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186
глобальный мир и внешняя политика РОССИИ
DOI: 10. 26794/2226-7867-2018-8-3-59-69 UDC 339.5(045)
AN EMPIRICAL sTUDY ON sTATUs AND POTENTIAL
of sino-Russian bilateral trade
Yang Da,
Researcher, Research Center for the Economies and Politics of Transitional Countries; Postdoctor, Liaoning
University School of International Studies, lecturer, Liaoning Prov, China
yangda5160@163.com
Cui Puge,
Liaoning University School of International Studies, undergraduate, Liaoning Prov, China
Abstract. This paper uses trade intensity index and trade complementarity index for statistical analysis of Sino-Russian bilateral trade status, adopting the bilateral trade data from 2006 to 2016, and uses the extended trade gravity model for empirical analysis of influencing factors on bilateral trade flows and trade potential respectively under the circumstances of invariable and improved terms of trade. We find that even if the fluctuations of Sino-Russian bilateral trade volume and growth rate are strong, the intensity and complementarity are both evident and there is a relatively large space for bilateral trade development. Furthermore, it could be effective to develop bilateral trade through improving informal-system at a family degree. We also give some policy suggestions in terms of cooperative mechanism, trade structure, FTA (Free Trade Area) and culture communication, on the basis of former empirical research. Keywords: Sino-Russian bilateral trade; trade status; trade potential; gravity model
эмпирическое исследование состояния и потенциала развития китайско-российской двусторонней торговли
Янг Да,
научный сотрудник, Исследовательский центр экономики и политики переходных стран; преподаватель Школы международных исследований Университета Ляонин, провинция Ляонин, Китай yangda5160@163.com
Цуй Пудж,
бакалавр Школы международных исследований Университета Ляонин, провинция Ляонин, Китай
Аннотация. В данной работе авторы применяют индексы интенсивности и взаимодополняемости торговли для статистического анализа китайско-российской двусторонней торговли на основе данных о двусторонних торговых сделках с 2006 по 2016 г. Также авторы использовали расширенную гравитационную модель торговли для эмпирического анализа факторов, влияющих на потоки двусторонней торговли и торгового потенциала в неизменных и улучшенных условиях.
Авторы отмечают, что даже при сильных колебаниях объемов и темпов роста российско-китайского товарооборота интенсивность и взаимодополняемость являются очевидными, а возможности для развития двусторонней торговли относительно велики. Кроме того, можно было бы эффективно развивать двустороннюю торговлю путем совершенствования неформальной системы. Авторы также делают некоторые политические предложения в отношении механизма сотрудничества, структуры торговли, зоны свободной торговли и культурной коммуникации на основе прежних эмпирических исследований. Ключевые слова: китайско-российская двусторонняя торговля; торговый статус; торговый потенциал; гравитационная модель
MODEL
1. INTRODUCTION
China and Russia are not only the most crucial geopolitical powers in the Asian area, but also two of the largest emerging economics in the world today. The volume of Sino-Russian bilateral trade reached 69.53 billion dollars with a year-on-year growth rate of 2.2%, which seems to be a contrarian growth against the slow economic recovery and sluggish growth of global trade. Further, China has been the first trade partner of Russia for several years and Russia is one of China's main sources of import energy and high-tech products. With the development of One Belt One Road (OBOD) initiative, the total trade has increased with fluctuations. It is worth noting that Russia is an important partner and the total import and export volume of Sino-Russia bilateral trade is the sixth one among the partners of OBOD, which takes up 7.3% of the total trade volume of China's foreign tradeunder the Belt and Road initiative. But the proportion of energy or raw material products could usually be close to or even over 50%, which means the trade structure between China and Russia is relatively simple1.
So, what is the potential for trade between China and Russia? How can we promote economic and trade cooperation between these two countries? Many scholars have made a detailed analysis on trade between China and other countries due to the rapid development of China's foreign trade. Sun Jinyan (2015) has argued Sino-Australian trade size, complementarity and potential are all expended through utilizing trade intensity index and Global Model to analyze. Jin Zhuiqiao (2015) has investigated the trade status, predicted the potential of Sino-Korean trade and concluded that it could be possible to expand bilateral trade and economic cooperation. At the same time, the research on Sino-Russian related issues has been paid more and more attention. Kang Chengwen (2014) has done empirical research on commodity structure, Relative Revealed Comparative Trade Advantage Index and Trade Complementarity Index of Sino-Russian and Russo-Japanese bilateral trade and the outcomes are positive. Developing Sino-Russian FTA should not only solve current problems, but also seek new and beneficial cooperation opportunities (Jia Haojie, 2015). Further, Li Yang (2017) has hold the view point that the strategic docking of
1 Source: Big Data Report of Trade Cooperation under the Belt and Road Initiative 2017.
One Belt One Road and Eurasian Economic Union could promote Sino-Russian cooperation.
