Abstract
China’s renewable energy products have an important place in international trade, and the conclusion of the RCEP agreement can create favourable external conditions for China’s renewable energy product exports. This paper measures the export potential of China’s renewable energy products to other RCEP countries through a trade gravity model. The results show that (1) the GDP of the importing and exporting countries, the energy consumption of the importing countries, and the particulate emissions damage significantly enhance China’s renewable energy product exports; (2) among the RCEP countries, China has a greater potential to export renewable energy products to five countries in 2020, which are mainly located in East and Southeast Asia; and (3) from a dynamic perspective, China’s renewable energy trade potential is increasing, while in the Oceania region it is weakening, while trade links to Southeast Asian countries are developing in a more mature direction. Based on the above research, this paper puts forward corresponding policy recommendations.
1. Introduction
As an important part of a series of international agreements on energy conservation and emission reduction, such as the Paris Agreement, countries around the world have begun to take more environmentally friendly and clean renewable energy as the key direction for future energy development. Among them, the development achievements of China’s renewable energy are particularly remarkable. On the one hand, China has made great development and progress in many fields of renewable energy science and technology, and the 2022 China Renewable Energy Development Plan for the 14th Five-Year Plan indicates that China’s renewable energy industry has strong advantages and international competitiveness in the fields of hydropower, wind power, and photovoltaic. On the other hand, China has vigorously promoted the international trade and investment in renewable energy. For some developing countries, achieving peak carbon and carbon neutrality means that they must face the pressure of emission reduction targets in international agreements and the contradiction of relatively poor domestic renewable energy technologies. For developed countries, achieving the target means that they must face the contradiction of promoting renewable energy and high manufacturing costs. One important way to resolve these contradictions is to rely on maximizing welfare from trade, and China plays an important role in this process. In 2015, China accounted for 18.4% of the world’s total exports of renewable energy products. In 2016, China replaced the United States as the world’s largest producer and consumer of renewable energy. Helveston et al. [1] found that China’s PV industry’s mass production at scale accelerates the cost of PV equipment, and that if countries switch to domestic production, PV modules will be 20-25% more expensive in 2030 than if they rely on global supply.
As shown in Figure 1, the Regional Comprehensive Economic Partnership Agreement (RCEP), which will enter into force in January 2022, is a great opportunity for China and other developing or developed countries in the agreement, and its members consist of three countries in East Asia: China, South Korea, and Japan; two countries in Oceania: New Zealand and Australia; and ten countries in ASEAN, covering nearly half of the world’s population and nearly one-third of the world’s international trade. The contributions of the agreement include, but are not limited to, creating better investment relations among member countries [2] and building more equal trade and investment cooperation [3]. Although events such as India’s withdrawal show that there is still room for improvement in the benefit-sharing relationship of the agreement [4, 5], but overall, China’s renewable energy industry will have the opportunity to grow significantly on the basis of the freer and better trade relations created by the agreement among its member countries.
In the context of promoting renewable energy cooperation among the member countries of the agreement, it becomes necessary to quantify the potential trade linkages (i.e., trade potential) that can be developed between China and various countries with different economic and noneconomic variables such as economic size and geographical distance. This proposition will allow us to understand China’s main partners in the future development of renewable energy cooperation in the RCEP countries and to analyze the future direction of China’s renewable energy industry in the region. This study has a strong academic value and practical significance for a deeper understanding of the development of China’s renewable energy exports and the strengthening of energy cooperation between China and other countries.
2. Review of the Literature
In the context of the world’s energy policy of promoting renewable energy to save energy and reduce emissions, the feasibility and development of the renewable energy industry development has naturally received extensive attention from the academic community. In terms of feasibility, the academic community is generally optimistic. Turner [6] points out that the current renewable energy can already meet all the energy needs of American society and suggests that relying on renewable energy as the main energy source has a high feasibility. There are also scholars who take a more cautious view of the issue, such as Moriarty and Honner [7] who point out that renewable energy requires significant energy savings and indicate that estimates of the technical potential of renewable energy vary widely and that there is a possibility that energy costs will increase with the output of renewable energy. Further, the academic community has made a discussion on the characteristics and development of the industry. In terms of industry characteristics, Koo and Wang [8] point out that the new energy industry is environmentally friendly, technologically advanced, emerging, and weak, and has a natural monopoly. On the issue of industry development, current research has identified a variety of factors that can promote the development of this industry. For example, Gielen et al. [9] found that energy efficiency and renewable energy technologies are core elements to accelerate the energy transition and that economic conditions, resources, science and technology, and socioeconomic effects can effectively support the world’s energy transition. Edenhofer et al. [10] pointed out that there are multiple public policies that can justify renewable energy development that can bring cobenefits and indicated that renewable The economic potential of renewable energy has the opportunity to be further exploited. These studies also form the background and theoretical basis of this paper.
