Download Determinants of China’s OFDI in European Union and North America Haverford College

Haverford College
Senior Thesis
Determinants of China’s OFDI in
European Union and North America
Are the determinants for European Union different from the
determinants for North America?
Supervisor:
Author:
Biswajit Banerjee
Chunan Liu
A thesis submitted in fulfilment of the requirements
for the degree of Bachelor of Art
in the
Department of Economics
April 2014
HAVERFORD COLLEGE
Abstract
Department of Economics
Bachelor of Art
Determinants of China’s OFDI in European Union and North America
Are the determinants for European Union different from the determinants for
North America?
by Chunan Liu
The role of Foreign Direct Investment (FDI) is more and more critical in a globalized
world. China’s Outward FDI (OFDI) has received increasing interest in empirical research since it started surging in 2004. China’s OFDI to European Union (EU) and
North America countries has been substantially growing recently, especially during financial crisis period. This thesis investigates the key determinants of China’s OFDI to
EU Member States and North America Countries and compares if the determinants for
EU countries are different from the determinants for North America Countries. Statistical analyses are applied to seek evidence of general considerations of FDI and specific
considerations on China’s OFDI, and on EU and North America Countries.
Acknowledgements
I take this opportunity to express my profound gratitude and deep regards to my advisor
Prof. Biswajit Banerjee for his exemplary guidance, monitoring and constant encouragement throughout the course of this thesis. The blessing, help and guidance given by
him time to time shall carry me a long way in the journey of life on which I am about
to embark.
I cannot express enough thanks to my instructors Prof. Anne Preston, Prof. David
Owens, Prof.Giri Parameswaran, Prof. Steven Lindell, Prof. David Wonnacott, who
provide countless support and encouragement to all seniors in the department, and
Prof. John Dougherty, who gave me valuable guidances as my Computer Science thesis
advisor. I offer my sincere appreciation for the learning opportunities provided by them.
Thanks to my friends Zhen, Ethan, Tom and Bryan, without your understanding and
support, I could not have gone this far today.
Finally, to my caring, loving, and supportive parents and grandparents: my deepest
gratitude. Your encouragement when the times got rough are much appreciated and
duly noted.
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Contents
Abstract
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Acknowledgements
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Contents
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List of Figures
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List of Tables
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1
1
1
Introduction
1.1 Motivation
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2 Literature Review and Hypotheses
2.1 General considerations of FDI . . . . . . . . . .
2.2 General Considerations on China’s OFDI . . .
2.3 Considerations of China’s OFDI in European
America . . . . . . . . . . . . . . . . . . . . . .
2.4 Hypotheses . . . . . . . . . . . . . . . . . . . .
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3 Data and Methodology
3.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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4 Results
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5 Conclusions
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A Supplementary Tables
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Bibliography
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Union
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(EU) and
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North
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List of Figures
1.1
1.2
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China’s OFDI flow in percent of its current GDP .
China’s OFDI stock in percent of its current GDP
Regional Weights of China’s OFDI Flow . . . . . .
Regional Weights of China’s OFDI Stock . . . . .
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List of Tables
A.1
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A.5
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A.8
Summary findings of Earlier Studies on China’s
Summary findings of Earlier Studies on China’s
Summary findings of Earlier Studies on China’s
Data Specifications . . . . . . . . . . . . . . . .
Data Specifications continued . . . . . . . . . .
Results: Full Sample . . . . . . . . . . . . . . .
Results: EU Countries . . . . . . . . . . . . . .
Results: Complete Specifications . . . . . . . .
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OFDI I. .
OFDI II.
OFDI III.
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Chapter 1
Introduction
This thesis aims to examine the key determinants of China’s outward foreign direct
investment (OFDI) in the European Union and North America.
1.1
Motivation
Foreign direct investment (FDI) is important in a globalized world. Firms have gone
beyond international trade and built (green-field FDI) or acquired (brown-field FDI)
plants abroad to carry out production and distribution. Dunning [1](1980) explained
the incentives of corporations to invest abroad in terms of Ownership, Location and
Internalization (OLI). Firms decide to invest abroad because it facilitates greater access
to market via ownership of financial capital, technology, trademarks, natural resources
and patents. By choosing appropriate destinations for FDI, firms can acquire economic
benefits, and political and social advantages. By internalizing cross border assets, firms
can reduce transaction costs via FDI. Although FDI requires firms to put in sunk costs
for building plants and setting up for production, it also brings tremendous benefits over
time.
