The Causality between Participation in GVCs, Renewable Energy Consumption and CO2 Emissions

Using the panel vector autoregressive (PVAR) model accompanied by the system-generalized method of moment (System-GMM) approach, this paper investigates the dynamic causality between participation in global value chains (GVCs), renewable energy consumption and carbon dioxide (CO2) emissions throughout 1990–2015 for 172 countries. The results show that participation in GVCs negatively causes renewable energy consumption except for the Middle East and North America (MENA) and sub-Saharan Africa. Second, except for the Asia–Pacific region and globally, participation in GVCs has no causal impact on CO2 emissions, and participation in GVCs has a positive effect on CO2 emissions in the Asia–Pacific region and globally. Third, except for globally and sub-Saharan Africa, CO2 emissions have no causal impact on participation in GVCs; however, CO2 emissions hurt participation in GVCs globally and in the sub-Saharan African region. Forth, renewable energy consumption positively causes participation in GVCs in MENA, while renewable energy consumption does not cause participation in GVCs globally and in other regions. Fifth, there is no causality between CO2 emissions and renewable energy consumption both at the global and regional levels. Several policy implications are proposed and discussed for promoting participation in GVCs and improving the environment.


Introduction
Global climate warming and energy scarcity are consensually regarded as the most challenging and threatening global environmental issues, which will severely affect all aspects of human life and health [1][2][3][4]. To ensure the energy security and sustainable development of human society, the relevant international organizations, policymakers and researchers have highlighted the significance of governing global warming and reducing greenhouse gas (GHG) emissions. In particular, as production sharing becomes the significant characteristic of today's global economy [5], much debate about the environmental consequences of participation in global value chains (GVCs) has emerged [6]. According to the recent report of the United Nations' Sustainable Development Goals, "Global supply chains play a critical role in many of the most pressing environmental stresses and social struggles" [7], which clearly emphasizes the effect of GVCs on the environment.
As carbon dioxide (CO 2 ) emissions are the primary source of climate warming, mitigating CO 2 emissions is the key to solving the problem of global climate change [8][9][10][11]. There is strong agreement among researchers that renewable energy provides a promising solution to stimulate CO 2 emission reduction [12,13]. Widespread use of renewable energy and further technological advancement of renewable energy technologies are all conducive to decreasing CO 2 emissions [14,15]. At the same time, it is widely accepted that integration in GVCs plays a growing role in accessing knowledge and enhancing learning and innovation ability [16], which is vital to the development of eco-technology

Impacts of Participation in GVCs on Environment and Energy Consumption
Participation in GVCs has a variety of impacts on energy consumption and CO 2 emissions. Chiou et al. [59] concluded that working closely with supply chain partners promotes environmentally friendly product innovations, thereby creating advantages (e.g., better product quality) over rivals. Khattak et al. [19] considered that GVCs represent both the drivers of environmental upgrading and the means by which to obtain the knowledge needed to upgrade, particularly for firms in relational networks. Khattak and Stringer [31] examined the impact of GVCs on the environment and claimed that through regular interaction, knowledge is created and transferred across the GVCs, resulting in environmental upgrading. Pathikonda and Farole [60] suggested that GVCs have altered the nature of Sustainability 2020, 12,1237 4 of 26 global trade, and offer significant opportunities for developing countries to expand exports, access technology and raise productivity.
However, not all impacts of participation in GVCs are equally helpful for energy conservation and environmental protection. Davis and Caldeira [46] pointed out that consumption-based accounting of CO 2 emissions demonstrates the potential for international carbon leakage, and CO 2 emissions traded internationally primarily export from China and other emerging markets to consumers in developed countries. Besides, Spaiser et al. [44] and Meng et al. [61] all considered that most developing countries, such as China, join GVCs by exporting relatively large amounts of final products in their early stage of development, which produce a large amount of CO 2 emissions, which makes the poorer countries bear the natural depletion costs.

