BY MOK KA YAN A PROJECT SUBMITTED IN PARTIAL …libproject.hkbu.edu.hk/trsimage/hp/09010408.pdf · Russia, in her exports（李永華、畢崇志，2008；李春豔，1999；趙傳君，2010；

BY

MOK KA YAN

STUDENT NO. 09010408

A PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE DEGREE OF

BACHELOR OF SOCIAL SCIENCES (HONOURS) DEGREE IN CHINA STUDIES

ECONOMICS OPTION

HONG KONG BAPTIST UNIVERSITY

APRIL 2012

09010408/China Studies - Economics Option/Honours project (Spring 2012)

HONG KONG BAPTIST UNIVERSITY

April 2012

We hereby recommend that the Project by Miss. Mok Ka Yan entitled “Sino-

Russian Trade: Empirical Studies of increasing the export value of China –

Upgrading China’s Trading Structure” be accepted in partial fulfillment of the

requirements for the Bachelor of Social Sciences (Honours) Degree in China Studies

in Economics.

_______________________ _______________________

Dr. LI, Sung Ko Dr.

Project Supervisor Second Examiner


Acknowledgements

I would like to thank my supervisor Dr. LI, Sung Ko for his kind help,

suggesting the research methods and guiding me through the entire study, and Dr. Bill

Hung for his website and his suggestions which assist me in computing work.

__________________________

Student signature

China Studies Degree Course

(Economics Option)

Hong Kong Baptist University

Date: ____________________


Table of Contents

Abstract

I. Introduction 1-2

II. Literature Review 3-5

III. Background and History 6-9

IV. Current Situation 10-15

V. Revealed Comparative Advantage (RCA) – in the world case 16-21

VI. Revealed Comparative Advantage (RCA) – in two countries case 22-25

VII. Trade Combining Density Index (TCD) 26-28

VIII. Empirical Result 29-59

i. Part 1 - Empirical Result on China’s exports to Russia

ii. Part 1 - Regression Model Implication

iii. Part 2 - Empirical Result on Upgrading China’s Trading Structure to Russia

iv. Part 2 - Regression Model Implication

v. Model Limitation and Suggestion

vi. Suggestion to the Sino-Russian trade

IX. Conclusion 60

X. Appendix 61-66

i. Part 1- Descriptions of variables

ii. Test for part 1 of regression

iii. Part 2- Descriptions of variables

iv. Test for part 2 of regression

XI. Bibliography 67-72

i. 中文文獻

ii. 中文參考書籍

iii. 中文報章

iv. 中文網頁

v. English Literature

vi. Online sources

vii. News

viii. Statistics sources


Abstract

China and Russia are two great and rising economic powers, and they have the

longest boarder. Their trade relations do have great potential power in further

development.

In this paper, we would use three methodologies in finding out their trading

structure, their trade relationship and the determinants that improve the Sino-Russian

trade, namely the Revealed Comparative Advantage index, the Trade Combining

Density Index (TCD), and two parts of regression model.

There are four major important findings. First, the Sino-Russian existing trading

structure matches the market of each other. China mainly exports manufacturing

products (either labour-intensive and high skilled or high-technology products) to

Russia, and Russia mainly exports primary products and fuels to China.

And, their existing bilateral trade relationship is not close enough when

compared to other trading partners of China, and could be further improved.

Third, there are several factors that significantly affect the exports value from

China to Russia, namely, per capita GDP of Russians, high-skilled and technology

intensity exports, exchange rate, and financial crises. And we discover the inefficient

of Russian tariffs in limiting China’s exports to Russia, and trade agreements in

facilitating their trade.

Forth, one of the methods that could increase the exports to Russia is to improve

the export structure by China, i.e. to export more high-skilled and technology

intensity exports. The method to increase its proportion could be done by attracting

more FDI in this field, increasing the R&D expenditure and to increase the number of

researchers in the R&D process. And we notice that increasing the Government

expenditure and increasing the number of firms in this field are not very effective in

raising its exports value.


1

I. Introduction

China and Russia have a very good cooperation and geographical background in

trade. For example, they are both emerging economies, and transformed from planned

economies into market-based ones, so they were both transition countries from

socialism, and are now the emerging powers in BRICS. They are also the largest

neighbor of each other, with 4,300 kilometers border and more than 20 trade ports.

And they have a long history (from the year 1653) of cooperation and relationship.

Sino-Russian trade is improving in the past years, and the Governments of the

two countries also have intention to boost their bilateral trade. They has reached

USD560 billion in 2010, and it reached USD719 billion in 2011. The year 2011 is the

10th anniversary of the signing of “The Treaty of Good-Neighborliness and Friendly

Cooperation between the People's Republic of China and the Russian Federation”

(FCT). It is also the 15th anniversary of the establishment of Sino-Russian strategic

partnership. And both China and Russia wanted to increase trade with each other. In June

2011 when China’s President Hu Jintao visited Russia, he announced the blueprint for

development of their bilateral relations in the next 10 years. In the blueprint,

Sino-Russian bilateral trade goal will be developed to USD1000 billion in 2015, and

increased to USD2000 billion in 2020.

As they have geographical and developmental advantages as mentioned

above, and the economic recession due to the dissolution of Russia (1992) has

pasted; the GDP of Russia have increased much in recent years, the purchasing

power of Russians boosted. So, we started to look whether China’s exports could,

and how it could further grab the import market of Russia.


2

So, in this project, we aim to find out (1) whether China and Russia have

incentives to continuous or further increase their trade with each other; (2)

whether the existing trade is close enough, (3) from China’s perspectives, the

determinants that affect China to increase her export value to Russia, and (4)

how China could improve her export structure to Russia in order to increase

trade or even grab the import market of Russia.

In the followings, the project will be divided into 4 major parts. In the first part,

we would look at the literature review, background and the current situation of

Sino-Russian trade. Second part would contain the analysis of Revealed Comparative

Advantage, both assuming in the world case and in two countries case, and also the

analysis of Trade Combining Density Index (TCD). The third part would be empirical

analysis about increasing the exports of China to Russia, and suggestions to improve

Sino-Russian trade partly based on the regression result.


3

II. Literature Review

There have been a number of academic researches carried out in arguing the

Sino-Russian trade could be increased in value, the major reasons for saying that are:

(1) their trade development does not match with the political development; (2) the

export structure for both countries should be improved; (3) Russia has imposed many

trade barriers for China’s exports, which hinder the development of their bilateral

trade. (4) The problem of “Grey customs clearance”. And there is a great potential for

China to more rely on the trade with Russia, especially after the financial crises in

USA and the potential of outbreak of European Bond Crisis.

For the first reason, scholars suggest that the value of bilateral trade between the

two countries have been relatively low when compared with the trade value of China

and Russia with other countries respectively（魏浩，2008；董銳，2010）.They think

that this phenomenon do not match with their political and strategic cooperation

relations（楊希燕，2005；曹英華，2007）, and also their needs for economic

development (i.e. they need to trade with each other for facilitating their economic

development in their own countries)（彭傳江、王麗英、周立，2004）.Also, as they

are both the emerging power of BRICS, the economic and trade cooperation should

not be that low（丁振輝；2010）, thus the bilateral trade value should be improved.

Moreover, there has been trade deficit for China continuously before 2007. Some

scholars suggested that the reason to explain this phenomenon is that Russia has long

been the exporter of resources, especially power sources（張紅燕，2004；曹英華，

2007；馬健美、趙岩，2010）. More importantly, it is due to the low-level export

structure of China, i.e. China only export low value-added consumer goods, such as


4

textiles, food and shoes（劉紅雨，2008；董銳，2010；任賢慧，2007）. Although

the trade deficit phenomenon has been improved after 2007, the low value-added and

labour-intensive export structure of China still hinders the growth in trade.

Third, there are many trade barriers imposed by Russia towards China’s exports.

Explicit trade barrier is mainly the high tariff rate, such as the high tariff imposed on

costume and shoes in 2010, which is direct against the China’s exports which have

comparative advantage（董銳，2010；魏浩，2008；石艾馨、李嬌，2008）. And there

are implicit trade barrier like the increase in the requirements for technical and safety

level of China’s exports（任鐵爭，2010）. These trade barriers imposed by Russia limit

the growth of China’s exports to Russia.

The last that hinder their trade is “Grey customs clearance” and “Baoji

Baosui”(smuggling), which leads officials underestimate the trade value between the

two countries（魏浩，2008；劉士濤、王乾，2006）. As these smuggling activities

are very common for Chinese merchants to export to Russia, the values of export by

these kind of method are considerably high（李永華、畢崇志，2008）.Thus, after

counting the value of these underground activities, the export value for China to

Russia should be greater（馬健美、趙岩，2010）.

On the other hand, some suggests that technical and technological level of China

exports (to Russia) should be improved in order to improve the trading structure. For

example, China should focus on exporting machines, electronic appliances and

high-technology products（李青；2001；韓立華，2001；李澤祥、楊定華，2003；

劉紅雨，2008）which are already increase slowly in the proportion of exports for

China to Russia.


5

Last but not least, scholars generally take a positive attitude towards the

foreground of Sino-Russian trade. Some of them even point out that the Financial

Tsunami in the US and the European Bond Crisis means China could no longer rely

on the unstable US and European countries in trade. And apart from expanding the

domestic market of China, China should rely on another big and rising economy –

Russia, in her exports（李永華、畢崇志，2008；李春豔，1999；趙傳君，2010；

趙鑫，2010）.


6

III. Background and History

i. Early stage:

China and Russia have been old trading partners with each other for more than

300 years. They signed the Treaty of Nerchinsk in 1689 to start bilateral trade. At the

beginning, they set Heilongjiang as the main area for Sino-Russian trade.

After the establishment of People’s Republic of China, the great diplomatic

relations between the two countries led to rapid development in their trade. For

example, the new government of China signed a number of free trade agreement,

agreement for the navigation of frontier rivers, tributaries, and lakes, and also giving

Most Favored Nation (MFN) to each other. These agreements led them became the

top trading partner with each other.

