Who will build new trade relations? Finding potential relations in international liquefied natural gas trade

Accepted Manuscript Who will build new trade relations? Finding potential relations in international liquefied natural gas trade

Sida Feng, Huajiao Li, Yabin Qi, Qing Guan, Shaobo Wen PII:

S0360-5442(17)31551-7

DOI:

10.1016/j.energy.2017.09.030

Reference:

EGY 11524

To appear in:

Energy

Received Date:

31 January 2017

Revised Date:

01 June 2017

Accepted Date:

07 September 2017

Please cite this article as: Sida Feng, Huajiao Li, Yabin Qi, Qing Guan, Shaobo Wen, Who will build new trade relations? Finding potential relations in international liquefied natural gas trade, Energy (2017), doi: 10.1016/j.energy.2017.09.030

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ACCEPTED MANUSCRIPT The study aims to find potential trade relations in international liquefied natural gas trade.  A method combing link prediction and trade rules is proposed to find potential links.  Countries with more trade partners are more likely to build new trade relations.  Countries tend to trade liquefied natural gas with familiar trade partners.  The trade role of a country effects the formation of new trade relations. 

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Who will build new trade relations? Finding potential relations in international liquefied natural gas trade Sida Fenga, Huajiao Lia,b,c,*, Yabin Qia,d, Qing Guana,e, Shaobo Wena a School of Humanities and Economic Management, China University of Geosciences, Beijing, China b Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing, China c Lab of Resources and Environmental Management, China University of Geosciences, Beijing, China d Chinese Academy of Geological Sciences, Beijing, China e Energy Systems Division, Argonne National Laboratory, Argonne, USA Abstract: Liquefied natural gas（LNG） trade has contributed to de-regionalizing and integrating the total natural gas market with its advantage of flexibility in delivery.. While because of this feature, the international trade of LNG is more changeable. Finding potential links in changeable international LNG trade can help the government quickly find a new partner when facing a sudden breakdown of trade relation or an urgent situation to diversify the trade partners. Moreover, the government could adjust its energy strategy in advance by estimating the potential trade relations of present partners. In this study, we find potential trade relations in international LNG trade by combining the trade motivation underlying in the network structure with rules explored from the LNG international trade. The findings are as follows: In the next five years, there is a very high possibility that India, Spain, Netherlands and Singapore will import LNG from USA, and there is a high possibility that Italy will import LNG from the USA. UK may export LNG to Japan and France is likely to export LNG to Rep of Korea. Suggestions about LNG trade according to the findings are offered to governments. Keywords: liquefied natural gas; international trade; potential trade links; link prediction

1. Introduction With the advantage of flexibility in delivery, liquefied natural gas（LNG） trade has contributed to de-regionalizing and integrating the total natural gas market [1,2]. In recent years, the trade of LNG is becoming more flexible. The proportion of LNG that is traded on a spot or short-term basis becomes higher. In 2010, the proportion was only 18.9%, while in 2015, it was 28% [3]. On the one hand, because of this feature, LNG Corresponding author. No.313, 4th Building, No. 29, Xueyuan Road, Beijing, 100083, China. E-mail address: [email protected] (H. Li). *

ACCEPTED MANUSCRIPT international trade is changeable and the trade relation is more venerable. For importers, this means the supply sources are not always reliable, which may threaten energy security [4,5]; for exporters, this means the demand is not always constant, which may decrease sale quantity and affect the economy [6]. On the other hand, due to its flexibility, LNG is an optimal choice for countries who urgently wants to diversify trade partners .Therefore, finding potential LNG trade links, or LNG trade relations that two countries have a high possibility to form, is of great practical significance. This can help the government quickly find a new partner when facing a sudden breakdown of trade relation or an urgent situation to diversify the trade partners. Moreover, because LNG trade is changeable, countries need to monitor the LNG market. For example, as for an exporter, if one of its major trade partners in natural gas builds a new trade relation and imports much LNG from another exporter, the exporter’s exports are likely to reduce, and its income from natural gas may be affected. By estimating the potential trade relations of present partners, the government could estimate the potential trade of their partners and adjust its energy strategy in advance. Based on the above, this study explores potential trade links in LNG trade. Most of the researches on estimating potential trade among countries by applying traditional gravity model method [7].This method has been used to study the potential trade flows of one kind of product such as forest products [8,9] and agricultural products [10], or the potential general trade relations among countries and regions [11,12]. While these researches are focused on estimating the potential trade volumes of existent links in the future. Gravity model is based on the country-specific variables (GDP, population, etc.) and bilateral relation variables (distance, boundary conditions, etc.)[13], and it is a good model to predict the trade flows of existent trade links [14]. However, when it comes to evaluate whether an inexistent link will be present in the future, the validity of this model is not satisfactory, because the data that gravity model used are information about the countries such as GDP, distance, rather than the trade relation itself [14,15]. However，this study aim to find new partners for countries, so a new method need to be applied to find potential trade relations which are inexistent at present but may appear in the future. Link prediction, which is based on the topological of network, is a method to explore potential links in the future, which are inexistent at present. Thus, in this study, we constructed a LNG network by trade relations and apply link prediction to uncover the potential links in LNG trade. Link prediction is a network-based method that estimates new future linkages based on the structure of the present network by a suitable algorithm [16]. As an emerging method, most studies treat the innovation of algorithms. Similarity-based algorithms are the mainstream class in link prediction [17]. Common Neighbor (CN) and Adamic/Adar (AA) have been proven to be more effective than other algorithms to describe the motivation of networks [18]. The Resource Allocation (RA) index, proposed by Zhou (2009), has a better effect than CN and AA in the experiments [19]. The Preference Attachment (PA) index is widely applied to explore the functional implication of a relation in network dynamics [20, 21, 22]. In application, link prediction is used in criminal networks [23], interpersonal relationships [24, 25, 26] transportation [27,28] and biology [29]. Few studies apply it to international trade. The

ACCEPTED MANUSCRIPT international trade relations between countries can be described as a network [30,31]. Vidmer et al (2015) [32] predict countries’ possible export products using algorithms based on heat and mass diffusion processes. Tuninetti et al (2016) [33] explore major factors driving the formation of embodied water trade relations. Researchers have tried to assess potential trade relations in international crude oil [34], but there is only one prediction algorithm applied in the research, which may limit the understanding of linking motivation and prediction results. Selecting the optimal link prediction algorithm of a certain network from several algorithms can provide strong evidence of the corresponding mechanism of an international trade relation network and thereby offer a more accurate estimation result [35]. Moreover, unlike the relatively free form of the oil trade, the natural gas trade is influenced by the configuration of natural gas, so the trade of natural gas has its own features [36]. In this paper, we apply link prediction method and select the most optimal from four mainstream indexes to explore potential trade relations in international LNG trade. This paper explores the motivation of international LNG trade relation establishment and finds potential trade relations using the link prediction method. However, this method is only based on the topology of network. In order to make the evaluation more practical and accurate, we then proposed an international LNG trade analysis model to select the most potential trade links from the ones proposed by link prediction model. First, in the link prediction model, four widely used algorithms (CN, AA, RA and PA) are introduced, and an evaluation index is used to select the optimal algorithm. These algorithms explore the linking motivation from the view of topological structure, so the optimal one implies the structural motivation of international LNG trade. An additional parameter is introduced to examine the effect of trade partners with different trade volumes. Second, in the international LNG trade analysis model, the potential links proposed by the optimal algorithm are compared with the actual links to further confirm the validity of link prediction model and then the trade rules are explored by defining country roles to select the most potential trade links from the links proposed by link prediction method. In this study, Section 2 introduces the data and the link prediction algorithms used in the paper. Section 3 presents the process of finding potential links. Section 4 discusses and concludes.