Importance of China’s OFDI has also been significantly growing over time. Figure 1.1
shows China’s OFDI flow in percent of its current GDP from year 2004 to year 2012.
In year 2004, China’s OFDI is only about 0.3 percent of China’s current GDP, but it
surged to around 1.2 percent of current GDP in 2008. Although during the Financial
Crisis and Sovereign Debt Crisis period, the OFDI flow to GDP ratio declined slightly,
it started recovering since 2011. China’s OFDI stock to current GDP ratio tells a similar
story (see Figure 1.2). During year 2004-2008, the growth of China’s OFDI stock was
faster than the growth during the crisis period.
1
Chapter 1. Introduction
Figure 1.1: China’s OFDI flow in percent of its current GDP
Figure 1.2: China’s OFDI stock in percent of its current GDP
2
Chapter 1. Introduction
3
The flow of FDI into China and out of China has received increasing interest in empirical
research. China’s OFDI has surged in the last decade from a very low base. In 2012,
China’s OFDI flow was US dollar 87.8 billion, or 1.07 percent of its current GDP, ranked
the third place in the world. In terms of stock, according to 2012 statistical Bulletin
of China’s Outward Foreign Direct Investment, China still has a long way to catch up.
United States cumulated US dollar 5191 billion of OFDI stock up to 2012, ranked the
first place in the world. China has only cumulated US dollar 531.9 billion of OFDI,
ranked the seventh place in the world.
The increasing trend of China’s OFDI reflects significant changes in geographical distribution. Although North America and European Union are not the most important
destinations of China’s OFDI, their importance has been potentially increasing over the
years and most importantly, did not decline during crisis period. Figure 1.3 shows the
weight of each destination region in China’s OFDI flow during the period of 2004-2012.
Investments into Asian areas except Hong Kong are slightly more important than those
into North America and EU, but declined during the crisis period. The weight of EU
and North America was very little in 2004, but the weights grew substantially over the
years. The growth rates appear to be greater after the financial crisis in 2008 took place.
Figure 1.4 shows the regional weight of China’s OFDI in terms of stock. It tells a similar story. Therefore, it will be interesting to look into what drives Chinese investors to
invest in EU and North America.
Figure 1.3: Regional Weights of China’s OFDI Flow
Note: OFDI to Hong Kong was excluded in the graph because China’s OFDI to Hong Kong
follows very different principles than to the rest of the world. Hong Kong, as the top recipient
of China’s OFDI, is used as a tax haven and a spring broad of China’s OFDI.
Chapter 1. Introduction
Figure 1.4: Regional Weights of China’s OFDI Stock
4
Chapter 2
Literature Review and
Hypotheses
2.1
General considerations of FDI
Dunning [1](1980) addressed three major determinants of OFDI location choice in his
eclectic OLI paradigm. One of the determinants is the incentive of expanding foreign
market. Foreign market seeking FDI takes place through both defensive and offensive
channels. In defensive foreign market seeking, the goal of Multinational Corporations
(MNCs) is usually hopping trade barriers. Offensive foreign market seeking FDI, in
contrast, refers to MNCs building plants abroad as intermediary for export to countries
beyond host countries. The second determinant emphasized by Dunning [1](1980) is
efficiency seeking OFDI. Home countries build factories in countries where labor, operation and transaction costs are lower, so that they can reduce their total production
costs. The ability of producing products at a lower cost enables MNCs to gain a comparative advantage over production costs. According to Dunning [1](1980), the third
determinant is that MNCs invest abroad in order to acquire resources. They seek either nature resources or technologies. In addition to the three major determinants in
Dunning [1](1980)’s eclectic paradigm, recent scholars suggested that location choice of
OFDI also depends on macroeconomic environment of the both the home country and
the host country.
Pain and Welsum [2](2003) have highlighted the role of exchange rate on FDI flows and
the impact occurs through multiple channels. Considerations in financing options suggest a negative relationship between exchange rate and FDI flows into the host country.
Holding assets denominated in a depreciating currency increases relative cost of capital
and reduces the easiness of financing abroad. As other factors are held constant, the
5
Chapter II. Literature Review and Hypotheses
6
weaker is the host country currency, the higher is the level of FDI flow into the host
country. Another way that the exchange rate could affect level of FDI inflow is through
uncertainty of investor. When investors expects the host country currency to appreciate, and they are eventually interested in collecting the profit in appreciated currency,
locations with appreciated currency will be more attractive to FDI investors. In this
channel, the exchange rate level of the host country is positively correlated with level of
FDI flow into the host country.