During the Cold War period, there was a Sino–Soviet split caused by the

worsening of political and ideological relations between them. They broke ties in

1966. This decreased the dependency for China towards Russia’s exports, and greatly

and directly affected trade. Their trade value had dropped from USD 82.79 million in

1960 to only USD 4.7 million in 1970. The trade value rose slowly in the 1970s,

although there was still confrontation between them.

ii. Late 1991 to 1993: Rapid development stage (First climax)

The dissolution of Soviet Union took place in late 1991. The China's State

Council and Ministry of Foreign Trade had issued a series of policies which

encouraged the scale-up of border crossings trade with Russia.


7

During 1992 to 1993, after Deng Xiaoping visited the southern part of China and

encouraged opening up and construction of China1, which speeded up the construction

of basic facilities, leading to large increases in imports for construction materials from

Russia (accounted for 39% of China’s imports from Russia). On the other hand, China

mainly exported consumer goods and food to Russia in order to fulfill the needs of her

market (accounted for 45% of her exports to Russia). In this period, most trade

belonged to barter trade. And the two countries exempted tariffs and other customs

duties of each other in order to facilitate trade2.

iii. 1994 to 1995: Great declination

Although their relations changed from "partnership" in 1992 to "constructive

partnership" in 1994; there was a shrink in trade. The following three reasons could

explain this: First, the Russian government had strengthen the macroeconomic

regulation and control towards trade, e.g. imposing a trade quota system on the export

of raw materials, increasing the tariffs for both imports and exports, and implementing

licenses on some export industries. Second, the quality of life for Russians had

improved, which increase their requirements towards the quality of goods. And at the

same time, there were more and more counterfeit commodities from China entered the

Russian market, which led to bad reputation of China’s products.

1995 was also the turning point for Sino-Russian trade. It was greatly contributed

by the signing of Sino-Russian Joint Communique, which decided to change from

1劉德喜：〈中俄夥伴關係中的經貿關係〉，《從同盟到夥伴－中俄（蘇）關係 50 年》，中共黨

史出版社，2005 年，頁 270。

2 蒒君度、陸南泉：《中俄經貿關係》，中國社會科學出版社，1999 年，頁 101-102。


8

barter trade to payment in cash that was already accepted by the international world.

This helps to standardize the mode of trade, and the trade value between them started

to increase again.

iv. 1996 to 1999: Adjustment of bilateral trade

The two Governments reached an agreement to increase their bilateral trade to

USD 80 to 100 billion. Russia agreed to export more natural gas, oil and energy

devices to China; while China agreed to export more labour-intensive products (e.g.

textiles) and high skilled and technology intensity products (e.g. chemicals) to Russia.

They both agreed to focus more on high-technology products and energy in their

trade3.

v. 21st century: Further cooperation

As the Russian market became more prosper and stable, the index for Russians’

quality of life rose from ranking 66 in 2000 to 55 in 2001, with the further

encouragement by the two governments towards bilateral trade; the trade value

reached higher. In 2004, the two Governments had set a target that in 2010; their

bilateral trade should reach USD 600 to 800 billion4. They agreed to improve their

trading structure5 that China should export more machinery, high value-added

products, and high skilled and technology products to Russia. And Russia agreed to

export more energy devices and energy sources to China.

3蒒君度、陸南泉：《中俄經貿關係》，中國社會科學出版社，1999 年，頁 108-112。

4 《中俄總理簽署第九次定期會晤聯合公報》，中華人民共和國外交部，2004 年 9 月。

5 陸南泉：《中俄經貿關係現狀與前景》，中國社會科學出版社，2011 年，頁 147-152。


9

The leaders of two countries also exchanged visits frequently for international

issues and bilateral trade relations. In 2001, they signed the “Treaty of

Good-Neighborliness and Friendly Cooperation”6 in order to develop a strategic

partnership in trade and military aspects. In the treaty, China could obtain a stable,

consistent and affordable level of fuel shipments, and she could better purchase and

deliver Russian oil, including the construction of a Trans-Siberian oil pipeline.

The leaders of the two countries had visited each other and signed

joint-statements almost every year. The Governments also launched a number of

policies to promote trade, e.g. the "Country Year" activities (2006) and the Year of

Russian language (2009). Sino-Russian trade relations were stabilized.

Moreover, as the problem of "Grey customs clearance" (the goods entering

Russia in this way is to avoid issuing official customs declaration documents, which

decrease the great costs of tariffs by Russia) has been a major problem of their trade

since the late 1980s, which caused Russia underestimate her import value from China,

and decreased her revenues from imposing tariffs. The Russian Government started to

fight against the problem since 20097.

After the financial tsunami and the high chance of the outbreak of European

Crisis, people started to think of the possibility for the two countries to set up

tariff-free area, and expected the two countries to improve their trading structure to a

more high-tech and high value-added trade. By doing so, they expected Sino-Russian

trade would be another chance for the revival of their economies.

6 “Treaty of Good-Neighborliness and Friendly Cooperation Between the People's Republic of China

and the Russian Federation”, Ministry of Foreign Affairs, the People's Republic of China. Retrieved

February, 24, 2012.

7 "China, Russia work to facilitate normal custom clearance", People's Daily Online, March 26, 2010.

Retrieved from :http://english.people.com.cn/90001/90776/90883/6932278.html


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IV. Current Situation

In this part, we would first look at the ranking of Russia as China’s trading

partner, then describe the trade balance and the trend for Sino-Russian trade. And last,

we would have an in-depth look at the export and import structure of China with

Russia.

There has been generally an increasing trend for the Sino-Russian trade, both

from China’s exports and imports’ view. First, from table 1, we notice that Russia

ranked 9th

as the importer of China’s products in 2011, with the value of USD389.038

billion. And her ranking has been increasing as she only ranked 13th

as China’s

importers in 2010. Also, the percentage increased in the export value (from China’s

perspective) was the largest among the top importers of China’s products. This, on

one hand because the Financial Tsunami led to decrease in exports; and on the other

hand, may mean Russia has great potential in buying China’s exports in the future.

Table 1:

Top trading partner of China (exports from China) in 2011(Jan-Dec)

Ranking Name of the country Value

(in thousands USD)

% increased

(compared with 2010)

1 European Union $356, 019,832 +14.4%

2 United Nations $324, 492,718 +14.5%

3 Hong Kong (China) $268, 025,399 +22.8%

4 Southeast Asian Nations $170,083,006 +23.1%

5 Japan $148,298,069 +22.5%

6 Korea $82,923,617 +20.6%


11

7 Holland $59,500,012 +19.7%

8 India $50,543,174 +23.5%

9 Russian Federation $38,903,829 +31.4%

10 Singapore $35,570,443 +10%

(Generated from: the General Administration of Customs of the People’s Republic of

China)

From the imports perspective of China, Russia was the 11th

exporters to China in

2011, with the import value USD 403.455 billion by China. The ranking also rose

when compared with last year which only ranked 12th

in 2010. And the import value

by China from Russia had increased by 55.6%, which was also the largest among the

top trading partners (table 2).

Table 2:

Top trading partner of China (imports by China) in 2011(Jan-Dec)

Ranking Name of the country Value

(in thousands USD)

% increased

(compared with 2010)

1 European Union $211,193,001 +25.4%

2 Japan $194,591,317 +10.1%

3 Southeast Asian Nations $192,770,814 +24.6%

4 Korea $162,709,438 +17.6%

5 Taiwan $124,919,879 +7.9%

6 United Nations $122,153,945 +19.6%

7 Germany $92,716,442 +24.9%

8 Australia $82,722,742 +35.3%

9 Malaysia $62,144,743 +23.2%


12

10 Brazil $52,359,344 +37.3%

11 Russian Federation $40,345,471 +55.6%

(Generated from: the General Administration of Customs of the People’s Republic of

China)

Throughout the period of 1997Q1 to 2010Q4, the bilateral trade balance (exports

minus imports of China) fluctuates, with mainly trade deficit for China before 2007.

Yet, in recent years, from figure 1, we know that except for the period during the

Financial Tsunami, there has been mainly a trade surplus for China in their bilateral

trade.

Figure 1 – the trade balance for Sino-Russian trade

(China’s exports to Russia minus China’s imports from Russia)

(Generated from:《中國統計年鑑》)

The trade between the two countries is generally in an increasing trend (figure 2

and 3). One thing that we should notice, i.e. it clearly shows that the financial crises


13

(in 1997 and 2008) have some short-term effects on their trade value. These two

figures show that their trade with each other only drops suddenly after the broke out

of the financial crises, and then increased and recovered to the original level very

rapidly. The Financial Tsunami in 2008 has a greater effect on their trade when

compared with the Asian Financial Crisis in 1997.

Figure 2: Total exports value from Russia to China


Figure 3: Total imports value for China from Russia



14

On the other hand, for their trading structure, the export structure of China to

Russia (figure 4) indicates that the top three categories of products that China export

to Russia includes: (1) labour-intensive products, like textiles and shoes; (2) heavy

industrial products which is capital intensive, i.e. base metals; and (3) the proportion

of high skilled and technology intensity products, i.e. electronic products and

machinery, increased rapidly.

Figure 4: Exports structure of China to Russia (by products)

(Generated from: 《海關統計 1997-2010》)

On the other hand, the import structure of China from Russia (figure 5) indicates

that the top two categories of products that China import from Russia includes: (1)

raw materials, i.e. minerals; (2) heavy industrial products which is capital-intensive,

i.e. base metals; and (3) relatively high technology intensity products, i.e. chemicals

and related industrial products.