From the perspective of analyzing the trade potential, there are lots of scholars have used Gravity Model to do empirical studies and modify this model. Luo Laijun (2014) has studied the directionality and asymmetry of the Gravity Model. Yu Yan (2014) has utilized the Gravity Model to do quantitative analysis in order to get the key elements of China's importexport trade. Gao Zhigang (2015) has built Stochastic Frontier Gravity Model and used Frontier 4.1 software to investigate the Sino-Pakistani trade efficiency and measure the potential. Tan Xiujieand Zhou Maorong (2015) has studied the trade potential of the countries along the "maritime silk road" using stochastic frontier gravity model, and analyzed the influencing factors. Then they argue that the trade efficiency of the 21st Maritime Silk Road continues to improve, and China's exports still have great potential. Wang Liang (2016) has investigated the fundamental situation of economy development, trade intensity and complementarity, and built the Stochastic Frontier Gravity Modelto estimate the trade potential, non-efficiency degree and other influencing factors of the Silk Road Economic Belt. Ding Janping (2016) has put the Gravity Model of scale effect in trade cost and analyzed the development potential of different industries through scale economical characteristics.
However, there are some shortages in the existing researches. Firstly, the tools which used in analyzing the status of bilateral trade are simple, not including all measure standards, and there lack researches with latest data. Secondly, when the scholars investigate the influencing factors of trade flows, they only focus on the economic perspective. Thirdly, there are just little diversities in the method used in trade potential study. Thus we try to use different methods to investigate the trade status in Chapter 2 and add both formal and informal system variables into Gravity Model to study the Sino-Russian bilateral trade potential in Chapter 3. In Chapter 4, we summarize the previous results in former parts and give some policy suggestions.
2. THE sITUATION OF sINO-RUssIAN BILATERAL TRADE
2.1. Sino-Russian Trade Overview
The trade between China and Russia showed big changes between 2006 and 2016 (Fig. 1). From general perspective, we could clearly see that the Sino-Russian gross trade volume peaked at 95.27 billion dollars in 2014 and then it decreased to 68.02 bil-
MOEAflbHblM MMP M BHEWHflfl nOAMTMKA POCCMM
Fig. 1. Bilitary trade between China and Russia
Data Source: calculation based on the data drawn from WITS DATABASE (http://wits.worldbank. org/) .
1 200,00 1 000,00 800,00 600,00 400,00 200,00 0,00
& <$> ^ ttttttttttt
100,00%
80,00%
60,00%% China exports to Russia
40,00%
20,00% China imports from Russia
0,00% Sino-Russia gross trade volume
-20,00°% Export growth rate
-40,00°%
-60,00% Import growth rate
(year) total trade growth rate
lion dollars in 2015 before slightly increasing to 69.60 billion in 2016. In most cases, the quantity of China's export was more than that of import during this period.
The year of 2008, which was a time of financial crisis, seemed to be a turning point.In 2009, all trade volumes reached the lowest level and especially the export growth rate and the total trade growth rate were respectively -47.05% and -31.83%. Overall, three growth rates decreased from 2010 to 2015 after soaringin 2009, and then they recovered in 2016. Based on this, we could hold a viewpoint that there is an uncertain future of the bilateral trade between China and Russia.
2.2. Commodity Composition of Sino-Russian Bilateral Trade
We use International Trade Standard Classification, which is proposed by the United Nations, as the fundamental to sort out goods of Sino-Russian bilateral trade. According to this classification method, it divides all commodities into nine parts (SITC 0-SITC 9)2. Generally speaking, product cords SITC 0-SITC 4 represent primary products, which are also called resource-intensive products, and product cords SITC 5-SITC 9 represent industrial manufactured products. In the latter classification, SITC 5, SITC 7 and SITC 9 goods belong to capital-intensive or tech-
2 Product codes SITC 0-SITC 9 separately represent food and live animals, beverages and tobacco, inedible raw materials other than fuel, mineral fuels, lubricants and related raw materials, animal and vegetable oils, fats and waxes, no-listed chemicals and related products, manufactures mainly classified by materials, machinery and transport equipment, miscellaneous manufactured articles and other uncategorized goods and transactions.
nology-intensive products, and SITC 6 and SITC 8 goods belong to labor-intensive products.