In the process of developing the renewable energy industry, most countries often need to integrate deeply into the global trade to reduce costs and improve efficiency, and the analysis of renewable energy products in international trade has become a hot topic. The current research in this field focuses on the competitiveness and global cooperation of renewable energy products, and there is less research on the trade potential. In terms of competitiveness, Shuai et al. [11] analyzed the international competitiveness of Chinese renewable energy products in the context of the Belt and Road Initiative through a CMS model and an explicit comparative advantage index and found that the overall international competitiveness of Chinese renewable energy is declining, but trade in ASEAN and South Asian markets is growing faster. Chen et al. [12] analyzed the international competitiveness of Chinese renewable energy products in the context of the Belt and Road through the ARDL boundary test and the VECM Granger causality method and found that there is a two-way causal relationship exists between foreign trade, CO2 emissions, and nonrenewable to renewable energy. In terms of global cooperation, Liu et al. [13] found through the Granger causality test that trade promotes economic development and renewable energy consumption. Zhao [14] argues that the opportunity to host the G20 summit could help China further promote renewable energy development and participate in global energy cooperation and governance. Lewis [15] notes that conflicts between renewable energy and trade policies may escalate as renewable energy deployment expands and suggests that resolving issues related to renewable energy development require extensive international cooperation. In terms of trade potential, Xu and Wang [16] analyze the current status of renewable energy development in Kazakhstan and find that China-Kazakhstan renewable energy cooperation has great potential. Shuai et al. [17] examined China’s trade potential in renewable energy products in 65 Belt and Road Initiative countries and found that China has significant trade potential in several countries. It can be seen that the gap in the current research on trade potential is that the trade potential in emerging trade organizations is less discussed. Considering the important role of emerging trade organizations in shaping the international trade market, this paper intends to fill the gap in this area by exploring RCEP, one of the emerging trade organizations.
This study focuses further on the current major trade potential measurement models. The most widely used model in trade potential estimation is the gravity model. This model has developed a solid theoretical foundation over many years. Bergstrand [18] showed that by proposing reasonable assumptions, a general equilibrium world trade model could be derived, and empirical analysis showed that the gravity model is a simplified form of a partial equilibrium submodel system of a general equilibrium model with country-differentiated products. Chaney [19] pointed out that under the assumption that the size of companies follows a Pareto distribution and the average square distance of company exports is an increasing power function of its size with constrained parameters, the distance elasticity of trade is constant at long distances, and when the size of companies follows Zipf’s law, trade is inversely proportional to distance. The application of this model is also very extensive. Sheng and Liao [20] used the gravity model to estimate the export potential of China to 40 major trading partners at both the aggregate and sector levels and found that China’s exports showed overall overtrade, but for seven countries, including Russia and Japan, it showed undertrade, and the main influencing factor was the total economic size of the trading partner. Sun [21] found that preferential trade arrangements have a significant promoting effect on China’s agricultural trade through the gravity model, and the trade potential between China and major developing countries is high and needs to be developed compared to the overall trade potential with developed countries. Boughanmi [22] analyzed the trade potential between Arab coastal countries using the gravity model and found that newly signed trade arrangements are expected to increase new trade opportunities in the Gulf Cooperation Council region. Improved versions of the gravity model, such as the stochastic frontier gravity model, have also been adopted by many scholars. He et al. [23] compared the trade potential of China and its trading partners before and after the opening of the Arctic route using the stochastic frontier gravity model and found that the opening of the Arctic route will increase China’s export potential and import potential to the route revenue countries by an average of 10.5% and 28.1%, respectively, and the average growth space for imports and exports reached 463.6%. Lu and Ma [24] used the gravity model to test the decision of developing countries on service export trade flows to OECD countries. Ravishankar and Stack [25] calculated the trade efficiency between Eastern and Western Europe under the background of trade integration using the stochastic frontier analysis gravity model, and the results showed that the trade between Eastern and Western Europe was highly integrated with low trade resistance. Cutting-edge machine learning methods are being applied in the estimation of trade potential. Guo and Mai [26] used a BP neural network to improve the trade gravity model and analyze the trade potential of Chinese photovoltaic products with RCEP countries. The study found that China’s trade potential for photovoltaic products with RCEP countries has matured to a significant extent, but there is still potential for further strengthening of trade links with some countries. However, this paper was limited to a small scope of discussion in the field of photovoltaic products and did not draw a conclusion that could be extended to the renewable energy industry. Therefore, this article is aimed at filling this research gap.