15

Figure 5: Imports structure of China to Russia (by products)

(Generated from: 《海關統計 1997-2010》)


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V. Revealed comparative advantage (RCA) in the world case

As we aim to find out whether the Sino-Russian trade could be further increased

in the future and particular whether the China’s exports could grab the imports market

of Russia, we would first see whether their existing trading situation matches the

needs of the market of each other. That means whether they would be complementary

in trade. So, in the following, we would calculate the revealed comparative advantage

of both China and Russia, and see which types of products they are better to produce

for trade. It is the first step to see whether the two countries could increase their trade,

and then we would look further whether their existing trade is close enough and how

China could further raise exports to Russia in latter parts. So, from this, we can look

in-depth whether their existing trading structure is complementary with each other.

The law of comparative advantage states that a country which has the ability to

produce a particular good or service at a lower marginal and opportunity cost means

she has a comparative advantage. It guides the direction of trade, i.e. the country

which has comparative advantage in produce a particular product should be the

exporter, and vice versa should be the importer. So, countries would base on it to

adjust their trading structure.

The quantitative indicators for calculating the comparative advantage is

“Revealed Comparative Advantage” (RCA), which was first suggested by Balassa

(1965)8. He suggests that the comparative advantage could be “revealed” by the

observed trade patterns, and this matches with the theory. Some researches counts

8 Balassa, B. (1965), Trade Liberalisation and Revealed Comparative Advantage, The Manchester

School, 33, 99-123.


17

RCA at global level (e.g. Vollrath, 1991)9, at a sub-global or regional level (Balassa,

1977)10

, and some evaluates the measurement as bilateral trade between two countries

or trading partners (e.g. Dimelis and Gatsios, 1995)11

. And this project would use

RCA index to measure the last type.

RCA is based on observed trade patterns. The RCA measures a country’s exports

of a commodity relative to its total exports. The formula for calculating RCA is

illustrated as:

RCAik =

where Xik is the exports value of k products in Country I, Xi is the total exports in

Country I, Xk,world is the exports of k products in the world, and Xworld means the total

world exports value. Accordingly, if the RCA index of the export product of Country

I is greater than 1, it has a comparative advantage in exporting that product, i.e. it has

a relatively stronger export competitiveness, and vice versa. In the table, for ease of

9 Vollrath, T.L. (1991), “A Theoretical Evaluation of Alternative Trade Intensity Measures of

Revealed Comparative Advantage”, Weltwirtschaftliches Archiv, 130, 265-79.

10 Balassa, B. (1977), “’Revealed’ Comparative Advantage Revisited”, The Manchester School, 45,

327-44.

11 Dimelis, S. and K. Gatsios (1995), “Trade with Central and Eastern Europe: The Case of Greece”,

in R. Faini and R. Portes (eds.), EU Trade with Eastern Europe: Adjustment and Opportunities, London:

CEPR.


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understanding, we use (*) for products with strong export competitiveness, and use

(**) for extremely strong export competitiveness12

.

Since the data from the database on international merchandise trade by the WTO

(CIS)13

includes almost all of the products traded between Russia and China, and it is

simpler for making comparison than the SITC or the HS-code; we choose the CIS as

the data set for calculating the RCA of the two countries.

As shown in tables 3 and 4, we can classify these sixteen types of export

products into three categories:

Table 3: Revealed Comparative Advantage (RCA) of China

12

The standard of giving (*) and (**) is according to the Japan Export Trade Research Organization

(JETRO) which state that RCA>1.25 means the product is with strong export competitiveness. And for

RCA>2.5, it means the export product is with extremely strong export competitiveness.

13 Time Series on international trade, World Trade Organization. Retrieved January 30, 2012, from:

http://stat.wto.org/StatisticalProgram/WSDBStatProgramHome.aspx?Language=E


19

(The above calculations of RCA are based on the database by the WTO)

First, for the export products that China has obvious comparative advantage than

that of Russia, i.e. textiles(15), clothing(16), office and telecom equipment(10),

electronic data processing(11) and office equipment and telecommunications

equipment(12). The first thing to note is that China has a strong comparative

advantage in the fields of textiles (15) and clothing (16). The major reason for this

phenomenon is that there is a large endowment of low-skilled and cheap labour

resources in China (about 13 billion of population). And China had developed in these

industries for many years, leading her to have relatively mature skills. This lead the

cost of production for textiles and clothing industries become lower than that of

Russia. On the other hand, the RCA of these two products for Russia has been low

throughout the years and even has a decreasing trend; it is mainly because of its slow

industrial development. And since some other countries are developing its industrial

sector rapidly but Russia are still relying on other sectors, RCA index for these two

products are decreasing. The second things to note is that the RCA index for (10), (11)

and (12) are high and have an increasing trend for China. It is because Chinese

companies no longer focus on developing low-skilled, low-cost, low-margin

industries, but are trying to move up the value chain to high-skilled and

high-technology. Also, the Government uses incentives to encourage companies to

innovate and discourage low-end manufacturers from operating in southern China. So,

Government policies are now more favor high-tech economic zones, research and

development centers and companies14

. This leads the fields of (10), (11) and (12) to

14

David Barboza (2008, August 1), China’s Ambition Soars to High-Tech Industry, The New York

Times.


20

develop, and lead these export products have comparative advantage. And for Russia,

although she has the second largest high-skilled labour resources in the world, the

Government does not give encouragement to these high-tech fields like that of China;

she does not have a comparative advantage in it throughout the years, and her

comparative advantage in the high-tech export products are increasing but in a slower

process.

Second, for the export products that Russia has obvious comparative advantage

than that of China, i.e. fuels and mining products(3), iron and steel(6) and fuels(4). It

is because there is a large amount of mineral resources in Russia. And Russia is also

the top three oil producer in the world market, and she has the largest reserves of

natural gas. Also, she has rich forest resources, and her reserves in timber accounted

for 25% of the world reserves. This explains why she has a comparative advantage in

these exports products. Also, China is the top “consumer” for fuels and mining

products as she is the “world factory”. For example, in 2010, half of the oil consumed

was imported15

. So, this explains why China does not own a comparative advantage in

them. On the other hand, we can note that the value of RCA index for the three types

of export products for Russia has been decreasing. It is mainly due to government

policies of tightening the export of fuels and raw materials.

The third category is the export products that both China and Russia do not own

comparative advantages, such as chemicals (7), machinery and transport equipment

(9), automotive products (14), etc. For China, there is a decreasing trend of the RCA

index for both primary and secondary labour-intensive products. Yet, the RCA index

15楊希燕（2005）：〈中俄貿易增長探析與前景預測〉，《現代財經》，第 25 卷第 190 期。


21

for the technology-intensive products is increasing. On the other hand, for Russia, the

RCA for primary products, (1) and (2), are increasing. And for the secondary products,

it has not changed much. This means Russia do not have a rapid development in these

export products. And as Russia still imposes many restrictions towards her export

industry, the RCA index for these products has been in a low level.

All and all, we know that in 2000 to 2010, China has comparative advantage in

labour-intensive export products, and she has been developing her comparative

advantages in high-technology products by companies’ incentives and Government

policies in recent years. And for Russia, during the period, she has comparative

advantages in fuel, raw materials and related products. Yet, her RCA in products other

than these has not changed much.

Table 4: Revealed Comparative Advantage (RCA) of Russian Federation

(The above calculation of RCA are based on the database by the WTO)


22

VI. Revealed Comparative Advantage in two countries case

In this part, we consider only the trade between China and the Russian

Federation. The purpose of assuming this is to have an in-depth look at the

comparative advantage of each type of products between these two countries. The

RCA in this part measures a country’s exports of a product relative to the total exports

of the two countries. The formula of calculating this is:

RCAik =

where Xik is the exports value of k products in Country I, Xi is the total exports in

Country I to Country J, Xk,ij is the total exports of k products by Country I and J, and

Xij means the total world exports value of Country I and J. Accordingly, if the RCA

index of the export product of Country I is greater than 1, it has a comparative

advantage in exporting that product, i.e. it has a relatively stronger export

competitiveness, and vice versa. In the table, for ease of understanding, we use (*) for

products with strong export competitiveness, and use (**) for extremely strong export

competitiveness16

.

In this project, since we are trying to know their possible trading structure by

comparative advantage, we choose the UNCTAD statistics17

(which use the SITC

code) as the data set for calculating the RCA of the two countries. And we have

16

The standard of giving (*) and (**) is according to the Japan Export Trade Research Organization

(JETRO) which state that RCA>1.25 means the product is with strong export competitiveness. And for

RCA>2.5, it means the export product is with extremely strong export competitiveness.

17 UNCTAD Statistics, United Nations Conference on trade and development. Retrieved February 19,

2012, from: http://www.unctad.org/Templates/Page.asp?intItemID=1584&lang=1


23

divided the products into different categories to have a closer look at their

comparative advantage, namely primary products, low-to-medium skilled products,

and high-skilled products.

Table 5: Revealed Comparative Advantage (RCA) of China (2 countries case)

(The above calculations of RCA are based on the UNCTAD statistics)

Table 6: Revealed Comparative Advantage (RCA) of Russia (2 countries case)


24

(The above calculations of RCA are based on the UNCTAD statistics)

From the table, for products that China has comparative advantage relative to

that of Russia, it includes low-to-medium skilled and high skilled products. We can

clearly note that she is a bit more competitive in low-to-medium skilled products than

that in high-skilled products. It is because China has long been developed in industries

without high technology or skills; for example, manufacturing and textiles industries.

So, she is more experienced and mature in developing the low-to-medium skilled

products. Yet, there is a decreasing trend in the comparative advantage for

labour-intensive and resource-based manufacture products. The reason is that with the

mature development in the secondary industries, China no longer needs to focus on

producing these products which greatly waste the resources of China. So, the Chinese

Government started to decrease the percentage of these industries in operating in main

parts of China. On the other hand, there is an increasing trend in the comparative

advantage for other secondary industrial products in China; for example, the RCA for

manufactures products with low skill and technology has been increased from 0.100

to 1.521 during 2000 to 2010. And the products with high skills and technology also

doubled in the period. This shows the Government’s effort in encouraging high

technology which somehow improves the trading structure of China. Yet, for Russia,

the situation just reverses. On one hand, it is because of the faster development of

secondary industries in China; on the other hand, it is due to the too much reliance of

primary industries for Russia.