Relationship between CO 2 Emissions and Renewable Energy
A wealth of empirical studies has emerged examining the possible causality between CO 2 emissions and renewable energy, mainly divided into two categories, namely single country analysis and cross-country analysis. Findings of both categories have been mixed. More details about relevant studies are shown in Table 1. Since in this paper we examined the case of countries at global and regional levels, previous research with cross-country data is discussed in detail below. A majority of studies have found evidence for a bidirectional causal relationship between CO 2 emissions and renewable energy (see Salim and Rafiq [62] for six emerging countries, Liu et al. [63] for ASEAN-4 countries, Jebli et al. [64] for 25 OECD countries, Dogan and Seker [65] for 15 EU countries and Dong et al. [66,67] for BRICS countries and 14 Asia-Pacific countries). Some previous studies have shown evidence for a unidirectional causal relationship between CO 2 emissions and renewable energy, such as Al-mulali and Ozturk [68], who examined this for 27 advanced economies, and Balsalobre-Lorente et al. [69], who studied this for 5 EU countries. Furthermore, Bölük and Mert [70], Zoundi [71] and Bhattacharya et al. [72] demonstrates that renewable energy consumption has a significant negative effect on CO 2 emissions, and renewable energy consumption is an efficient tool for protecting the environment.

Methodology
In order to comprehensively analyze the endogenous dependent relationship between participation in GVCs, renewable energy consumption and CO 2 emissions, the PVAR model proposed by Love and Zicchino [79] was adopted in this paper. As a powerful analysis tool of macroeconomic dynamics, the PVAR model treats all the variables as endogenous and interdependent and allows for the existence of unobserved individual heterogeneity. The PVAR model is given as where Y i,t is the vector of endogenous variables, and µ i refers to the matrix of country-specific fixed effects; i = 1, 2, · · · N and t = 1, 2, · · · T represent the country and time, respectively. φ(I) is the lag operator of the matrix polynomial, α i is the individual specific effects, δ t is the time effects and ε i,t is the random error vector. Based on the selection criteria of AIC (Akaike information criterion), HQIC (Hannan-Quinn information criterion) and BIC (Bayesian information criterion), the optimal lag of this model was confirmed as the first-order PVAR model. Therefore, Equation (1) can also be rewritten as During the process of estimation of the PVAR model, to eliminate the individual specific effect and fixed time effect, the mean-difference method and forward mean-difference (known as "Helmert procedure") method were applied. Then, the lagged independent variables were used as the tool variables to estimate the parameters of the model using the system-generalized method of moment.

Data Selection and Description
Annual data over the period of 1990-2015 for a total of 172 countries (see Appendix A for the countries used in this study) comes from the World Bank Development Indicators databases (WDI) and Euro database [56,80]. Economic growth was proxied using per capita GDP in current US dollars. Renewable energy consumption was represented by the percentage of renewable energy consumption of the total final energy consumption. CO 2 emissions were measured by carbon dioxide emissions (kg) per PPP (purchasing-power-parity) US dollars as a percent of GDP. The percentage of total labor force participation on total population ages 15-64 was used as a proxy for labor force. There are no direct statistics data on the participation in GVCs for all of the countries; thus, the relevant data was obtained by the formula as follows: where FVA it is the foreign value added, and DVX it is the indirect domestic value added in country i at time t. FVA share identifies the share of a country's exports, which consists of inputs produced in other countries, and it captures the extent of GVC participation for downstream firms and industries. It is considered a measure of backward GVC participation. DVX share captures the contribution of the domestic sector of a country to the exports of other countries, thus indicating the extent of GVC participation for relatively upstream sectors. It is considered as a measure of forward GVC participation. The FVA and the DVX components of a single country/area gives us a comprehensive description of GVC participation [57,58,81]. Total exports is measured by the exports of goods and services (BOP) in current US dollars. The larger the ratio, the greater the intensity of involvement of a particular country in GVCs. All the variables in this paper were converted to natural logarithm to eliminate heteroscedasticity and increase the reliability and consistency of the results.