The import and export commodity structures of Sino-Russian bilateral trade are different and advantage products have disparities. The total trade volume of Sino-Russian bilateral trade between 2006 and 2016 is presented in Tablel. Panel A of Table 1 which regards China as the source country and Russia as the target country, illustrates that commodities, which China exports to Russia, are mainly five categories including SITC 0, SITC 5, SITC 6, SITC 7 and SITC 8, and among these, the trade volume of SITC 8 products specializing in clothing is the most one. In 2016, the largest selling of products was up to 15049 million dollars accounting for 40.3% of total exportations of Sino-Russian bilateral trade. The export trade growth of SITC 7 has changed triple during these eleven years. We regard Russia as the source country and China as the target country in Panel B. The imported products of China from Russia are mainly goods with product code SITC 0, SITC 2, SITC 3, SITC 5 and SITC 6. The largest one, SITC 3 classification, took up approximately 45% to 70% of the total importations and the largest share of it was 71% in year 2014.
We analyze the commodity composition of Sino-Russian bilateral trade in Fig. 2 and Fig. 3 using China as the reporter, and draw conclusions as follow: (1) Although the proportion of resource-intensive products kept a low level of 5% to 7% in exceptions of China during 11 years, it was the most popular part of imported goods with more than 80 percent in most years. (2) The expectations mainly relied on industrial manufactured
Table 1
Total Export-Import Volume of sino-Russian Bilateral Trade between 2006 and 2016
A. The exportations of China with Russia (million)
Product Code 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
SITC 0 790 1114 1241 1056 1377 1754 1755 1905 2102 1634 1780
SITC 1 12 12 16 17 20 28 28 26 17 13 14
SITC 2 82 104 146 82 141 248 211 173 202 160 153
SITC 3 142 197 270 89 222 351 294 286 185 177 158
SITC 4 0.43 0. 66 1.98 1.85 2. 80 5.84 5. 61 3.68 4. 78 3.08 3. 71
SITC 5 741 1228 1632 1019 1551 2074 2248 2509 2837 2115 2194
SITC 6 2704 4482 6528 3256 5511 7501 8499 9318 9888 5954 5777
SITC 7 4359 8321 11587 5441 10472 14831 17543 17524 18171 11690 15049
SITC 8 7001 13070 11652 6543 10308 12093 13473 17846 20272 13010 12151
SITC 9 0. 50 0.46 1. 89 8. 88 6. 83 15.75 0.20 0. 02 0.22 0. 10 60. 88
B. The importations of China with Russia (million)
Product Code 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
SITC 0 1281 1427 1308 1277 1373 1669 1493 1494 1469 1439 1579
SITC 1 0.57 1. 97 2.83 1. 56 1. 94 2.41 2 .34 17.08 18. 98 20.89 30. 83
SITC 2 3485 5001 5758 4338 5313 8567 6864 6056 5554 5272 5760
SITC 3 9464 9354 11947 9386 12848 22923 29522 26880 29719 20191 19021
SITC 4 0.00 0.00 0.02 0.04 0.00 0.35 2. 52 7. 70 9. 06 75.07 194.63
SITC 5 1870 2171 2537 1796 2824 3128 3087 2283 1881 1747 1238
SITC 6 1222 1460 1858 4040 3148 3764 2812 2608 2394 3680 3314
SITC 7 196 224 361 387 331 220 224 187 363 553 691
SITC 8 29 40 55 54 72 84 122 125 127 144 207
SITC 9 7.64 10 . 24 5. 69 2. 76 3.31 5. 92 9.36 10.33 57. 15 135.56 224.13
Data Source: UNCOMTRADE DATABASE (http://comtrade .un . org) .
goods (labor-intensive products and capital-intensive or technology-intensive products), while they were comparatively minor in importations. In addition, the decreasing labor-intensive products and increasing capital-intensive or technology-intensive products gradually reached the similar proportion. (3) China's import commodity structure from Russia was relatively fixed, but the structure of exported goods continued to improve. Even if the quantity of capital-intensive or technology-intensive products was slightly below that of laborintensive ones, it had the tendency to become the highest.
2.3. Sino-Russian Bilateral Trade Intensity
We analyze the trade intensity of Sino-Russian bilateral trade through Index of Trade Intensity3. Let us donate export for X and import for M, then the calculation formula is:
TCDab = (ХУХ) / (Mb/M). ^
3 Index of Trade Intensity (TCD) is an index used to measure the trade intensity of a trade partner. Its value is equal to the ratio of a country's exports to certain trading partner of the country's total exports divided by the rate of the partner' exports accounted for the proportion of total world imports.
