this technique must be included. The authors assume two scenarios: normal trade scenario for free trade scenario and no trade scenario for protection scenario. Do other works employ these scenarios? What limitations they have?
Response 3：Thank you very much for your questions about this manuscript. We have revised the manuscript based on your suggestions. We predetermine and define the terms , , and in detail. Studies using the same division of trade links as this study are described in the literature review section. In the conclusion part, it points out the limitations of the hypothetical " free trade scenario replaces normal trade scenario and no trade scenario replaces trade restriction scenario ".
(1) We are very sorry for the misunderstanding caused by our non-standard writing. The terms , , and have not been explained in advance, making the content unclear. We have explained and defined the terms , , and in advance. is defined as the transnational investment demand of final goods, where investment partners directly absorb transnational investment products. is the transnational investment demand of end-stage intermediary goods, which needs further reproduction by the investment partner before it can be fully absorbed by the investor. is narrowly defined as transnational investment demand of remaining-stage intermediary goods. Investment in the first two forms of trade crosses borders once and is eventually absorbed by the investors.
(2) This article divides the international trade into three trade links, namely trade of final goods, trade of end-stage intermediary goods and trade of remaining-stage intermediary goods. Investment partners directly absorb transnational investment products in the trade of final goods. The trade of end-stage intermediary goods needs further reproduction by the investment partner before it can be fully absorbed by the investor. Investment related to remaining-stage intermediary goods crosses more than once and requires direct or indirect investment between sectors in countries other than the home country. Wang et al. (2022) decompose the trade area triggered by domestic demand into three links, namely trade of final goods, trade of end-stage intermediary goods and trade of remaining-stage intermediary goods in accordance with the Leontief inverse matrix's decomposition findings. Zhang et al. (2017) use the same decomposition method to divide trade into three links in order to study the effect of different trade links on global CO2 emissions.
(3) In this paper, normal trade is used instead of free trade, and no trade is used instead of trade restriction. No trade is based on a differentiated technological assumption that exports are eliminated and imports are produced using domestic technology to meet demand. This scenario assumes that, in the absence of global trade, the goods requested by the importer should be produced domestically using its own level of technology. Trade has led to the flow of technological elements on a global scale. Once the deal is cancelled, then the flow of these technical factors should also stop. We believe this assumption is more realistic. For example, Ackerman et al. (2007) study the effect of Japan-US trade on CO2 emissions and find that in the absence of trade, Japan's CO2 emissions increased by 6.7 million tons, while the US' CO2 emissions decreased by 14.6 million tons. Global CO2 emissions increase by 7.9 million tons (The carbon content of Japan–US trade.). Wang et al. (2022) estimate the environmental efficiency of developing and developed countries with and without trade. The results confirm that trade increases CO2 in developing economies by 12.9% and reduces CO2 emissions in advanced economies by 6.0%, respectively.
But this assumption is an extreme case of two trade scenarios. With the improvement of the economic strength of some countries, in order to maintain their own market competitiveness, they will inevitably take some measures to restrain the development of other countries. There will always be trade frictions. We calculate outcomes for the no trade scenario using undifferentiated technical assumptions, namely, each country uses its own technology to produce the original imported good. But the reality is that a country may not have the technology or resource endowment to make it happen. This assumption is also limited. Although this assumption is an extreme case of the two trade situations, this extreme case facilitates the quantification of the effect of trade protection on investment-related CO2 emissions. Provide a reference to policymakers to better grasp the environmental costs behind the evolution of the current trade situation and timely adjust investment policies ac-cording to possible changes in the future.
Manuscript changes please see line 281-289 in page 6, line 183-189 in page 4, line 579-592 in page 16.
Point 4: In the data source, the authors must justify the used databased. In the conclusion, section mention other sources, but they don´t justify the use of WIOD. EORA include more recent data.
Response 4: We would like to thank you for careful reading of this manuscript and for the thoughtful comments. In the methodology and conclusion, we compared various multi-regional input-output table databases to explain why this study uses WIOD.
At present, many mature teams around the world have completed the compilation of multi-regional input-output tables by integrating trade data between countries, which facilitates researchers to directly use these well-compiled data to carry out their own research. Multi-regional input-output table databases include EORA, GTAP, WIOD, etc. By comparing and analyzing various multi-regional input-output table databases, this study decided to use the WIOD.
The EORA global supply chain database consists of a multi-regional input-output table model, which contains a complete time series from 1990-2021. However, compared with the 56 departments in the WIOD database, the EORA database has only 26 departments. The WIOD database provides a more detailed description of sectoral transfers between countries.
The GATP database describes domestic transactions, global bilateral trade patterns, international transportation costs, and trade protection matrices connecting various countries and regions. The eleventh edition of the GTAP database (the latest edition) provides only five reference years (2004, 2007, 2011, 2014 and 2017). The GTAP database does not have a complete time series, which is very unfavorable for studying the trade rules of continuous years.
WIOD has time-series data tables specifically designed to track growth over time, using national accounts data on output, value added, trade, and consumption as standard. The economic transactions in the multi-regional input-output table are all calculated at the basic price, so as to better represent the production technology structure. The latest multiregional input-output tables describe trade flows between countries and sectors from 2000 to 2014, covering 43 countries and 56 sectors.
The period 2000-2014 covered by WIOD contains large-scale events in global trade, and the year 2000 was chosen as the starting point for the study. This is because the structure of global trade has undergone profound changes since the early 2000s, especially since China's accession to the World Trade Organization in 2001, as emerging developing economies have continued to participate in international trade. Trade has led to changes in the source structure of goods, which in turn has an effect on the economy, resources and environment of various countries. The World Trade Organization (WTO), the European Free Trade Association (EFTA) and China's "One Belt, One Road" strategy have all promoted the liberalization and facilitation of trade between regions or countries to varying degrees. With a large number of third world countries participating in global trade, the world trade center began to shift to large emerging developing economies, and the proportion of developed countries in international trade declined sharply. This has also led to developing economies such as China and India becoming the "world's factory". The hidden pollutants in the export trade have greatly increased their environmental pressure.
However, the financial crisis in 2008 swept the world, and the global free trade system was greatly affected, which exacerbated the uncertainty of the global economic recovery. At the same time, global trade has been severely affected, and trade protectionism continues to heat up. In 2013, the United States and the European Union officially launched negotiations on the Transatlantic Trade and Investment Partnership. Global bilateral and regional trade rules are gradually emerging as tariff levels continue to increase. The effect of trade on the global environment has also created additional uncertainty. In summary, after weighing, the WIOD database was selected.
Manuscript changes please see line 363-368 in page 9.
Point 5: In the results section, acronyms for the countries and sectors (see figures) should be established. Maybe in an appendix. Does the literature countersing the results?
Response 5: Thank you very much for your careful reading of our manuscript. Thank you very much for your careful reading of our manuscript.
（1）Due to the length of the manuscript, no detailed information on country and sectoral classifications is provided in the manuscript. We supplement in the appendix, the specific classification is as follows Table 1, Table 2. And state the location in the results section.