The following two research questions are attempted in this paper to fill this research gap: (1) What are the factors affecting the trade volume between China and RCEP countries? (2) What is the trade potential between China and the RCEP countries and how has it changed?
3. Scope of the Study, Data Sources, and Research Methodology
3.1. Scope of the Study and Data Sources
This paper selects 14 countries in the RCEP, excluding China, as the research sample, covering the time period 2010-2020 and covering various major events in the development of China’s renewable energy industry, such as the revision of the Renewable Energy Law in 2010, the decreasing cost of renewable energy generation products, and the “12th Five-Year Plan”. The final result is a short panel of 14 cross-sectional individuals with a 10-year span. The commodity groups studied in this paper include solar, wind, biomass, hydro, geothermal, and marine energy, involving 81 commodities. The HS codes for 17 solar products are as follows: 700991, 700992, 711590, 730890, 732290, 721090, 830630, 841280, 841919, 841990, 850239, 850440, 854140, 900190, 900290, 900580, and 901380; for 19 wind products, the HS codes are as follows: 730820, 841290, 848210, 848220, 848230, 848240, 848250, 848280, 848280, 901380, 902830, 903020, 903031, 903039, and 903289; 17 products of water energy with HS codes are as follows: 382450, 681091, 841011, 841012, 841013, 841090, 850161, 850162, 850163, 850164, 850421, 841620, 841931, 841940, 841989, 842129, 824139, 847920, and 847989; 8 products of geothermal energy with HS codes are as follows: 730431, 730441, 730451, 741121, 741122, 741129, 841861, and 841950; marine energy 2 products with HS codes are854449 and 854460. Compared to the 17 types of solar products studied by Guo and Mai [26], the renewable energy products covered in this study are more comprehensive in terms of energy types and basically include most of the currently commercially available energy types.
The distances between countries in this article come from the CEPII-BACI database, while renewable energy generation and capacity data are from the International Renewable Energy Agency (IRENA). GDP, renewable energy consumption (as a percentage of total energy consumption), CO2 damage (as a percentage of GNI), natural resource depletion (as a percentage of GNI), and particulate matter emissions damage (as a percentage of GNI) are sourced from the World Development Indicators (WDI), and total energy consumption data is from the International Energy Agency (IEA). Trade data between countries is from the United Nations Comtrade database.
3.2. Research Methodology
3.2.1. Trade Potential
Guo and Mai [26] used a modified BP neural network trade gravity model to measure the theoretical value of exports, but there is a “black box” problem in this measurement, so this study focuses more on the role of each variable in China’s trade with RCEP countries, so this paper uses the more traditional but more transparent multiple linear regression as an analytical tool. Trade potential refers to the potential of one country to develop closer trade ties with another country. Trade potential can be quantified by calculating the ratio of the actual value of trade between two countries to the theoretical estimate, as shown in the following equation. where is a ratio measuring trade potential, refers to the actual value of a country’s exports from country i to country j in period t, and refers to the theoretical value of a country’s exports from country to country in period . The current way to classify the size of trade potential is mainly based on the “0.8-1.2 cut-off,” in which less than 0.8, within the range of 0.8 to 1.2, and more than 1.2 correspond to “great potential,” “growth potential,” and “limited potential,” respectively. In this paper, we also use this method to classify trade potential.
3.2.2. Theoretical Estimates of Export Value
The trade gravity model, first proposed by Tinbergen [27] and Poyhonen [28], is the main model for calculating theoretical estimates of export values, which considers the size of bilateral trade between the two countries to be proportional to the total economic volume of the two countries and inversely proportional to the distance between the two countries, and can be expressed by the following equation. where EXP refers to the amount of exports from one country to another, GDP refers to the GDP of the exporting country, GDP refers to the GDP of the importing country, and DIS refers to the distance between the two countries. Taking the logarithm of both sides of this equation, the model can be transformed into a regression model.
It should be noted that the model is open-ended, and more control variables can be added to the model to achieve more accurate estimates, such as Linnemann [29], who first introduced demographic factors into the basic gravity model, and Bergstrand [30], who further added per capita income and exchange rate. In conjunction with the research objectives of this paper, this paper adds seven control variables such as particulate matter emission damage (as a percentage of GNI), to the basic gravity model with the availability of data for a total of ten independent variables. The final extended gravity model of this study is as follows, and the meanings and expected signs of each variable are shown in Table 1.