Duanmu and Guney [3] (2009) addressed the importance of host country and home country institution environment in location choice of OFDI. Taxes, fiscal incentive structure,
legal and macroeconomic infrastructure in both of the home country and the host country will have potential affect on FDI from the home country to the host country.
2.2
General Considerations on China’s OFDI
Existing literature has confirmed the market seeking theory on China’s OFDI. Buckley et
al[4] (2007), Duanmu and Guney [3] (2009) and Cheng and Ma [5] (2007) specified market
size by the nature log of host country’s current Gross Domestic Product. They all found
significant and positive sign on lnGDP. Fung et al Fung and Siu [6](2007) and Kolstad
and Wiig [7] (2009) estimated the same motivation, but in terms of nominal current
GDP of host country, and found positive and significant signs on host country’s current
GDP.Korniyenko and Sakatsume [8] (2009) used Purchasing Power Parity adjusted GDP
per capita to estimate the effect of market seeking, and found a significant and positive
sign. Cheung and Qian [9] (2009) used the ratio of host country GDP to China’s GDP
as a proxy for market seeking and found significant and positive as well. The results
confirmed that Chinese investors are seeking destinations with greater market size.
Trade openness is another proxy for market seeking motivation of OFDI. Fung et al Fung
and Siu [6](2007), Duanmu and Duanmu and Guney [3] and Kolstad and Wiig [7](2009)
included host country’s net trade to current GDP ratio, as a proxy for trade openness,
in their study. Only Duanmu and Guney [3](2009) found a significant and positive sign
on trade openness of host country, indicating that Chinese investors are more attracted
to countries that are more open to international trade.
Two studies have considered exchange rate as a determinant of China’s OFDI. Both
Buckley et al[4](2007) and Duanmu and Guney [3] (2009) included nominal bilateral
exchange rate between host country and china in their regression equations. Buckley et
al (2007) did not find any significant relationship between bilateral exchange rate and
Chapter II. Literature Review and Hypotheses
7
China’s OFDI, while Duanmu and Guney [3](2009) found a significant and positive relationship. The positive relationship suggests that Chinese investors are more interested
in the long-term value of their investment projects, and therefore, more attracted to
host countries with appreciating currencies.
Another major motivation of investing abroad suggested by Dunning [1](1980) is technology seeking in the host country. Earlier studies (e.g. Fung et al Fung and Siu [6]
(2007)) have used three proxies to test the hypothesis on China’s OFDI. One variable
is the Research and Development (R&D) expenditure in the host country. One variable is secondary education enrollment and another variable is annual number of patent
registration in host country. Fung et al Fung and Siu [6] (2007) found that both R&D
expenditure of host country and secondary education enrollment in the host country are
statistically significant and have negative sign. Buckley et al[4](2007) included annual
number of patent registration in host country as another proxy for technology seeking.
However, they did not find it significant in any steps. The results suggest, contrary
to expectation, that Chinese investors are not interested in host countries with high
technology capability.
In order to account for the gradual changes taking places over the sample period, Cheung
and Qian [9](2009) included a time trend variable in their regression equation. They
found an significant positive sign on the time trend variable, meaning that Chinese
OFDI is increasing over years because of factors that are not captured in the equation.
For instance, the variable may capture the loosening restriction of OFDI from China’s
government over the years.
Fung et al Fung and Siu [6] (2009) found that none of the proxies for natural resource
seeking hypothesis is significant in the full sample. However, in their step-wise regression, the food seeking parameter was found to be significant. Buckley et al[4] (2007)
found a the significant and positive correlation between the variable measuring share of
ore in exports of host country and China’s OFDI for the period 1992-2001, and argued
that securing nature resources is a key factor for China’s recent growth and that the
investments to secure nature resources have been redirected to political risky countries.
In contrast, Duanmu and Guney [3] (2009) found an insignificant and counter-intuitive
negative sign for resource seeking variable. They explained the phenomenon by arguing
that nature resources attract some industries but not necessarily the others, and therefore the coefficient is insignificant for the whole sample. Kolstad and Wiig [7](2009)
confirmed that the coefficient of nature resource seeking proxy is significant and positive
as expected in the non-OECD sub-sample.