Empirical Results and Discussion
This section discusses the main results of the estimation of the system-generalized method of moment (System-GMM) PVAR model and presents the results of variance decomposition and impulse response function analysis.

System-GMM PVAR Causality Results
For the global level, the causal relationship between participation in GVCs, renewable energy consumption and CO 2 emissions is shown in Panel A of Table 2. The results show that the participation in GVCs negatively causes renewable energy consumption at the 1% level of significance, which indicates that renewable energy consumption decreases 0.0637% when participation in GVCs increases by 1%. Additionally, participation in GVCs positively causes CO 2 emissions, which implies that a 1% increase in participation in GVCs increases the CO 2 emissions by 0.0313%. This result supports the finding of De Vries and Ferrarini [82], who found that a substantial share of CO 2 emissions growth in emerging countries accounted for increasing participation in GVCs, and contradicts the findings of Sun et al. [83], who found that the promotion of participation in GVCs could reduce CO 2 emissions significantly in developing countries compared with those in developed countries. Panel A of Table 2 also shows that renewable energy consumption does not cause the participation in GVCs and the CO 2 emissions. CO 2 emissions cause the participation in GVCs and the relationship is negative at the 10% level of significance. This suggests that a 1% increase in CO 2 emissions will decrease the participation in GVCs by 0.0620%. Additionally, CO 2 emissions do not cause renewable energy consumption. This evidence is inconsistent with the finding of Bhattacharya et al. [72] who found that the growth of renewable energy consumption had a significant negative effect on CO 2 emissions in 85 developed and developing countries. Panel B of Table 2 shows the causal relationship between participation in GVCs, renewable energy consumption and CO 2 emissions for the Asia-Pacific region. First, the results show that the participation in GVCs negatively causes renewable energy consumption and the relationship is significant at the 1% level. This suggests that a 1% increase in participation in GVCs will decrease renewable energy consumption by 0.0507% in Asia-Pacific region. In addition, the results also show that participation in GVCs positively causes CO 2 emissions, and the relationship is significant at the 1% level. This indicates that 1% increase in participation in GVCs will increase CO 2 emissions by 0.0333% in the Asia-Pacific region. Besides, renewable energy consumption does not cause the participation in GVCs and CO 2 emissions. This implies that there are not causal effects of renewable energy consumption on participation in GVCs and CO 2 emissions. Furthermore, the results also show that CO 2 emissions do not cause the participation in GVCs. This suggests that an increase in CO 2 emissions does not influence the participation in GVCs of countries in the Asia-Pacific region. CO 2 emissions also do not cause renewable energy consumption. This empirical result contradicts the finding of Dong et al. [66] and Liu et al. [63] who proposed that renewable energy consumption has a negative impact on CO 2 emissions, and that there is a feedback causalities between CO 2 emissions and renewable energy consumption in four selected countries of the Association of Southeast Asian Nations.
Panel A of Table 3 presents the causality between participation in GVCs, renewable energy consumption and CO 2 emissions in the Caribbean-Latin America. The results show that the participation in GVCs causes renewable energy consumption and the relationship is negative at the level of 10% significance. This indicates that renewable energy consumption will decrease by 0.0698% when participation in GVCs increases by one percent. However, participation in GVCs does not cause CO 2 emissions. From Panel A of Table 3, renewable energy consumption does not cause participation in GVCs. This implies that there is no causal effect of renewable energy consumption on participation in GVCs in Caribbean-Latin America. Renewable energy consumption also does not cause the CO 2 emissions. In addition, Panel A of Table 3 also shows that CO 2 emissions do not cause the participation in GVCs and renewable energy consumption. This suggests that CO 2 emissions do not have casual effects on participation in GVCs and renewable energy consumption.