The theoretical basis for the expected signs of the variables in this study is as follows: Exporting country GDP and importing country GDP reflect the supply capacity of the exporting country and the demand level of the importing country, so the expected coefficient sign is positive. The distance between the two countries affects the transaction costs such as transportation costs of trade between the two countries. Generally speaking, the cost of trading between two countries that are farther apart is higher, so the expected sign is negative. Carbon dioxide damage, natural resource depletion, and particle emission damage reflect a country’s potential demand for renewable energy products, and the expected coefficient sign is positive. Among them, the positive effect of carbon dioxide emissions on the use of clean energy has been confirmed in Mohammad and Khosrul [31]. Muhammad et al. [32] also confirmed the bidirectional causal relationship between ecological footprint and renewable energy use. Total electricity consumption reflects a country’s demand for energy, and the significant impact of this variable on renewable energy product trade has been confirmed in Shuai et al. [17], so the expected sign is positive. Renewable energy generation capacity and renewable energy generation amount depend on the quantity and demand of renewable energy products available within a country, so the expected sign for these variables is also positive. In addition, renewable energy consumption (percentage of final energy consumption) reflects a country’s direct consumption and demand for renewable energy products, so the expected sign is also positive. These two variables directly reflect a country’s renewable energy product ownership and demand, and we believe that their role in trade volume is self-evident. lnNRR, lnEC, and lnEG are processed by taking the logarithm of the original value plus one due to the existence of zero values.
This study uses this extended gravity model to obtain a theoretical estimate of China’s exports to RCEP countries, EV, and combines it with the actual value of exports, EXP, to estimate the trade potential, .
4. Analysis of Empirical Results
4.1. Choice of Estimation Method
For panel data, there are three commonly used estimation methods: mixed regression (PR), fixed effects (FE), and random effects (RE). In order to accurately estimate trade potential, this study conducted F-test and LM-test with the Hausman test for the three regression methods. The estimated coefficients and test results of the three estimation methods are shown in Table 2, and the detailed process is described below.
Firstly, the F-test was used to analyze the effect of the individual effect in the model, and the value of the F-test was 0.000, so the original hypothesis “H0: all ” was strongly rejected, i.e., FE was better than PR. Further, the LM-test was used to identify the random effects in the model, and the value of the LM-test was 0.000, i.e., RE was better than PR. Finally, the Hausman test can be used to test the hypothesis “H0: ui is not correlated with xit and zi “, and the value of the Hausman test is 0.2449, which does not reject the original hypothesis, making RE more valid than FE.
4.2. Analysis of Model Estimation Results
Based on the results of the above analysis, this study uses a random effects model as a method to estimate the theoretical value of trade. Further, in order to estimate the theoretical values more robustly, a panel model with stepwise regression was used to remove insignificant or colinear variables from the random effects until all variables were significant, and finally five significant variables were selected: log GDP of exporting countries, log GDP of importing countries, log particulate emissions damage (as a percentage of GNI), log renewable energy consumption, and log of total consumption of electricity. Total consumption of electricity. The regression results of the basic and extended trade gravity models are shown in Table 3.
It can be seen that all five independent variables screened out have high significance. However, stepwise regression of the panel data may eliminate variables with large differences between the coefficients estimated by RE and FE, which may lead to changes in the Hausman test results. For robustness reasons, this study conducted the Hausman test again on the random effects model obtained after stepwise regression, and the results are shown in Table 4.
It can be seen that the results after stepwise regression still do not reject the original hypothesis, and we believe that the random effects model after stepwise regression can estimate the theoretical value of renewable energy exports more accurately, so the final regression equation is
Continuing the approach of Shuai et al. [17], we can formulate the model as follows and describe the importance of each variable: (1) exporters’ GDP is significantly and positively correlated with exports of renewable energy products, with each 1% increase in exporters’ GDP increasing exports of renewable energy products to RCEP countries by 1.039%. (2) The GDP of importing countries has a pulling effect on the export of renewable energy products, with each 1% increase in the GDP of importing countries increasing the export of renewable energy products by 0.422%. (3) Particulate matter emission damage has a boosting effect on the export of renewable energy products, as shown by the fact that for every 1% increase in carbon dioxide damage, the export value of renewable energy products will rise by 0.580%. (4) There is a negative correlation between renewable energy consumption in importing countries and the export value of renewable energy products, as a 1% increase in renewable energy consumption will lead to a 0.269% decrease in export value. (5) Electricity consumption has a significant contribution to the export of renewable energy, as shown by the fact that for every 1% increase in electricity consumption, the export value will rise by 0.497%.