Table A1. List and classification of economies
|
Acronym |
Economy |
|
AUS |
Australia |
|
BRA |
Brazil |
|
CAN |
Canada |
|
CHE |
Switzerland |
|
CHN |
China |
|
IDN |
Indonesia |
|
IND |
India |
|
JPN |
Japan |
|
KOR |
South Korea |
|
MEX |
Mexico |
|
NOR |
Norway |
|
RUS |
Russia |
|
TUR |
Turkey |
|
USA |
America |
|
EU-28 |
Austria, Belgium, Britain, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden (As of 2014) |
Table A2. Classification of sectors
|
Code |
Integrated sector |
Sector in WIOD |
|
S1 |
Agriculture |
Crop and animal production, hunting and related service activities |
|
Forestry and logging |
||
|
Fishing and aquaculture |
||
|
S2 |
Mining |
Mining and quarrying |
|
S3 |
Manufacturing |
Manufacture of food products, beverages and tobacco products |
|
Manufacture of textiles, wearing apparel and leather products |
||
|
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials |
||
|
Manufacture of paper and paper products |
||
|
Printing and reproduction of recorded media |
||
|
Manufacture of coke and refined petroleum products |
||
|
Manufacture of chemicals and chemical products |
||
|
Manufacture of basic pharmaceutical products and pharmaceutical preparations |
||
|
Manufacture of rubber and plastic products |
||
|
Manufacture of other non-metallic mineral products |
||
|
Manufacture of basic metals |
||
|
Manufacture of fabricated metal products, except machinery and equipment |
||
|
Manufacture of computer, electronic and optical products |
||
|
Manufacture of electrical equipment |
||
|
Manufacture of machinery and equipment n.e.c. |
||
|
Manufacture of motor vehicles, trailers and semi-trailers |
||
|
Manufacture of other transport equipment |
||
|
Manufacture of furniture; other manufacturing |
||
|
Repair and installation of machinery and equipment |
||
|
Publishing activities |
||
|
S4 |
Electricity, Gas and Water Supply |
Electricity, gas, steam and air conditioning supply |
|
Water collection, treatment and supply |
||
|
S5 |
Construction |
Construction |
|
S6 |
Transport |
Land transport and transport via pipelines |
|
Water transport |
||
|
Air transport |
||
|
Warehousing and support activities for transportation |
||
|
S7 |
Commercial and public services |
Sewerage; waste collection, treatment and disposal activities; materials recovery; remediation activities and other waste management services |
|
Wholesale and retail trade and repair of motor vehicles and motorcycles |
||
|
Wholesale trade, except of motor vehicles and motorcycles |
||
|
Retail trade, except of motor vehicles and motorcycles |
||
|
Postal and courier activities |
||
|
Accommodation and food service activities |
||
|
Motion picture, video and television program production, sound recording and music publishing activities; programming and broadcasting activities |
||
|
Telecommunications |
||
|
Computer programming, consultancy and related activities; information service activities |
||
|
Financial service activities, except insurance and pension funding |
||
|
Insurance, reinsurance and pension funding, except compulsory social security |
||
|
Activities auxiliary to financial services and insurance activities |
||
|
Real estate activities |
||
|
Legal and accounting activities; activities of head offices; management consultancy activities |
||
|
Architectural and engineering activities; technical testing and analysis |
||
|
Scientific research and development |
||
|
Advertising and market research |
||
|
Other professional, scientific and technical activities; veterinary activities |
||
|
Administrative and support service activities |
||
|
Public administration and defense; compulsory social security |
||
|
Education |
||
|
Human health and social work activities |
||
|
Other service activities |
||
|
Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use |
||
|
Activities of extraterritorial organizations and bodies |
(2) Existing studies supports the results of the study
This study is the first to construct an accounting framework for investment-related CO2 emissions in 43 major countries based on the MRIO model, and investment-related CO2 emissions in 43 major countries are determined in both free trade and restricted trade scenarios. Then, based on the comparison of the two scenarios, the effect of global trade protection on investment-related CO2 emissions is revealed from the three levels of country, section and trade links.
It is found that global trade protection would lead to an increase of up to 546.17 million tons in investment-related CO2 emissions under current trade structures. Transnational investment in the trade of end-stage intermediary goods contributed 81.6% of the total effect. In terms of countries, trade protection is quite disadvantageous to CO2 emissions reduction in China and India, and their CO2 emissions will respectively increase by 105 million tons and 141.5 million tons compared to normal trade. The electricity, gas, and water supply sectors and the manufacturing sector are the main sectors to investment-related CO2 emissions.
The main conclusion of the study is that compared with normal trade, trade protection increases global CO2 emissions, and trade openness is more conducive to the reduction of investment-related CO2 emissions. At present, more studies focus on the effect of investment on CO2 emissions under normal trade. Wang and Wang (2021) study the effect of trade openness on CO2 emissions, choose FDI as an intermediary variable, and explore the threshold effect of FDI on trade openness affecting CO2 emissions. The research results show that with the increase of FDI, trade openness is obviously beneficial to the reduction of carbon intensity. Du et al. (2020) find that the trade conflict between China and the United States cannot make the two economies and the environment win-win, so trade restrictions are not the best way to govern the environment. Khan et al. (2022) find that trade openness and FDI are negatively correlated with CO2 emissions, namely, trade openness and FDI increase in direct investment will reduce CO2 emissions. Zhang and Zhou (2016) use the STIRPAT model to study that FDI is beneficial to the reduction of investment-related CO2 emissions in China. Existing studies have shown that trade frictions are not conducive to the governance of the global environment, and trade openness and FDI have a negative effect on CO2 emissions. This paper even combines trade openness and transnational investment to conclude that trade openness is more conducive to the reduction of investment-related CO2 emissions.
Manuscript changes please see appendix.
Reference
Ackerman, F., Ishikawa, M., & Suga, M. (2007). The carbon content of Japan–US trade. Energy Policy, 35(9), 4455-4462. doi:https://doi.org/10.1016/j.enpol.2007.03.010
Du, M., Chen, L., Lin, J., Liu, Y., Feng, K., Liu, Q., . . . Adeniran, J. A. (2020). Winners and losers of the Sino–US trade war from economic and environmental perspectives. Environmental Research Letters, 15(9), 094032. doi:10.1088/1748-9326/aba3d5
Khan, H., Weili, L., & Khan, I. (2022). Environmental innovation, trade openness and quality institutions: an integrated investigation about environmental sustainability. Environment, Development and Sustainability, 24(3), 3832-3862. doi:10.1007/s10668-021-01590-y
Shahbaz, M., Nasir, M. A., & Roubaud, D. (2018). Environmental degradation in France: The effects of FDI, financial development, and energy innovations. Energy Economics, 74, 843-857. doi:https://doi.org/10.1016/j.eneco.2018.07.020
Wang, Q., Jiang, F., Li, R., & Wang, X. (2022). Does protectionism improve environment of developing countries? A perspective of environmental efficiency assessment. Sustainable Production and Consumption, 30, 851-869. doi:https://doi.org/10.1016/j.spc.2022.01.011
Wang, Q., & Wang, L. (2021). How does trade openness impact carbon intensity? Journal of Cleaner Production, 295, 126370. doi:https://doi.org/10.1016/j.jclepro.2021.126370
Wang, Q., Wang, L., & Li, R. (2023). Trade protectionism jeopardizes carbon neutrality – Decoupling and breakpoints roles of trade openness. Sustainable Production and Consumption, 35, 201-215. doi:https://doi.org/10.1016/j.spc.2022.08.034
Wang, Q., & Wang, S. (2020). Preventing carbon emission retaliatory rebound post-COVID-19 requires expanding free trade and improving energy efficiency. Science of The Total Environment, 746, 141158. doi:https://doi.org/10.1016/j.scitotenv.2020.141158
Wang, Q., & Zhang, F. (2021). The effects of trade openness on decoupling carbon emissions from economic growth – Evidence from 182 countries. Journal of Cleaner Production, 279, 123838. doi:https://doi.org/10.1016/j.jclepro.2020.123838
Zhang, C., & Zhou, X. (2016). Does foreign direct investment lead to lower CO2 emissions? Evidence from a regional analysis in China. Renewable and Sustainable Energy Reviews, 58, 943-951. doi:https://doi.org/10.1016/j.rser.2015.12.226
Zhang, Z., Zhu, K., & Hewings, G. J. D. (2017). A multi-regional input–output analysis of the pollution haven hypothesis from the perspective of global production fragmentation. Energy Economics, 64, 13-23. doi:https://doi.org/10.1016/j.eneco.2017.03.007
Round 2
Reviewer 2 Report
Thank you for making many significant amendments and changes.