глобальный мир И внешняя политика РОССИИ
70,00% 60,00% 50,00% 40,00% 30,00% 20,00°% 10,00% 0,00%
00000000000 22222222222
resource-intensive products
labor-intensive products
capital-intensive or
technology-intensive
products
Fig. 2. Commodity Composition of China's exports to Russia between 2006 and 2016
100, 90, 80, 70, 60, 50, 40, 30, 20, 10 0
00% 00% 00% 00% 00% 00% 00% 00% 00% 00% 00%
resource-intensive products
labor-intensive products
capital-intensive or
technology-intensive
products
67 00 00 22
89 00 00
2222
000 222
Fig. 3. Commodity Composition of China's imports from Russia between 2006 and 2016
Data Source: calculation based on the data from WITS DATABASE (http://wits.worldbank. org/).
Where TCDab measures the importance of Country b as an export market of Country a, Xab represents the exportations of Country a to Country b, Xa represents the gross exportations of Country a, and Mb and Mw are respectively the importations of Country b and the world. If values of TCD b and TCDb are
ab ba
both greater than 1, the two countries act as the vital export market to each other. The higher value indicates that the close links between the two trade countries and the higher level of importance of the country's trading partner as the export market to the report country.
TCDcr donates the importance of Russia as a China's export market and TCDRC is the significance of China as an export market of Russia (Table 2). We find that TCDCR > 1 since 2006, which illustrates Russia is always an essential export
market to China. Although TCDRC ^ 1 before 2015, it has an upward trend in recent years. It is worth noting that in both 2015 and 2016, TCDCR > 1 and TCDRC > 1 shows that these two countries become vital partners to each other. Additionally, even if these two indexes have different changing tendency, the phenomenon that TCDCR > TCDRC always exists, which means China depends moreon Russia's market.
2.4. Complementarity of Sino-Russian Bilateral Trade
Under the free trade environment, different countries form division of labor in manufacturing process due to comparative advantages. Based on this, we analyze Sino-Russian bilateral trade complementarity through Revealed Comparative Advantage
Table 2
Sino-Russian Trade Intensity Index between 2006 and 2016
Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2016
TCDCR 1.43 1.62 1.38 1. 05 1.23 1.20 1.22 1.30 1.46 1.34 1.44 1.44
TCDRC 0. 97 0. 89 0. 78 0. 94 0. 76 0.86 0.90 0. 77 0.84 1.01 1/05 1.05
Source: calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/) .
The Value C Calculated by China as the Exporting Country
Table 3
year resource-intensive products labor-intensive products capital-intensive/technology-intensive products
SITC 0 SITC 1 SITC 2 SITC 3 SITC 4 SITC 6 SITC 8 SITC 5 SITC 7 SITC 9
2006 1.26 0.36 0. 21 0.01 0. 15 1.13 1.68 0. 51 1.47 0. 11
2007 0.96 0.30 0. 16 0.01 0. 07 1. 09 1.91 0.44 1.66 0. 06
2008 0. 76 0.26 0. 18 0.01 0. 09 1.13 2.13 0.49 1.99 0. 03
2009 0. 88 0.30 0. 16 0.01 0.07 1.11 2. 03 0.49 1.65 0. 03
2010 0. 89 0.30 0. 09 0.01 0.06 1.13 2.37 0.56 1.76 0.03
2011 0. 79 0.28 0. 08 0. 01 0.05 1.17 2.31 0.58 2.03 0.04
2012 0. 73 0.28 0.11 0. 01 0.04 1.38 2.68 0.57 2.21 0.00
2013 0. 74 0. 27 0.11 0. 01 0.05 1.41 2.69 0. 59 2.13 0.00
2014 0.68 0. 28 0.14 0. 01 0.04 1.39 2.48 0 . 61 1.91 0.00
2015 0.66 0 .31 0.18 0. 02 0.06 1.32 1.94 0. 65 1.56 0.00
2016 0.65 0.33 0.17 0. 02 0.05 1.27 1.82 0. 62 1.42 0. 02
Source: calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/) .
Index (RCA)4. If the trade complementarity is obvious, which means intensive export products of a country are suitable for intensive import products of its partner, the development of their trade relationship and their existing production model could be maintained.