2. Data and methodology 2.1 Data The annual import and export data of international LNG (HS code 271,111) trade from 2006 to 2015 were downloaded from the United Nations Statistics Division (https://comtrade.un.org/) on Nov. 9th, 2016. The data contain year, reporter, trade flow code (including import and export), partner and weight (kg). Partners whose codes do not represent a specific country are deleted. Relations in which the reporter and partner represent the same country are removed, and repeated trade relations are also deleted. When the trade volume reported by an exporter is different from the one reported by the importer, the larger volume is selected because the smaller volume may be caused

ACCEPTED MANUSCRIPT by omission. In addition, the production and consumption data of countries are acquired from BP Statistical Review of World Energy (June 2016). Figure 1 represents the trade relations under the circumstance of global natural gas usage in 2015. The links between countries indicate the LNG trade relations in 2015.And the color of the countries represent the consumptions of natural gas (LNG + pipeline). The more consumption a country has, the darker of its color is. The links between countries indicate the LNG trade relations in 2015.Japan，Rep. of Korea, China, India and Spain are the top five LNG importers in 2015. Algeria, Qatar, Nigeria, Malaysia and Australia are the top five LNG exporters in 2015. And the color of the countries represent the consumptions of natural gas (LNG+ pipeline). The more consumption a country has, the darker of its color is. As for importers, with the large amount of natural gas consumption, Asia is the biggest buyer of LNG. As for exporters, unlike traditional natural gas producers, Australia is an emerging LNG seller. USA and Russia are both countries with great consumption.

2.2 Methodology 2.2.1 Construction of the LNG trade network Based on complex network theory, the undirected weighted network of annual LNG trade is constructed. The nodes are the countries, and the edges are the existent LNG trade relations between each country pair. The weight of each edge represents the volume (kg) of trade. In this way, 10 networks are built. Figure 2 is the international LNG trade network of 2015. 2.2.2 Link prediction model Link prediction, which is based on a complex network, has been successfully applied in several papers about international trade [32,33]. In this paper, it is introduced to discover the structural motivation and find potential links in LNG trade. Figure 3 is a simple example of the link prediction process. The specific steps of this study are as follows: Step1: Choose indexes To explore the structural motivation of the LNG trade network, the most optimal algorithm needs to be selected. According to the review in Section 1, CN, AA, RA and PA are mainstream algorithms and have been proven valid in many networks, so they are used in this study. Moreover, in some networks, the weak links with small weight play a significant role in the forming of links, under the Weak Tie Theory [37], so emphasizing the contributions of weak links can remarkably enhance prediction accuracy [38]. Therefore, the parameter (α) is introduced to explore the contributions of trade volumes, which can both test the effect of trade partners with different volumes and avoid misjudgment of the optimal index caused by neglecting the effect of trade volume. Combined with LNG international trade and the definition of the index, a brief introduction of these indexes is given below: (1) Common Neighbor (CN). The CN index follows the idea that the more common direct trade partners that two nodes have, the more likely they will trade in the future.

ACCEPTED MANUSCRIPT The first formula is the unweighted algorithm, which takes no consideration of trade volume. The second is the algorithm considering the contributions of trade partners with different trade volumes. 𝑆𝐶𝑁 𝑥𝑦 = |Γ(𝑥)⋂Γ(𝑦)|

(1)

where x and y are two countries in the trade network. Γ(𝑥) represents the group of countries that has direct trade relations with x. Thus, |Γ(𝑥)⋂Γ(𝑦)| indicates the number of common direct trade partners between x and y. 𝑤(𝑥,𝑧) ∝ + 𝑤(𝑧,𝑦) ∝ 𝐶𝑁 𝑆 𝑥𝑦 = （2） 2

∑

𝑧 ∈ Γ(𝑥)⋂Γ(𝑦)

where z is a common trade partner of x and y. w(x, z) is the trade volume between x and z. α is a parameter controlling for the contribution trade volume. When α=0, the index converts to the unweighted case, in which the trade partners with different trade volumes play the same role. When α=1, the trade partners with larger trade volumes play stronger roles. When α=-1, the trade partners with smaller trade volumes play stronger roles. (2) Adamic/Adar (AA). If a common trade partner of two countries has more trade partners, it contributes less to connecting two nodes. 1 𝑆𝐴𝐴 （3） 𝑥𝑦 = log 𝑘𝑧

∑

𝑧 ∈ Γ(𝑥)⋂Γ(𝑦)

𝑤(𝑥,𝑧) ∝ + 𝑤(𝑧,𝑦) ∝ log (1 + 𝑆(𝑧))

∑

𝑆𝐴𝐴 𝑥𝑦 =

(4)

𝑧 ∈ Γ(𝑥)⋂Γ(𝑦)

where 𝑘𝑧 is the number of direct trade partners of z, and S(z) = ∑𝑗 ∈ Γ(𝑧)𝑤(𝑧,𝑗) ∝ . j belongs to the set of direct trade partners of z. (3) Resource Allocation (RA). Regarding the common trade partners as transmitters of resources, the RA index is similar to AA. 1 (5) 𝑆𝑅𝐴 𝑥𝑦 = 𝑘𝑧

∑

𝑧 ∈ Γ(𝑥)⋂Γ(𝑦)

∑

𝑆𝑅𝐴 𝑥𝑦 =

𝑧 ∈ Γ(𝑥)⋂Γ(𝑦)

𝑤(𝑥,𝑧) ∝ + 𝑤(𝑧,𝑦) ∝ 𝑆(𝑧)

(6)

(4) Preferential Attachment (PA). A country with more trade partners has a higher possibility to form new trade relations. 𝑆𝑃𝐴 𝑥𝑦 = |Γ(𝑥)| × |Γ(𝑦)| 𝑆𝑃𝐴 𝑥𝑦 =

∑ 𝑤(𝑥,𝑖) 𝑖 ∈ Γ(𝑥)

∝

×

(7)

∑ 𝑤(𝑦,𝑡) 𝑡 ∈ Γ(𝑦)

∝

(8)