5. Trade Potential Estimation and Discussion
By converting the theoretical values of renewable energy product exports estimated by the extended gravity model (5) to the actual values using equation (1), this study estimates the trade potential between China and the remaining RCEP 14 countries.
5.1. Trade Potential in 2020
In order to observe the latest trend of China’s renewable energy export trade potential, this paper first analyzes the trade potential in 2020 and obtains the trade potential values for each country as shown in Table 5.
5.1.1. Segmentation of Trade Potential
Based on the classification in Subsection 4, the paper further classifies the RCEP 14 countries in 2022 according to their trade potential as “high potential,” “growing potential,” and “limited potential.” The paper further classifies the RCEP 14 countries in 2022 into “high potential,” “growing potential,” and “limited potential” based on their trade potential. The final result is that there are four countries in the “great potential” category, three countries in the “growth potential” category, and seven countries in the “limited potential” category, and the detailed results are shown in Table 6.
5.1.2. Regional Analysis
In order to analyze the trade potential of Chinese renewable energy products in RCEP countries in 2020 and to find potential markets, this paper further marks the types of trade potential of 14 RCEP countries other than China on the map, and the results are shown in Figure 2. (1)China has a high trade potential in East Asia. In addition to China, the two East Asian members of RCEP are Japan and South Korea. China has a high potential to trade renewable energy products to Japan and South Korea. Although China has a high export volume of renewable energy products to these two countries, there is still some room to increase the export volume of renewable energy products due to the large economic volume and energy consumption of these two countries(2)China’s trade relations in the Oceania region are more mature, with the two Oceania members of the RCEP being New Zealand and Australia. Overall, China’s renewable energy trade potential with both countries is relatively small. In particular, trade potential with New Zealand tends to grow, while trade potential with Australia is more limited(3)China’s trade potential with Southeast Asian countries varies greatly from country to country. The majority of countries with limited trade potential in renewable energy products are located on the western side of the South Central Peninsula (Cambodia, Laos, and Vietnam), the southern side (Singapore), and the Malay Archipelago (Indonesia). Fewer countries have increased trade potential, mainly on the western side of the South Central Peninsula (Myanmar) and the northern side of the Malay Archipelago (Malaysia), and a limited number of countries have significant trade potential, mainly in south-eastern Asia (the Philippines), the central South Central Peninsula (Thailand), and the northern Malay Archipelago (Brunei).
Overall, after a long period of development, China’s trade ties with more of the 14 RCEP countries in 2020 has become closer, and the trade potential has been more fully utilised; therefore, the important development direction for China’s renewable energy products in the RCEP countries is East Asia, New Zealand, and the Philippines in ASEAN. Further strengthening China’s renewable energy trade ties with these regions could be an effective pathway to market diversification for Chinese renewable energy products. From the perspective of the trade gravity model, this result can be explained by the potential of the East Asian region, which has a higher GDP, electricity consumption, and particle emission damage, to import the highest-renewable energy products. Although Oceania is also developed, its particle emission damage is relatively low due to differences in industrial structure and geographical factors. Southeast Asia, on the other hand, has a generally lower economic level and thus a smaller overall trade potential.