Please continue to make additions as noted below.
Overall remarks.
1. Please indicate clearly which sentences from the abstract reference the elements mentioned in the review (Objective. Research Design & Methods. Hypothesis, research questions. Findings. Implications & Recommendations. Contribution & Value Added).
2. The data used in the paper was partially extended to 2016. Are later data available? If not, the descriptions in the paper can only apply to that period.
Detailed remarks (line and content as in Report 1).
31. Current studies should be cited. Their reliability (whether CO2 emissions cause climate change) and conclusions (what level of CO2 emissions is acceptable) should be discussed at length. Reference to the papers from 2011 [2] and 1990 [3] is insufficient. Item [4] is not relevant to this topic.
The remark was only partially taken into account by the authors. Please state how much CO2 is currently (please indicate the year for which the latest data is available) in circulation in the environment. Please say how much CO2 is introduced into the environment due to human activities. Please state how much CO2 is absorbed by the environment. This should lead to the determination of the CO2 balance. Please then say how much will be released into the environment in two situations: (1) international cooperation, without the use of protectionist mechanisms; (2) a situation in which protectionist mechanisms are used. In the case of (2), please state which protectionist mechanisms have been used, by which countries, in which years, and how, according to the authors, this affects the CO2 balance in precisely those years.
36. Item [5] is outdated and cannot form the basis of the thesis in the paper. Current research should be pointed out and reliably discussed.
The new reference to the literature refers to data from 2000-2016. The authors' hypothesis on the impact of protectionist mechanisms also applies to the later period. Also, the COVID-19 pandemic occurred later. How did CO2 emissions change between 2017 and 2022? Were CO2 emissions correlated with changes in investment levels? How has investment in recent years been correlated with trade protectionism?
41. The use of the phrase "trade war" is not professional in an academic paper. Instead, the mechanisms used by countries in international trade should be discussed. Relevant studies should be cited and quantitatively described. You should embed considerations for successive years of the assumed period of analysis.
The remark was not taken into account by the authors. Only changes in UK trade between 2012 and 2015 are given. If the authors only have such data, they should limit the scope of the paper and the conclusions drawn accordingly.
42. Identifying only three countries based on three causal papers is insufficient. Studies on all relevant countries should be cited. The conclusions of these studies should be discussed.
The remark was not taken into account by the authors. The paper was supplemented with the UK (as in the previous remark). The same literature item was referred to as before. Are the authors confident in the conclusions of the Tian et al. (2022) paper (barrier reduction increases emissions)? The conclusions of the paper by Du et al. (2020) are a tautology.
43. The changes that occurred as a result of the COVID-19 pandemic (quantitative and qualitative) should be discussed.
The remark was only partially taken into account by the authors. What effects has the COVID-19 pandemic had on CO2 emissions?
54. Nothing comes out of quantifying relationships. Indicate what this information can be used for and how.
Thank you for your explanation. However, the question arises: is it the aim of the authors to guide several countries as to what investment policy they should pursue in the context of their impact on CO2 emissions?
57. There should be a precise definition of what normal trade and no trade mean.
Thank you for the clarification. These concepts are extreme (binary) in nature. It is not the case in practice, and the variation of technological assumptions is another level of analysis. How do the authors analyze intermediate (partial protection) cases? By analyzing the worst case (no trade), the results obtained are only an estimation of the real situation.
70. This is a strong hypothesis that needs to be proven.
Thank you for your clarification. What does the phrase "We based on your opinion on the hypothesis..." mean.
Once the above questions have been clarified, it will be possible to respond to the conclusions.
The paper contains some linguistic faults.
Author Response
Thank you for carefully reading our revisions and for your thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. Our response (red font) to your comment (black font) is below. Line and page numbers indicated in the response correspond to the highlighted version of the revised manuscript (changes marked).
Point 1: Please indicate clearly which sentences from the abstract reference the elements mentioned in the review (Objective. Research Design & Methods. Hypothesis, research questions. Findings. Implications & Recommendations. Contribution & Value Added).
Response 1：Thank you for your reply. We indicate the mentioned elements in the abstract. The objective is "This study aims to explore the effect of global trade protection on investment-related CO2 emissions". The manuscript please see line 12-13 on page 1.
The research design and methods are "We construct an accounting framework for investment-related CO2 emissions under trade freedom and trade restriction based on the MRIO model for the first time, and investment-related CO2 emissions in 16 economies are determined in both trade freedom and trade restriction scenarios. Then, based on the comparison of the two scenarios, the effect of global trade protection on investment-related CO2 emissions is revealed from the three levels of country, section and trade links". The manuscript please see line 13-21 in page 1.
The hypothesis is "The study uses normal trade and no trade scenarios instead of free trade and restricted trade scenarios". The manuscript please see line 18-19 in page 1.
We consider the research question to be the object of exploration in the purpose of the research, that is, "quantify the effect of global trade protection on investment-related CO2 emissions". The manuscript please see line 18-19 in page 1.
Findings are "It is found that global trade protection would lead to an increase of up to 546.17 million tons in investment-related CO2 emissions under current trade structures. Transnational investment in the trade of end-stage intermediary goods contributed 81.6% of the total effect. In terms of countries, trade protection is quite disadvantageous to CO2 emissions reduction in China and India, and their CO2 emissions would respectively increase by 105 million tons and 141.5 million tons compared to normal trade. The electricity, gas, and water supply sectors and the manufacturing sector are the main sectors to investment-related CO2 emissions". The manuscript please see line 21-28 in page 1.
The implications and recommendations are "According to the research results, we should promote free trade to alleviate the pressure of investment-related CO2 emissions". The manuscript please see line 31-32 in page 1.
Contribution and added value are "This study reveals the effect of trade freedom and trade protection on the environment of various countries from the viewpoint of investment-related CO2 emissions, which has important reference value for global CO2 emissions reduction in the context of the evolving trade situation.” The manuscript please see line 28-31 in page 1.
Point 2: The data used in the paper was partially extended to 2016. Are later data available? If not, the descriptions in the paper can only apply to that period.
Response 2: The first point is that the data covered by the newly added references in this article is from 2000 to 2016. This study is to illustrate the main investment target of China as a developed country, and the impact of investment intensity on China's CO2 emissions. The newly added research uses an extended logarithmic mean Divisia index (LMDI), focusing on the investigation of the impact of R&D (research and development) efficiency, R&D intensity, investment intensity, labor productivity, employment structure, urban employment rate, and population urbanization level on China's CO2 emissions the role of the role. The results show that during the period 2000-2016, the decline in R&D efficiency and energy intensity are the most important factors for emission reduction, and the increase in investment intensity has a positive impact on the growth of CO2 emissions. The authors study the total amount of CO2 emissions, not the CO2 emissions caused by cross-regions and does not need an input-output table. As an illustration, the time frame covered by this study has no reference value for our research, but only shows that there is a positive relationship between investment intensity and China's CO2 emissions.