ACCEPTED MANUSCRIPT where i is the direct trade partner of country x, and t is the direct trade partner of country y. Step 2: Randomly divide existent trade links into two parts. To evaluate the accuracy of the index, the group of existent trade links, represented by E, is divided into two sets. Ten percent of existent links are randomly selected to form the test set (ET), which are treated as samples for testing [17]. The rest of the links belong to the training set, which is represented by EP. E = EP + ET (9) T E = 10% ∗ E (10) Step3: Find the inexistent links The potential links are implied in the inexistent links, so the set of inexistent links needs to be found. Suppose there are n countries. The set of all possible trade links between them is U. The number of links in U can be calculated by formula (11). Thus, the number of inexistent links (EI) can be obtained by formula (12). n(n ‒ 1) U= (11) 2 (12) EI = U ‒ E Step4: Calculate and rank the scores of test links and inexistent links The scores of test links and inexistent links are calculated by one of the four indexes and then ranked in descending order according to their scores. Based on the definitions of indexes, the inexistent links with higher scores are more likely to form in the future. In this paper, four indexes are applied. Thus, for each trade network, the scores are calculated and ranked separately four times, once for each index. Step 5: Evaluate estimation accuracy of each index and find the most optimal one There are three criteria that can evaluate the accuracy of link prediction algorithms: Precision, Ranking Score and AUC. AUC evaluates the accuracy according to the entire rank list, while the others focus on only sectional information [17]. Considering that the aim of this paper is to explore the structural motivation of the whole network, AUC is applied to make the evaluation. AUC can be understood as the probability that the score of a randomly chosen test link is higher than a randomly chosen inexistent one. Independent comparisons are conducted n times. If the score of the test link is higher n’ time and the scores of two links are equal n’’ times, the AUC value is: 𝑛' + 0.5𝑛'' AUC = 𝑛

(13)

If all the scores are generated randomly, the AUC value should be approximately 0.5, and the value ranges from 0.5 to 1. The degree to which the value exceeds 0.5 indicates how much better the algorithm performs than coincidence [39]. To calculate the value of n, the most accurate way is to compare each test link with every inexistent one. Thus, the n in this paper equals to the number of test links multiplied

ACCEPTED MANUSCRIPT by the number of inexistent links, which is a rigorous method and avoids randomness. The optimal algorithm is the one with the highest AUC. 2.2.3 International LNG trade analysis model The link prediction model is only based on the topological structure of the trade network. Aiming to make more specific and practical prediction, the international LNG trade analysis model is constructed to link the physical topological features with the trade characteristics by testing the practical validity of link prediction model and finding trade rules of potential links proposed by the link prediction model. To achieve this goal, there are two steps in this model: Step1: Examine practical validity by comparing potential links with real links In order to examine the practical meaning of link prediction model, further validity test of the optimal algorithm based on the international LNG trade is conducted by comparing the top10 potential and real trade links from 2006 to 2014 .For example, if a potential link proposed by the optimal algorithm in 2006 does have trade relation in the recent coming years, the potential relation is fulfilled. Otherwise, it is unfulfilled. If most of the potential trade links are fulfilled in the following years, it can indicate that the optimal algorithm is not only theoretically but also practically valid. Besides，the aim of this study is to find potential links in the coming years. So these links, which need further evaluating, are summarized based on the comparison of potential links with real trade links in the last decade. Step 2: Explore and apply the trade rules by defining country roles To explore and apply the trade rules in the fulfilled and unfulfilled potential links proposed by the link prediction model, the division of country role consists two parts: the past role and future role. The past roles of a country from 2006 to 2014 can help to explore linking rules by observing the features of fulfilled and unfulfilled links in the last decade. The countries appeared in the top10 potential links are divided into net importers and net exporters based on the trade data from UN Comtrade in a certain year. The definition is as follows:

{

𝐼𝑡, 𝐸𝑥𝑡 ‒ 𝐼𝑚𝑡 < 0 𝑅𝑡 = 𝐸 , 𝐸𝑥 ‒ 𝐼𝑚 > 0 𝑡 𝑡 𝑡

(14)

Where t is the year; 𝑅𝑡 means the role in the particular year; If the export volume in the year（ 𝐸𝑥𝑡） is smaller than the import value (𝐼𝑚𝑡), the country is defined as a net importer (𝐼𝑡). Otherwise, the country is considered as a net exporter (𝐸𝑡). The future role of a country can assist to apply the rules to evaluate the potential links in the future. As the natural gas production of countries changes over time, the productions in recent years is an important issue to determine the role in LNG trade. So we considered the recent productions from BP Statistical Review of World Energy (June 2016) as well as the recent trade roles to define the future role of each country involving in the potential links in the future.

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3. Results 3.1Optimal algorithm selection To reveal the structural motivation of the LNG trade network, four indexes, each of which corresponds to a structural motivation, are used in this study. The optimal algorithm is the one with the highest evaluation score (AUC score). The corresponding structural motivation, which is implied in the optimal index, is the one that can explain the construction of trade links from the aspect of topological structure. Moreover, α is applied to make the selection of algorithms more scientific and to explore the effect of trade partners with different trade volumes. Figure 4 displays the AUC score of each index from 2006 to 2015. To reduce random error, an experiment was independently conducted 10 times for each year with the random divisions of the test links and training links [19]. Hence, the AUC score is the average of the 10 results. Figure 4 shows that the PA index performs best in every year, with the highest AUC scores. To further test the validity of the PA index, we observe its specific AUC score. Table 1 shows the AUC scores of every year. The first row is the year. For each year, the AUC scores calculated by PA index under three conditions are displayed. The first one is the AUC score without consideration of trade volume (α=0), which is represented by PA. The second one is the AUC score with full consideration of trade volume (α=1), which is donated by WPA. The third one is the highest AUC score displayed by WPA*, and the corresponding α is shown in the fourth row. For example, as for 2006, the highest AUC value is 0.8564, and the corresponding α is -0.02; The AUC score without consideration of trade volume (α=0) is 0.7754 and with full consideration of trade volume (α=1) is 0.8554. The scores of PA and WPA* are all approximately 0.9 and far exceed 0.5, which is considered good and efficient [19, 25]. Moreover, the AUC in this study is calculated in the most accurate and rigorous way. Therefore, it can be concluded that the good performance of the PA index is valid. It is clear that the PA values of every year have much higher AUC scores than WPA and almost the same as WPA*. Moreover, α is close to 0, which means that weak ties play the same role as strong ties. That is to say, to form new trade relations using the PA index, the trade relations with small volume are as important as those with large volume. According to the above, it can be proven that PA performs the best of the four indexes. The structural cause of LNG trade is that a country with more trade partners has a higher possibility of developing new trading relations, and the existent trade relations with different trade volumes have almost the same contribution. 3.2 Comparison of potential and real trade links In the previous part, PA was proven to be the optimal index for finding potential links, and the trade partners with different trade volumes have the same contribution. Therefore, for each year, country pairs, as test links or inexistent links, are ranked in descending order according to PA value without consideration of trade volume. It is