Secondly, for products that Russia has more comparative advantage than China

in this two-country case. They are mainly primary products. And except for iron and

steel, all other primary products have an increasing trend in comparative advantage,


25

with the RCA value doubled. This shows that comparatively, Russia developed better

in them, and would focus in exporting primary products.

Thirdly, there is only iron and steel product that both Russia and China do not

have stable comparative advantage in it, and the RCA index for both countries in this

product has been fluctuated. It is because both Russia and China have great

development and export in this field. China has great steel production and

consumption, and her crude steel production has ranked first in the world for 13

consecutive years18

. And Russia's ferrous metallurgy industry investment plans have

improved her development in this type of product19

To conclude, when we consider only two trading members, China has a

comparative advantage in secondary products (for both labour-intensive and

technology intensive), and Russia is more competitive in exporting primary products.

18

餘華彬（2010）：〈重估中國鋼鐵工業發展空間〉，《金融實務》，2010 年第 2 期。

19 〈新興國家鋼鐵產業發展：俄羅斯產量迅速增長〉，上海情報服務平臺，2006 年 9 月 19 日。


26

VII. Trade Combining Density Index (TCD)

After knowing the revealed comparative advantage of the two countries, we

would look at the Trade combing Density Index, in order to see whether their bilateral

trade relationship is close enough.

TCD was first proposed by Brown in 194720

, and revised by Kojima Kiyoshi and

Yamazawa Ippei21

. It illustrates the degree of bilateral trade contact and degree of

interdependence between two countries, i.e. whether they are greatly relying on each

other in trade). The model can be illustrated as followed:

ab aab

b w

X XTCD

M M

where TCDab = trade combining density index between country a and country b, and

X means exports, (Xab/Xa) means the share of exports of counry a to country b in the

total share of country a, M means imports. And (Mb/Mw) is the share of country b’s

imports from country a as against the total import values that country b imports from

the world.

The greater the value of TCD index, the closer the bilateral trade relationship

between the two countries. For details, if TCDab is greater than 1, it means country a

and b have a close trade relationship, and vice versa. The model can be illustrated as

TCDab, which means the trade combining density index between country a and

country b. We use it to see how close the trade relationship between Russia and China

is.

20

Brown, AJ (1947). Applied Economics. (London: George Allen and Unwin).

21 Ippei Yamazaw(1970). Intensity Analysis of World Trade Flow. Hitotsubashi Journal of Economics,

10(2): 61-90


27

In this part, we use the database on international merchandise trade by the

WTO22

, and we have calculated the value of Sino-Russian(TCDCR) and

Russian-China(TCDRC) TCD index in the period 1995 to 201023

.

Table 7: TCD index between China and Russia

1995 1996 1997 1998 1999 2000 2001 2002 2003

TCD CR 0.843 0.815 0.798 0.876 1.024 1.198 1.093 1.067 1.268

TCD RC 1.693 1.755 1.791 1.700 1.634 1.451 1.432 1.428 1.135

(The above calculations of TCDs are based on the statistics from the World Trade

Organization.)

From table 2, we found that the Sino-Russian TCD (TCDCR) index was relatively

low before the year 2000, from 0.7 to 1, which means export relationship of China to

Russia was not close enough. Yet, from 2000 to 2008, it fluctuated from the value of

1.05 to 1.3. So, export relationship for China to Russia is having a closer relationship

than before. It is because China is rising as an international exporting country, she is

also rising as the top three exporters to Russia. Moreover, in the year of 2008 to 2010,

the TCD was relatively lower than before; it may due to the Financial Tsunami that

leads to decrease in bilateral trade.

22

Time Series on international trade, World Trade Organization. Retrieved February 10, 2012, from:

http://stat.wto.org/StatisticalProgram/WSDBStatProgramHome.aspx?Language=E

23 All the data needed for calculating TCD only available from 1995.

2004 2005 2006 2007 2008 2009 2010

1.341 1.347 1.113 1.348 1.181 0.872 1.050

0.921 0.869 0.809 0.634 0.650 0.690 0.542


28

On the other hand, before the year 2004, the Russian-China TCD index (TCDRC)

was relatively higher. However, due to China’s entry to the WTO, China’s market has

been opened to the WTO’s members with the decrease or even zero tariffs. Although

the value of Russia’s exports to China was still increasing, the share of China’s

imports from Russia in the total share of her import has been decreased. This is the

main reason which leads to the decrease of TCDRC index.

Table 8: TCD index of China with Japan and USA respectively

1995 1996 1997 1998 1999 2000 2001 2002 2003

TCD CJ 2.954 3.190 2.908 3.210 3.115 2.892 3.070 2.915 2.725

TCD CU 1.119 1.178 1.128 1.222 1.182 1.093 1.099 1.184 1.248

2004 2005 2006 2007 2008 2009 2010

2.550 2.290 2.014 1.905 1.746 1.864 1.696

1.296 1.325 1.352 1.343 1.339 1.452 1.400

(The above calculations of TCDs are based on the statistics from the World Trade

Organization.)

Moreover, from the table above, when we compare the Sino-Russian TCDs with

other world powers, such as the Sino-US and Sino-Japan TCDs, the Sino-Russian

TCD was lower than that of others. This shows that there is still a room for

improvement in Sino-Russian bilateral trade relations.


29

VIII. Empirical Model

i. PART 1 – Exports to Russia from China

In the previous parts, we have counted the RCA of them; it only proves that their

trading structure could be complementing with each other, which provides great

opportunity for trade between them. And we have looked at the TCD that the bilateral

trade for two countries could be further improved. Yet, it doesn’t mean that trade

between the two countries is inevitable. So, in this part, we attempt to set up an

empirical model to investigate the role and the importance of each determinant as

suggested by literature on the trade between China and Russia. The reason why we set

this regression model is basically because we want to find out what factor(s) affect

China’s exports to Russia.

To conceptualize our analysis, a set of variables have been designed to test the

hypothesis. In the following, we would have an in-depth look at the exports from

China to Russia first:

1. Model Specification

A reasonable regression model to be considered might be:

X = f (RPER, HIGH, EX, R_C_PRICE, R_TARIFF, FIN1997, FIN2008,

CONTRACT) + εi

Cobb-Douglas function is:

X = (RPER)^b1．(HIGH)^b2．(EX)^b3．(R_C_PRICE)^b4．(R_TARIFF)^b5

．(FIN1997)^b6．FIN2008^b7．CONTRACT^b8


30

The empirical regression equation can be written as:

ln(X) = β0 + β1 ln(RPER) + β2 ln(HIGH) + β3 ln(EX) + β4 ln(R_C_PRICE)

+ β5 ln(R_TARIFF) + β6FIN1997 + β7 FIN 2008 + β8 CONTRACT + ei

The expected sign of the coefficients are:

β1 >0, β2>0, β3<0, β4>0, β5<0, β6<0, β7<0, β8>0

2. Description of variables

i. Dependent Variable: LNX

This is the natural logarithm of the real total exports value (using the year 2000

as the base year) of China to Russia.

ii. Independent Variables:

1. LNRPER

This is the natural logarithm of the per capita real GDP of Russia, which implies

her purchasing power in consuming China’s exports.

Traditionally, real GDP of the export partner has been identified as a major

explanatory variable for exports in empirical studies. It is because it has a direct

relationship with the purchasing power of the export partner.

But, in this model, we use per capita real GDP to represent the ability for

consumption of China’s exports, as it is more representative to explain Russia’s

ability to consume per number of population there. And, we use the real GDP at 2000

as the base year for constant price level. Theoretically, when the people generally

have higher income, the ability to consume (include the consumption of imports)


31

would increase. So, the export value for China to Russia would also increase. The

expected sign of this variable is positive.

2. LNHIGH

This is the natural logarithm of the real exports value of the high skilled and

technology intensity products (measured at 2000 constant price). As the high skilled

and technology intensity products generally have higher return, i.e. the export value of

these goods would be higher. So, if China exports more high skilled and technology

intensity goods, the exports value is expected to increase. So, the expected sign is

positive.

3. LNEX

This is the natural logarithm of the exchange rate of the Russian Ruble to that of

China’s RMB. Theoretically, when this variable increases, that means RMB would

appreciate, and Ruble would depreciate. This means the price of China’s exports

would be more expensive, which decrease the quantity demanded of it in the Russian

market. So, the expected sign of this variable is negative.

4. LNR_C_PRICE

This is the natural logarithm of the general price level of Russia divided by that

of China. When the price level of Russia to China increases, it means the price of

goods for Russia increase relatively, and that of China decrease relatively.

Theoretically, a higher price level would increase the relative price of domestic

exports to other countries. This results in a decrease in exports. So, increase in this


32

variable means an increase in China’s exports to Russia. The expected sign of this

variable is positive.

5. LNR_TARIFF

This is the natural logarithm of the average tariff rate for Russia imposed on

China’s imports. Theoretically, the tariff imposed on import goods is a cost for

exports. The higher the tariff imposed, the higher the cost of China’s exports, leading

to higher price of the exports of China in Russian market. So, this would lead to a

drop in the export value from China to Russia. The expected sign of this variable is

negative.

6. FIN1997

This is a dummy variable which imply The Asian Financial Crisis. In this

analysis, when it occurs, we take dummy=1, and otherwise=0. When The Asian

Financial Crisis occurred, which somehow affected Russia, it is expected that the

ability to buy the imported goods would decrease. So, this variable would have a

negative effect on the export from China to Russia.

7. FIN2008

This is a dummy variable which imply The Financial Tsunami. In this analysis,

when it occurs (mainly in 2008Q4 to 2009), we take dummy=1, and otherwise=0.