The second point is for the input-output table in WIOD we use. Because the real-time update of the database consumes a lot of time, manpower, and material resources, WIOD currently only updates the data from 2000 to 2014. Although the input-output database also includes EORA and GATP, which cover longer periods of time, EORA has only 26 departments. The WIOD provides a more detailed description of sectoral transfers between countries. The eleventh edition of the GTAP database (the latest edition) provides only five reference years (2004, 2007, 2011, 2014 and 2017). The GTAP database does not have a complete time series, which is very unfavorable for studying the trade rules of continuous years.
The period 2000-2014 covered by WIOD contains large-scale events in global trade, and the year 2000 was chosen as the starting point for the study. This is because the structure of global trade has undergone profound changes since the early 2000s, especially since China's accession to the World Trade Organization in 2001, as emerging developing economies have continued to participate in international trade. Trade has led to changes in the source structure of goods, which in turn has an effect on the economy, resources and environment of various countries. The World Trade Organization (WTO), the European Free Trade Association (EFTA) and China's "One Belt, One Road" strategy have all promoted the liberalization and facilitation of trade between regions or countries to varying degrees. With a large number of third world countries participating in global trade, the world trade center began to shift to large emerging developing economies, and the proportion of developed countries in international trade declined sharply. This has also led to developing economies such as China and India becoming the "world's factory". The hidden pollutants in the export trade have greatly increased their environmental pressure. However, the financial crisis in 2008 swept the world, and the global free trade system was greatly affected, which exacerbated the uncertainty of the global economic recovery. At the same time, global trade has been severely affected, and trade protectionism continues to heat up. In 2013, the United States and the European Union officially launched negotiations on the Transatlantic Trade and Investment Partnership. Global bilateral and regional trade rules are gradually emerging as tariff levels continue to increase. The effect of trade on the global environment has also created additional uncertainty.
Based on the input-output data in WIOD from 2000 to 2014, we conclude that trade freedom is more conducive to the reduction of investment-related CO2 emissions, which can be used as a reference for the impact of trade protection on investment-related CO2 emissions in recent years. When the database is further updated, new data can be used for verification.
Manuscript changes please see line 39-45 in page 1.
Point 3: The remark was only partially taken into account by the authors. Please state how much CO2 is currently (please indicate the year for which the latest data is available) in circulation in the environment. Please say how much CO2 is introduced into the environment due to human activities. Please state how much CO2 is absorbed by the environment. This should lead to the determination of the CO2 balance. Please then say how much will be released into the environment in two situations: (1) international cooperation, without the use of protectionist mechanisms; (2) a situation in which protectionist mechanisms are used. In the case of (2), please state which protectionist mechanisms have been used, by which countries, in which years, and how, according to the authors, this affects the CO2 balance in precisely those years.
Response 3: Thanks a lot for your suggestion. We split these questions into two parts to answer. (1) For the latest carbon emission situation, we collected relevant data and made changes in the manuscript. Near real-time data show that in 2022, global energy-related CO2 emissions will hit a new high, reaching more than 36.8 billion tons, an increase of 321 million tons over the previous year (IEA2022). The 2022 carbon budget report shows that in 2022, global human activities are expected to emit 40.6 billion tons of carbon dioxide. The impact of climate change has reduced the carbon dioxide absorption of ocean carbon sinks by about 4%, and land absorption by about 17%. Ocean carbon sinks absorb about 26% of global emissions in 2022. Land carbon sinks are also continuing to grow and are expected to absorb around 31% of global emissions by 2022. The remaining carbon budget is about 380 billion tons. This means that there is a 50% chance that the global average temperature will increase by 1.5°C in the next 9 years.
(2) Regarding the impact of the two scenarios on CO2 emissions, we found some literature to explain. The first is the impact of trade openness on CO2 emissions. Shahzad et al.（2017） empirically test the co-integration relationship between CO2 emissions, energy consumption, trade openness, and financial development in Pakistan. The Granger causality results show that there is a one-way causal relationship between energy consumption, trade openness, and financial development and CO2 emissions. Long-term results show that for every 1% increase in trade openness and financial development, CO2 emissions will increase by 0.247% and 0.165%, respectively. Wang et al.（2023）investigate the decoupling impact of trade on CO2 emissions and the circumstances under which trade contributes to the decoupling of CO2 emissions. A combination of the Tapio decoupling model and the structural threshold model was developed to study and quantify the impact. The results show that the dominant state of the relationship between trade openness, economic growth, and CO2 emissions is weak decoupling. In addition, there are two breakpoints in the impact of trade openness on CO2 emissions. Once the structural breakpoint is broken, trade openness will curb CO2 emissions and help achieve global carbon neutrality, which runs counter to the claims of trade protectionists. At the subregional level, trade openness helps rich countries achieve carbon neutrality, but not poor countries. Therefore, achieving carbon neutrality requires free trade, and fairer free trade needs to benefit countries of different income groups.
The second is the impact of trade protection or trade restrictions on CO2 emissions. Tian et al. (2022) study the impact of reducing regional tariffs among RCEP member countries on CO2 emissions, and find that completely canceling tariffs among RCEP member countries will make the global CO2 emissions from fuel combustion increase by about 3.1% per year. Using the 2000-2014 input-output table in WIOD, Wang and Han（2021）find that the trade restrictive measures adopted between China and the United States have different impacts on CO2 emissions in China and the United States. US-China trade conflict will reduce US CO2 emissions but increase China's CO2 emissions. Lu et al.（2020）establish a multi-regional computable general equilibrium model to simulate the environmental impact of the US-China trade conflict under different scenarios of tariff and non-tariff barriers. The study finds that the US-China trade conflict leads to land-use changes and increases emissions in some developing countries. In Brazil and Argentina in particular, increases in CO2 emissions from land-use change would far outweigh reductions in emissions from reduced global production.
In the literature review section, we cite relevant literature to illustrate the impact of different scenarios of trade on CO2 emissions. Existing studies are more based on the assumptions of international cooperation and protectionism, studying the impact of different scenarios of trade in representative economies on CO2 emissions. These are measurements and no conclusions can be drawn about absolute quantities on a global scale. If we want to get global conclusions, we have to use the IO table. This paper establishes the scenarios of no trade and normal trade, and obtains the CO2 emissions related to investment in the two scenarios. Global investment-related CO2 emissions between 2000 and 2014 are higher under the scenario of no trade than those under the scenario of normal trade, with a maximum difference of 546.17 million tons. Normal trade is more conductive to reducing global investment-related CO2 emissions. From the viewpoint of countries, trade protection is quite disadvantageous to CO2 emissions reduction in China and India, and their CO2 emissions will respectively increase by 105 million tons and 141.5 million tons compared to normal trade. While trade protection can decrease the investment-related CO2 emissions of Russia and Japan. Trade scenarios affect different countries differently.
Point 4: The new reference to the literature refers to data from 2000-2016. The authors' hypothesis on the impact of protectionist mechanisms also applies to the later period.