ACCEPTED MANUSCRIPT proven that countries with more trade partners tend to make new trade relations, so country pairs with high PA values are more likely to form trade relations. Hence, the inexistent links ranking at the top are potential trade links that may trade LNG in the future. To confirm the validity of PA and explore more rules of trade relations, the top 10 inexistent links are selected to observe whether they have trade relations in the following years. As an example, Table 2 displays the top 16 in the ranking of inexistent links and test links by PA score in 2015. In Table 2, there are 16 rows which contain the information of 16 country pairs. For each pair, the first column is the ranking, the second and third columns are the countries, the fourth column is the PA value of each pair and the last column is the type of the link (potential link or test link). The six pairs in grey, which have trade relations in 2015, are the existent links in the test group. So they are test links. Their appearances are random according to the division of the test set and the training set. While the remaining 10 pairs in white are the potential trade pairs which we concern and need further analysis. They are inexistent links which do not trade LNG in 2015, and their rankings as inexistent links are consistent, no matter how the test and training sets are divided. These inexistent links with top 10 PA scores are the country pairs with the most potential for LNG trade relations in the following years, so these 10 inexistent relations are regarded as the top 10 potential trade links and selected from the ranking to observe whether trade relations are fulfilled in the following years. The top 10 potential trading country pairs from 2006 to 2014 are listed in Table 3. There are 41 pairs of countries, and some of the pairs appear repeatedly. For each country pair, the “P” means that, although they do not have LNG trade relations in this year, they are among the top 10 potential trade country pairs calculated by PA, which means they have a high possibility to trade LNG in the future. To compare the potential links with reality, we check the trade relations of these 41 pairs from 2006 to 2015 according to the data obtained from UN Comtrade. For each country pair, “T” means that the countries have LNG trade relations in a certain year. If a “T” appears after a “P” at least for one time, it means the potential trade relation occurs in the following years, and these country pairs are considered as fulfilled country pairs. For example, the pair of France and USA (No.1) appears in the top10 potential trade links in 2006. In 2007, the LNG trade relation between them came true, so they are fulfilled pairs. For a pair, if there is no “T” after “P”, it means that they are assumed to trade LNG in the following years but they do not have trade relations. These pairs are called unfulfilled countries. For instance, as for Uganda and UK (No.32), there is a “P” in 2008, while there is no “T” in the following years, so it is an unfulfilled pair. Therefore, the validity of the evaluation index can be further testified by observing how many country pairs in the top 10 have LNG trade relations in the future. Table 3 shows that 41 country pairs appear in the top 10 from 2006 to 2014. The potential relations of the first 29 pairs (71%) are fulfilled after their first appearance among the top 10, which shows that the PA value is valid in finding potential trade relations in international LNG trade. 3.3Selection of potential trade links to be further evaluated The aim of this study is to find potential LNG trade links, so potential links

ACCEPTED MANUSCRIPT evaluated by PA need to be summarized and further analyzed. In this part, we collect the potential links to be further evaluated according to the top 10 potential links in section 3.2 (Table 2 and Table 3). There are three parts: The first part is the top 10 potential links in 2015. Because of the lack of data in 2016, the potential relations in 2015 cannot be proven. Therefore, all of the links in the top 10 in 2015 are regarded as potential trade links (Table 2). Second, by observing the first 29 country pairs (Table 3), which have been successfully evaluated at least once, it can be found that almost all of them form trade relations in the five years after their first appearances in the list of the top 10 potential links. Only four pairs form links in the six years afterwards. It can be concluded that if a pair of countries appears in the top 10, they are likely to trade LNG in the following five years. Therefore, it can be inferred that the potential links that appear in the top 10 after 2011 but do not have real trade relations in the following years still have a rather strong possibility to trade with each other. Consequently, these links are regarded as potential links. Third, in the first 29 country pairs, there are three pairs of countries (from No. 10 to No. 12 in Table 3) whose potential trade links are fulfilled once, but unfulfilled in later times. These three are regarded as potential trade links that may have trade relations in the future because they have been successfully evaluated and appear frequently in the top 10 potential link list. To summarize, there are 18 country pairs to be further evaluated, which are displayed in Table 4. The trade situation of each pair from 2006 to 2015 is displayed in each row. For each country pair, “T” means that the countries have LNG trade relations in a certain year. For example, USA and Netherlands trade LNG in 2007, 2010, 2011 and 2014. In 2015, they do not have trade relation, but they are in the top 10 potential trade links, which means that they are possible to trade LNG in the future according to the link prediction model. 3.4 Division of trade role in international LNG trade Although the validity of link prediction model is good, there are still unfulfilled pairs in section 3.2. This is because the link prediction model is merely based on the physical topological network. The features of international LNG trade need to be discussed to make the prediction more specific. Therefore, we divided the countries into different roles, net importer and net exporter, to explore and then apply trade rules to select the most potential links from links provided by the link prediction model. The past role and future role of a country are both defined. The countries past roles in LNG trade are defined based on the role index to explore further trade linking rules of the potential links. The future role of a country could help to apply the rules to evaluate the potential links in the future. The production in the recent year is an important factor to determine the role in LNG trade. So when defining the future role of each country involving in the potential links in the future, we took both the recent productions from BP Statistical Review of World Energy (June 2016) and the recent trade roles into consideration.

ACCEPTED MANUSCRIPT 3.4.1 The division of past roles In order to further analyze the rules of trade link construction between potential trade country pairs, the past trade roles of countries appearing in the top 10 from 2006 to 2015 are divided into net importers and net exporters. First, the past role of a country in each year is calculated by the role index according to the trade data in UN Comtrade. In one year, a country is regarded as a net importer if the import volume is higher than the export volume. Otherwise, it is a net exporter. The year of 2015 is taken as an example. As shown in Table 5, the countries which appear in the top 10 potential links are displayed. The LNG importation and exportation volume (unit: kg) are also listed. The countries in grey are net exporters, and those in white are net importers. Second, the final classification of countries’ past role in each pair are made. We would like to find rules from the potential country pairs, so we only need to focus on the countries’ past role in each pair after the appearance of the potential link. In Table 6, the past roles of the country in the potential links from 2006 to 2015 are displayed in each row. “E” in the grey block means that the country is a net exporter in a certain year, while “I” in the white block means it is a net importer. For example, UAE is a net importer in 2008 and a net exporter in other years. As for each pair, if the trade role of a country is the same after the year that the link appears in the top 10 potential ones, the country is defined as the corresponding role. For example, in Table 3 South Africa and UK appears in the potential links in 2006, the roles of Singapore South Africa and UK are both importer from 2013 to 2015, so in this pair, the two counties are importers. Otherwise, further discussion need to be done. If it is a fulfilled link, we define the country as the role in the year that the potential link comes true. Germany and USA is a fulfilled link which first appears in the potential links in 2006, but the role of Germany are distinct after 2006.They trade LNG after the prediction in 2007, and Germany is a net exporter this year, so Germany is a net exporter in this pair. Similarly, Egypt is a net importer in the link of Egypt and Nigeria. UAE is a net exporter in the links of “UAE and China” and “UAE and Algeria” .If it is a unfulfilled link, we define the country role in most years after the appearance as the past role of that country in the link. UAE and South Africa appears in 2007, in the following years, UAE is a net exporter except 2008.So UAE is a net exporter in this link. Similarly, Kazakhstan is a net exporter in “Nigeria and Kazakhstan”. At last, the division of past roles are marked in each pairs in Table 3, where the importers are in white and exporters are in grey. 3.4.2 The division of future role In order to apply the rules we found based on the trade roles, the future roles of countries in the potential links to be further evaluated need to be defined. This is because the natural gas production changes over time. A former net exporter may turn to be a net importer due to the lower production than before, and vice versa. So the