The formula for the trade complementarity index of a single product is:
Ckij = RCAk xi x RCAkmj, RCAk xi = (Xki/Xi) / (Xk w/Xw), RCAk mi = (Mk i/Mi) / (Xk w/Xw).
(2)
(3)
(4)
4 Revealed Comparative Advantage (RCA) is an index comparing a proportion of a specific kind of export goods in a country's total exportations and the proportion of this kind of goods in the global total exportations.
Where XkI and Xkw are separately the exportations of Product k in Country i and the world, Xi and Xw are respectively the total exportations of Country i and the globe, Mk I is the import quantity of Product k in Country i and Mi is the total importations of this country.
According to Product k, if Ckij > 1, the trade complementarity of this kind of products is very strong and if not, the trade complementarity is weak or un-obvious. The higher the value of Ckij is, the stronger the trade complementarity is.
We conclude from Table3 and Table4: (1) From the perspective of the trade complementarity of Chinese exports and Russian imports (Table 3), the complementary effects of labor-intensive products (SITC 6 and SITC 8) and partial capital-intensive/technology-intensive products (SITC 7) are relatively obvious, especially the index of SITC 8 is
MOEAflbHblM MMP M BHEWHflfl nOAMTMKA POCCMM
Table 4
The Value C Calculated by Russia as the Exporting Country
year resource-intensive products labor-intensive products capital-intensive/technology-intensive products
sitc 0 sitc 1 sitc 2 sitc 3 sitc 4 sitc 6 sitc 8 siTC 5 siTC 7 siTC 9
2006 0.07 0. 04 3. 75 3.74 0. 53 0 . 84 0. 05 0.41 0. 12 0. 16
2007 0.10 0.05 4. 17 4.03 0. 58 0. 81 0. 05 0.43 0. 12 0. 13
2008 0. 06 0.06 4.35 3.66 0. 53 0.61 0. 05 0.47 0.11 0. 17
2009 0. 10 0.07 3. 72 4.31 0. 75 0.86 0. 05 0.36 0.12 0. 11
2010 0. 08 0.05 2. 95 3.94 0.34 0.65 0. 04 0.36 0.09 0.56
2011 0. 09 0.06 2. 93 3. 58 0.33 0.52 0.03 0.38 0.08 1.29
2012 0. 15 0.09 2.90 4. 22 0.83 0.59 0.06 0.42 0.11 0.48
2013 0. 15 0. 09 2.94 4 06 0.78 0.54 0.06 0.39 0 . 13 0.67
2014 0.19 0. 11 3.12 4. 74 0.74 0. 63 0.06 0.40 0 . 13 0.59
2015 0.28 0. 17 3.73 7 03 0.88 0. 66 0.08 0.48 0. 16 0.62
2016 0.32 0. 18 4.09 8.57 1.02 0. 72 0.07 0.40 0. 15 1. 93
Source: calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/)/
the most evident and its average is around 2. Especially to deserve to be mentioned, numerical values in Table 3 are relative stable with little fluctuations.
(2) Index of Table 4 reflects the coincidence degree of Russian exports and Chinese imports. The high numerical values gather in the same kind of products, resource-intensive products. Specifically, the indexes of SITC 2 and SITC 3 are very obvious, which could reach up to 3-4. What's more, the trade complementarity indexes of SITC 3 in 2015 and 2016 are respectively 7.03 and 8.57, which are fairly high coincidence degrees in the bilateral trade field.
In order to further clarify the trade complementarity between the two countries, we calculate the comprehensive trade complementarity (Table5) by the following formula:
C = Zk[(RCAxik * RCAmik) * (Wk / W)L
(5)
where C is the index of comprehensive trade complementarity which is a weighted average of all products or all industries, and the weighted factor is the proportion of all kinds of products in the global trade, Wk / W.
In the case of multiple industries, if we don't want to distinguish the exporter, we should first determine the comparative advantages between these two countries. The assumption is that as long as a country has
the comparative advantage in one industry, it would be able to export to its partner whose products in that industry are relative inferior.The formula based on this method is:
C., = 1 £,{[(RCA . * RCA ) *
ijt a biL\ xia mja'
(Xwa / Xw) (RCAxjb RCAmia) (Xwb / ^w^^ (6)
where 1a and 1b are respectively superior product sets for Country i and Country j, Cijt represents the comprehensive trade complementarity index without distinguishing the export country, Xwa and Xwb are global exportations of industry a and b. And we investigate the comparative advantages before.