5.2. Changing Dynamics of Trade Potential 2010-2020
To further study the evolution trend of China’s export potential for renewable energy to RCEP member countries, this article has depicted the trade potential situation of each country from 2010 to 2020 and analyzed the possible reasons for the changes in trade potential from the perspective of the gravity model constructed in the previous section. As shown in Figure 3: (1)Overall, China has a large trade potential with East Asia, and its trade potential has been growing in recent years. China’s trade potential with Japan has shown a continuous upward trend. In 2010, China’s trade potential with Japan was 1.05, which belonged to the type of increasing potential. Its trade potential has been on a rising trend in all years except for 2011, 2014, and 2019 and finally reached a value of 0.42 in 2020, becoming a huge potential. This trend is mainly related to the continuous and stable rise in the GDP of Japan and China during the research period, and the continuous increase in Japan’s particle emission damage in two time periods from 2010 to 2014 and from 2017 to 2020 also contributed to the growth of its trade potential. The continuous decline in Japan’s total electricity consumption during this period is the main reason hindering its further trade potential growth. On the other hand, China’s trade potential with South Korea experienced a process of first rising and then falling. In 2010, China’s trade potential with South Korea was 0.71. This value continued to increase from 2010 to 2014 and reached 1.21 at the end of the period. After reaching the level of limited trade potential, the trade potential value began to decline continuously. In 2020, the value dropped to 0.54, indicating a large untapped potential. During the research period, all indicators in the gravity model steadily increased, and the theoretical export value steadily increased as well. However, the actual export value showed a trend of first rising and then falling. This change may be caused by factors outside the model, which we will discuss in Section 6. It is worth noting that China’s trade potential with Japan and South Korea has shown a continuous upward trend since 2014, indicating that China has significant untapped trade potential in East Asia(2)China’s trade relations with the Oceania region are developing in a more mature direction. China’s trade potential with New Zealand has shown a declining trend. Except for a slight decline in 2016, China’s trade potential value for exporting renewable energy products to New Zealand has continued to rise. The trade potential value in 2010 was 0.46, and by 2020 it had reached 1.04, but it has not yet reached the level of limited trade potential, indicating that China still has room to further tap the trade potential of renewable energy with New Zealand. This trend of change is related to the increasing GDP of both countries and the rising particulate matter emissions damage in New Zealand during this period. The overall increase in energy consumption in New Zealand after 2013 has also promoted the improvement of trade potential. In contrast to the situation in New Zealand, China’s trade potential for renewable energy products with Australia during the study period is limited, although the trade potential value has fluctuated greatly. In 2010, China’s trade potential value with Australia was 1.94. After rising to 2.93 in 2011, it continued to decline to 1.27 in 2016, and then rose again to 2.32 in 2018 before declining again to 1.90 in 2020. This indicates that the trade of renewable energy products between China and Australia has reached a relatively mature stage, and its trade potential is more limited. The theoretical trade value between the two countries did not increase significantly during this period, and the change in Australia’s trade potential value was more affected by the actual trade value, reflecting more uncertainty in the trade volume between the two countries, but this uncertainty does not affect the conclusion that the trade relationship between the two countries is highly mature. As Australia’s trade potential value has always been high, while New Zealand, with a smaller trade potential value, has experienced continuous growth in trade potential value, overall, China’s trade potential with the Oceania region is continuously being realized, and China’s relationship with Oceania is becoming more mature(3)Changes in China’s trade potential with countries in Southeast Asia show obvious differences, but in general, the trade potential of Southeast Asian countries has been decreasing in recent years. Three of the Southeast Asian member countries of the RCEP have a large trade potential overall: the Philippines, Brunei, and Thailand, and the value of China’s trade potential with the Philippines fluctuates considerably, with its value experiencing two significant decreases (2011 and 2015). However, in overall, China’s trade potential with the Philippines remains high, and China’s trade potential with Brunei also fluctuates greatly, with a minimum value of 0.14 in 2010 and a maximum value of 0.27 in 2018. As China’s trade potential with Brunei is below 0.6 except for 2017 when it reached 1.00 and 2018, and the value drops back to 0.18 in 2020, overall China still has a large trade potential with Brunei. Until 2014, China’s trade potential with Thailand for renewable energy products was in a state of potential growth, and in 2014, China’s trade potential with Thailand dropped to 0.75. Between 2014 and 2020, the trade potential with Thailand fluctuates slightly but is in the range of great potential, and in 2020, China’s trade potential with Thailand is 0.70, which overall means there is still more trade potential available
There are four countries with limited trade potential overall, namely, Indonesia, Vietnam, Singapore, and Laos. After rising from 2.33 to 2.77 in 2011, China’s trade potential with Indonesia showed a downward trend until it reached 1.40 in 2016, after which it resumed its upward trend, and its trade potential has been relatively limited overall. The value of China’s trade potential with Vietnam is also high, rising twice, to 2.97 and 4.91 in 2014 and 2020, respectively, and never dropping below 1.2 during the study period, making China’s trade potential with Vietnam more limited overall. China’s trade potential with Singapore is more stable, with the exception of 2010, 2014, and 2015, when it rises; it remains slowly declining in all other years, but the potential is always above 1.2, making the overall trade potential more limited. The value of China’s trade potential with Laos, on the other hand, generally shows an upward and then stable trend, with the value of China’s trade potential with Laos always below 1.2 before 2012, in the potential growth or great potential category, while after 2012, the value oscillates around 1.4 and is generally above 1.2. The potential is more limited as it is fully utilised.