ACCEPTED MANUSCRIPT future role of a country are defined by both the recent trade roles and production. Specifically, the trade roles used are the roles in the recent five years defined in the last part; the recent natural gas production data are from BP Statistical Review of World Energy(June 2016). As for the countries which are net exporters in the recent five years, we focus on whether there is a sharp decrease of production. If it happens, it may be a net importer in the future. As for the countries which are net importers in the recent five years, we focus on whether there is a huge increase of production. If so, it may become a net exporter in the future. If the past roles of a country are different in the recent five years, the future role of this country need to be further discussed based on the production and past roles. The countries in Table 7 are in the potential links in the future, which are summarized in section 3.3. The past roles and productions in the recent five years of each country are listed. In the row of past role, “E” in grey block means it is a net exporter and “I” in white block indicates it is a net importer. In the row of production, the unit is billion cubic meters and NA means the there is no data. And the future role, which is defined by the recent role and production, is displayed in the last row. The first four countries (Norway, Qatar, Malaysia and UAE) are net exporters in the recent five years and the productions of these countries have a tendency to increase. And the natural gas resources are rich in these countries. So in the future, these countries will continue to be net exporters. Germany is a net exporter in 2011 and 2014, while it is a net importer in the other three years. The production of its natural gas is rather low and declining. So it will be a net importer. There is a large increase of production in USA owing to the shale gas revolution and this trend will continue, so USA is going to be a net exporter. The five countries from No.7 to No.11 are net importers and there is no large increase of production during the five years, so they will continue to be net importers. Though the production data of Rep of Korea, Japan, France, Spain, Singapore and South Africa are not available, as we concerned, they are net importers and they do not have the huge increase of natural gas production like USA does. So they are considered as importers in the future 3.5 Exploration of linking rules among potential trade links Combined with the division above, the features of fulfilled and unfulfilled country pairs are found by observing the country pairs in Table 3, in which net exporters are marked in grey and net importers in white according to the final division in Table 7. Pairs No. 40 (China and Japan) and No. 41 (France and UAE) appear after 2011 and are regarded as links to be evaluated in Section 3.3. Therefore, we only observe the characteristics from pair No. 1 to pair No. 39 (Table 3). Some linking rules are summarized by observing fulfilled and unfulfilled potential trade links proposed by the PA index. It should be pointed out that these rules are found to select the most potential trade links from the potential links proposed by the structural motivation. So it is assumed that the pairs selected by these rules are with relatively high possibility to trade LNG with other, while it does not mean that other pairs will not have LNG trade

ACCEPTED MANUSCRIPT relations. The rules are as follows: Rule 1. In the potential LNG trade links, the country pairs that have LNG trade relations less than two years from 2006 to 2015 have a low possibility to trade LNG in the future, and vice versa. Generally speaking, of the fulfilled country pairs (No. 1 to No. 29), 24 pairs (83%) have trade relations more than one year. This indicates that a country tends to trade LNG with a more familiar partner. The LNG trade relations between 10 unfulfilled country pairs (No. 30 to No. 39) are less than 2 years from 2006 to 2015, and 80% of the unfulfilled country pairs have no LNG trade relation during the 10 years, perhaps because of complex factors, such as politics, price or geography. Therefore, the country pairs that have LNG trade relations less than two years from 2006 to 2015 are considered less likely to have LNG trade relations in the future. Rule 2. Among the potential links, LNG trade relations between net exporters, especially countries with abundant natural gas resources, are not likely to occur. According to Table 3, 83% of the trade pairs between two net exporters are not fulfilled, except for Algeria and UAE, which only traded twice in the decade. Trade relations between two exporters represent 50% of the unfulfilled country pairs (from No. 30 to No. 39), and 83% of these unfulfilled country pairs have no trade relation in the ten years, except that Nigeria and Qatar traded once in 2009. These countries are all with rich natural gas resources. This finding confirms that countries with rich natural gas resources, which export LNG to many trade partners, have little need to trade LNG with each other. Rule 3. For potential LNG trade links between net importers, two net importers have a low possibility of building LNG trade relations, but the UK, USA and Rep. of Korea may more easily form new trade relations with other countries. There are 23 country pairs involving both net importers in Table 3, No. 1 to No. 39. Five of these pairs are not fulfilled, representing 50% of the unfulfilled pairs (No. 30 to No. 39). There are 18 pairs that fulfill the trade relations at least once; among them, there are 15 (83%) country pairs in which the USA (seven pairs) or the UK (five pairs) or the Rep. of Korea (three pairs) is one of the partners. Therefore, it can be concluded that although trade relations between net importers have low possibility to form, the USA, UK and Rep. of Korea have high possibility to trade LNG with other net importers. As the country with the most natural gas consumption, the USA tries to reduce its dependence of natural gas on the Middle East countries and thus diversifies its import sources. Moreover, with the ongoing shale gas revolution, the USA has become the largest natural gas producer and exports natural gas to many countries. The operation of the Sabine Pass LNG Terminal and Freeport LNG will largely enhance the ability of the USA to export LNG. Moreover, unconventional gas extraction (“fracking”), which is the method used to exploit shale gas, is likely to be central to the energy policy of president-elect Donald Trump [40], so the natural gas industry will become more prosperous in the USA. As a result, the USA will become a LNG net exporter in the near future and export LNG to more and more countries. The UK has a great demand

ACCEPTED MANUSCRIPT for natural gas and owns the first and most active natural gas trade center (National Balancing Point) in Europe, which makes it an important link in the natural gas trade. As the second largest LNG importer in the world, the Rep. of Korea has signed many long-term contracts with exporters. Unlike Japan, which is the largest LNG importer in the world and has little LNG exportation, the Rep of Korea tends to have more export relations. To summarize, although trade between two net importers is not likely to happen, the UK, USA and Rep. of Korea have a high possibility of trade with other net importers by acting as links transferring LNG from exporters to importers. Rule 4. In the potential links, LNG trade between a net importer and a net exporter has a high possibility of fulfillment in the following years. There are 11 country pairs in which one is a net importer and the other is a net exporter (among No. 1 to No. 39), and 10 of them (91%) have trade relations after they appear in the top 10 potential trade links. This also corresponds with the common sense that countries with different trade roles are more likely to establish cooperative relations. 3.6 Evaluation of most potential links according to the rules In this part, potential links selected in section 3.3 are evaluated using the four rules we found. The aim of this study is to find potential LNG trade links between countries .Therefore, ruling out the pairs with rather low possibility by Rule 1 and Rule 2 is the priority. So at first, the potential links are filtered by Rule 1 and Rule 2.It is worth noting that the most potential trade pairs in this study are the potential pairs proposed by historical trade data mining which have high possibility to trade LNG .It does not mean that other country pairs will not have new LNG trade relations in the future. Thus, our exclusion of the country pairs based on Rule 1 and Rule 2 does not mean that they will not have trade relations. It just means the trade possibility of the remaining ones are relatively higher according to the rules analyzed by historical trade data. Then, the LNG trade possibility of the remaining country pairs is assessed by Rule 1, Rule 3 and Rule 4. As shown in Table 8，the country pairs are potential trade links to be evaluated selected in section 3.3. The future role of a country is defined in 3.4.1. The country in grey is a net exporter, and the one in white is a net importer. For each pair, the trade relations from 2006 to 2015 are displayed. “P” means the country pair appears in the top 10 potential links in a certain year, and “T” means the country pair has a trade relation in this year. The rules are used to evaluate the possibility of trade between each pair. First, according to Rule 1 and Rule 2.Ten country pairs are excluded by Rule 1 and 2. “E” means the links are excluded. Norway and Qatar are net exporters, so they are not likely to trade LNG according to Rule 2. As for the other nine countries, they have LNG trade relations less than two years between 2006 and 2015. Next, the possibility of other trade relations is assessed by Rule 1, Rule 3 and Rule 4. As for Rule 1, “two years” is the baseline of not being excluded, so if the country pair trades LNG more than two years from between 2006 and 2015, they are expected to have a high possibility of trading LNG in the future. An “h” is marked in the corresponding blank. According to Rule 3,