When there is The Financial Tsunami took place, which somehow affected Russia, the

ability to buy the imported China’s goods would decrease. So, it is expected that this

variable would have a negative effect on the export from China to Russia.


33

8. CONTRACT

This is a dummy variable which means Russia and China have signed contracts

or agreements on trade issue which facilitate their bilateral trade (dummy=1,

otherwise=0). There would be a positive effect for the signing of these agreements to

the exports of China to Russia.

To obtain a general description of the exports and other possible relevant

determinants, a profile of all variables please sees the table in Appendix 1.

3. Data Type

In this project, we apply the time series quarterly data in the period 1997Q1 to

2010Q4 and run the OLS regression. We would use the backward regression method,

i.e. first test all the variables and testing them one by one for statistical significance.

And then delete any independent variables that are less significant and relatively not

supported by economic principals.


34

4. Empirical Results (the final model):

ln(X) = β0 + β1 ln (RPER) + β2 ln (HIGH) + β3 ln (EX) +β4ln (R_TARIFF)

+ β5 FIN1997 + β6 FIN2008 + ei

Dependent Variable: LOG(X)

Method: Least Squares

Date: 04/13/12 Time: 17:06

Sample (adjusted): 1997Q2 2010Q4

Included observations: 55 after adjustments

Convergence achieved after 17 iterations

Variable Coefficient Std. Error t-Statistic Prob.

C -2.176299 1.481123 -1.469357 0.1484

LOG(RPER) 1.744202 0.177604 9.820708 0.0000

LOG(HIGH) 0.348691 0.060427 5.770467 0.0000

LOG(EX) -0.446899 0.111011 -4.025732 0.0002

LOG(R_TARIFF) -0.063805 0.402657 -0.158461 0.8748

FIN1997 -0.498449 0.203833 -2.445378 0.0183

FIN2008 0.122066 0.107299 1.137621 0.2610

AR(1) 0.361033 0.168415 2.143714 0.0373

R-squared 0.981302 Mean dependent var 14.35421

Adjusted R-squared 0.978517 S.D. dependent var 1.121250

S.E. of regression 0.164341 Akaike info criterion -0.640020

Sum squared resid 1.269378 Schwarz criterion -0.348045

Log likelihood 25.60056 Hannan-Quinn criter. -0.527111

F-statistic 352.3792 Durbin-Watson stat 1.934193

Prob(F-statistic) 0.000000

Inverted AR Roots .36

From the above, the Durbin-Watson statistics shows no statistical evidence that

the error terms are positively autocorrelated, as the value of it is 1.934 now. And, all

variables, except FIN2008, show correct sign. But, the p-value for LNR_TARIFF is

high, which means it is not very significant. Also, there are no problems of


35

multicollinearity and heteroskedasticity for this regression model (for proves, please

see Appendix 2).

The following is an overall regression table for the 1st to 5

th regression model in

order to let us have a clear look, where (*) means the variable is in 10% level of

significance, (**) means the variable is in 5% level of significance, and (***) means

the variable is in 1% level of significance:

1st 2

nd 3

rd 4

th 5

th

C

(se)

-1.360

(1.259)

-2.120*

(1.232)

-2.199

(1.491)

-2.164*

(1.224)

-2.176

(1.481)

LNRPER

(se)

1.816***

(0.184)

1.694***

(0.178)

1.743***

(0.179)

1.698***

(0.177)

1.744***

(0.178)

LNHIGH

(se)

0.228**

(0.090)

0.374***

(0.052)

0.350***

(0.061)

0.373***

(0.051)

0.349***

(0.060)

LNEX

(se)

-0.691***

(0.145)

-0.467***

(0.092)

-0.446***

(0.112)

-0.470***

(0.091)

-0.447***

(0.111)

LNR_C_PRICE

(se)

0.458*

(0.234)

/ / / /

LNR_TARIFF

(se)

0.044

(0.302)

-0.051

(0.307)

-0.061

(0.404)

-0.035

(0.304)

-0.064

(0.403)

FIN1997

(se)

-0.604***

(0.155)

-0.685***

(0.154)

-0.500**

(0.203)

-0.693***

(0.153)

-0.498**

(0.204)

FIN2008

(se)

-0.016

(0.090)

0.040

(0.088)

0.118

(0.108)

0.047

(0.087)

0.122

(0.107)


36

CONTRACT

(se)

0.036

(0.050)

0.036

(0.051)

0.020

(0.044)

/ /

correcting

autocorrelation

N 56 56 55 56 55

Adj R-squared 0.978 0.977 0.978 0.977 0.979

D.W. 1.564 1.452 1.927 1.437 1.934


37

ii. Model Implication - Part 1 of the regression

From the above first regression, it gives us some important message - there are

several factors that are significant in affecting China’ exports to Russia, i.e. the

purchasing power of the Russians (the real per capita GDP), the trade barrier (tariff

imposed by Russia), the financial crisis (in 1997 and 2008), the relative price of their

currencies (the exchange rate), and the high skilled and technology intensity exports.

And we also see the ineffectiveness of signing the trade agreements in our model.

Firstly, for tariff, our finding shows that the tariff by Russia is indeed a means to

reduce the exports from China, but it is very insignificant. In fact, although more than

30% of Russian imports have imposed with a tariff rate higher than 25%24

, the high

tariff rate is not so effective to block the exports from China to Russia. The reason is

that the “Grey customs clearance” between China and Russia greatly contribute to the

ineffectiveness of tariff25

. It means the exporters of China signed non-disclosure

agreement with the customs officials, which help to under-report their exports goods

to Russia. For example, underreporting the value and weight or concealed the product

name26

. This helps the exporters to enjoy a low tariff rates, yet it could not be

measured. Also, China and Russia are close to each other, a great number of exporters

would make use of the boarders, and carry duty-free goods from China to Russia in

24〈關稅及通關環節壁壘頻繁〉，《俄羅斯商情》。

Retrieved from: http://blog.mostgroup.com/post/278.html

25 王成剛（2011）：〈後危機時代中俄經貿問題研究〉，《黑龍江對外經貿》，2011 年第 10 期。

26 〈俄羅斯下調入境免稅品價值界限衝擊中俄貿易〉，《環球財經》，《星島日報》，2009 年

8 月 26 日。

http://blog.mostgroup.com/post/278.html


38

person27

. So, the high tariff rates led to these illegal actions, and indirectly led to its

ineffectiveness in limiting exports from China to Russia.

For GDP, like the following diagram, which is drawn on the assumption that

interest rate is fixed. The accounting identity is savings minus investment equals

exports minus imports, S-I = X-M. Both sides of the identity depend on GDP: higher

GDP means more imports and also more savings. So, increase in GDP of Russia

would increase the imports from other countries (e.g. China).

On the other hand, our finding shows the financial crisis have different

implication on the exports to Russia. Our result shows that the Asian Financial Crisis

in 1997 have a negative impact on the exports to Russia. The explanation of this

phenomenon is that the crisis which took place in Thailand, then spread to countries

like Korea and Japan, which had set up their companies in Russia. The crises led these

companies move out their capital (about USD 100 billion) from Russia to save their

27中國駐俄使館：〈2011 年俄羅斯投資經營障礙報告〉，中俄法律網，2012 年 2 月 22 日。

Retrieved from: http://www.chinaruslaw.com/CN/InvestRu/tz009/2012222223451_782314.htm

http://www.chinaruslaw.com/CN/InvestRu/tz009/2012222223451_782314.htm


39

domestic stock market. This led the stock price of Russia dropped by 30%28

. The

Russian Government, in order to save the stock market, had issued large amount of

Government bonds, and the foreign exchange of Russia dropped rapidly29

. This led to

a small-scale financial crisis within the Russian economy. This economic recession

led the purchasing power of Russians dropped sharply, which had a negative effect on

importing China’s goods.

For the Financial Tsunami in 2008, the regression result shows that this crisis

had a positive relationship with the exports from China to Russia, which do not match

with the economic principal that economic recession would lead to a decrease in

income of Russians, and thus lower the purchasing power of China’s exports. The

explanation for this phenomenon is: (1) China mainly export commodity to Russia30

,

such as shoes, textiles products, which have an inelastic demand for these products.

And the exports price of China were cheaper than that of the Western countries, so the

Financial Tsunami didn’t lead to great drop in China’s exports by Russia. (2) The

Financial Tsunami only led to a short-term decrease in the exports of China by Russia.

Although the exports of China to Russia in January to April 2009 dropped by 46.2%,

the exports to Russia increased by 69% to 296.1 billion in shortly after that31

. This

28

張康琴（1999）：〈俄羅斯金融危機〉，東歐中亞研究。

http://wiki.hexun.com.tw/view/3059.html

29 〈俄羅斯 98 年金融危機爆發始末〉，《新聞透視》，俄新社。

http://big5.rusnews.cn/xinwentoushi/20080818/42238501.html

30 王酈久：〈中俄貿易：600 億元的尷尬〉，《中國經營報》，2011 年 6 月 25 日。

31 常玢：〈金融危機背景下中俄經貿合作的影響因素和發展思路〉，《新華財經》，新華網，

2009 年 8 月 16 日。

http://big5.xinhuanet.com/gate/big5/news.xinhuanet.com/topbrands/2009-08/16/content_11891308.htm


40

shows that the export value from China to Russia didn’t be attack much by the

Financial Tsunami.

And for exchange rate, as the two countries no longer rely on barter trade;

instead, they implemented the local currency settlement, which lead exchange rate

becomes more important in affecting their products’ price. When the exchange rate of

the Ruble to RMB increases (see figure 6), the prices of China’s exports are more

expensive. So, it is by theory that this leads to decrease in the quantity demanded of

China’s exports in the Russian market.

