Energy Trade Cooperation Between China and Regional Comprehensive Economic Partnership Countries Under the Background of Carbon Neutrality

Abstract

At present, the global carbon neutrality action is intended to change the energy structure and promote the development of regional energy trade, which is conducive to alleviating the contradiction between energy supply and demand. Based on this, the paper uses the RCA index to explain the complementary advantages of different types of energy trade among RCEP countries in depth. In addition, the trade gravity model is applied to compare and analyze the various influencing factors of energy trade to seek the best measures for energy trade cooperation. The results show that compared with renewable energy, traditional energy is more complementary. China and Australia have the strongest energy complementarity, followed by ASEAN countries. The GDP, energy trade complementarity, economic liberalization, the trade environment, and the technological level all affect fossil energy trade and renewable energy trade to varying degrees. When the detailed planning of the carbon neutrality target is completed, the effect of each significant factor on trade is stronger. In this regard, the smooth realization of energy trade cooperation between China and the RCEP requires a series of measures to support.

1. Introduction

In November 2020, 15 countries officially signed the Regional Comprehensive Economic Partnership (RCEP), covering resource-endowed and technology-endowed countries, which not only boosted confidence in regional trade liberalization and globalization but also contributed to the development of energy markets [1]. On the one hand, all members of the RCEP have promised to reduce tariffs and standard barriers, which is conducive to further strengthening trade cooperation and solving the problem of energy supply shortage. On the other hand, the economic and energy endowments of the RCEP countries are quite different, forming a certain complementarity of energy and technology, which is conducive to the regional countries playing their respective comparative advantages and strengthening energy trade cooperation. Under the background of the signing of the RCEP, energy trade cooperation between relevant countries and regions, as an important part of regional economic and trade integration, will continue to play a major role in international trade. In addition, the particularity of the distribution of energy resources in the Asia-Pacific region gives the sub-regional energy trade great cooperation advantages [2], which plays an important role in promoting RCEP energy trade cooperation. At present, countries in the region have a high degree of dependence on foreign energy, especially fossil energy, which in many countries is heavily dependent on imports. According to the BP World Energy Statistics Yearbook 2024, abundant resources make ASEAN and Australia important energy exporters. For example, Australia has long exported coal and natural gas to China. In addition, according to UNCTAD statistics, bilateral energy trade between RCEP countries is frequent. More than 50% of energy trade in most countries comes from the RCEP region. In particular, 96% of New Zealand’s trade volume in 2023 came from countries in the RCEP region. Obviously, the trade cooperation between RCEP countries has a certain realistic basis.

In addition, whether it is a change in the global energy landscape or the introduction of carbon neutrality goals, there is an urgent need to strengthen regional energy trade. At the same time, promoting energy trade cooperation also requires an accurate and appropriate entry point and an optimal combination of measures. In view of this, it is very important to comprehensively explore the driving factors behind the energy trade of RCEP countries. Therefore, this paper focuses on the regional scope of the RCEP. Firstly, based on the actual data, this paper analyzes in depth the trade complementary advantages of different energy sources (categorized into three traditional fossil energy sources, namely oil, coal and natural gas, and six renewable energy sources, namely solar energy, wind power, bioenergy, hydraulic power, geothermal energy, and ocean energy) in RCEP countries, to determine the realistic conditions for regional energy trade cooperation. The second is to explore the important factors affecting different types of energy trade using the trade gravity model. Finally, based on whether to propose a detailed plan for carbon neutrality targets, this paper further analyzes how to shape the energy trade impact pattern between China and RCEP countries in order to seek the best measures for energy trade cooperation.

2. Literature Review

Energy trade is a long-standing research topic. Many scholars have found that energy trade is inextricably linked with economic development, energy security, energy consumption, and carbon emissions. Energy trade boosts economic growth [3,4] to enhance energy security [5,6] and to reduce regional carbon dioxide emissions [7,8,9]. As the world’s energy supply and demand pattern becomes more multidimensional, international energy cooperation is also facing renewal and evolution. In the complex energy trade situation, the structure of energy trade has changed. More and more countries are actively seeking regional energy trade cooperation to address new situations and problems in the international energy market. Based on this, regional energy cooperation has become a hot topic of current research. The current energy trade cooperation faces many challenges, such as the limitations and uneven distribution of fossil energy carriers, the increasing dependence on energy consumption and fossil fuels, and the influence of geopolitical layout, which may lead to the uncertainty of regional energy trade cooperation [10,11,12,13]. In spite of this, there is still strong energy complementarity and huge energy trade potential among regional countries. Energy import and export trade among countries helps to enhance regional energy security and has great room for cooperation and development prospects [14,15,16].