ACCEPTED MANUSCRIPT if one country in the pair is a net importer and the other is a net exporter, they are likely to have an LNG trade relation, and an “h” is marked. According to Rule 4, for two net importers, if one of the countries is the UK, USA or Rep. of Korea, the possibility of trading is higher, so an “h” is marked in the corresponding column. Finally, the “possibility” column is the sum of the “h” in the first three columns. The more “h” a country pair has, the more likely they will trade in the future. Eventually, Netherlands, Singapore, India and Spain are considered to have very high possibility to trade LNG with USA; Italy has high possibility to trade LNG with USA; Japan and UK, France and Rep of Korea are likely to trade LNG in the following five years.

4. Discussion and conclusion This study aims to find potential international LNG trade using the link prediction method, which is an emerging method based on complex network theory. To explore the structural mechanism of the international LNG trade network, the optimal algorithm was selected from four mainstream ones, and a parameter was introduced to examine the contributions of trade partners with different trade volumes. The result shows that the PA index is optimal to reveal the structural motivation of international LNG trade, and trade partners with different trade volumes play the same role. Moreover, the potential trade links are compared with the real situation, indicating that 71% of the country pairs have been successfully evaluated at least once. To make the evaluation of potential trade links more practical, further rules of the linking motivation in the potential links are explored. The features of fulfilled and unfulfilled country pairs are analyzed by the division of countries as importers and exporters. Finally, potential links are selected by the combination of structural motivation and rules. According to the results, we make the following discussions and conclusions: 4.1 Linking motivation of international LNG trade The awareness of future international trade relations is important, as it can help the government avoid energy supply risk or income loss. However, the construction of international trade relations is complex and affected by various factors. It is challenging to predict specifically which pair of countries will have trade relations. However, that does not mean we should give up our endeavor to find potential trade links. In this study, potential LNG trade links are found following two steps. First, the structural linking motivation is explored using the link prediction method. The PA index is found to be the most optimal of the four mainstream algorithms revealing the structural motivation in the international LNG trade network. The PA index posits that a country with more trade relationships has a higher possibility to form new trade relations with other countries, which indicates that there is a rich club phenomenon in international LNG trade 19. Moreover, it is proven that trade partners with different trade volumes have the same effect on the evaluation of potential links. Next, to make the evaluation of potential LNG trade links more scientific and reasonable, the linking rules based on the practical international LNG trade are explored by observing the features of fulfilled and unfulfilled country pairs. Among the potential links evaluated by the PA index, countries tend to trade LNG with former trade partners, with whom they are more familiar. In addition, a country’s role in international LNG

ACCEPTED MANUSCRIPT trade plays a significant part in the forming of a new LNG trade relation. Two net exporters are not likely to trade LNG with each other, while the potential trade relation between countries with different roles has a high probability. As for two net importers, the USA, UK and Rep. of Korea are more likely to trade LNG with other net importers. Although they are net LNG importers, they act as bridges and transfer LNG from exporters to importers. To summarize, potential international LNG trade can be discovered according to the number of countries’ trade partners and then further evaluated by the rules we found. This method is of great practical significance and can provide the government with a reference when seeking new LNG trade relations. 4.2 Potential links in LNG trade Potential LNG trade links can be found by combining the structural motivation and rules to provide reference for governments. According to Table 8, there is a very high possibility that India, Spain, Netherlands and Singapore will build new LNG trade relations with the USA. There is a high possibility that Italy will trade LNG with the USA. In addition, Japan and the UK, France and the Rep. of Korea are likely to trade LNG within the next five years. As we found in section 3.4.2, the USA will be a net LNG exporter in the future, so we assume that India, Spain and Italy, which lack of natural gas, will import LNG from the USA. Meanwhile, owing to its geographical advantage and developed pipeline network, the Netherlands is one of the trade hubs in Europe. It is likely to import LNG from the USA and sell it to other European countries. Similarly, aiming to be the center of LNG trade in Asia, Singapore has the possibility to import LNG from the USA. As the largest LNG importer in the world, the LNG importations of Japan are mainly from Qatar and Australia, which occupy about 50% of the whole importations from the world in 2015. The LNG dependency of these two countries is high and Japan may import LNG from the UK to diversify its importation source. In the same manner, we consider that the Rep. of Korea will import LNG from France. Although data for 2016 are not yet available from UN Comtrade, it has been reported that Italy received LNG from the USA in December, 2016, and Spain likewise received LNG from the USA earlier in 2016. Moreover, Bloomberg News reported that India became the first country in Asia to import LNG made by shale gas from the USA in April, 2016. In addition, British Petroleum (BP) and Japan's Kansai Electric (JKE) signed an LNG contract in 2015, in which BP would offer LNG to JKE. To reach new buyers in Asia, the French oil and gas company Total signed a contract with Korea Gas to extend cooperation in the LNG business, including LNG trade. These facts verify the validity of the method proposed by this study to find potential trade links. 4.3 Suggestions for LNG trade policy This study finds potential trade links in international LNG trade. The main practical implications are two-folds: On the one hand, countries could seek new partners by this study when facing a trade relation breakdown or wanting to diversify the trade partners. On the other hand, countries whose important natural gas partners, not only LNG partners, are involved in the above potential pairs could make advanced preparation to adjust their trading strategies because their supply or demand may be

ACCEPTED MANUSCRIPT affected by the new trade relation of their important partners. For example, as for an exporter, if one of its major trade partners in natural gas builds a new trade relation and imports much LNG from another exporter, the exporter’s exports are likely to reduce, and its income from natural gas may be affected. Russia and Europe is a practical example. Since the Ukraine Crisis in 2013, the relation between Europe and Russia has become tenser, especially in the aspect of natural gas trade, so European countries are attempting to reduce their energy reliance on Russian. In terms of European countries, diversifying natural gas sources is an effective solution. In this study, we found that Spain, Netherlands and Italy are likely to import LNG from USA. The news mentioned in section 4.2 has already verified the potential links between Italy and USA, as well as Spain and USA. The USA is becoming an LNG export country owing to the shale gas revolution and the construction of new LNG infrastructure. Many European countries recently began to import LNG from the USA, and this trend will continue according to the potential LNG trade pairs found in this study. However, this trend will affect the natural gas exportation of Russia. Russia should then take measures such as lowering prices or changing trade patterns to maintain its status and influence in Europe. Increasing exportation to other buyers elsewhere is another solution to avoid economic loss. Asia seems to be a good option for Russia due to its shorter geographical distance and massive quantity demand, but Russia is facing another competitive rival-- the rising natural gas producer Australia, whose buyers are almost Asian countries. The production and exportation of Australia ramped up in recent years. In 2015, the LNG exportation of Australia occupied 12% of the world LNG exportation. And Australia is expanding new trade relations. Besides the large amount of exportation to China, Japan, Korea and Singapore, Australia set new exportation trade relations in 2015 with India (7.1E+08 kg), Thailand (2E+08 kg), Pakistan (1.2E+08 kg) and Jordon (7.1E+08 kg). So Russia need to make more competitive offer than Australia to gain more trade opportunity from Asia. Furthermore, the more LNG trade partners a country has, the more likely it will form new LNG trade relations with other countries. In this method, the trade partners with small trade volumes are as important as those with large trade volumes. Therefore, countries should try to establish LNG trade relations with more partners, even if the trade volumes are not large, because this can not only enhance energy security but also expand influence in the international LNG trade market. This paper studies the international LNG trade with a new perspective and tries to solve the practical problems that result from sudden fracture of trade relations by finding potential trade links. However, the forming of international LNG trade relations may be determined by many factors. Consequently, in the future, further analyses will be conducted with the consideration of geography, economic and political factors for a more specific evaluation of potential trade links.