Figure 6 - exchange rate of the Russian Ruble to that of China’s RMB

(Data generated from: IMF)

Before we move on to the implications in high skilled and technology intensity

products in affecting the export value of China to Russia, we notice the signing of

contracts is insignificant in increasing the exports from China to Russia. The

explanation for this is that a number of inter-governmental cooperation projects were

just in file and protocol level. For example, in recent years, Russia put more emphasis


41

on the liberalization of trade with China, but in real situation, she has imposed many

resistances and obstacles to China’s exports. In fact, although a number of trade

contracts were signed, the two countries didn’t make efforts in executing the contract.

Instead, arbitrarily detain goods and capital, and the property security of China is not

fully guaranteed. Moreover, through the two governments promised to improve the

bank settlement system, the arbitration system, the credit insurance system, the quality

monitoring system and customs clearance system; not much efforts had been made

and this lead to ineffectiveness of these systems32

.

Moreover, we discover from the regression result that exporting more high

skilled and technology intensity products help to increase the export value from China

to Russia. This is because of four reasons: (1) the per capita income of Russia or the

GDP of Russia has been increasing. Thus, the purchasing power of Russians to

China’s high-tech products increases. (2) The Russian Government lower or even

cancel the import tariff of high-tech products, due to the need of the country’s

development and the inability for Russia to produce these products with comparative

advantage33

. For example, in 2007, the Russian Government cancelled the tariff on

high-tech products, like machinery, and lowered the tariff rate to 5% for high-tech

construction machines34

. (3) Labour-intensive export products from China have low

reputation in the Russian market. And Russia also targeted on Chinese exports, and

32田春生：〈中俄經貿合作關係新析——經濟利益的視角〉，《俄羅斯研究》，2010 年第 1 期。

33 〈俄取消部分高科技設備進口關稅〉，國際稅訊，中華會計網校。

http://www.chinaacc.com/new/253/263/2008/2/zh452961124162280029056-0.htm

34 〈俄羅斯取消部分高科技設備的進口關稅〉，中俄蒙資訊網，2007 年 6 月 21 日。

http://big5.xinhuanet.com/gate/big5/www.nmg.xinhuanet.com/nmgwq/2007-06/21/content_10361866.

htm


42

imposed higher tariff on labour-intensive products. For example, the tariff on textiles

for other countries is 6-7%, but it is 11% for China35

. So, the only way to further

develop the Russian market is to export high skilled and high-tech products with good

quality. (4) Russia is applying for the entry of WTO, and is expected to enter it in

2015, and the WTO agreement indicates that Russia should cancel her tariffs on high

skilled and technology intensity products36

, and cancel the license exporters for these

products37

.

35

李傳勛（2007）：〈俄羅斯「入世」對中俄區域經貿合作的影響〉，俄羅斯中亞東歐市場，

2006 年第 10 期。

36 〈2005 俄羅斯貿易投資環境報告〉，中俄法律網，2006 年 1 月 11 日。

http://www.chinaruslaw.com/CN/InvestRu/Law/2006111134032_5253237E02.htm

37趙學信：〈入世後俄羅斯將對進口高科技產品實行零關稅〉，東寧招商網，2011 年 11 月 16 日。

http://www.dongningzs.com/article.asp?id=1502


43

iii. PART 2 - High skilled and technological intensity exports

In the previous part, it shows that high skills and technology intensity exports

from China are one of the significant factors that affect China’s exports value to

Russia. As stated in the literature review in previous chapter（李青；2001；韓立華，

2001；唐朱昌，2002；李澤祥、楊定華，2003；陸南泉，2004；任賢慧，2007；

劉紅雨，2008；董銳，2010）, changing the exports structure of China to Russia is an

effective method to increase exports value from China to Russia.

So, in this part, we attempt to set up an empirical model to investigate the factors

that determine the proportion of high skills and technology intensity products in total

exports from China to Russia. The reason why we set this regression mode, not only

because it is suggested by literature, but also because the RCA index in previous

chapter shows that China has a comparative advantage in it, and it is easier for China

to adjust the proportion of its exports than other variables (like GDP of Russia).

To conceptualize our analysis, a set of variables have been designed to test the

hypothesis.

1. Model Specification

A reasonable regression model to be considered might be:

HIGH= f (FDI, RD_COST, GOVT, PEOPLE, EX, ENTERPRISE) + εi

Cobb-Douglas function is:

HIGH = (FDI)^b1．(RD_COST)^b2．(GOVT)^b3．(PEOPLE)^b4．(EX)^b5

．(ENTERPRISE)^b6


44

The empirical regression equation can be written as:

ln(HIGH) = β0 + β1 ln(FDI) + β2 ln(RD_COST) + β3 ln(GOVT) + β4 ln(PEOPLE)

+ β5 ln(EX) + β6 ln(ENTERPRISE) + ei

The expected sign of the coefficients are:

β1 >0, β2>0, β3>0, β4>0, β5<0, β6>0

2. Description of variables

i. Dependent Variable: LNHIGH

This is the natural logarithm of the real high skilled and technology intensity

exports (using the year 2000 as the base year) of China to Russia. According to the

“China Statistics Yearbook on High Technology Industry”38

, high skilled and

technology intensity products can be divided as electronic information, software,

aeronautics and astronautics, opto-mechatronics, bio-pharmaceuticals and medical

devices, new materials, new energy and energy-saving products, environmental

protection and modern agriculture. We choose the data of “high skilled and

technology intensity exports from China to Russia” as our data, which means

categories 16 (machinery and mechanical appliances), 17 (vehicles, aircraft, vessels

and associated. transport equipment) and 18 (Optical, photographic, cinematographic,

measuring, checking, precision, medical or surgical instruments and apparatus) from

China.

38《中國高新技術產品出口目錄》，中國科學技術部、財政部、國家稅務總局、海關總署，2006

年。


45

ii. Independent Variables:

1. LNFDI

This is the natural logarithm of the real value of foreign direct investment (using

the year 2000 as the base year). FDI helps to improve Chinese exports structure,

especially improve export competitiveness of the high-tech products. As suggested by

literature, FDI helps to improve the technical and technology level of the labor-intensive

products and thus improve the export quality（賴明勇、許和連、包群，2003）39. So, the

expected sign is positive.

2. LNRD_COST

This is the natural logarithm of the cost of research and development (using the

year 2000 as the base year). When the R&D cost of China increases, it means China

have more ability to produce products with higher technological level. And in

long-term, it may lower the cost to produce high technology goods, and increase her

comparative advantage in producing it, which favor the increase in high-tech exports.

The expected sign of this variable is positive.

3. LNGOVT

This is the natural logarithm of the Chinese Government’s financial support

(using the year 2000 as the base year) to the development of high skilled and

technology intensity industry. With the Government’s support, it would favor the

development of this industry, and thus increase the exports value of these goods. So,

39賴明勇、許和連、包群（2003）：《出口貿易與經濟增長——理論、模型及實證》，三聯書店

出版社。


46

the increase in government support is expected to have a positive relationship with the

exports of high skilled and technology intensity products.

4. LNPEOPLE

This is the natural logarithm of the researchers who are involved in research and

development of the high skilled and technology intensity products. With more

professionals involve in this industry, it is expected that it would have a positive

relationship with the increase in export value indirectly.

5. LNEX

This is the natural logarithm of the exchange rate of the Russian Ruble to

that of China’s RMB. Theoretically, when this variable increases, that means the price

for China’s exports would be more expensive, which decrease the quantity demanded

of her exports in the Russian market. It is a variable suggested by literature, which

stated that the appreciation of RMB to other foreign currencies would especially

decrease the exports of the high-tech products rather than the labour-intensive low

technology intensity product（謝裡、隋楊、張婭，2011）40. So, the expected sign of

this variable is negative.

6. LNENTERPRISE

This is the natural logarithm of the enterprises that involved in research and

development and involved in export activities of the high skilled and technology

40謝裡、隋楊、張婭（2011）：〈人民幣匯率與商品出口結構——基於中國省際數據的經驗研究〉，

《投資研究》，2011 年 08 期


47

intensity products. Generally, when the value of this variable increases, the exports

for this type of product would also increase. The expected sigh is positive.

In order to obtain a general description of the export value of the high skilled and

technology intensity products, and other possible relevant determinants; the following

table is a profile of all variables:

3. Data Type

In this project, we also apply the time series quarterly data in the period 1997Q1

to 2010Q4 and run the OLS regression. We would use the backward regression method

like in the last part.

4. Empirical Results

ln(HIGH) = β0 + β1 ln(FDI)+ β2 ln(RD_COST) + β3 ln(PEOPLE) + ei

Dependent Variable: LOG(HIGH)


Date: 04/13/12 Time: 17:14

Sample (adjusted): 1997Q2 2010Q4

Included observations: 55 after adjustments

Convergence achieved after 9 iterations


C -10.02818 4.263216 -2.352257 0.0226

LOG(FDI) 1.642300 0.571116 2.875597 0.0059

LOG(RD_COST) 0.144744 0.224279 0.645374 0.5216

LOG(PEOPLE) 0.905908 0.491700 1.842400 0.0714

AR(1) 0.941221 0.048158 19.54450 0.0000





48





Inverted AR Roots .94

This is the final regression model that is most explainable, with adjusted

R-squared equals to 0.989. All variables have correct sign. And only LNRD_COST is

not significant in 10% significance level.