Fung et al[6] (2009), Cheng and Ma [5] (2008) and Duanmu and Guney [3] (2009)
found geographical distance as a deterrent of China’s OFDI. Buckley et al[4](2007), in
Chapter II. Literature Review and Hypotheses
8
contrast, found an unexpected positive sign in the 1984-1991 sample of OECD and nonOECD countries. They interpreted the phenomenon as a result of increased maturity of
Chinese market-seeking investors and increased propensity of seeking natural resources
all over the world. Kolstad and Wiig [7](2009) found distance significant and negative
in non-OECD countries sub-sample, indicating that distance only affect location choice
for non-OECD countries.
Political risk rating of the host country has been commonly used as a proxy to study the
effect of host country institution environment to China’s OFDI. Buckley et al[4](2007)
found a counter-intuitive and significant sign on political risk rating for sub-sample
of 1992-2001, implying that during the period, Chinese enterprises prefer to invest in
politically risky countries. Cheung and Qian [9](2009) found that Chinese OFDI is
insensitive of host country political risk ratings. However, Duanmu and Guney [3]
(2009) found that China’s OFDI are attracted to host countries with good institutional
environment.
Besides unconditional effects of institution quality of host country and natural resources
on China’s OFDI, Kolstad and Wiig [7](2009) also believed that there is a joint effect
of institution and nature resource in host country on China’s OFDI because given the
competitive advantage that Chinese enterprises operating in emerging market or underdeveloped countries, the return is greater in countries with poorer institution ratings if
nature resource is present in those countries Other explanation of the interaction term
is also possible.
For summary of literature findings, see Table A.1 A.2 and A.3
2.3
Considerations of China’s OFDI in European Union
(EU) and North America
Hanemann [10]( 2012) suggested that, nature resource, as an overall goal of Chinese
global acquisition, is also a target of China’s OFDI in the EU and United States. Therefore, Chinese enterprises have been eagerly involved in investments in energy sector.
However, I will not consider nature resource as a motivation in my study because Chinese investors are seeking opportunities to secure their position in nature resource by
taking over more European and American energy companies instead of exploiting their
nature resources. Moreover, Apoteker et al[11] (2013) suggested that Chinese investment in utility sector of EU and North American have gone through a spring board in
Hong Kong, then to the destination country. Big investment in utility sector will not be
shown in the data for Mainland China.
Chapter II. Literature Review and Hypotheses
9
Hanemann [10] (2012) found that Chinese investors are seeking advanced industrial
assets in EU and USA. However, Chinese enterprises seem to be more interested in the
advanced technologies in EU because they are taking the opportunity of economic crisis
in EU to acquire assets in lower prices. The utility sector is also more preferable than
the utility sector in US because privatization in EU forced EU enterprises to attract
foreign capitals. Although the US is more advanced in several high-tech clusters than
EU, it does not attract more investment in those sectors then EU does.
Hanemann [10] (2012) observed that although commercial opportunity is important to
Chinese enterprises when making investment decisions, policy of Chinese government
also plays an important role in location selection. Concerns about national security of
China drive Chinese enterprises to invest defense industries in both the EU and US.
Policy is expected to be more influential on Chinese OFDI in the future, as Chinese
government and enterprises become more familiar with doing business abroad and their
skill of measuring the risk of doing international business is improved.
From previous literatures (see Table A.1 A.2 and A.3 ) and specific considerations on
EU Member States and North America countries, several determinants can be eliminated
by intuition for the case of China’s OFDI in EU and North America. First of all, I will
not consider the contribution of distance to OFDI since there is not much variation of
distance between EU a country and China or between North American countries and
China. Second, I will not count the effect of political risk in my study because both EU
and North American countries are relatively politically stable. The political risk rating
will be similar for most of observations. Last but not the least, nature resource seeking
will not be included in the study for two reasons: One, natural resources in EU and North
American countries are not being exploited by Chinese enterprises. The host countries
do not have much reserve of natural resources. Two, although Chinese investors have
been devoting their wealth into utility sectors in EU and North America, they are not
interested in taking the resource from EU and North America, but interested in stepping
into the management of huge utility or energy firms and getting easier access to natural
resources from rest of the world.
2.4
Hypotheses
I would like to make following hypothesis prior to my estimations:
1. Chinese investors will seek market opportunities in EU Member States and North
American countries. They will invest more in countries with greater market size
Chapter II. Literature Review and Hypotheses
10
and trade openness. Therefore, I expect positive signs on both host countries’
GDP and trade openness.