5. Acknowledgement This research is supported by grants from the National Natural Science Foundation of China (Grant No. 71173199). The authors would like to express their gratitude to Weiqiong Zhong, Xiaoqing Hao, Nairong Liu who gave valuable suggestions on this

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Russia USA

Spain Algeria Nigeria

Rep. of Korea China Japan Qatar India Malaysia

Legend LNG trade relation Natraul Gas Consumption(NGC) NGC Unit:Billion cubic meters 0-20 20-60 60-120 120-400 400-800

Australia

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Figure1 The LNG trade under the global context of natural gas consumption in 2015

Figure 2 International LNG trade network in 2015 Step 1 Choose four algorithms:CN,AA,RA,PA. Details of the network:

A

B

Step 2 Chose 10% of exis tent links (10%*10=1)randomly as test

B

A

set(EP ),and the rest as training s et(ET)

Number of nodes=6 Number of links=10 Number of U(possible F links)=6*(6-1)/2 Nodes={A,B,C,D,E,F} E(Links)={AB,AD,AE,AF, BC,BD,BE,CE,CF,DE}

C

EP ={AB} C ET={AB,AD,AE,AF,BC,BD,BE,CE,C

F

F,DE}

E

Step 4 Calculate and rank the scores of inexistent links and test links by CN,AA,RA and PA.

D

Step 3 Find inexistent links The s et of possible links is U. U={AB,AC,AD，AE，AF，BC， BD，BE，BF，CD，CE，CF， DE，DF，EF} Thus the set of inexistent linlks is:

D

E

EI+EP={AC,BF,CD,DF,EF} Step 5 Make an evaluation of different Rank 1 algorithms and find the most optimal one by AUC according to 2 3 the scores of inexis tent links and 4 test links 5 6

EI =U-E ={AC,BF,CD,DF,EF} B A Link AC BF CD EF AB DF

CN 3 2 2 2 2 1

Link AC AB BF EF CD DF

AA 6.64 6.64 3.76 3.76 3.32 1.66

Link AC AB BF EF CD DF

RA 1 0.58 0.58 0.58 0.5 0.25

Link AB AC CD BF EF DF

PA 16 12 9 8 8 6

F

C

E

Figure 3 Algorithm process demonstration with a simple example

D

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Figure 4 Evaluation of four algorithms from 2006 to 2015

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Tables: Table 1 The AUC score of the PA index considering the contribution of trade volume 2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

PA(α=0)

0.7754

0.8000

0.8946

0.9008

0.8912

0.8825

0.8950

0.8971

0.8817

0.8892

WPA(α=1)

0.8554

0.8941

0.8200

0.8142

0.8116

0.8275

0.8221

0.8212

0.7934

0.8273

WPA*

0.8564

0.8947

0.8946

0.9009

0.8912

0.8833

0.8953

0.8976

0.8864

0.8912

α

-0.02

-0.01

-0.01,0

-0.02

0

-0.01

-0.01

-0.01

-0.05

-0.03

Table 2 The top 16 country pairs in 2015 ranked by PA Country A

Country B

PA value

Type of the link

1

Netherlands

USA

1480

Potential link

2

Spain

USA

1110

Potential link

3

India

USA

888

Potential link

4

China

Netherlands

840

Potential link

5

Japan

Netherlands

840

Potential link

6

Rep. of Korea

Spain

810

Test link

7

Netherlands

Singapore

800

Potential link

8

Netherlands

Belgium

760

Test link

9

Singapore

America

740

Potential link

10

France

Spain

720

Test link

11

Malaysia

Netherlands

720

Potential link

12

Trinidad and Tobago

USA

703

Test link

13

India

UK

696

Test link

14

Norway

Qatar

660

Potential link

15

Rep. of Korea

India

648

Test link

16

France

Rep. of Korea

648

Potential link

Table 3 Comparison of potential trade links with real trade links from 2006-2014 No.