The complementary relationship between China and Russia is consistent with the stability of the factor endowment and these two countries' comparative advantages (Fig. 4).To be more specific, resource-intensive products have the highest values which would reach up to more than 3 and they always take up the majority of Russian exportations to China.
According to the outcomes of Table 5, all indexes of Chinese exports to Russia are over 1. Albeit to some values less than 1, the indexes of Russian exports to China increase in general. The integral index (Table 6) without export country distinction shows that the volume increased before 2012 which is a year with the highest number of 2.16 and then decreased
Table5
Index of Comprehensive Trade Complementarity
Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Russia as the target country 1. 01 1. 07 1.14 1. 04 1.10 1.14 1.27 1.25 1.20 1.09 1.04
China as the target country 0. 89 0. 92 0. 97 0. 95 0.93 0.98 1.07 1.04 1.10 1.15 1.18
Source: calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/) .
4,00 3,50 3,00 2,50 2,00 1,50 1,00 0,50 0,00
resource-intensive products
labor-intensive products
capital-intensive or
technology-intensive
products
—I-1-1-1-1-1-1-1-1-1-
tf £ & rf? <$> <$>
Fig. 4. Complementarity Index of Chinese and Russian products
Source: Calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/) .
The Comprehensive Complementarity Trade Index without Distinguishing export country
Table 6
Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
C, 1.68 1.77 1.93 1.78 1.87 1.97 2.16 2.12 2.11 2. 01 1.98
Source: calculation based on data downloaded from WITS DATABASE (http://wits.worldbank. org/) .
slightly. On the whole, the comprehensive index is relatively high, which means, in spite of imports and exports, the complementarity of Sino-Russian bilateral trade is very strong.
3. THE POTENTIAL OF siNO-RUssiAN BILATERAL TRADE
The former statistical study indicates that China and Russia have strong trade relationship during these ten years and trade intensity shows an upward tendency. In addition, Import and export products of these two countries have different commodity compositions due to comparative advantages. The complementarity of resource-intensive products strengthens, whereas that of the other two catego-
ries is almost invariable. Taken together, we should further investigate the potential of Sino-Russian bilateral trade.
3.1. Model, variables and sample
The thought of Gravity Model initially comes from Newton's law of gravitational attraction and it has been a main method of studying the international trade, economic behavior and influencing factors. The classical gravity model assumes that the scale of economic cooperation among countries is directly proportional to the total economic volume and is inversely proportional to its geographical distance. The majority of current researches introduce variables, such as whether they are both members of the
Table 7
The names, meanings, expected symbols and data sources of variables
Name Expected symbol Meaning Data sources
LnYCt positive The logarithm of GDP of Chinain year t after using GDP deflator to correct (eliminating price factors) WDI of World Bank Database
LnYFt positive The logarithm of GDP of a foreign countryin year t after using GDP deflator to correct (eliminating price factors) WDI of World Bank Database
APEC positive Whether trade partners are members of APEC (0,1) The APEC official website
LnDISTCF negative The logarithm of the spherical distance between capitals of importing and exporting countries Distance calculator on the website www. geobytes . com
LnDPICF negative Institutional differences between trade partners Dow & Kautarant (2006)
LnDLANCF negative Linguistic differences between trade partners Dow & Kautarant (2006)
LnDCULCF negative Cultural differences between trade partners Hofestede (2001)
LnDRELCF negative Religious differences between trade partners Dow & Kautarant (2006)
APEC organization (Jin Zhuiqiao and Yang Fengmin, 2015) or Shanghai Cooperation Organization (Zhang Ying, 2012), on the basis of classical model, while this improvement is limited to the way of explaining foreign trade flows from an economic perspective. Following the phenomenon that institutional factors play an increasingly prominent role in international economic activities, especially after Nos (1990) proposing proposition system launches trade, scholars has begun trying to expend the Gravity Model from a system-factor perspective (Kolstad and Wiig, 2009; Jiang Guanhong, 2012). In addition, more and more researches support that the differences of informal systems, like languages, cultures and religions, are also vital determinants (Kan Daxue and Luo Li-angwen, 2012; Tian Hui and Jiang Chenchun, 2012; Huang Xinfei, etc., 2013; Song Yimiao, etc. 2015; Liu Hongduo, 2016).Bases on existing studies, we introduce formal and informal systematic factors into our research, such as the differences of systems, languages, cultures and religions.