Panel B of Table 3 presents the causal relationship between participation in GVCs, renewable energy consumption and CO 2 emissions in the Middle East and North America (MENA). The estimated results show that the participation in GVCs does not cause renewable energy consumption and CO 2 emissions. Renewable energy consumption causes the participation in GVCs and the relationship is positive at the level of 1% significance. This indicates that one percent increase in renewable energy consumption would increase the participation in GVCs of countries in MENA by 0.0551%. However, renewable energy consumption does not cause CO 2 emissions. Panel B of Table 3 also shows that CO 2 emissions do not cause participation in GVCs and renewable energy consumption. Thus, CO 2 emissions have no causal effects on participation in GVCs and renewable energy consumption in MENA. This empirical evidence collaborates the findings of Charfeddine and Kahia [4] who found that renewable energy consumption has a slight influence on CO 2 emissions in MENA.
Panel C of Table 3 describes the causal relationship between participation in GVCs, renewable energy consumption and CO 2 emissions in sub-Saharan Africa. The empirical results show that the participation in GVCs does not cause renewable energy consumption and CO 2 emissions. That suggests that an increase in participation in GVCs would not affect renewable energy consumption and the CO 2 emissions in sub-Saharan Africa. From Panel C of Table 3, renewable energy consumption does not cause the participation in GVCs and CO 2 emissions, which implies that renewable energy consumption has no causal effects on participation in GVCs and CO 2 emissions in sub-Saharan Africa. In addition, the result also shows that CO 2 emissions cause the participation in GVCs and the relationship is negative at the level of 5%. Thus, one percent increase in CO 2 emissions will decrease the participation in GVCs by 0.139%. On the contrary, CO 2 emissions do not cause renewable energy consumption, which implies that an increase in CO 2 emissions would not influence renewable energy consumption.
This result is inconsistent with the finding of Zoundi [71] who found that renewable energy had a negative effect on CO 2 emissions in 25 selected African countries. Notes: t-statistics are given in parentheses. *, **, *** show significance at the 10%, 5% and 1% levels, respectively.

Variance Decomposition
In order to specify the degree of mutual dynamic effects between variables, in this section we use the forecast error variance decomposition method of the PVAR model to present the first 10 years of variance decomposition (see Appendix B for the variance decomposition). However, before the analysis of forecast error variance decomposition and impulse response functions, the stability of the PVAR model must be test. Referring to the studies of Hamilton [84], Lütkepohl [85] and Abrigo and Love [86], the model is stable only when the modulus of all eigenvalues of the adjoint matrix is less than one. The stability graphs (see Appendix C for the stability graphs) show that the characteristic roots are all less than one and all fall within the unit circle at both global and regional levels, which indicates that the PVAR models in this paper are all stable.
For the global level, only 0.020% of the forecast error variance of participation in GVCs after ten periods can be explained by shocks in renewable energy consumption, while 0.174% of the forecast error variance of participation in GVCs is explained by shocks in CO 2 emissions. After ten years forecast, around 0.482% of the forecast error variance of renewable energy consumption can be explained by disturbances in participation in GVCs, while around 0.006% can be explained by shocks in CO 2 emissions. Shocks in participation in GVCs appear to have minimal effect (only 0.262%) in forecasting CO 2 emissions, while shocks in renewable energy consumption appear to have a more important impact (3.187%) in forecasting CO 2 emissions.
In the Asia-Pacific region, the variance contribution of renewable energy consumption and CO 2 emissions to participation in GVC shocks are 0.028% and 0.135%. A shock to participation in GVCs accounts for 2.644% of the variance in energy consumption, and it accounts for 0.262% of the variance in CO 2 emissions. This result indicates that renewable energy consumption and CO 2 emissions appear to have insignificant or minor effects on participation in GVCs, while the participation in GVCs seems to have some impact in renewable energy consumption.
In the Caribbean-Latin America region, around 0.094% of the variance of participation in GVCs is explained by shocks in renewable energy consumption, and around 0.250% can be explained by shocks in CO 2 emissions; 0.835% of the variance of renewable energy consumption is attributed to shocks in participation in GVCs, and 0.194% of the variance of renewable energy consumption is attributed to shocks in CO 2 emissions. The variance contribution of participation in GVCs and renewable energy consumption and to CO 2 emission shocks are 1.138% and 5.881%, respectively.