2. Exchange rate has two channels to influence FDI inflow into host country. Therefore, what we will end up with will be a mixed effect of the two and we can only
see which side is more dominant than the others.
3. Since EU countries and North American countries are known for their advanced
level in technology. Chinese investors might be seeking technologies in these countries. Therefore, I expect positive sign on technology seeking proxies.
4. It is also reasonable to consider the growth of host country’s productivity as a determinant of China’s OFDI besides technology seeking proxies. Greater productivity growth in host countries may attract more investment from China. Therefore,
I expect a positive sign on the growth of real GDP of host country. I chose a one
year lag in my specification because evaluation of investment is usually done with
the data of previous year.
5. Since China has become more open to its trade and foreign investment policies
over the years, the economic environment is like to be more and more supportive
of China’s OFDI. Time trend may have a significant effect on China’s OFDI to
account for factors taking places gradually over time and not captured by other
factors in the equation. Therefore, I expect a positive sign on time trend variable.
6. Since China’s OFDI to EU and North America did not decrease during crisis
period, Chinese investors have been blamed as taking the chance of buying cheap
assets during the crisis period. Therefore, I expect a positive sign on the dummy
variable of crisis period.
Chapter 3
Data and Methodology
3.1
Data
In my estimation, I will be considering macroeconomic level determinants of China’s
OFDI to EU Member States and three North American Countries (Canada, Mexico and
U.S.A) during the period of 2004 - 2012.
3.2
Specifications
Specification 1:
OFDIj,t = β0 + β1 GDPj,t + β2 GDPGrowthj,t−1 + β3 TradeOpenessj,t + β4 REERj,t
Specification 2:
OFDIj,t = β0 + β1 GDPj,t + β2 GDPGrowthj,t−1 + β3 TradeOpenessj,t + β4 REERj,t +
β5 R&Dj,t + β6 2ndEduj,t + β7 TimeTrendt
All variables are defined in Table A.4 .
OFDIj,t is the OFDI flow from China at year t, to host country j, collected from the
statistical bulletin of China’s Out ward Foreign Direct Investment.
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Chapter III. Data and Methodology
12
GDPj,t is the current GDP adjusted by Purchasing Power Parity of host country j at
year t, collected from World Economic Outlook.
GDPGrowthj,t−1 is the real GDP growth rate of host country j at one year prior to year
t, that is , year (t-1), collected from World Development Indicator.
TradeOpenessj,t is the value of imports plus value of exports in percentage of current
GDP in host country j at year t. Imports and exports data are collected from World
Development Indicator.
REERj,t is the real effective exchange rate calculated by consumer price indices in host
country j at time year t, collected from World Economics Outlook.
R&Dj,t is the Research and Development expenditure in percentage of current GDP in
host country j at year t.
2ndEduj,t is defined as the enrollment in secondary education in percentage of total labor
force in host country j at time t. Both indicators were collected from World Development
Indicator.
TimeTrendt is defined as the distance of current year to the year 2004 plus one. For
instance, in year 2004, the time trend will be 1; in year 2005, it is 2, and so on. More
detailed explanation of variables can be found in Table 2.
3.3
Methodology
In order to examine whether the determinants of OFDI to EU countries are different
from the determinants to North American countries, I decided to include a EU dummy
variable, equal to 1 when the country is EU Member States, while 0 if it’s North American
countries. Dummy variable for crisis period can be defined as 1 if the year is from 20092012, other wise zero. The variable is aiming at accounting for impact of crisis period
China’s OFDI.
First step of my estimation is to examine Specification 1 and Specification 2 for the full
sample, with both EU countries and North American countries. Then I will repeat the
same steps on the EU sub-sample to see if the result is significantly different from the
full sample.
Chapter 4
Results
Table A.6 shows the estimation results on the full sample. Equation 1 is the baseline
estimation of the sample. GDP of host country is positively and significantly correlated
with OFDI from China to host country, indicating that Chinese investors are attracted
to countries with bigger market size. Trade openness is also found to be statistically
significant and positively correlated with China’s OFDI flow. However, the sign of
Real GDP growth rate is counter intuitive. The negative and significant sign can be
interpreted that Chinese investors are not interested in countries with fast productivity
growth. REER of host country has a negative sign but it is not significant. The result
corresponds to my hypothesis that the effect of REER might be ambiguous.
Equation 2 adds the R&D Expenditure variable to the baseline equation. It did not
change the sign and robustness of the variables in baseline equation. Although the R&D
Expenditure in percent of GDP of host country is not statistically significant. Equation
3 adds in secondary education variable to baseline equation instead of the R&D Expenditure variable. It did not change the sign and robustness of baseline equation variables.