In addition, under the background of the great change in global energy supply and demand patterns and the increasingly serious global climate pollution problem, the call for regional energy trade cooperation is getting stronger, and the exploration of the driving factors behind energy trade cooperation has also become the focus of research. Initially, most scholars mainly focused on fossil energy, focusing on macro-level elements, such as the global political landscape [12], global conflicts of interest [17], policy trade sanctions [18], economic development [4], and trade and investment barriers [6]. In recent years, more and more attention has been paid to the analysis of micro factors. It is generally believed that the development of energy industry trade is the result of the comprehensive effect of many factors, among which market conditions and scale, geographical distance, and factor endowment have significant effects [16]. Location advantages can bring more convenient trade and logistics conditions, and the regional agglomeration characteristics of the global value chain can also achieve the growth of trade volume [19,20]. In addition, technological innovation has injected technological advantages into the energy trade [21]. The energy trade environment and energy complementarity determine the process of energy trade cooperation to a certain extent [15]. At present, the global pollution pressure is becoming more and more serious, and the demand for renewable energy is increasing, which is leading to academic research on the factors influencing renewable energy import and export. It mainly focuses on the situational analysis of a country or a region, with more analysis of the Asian region [22,23]. The significant influencing factors obtained are not the same. It is generally believed that GDP, population, renewable energy consumption, renewable energy complementarity, policy adjustments, market demand, tariff conditions, and other factors have a greater effect [21,24,25].

In summary, the research on related issues mainly adopts two empirical methods. The first is the systematic network analysis method. Specifically, by analyzing the complex network system composed of multinational nodes, the role of each country in the system is studied to promote the formation of a multi-polar trade pattern [26,27]. For example, by using the network analysis method, it is found that there is a dynamic competitive relationship in the coal trade, where the coal competition network has changed from a core-periphery structure to a network structure, with competition intensity of the coal trade continuing to rise [28,29]. Inter-regional natural gas trade links continue to deepen, and the development of the liquefied natural gas trade is faster than that of the pipeline natural gas trade. The integration of the international natural gas market and inter-regional liquefied natural gas trade is highly correlated and mutually influential [30,31,32]. The second method is the trade gravity model. This model mainly explores the potential of inter-regional energy trade cooperation [33,34,35] and analyzes the influencing factors of energy trade [36]. For example, through the establishment of the trade gravity model, the potential of natural gas trade between China and Russia is empirically analyzed [33]. Based on the analysis model of China–EU green trade cooperation potential (i.e., the trade gravity model), the development direction of China–EU green energy trade is analyzed. Using the trade gravity model, the host country’s GDP, commodity trade conditions, population size, and exchange rate affect the export of new energy vehicles [36]. An in-depth analysis of the important factors influencing the energy trade between China and Indonesia shows that energy imports are mainly determined by each other’s trade environment and energy complementarity [15]. Based on the above comparison, it is found that the analysis of the influencing factors of regional energy trade is mostly based on the trade gravity model, which is also the main method of this paper’s follow-up research.

All in all, all members of the RCEP have promised to reduce tariffs and standard barriers, which is conducive to strengthening regional trade cooperation, which is also applicable to energy trade. At the same time, according to the current research status, the academic community has launched a heated discussion on the issue of regional energy trade. Most are analyses of a single global energy trading network, with relatively few studies addressing the regional scope of RCEP. However, most of the existing research on RCEP regional issues is to analyze a series of issues, such as the prospect and impact of economic trade [37,38] or the complementarity and influencing factors of fossil energy trade. However, these studies do not compare fossil energy trade with renewable energy trade within a research system. Based on this, with reference to previous studies, this paper makes the following contributions to the related research of regional energy cooperation: (1) The theory of comparative advantage is introduced into the field of energy trade. At present, the RCA index is one of the most widely used indexes to measure global and domestic product trade [39,40]. According to the comparative advantages of energy trade in various countries, the trade cooperation advantages of RCEP countries are analyzed by means of the RCA index and trade complementarity index. (2) It breaks through the research limitations of focusing on a single energy source and a single region by conducting a comparative analysis of the trade of three kinds of fossil energy and six kinds of renewable energy in RCEP countries, which enriches the research dimension of energy trade. (3) Based on whether to propose a detailed plan for carbon neutrality targets, this paper further analyzes how the carbon neutrality targets shape the energy trade impact pattern between China and RCEP countries. In this way, the best measures for energy trade cooperation are sought.

3. Advantages of Energy Trade Cooperation

Energy trade between RCEP countries is still an important part of regional economic and trade integration. In any case, regional energy trade and cooperation have certain prospects. Based on this, first of all, it is necessary to analyze the external dependence of national energy products from the actual trade situation of the region to explore the basic conditions of cooperation. Secondly, with the help of the RCA index and the TCI, this paper analyzes the international market competitiveness of energy and the complementarity of energy trade to encourage countries to choose appropriate energy trade partners.