In the MENA region, a disturbance to renewable energy consumption accounts for only 0.653% of forecast error variance in participation in GVCs, and a disturbance to CO 2 emissions accounts for only 0.730% of the variance in participation in GVCs. This means that renewable energy, renewable consumption and CO 2 emissions appear to have insignificant or minor effects on participation in GVCs in the short and long run. In contrast, 3.181% of variance of renewable energy consumption after ten periods can be explained by the disturbances in participation in GVCs.
In the sub-Saharan Africa region, a shock to renewable energy consumption accounts for 0.169% of the forecast error variance in participation in GVCs, and a shock to CO 2 emissions accounts for 1.164% of the variance in participation in GVCs. Additionally, around 0.976% of the variance of renewable energy consumption is explained by disturbances in participation in GVCs and 0.016% from disturbances in CO 2 emissions, while the variance contribution of participation in GVCs and renewable energy consumption and to CO 2 emissions' shocks are 1.649% and 14.783%.

Impulse-Response Function (IRF) Analysis
This section portrays the results of impulse response functions (IRFs) of economic growth, participation in GVCs, renewable energy consumption, CO 2 emissions and labor force, and we focus on the three variables of participation in GVCs, renewable energy consumption and CO 2 emissions using the Monte Carlo method to simulate the process 200 times. The IRFs proposed by Love and Zicchino [79] characterize the impact of adding a standard deviation to the error term on the current and future values of other endogenous variables while holding other variables unchanged. However, due to the uncertainty of variance-covariance of errors orthogonality, it is important to ensure the orthogonalization of shocks based on the Cholesky decomposition of variance-covariance matrix residues [87]. Thus, it is necessary to determine the order of variables on the basis of their endogeneity. Sims [87] considered that more exogenous and affect the following variables simultaneously or even with a lag should come out earlier; nevertheless, the variables coming out later are more endogenous and affect foregoing variables only with a lag. According to this and preceding studies, we ensured the order of variables in this paper as follows: economic growth, participation in GVCs, renewable energy consumption, CO 2 emissions and labor force. Economic growth may affect participation in GVCs, renewable energy consumption and CO 2 emissions contemporaneously or even with a lag, whereas renewable energy consumption and CO 2 emissions may affect the economic growth and participation in GVCs only with a lag. Figure 1 shows the global impulse response functions, which reports that the responses of participation in GVCs to one standard deviation shock of renewable energy consumption is positive, which initially increases and then decreases and stabilizes in the long run from year 2 to 10. More precisely, the maximum positive effect occurs in the first year with the value equal to about 0.002. On the contrary, a shock in CO 2 emissions will decrease participation in GVCs firstly and then increase it and eventually stabilize. The maximum negative effect also occurs in the first year. The responses of CO 2 emissions as the result of one standard deviation shock to participation in GVCs initially increase and then decrease and stabilize in the long run, while the responses of renewable energy consumption as the result of one standard deviation shock to participation in GVCs initially decrease and then increase and stabilize in the long run from year 2 to 10.