The secondary education variable itself was not significant but has a positive sign, corresponding to my hypothesis that Chinese investors are more interested in countries with
better technology background.
Equation 4 adds time trend specification to the baseline equation. The sign and robustness of GDP and trade openness remained the same. However, when adding time
trend variable, real GDP growth rate became insignificant while time trend obtained
a significant and positive sign. There is no evidence that Real GDP growth rate is a
determinant of China’s OFDI, while China’s OFDI growth over time because of factors
cannot be captured in the equation, such as policy changes in China and the world economic environment. REER is always not significant, meaning that the effect of REER
on OFDI is ambiguous.
13
Chapter IV. Results
14
Equation 5 includes the baseline equation and the crisis dummy variable. The signs and
robustness of other variables did not change after adding the crisis variable. A positive
and significant sign of crisis variable was obtained, meaning that Chinese investors intentionally increased the amount of FDI into EU and North America during the crisis
period. Notice that crisis variable and time trend variable cannot be included in the
equation at the same time because they are highly correlated. Crisis period took place
in the second half of study period, when the time trend value is greater. However, crisis
only explains part of external factors of China’s OFDI growth, while time trend shows
a net effect of all factors cannot be counted by other variables. Time trend accounts for
the effect that open policy in China increases China’s OFDI in EU and North America
over time, as well as the effect that Chinese investors increases their investment during
crisis period, which occurs in the second half of study period.
Equation (1) in Table A.8 is a full estimation including corresponding to specification
2. All signs and robustness remained the same as previous estimations.
In the EU sample estimation, the results (See Table A.7 and Table A.8 ) are very similar
from the estimation for the full sample. The robustness and coefficients are close to the
estimation for the full sample, except in Equation 4 and 5, REER has a negative sign and
statistically significant in 10 percent level, meaning that Chinese investors are attracted
to depreciating currencies in EU. However, it became insignificant in full specifications.
Therefore, same conclusions can be drawn for China’s OFDI in EU countries and there
is no evidence that the determinants of China’s OFDI in EU countries are different from
those in North American countries.
Chapter 5
Conclusions
This paper attempts to test if conventional determinants of China’s OFDI can be applied
to China’s OFDI in advanced economies, such as North American countries and EU
Member States. Formal statistical analysis was conducted to prove or disprove my
hypotheses. Some of my findings conform perfectly to my predictions, but also reveal
rather interesting stories.
I found conventional results for market-seeking hypothesis via the host country’s PPP
adjusted nominal GDP and trade openness. However, the insignificant coefficient of real
GDP growth of the host country indicates that investors from China are not interested
in investing in destinations where productivities are catching up.
Although earlier studies demonstrated the ambiguous connection between exchange rate
and FDI (Pain and Welsum [2](2003)), I found that one of the channels does dominate
in the case of China’s OFDI to EU countries. The significant and negative relationship
indicates that Chinese investors are interested in host countries with weaker currencies
so that financing of capitals will be easier. However, the results were not robust when
complete specification is applied to the dataset.
I did not find evidence that Chinese investors are seeking technologies in North America
and EU countries. It is possible that the technology-seeking motivation might be captured in the time trend variable or crisis variable rather than the two technology-seeking
proxies in my specifications, because China’s OFDI significantly increased during the
period of 2009-2012, indicating that Chinese investors might be taking the opportunity
of financial crisis to acquire cheap technology asset in North America and EU countries.
It is also possible that although it is intuitive that Chinese investors are interested in
technological assets in advanced economy, the investments are not captured in the data,
15
Chapter V. Conclusion
16
because some Chinese firm conduct their OFDI via their Hong Kong branches, but the
data only captures investments from China Mainland.
Time trend variable was found to be significant and positive. It captures any factor
that changed over the study period. One favorable explanation is that the time trend
variable reflects the policy liberalization of China on OFDI over the study period. The
Chinese government became more and more supportive to OFDI projects and therefore
China’s OFDI increases over time. Since crisis took place during 2009-2012, the second
half of study period, when time trend values are larger, the time trend variable is highly
correlated with the crisis dummy variable and can catch the investor behaviors during
the crisis period as well. Thus, the positive correlation between time trend and China’s
OFDI also indicates that Chinese investors increased their investments in EU and North
America countries during the crisis period, possibly for the sake of acquiring cheaper
assets.