3.1. Regional Energy Consumption and Trade Status

As far as fossil energy is concerned, the BP World Energy Statistics Yearbook 2024 shows that China has consistently ranked first in consumption in the Asia-Pacific region. The consumption of oil and natural gas is higher than production, and both depend on imports. In 2023, China’s oil imports increased by 13%, natural gas imports increased by 9.4% [41], and coal production exceeded consumption. The production of fossil energy in ASEAN countries exceeds consumption. Indonesia is rich in coal and natural gas resources, and oil is dependent on imports. Japan and the Republic of Korea are relatively deficient in energy resources, and fossil energy is dependent on imports, of which Japan imports $ 1690.27 billion in 2023. Australia is a major energy producer, and its export ranks third in the world. In 2023, the growth rate of coal production was 3.6%, and the natural gas production was 153.5 billion cubic meters. China had become the world’s largest importer of liquid natural gas by 2023, with one-third of its imports coming from Australia due to its strong demand for fossil energy. In addition, according to United Nations Statistics (UNCTAD), 96% of New Zealand’s trade volume in 2023 came from countries in the RCEP region, followed by ASEAN (49.8%), Australia (41.5%), Japan (38.6%), and China (15.7%).

In terms of renewable energy, China (27.49 AJ) accounts for the largest share of the total consumption of renewable energy (including hydropower) in the Asia-Pacific region, which is 68.5%, and the annual growth rate is 8.0%. Following China, the major consumers of renewable energy in the region are Japan (2.19 AJ, 5.4%), Vietnam (1.11 AJ, 2.8%), Indonesia (1.06 AJ, 2.6%), Australia (0.90 AJ, 2.2%), and the Republic of Korea (0.59 AJ, 1.5%). Among various types of energy, solar energy consumption is the largest. China (5.46 AJ) accounts for the largest share of total consumption in the Asia-Pacific region, which is 63.0%, and the annual growth rate is 36.2%. It is followed by Japan (0.9, 6.1%), Australia (0.42, 19.4%), Vietnam (0.24, −0.5%), and the Republic of Korea (0.27, −4.8%). Compared with other countries, China has the largest consumption of solar energy, wind energy, geothermal energy, and biomass energy, followed by Japan. In addition, considering the renewable energy trade volume of each country, 62.3% of Australia’s solar energy trade volume in 2023 came from RCEP countries, followed by ASEAN (61.7%), Japan (61.5%), New Zealand (51.9%), and China (30.5%). Among the trade volume of wind energy, ASEAN has the largest number of countries in the RCEP region as trade options, accounting for 55.4% of the total trade volume of ASEAN, followed by Japan (51.5%), New Zealand (50.1%), Australia (45.2%), and China (28.1%). Among the geothermal energy trade volume, Australia is the country with the most trade options in the RCEP region, accounting for 57.3%, followed by ASEAN (51.6%), Japan (50.1%), New Zealand (39.6%), and China (26.7%). Among the trade volume of biomass energy, 51.4% of ASEAN trade volume comes from RCEP region countries, followed by New Zealand (47.3%), Japan (47.1%), China (39.6%), and Australia (37.3%) [41].

In summary, the demand for fossil energy in RCEP countries is still large, and the consumption of renewable energy is also increasing. At the same time, the trade volume of fossil energy between regions is dominant, and the trade of renewable energy is becoming more and more frequent. Therefore, the trade cooperation between RCEP countries has a certain foundation. Next, we will further analyze the advantages of China’s inter-regional energy trade cooperation from the perspective of competitiveness and complementarity.

3.2. Comparative Advantage of Energy Trade

From the perspective of the RCA index, an RCA index >2.5 usually indicates that the country’s products have the highest international competitiveness, 1.25 ≤ RCA ≤ 2.5 indicates that the country’s products have stronger international competitiveness, 0.8 ≤ RCA ≤ 1.25 indicates that the country’s products have strong international competitiveness, and an RCA < 0.8 indicates that the country’s international competitiveness of such products is weak. As shown in

Table 1. The average value of revealed comparative advantage of energy trade from 2011 to 2023.

	CHN	JPN	KOR	ASEN	NZL	AUS
Coal	0.07	0.00	0.00	2.73	0.09	27.66
Oil	0.01	0.00	0.00	0.31	0.33	0.52
Natural gas	0.04	0.00	0.00	1.82	0.08	7.40
Geothermal	1.04	1.53	1.49	0.33	0.20	0.12
Ocean energy	1.07	0.62	1.33	0.54	0.39	0.09
Solar	2.56	1.34	2.85	1.01	0.30	0.08
Wind power	1.13	2.12	0.82	0.87	0.28	0.18
Hydraulic power	1.31	0.53	1.10	0.59	0.47	0.11
Bioenergy	0.60	1.89	1.58	0.54	0.19	0.20

Note: The data are from the UN Comtrade statistical database [42].