simultaneously or even with a lag should come out earlier; nevertheless, the variables coming out later are more endogenous and affect foregoing variables only with a lag. According to this and preceding studies, we ensured the order of variables in this paper as follows: economic growth, participation in GVCs, renewable energy consumption, CO2 emissions and labor force. Economic growth may affect participation in GVCs, renewable energy consumption and CO2 emissions contemporaneously or even with a lag, whereas renewable energy consumption and CO2 emissions may affect the economic growth and participation in GVCs only with a lag. Figure 1 shows the global impulse response functions, which reports that the responses of participation in GVCs to one standard deviation shock of renewable energy consumption is positive, which initially increases and then decreases and stabilizes in the long run from year 2 to 10. More precisely, the maximum positive effect occurs in the first year with the value equal to about 0.002. On the contrary, a shock in CO2 emissions will decrease participation in GVCs firstly and then increase it and eventually stabilize. The maximum negative effect also occurs in the first year. The responses of CO2 emissions as the result of one standard deviation shock to participation in GVCs initially increase and then decrease and stabilize in the long run, while the responses of renewable energy consumption as the result of one standard deviation shock to participation in GVCs initially decrease and then increase and stabilize in the long run from year 2 to 10. In Figure 2, participation in GVCs will have a negative response to a standard deviation shock in renewable energy consumption and CO2 emissions in the Asia-Pacific region in period 0 and 1 but the response is equal to zero from 2 to 10. More precisely, the maximum negative effects all occur in the first year with the value equal to about 0.005 and 0.01, respectively. This is consistent with the PVAR estimation that the contributions of renewable energy consumption and CO2 emissions to participation in GVCs are very weak in Asia-Pacific. In addition, the response of CO2 emissions to one standard deviation shock in participation in GVCs is positive and it is strongly positive in the first year. The response of renewable energy consumption to one standard deviation shock in In Figure 2, participation in GVCs will have a negative response to a standard deviation shock in renewable energy consumption and CO 2 emissions in the Asia-Pacific region in period 0 and 1 but the response is equal to zero from 2 to 10. More precisely, the maximum negative effects all occur in the first year with the value equal to about 0.005 and 0.01, respectively. This is consistent with the PVAR estimation that the contributions of renewable energy consumption and CO 2 emissions to participation in GVCs are very weak in Asia-Pacific. In addition, the response of CO 2 emissions to one standard deviation shock in participation in GVCs is positive and it is strongly positive in the first year. The response of renewable energy consumption to one standard deviation shock in participation in GVCs is positive at 0 and negative in the first year and stabilizes in the long run from 2 to 10. Figure 3 presents the Caribbean-Latin America impulse response functions, in which a positive shock to renewable energy consumption has a negative effect on the participation in GVCs at the first year and then positive in the second year, and the effects of shocks entirely die after three years. The maximum effect occurs in the first year. Similarly, the impact of a one standard deviation shock in CO 2 emissions on participation in GVCs is negative in the first year and positive in the second. Furthermore, the maximum impact also appears in the first year. The response of renewable energy consumption to a one standard deviation shock of participation in GVCs initially decreases and then increases and stabilizes in the long run from 3 to 10. The response of CO 2 emissions to one standard deviation shock in the participation in GVCs is instantaneously negative but positive in the first year and equal to 0 from year 2 to 10. shock to renewable energy consumption has a negative effect on the participation in GVCs at the first year and then positive in the second year, and the effects of shocks entirely die after three years. The maximum effect occurs in the first year. Similarly, the impact of a one standard deviation shock in CO2 emissions on participation in GVCs is negative in the first year and positive in the second. Furthermore, the maximum impact also appears in the first year. The response of renewable energy consumption to a one standard deviation shock of participation in GVCs initially decreases and then increases and stabilizes in the long run from 3 to 10. The response of CO2 emissions to one standard deviation shock in the participation in GVCs is instantaneously negative but positive in the first year and equal to 0 from year 2 to 10.  The MENA impulse response functions are shown in the Figure 4. Figure 4 shows that the response of the participation in GVCs to a one standard deviation shock in the growth of renewable energy consumption initially increases and then decreases and later increases and equals zero from year 3 to 10. The response of participation in GVCs to a one standard deviation shock of CO2 emissions is positive in the first two years and then negative in the third year and later equal to 0 from year 5 to 10. Additionally, the responses of renewable energy consumption to a one standard deviation shock in participation in GVCs are instantaneously positive but negative at the first year The MENA impulse response functions are shown in the Figure 4. Figure 4 shows that the response of the participation in GVCs to a one standard deviation shock in the growth of renewable energy consumption initially increases and then decreases