Response 4: Thanks for your suggestion. The data covered by the newly added study in this article is from 2000 to 2016. This study is to illustrate the main investment target of China as a developed country, and the impact of investment intensity on China's CO2 emissions. This study takes China as the research object, and the research is on the total CO2 emissions, not the CO2 emissions caused by cross-regions and does not require an input-output table. As an illustration, the time frame covered by this study has no reference value for our research, but only shows that there is a positive relationship between investment intensity and China's CO2 emissions. The latest existing literature is all about measurement, and it is impossible to draw conclusions about the absolute amount of CO2 emissions related to investment on a global scale. If we want to get a global conclusion, we have to use the IO table, and we can only reach 2014. The most recent data used in some of the latest articles published in the Nature sub-journals is also up to 2014. For example, Klimek et al. (2019) quantified the economic resilience of countries and sectors based on 2000-2014 input-output tables to determine the impact of economic shocks on them. Xu et al. (2020) examine the impact of trade on global sustainability indicators. The dataset used is the input-output table from 1995-2009 provided by WIOD. Zhang et al. (2021) used the global nitrogen budget from 1961 to 2015, and Yang et al. (2020) calculated the implicit socioeconomic footprint of trade in the Asia-Pacific region. They used the 1995-2015 input-output table provided by Exiobase 3.6, but their 2015 input-output table was estimated based on the latest data from 2014. In summary, the WIOD used in this study can only use the period 2000-2014, when the data is updated, the results can be further verified.
Point 5: the COVID-19 pandemic occurred later. How did CO2 emissions change between 2017 and 2022? Were CO2 emissions correlated with changes in investment levels? How has investment in recent years been correlated with trade protectionism?
Response 5: Thank you for your careful reading, and we will answer your questions one by one below.
(1) Real-time data on global CO2 emissions shows that global CO2 emissions have increased from 34.69Gt in 2017 to 35.34Gt in 2019 for two consecutive years. In 2020, the COVID-19 pandemic has hit demand for oil and coal more than other energy sources, causing global CO2 emissions to fall by 5.8%, or nearly 2 Gt CO2. In 2021, the economy will slowly recover. In order to restore the economy as soon as possible, the CO2 emissions of various countries have shown explosive growth, reaching 35.51Gt, a year-on-year increase of 6%, exceeding the level before the outbreak of the COVID-19 pandemic, and setting a record high. CO2 emissions are still rising in 2022, reaching 36.12Gt. The outbreak of COVID-19 has caused various countries to introduce various control measures against the epidemic, which has significantly inhibited transnational investment and greatly reduced investment efficiency. In March 2020, the latest global FDI trend monitoring report released by the United Nations Conference on Trade and Development showed that the outbreak and spread of COVID-19 had a negative impact on global foreign direct mobility. Corinne and others pointed out that the policies implemented by governments during the virus outbreak have greatly changed the energy demand pattern. Many international borders have been closed, investment between countries has decreased, people are restricted at home, and consumption patterns have changed. These series of changes significantly reduce CO2 emissions.
(2) From reading recent research, we provide support for the existence of a relationship between investment and CO2 emissions. Ahmed et al.（2021）examine the symmetric and asymmetric effects of public R&D investment on nuclear and renewable energy development and economic growth in Japan on CO2 emissions between 1974 and 2017 and find that higher public investment in clean energy research and development projects helps curb CO2 emissions in Japan. Zhang et al.（2021）analyze the combined impact of renewable energy investment on CO2 emissions in China. Results from the linear part of the model show that investments in renewable energy can slightly reduce CO2 emissions. Zhang et al.（2020）use the panel data of 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Macao and Taiwan) from 2008 to 2017, and used a threshold regression model to empirically analyze the impact of environmental regulation and foreign investment behavior on the quantity and intensity of investment. It is found that investment has regional heterogeneity. Foreign investment behavior in the eastern and central regions can inhibit CO2 emissions, while the opposite is true in the western region. FDI in low-emission intensity regions can significantly reduce CO2 emissions.
(3) Since 2018, with the help of Sino-US trade frictions, the new crown epidemic, the conflict between Russia and Ukraine, and other factors, the new global geopolitical and economic patterns are rapidly evolving. Geopolitical fragmentation will promote changes in the geoeconomic structure and increase conflicts in multiple fields. Individual countries have adopted trade protection measures to restrain exports from other countries, bringing more complex potential risks to Chinese companies' overseas investment. This is mainly reflected in four aspects. First, regional organization divisions and conflicts have increased, reducing investment space and affecting investment decisions. The second is the intensification of international trade protectionism, which makes the relationship between countries more tense and affects investment opportunities and confidence. The third is the rise of regionalism. This trend leads to the decentralization of geopolitics and the rise of nationalism in some countries, which affects the inflow of foreign capital. Fourth, the multi-polarization trend of the international order and governance is obvious, and the failure of global governance affects the stability and sustainability of transnational investment.
In summary, global CO2 emissions continued to increase from 2017 to 2019. With the outbreak of COVID-19 in 2020, the country has adopted containment measures, production activities have been reduced, and global CO2 emissions have been reduced. CO2 emissions will show explosive growth in 2021 and still rise in 2022. In 2020, the regulatory measures of various countries have suppressed transnational investment, which has a negative impact on global foreign direct mobility. Many countries have changed their energy demand patterns to reduce CO2 emissions. This also reflects that when a country adopts trade protection measures, it will inhibit other countries' exports and reduce transnational investment.
Point 6: The remark was not taken into account by the authors. Only changes in UK trade between 2012 and 2015 are given. If the authors only have such data, they should limit the scope of the paper and the conclusions drawn accordingly.
Response 6: We are very sorry that due to our negligence, we did not provide sufficient research evidence to support the feasibility of our research scope. We examine the trade protection measures adopted by individual countries in recent years. When a trade conflict occurs, some countries restrict trade between the two countries through tariff or non-tariff barriers. This paper complements some studies quantifying the impact of trade protection on CO2 emissions. For example, Tian et al. (2022) studied the impact of reducing regional tariffs among RCEP member countries on CO2 emissions, which was evaluated by changing the tariff structure among RCEP member countries and keeping the tariff structure of countries outside the agreement unchanged. It was found that the complete removal of tariffs between RCEP member countries would increase global annual CO2 emissions from fuel combustion by about 3.1%. In a globalized economy, the production of goods can be disrupted by trade disputes. Lin et al. (2019) studied the impact of trade disputes on CO2 emissions and found that higher tariffs are beneficial to reduce CO2 emissions by 6.3%. The free trade scenario would increase global CO2 emissions and air pollution because of higher levels of production, especially in developing regions where emissions intensity is relatively high.
We also add trade measures for individual countries during the analysis period, such as the UK's reduced engagement with EU trading partners starting in 2013. Fezzigna et al. (2019) studied the EU's foreign trade with the rest of the world over the period 2012-2015 and found that diverting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would Its emissions liability increased by 5%. A similar outcome would occur if the UK replaced its current EU partners with key Commonwealth trading partners. In addition to trade changes in the UK, we also introduce other studies to illustrate the feasibility of this research scope. Ertugrul et al. (2016) investigated the relationship between real income, real income squared, energy consumption, trade openness, and CO2 emissions in an EKC framework for the top 10 CO2 emitters in emerging countries between 1971 and 2011. In most of the countries analyzed, energy consumption stimulates environmental pollution, and trade openness increases CO2 emissions in Turkey, India, China, and Indonesia, while having no impact on the environment in Thailand, Brazil, and South Korea. Andersson (2018) studied the impact of China's institutional reforms on CO2 emissions from 1995 to 2008. China joined the World Trade Organization in 2001, and trade liberalization led to a rapid increase in China's CO2 emissions. The research results show that once the initial impact of trade liberalization The growth rate of embodied emissions in trade between China and developed countries will slow down.
In summary, we consider trade protection measures in recent years and supplement trade behavior during the analysis period to support the feasibility of the study scope.
Point 7: The remark was not taken into account by the authors. The paper was supplemented with the UK (as in the previous remark). The same literature item was referred to as before. Are the authors confident in the conclusions of the Tian et al. (2022) paper (barrier reduction increases emissions)? The conclusions of the paper by Du et al. (2020) are a tautology.