The following is an overall regression table for the 1st to 8

th regression model in

order to let us have a clear look, where (*) means the variable is in 10% level of

significance, (**) means the variable is in 5% level of significance, and (***) means

the variable is in 1% level of significance:

1st 2nd 3rd 4th 5th 6th 7th 8th

C

(se)

-12.017***

(1.933)

-8.853***

(3.063)

-12.286***

(1.870)

-8.805***

(3.029)

-4.582

(3.218)

-10.600**

(4.471)

-4.429

(2.981)

-10.028**

(4.263)

LNFDI

(se)

-2.506***

(0.451)

-1.571***

(0.425)

-2.411***

(0.421)

-1.580***

(0.534)

2.978***

(0.707)

1.569**

(0.591)

2.987***

(0.698)

1.642***

(0.571)

LNRD_COST

(se)

-0.214

(0.147)

-0.179

(0.184)

-0.267**

(0.119)

-0.166

(0.176)

1.015***

(0.206)

0.082

(0.255)

1.005***

(0.192)

0.145

(0.224)

LNGOVT

(se)

1.435***

(0.184)

1.636***

(0.259)

1.411***

(0.179)

1.637***

(0.256)

-0.058

(0.434)

0.185

(0.363)

/ /

LNPEOPLE

(se)

5.061***

(0.522)

4.127***

(0.642)

5.123***

(0.509)

4.114***

(0.634)

-1.018

(0.720)

0.863*

(0.502)

-1.081*

(0.540)

0.906*

(0.492)

LNEX -0.036 0.022 / / / / / /


49

(se) (0.059) (0.092)

LNENTERPRISE

(se)

-5.118***

(0.276)

-4.988***

(0.425)

-5.107***

(0.274)

-4.991***

(0.421)

/ / / /

correcting

autocorrelation

N 56 55 56 55 56 55 56 55

Adj R-squared 0.994 0.997 0.995 0.997 0.954 0.989 0.955 0.989

D.W. 0.795 1.833 0.776 1.824 0.352 1.817 0.354 1.825


50

iv. Model Implications - Part 2 of the regression

As improving the exports structure by China to Russia is strongly supported by

literature and the above regression result, and these types of products are less

restricted by the trade barrier of Russia as mentioned above. Exporting high-skilled

and technology intensity products to Russia is one of the most effective methods to

increase the export value from China to Russia.

From part 2 of the empirical result, it shows the insignificance of Government

investment on the exports of high-skilled and technology intensity products to Russia.

This is because R&D investment by the Chinese Government accounted for only

1.3% of GNP, while that of the Western countries are usually 2.5%. And investment

in R&D by the Government is mainly on space development and manned space flight;

only very little investment are invested on scientific research or improving the level of

products or the trading structure (less than 6% in the proportion of Government’s

R&D investment, while in Western countries accounted for 20%)41

.

On the other hand, we know that the factors that could affect the export values of

high skilled and technology intensity products are cost for research and development

(R&D), the number of professionals involved in the R&D process, and the foreign

direct investment (FDI).

Yet, from the result, it shows that the cost of R&D is not very significant in

affecting the export value of the high skilled and technology products from China to

Russia, although this is supported by theory. The explanation of its insignificance is

that: (1) the importance for R&D is more encouraged in China only since the year

41〈「中國製造」的高科技主要依賴外資〉，《經濟縱橫》，2005 年 7 月 16 日。


51

200042

. So, the achievement for R&D may not be significant, as the technique may be

still not mature enough; (2) R&D cost may be invested in various types of

development, but not only in high-skilled and technology products. For example,

forestry, transportation, software industry, etc43

. So, R&D investment on high skilled

and technology intensity products is only one kind of investment. (3) The products

which developed by R&D process would not be totally exported to Russia. Instead, it

may be exported to other countries with higher purchasing power or that China with

more comparative advantages, or sell in the domestic market. (4) The capital which

put on R&D is still low when compared to other countries (see figure 7), , such as EU

and the US.

Figure 7: R&D expenditure per GDP for major powers

(Source: 2010 Science and Engineering Indicators, the US National Science Board)

42思坦芬•濤特（2007）：〈中國的創新經濟：為中國成為世界領先者奠定基礎〉，Medstat Research。

43羅彥平（2011）：〈中國研究與發展投入產出效率分析〉，《經濟與管理》，2011 年第 6 期。


52

Moreover, the regression result also shows that the number of researchers

involved in R&D is, to a large extent, significant in affecting the exports of

high-skilled and technology intensity products. The reason for that is probably

because the number of PhDs, masters and professionals for China rank first

throughout the world44

. And China keeps sending students to foreign countries since

198545

. For example, over 80% of students from Tsing Hua University who are

major in high-tech products are sent to USA for further studies, and over 76% of that

from Beijing University46

. Also, average annual growth rate of researchers in China

ranked first in the world (see figure 8). The large amount and high-quality of

professionals probably leads the research and development process more efficient in

practice, and thus contributes to the growth in exports of high skilled and technology

products.

44

“IMD World Competitiveness Yearbook 2007”, International Institute for Management

Development (IMD), 10 May 2007.

45王輝耀（2010）：〈中國人才戰略須著眼於攬全球人才為我所用〉，《綠葉》。

46《中國科技人力資源發展研究報告 2008》，中國科學技術協會發展研究中心。


53

Figure 8: Average annual growth rates in number of researchers for major powers

(in 1995-2007)


And for the FDI, the regression result shows that it is the most significant in

affecting the dependent variable. It is supported by many researches. FDI not only

improves the exports of labor-intensive products, but also increases the high

value-added technology-intensive exports if more technical input is invested. It also

leads to multinational vertical and horizontal integration; which increases the

opportunities for exporting high value-added products（賴明勇、包群，2002）47. This is

also supported by Bergsten. C.F.(1978) that in the US case, the more the FDI invested

in a particular high-tech industry, the more the export value of that industry. FDI also

promotes the improvement in the structure of export commodities, and enhance the

competitiveness of export commodities（江小娟，2002）48.

47賴明勇、包群：〈中國外商直接投資與技術進步的實證研究〉，《經濟評論》，2002 年第 6 期，

第 62-66 頁。

48江小娟：〈中國出口增長與結構變化：外商投資企業的貢獻〉，《南開經濟研究》，2002 年第

2 期，第 30-34 頁。


54

v. Model Limitation and Suggestion

There are two limitations in this research report, namely the data source and the

size of the data base.

1. Data Source

The data of the variables are from different organizations (e.g. IMF, the National

Bureau of Statistics of China, etc). The calculations and measurement of different

variables from these organizations might be a bit different. Although I have tried to

take all data from the National Bureau of Statistics of China, updated data for some

variables are not free in use. That makes us take the data from other international

organization, or find other similar variables to replace it. The suggestion for future

study is to use other variables to replace them, which are updated and completely free.

Also, more data will be available for future study when times go on.

2. Size of Data Base

The availability of data source only allows us to take data from 1997Q1 to 2010Q4.

Since the dissolution of Soviet Union took place in late 1991, which means the

establishment of the Russian Federation; it is better to take data from the year 1992 if

more data will be released in the future. This leads our model more accurate in

reflecting the real situation of Sino-Russian trade.


55

vi. Suggestion to the Sino-Russian trade

The above sections have shown us the Sino-Russian trade can be improved in

order to make China able to grab more proportion of the Russian market. So, in this

section, we would make suggestions on how China could increase and stabilize her

exports to Russia.

Firstly, literatures and part 1 of our regression have shown us the most effective

way to increase the exports from China to Russia– to export more high-skilled and

technology intensity products. The RCA index also shows us that China have a

comparative advantage in exporting these products in their trade. In fact, this

suggestion is not pushing China to do something that she couldn’t. Because figure 9

shows us that China’s exports of high-skilled and technology manufacturing products

to her trading partners have surpassed the US in 2004, and surpassed the EU in 2006.

And, Russia had implemented prohibitive tariffs towards China’s cheap and

labour-intensive exports in order to protect her domestic industry, e.g. she

implemented prohibitive tariffs on clothing, textiles and footwear in 2010. Moreover,

over 10% of China’s exports are subjected to high tariffs (more than 25%), such as

plastic products. And textile fabrics, garments and sugar even have an average import

tariffs up to 30%. It is only the high skilled and technology-intensity products that the

Russian Government imposed a lower tariff rate, as she needs these imports for local

development (as Russia focus too much on producing capital goods throughout the

years). So, increasing the proportion of high-skilled and technology intensity products

would lead China’s exporters enjoy a lower tariff rate by Russia. Moreover, Russia

has high demand in China’s high-tech products, such as products of electronic

appliances manufacturing technology, computer production technology, production

technology of communications equipment, engineering machinery production


56

technology, etc. By our regression result, the Chinese Government could achieve

exporting more high-skilled and technology intensity products by increasing the

inputs (capital and researchers) for R&D of export products, and attract more FDI in

high-skilled and technology fields (like the “vacating cage to change bird” policy (騰

籠換鳥) by the Guangzhou government).

Figure 9: Exports of high-technology manufactured goods by major powers (in

1995-2008)


Secondly, China could export high value-added products. The export structure

of China to Russia is rather simplistic now, i.e. she exports mainly food, clothing,

textile and other necessities to Russia. For example, textile, clothing, footwear and

leather goods accounted for 52.03% of her exports to Russia, and although higher

technology products, such as mechanical and electrical products, has accounted for

only 15.7% of her exports to Russia. Yet, a large proportion of them were just

electronic home appliances which are not high value-added. Unlike those exports

from the European countries to Russia, exports from China to Russia are mainly in


57

low-to-medium class. As shown in figure 10, the GDP for Russia is no longer as low

as she was just dissolute in 1992; instead, the GDP(at PPP) has increased dramatically

throughout the years, and reached USD2100 billion in 2010. This shows the

purchasing power of Russians for high quality products with higher price has been

increased. Also, with the establishment of the Russian market system, her economic

recovery and the rise of the living standard of Russians; the consumer's preferences

and tastes has been improved, they now prefer higher quality products. That explains

why the European countries who produce goods with better quality are grabbing more

proportion of the Russian market. So, as the demand for Russians is directed to

medium-to-high class products, China could supply more of them to meet the

increasing Russians’ demand. Also, Chinese exporters could establish brand name on

these products in order to create an image of good quality and make them high

value-added.

Figure 10: GDP (at PPP) of Russian Federation (1992 to 2010)

(Source: International Monetary Fund)

Thirdly, many researchers suggest the establishment of free trade area (FTA). In


58

fact, FTA would lead to a better flow of factors of production between the two

countries, and improve the efficiency of resources allocation. And the two countries is

in fact have good foundations in establishing FTA, e.g. stable political environment,

the longest border (4300 km), and exporters have used Heilongjiang as the base of

border trade for many years, etc. The establishment of FTA leads their trade closely

connected.