and later increases and equals zero from year 3 to 10. The response of participation in GVCs to a one standard deviation shock of CO 2 emissions is positive in the first two years and then negative in the third year and later equal to 0 from year 5 to 10. Additionally, the responses of renewable energy consumption to a one standard deviation shock in participation in GVCs are instantaneously positive but negative at the first year and equal to 0 from year 3 to 10. The response of CO 2 emissions to a one standard deviation shock in participation in GVCs is positive in the first year and weakly negative in the second year, and the effect dies after a weakly positive response in the third year. From the sub-Saharan Africa impulse response functions in Figure 5, the reaction of participation in GVCs to one standard shock in renewable energy consumption is positive for the whole period (up to ten years), and the maximum positive impact occurs in the first year with the value approximately equal to 0.01. The reaction of participation in GVCs to a one standard deviation shock in CO2 emissions is strongly negative in the first year with a value of about 0.02. The impact dies after three years after a weakly positive response in the second year. The response of CO2 emissions to one standard deviation shock in participation in GVCs is negative from year 0 to 1 and equal to zero from year 1 to 10. The reaction of renewable energy consumption to a one standard deviation shock in participation in GVCs is positive for the whole period and then stabilizes from the first year. From the sub-Saharan Africa impulse response functions in Figure 5, the reaction of participation in GVCs to one standard shock in renewable energy consumption is positive for the whole period (up to ten years), and the maximum positive impact occurs in the first year with the value approximately equal to 0.01. The reaction of participation in GVCs to a one standard deviation shock in CO 2 emissions is strongly negative in the first year with a value of about 0.02. The impact dies after three years after a weakly positive response in the second year. The response of CO 2 emissions to one standard deviation shock in participation in GVCs is negative from year 0 to 1 and equal to zero from year 1 to 10. The reaction of renewable energy consumption to a one standard deviation shock in participation in GVCs is positive for the whole period and then stabilizes from the first year. Sustainability 2019, 11, x FOR PEER REVIEW 15 of 28

Robustness Check
In order to check the robustness of the previous analysis, we conducted the panel Granger causality test. The results from the test revealed the same direction of causal relationships between participation in GVCs, renewable energy consumption and CO2 emissions.
From Table 4 and 5 the participation in GVCs granger causes renewable energy consumption at the global level and in the Asia-Pacific, Caribbean-Latin America region, whereas all were without feedback. Renewable energy consumption causes the participation in GVCs in MENA region without feedback inversely. There is a bidirectional causality between participation in GVCs and CO2 emissions at the global level. However, there is only a unidirectional causal relationship running from CO2 emissions to participation in GVCs in selected sub-Saharan Africa countries and from participation in GVCs to CO2 emissions in Asia-Pacific region. Additionally, there is no causality between renewable energy consumption and CO2 emissions at global and regional levels.

Robustness Check
In order to check the robustness of the previous analysis, we conducted the panel Granger causality test. The results from the test revealed the same direction of causal relationships between participation in GVCs, renewable energy consumption and CO 2 emissions.
From Tables 4 and 5 the participation in GVCs granger causes renewable energy consumption at the global level and in the Asia-Pacific, Caribbean-Latin America region, whereas all were without feedback. Renewable energy consumption causes the participation in GVCs in MENA region without feedback inversely. There is a bidirectional causality between participation in GVCs and CO 2 emissions at the global level. However, there is only a unidirectional causal relationship running from CO 2 emissions to participation in GVCs in selected sub-Saharan Africa countries and from participation in GVCs to CO 2 emissions in Asia-Pacific region. Additionally, there is no causality between renewable energy consumption and CO 2 emissions at global and regional levels.

Conclusions
Based on the previous studies about participation in GVCs, renewable energy consumption and CO 2 emissions, this paper firstly employs the PVAR model with the System-GMM approach to examine the causality between participation in GVCs, renewable energy consumption and CO 2 emissions, while taking into account the variables of economic growth and labor force using the panel data of 172 countries throughout 1990-2015.
The main conclusions of the PVAR analysis can be summarized in three important points. Firstly, except for sub-Saharan Africa, there is a unidirectional causality between participation in GVCs and renewable energy consumption. Participation in GVCs negatively causes renewable energy consumption at the global level and in the Asia-Pacific and Caribbean-Latin America regions, which indicates that participation in GVCs aiming at accelerating economic development will not be conducive to the development and utilization of renewable energy. Renewable energy consumption positively causes participation in GVCs in MENA, which suggests that renewable energy policies aiming to increasing the use of renewable energy and reducing traditional energy use will promote the participation in the international division of labor. There is no causality between participation in GVCs and renewable energy consumption in sub-Saharan Africa.