Response 7: Thank you for your careful reading, and we will answer these questions one by one.
(1) We are sorry that our explanation was not clear enough and you misunderstood that we did not consider this issue. We further illustrate a modification of this question. The trade conflicts between China and the United States, the United States and Japan, and the United States and Russia introduced in the manuscript are to illustrate that some countries such as the United States set up trade barriers to reduce trade exchanges in order to inhibit the economic development of other countries. According to your last suggestion, we should discuss the mechanism of international trade, we think it is one-sided for us to only describe the trade conflicts between countries, and we should discuss what measures countries have taken to set up trade barriers and the impact of these measures on CO2 emissions. Therefore, we change this part to the impact of trade restriction mechanisms adopted by some countries on CO2 emissions. For example, some countries raise tariffs to reduce trade deals. Tian et al. (2022) studied the impact of regional tariff reductions among RCEP members on CO2 emissions, and found that the complete cancellation of tariffs among RCEP members would increase global annual CO2 emissions from fuel combustion by about 3.1%. Du et al. (2020) based on the impact of Sino-US trade conflicts on CO2 emissions, found that Sino-US trade conflicts cannot bring win-win results for the economy and the environment, so trade restrictions are not the best way to manage the environment. We also add factors that should be considered during the analysis, such as the UK's reduction of engagement with EU trading partners since 2013. Fezzigna et al. (2019) studied the EU's foreign trade with the rest of the world over the period 2012-2015 and found that diverting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would Its emissions liability increased by 5%. A similar outcome would occur if the UK replaced its current EU partners with key Commonwealth trading partners. In addition to trade changes in the UK, we also introduce other studies to illustrate the feasibility of this research scope. Ertugrul et al. (2016) investigated the relationship between real income, real income squared, energy consumption, trade openness, and CO2 emissions in an EKC framework for the top 10 CO2 emitters in emerging countries between 1971 and 2011. In most of the countries analyzed, energy consumption stimulates environmental pollution, and trade openness increases CO2 emissions in Turkey, India, China, and Indonesia, while having no impact on the environment in Thailand, Brazil, and South Korea. Andersson (2018) studied the impact of China's institutional reforms on CO2 emissions from 1995 to 2008. China joined the World Trade Organization in 2001, and trade liberalization led to a rapid increase in China's CO2 emissions. The research results show that once the initial impact of trade liberalization The growth rate of embodied emissions in trade between China and developed countries will slow down.
(2) Tian et al. (2022) studied the impact of regional tariff reduction among RCEP members on CO2 emissions. The study controlled variables by changing the tariff structure between RCEP member countries and keeping the tariff structure of countries outside the agreement unchanged. The research results only focus on the impact of tariff reduction among RCEP member countries on CO2 emissions. This study uses the input-output model, which is widely used in the study of trade between countries, and the model is quite mature. From the perspective of variable control and model selection, the conclusions of this study are trustworthy. After our analysis, the research conclusions of Tian and Du are different. It may be because our writing is not standardized and misunderstood you, making you think that Du's conclusion is "a tautology". The two studies draw conclusions for different research objects and different regions. The research of Tian et al. is based on the trade exchanges between RCEP member countries, and Du et al. is based on the trade conflict between China and the United States. The conclusions drawn in different regions may be different, which also reflects the necessity of our global research.
Point 8: The remark was only partially taken into account by the authors. What effects has the COVID-19 pandemic had on CO2 emissions?
Response 8: We are very sorry that we did not give this issue a comprehensive consideration. We pored over recent research discussing the impact of COVID-19 on CO2 emissions. Ray et al.（2022）investigate the impact of COVID-19 lockdown measures on global annual CO2 emissions, focusing on 47 countries and their 105 cities that were severely affected by December 2020. Overall, the total CO2 emissions of select 184 countries reduced by 438 Mt in 2020 than in 2019. Liu et al.（2020）provide daily estimates of country-level CO2 emissions in different sectors based on near real-time activity data. The key result is a sudden 8.8% reduction in global CO2 emissions in the first half of 2020 compared to the same period in 2019. IEA2021 shows that global CO2 emissions fell by 5.8% in 2020, or almost 2 Gt CO2, which is almost five times the drop in 2009 after the global financial crisis. These studies all show that COVID-19 has reduced global CO2 emissions.
Manuscript changes please see line 72-75 in page 2.
Point 9: However, the question arises: is it the aim of the authors to guide several countries as to what investment policy they should pursue in the context of their impact on CO2 emissions?
Response 9: Thank you for reading carefully. It is one of the practical purposes of this study to provide policy reference value for some countries.
As far as the purpose of the research is concerned, we would like to explain it in two points. On the one hand, the purpose of this study is to explore the impact of trade protection on investment-related CO2 emissions. It is concluded that trade liberalization is more conducive to the reduction of investment-related CO2 emissions, which provides a reference for the global reduction of trade barriers and promotion of trade opening.
On the other hand, it is to provide guidance for the country's investment policy. Trade refers to the flow of goods and services between countries and is an activity between countries. Trade protection is a measure taken by various countries to reduce trade exchanges. This paper also studies the relationship between trade protection and investment-related CO2 emissions from three perspectives: country, trade link, and sector. From the viewpoint of countries, trade protection is quite disadvantageous to CO2 emissions reduction in China and India, and their CO2 emissions will respectively increase by 105 million tons and 141.5 million tons compared to normal trade. While trade protection can decrease the investment-related CO2 emissions of Russia and Japan. So this study provides some suggestions for some countries that China and India can attract transnational investment to reduce investment-related CO2 emissions in both countries. China should focus on introducing clean technologies for transnational investment in manufacturing to reduce the sector's contribution to investment- related CO2 emissions. Strengthening China's barriers in trade of final goods or focusing on the energy efficiency of this trade link will have a favorable effect on reducing investment-related CO2 emissions in this trade link. For Russia and Japan, we should pay attention to the quality of investment and optimize the investment structure.
Point 10: These concepts are extreme (binary) in nature. It is not the case in practice, and the variation of technological assumptions is another level of analysis. How do the authors analyze intermediate (partial protection) cases? By analyzing the worst case (no trade), the results obtained are only an estimation of the real situation.
Response 10: Thank you very much for your advice. The purpose of using the undifferentiated technology hypothesis is to estimate the impact of a no trade scenario on investment-related CO2 emissions during 2000-2014. The results may be biased, but we believe that this method can provide a useful approximation. Under this assumption, a country's import needs are met through domestic technology production. This hypothesis was also used to describe the no-trade scenario in existing studies. Xu et al.（2020）studied the impact of international trade on global sustainable development. They used the hypothesis of a no trade scenario to estimate the impact of current international trade on the current world's achievement of the SDGS, but not to predict or describe a viable future. In this hypothetical scenario, they shift the trade balance (exports minus imports) back into resource supply. Thus, countries' SDG performance in a no-trade scenario is achieved by adding exporters (net exports) to the trade balance and then calculating SDG indicator scores. The final results showed that international trade improved the global SDG score compared to a no-trade scenario and had a positive impact on progress towards achieving all nine SDGS at the global level. Zhang et al.（2017）simulated a no trade scenario using a domestic technology hypothesis to study the pollution refuge hypothesis, showing that total international trade corresponds to a negative balance of avoided emissions. This means that international trade helps to reduce global emissions, for example, in the absence of international trade, global CO2 emissions would have increased by 8226.1 million tons in 2009. The study by Zhang et al. aims to conduct a comprehensive analysis of the pollution harbor hypothesis of CO2 emissions in three different trade patterns from global, bilateral, and national perspectives. They introduce a multiregional input-output analysis approach and discuss the contribution of production fragmentation to global emissions. Study finds fragmentation of international production saves global emissions. Trade in intermediate goods has a negative balance of avoiding emissions. Over the period 1995-2009, trade in final goods has become increasingly less environmentally efficient. Different trade patterns have significant differences in the environmental impacts of each country
Point 11: What does the phrase "We based on your opinion on the hypothesis..." mean.