The remaining three countries: Cambodia, Malaysia, and Myanmar, have seen large changes in their trade potential values over the study period, spanning a wide range, indicating that these countries have undergone a transition in their trade potential over the study period. For Cambodia, the value of China’s trade potential for it has changed more widely and in an unpredictable pattern. Overall, it has gone through three stages of rising, then falling, then fluctuating upwards, with an upward trend from 2010 to 2012, when the value of trade potential changed from a potential growth type to a potential limited type, followed by a large decline from a potential limited type to a potential large type between 2012 and 2014, and For Malaysia, the value of China’s trade potential with it has gone through two phases, one being the limited potential phase from 2010 to 2015, during which the value of trade potential first rose from 2010-2012 and then fell to 1.23 in 2015, a period during which Malaysia’s trade potential has been of the limited potential type and but trending downwards. The second is the growth potential phase from 2016 to 2020, during which the trade potential value fluctuates around 1 and remains in the growth potential category. China’s trade potential with Myanmar can be broadly divided into three periods: between 2010 and 2015, the trade potential values fluctuate widely and are generally of the growth potential type, reaching limited potential (2010, 2015) and growth potential (2012) in individual years, and the second period is 2016-2019. The value of trade potential in this period is generally lower than in the previous period; it has been of the great potential type and shows a slow decline. The third period is from 2019 to 2020, when the value of trade potential rises rapidly and becomes potential growth type at the end of the period.
It is worth noting that in the last three years (2018-2020), only two countries (Malaysia and Brunei) have seen an overall increase in trade potential, while China’s trade potential with other Southeast Asian countries has shrunk to varying degrees, with Vietnam and Cambodia showing the most significant reduction in trade potential in the last three years. The above analysis shows that the export potential of Chinese renewable energy products in Southeast Asian countries is decreasing. From the perspective of the gravity model, the reason for this trend is the continuous decline in total particulate matter emissions in Southeast Asia during the research period, and the overall decline in GDP and total electricity consumption since 2019 are also important reasons for the decrease in trade potential.
Overall, China’s renewable energy trade potential with most RCEP countries has undergone a complex process of change, indicating the presence of some external factors affecting renewable energy product trade outside the model during the study period. These factors will be discussed in Section 6 of this article. In general, the overall trend for each country is an increase in trade potential values, with the type of trade potential shifting towards limited potential or potential growth, demonstrating the gradual maturity of China’s renewable energy product trade with RCEP countries.
6. Discussion
The factors that affect trade potential within a trade organization are complex and diverse. This article constructs an extended trade gravity model with five variables to estimate the trade potential between China and other RCEP member countries. Like other models, we must acknowledge that the trade gravity model cannot fully explain the impact of these factors, and the heterogeneity problem of the model has not been fully resolved and is difficult to fully resolve. The unexplained factors in the model include (1) advances in renewable energy technology in each country. This factor will affect trade volume through the production of substitutes, changes in China’s comparative advantage in renewable energy products, and the enhancement of a country’s self-sufficiency in its own products; (2) renewable energy development policies in each country. Countries with higher environmental requirements (such as developed countries in East Asia and Oceania) may formulate more stringent environmental protection policies and more active renewable energy development policies. At the same time, a country may designate short-term renewable energy development plans, leading to a significant increase in imports in the short term, all of which will affect a country’s trade volume; (3) differences in resource endowments. Some renewable energy facilities, such as photovoltaics and wind power, require certain natural conditions for construction. Therefore, differences in resource endowments among countries will directly lead to differences in trade volumes. For example, the demand for photovoltaic products may be lower in the ten ASEAN countries located in tropical rainforest climates, while Australia, which has a large land area and heat, may have greater demand for photovoltaic products; (4) bilateral relations. The trade volume of renewable energy products between two countries is also affected by the political relations between the two countries. There are many more factors that affect the trade potential of renewable energy between two countries, and in further research, a more effective tool should be found to consider the impact of these factors.