Secondly, we also found that the causality between participation in GVCs and CO 2 emissions has different aspects in global and regional levels. There is a feedback causal relationship between participation in GVCs and CO 2 emissions at the global level. The environmental policies aimed at reducing CO 2 emissions will increase the participation in GVCs while GVCs policies, such as industrial innovation policies, will cause environmental degradation. There is a unidirectional causality running from participation in GVCs to CO 2 emissions, and participation in GVCs positively causes CO 2 emissions in the Asia-Pacific region. This indicates that the GVC policies will lead to environmental damage. There is a unidirectional causality running from CO 2 emissions to participation in GVCs, and CO 2 emissions negatively cause participation in GVCs in sub-Saharan Africa. This suggests that the environmental policies are beneficial for sub-Saharan African countries to participate in GVCs. However, there is no causality between participation in GVCs and CO 2 emissions in Caribbean-Latin America and MENA.
Thirdly, unlike many previous studies, we also found that there is no causal relationship between renewable energy consumption and CO 2 emissions both at global and regional levels. This implies that existing renewable energy policies fail to protect the environment, and environmental policies aimed at reducing CO 2 emissions also have no effect on the development and use of renewable energy.
From the forecast error variance decomposition, renewable energy consumption and CO 2 emissions appear to have a slight effect on participation in GVCs in the short and long run at the global and regional levels. Shocks in participation in GVCs also appear to have minimal effects in forecasting CO 2 emissions and renewable energy consumption. In addition, the impulse response results show that with the exception of the MENA region, the overall effect of a one standard deviation shock of CO 2 emissions on participation in GVCs is negative, while except for Asia-Pacific and Caribbean-Latin America region, the cumulative effect of a one standard deviation shock of renewable energy consumption on participation in GVCs is positive. For the global level and the Asia-Pacific and MENA regions, the cumulative effect of a one standard deviation shock of participation in GVCs on CO 2 emissions is positive, but for the global level and Asia-Pacific and Caribbean-Latin America regions, the overall effect of a one standard deviation shock of participation in GVCs on renewable energy consumption is negative.
Overall, this study demonstrates that there are environmental costs related to GVC policies aiming to participate in the global division of labor. Hence, the implementation of GVCs policies will be a challenge to environment protection. On the contrary, renewable energy policies and environmental protection policies do not have adverse effects on participation in GVCs. To some extent, environmental policies seeking to mitigate CO 2 emissions and to increase the use of renewable energy facilitate participation in GVCs. Thus, this investigation argues that reasonable environmental, energy and industrial policies should be developed to promote participation in GVCs while protecting the environment. Some of the policy recommendations are as follows.
Firstly, industrial policies aiming to promote participation in GVCs should be executed with care and should consider technological innovation to reduce traditional energy consumption and to accelerate renewable energy consumption. On the one hand, firms should be required to produce intermediate and final products complying with global standards and environmental certifications. On the other hand, since participation in GVCs is an important way to obtain technical information, governments should encourage firms to learn and absorb the environmental knowledge and technology in the process of participation in GVCs.
Besides, given that effective environmental governance can accelerate global competition through GVCs, environmental conservation policies targeting reduction of CO 2 emissions and increasing the use of renewable energy should be exercised rigorously. Sound environmental protection laws and regulations need to be developed to strengthen environmental management. At the same time, governments should provide financial support for environmental projects and facilities and offer tax breaks for companies, projects or products that are in line with environmental standards.
Furthermore, considering that renewable energy consumption does not play a role in alleviating CO 2 emissions currently, governments should continue the process of energy production and consumption reforms by setting mandatory renewable energy targets and development plans. Additionally, governments should raise funds through multiple channels to support renewable energy development to break through the constraints of inadequate inputs of funds.    Figure C1. Global stability graph.