Response 11: We express our sincere apologies for the misunderstanding caused by our clerical errors. Here we explain further. We based on your opinion on the hypothesis..." mean we accept your suggestion, and prove the hypothesis "Many developed countries transfer the environmental pollution generated by their own consumption demand to developing countries through international trade, transnational investment and technology transfer, which results in global environmental pollution".
Reference
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Author Response File: 
Author Response.docx
Round 3
Reviewer 2 Report
Thank you for making amendments. Please continue to make additions as noted below.
Detailed remarks (line and content as in Report 1).
31. Current studies should be cited. Their reliability (whether CO2 emissions cause climate change) and conclusions (what level of CO2 emissions is acceptable) should be discussed at length. Reference to the papers from 2011 [2] and 1990 [3] is insufficient. Item [4] is not relevant to this topic.
The remark was only partially taken into account by the authors. The authors indicated the CO2 balance for 2022 but did not state where the data came from. Nor did they conduct a detailed analysis of them. Please say how this balance will change in two situations: (1) international cooperation, without protectionist mechanisms; (2) a situation in which protectionist mechanisms are used. In the case of (2), please state which protectionist mechanisms have been used, by which countries, in which years, and how, according to the authors, this affects the CO2 balance in precisely those years. How is the CO2 balance counted in hundreds of billions of tons affected by changes, even in hundreds of millions of tons, as the thesis in the paper suggests (a difference of two-three orders of magnitude)?
36. Item [5] is outdated and cannot form the basis of the thesis in the paper. Current research should be pointed out and reliably discussed.
The remark was not taken into account by the authors. How did CO2 emissions change between (2014-2016) and (2017-2022)? It would be welcome to complete the figures. Were CO2 emissions correlated with changes in investment levels? How has investment in recent years been correlated with trade protectionism?
41. The use of the phrase "trade war" is not professional in an academic paper. Instead, the mechanisms used by countries in international trade should be discussed. Relevant studies should be cited and quantitatively described. You should embed considerations for successive years of the assumed period of analysis.
The remark was not taken into account by the authors. Only changes in UK trade between 2012 and 2015 are given. If the authors only have such data, they should limit the scope of the paper and the conclusions drawn accordingly.
42. Identifying only three countries based on three causal papers is insufficient. Studies on all relevant countries should be cited. The conclusions of these studies should be discussed.
The remark was not taken into account by the authors. The paper was supplemented with the UK (as in the previous remark). The same literature item was referred to as before. Are the authors confident in the conclusions of the Tian et al. (2022) paper (barrier reduction increases emissions)? The paper's conclusions by Du et al. (2020) are a tautology.
Minor linguistic faults remain.
Author Response
Point 1：Current studies should be cited. Their reliability (whether CO2 emissions cause climate change) and conclusions (what level of CO2 emissions is acceptable) should be discussed at length. Reference to the papers from 2011 [2] and 1990 [3] is insufficient. Item [4] is not relevant to this topic.
The remark was only partially taken into account by the authors. The authors indicated the CO2 balance for 2022 but did not state where the data came from. Nor did they conduct a detailed analysis of them. Please say how this balance will change in two situations: (1) international cooperation, without protectionist mechanisms; (2) a situation in which protectionist mechanisms are used. In the case of (2), please state which protectionist mechanisms have been used, by which countries, in which years, and how, according to the authors, this affects the CO2 balance in precisely those years. How is the CO2 balance counted in hundreds of billions of tons affected by changes, even in hundreds of millions of tons, as the thesis in the paper suggests (a difference of two-three orders of magnitude)?
Response 1：Thank you for your comment.
(1) Description of carbon dioxide data in 2022
The CO2 balance data for 2022 is derived from "World Energy Outlook 2022" report released by the International Energy Agency. It shows that global energy-related CO2 emissions hit a new high in 2022, reaching more than 36.8 billion tons. The terrestrial carbon sink absorbed around 31% of global CO2 emissions and ocean carbon sinks absorb about 26% of global CO2 emissions. The remaining carbon budget is about 380 billion tons, which means a 50% chance that the global average temperature would rise by 1.5°C over the next 9 years. According to a UNEP report, Global warming of 1.5°C will bring extreme weather, sea level rise and ecological damage.
(2) Description of CO2 emissions under two trade scenarios
Humans can only control CO2 emissions by changing development patterns, such as trade patterns, and it is difficult to affect the carbon absorption capacity of oceans and land, which is also beyond the scope of this study. So we collected the following literature to show how trade patterns affect CO2 emissions.
â… . The impact of trade freedom and trade protection on emissions / How do emissions change in the two situations
Cranachan (2017) studied the impact of the North American Free Trade Agreement on pollutant emissions, using U.S. corporate-level pollution emissions data. He found that the contribution of trade liberalization accounted for about two-thirds of the air pollution reduction in US manufacturing sector. The empirical analysis by Shapirp and Walker (2018) shows that there is a negative correlation between the productivity improvement caused by trade liberalization and the pollution emissions of enterprises. These studies reflect that free trade is beneficial to the reduction of CO2 emissions.
- Effects of using protectionist mechanisms on CO2 emissions
Some countries use trade restrictions to maintain markets for their products. Liu et al. (2014) focused on the products involved in the anti-dumping of ten countries against China, calculated the CO2 emissions of the eight manufacturing industries that were most subject to anti-dumping investigations from 1995 to 2011, and found that the number of dumping cases sued and the CO2 emissions of industries involved in anti-dumping cases show a consistent trend of change. Lu et al. (2020) explored the 2018 Sino-US trade conflict and found that the Sino-US trade conflict led to increased emissions in some developing countries. In Brazil and Argentina in particular, the increase in CO2 emissions from land-use change would far outweigh the reduction induced by reduced global production. Although this is the trade protection that occurred in 2018, it supports the conclusion of this study. Brexit is a protective measure for the UK to reduce trade with the EU and maintain its own economic development. Fezzigna et al. (2019) studied the EU's foreign trade with the rest of the world over the period 2012-2015 and found that diverting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would Its emissions liability increased by 5%. A similar outcome would occur if the UK replaced its current EU partners with key Commonwealth trading partners. These studies show the trade restrictions' impact on CO2 emissions.
(3) The calculation process of investment-related carbon dioxide emissions under the two trade scenarios in this study
This study aims to explore the impact of global trade protection on investment-related CO2 emissions. Based on the MRIO model, we constructed an accounting framework for investment-related CO2 emissions under two scenarios of free trade and trade restriction, and determined the investment-related CO2 emissions of 16 economies under two scenarios. Specifically, we build normal trade and no trade scenarios by changing the carbon intensity matrix in the MRIO model. Then, we reveal the impact of global trade protection on investment-related CO2 emissions from three levels: country, sector and trade link. We describe the detailed calculation steps in the Methodology section.
Reference [4] has been deleted in the first round of revisions.
Point 2: The remark was not taken into account by the authors. How did CO2 emissions change between (2014-2016) and (2017-2022)? It would be welcome to complete the figures. Were CO2 emissions correlated with changes in investment levels? How has investment in recent years been correlated with trade protectionism?
Response 2: Thank you for your comment.