The modified trade gravity model is as followed:
lnTCFt = a1lnYCt + a2lnYFt +
+ a3APEC + a4lnDISTCF + a5lnDPICF + a6lnDLANCF + + a7lnDCULCF + a8lnDRELCF + £t, (7)
where dependent variables lnTCFt represent the logarithm of bilateral trade volume between China and another foreign country in the year tand the data source is UN COMTRADE database.
The expected symbol and data source of the explanatory variables are shown in Table 7.
We select samples within the scope of the emerging economies because China and Russia both belong to this kind of economic structure and these emerging economics are located on different continents, which show big differences among them. Selecting these countries or regions as samples of Sino-Russian bilateral trade potential, is representative (Jin Zhuiqiao and Yang Fengmin, 2015). And Sample countries and indicators are screened based on data available principles5. Based on the two above considering points, we select Vietnam, Turkey, South Korea, Brazil, Indonesia, Indonesia, Indonesia, and Iran as sample countries and the sample spans between 2002 and 2016. So the quantity of effective samples is 135.
3.2. The analysis of Sino-Russian bilateral trade flows
At first, considering the existence of the panel autocorrelation problem and the phenomenon that panel data is sensitive to the variance of sample data, we do panel hetero-variance and autocorrelation test. The outcome of Hausman test indicates that the evaluated outcome of fixed effects model is more ideal than that of random effects model and the former one is suitable
5 The data of culture differences comes from Hofstede(2001), At first, we should remove the excluded countries and then we select four dimensions of PDI, IDV, MAS and UAI in Hofstede (2001) due to some countries missing IND and LTO indictors. On this basis, we construct culture difference index variables combining the method of Kogut and Singh (1988).
to our research. Then regarding the differences of system, language, culture and religion, and geographical distance would be unchanged over time, we use the least squares dummy variable model (LSDV) and then consider time effects, termed bidirectional fixed effects. Last but not least, we do the multi-collinearity test because there may be some multi-collinearity problems among differences of systems, languages, cultures and religions6. The regression results of the model are consistent with rational expectations, the regression coefficients of all variables are highly obvious and we get the empirical equation:
lnTCFt = 2.03lnYFt + 0.89APEC + 0.71lnYCt-
CFt Ft Ct
- 0.32lnDLAN„„ - 0.29lnDCULT,-
■ 0.16lnDIST - 0.12lnDPL
■ 0.11lnDREL. (8)
3.3. Evaluating the potential
The significant application of trade gravity model is estimating the potential of bilateral trade flows among countries, which means estimating development potential of bilateral trade flows through comparing the actual trade flows and theoretical ones calculated by gravity model.
There are two ways to estimate trade potential. The first one was used by Liu and Jiang (2002) firstly. They used trade gravity model to empirically analyze the main factors determining bilateral trade flows between China and other countries, and proposed methods to measure trade potential by the ratio of real bilateral trade volume (T) and analog value (T*). Then they divided bilateral trade potential among countries into three categories: (1) Potential Remodeling (T/T* > 1.2), the trade potential of trade partners in this kind is limited and there could be a relatively large spacious room for trade development under circumstance of new positive influencing factors. (2) Potential Development (0.8 < T/T* < 1.2), there is still trade potential between trade partners in this kind and it has certain space to expand bilateral economy and trade as well. (3) Potential Huge (T/T* < 0.8), there is a massive trade potential between trade partners in this kind and it is a good choice for the trade partners to remove bilateral trade barriers in order to promote the normal trade development.
6 Generally speaking, if VIF>10, there exists severe multiple collinear; if 5 < VIF < 10, there exists a degree of multiple collinear conditions; if VIF<5, there is no multiple collinear. The VIF values in results of the model test are all under 5, which indicates there exists no multi-collinearity problem. In other words, if you do not include the above explanatory variables, there could be a variable-missing problem.
Nowadays, the current researches on the potential of China and other countries often use this method such as Bi and Shi (2011) estimated the trade potential between China and East Asian countries, and Li (2013) estimated the goods trade potential between China and Korea.
However, the method of Liu and Jiang (2002) is only used to estimate the relative size of trade bilateral potential under existing trade conditions and it has not estimated concrete values. The study method of Wilson Mann and Otsuki (2003) is different. They got empirical equation through doing gravity model regression of trade flows of APEC members. In addition, they enhanced trade facilitation level below average to the average level and substitute it into the empirical equation for purpose of estimating trade potential result from trade facilitation improvement.
This paper comprehensively uses two research methods. At first, use the ratio of real gross trade volume and simulated fitting value to measure the Sino-Russian bilateral trade potential, and the outcome is showed in the Table 8.