Country A

Country B

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

1

France

USA

P

T

T

T

P

P

T

T

P

T

2

India

USA

P

P

P

T

T

T

T

T

P

3

Belgium

USA

P

T

T

P

T

4

Malaysia

USA

P

T

T

T

T

T

5

South Africa

UK

P

T

T

T

T

T

6

China

UK

P

P

P

P

T

P

7

Rep. of Korea

UK

P

P

T

P

P

T

8

India

UK

P

P

T

T

9

France

Japan

P

P

P

P

T

T

P

10

South Africa

USA

P

T

P

P

P

P

P

P

11

Germany

USA

P

T

P

P

P

P

12

Italy

USA

T

P

P

P

P

T

P

T

T

T

T P

T T

P

P

T

ACCEPTED MANUSCRIPT

13

UAE

China

T

P

T

14

Japan

UK

T

P

15

Algeria

UAE

T

P

16

Spain

USA

T

T

17

Qatar

Italy

T

18

UAE

Italy

P

T

19

France

Rep. of Korea

P

P

20

Nigeria

Egypt

P

21

Nigeria

Uganda

P

22

Nigeria

Italy

T

P

23

UAE

USA

T

P

24

China

Spain

25

France

Singapore

26

Japan

USA

27

UAE

Rep. of Korea

28

China

Rep. of Korea

29

Japan

Rep. of Korea

T

P

P

P

T

T

T

P

T

P

P

T

T

T

T

T

T

T

T

T

P

T

T T

T

T

T

T

T

T

T

P

T

T

T

T

P

T

P

T

T

T

1

China

France

P

P

31

2

UAE

South Africa

P

32

3

Uganda

UK

33

4

France

South Africa

36

5

China

Italy

P

34

6

Nigeria

Algeria

P

35

7

Nigeria

Kazakhstan

P

37

8

Nigeria

UAE

P

38

9

T

T

P

T T

P

P

Tobago Qatar

T

40 11

China

Japan

T

41 12

UAE

France

T

P

P

P P

T

T

T

P

Table 4 Potential trade links to be further evaluated USA

Netherlands

China

Netherlands

Japan

Netherlands

Singapore

Netherlands

Singapore

USA

Malaysia

Netherlands

2006

T

P

P

Nigeria

Country B

P

P

P

39 10

Country A

T

P

P

2007

2008

2009

T

2010

2011

T

T

2012

2013

2014

2015

T

P

T

P T

T T

T

T

P P

T

T

P P

T

P

P

Trinidad and

T

T T

T

T

30

Nigeria

T

P

T

T

T

T

T

T

T

T

ACCEPTED MANUSCRIPT

Norway

Qatar

P

India

USA

P

P

P

T

T

T

T

T

China

UK

P

P

P

P

T

P

P

P

Japan

UK

T

P

T

Spain

USA

T

T

P

Rep. of

France

Japan

UAE

France

Germany

USA

South Africa Italy

P P

T

T

T T

T

P

T

P

USA

P

T

USA

T

P

T

P

P

P

P

Korea

China

P

T

P

T

P

P

T

T

P

T

T

P P

P

P

P

P

P

P

P

P

P

P

P

P

P

Table 5 The division of past role in 2015 Countries Algeria Trinidad

and

LNG

LNG

Countries

Importation

Exportation

9.13E+02

1.45E+10

8.75E+05

8.92E+09

Tobago

LNG

LNG

Importation

Exportation

Japan

9.50E+10

0

Rep. of

4.79E+10

6.73E+07

Korea

Malaysia

1.48E+09

2.31E+10

Netherlands

2.17E+09

5.27E+08

Nigeria

1.37E+06

1.47E+10

Belgium

2.93E+09

6.04E+08

Norway

3.69E+06

5.03E+09

India

1.95E+10

3.17E+08

Qatar

2.25E+03

1.13E+11

Singapore

5.70E+09

4.30E+08

Kazakhstan

0

4.32E+06

South

2.98E+09

4.39E+08

Africa UAE

4.86E+09

5.66E+09

Spain

1.13E+10

1.55E+09

China

2.17E+10

7.60E+04

Uganda

1.69E+06

1.17E+04

France

6.94E+09

3.65E+08

Egypt

2.76E+09

6.30E+07

Germany

3.77E+07

9.53E+06

UK

9.90E+09

2.91E+08

Italy

4.95E+09

2.97E+07

USA

1.72E+09

8.09E+08

Note: The unit of LNG in this table is kg. Table 6 Past roles of the counties in the potential links from 2006 to 2015 No.

Country

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

1

Algeria

E

E

E　

E

E

E

E

E

E

E

2

Nigeria

E

E

E

E

E

E

E

E

E

E

3

Norway

E

E

E

E

E

E

E

E

E

E

4

Qatar

E

E

E

E

E

E

E

E

E

E

5

Malaysia

E

E

E

E

E

E

E

E

E

E

6

Trinidad and

E

E

E

E

E

E

E

E

E

E

Tobago

ACCEPTED MANUSCRIPT

7

UAE

E

E

I

E

E

E

E

E

E

E

8

Egypt

E

E

E

E

E

E

E

E

E

I

9

Kazakhstan

E

E

E

E

E

E

I

E

I

E

10

Germany

E

E

E

E

E

E

I

I

E

I

11

Singapore

I

E

I

E

I

I

I

I

I

I

12

South Africa

E

I

I

I

I

I

I

I

I

I

13

China

I

I

I

I

I

I

I

I

I

I

14

France

I

I

I

I

I

I

I

I

I

I

15

Italy

I

I

I

I

I

I

I

I

I

I

16

Japan

I

I

I

I

I

I

I

I

I

I

17

Rep of Korea

I

I

I

I

I

I

I

I

I

I

18

Netherlands

I

I

I

I

I

I

I

I

I

I

19

Belgium

I

I

I

I

I

I

I

I

I

I

20

India

I

I

I

I

I

I

I

I

I

I

21

Spain

I

I

I

I

I

I

I

I

I

I

22

Uganda

I

I

I

I

I

I

I

I

I

I

23

UK

I

I

I

I

I

I

I

I

I

I

24

USA

I

I

I

I

I

I

I

I

I

I

Table 7 Future roles of the counties in the potential links to be further evaluated No.

Country

1

Norway

2 3 4 5 6 7 8 9 10 11

Qatar Malaysia UAE Germany USA UK China India Italy Netherlands

2011

2012

2013

2014

2015

Future role

Past role

E

E

E

E

E

Exporter

Production

101.3

114.7

108.7

108.8

117.2

Past role

E

E

E

E

E

Production

145.3

157

177.6

174.1

184.1

Past role

E

E

E

E

E

Production

62

61.3

67.1

66.7

68.2

Past role

E

E

E

E

E

Production

52.3

54.3

54.6

54.2

55.8

Past role

E

I

I

E

I

Production

10

9

8.2

7.7

7.2

Past role

I

I

I

I

I

Production

648.5

680.5

685.4

728.5

767.3

Past role

I

I

I

I

I

Production

45.2

38.9

36.5

36.8

39.7

Past role

I

I

I

I

I

Production

109

111.8

122.2

131.6

138

Past role

I

I

I

I

I

Production

44.5

38.8

32.2

30.4

29.2

Past role

I

I

I

I

I

Production

7.7

7.8

7

6.5

6.2

Past role

I

I

I

I

I

Exporter Exporter Exporter Importer Exporter Importer Importer Importer Importer Importer

ACCEPTED MANUSCRIPT

12

Rep of Korea

13

Japan

14

France

15

Spain

16

Singapore

17

South Africa

Production

64.1

63.8

68.6

55.7

43

Past role

I

I

I

I

I

Production

NA

NA

NA

NA

NA

Past role

I

I

I

I

I

Production

NA

NA

NA

NA

NA

Past role

I

I

I

I

I

Production

NA

NA

NA

NA

NA

Past role

I

I

I

I

I

Production

NA

NA

NA

NA

NA

Past role

I

I

I

I

I

Production

NA

NA

NA

NA

NA

Past role

I

I

I

I

I

NA

NA

NA

Production NA NA Note: The unit of production is billion cubic meters.

Importer Importer Importer Importer Importer Importer

Table 8 Evaluation of most potential links Country A

Country B

USA

Netherlands

China

Netherlands

Japan

Netherlands

Singapore

Netherlands

Singapore

USA

Malaysia

Netherlands

Norway

Qatar

India

USA

P

P

P

T

T

T

T

T

China

UK

P

P

P

P

T

P

P

P

Japan

UK

T

P

T

Spain

USA

T

T

P

France

UAE

France

Germany

USA

Italy

2008

2009

T

2010

2011

T

T

2012

2013

2014

2015

T

P

T T T T

T

T

T

T

P

P P

T

T

P

Korea Japan

Africa

2007

Rep. of

China

South

2006

T T

T

P

T

P

USA

P

T

USA

T

P

T

P

R1&

R R R

R2

1

3 4

h

h h

hhh

h

h h

hhh

h

h h

hhh

h

h

h h

hhh

P

E

P

E

P

E

P P

E

P

E

P

Possibility

E

P T

P

T

P

P

T

T

P

P

h

h

h

E

T

T

P

E

P

E

P

P

P

P

P

P

P

P

P

P

P

E P

h h

hh