, RCEP countries have strong international competitiveness in energy, especially renewable energy. Among them, solar energy has the strongest comparative advantage (four countries with an RCA index greater than 1, with a maximum value of 2.85, indicating strong international competitiveness), followed by geothermal energy (three countries with an RCA index greater than 1, with a maximum value of 1.53, indicating strong international competitiveness), biomass energy (two countries with an RCA index greater than 1, with a maximum value of 1.89, indicating strong international competitiveness). In terms of specific national conditions, Australian coal has strong international competitiveness (the RCA index is far more than 20). The RCA index of coal, natural gas, and solar energy in ASEAN countries is greater than 1, and the competitiveness is decreasing. The international competitiveness of renewable energy in China, Japan, and the Republic of Korea is stronger than that of traditional energy. In addition to biomass energy, China’s RCA index is greater than 1, indicating that solar energy has strong international competitiveness, water energy has strong competitiveness, and surplus energy has strong competitiveness. The RCA index of the Republic of Korea is greater than 1, except for wind energy. Solar energy also has strong international competitiveness, hydropower has strong competitiveness, and remaining energy has strong competitiveness. On the whole, RCEP countries have varying comparative advantages across different energy products, which provides a good foundation for energy trade cooperation.

3.3. Energy Trade Complementarity

Based on the above comparative advantage analysis, the complementarity of energy trade in RCEP countries can be further studied. According to the advantages and disadvantages of a product in different countries, when a product has a greater comparative advantage in the exporting country and a greater comparative disadvantage in the importing country, the trade complementarity of that product between the two countries is strong. Therefore, the trade complementarity index (TCI) proposed by Drysdale (1967) [43] is used for reference, and the specific calculation formula is as follows:

$${\mathrm{TCI}}_{\mathrm{ij}}^{\mathrm{k}}={\mathrm{RCA}}_{xi}^{\mathrm{k}}\ast {\mathrm{RCA}}_{\mathrm{mj}}^{\mathrm{k}}.$$

(1)

In the above formula, k is the product, and i and j are the countries. If the TCI > 1, it shows that the trade complementarity between the two countries is strong, and the greater the value, the stronger the complementarity; if the TCI < 1, the trade complementarity between the two countries is weak, and the smaller the value, the weaker the complementarity. This paper calculates the energy trade complementarity index of RCEP countries from 2011 to 2023, and the results are shown in

Table 2. TCI index (mean) of energy trade between China (export) and RCEP from 2011 to 2023.

	Coal	Oil	Natural Gas	Geothermal	Ocean Energy	Solar	Wind Power	Hydraulic Power	Bioenergy
AUS	0.00	0.01	0.00	1.96	1.63	3.11	1.38	1.53	0.76
KOR	0.27	0.02	0.11	0.85	0.32	3.48	1.36	1.16	0.73
JPN	0.31	0.02	0.15	0.58	0.38	2.66	0.75	0.68	0.41
NZL	0.00	0.01	0.00	0.84	1.37	1.41	0.90	1.51	0.46
ASEN	0.05	0.01	0.02	0.98	1.12	2.40	1.39	1.55	0.63

Note: The data are from the UN Comtrade statistical database [42].

below.

Taking China as an exporter, on the annual average, the TCI values of China’s exports and RCEP imports from 2011 to 2023 are both greater than 0, but the complementary strength is not high. In terms of energy types, the complementarity of renewable energy is stronger than that of traditional energy. Among them, solar energy has the strongest complementarity (all TCI values are greater than 1), with a maximum value of 3.48. It is followed by hydropower (China’s bilateral trade TCI value with four countries exceeds 1, with a maximum value of 1.55), ocean energy (China’s bilateral trade TCI value with three countries exceeds 1, with a maximum value of 1.63), and wind energy (China’s bilateral trade TCI value with three countries exceeds 1, with a maximum value of 1.39). As far as countries are concerned, China and Australia have the strongest energy complementarity, followed by ASEAN countries, while China and Japan have the worst energy complementarity.

Taking China as the importing country (see

Table 3. TCI index (mean) of energy trade between China (import) and RCEP from 2011 to 2023.

	Coal	Oil	Natural Gas	Geothermal	Ocean Energy	Solar	Wind Power	Hydraulic Power	Bioenergy
AUS	39.36	0.91	7.87	0.08	0.05	0.15	0.19	0.05	0.23
KOR	0.00	0.00	0.00	0.92	0.65	6.73	0.82	0.44	1.74
JPN	0.00	0.00	0.00	0.92	0.31	2.85	2.16	0.22	2.13
NZL	0.13	0.55	0.09	0.12	0.22	0.54	0.31	0.18	0.22
ASEN	3.97	0.52	1.58	0.20	0.26	1.94	0.88	0.22	0.60

Note: The data are from the UN Comtrade statistical database [42].

), on the annual average, the TCI values of China’s imports and RCEP exports from 2011 to 2023 are both greater than 0, but the complementary strength is quite different. In terms of energy types, the complementarity of traditional energy is stronger than that of renewable energy. Among them, coal is the most complementary, with a maximum value of more than 30, followed by natural gas (a maximum value of 7.87). Although the TCI of solar energy exceeds 1 in three countries, the complementarity intensity is not high (a maximum value of 6.72). As far as countries are concerned, China and Australia have the strongest energy complementarity, followed by ASEAN countries, while China and New Zealand have the worst energy complementarity.