7. Conclusions and policy recommendations
The analysis of the empirical results above shows that (1)The GDP, energy consumption, and particulate matter emissions of RCEP countries significantly promote China’s exports of renewable energy products. The regression results show that for every 1% increase in the GDP of the exporting country, the export value of renewable energy products to RCEP countries will increase by 1.039%, and for every 1% increase in the GDP of the importing country, the export value will increase by 0.422%. For every 1% increase in particulate matter emissions, the export value will increase by 0.580%. For every 1% increase in electricity consumption, the export value will increase by 0.497%. Therefore, an increase in these variables, while the actual export value remains constant, will increase the trade potential(2)In RCEP countries, China has significant export potential for renewable energy products to five countries in 2020, mainly distributed in East Asia and Southeast Asia. There are two countries in East Asia, South Korea and Japan, and three in Southeast Asia, Brunei, the Philippines, and Malaysia, among which Brunei, South Korea, and Japan are the top three countries in terms of trade potential. Two factors contribute to the high export potential of these countries: one is that they have relatively high GDP, energy consumption, and particulate matter emissions; the other is difficult-to-quantify factors such as technological progress, resource endowments, and bilateral relationships(3)From a dynamic perspective, China’s trade potential for renewable energy in East Asia is constantly increasing, while its potential in Oceania is weakening and its trade links with Southeast Asian countries are moving towards a more mature direction. The possible reasons for this trend are the continuing growth in GDP and particulate matter emissions in East Asia and Oceania and the recent reduction in GDP, electricity consumption, and particulate matter emissions in Southeast Asia. However, considering the significant differences in China’s trade potential with Southeast Asian countries, there is still the possibility for China to further expand its markets in specific countries in Southeast Asia under the RCEP framework, such as Brunei, the Philippines, and Thailand. Overall, China still has the potential to develop closer trade cooperation with East Asia and Southeast Asia
Based on the above research conclusions, this article further proposes the following corresponding policy suggestions: (1)Further promote the implementation of the RCEP agreement and remove trade barriers between RCEP member countries. China should actively implement the content of the RCEP agreement and use effective means such as reducing tariff preferences, strengthening regional industrial and supply chains, and removing trade barriers to reduce transaction costs, promote cooperation in renewable energy product trade within the region, and pay particular attention to potential environmental problems caused by trade. It is necessary to first improve and implement regulations on industrial transfer, foreign investment, and trade in the agreement and minimize ecological inequality in the trade process. In addition, trade organizations should promote the development of labor welfare and environmental issues in renewable energy product trade, and it is necessary for all countries to jointly formulate labor standards that can protect human rights and create a better working environment, and governments and enterprises should take social responsibility for governance and protection against environmental pollution caused by trade(2)Strengthen the deep integration of the renewable energy product industry chain and innovation chain and promote the expansion of China’s renewable energy industry to high value-added and highly competitive sectors. In China’s trade with other countries in the RCEP, product technology level and product competitiveness are key factors in increasing China’s trade volume with other countries, especially the four developed countries in East Asia and Oceania. By further strengthening the energy input into renewable energy products, China has the opportunity to seize more market share in countries with high trade potential such as Japan and South Korea, and also to create new competitive points for renewable energy products in mature trading countries, stimulating trade(3)Further improve differentiated marketing strategies for renewable energy products. Based on the demand characteristics of different countries, using the RCEP agreement to consolidate trade relations with mature trading countries while fully tapping into the huge trade potential and potential demand of countries with overall trade potential, will promote further optimization of China’s renewable energy product market structure
Data Availability
The data and estimation commands that support the findings of this paper are available on request from the first and corresponding authors.
Consent
Informed consent was obtained from all the subjects involved in the study.
Conflicts of Interest
The authors declare no conflict of interest.
Authors’ Contributions
Conceptualization was done by Qing Guo. Methodology was worked by Qing Guo. Software and formal analysis was focused by Zishan Mai. Writing the original draft preparation was conceived by Qing Guo and Zishan Mai. Writing the review and editing was assigned by Qing Guo and Zishan Mai. Supervision and funding acquisition was conducted by Qing Guo. All authors have read and agreed to the published version of the manuscript.
Acknowledgments
This research was funded by the National Social Science Foundation (21CJL007); the Humanities and Social Science Project of China’s Ministry of Education (20YJC790036); Guangdong-Hong Kong-Macao Greater Bay Area Accounting and Economic Development Research Center Project, Guangdong University of Foreign Studies (YGAZD2022-04); Institute of City Strategy Studies Project, Guangdong University of Foreign Studies (JDZB202104); Pacific Island Countries Strategy Research Centre Project, Guangdong University of Foreign Studies (2021PIC003); Institute for African Studies, Guangdong University of Foreign Studies (HX-FZ2022-2); Asia-Pacific Security and Economic and Political Cooperation Research Centre Project, Guangdong University of Foreign Studies (YT2022001); Guangdong Postgraduate Education Innovation Project (2022XSLT027); Philosophy and Social Science Development Planning Project of Guangzhou (2021GZGJ07); and Center for Translation Studies Project Guangdong University of Foreign Studies (CTS202201).