The forth suggestions is to enforce the trade agreements and put it in progress.

Our regression result in part 1 has shown the ineffectiveness of the signing of trade

agreements between the two countries. We have already explained with examples that

many trade agreements are just in file and protocol level, but not under strict

enforcement. In fact, many of these agreements, if they can put in progress, would be

effective in helping the development of Sino-Russian trade. Examples include

liberalization of trade with China, improving the bank settlement system, etc. These

trade agreements would, to a large extent, help to facilitate the Sino-Russian trade.

Moreover, the two Governments should fight against the problem of “Grey

customs clearance". Although it leads the Chinese exporters could use a lower cost to

transport products to Russia by bribing the Russian Customs union, these

underground activities lead the low quality or even fake products could enter the

Russian market. In long-term, this destroys the reputation of “made in China’s

products”, and lead to a bad image of China’s exports.

Last but not least, the law and legislation of trade in Russia should be improved.

One of the existing problems(see figure 11) is that the laws and regulations between

the two countries are not perfect, e.g. the operation of banking institutions are not

standardized, the customs clearance ability is low, the imperfect trade arbitration

mechanism also makes trade disputes difficult to resolve; and the inconsistence of tax


59

and tariffs of Russia lead confusion. These problems must be solved by implementing

laws and regulations with strong enforcement in order to keep the good trade

relationship between the two countries and to facilitate the Sino-Russian trade.

Figure 11: Problems incurred in Sino-Russian trade

(Source: 王靜（2003）：〈中俄關係：一瘸一拐〉，《經濟月刊》，頁75。)


60

X. Conclusion

All in all, although the scale of Sino-Russian trade may not be that large and

strong like China with the EU and the US now, and China could hardly rely on the

trade with her to face another financial crisis in this moment, Russia’s growth as

China’s major trading partner should not be overlooked because their trade does have

a great potential to further develop in the future.

Our empirical studies show that China could further export to Russia with a

greater trade value in the future. As Russia is growing in her economy and her GDP,

she has greater purchasing power in consuming medium-to-high level products; China

could further grab the market of Russia by exporting more high-skilled and

technology intensity products, which can be achieved by attracting more FDI,

increasing the expenditure of R&D and increasing the number of researchers as

suggested by our regression model.

In their future trade development, they could make use of their geographical

advantage (long boarder and near to each other), comparative advantages and matched

trading structure, and to make improvements of their problems involved in their trade.

By doing so, they could probably achieve the bilateral trade goal that suggested by

President Hu Jintao in 2011, which is USD 1000 billion in 2015, and USD2000

billion in 2020. Thus, China could further rely on the trade with this BRIC’s member

in the coming future.


61

XI. Appendix

i. Part 1 – Description of variables

Variable Unit Description Source Expected

sign

LNX

(dependent

variable)

USD Log value of the total real

exports value of China to

Russia (measured at 2000

constant price)

China Statistical

Yearbook

1. LNRPER USD

(in ten

billions)

Log value of the per capita

real GDP of Russia

(measured at 2000

constant price)

China Statistical

Yearbook

(Appendix), China

INFOBANK

(International)

Limited.

+

2. LNHIGH USD (in

thousands)

Log exports value of the

high skilled and

technology intensity

products from China to

Russia (measured at 2000

constant price)

United Nations

Conference on trade

and development

(UNCTAD)

+

3. LNEX % in USD Log value of exchange

rate of Russian Ruble to

RMB

International

Monetary Fund

(IMF)

-

4. LNR_C_PRICE % in USD Log value of general price

level of Russia divided by

the price level of China

China Financial

Statistics Yearbook,

China Statistical

Yearbook

(Appendix),

China INFOBANK

(International)

Limited.

+


62

5. LNR_TARIFF % Log value of average tariff

for Russia imposed on the

China’ s exports

China Customs

Statistics Yearbook,

China Financial

Statistics Yearbook

-

6. FIN1997 dummy The Asian Financial crisis

occurs=1, otherwise=0

WiseNews -

7. FIN2008 dummy The Financial Tsunami

occurs=1, otherwise=0

WiseNews -

8. CONTRACT dummy signed contracts or

agreements on trade issue

= 1, otherwise = 0

WiseNews +

ii. Test regression for part 1

We will test whether the 5th

regression model involves multicollinearity. From

below, the VIF for all variables is less than 10, meaning there is no problem of

multicollinearity.

Variance Inflation Factors

Date: 04/13/12 Time: 17:09

Sample: 1997Q1 2010Q4

Included observations: 55

Coefficient Uncentered Centered

Variable Variance VIF VIF

C 2.193727 1824.077 NA

LOG(RPER) 0.031543 1446.456 4.399975

LOG(HIGH) 0.003651 468.8821 6.762520

LOG(EX) 0.012323 15.76799 2.339237

LOG(R_TARIFF) 0.162133 730.8511 3.107189

FIN1997 0.041548 2.084872 2.017156

FIN2008 0.011513 1.178069 1.098952

AR(1) 0.028364 1.635013 1.634078


63

In order to ensure there is no problem of heteroscedasticity, we use the

Breusch-Pagan-Godfrey Test (LM test):

H0: homoscedasticity var(εi) = 2

H1: heteroscedasticity var(εi) = 2

Heteroskedasticity Test: Breusch-Pagan-Godfrey

F-statistic 1.817018 Prob. F(6,48) 0.1156

Obs*R-squared 10.17987 Prob. Chi-Square(6) 0.1173

Scaled explained SS 4.926118 Prob. Chi-Square(6) 0.5533

Test Equation:

Dependent Variable: RESID^2


Date: 04/13/12 Time: 17:10

Sample: 1997Q2 2010Q4



C -0.129765 0.183004 -0.709081 0.4817

LOG(RPER) 0.045139 0.026665 1.692790 0.0970

LOG(HIGH) -0.013804 0.007695 -1.793952 0.0791

LOG(EX) 0.011311 0.013590 0.832315 0.4094

LOG(R_TARIFF) -0.011005 0.045298 -0.242941 0.8091

FIN1997 0.043467 0.024177 1.797847 0.0785

FIN2008 -0.011353 0.012993 -0.873794 0.3866









64

From the above result, it shows that the p-value is larger than 0.05, meaning F*

or the Breusch-Pagan-Godfrey (BPG*) is smaller than the critical F. So, we do not

reject the assumption that homoscedasticity is exists, meaning that there is no problem

of heteroscedasticity.

iii. Part 2 – Descriptions of variables

Variable Unit Description Source Hypothesis

LNHIGH

(dependent variable)

USD

( in

thousands)

Log value of the total

real exports value of the

high skilled and

technology intensity

products of China to

Russia (measured at

2000 constant price)

United Nations

Conference on

trade and

development

(UNCTAD)

1. LNFDI USD (in

billions)

Log value of the real

value (measured at 2000

constant price) of foreign

direct investment(FDI)

中國商務年鑒 +

2. LNRD_COST USD

(in ten

thousands)



constant price) of R&D

cost for China

中國科技統計年鑒 +

3. LNGOVT USD(in

ten

thousands)



constant price) of

Government support in

this industry


4. LNPEOPLE Person Log value of the

researchers involved in

the R&D development



65

5. LNEX % in USD Log value of exchange

rate of Ruble to RMB

International

Monetary Fund

(IMF)

-

6. LNENTERPRISE Enterprise Log value of the

enterprises involved in

the R&D development

which also involved in

exports activities


iv. Test regression for part 2

In order to ensure there is no problem of heteroscedasticity, we use the

Breusch-Pagan-Godfrey Test (LM test):

H0: homoscedasticity var(εi) = 2

H1: heteroscedasticity var(εi) = 2

Heteroskedasticity Test: Breusch-Pagan-Godfrey

F-statistic 0.549157 Prob. F(3,51) 0.6510

Obs*R-squared 1.721088 Prob. Chi-Square(3) 0.6323

Scaled explained SS 8.114081 Prob. Chi-Square(3) 0.0437

Test Equation:

Dependent Variable: RESID^2


Date: 04/13/12 Time: 17:15

Sample: 1997Q2 2010Q4



C -0.415488 0.730947 -0.568425 0.5722

LOG(FDI) -0.157981 0.171739 -0.919891 0.3620

LOG(RD_COST) 0.020892 0.048198 0.433453 0.6665

LOG(PEOPLE) 0.068035 0.132574 0.513184 0.6100


66


Adjusted R-squared -0.025690 S.D. dependent var 0.077097






From the above result, it shows that the p-value is larger than 0.05, meaning F*

or the Breusch-Pagan-Godfrey (BPG*) is smaller than the critical F. So, we do not

reject the assumption that homoscedasticity is exists, meaning that there is no problem

of heteroscedasticity.

Then, we will test whether the 8th

regression model involves multicollinearity.

From below, the VIF for all variables is less than 10, meaning there is no problem of

multicollinearity.

Variance Inflation Factors

Date: 04/13/12 Time: 17:16

Sample: 1997Q1 2010Q4


Coefficient Uncentered Centered

Variable Variance VIF VIF

C 18.17501 138.8251 NA

LOG(FDI) 0.326174 71.21707 2.077844

LOG(RD_COST) 0.050301 111.7440 2.170501

LOG(PEOPLE) 0.241769 347.5793 3.107665

AR(1) 0.002319 1.471542 1.249783


67

XII. Bibliography

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68

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69

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70

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8. International Monetary Fund (IMF)

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10. China Commerce Yearbook（中國商務年鑒）



Documents

BY MOK KA YAN A PROJECT SUBMITTED IN PARTIAL …libproject.hkbu.edu.hk/trsimage/hp/09010408.pdf · Russia, in her exports（李永華、畢崇志，2008；李春豔，1999；趙傳君，2010；