Based on the above analysis, China mainly relies on imports for fossil energy, while it mainly focuses on exports for renewable energy. The complementarity of traditional energy is stronger. Although there are more countries with TCI values greater than 1 in bilateral trade of renewable energy, they are obviously smaller and less complementary. China and Australia have the strongest energy complementarity, followed by ASEAN countries. Based on the actual data and various indexes, the trade cooperation between China and RCEP countries has a certain foundation, and the complementarity of energy trade is strong, indicating that the advantages of energy trade cooperation between China and the region are also strong. Furthermore, it is found that both energy trade competition and energy trade complementarity affect regional energy trade cooperation. Based on this, in order to promote RCEP regional energy trade cooperation, it is necessary to explore the influencing factors behind it to seek effective ways of energy cooperation.

4. Materials and Methods

4.1. Method

At present, the trade gravity model is commonly used to explain international trade issues, such as the impact and development of trade cooperation. It is believed that the occurrence of trade is related to many factors, such as the level of economic development, market demand, distance, terms of trade, and so on. Based on this, this paper expands the Linnemann trade gravity model by introducing relevant variables and constructs the trade gravity model between China and RCEP countries to explore the specific factors affecting the energy trade between China and RCEP countries. The specific model is as follows:

$$LN{T}_{nit}={\alpha }_0+{\alpha }_{1}LNGD{P}_{it}+{\alpha }_{2}LNGD{P}_{jt}+{\alpha }_{3}LND{D}_{it}+{\alpha }_{3}LN{Z}_{it}+{\epsilon }_{it},$$

(2)

where T_nit represents the energy trade volume between China and the ith RCEP country; n = 1 (fossil energy), 2 (renewable energy); Z_it = (PP_it, TCI_it, EF_it, TE_it, EX_it, TL_it); and DD_it is the trade distance.

4.2. Variables Declaration

The panel data of RCEP countries (excluding Laos and Cambodia) from 2011 to 2023 are selected, and the missing data are supplemented using the linear interpolation method. The explanatory variable is the trade volume of two types of energy between China and RCEP countries. According to the SITC coding standard, it is divided into traditional fossil energy (coal, oil, natural gas) trade and renewable energy (solar energy, geothermal energy, etc.) trade. The specific variables and data information are shown in

Table 4. Variables.

Variables	Explanation
Energy trade	The total energy trade volume Tit between China and RCEP countries is divided into traditional energy Tit (fossil) and renewable energy Tit (renewable) [42].
GDPit	Economic development requires energy input, and with the rapid development of the economy, energy demand is increasing day by day, which in turn promotes the development of energy trade. This is represented by GDP [44].
PPit	The larger the population of a country, the stronger the productivity and the greater the energy demand, thus promoting the development of the energy trade industry. Here is the total annual population [44].
TCIit	The complementary relationship between bilateral energy import and export trade can reflect the development prospects of the two countries. According to the previous article, the greater the complementary index, the more opportunities for energy trade cooperation [42].
DDit	Distance affects trade costs and leads to changes in trade volume. However, because the distance does not change with time, it will lead to collinearity problems. In view of this, referring to the research of Jiang Guanhong et al. (2012) [45], the interaction term between international crude oil prices and geographical distance is used [46,47].
EFit	The higher the level of liberalization of a country’s economy, the more frequent the import and export trade activities, and the greater the scale of trade. It is expressed by the economic freedom index [48].
TEit	The better the trade environment (including political stability, investment environment, financial risks, etc.), the more conducive it is for import and export trade. Here, it is expressed by the international Country risk Guide (ICRG) comprehensive risk level [49].
EXit	The higher a country’s exchange rate and currency appreciation, the more conducive it is to the country’s imports but less conducive to exports. Here, the bilateral exchange rate of the RMB against the currencies of RCEP countries is expressed using the indirect pricing method [44].
TLit	The stronger a country’s technological capacity, the more fully its energy resources can be developed, making energy exports more conducive and thus leading to a more prosperous energy trade market. Here, high-tech exports are used as a representation [44].

below.

5. Results

5.1. Analysis Preparation

5.1.1. Descriptive Statistics and Multicollinearity Analysis

According to the following

Table 5. Descriptive statistics and multicollinearity results.

	Mean	S.td	Max	Min	VIF
Tit (fossil)	12.57	6.34	24.49	0.00
Tit (renewable)	10.45	4.55	19.88	0.01
GDPit	6.79	1.54	3.74	9.38	3.72
GDPjt	8.98	1.02	7.89	4.39	4.55
PPit	16.98	1.79	12.85	19.43	2.57
TCIit	0.68	0.79	1.26	−4.67	1.29
DDit	9.38	2.38	13.16	11.421	2.12
EFit	3.89	0.55	4.33	5.48	1.34
TEit	0.95	0.37	3.41	1.33	0.99
EXit	0.75	0.19	1.59	0.50	1.24
TLit	0.66	0.17	1.07	0.35	1.76

Note: After the logarithm, the mean value of VIF is 2.18.