As data in Table 8 show, Sino-Russian bilateral trade potential fluctuated around 1 with slightly increasing in recent years. This phenomenon illustrates the whole trade form between China and Russia belongs to potential-development type and there is a relatively large space for their bilateral trade development.
Based on this, we reduce the difference in the Sino-Russian informal system, like linguistic difference and cultural difference, to a certain percentage and then analyze the trade potential brought by the improvement of familiar degree in language, culture and other aspects. Taking year 2016 as an example, if the distance of language or culture between China and Russia could reduce 10 percent, the bilateral trade potential could be promoted 3.2% and 2.9% respectively. Thus, it is effective to promote bilateral trade development through improving familiar degree of language, culture and other aspects.
4. conclusions
To sum up, the volatilities of Sino-Russian bilateral trade volume and growth rate are both strong and the future trend is not very clear. The commodity structures of these two countries are different because of comparative advantages. From a trade-balance perspective, China's trade surplus has been shrinking and the balance of trade between China and Russia has improved. Additionally, the complementarity and intensity of their products are relatively evident and
Table 8
Sino-Russian Bilateral Trade Potential
Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Trade potential 0. 96 1.07 0. 99 0.89 1. 05 1. 04 1.07 1. 06 1.06 1. 05 1. 07
keep steady with slightly increasing trend, and the complementarity of resource-intensive products is the most distinct one, whereas that of the other two categories is almost invariable and at relative low level. What's more, from the potential point of view, the whole trade form between China and Russia belongs to potential-development type and there is a large space for their bilateral trade development. It could be effective to develop bilateral trade through improving informal-system familiar degree. Based on the above empirical analysis, we give following suggestions:
(1) Further deepen the cooperation mechanism.
There are many existing mechanisms of cooperation between China and Russia. Specifically, they are both members of Asian-Pacific Economic Cooperation (APEC), Shanghai Cooperation Organization (SCO), as well as belong to BRICS. One Belt One Road (OBOD) initiative proposed by Chinese president Xi and Eurasian Economic Union proposed by Russia have lots of common interests and cooperation opportunities. The two countries, China and Russia, should not only strengthen the docking and cooperation of existing mechanisms, but also establish some new cooperation mechanisms. They should maintain the comprehensive strategic partnership, start bilateral trade and investment facilitation negotiations, perfect dialogue mechanism, cooperation on more potential fields and develop a long-term and operational outline for economic and trade cooperation.
(2) Gradually improve the trade structure
We found within the former results that export products of both countries have obvious differences and trade complementarity is very evident especially in resource-intensive products. Although comparative advantages determine the type of export products and merchandising the goods with high complementarity is reasonable, strengthening other types of commercial trade could promote the overall development of Sino-Russian trade. The process of optimizing the structure of commodities should be gradual because too fast change could lead to instability of total trade and domestic markets, even the global market. And improving commodity composition does not mean transferring the trade amount of previous high-proportional products to other categories, it is a method
to improve the volume of low-proportional products on the basis of original trade situation. In order to seize the cooperation opportunity to seek common development, both countries should strengthen infrastructure construction, such as the construction of pipelines and transportation, which could guarantee the development of transaction and trade.
(3) Strengthen the construction of Sino-Russian free trade area
Establishing Sino-Russian free trade area is a beneficial method to accelerate the development of their bilateral trade and it is a field that worth concerning, negotiating and promoting. We argue that expending the scale of free trade area after succeeding in some particular areas would be an effective measure. Trade partners should negotiate following the principle of reciprocity and mutual benefit. Meanwhile, they should reinforce private transaction. On one hand, it could stimulate each part to participate in Sino-Russian trade to promote the overall trade. On the other hand, it could be conducive to the diversity of products which has the possibility to promote the trade balance.
(4) Enhance the cultural communication
The communications between China and Russia could be traced back to ancient times. The Silk Road gives these two countries chances to indirect with each other and since then the exchanges between China and Russia have not been interrupted. Although they have different languages, civilizations and religions, China and Russia should accept the attitude of mutual understanding to keep the good relations of peaceful coexistence, for sake of common development. Admittedly, enhancing familiarity could be beneficial to the economical development and it is one of the foundations of building trade trust. There are some measures to enhance the mechanism of cultural communication, such as establishing more Confucius institutes, holding Sino-Russian cultural year, exchange of overseas students, holding regular forums and culture events, and promoting development of their tourisms. Moreover, the One Belt One Road initiative is an essential opportunity to constantly improve the scale and level of cultural exchanges between China and Russia.