(1) Discussion on CO2 emissions from 2014 to 2022
Real-time data on global CO2 emissions shows that global CO2 emissions in 2014 were 34.23Gt. By 2015, global production grew at a low speed, trade continued to be sluggish. CO2 emissions also were reduced to 34.08Gt. In 2016, CO2 emissions increased to 34.14Gt. Global CO2 emissions have increased from 34.69Gt in 2017 to 35.34Gt in 2019 for two consecutive years. In 2020, the COVID-19 pandemic has hit the oil and coal demand, causing global CO2 emissions to fall by 5.8%, or nearly 2 Gt CO2. In 2021, the economy slowly recovered. In order to restore the economy, the CO2 emissions of various countries have shown explosive growth, reaching 35.51Gt, a increase of 6%, exceeding the level before the outbreak of the COVID-19 pandemic, and setting a record high. CO2 emissions are still rising in 2022, reaching 36.12Gt. The outbreak of COVID-19 has caused various countries to control the epidemic, which has significantly inhibited transnational investment and greatly reduced investment efficiency. The latest global FDI trend monitoring report released by the United Nations Conference on Trade and Development showed that the spread of COVID-19 had a negative impact on global foreign direct mobility. The policies implemented by governments during the virus outbreak have greatly changed the energy demand pattern. Many international borders have been closed, investment between countries has decreased, and people’s consumption patterns have changed. These series of changes significantly reduce CO2 emissions. Overall, except for 2015 and 2020, CO2 emissions from 2014 to 2022 show an increasing trend.
(2) Relationship between carbon dioxide and investment level
We collected the recent research to illustrate the relationship between carbon dioxide and investment level. Ahmed et al. (2021) examined the symmetric and asymmetric effects of Japan's public R&D investment on CO2 emissions from 1974 to 2017, and found that higher public investment in clean energy R&D projects helps curb Japan's CO2 emissions. Zhang et al. (2021) analyze the combined impact of renewable energy investment on CO2 emissions in China, and results show that investments in renewable energy can slightly reduce CO2 emissions. Zhang et al. (2020) empirically analyzed the impact of foreign investment behavior on investment intensity in China’s 30 provinces based on a threshold regression model. It is found that investment has regional heterogeneity. Foreign investment behavior in the eastern and central regions can inhibit CO2 emissions, while the opposite is true in the western region.
(3) The relationship between investment and trade protection
We summarize it in four aspects. First, conflicts between regions have increased and investment space has shrunk, affecting investment decisions. Second, international trade protectionism is intensifying, which will affect investment opportunities and confidence. The third is the rise of regionalism. Geopolitical decentralization and rising nationalism in some countries have affected the inflow of foreign capital. Fourth, the multi-polarization of international order and governance affects the stability and sustainability of transnational investment.
Point 3: The remark was not taken into account by the authors. Only changes in UK trade between 2012 and 2015 are given. If the authors only have such data, they should limit the scope of the paper and the conclusions drawn accordingly.
Response 3:
Thank you for your comment. We supplemented the impact of trade measures adopted by some countries on CO2 emissions to support the feasibility of the study in this paper in terms of time and space.
Fezzigna et al. (2019) studied the EU's foreign trade with the rest of the world over the period 2012-2015 and found that diverting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would Its emissions liability increased by 5%. A similar outcome would occur if the UK replaced its current EU partners with key Commonwealth trading partners. This article chooses the changes in UK trade from 2012 to 2015 because the UK put forward the idea of reducing trade with the EU in 2013.
Andersson (2018) examined the impact of institutional reforms in China from 1995 to 2008 on CO2 emissions. China joined the World Trade Organization in 2001, and trade liberalization led to a rapid increase in China's CO2 emissions. The research results showed that in the long run, the promotion effect of trade liberalization on China's emissions embodied in the trade with developed countries would be weakened.
Long et al. (2021) studied the impact of the 2008 economic crisis and the 2011 Tohoku Earthquake on Japan's CO2 emissions, and found that the economic crisis and natural disasters shut down the Japanese economy and reduced trade with other countries. This has reduced Japan's CO2 emissions to a certain extent.
Point 4: The remark was not taken into account by the authors. The paper was supplemented with the UK (as in the previous remark). The same literature item was referred to as before. Are the authors confident in the conclusions of the Tian et al. (2022) paper (barrier reduction increases emissions)? The paper's conclusions by Du et al. (2020) are a tautology.
Response 4: Thank you for your comment. We are sorry that our explanation was not clear enough.
(1) The reason why we did not cite three studies that China-US, US-Japan and US-Korea trade conflicts
The trade conflicts between China and the US, the US and Japan, and the US and Russia introduced in the manuscript are to illustrate that some countries set up trade barriers to inhibit the economic growth of other countries. According to your suggestion, we change this part to discuss the impact of trade restriction mechanisms adopted by some countries on CO2 emissions.
For example, some countries raise tariffs to reduce trade deals. Tian et al. (2022) studied the impact of regional tariff reductions among RCEP members on CO2 emissions, and found that the complete cancellation of tariffs among RCEP members would increase global annual CO2 emissions by about 3.1%. Du et al. (2020) explored the impact of Sino-US trade conflicts on CO2 emissions, and found that Sino-US trade conflicts cannot bring win-win results for the economy and the environment, so trade restrictions are not the best way to manage the environment.
(2) The reason why the same literature item was referred to as before
We also add factors that should be considered during the analysis, such as the UK's reduction of engagement with EU trading partners since 2013. Fezzigna et al. (2019) studied the EU's foreign trade with the rest of the world over the period 2012-2015 and found that diverting 10% of the UK's imports from EU partners to its main non-EU trading partners (India, China and the US) would Its emissions liability increased by 5%. A similar outcome would occur if the UK replaced its current EU partners with key Commonwealth trading partners. The reason why we mention this paper by Fezzigna et al. here again is that we consider this suggestion in conjunction with the previous one, thus changing the structure of the article.
In addition to trade changes in the UK, we also introduce other studies to illustrate the feasibility of this research scope. Ertugrul et al. (2016) investigated the relationship between real income, real income squared, energy consumption, trade openness, and CO2 emissions in an EKC framework for the top 10 CO2 emitters in emerging countries between 1971 and 2011. The results show that trade openness increases CO2 emissions in Turkey, India, China, and Indonesia, while having no impact on the environment in Thailand, Brazil, and South Korea. Andersson (2018) studied the impact of China's institutional reforms on CO2 emissions from 1995 to 2008. China joined the World Trade Organization in 2001, and trade liberalization led to a rapid increase in China's CO2 emissions. The research results show that in the long run, trade liberalization will reduce the growth rate of China's embodied emissions from trade with developed countries.
(3) Interpretation of Tian et al.'s study and Du's study
Tian et al. (2022) study the impact of regional tariff reduction among RCEP members on CO2 emissions, which control variables by changing the tariff structure between RCEP member countries and keeping the tariff structure of countries outside the agreement unchanged. Its results only focus on the impact of tariff reduction among RCEP member countries on CO2 emissions. Tian et al. uses the input-output model, which is widely used in the study of trade between countries, and the model is quite mature. From the perspective of variable control and model selection, its conclusions are trustworthy. After our analysis, the research conclusions of Tian and Du are different. It may be because our writing is not standardized and misunderstood you, making you think that Du's conclusion is "a tautology". The two studies draw conclusions for different research objects and different regions. The research of Tian et al. is based on the trade exchanges between RCEP member countries, and Du et al. is based on the trade conflict between China and the United States. The conclusions drawn in different regions may be different, which also reflects the necessity of our global research.
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