, the mean values of variables such as economic development (GDP), population size (PP), trade distance (DD), economic liberalization (EF), trade environment (TE), exchange rate level (EX), and technological level (TL) are greater than the standard deviation, indicating that the data are more concentrated and less volatile. Although the standard deviation of the trade complementary TCI is greater than the mean, the difference between the two is not large, indicating that the data have certain volatility. Through further VIF testing, it can be seen that the VIF values of all variables do not exceed 10, with an average value of 2.18, indicating that there is no possibility of multicollinearity among the variables, so the next regression analysis can be carried out.

5.1.2. Model Test

Before conducting empirical analysis, it is necessary to determine the specific model form (random, fixed, or mixed effect). The LM test is used to detect whether there is an autocorrelation problem in the regression model to ensure the accuracy of the regression results. Firstly, according to the purpose of this study, the original model is set, and the parameters are estimated. Then, the auxiliary regression model is constructed, and the residual or other related variables of the original model are used as the explanatory variables, and the possible sequence correlation or heteroscedasticity variables are used as explanatory variables. Then, the auxiliary regression model is analyzed to obtain the LM statistic. Finally, the LM test and Hausman test are conducted separately. Among them, the LM test is a hypothesis testing by determining the level of significance based on the distribution and critical value of the LM statistic. The Hausman test compares the parameter estimates of the model to determine whether the model hypothesis is valid and to decide whether to adopt the fixed effect model, the random effect model, or the mixed effect model. The results in

Table 6. Model selection.

Model 1 (Fossil Energy)	Statistic	Model 2 (Renewable Energy)	Statistic
LM	420.75 ***	LM	147.97 ***
Hausman	38.33 *	Hausman	24.48 **

Note: ***, **, and * are significant at the level of 1%, 5%, and 10%, respectively.

showed that the LM test statistic is significant at 1%, and the Hausman test statistic rejects the null hypothesis at a significant level of 10%. Finally, the fixed effect model should be selected.

5.2. Benchmark Regression Results

The first model (n = 1; that is, fossil energy is the explained variable) analyzes the main factors influencing China’s fossil energy trade with RCEP countries. According to the results in

Table 7. Benchmark regression results.

	Model 1 (Fossil Energy)	T	Model 2 (Renewable Energy)	T
CHN GDPit	1.68 *	1.91	1.17	0.54
Rest GDPjt	−0.50	−0.66	2.51 **	2.01
PPit	−0.18	−0.52	−0.80	−1.80
TCIit	0.39 ***	2.52	2.31 ***	6.31
DDit	−0.71	0.39	0.30	0.45
EFit	2. 77 ***	17.94	4.61 **	4.63
TEit	4.28 ***	4.33	1.53 *	1.92
EXit	−1.16	−1.47	−1.45 *	−1.85
TLit	0.18 *	1.92	0.24 ***	4.94
Fixed effect	Yes		Yes
R2	0.88		0.74
Rho	0.87		0.92

Note: Use the individual-time two-way fixed effect model; ***, **, and * are significant at the level of 1%, 5%, and 10%, respectively.

, China’s GDP, trade complementarity index, economic liberalization, trade environment, and technological level have significant effects, and other factors are not significant. The significant influence coefficient of GDP is significantly positive, which indicates that with the development of China’s economy, energy demand is increasing, which promotes the development of China’s energy trade. The significant influence coefficient of the trade complementarity index is significantly positive, indicating that the trade complementarity index changes by 1%, and the trade changes by 39%. The higher the degree of liberalization of regional economies and the better the trade environment, the more frequent the fossil energy trade. The significant influence coefficient of the technological level is significantly positive, indicating that the technological level is increased by 1%, the energy demand is the largest, and the trade volume is increased by 18%. The results of population factors, exchange rate conditions, and geographical distance are not significant. Therefore, to promote China’s fossil energy trade with RCEP countries, cooperation should focus on improving regional economic strength, trade environment, economic openness, and technological level.

The second model (n = 2; that is, renewable energy is the explained variable) analyzes the main factors influencing China’s renewable energy trade with RCEP countries. The concludes (see Table 7) that regional trade is related to the GDP, the trade complementarity index, economic liberalization, the trade environment, the exchange rate level, the technological level, and other factors of RCEP sample countries, but not to population or geographical distance. Among them, the influence coefficients of economic freedom, GDP, and the trade complementarity index of RCEP sample countries are significantly positive. The exchange rate index has a negative impact, indicating that an increase in the exchange rate level leads to a decline in the trade volume of renewable energy. On the whole, the changes in energy trade between China and RCEP countries are mainly affected by regional economic factors, technical factors, and energy complementarity. In order to promote RCEP regional energy export trade, multi-party cooperation is needed, and China’s efforts alone are far from enough.