No factor has been found significantly different for the full sample and for the EU subsample, indicating that the determinants of China’s OFDI to EU countries and to EU
and North America countries are the same. Unfortunately, since there are only three
countries and less than thirty observations for North America sub-sample, I was not able
to test whether the determinants for North America countries are significantly different
from those for EU countries, but comparing the EU countries and all countries in my
sample, I found that the determinants for EU countries are not significantly different
from the determinants for all EU and North America countries.
Appendix A
Supplementary Tables
17
Appendix. Supplementary Tables
18
Table A.1: Summary findings of Earlier Studies on China’s OFDI I.
Authors/
GDPhost
Variables
Buckley et
Trade
R&D
Openess
lnGDP (+)
-
2nd
Education
-
-
al (2007)
Secondary
Fung et al (2007)
GDP (+)
Net trade of
R&D
education
host country over
Expenditure
enrollment in
its current GDP
in host country
percent of
(not significant)
(-)
total population
in host country
Net trade of
Duanmu and
lnGDP (+)
Guney(2009)
host country
-
-
-
-
-
-
-
-
-
-
-
-
over its current
GDP (+)
Cheng and Ma
lnGDP (+)
-
(2008)
Net trade of
Kolstad and
GDP(+)
Wiig (2009)
host country
over its current
GDP (+)
Cheung and
Qian (2009)
GDPhost
GDPChina
(+)
Log (GDP
Korniyenko,
per capita
Sakatsume
PPP
(2009)
adjusted)
(+)
Appendix. Supplementary Tables
19
Table A.2: Summary findings of Earlier Studies on China’s OFDI II.
Authors/
Exchange
Time
Nature
Variables
Rate
Trend
Resource
Distance
Nature log
of Bilateral
lnShare of
exchange rate
ore and metal
Buckley et
between
exports in
Ln(Distance)
al (2007)
host country
total exports
(-)
and China
of host
(not
country (+)
-
significant)
Shares of
food, fuel,
Fung et al (2007)
GDP (+)
-
and ores
Distance
in total
(-)(+)
exports of
host country
Bilateral
Share of
exchange
ore and
Duanmu and
rate between
Guney(2009)
Cheng and Ma
metals in
Ln(Distance)
host country
total exports
(-)
and China
of host
(+)
country
-
-
-
-
(2008)
Kolstad and
Ln(Distance)
(-)
-
-
-
Wiig (2009)
Distance
(-)
Share of raw
materials
Cheung and
-
Qian (2009)
Time
exports in
trend (+)
total exports
-
of host
country
Korniyenko,
Sakatsume
(2009)
-
-
-
-
Appendix. Supplementary Tables
20
Table A.3: Summary findings of Earlier Studies on China’s OFDI III.
Authors/
Patent
Host Country
Institution
Variables
Registrition
Political Stability
∗Resource
lnAnnual
ln Host country
patent registrations
political stability
in host country
rating(-)
GDP (+)
-
Buckley et
-
al (2007)
Fung et al (2007)
-
Host country
Duanmu and
-
political stability
-
Guney(2009)
rating(+)
Cheng and Ma
-
-
-
-
-
-
(2008)
Kolstad and
Wiig (2009)
Cheung and
-
Qian (2009)
Time
-
trend (+)
Korniyenko,
Sakatsume
(2009)
-
-
-
Appendix. Supplementary Tables
21
Table A.4: Data Specifications
Variables
Definition
N
Source
Proxy for
225
-
-
Annual FDI
OFDI from
flow from
China
China to
host country
Annual current
GDP of host
GDP − P P Phost
country adjusted
World
225
Market
Economy
seeking
by Purchasing
Outlook
Power Parity
One time
lag of Real
Real GDP Growth Lag1host
GDP growth
World
200
Productivity
Development
seeking
of host
Indicators
country
Net trade
of host
World
Trade in %
GDP host
country in
219
Market
Development
percent of
seeking
Indicators
its current
GDP
Real Effective
Exchange
World
REER
host
Rate of
216
Macroeconomics
Economy
Host country
condition
Outlook
calculated
by CPI.
Appendix. Supplementary Tables
22
Table A.5: Data Specifications continued
Variables
Definition
N
Source
Proxy for
Percent of
population
World
2nd edu
host
finished
200
Technology
Development
seeking
secondary
Indicators
education in
host country
Research
and
Development
World
R&Dhost
expenditure
218
Technology
Development
in percent
seeking
Indicators
of current
GDP in
host country
EU = 0
if host country
EU
is not a EU
225
-
EU
Countries
Member State
, otherwise
EU =1
Year 2004 = 1,
time trend is
Time
incremented by
225
-
trend
Policy
changes
one for the
next year.