In short, with the growth of the national economy, energy consumption will also increase, which reflects the more active international trade activities. Therefore, China is committed to promoting and participating in various forms of energy transactions to obtain the important resources it needs. In contrast, some regions have limited demand for energy and are more suitable for exporting energy products. Moreover, given the low gross domestic product (GDP) of most RCEP signatories, China can further boost the expansion of energy trade by forging friendly alliances. It is worth noting that most of the RCEP member countries are located in the surrounding areas of China, and pipeline transportation is also expanding rapidly, making logistics costs dwarf the benefits obtained, which is not a great obstacle to China’s energy cooperation with other countries. Countries with high dependence on foreign trade have a stronger demand for energy trade, and energy trade is correspondingly more frequent. Economic freedom reflects the degree of openness of the country and has a positive impact on trade. Most of the countries in the RCEP agreement have a high level of economic freedom, which is conducive to the development of energy trade between China and them.

5.3. Robustness

In order to verify the robustness of the above benchmark regression results, this paper refers to the practice of Chen et al. (2020) [50] and shrinks the total trade volume of fossil energy and renewable energy (at the 1% quantile). The results in the

Table 8. Robustness results.

	Model 1 (Fossil Energy)	T	Model 2 (Renewable Energy)	T
CHN GDPit	2.67 *	1.93	0.13	0.59
RestGDPjt	−0.89	−0.69	1.52 **	2.03
PPit	−0.14	−0.50	−0.71	−1.42
TCIit	0.47 ***	12.52	4.31 ***	8.30
DDit	−0.78	0.33	0.32	0.44
EFit	1.76 ***	10.90	6.61 **	3.63
TEit	2.28 ***	6.36	1.58 ***	9.09
EXit	−1.16	−1.47	−1.19 *	−1.85
TLit	0.17 ***	6.53	0.18 ***	8.94
Fixed effect	Yes		Yes
R2	0.84		0.64
Rho	0.95		0.96

Note: ***, **, and * are significant at the level of 1%, 5%, and 10%, respectively.

show that the coefficients of each variable have changed, but the positive and negative directions and their significance have not changed, indicating that the previous model analysis is robust and the conclusions are credible.

5.4. Heterogeneity

In view of the fact that the carbon neutrality target puts forward higher requirements for the development of the energy sector, regional energy trade cooperation needs to consider whether the carbon neutrality target has an impact. For example, achieving the goal of carbon neutrality requires optimizing the energy industrial structure, reducing fossil energy consumption, and increasing the proportion of renewable energy consumption to promote the coordinated development of renewable energy and traditional fossil energy and then promote the development of regional energy trade [51,52]. Based on this, this paper further analyzes the carbon neutrality goal and how to shape the energy trade impact pattern between China and RCEP countries. Specifically, heterogeneity analysis is performed based on whether to propose a detailed plan for carbon neutrality goals (hereinafter referred to as detailed planning). According to Net Zero Tracker, New Zealand and Australia have completed detailed planning, while China, Japan, the Republic of Korea, and ASEAN countries have not yet completed research.

Compared with the benchmark regression, among the main influencing factors of fossil energy trade in countries that have completed detailed planning, the effect of GDP is more significant, which can promote regional energy trade to a greater extent. The impact coefficient of the TCI index, the impact coefficient of economic liberalization, the impact coefficient of the trade environment, and the impact coefficient of technological level are all larger, and the impact on energy trade is correspondingly higher. Among the main influencing factors of renewable energy trade, the impact of China’s GDP has become significant, and the impact of trade complementarity index, economic liberalization, trade environment, technical level and other factors is higher, but the impact of exchange rate level is not significant. Among the main influencing factors of fossil energy trade in countries that have not completed detailed planning, China’s GDP and economic liberalization have a greater impact, while TCI index, trade environment and technical level have a weaker impact. Among the main influencing factors of renewable energy trade, the impact of China’s GDP has become significant, the impact of RCEP sample countries’ GDP has become smaller, the impact of economic liberalization has become stronger, the impact of TCI index and trade environment has become weaker, and the impact of exchange rate level is not significant. Specific results are shown in

Table 9. Heterogeneity results.

	Model 1 ①	T	Model 2①	T	Model 1 ②	T	Model 2 ②	T
GDPit	3.08 **	2.11	2.22 *	1.97	2.08 *	1.94	0.17 *	1.83
GDPjt	1.50 *	1.95	4.50 ***	3.31	−0.90	−0.96	2.01 *	1.89
PPit	−1.18	−0.92	−6.81	−1.00	−3.14	−0.72	−0.76	−0.80
TCIit	0.89 ***	2.92	3.31 ***	6.01	0.19∗	1.93	1.93 ***	5.31
DDit	−1.81	0.68	3.30	0.95	−0.79	0.88	4.43	0.55
EFit	3.27 ***	10.94	6.60 ***	14.60	3.07 **	2.22	5.76 *	1.90
TEit	6.08 ***	6.33	3.53 **	1.93	3.88 *	1.96	0.93 *	1.88
EXit	−1.16	−1.47	−1.15	−1.05	−5.16	−6.47	1.05	1.05
TLit	0.98 **	2.22	1.04 ***	7.94	0.57 ***	6.92	0.84 ***	11.04
Fixed	Yes		Yes		Yes		Yes
R2	0.77		0.69		0.58		0.80
Rho	0.85		0.86		0.90		0.84

Note: ① for countries that have proposed detailed plans, ② for countries that have not proposed detailed plans; ***, **, and * are significant at the level of 1%, 5%, and 10%, respectively.

.

In contrast, whether it is fossil energy or renewable energy, when completing the detailed planning of carbon neutrality targets, the significant factors have a stronger effect on trade, and the improvement of relevant factors can better promote energy trade. It shows that the detailed planning objectives put forward specific requirements for energy development, and the earlier energy structure optimization can be realized, the better the energy trade structure can be improved and the development of energy trade can be promoted.

6. Conclusions

In view of the fact that RCEP countries are important partners in China’s energy trade cooperation, this paper takes inter-regional energy trade cooperation as the starting point, analyzes in depth the differences in energy consumption and trade status, and then explains the complementary advantages of various types of energy trade in RCEP countries. Finally, the trade gravity model is used to explore the important factors affecting energy trade and seek the best measures for energy trade cooperation.

The following conclusions are drawn: (1) The demand for fossil energy in RCEP countries is still large, and the consumption of renewable energy is also increasing. At the same time, the trade volume of fossil energy between regions is dominant, and the trade of renewable energy is becoming more and more frequent. (2) RCEP countries have different comparative advantages among different energy products, which provides a good foundation for energy trade cooperation. (3) For fossil energy, China primarily relies on imports, while for renewable energy, it mainly focuses on exports. The complementarity of traditional energy is stronger. Although there are more countries with TCI values greater than 1 in bilateral trade of renewable energy, they are obviously smaller and less complementary. China and Australia have the strongest energy complementarity, followed by ASEAN countries. (4) On the whole, GDP, the trade complementarity index, economic liberalization, the trade environment, and the technological level can effectively affect fossil energy trade and renewable energy trade. Population and geographical distance have nothing to do with energy trade. The effect of the exchange rate level on the two types of energy trade is inconsistent. (5) Whether it is fossil energy or renewable energy, when completing the detailed planning of carbon neutrality targets, significant factors have a stronger effect on trade, and the improvement of relevant factors can better promote energy trade.

In any case, in view of the fact that many factors and data limitations make it impossible to accurately assess the specific influence of some factors on energy trade between China and RCEP countries, this paper does not discuss the comparison of these factors in depth but analyzes how they play a role in the transaction process from an overall perspective, which makes the research scope and depth of this paper slightly insufficient. Therefore, in the future, we should adopt a variety of quantitative empirical methods to analyze the specific value range of the factors that promote energy trade to explore the best way to realize the energy trade cooperation between China and RCEP countries.

The scale of energy trade between China and RCEP countries is growing, and the volume of bilateral trade is gradually increasing. In the process of this rapid growth, there are also some problems and negative effects.

Firstly, it is necessary to strengthen communication on energy policies among RCEP member countries and encourage industrial cooperation in the field of regional energy. Furthermore, a reduction in non-tariff trade barriers should be explored. (According to the previous research, non-tariff factors, such as technology and exchange rates, have a significant impact on trade, so trade cooperation needs to take technical measures—see below.) Enhancing energy trade interconnection will help expand economic freedom and openness, accelerate the implementation of relevant tariff policies under the agreement, strive to improve customs clearance efficiency, and reduce time costs. Secondly, energy technology is the basis for strengthening international cooperation, and it is necessary to promote core energy technology. This study found that improvements in technological levels will force adjustments in the energy structure, which, in turn, will affect regional energy trade. Thirdly, starting from the actual needs of energy partners and in accordance with local conditions, precise energy docking cooperation should be achieved, and an RCEP energy cooperation demonstration zone should be established. For example, in-depth cooperation should be pursued in specific energy categories such as crude oil, liquefied natural gas (LNG), and energy chemicals such as light cycle oil (LCO). At the same time, China should coordinate the integration and complementarity of traditional energy and renewable energy to expand energy cooperation. Finally, it is necessary to clarify the carbon-neutral target planning and set up a clear route and target supervision mechanism. Otherwise, due to the lack of a clear policy mechanism and a perfect target supervision and accountability mechanism, many countries’ carbon neutrality goals will fail in the future [50], which will affect the progress of regional energy trade. The vast majority of the current RCEP countries that have proposed carbon neutrality targets have made slow progress, and the region’s demand for fossil energy and trade volume dominate. In this regard, drawing on the detailed planning of New Zealand and Australia, we will focus on improving measures in the energy sector.