Crisis = 1 if year is
Crisis
2009-2012,
otherwise,
crisis = 0
225
-
Crisis
Appendix. Supplementary Tables
23
Table A.6: Results: Full Sample
Variables
1
2
3
4
5
.0936
.2191
.0615
.0898
.0912
(.0146)∗∗∗
(.0518)∗∗∗
(.0141)∗∗∗
(.0141)∗∗∗
(.0142)∗∗∗
-30.1782
-27.1997
-34.1109
-10.58195
-2.6714
(12.6106)∗∗
(11.527)∗∗
(12.0133)∗∗∗
(13.3055)
(14.7258)
Trade
2.6289
3.4302
2.3278
2.4055
2.4637
Openess
(.6884)∗∗∗
( .6718)∗∗∗
(.6604)∗∗∗
(.6678)∗∗∗
(.6706)∗∗∗
-7.7508
-7.5251
-3.2366
-8.3107
-8.4231
(5.9278)
( 5.8961)
(5.6710)
(5.7289)
(5.7627)
-
-
-
-
-
-
-
GDP
Real
GDP
Growth
REER
R&D
-
-.0936
( 2.5913)
2nd
-
-
Edu
EU
20.7368
(41.3073)
-
-
-
-
-
-
Crisis
-
-
-
-
N
179
164
156
179
179
R-square
0.2483
0.2044
0.1939
0.3025
0.2946
0.2311
0.1792
0.1670
0.2823
0.2742
0.0000
0.0000
0.0000
0.0000
0.0000
Time
Trend
Adjusted
66.9385
( 18.2702)∗∗∗
306.7772
(91.1130)∗∗∗
R-square
Prob>F
Appendix. Supplementary Tables
24
Table A.7: Results: EU Countries
Variables
1
2
3
4
5
.2152
.2154
.1782
.2006
.2071
(.0520)∗∗∗
(.0533)∗∗∗
(.0550)∗∗∗
(.0515)∗∗∗
(.0513)∗∗∗
-26.7747
-26.7541
-28.2359
-13.6762
-6.8852
(11.71431)∗∗
(11.9410)∗∗
(12.3471)∗∗
(12.7061)
(14.0430)
Trade
3.4583
3.4588
3.2725
3.2464
3.3019
Openess
(.6801)∗∗∗
( .6841)∗∗∗
(.7327)∗∗∗
(.6746)∗∗∗
(.6717)∗∗∗
-9.0876
-9.0710
-5.2620
-10.1379
-10.3063
(5.8285)
( 6.0901)
( 6.1508)
(5.7499)∗
(5.7524)∗
-
-
-
-
-
GDP
Real
GDP
Growth
REER
R&D
-
-.0269
( 2.7654)
2nd
-
-
Edu
Time
14.5085
(43.8353)
44.12603
-
-
-
Crisis
-
-
-
-
N
155
155
135
155
155
R-square
0.2125
0.2125
0.1892
0.2429
0.2436
0.1915
0.1861
0.1577
0.2175
0.2182
0.0000
0.0000
0.0000
0.0000
0.0000
Trend
Adjusted
( 18.0286)∗∗∗
220.8656
(89.1986)∗∗∗
R-square
Prob>F
Appendix. Supplementary Tables
25
Table A.8: Results: Complete Specifications
Variables
(1) Full Sample
(2) EU Countries
.1681
.1661
(.0551)∗∗∗
(.0557)∗∗∗
.-16.2109
-13.4988
(13.6580
(13.9964)∗∗
Trade
3.0884
3.0677
Openess
(.7268)∗∗∗
( .7336)∗∗∗
.-5.6385
-8.4830
(6.3462)
( 6.6555)
-.5047
-.3340
(2.7413)
( 2.8061)
2nd
19.1938
3.3909
Edu
(42.7836)
(44.6864)
GDP
Real
GDP
Growth
REER
R&D
EU
-108.5363
-
(164.1356)
Time
43.0090
49.7984
Trend
(21.1660)∗∗∗
(22.3654)∗∗∗
N
144
135
R-square
0.2079
0.2197
0.1609
0.1767
0.0000
0.0000
Adjusted
R-square
Prob>F
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