Bachelor Thesis in Economics and Business Economics
The People’s Republic in the European Union:
China’s New Investment Imperative after the
Sovereign Debt Crisis
Vincent Coon Dr. B. Karreman
August 17th, 2015
Academic Year 2014/2015
Table of Contents
1. Introduction ................................................................................................................3
2. Theoretical Framework............................................................................................. 6
2.1 The eclectic (OLI) paradigm................................................................................................................6
2.2 Recent theoretical extensions............................................................................................................7
2.3 OLI paradigm applied to Chinese MNEs in Europe.................................................................7
2.4 Beyond the eclectic paradigm............................................................................................................9
3. Hypothesis development.........................................................................................10
3.1 Geographic choice of FDI in the European Union................................................................10
3.2 Industry-specific choiceof FDI in theEuropean Union....................................................13
4.Data and Methodology..............................................................................................16
4.1. The European SovereignDebt Crisis andData sub-sampling.....................................16
4.2. Investment Data.....................................................................................................................................18
4.3. Methodology: choice of model.......................................................................................................21
4.4. Dependent variable..............................................................................................................................22
4.5. Independent variables and data aggregation.......................................................................26
5.1 The MNLModel:Drivers andinterpretationof model.....................................................27
5.2. Hypotheses evaluation.......................................................................................................................30
5.2.1. Hypothesis 1.........................................................................................................................................30
5.2.2 Hypothesis 2..........................................................................................................................................31
The 2009 Sovereign Debt and Banking Crisis has left continental Europe in a dire
economic state. Stagnating GDP figures, sluggish productivity growth, volatile
inflation expectations about the Euro and an unsatisfied labor market have engulfed
the European Union and together, yield a gloomy outlook for an economic recovery
of the EU. Countries within the EU have emerged in varying degrees of economic
stability from the crises, and the European Central Bank as well as the fiscal
authorities of member states struggle to find a unifying policy to stop the intra-
European divergence of economic performance. Such conditions seem heinous to
most investors, and many have eschewed Europe as a destination for new capital
investments. This attitude stands in stark contrast to China. The People’s Republic
has moved in the opposite direction of the general financial consensus and flooded
the European market with capital for cash-strapped industries (Anderlini, 2014).
China’s willingness to lean against the wind despite a global economy that has been
succinctly punctured by the 2008 global financial crisis and 2009 European
sovereign debt crisis is particularly exemplified through their outward foreign
direct investments (OFDIs). In 2008, global OFDIs fell by 15 percent, while Chinese
OFDI has doubled (Davies, 2012). Even with the onset of the 2009 crisis, while
global OFDI has collapsed by a staggering 43 percent, China has still managed to
grow its OFDIs by 1 percent (UNCTAD, 2012).
With such vast scaling back of investments on a global level, liquidity in the
European market had dried up and left an investment gap for many governments in
need for financial support. Governments desperate for funding are putting ‘assets up
for sale’ (Hook & Sakoui, 2012). China has filled this void of lacking capital support
and stepped into the situation by making Greenfield FDI investments available.
While the rest of the world secured their money in financial save havens, China has
taken a calculated risk in using a highly receptive equity market that was left by the
financial mayhem of 2009. Assets were cheap and equities undervalued (The
European Union Chamber of Commerce in China , 2013). Specifically, while Chinese
OFDIs in Europe between 2004 and 2008 were a mere EUR700 million, this number
increased threefold to EUR2.3 billion in 2009 and 2010, and again tripled in 2011
alone to an astonishing EUR7.4 billion (Hanemann & Rosen, 2012). Clearly, changes
have occurred in Chinese investment behavior after the crisis, but these are not
simply changes in magnitude. The People’s Republic was able to opportunistically
diversify its portfolio of investments, and secure a solid foothold in various
European industries and countries. While the rest of the world was retrenching,
China was spending (LI & FUNG Limited , 2009 ). As will be explained in the
‘Investment Data’ section of this paper, this increase in magnitude has to be
evaluated against an overall small Chinese investment portfolio in the European
Union. When compared to China’s investments in other regions of the world, such as
Hong Kong, the Americas and Africa, their investment in the EU is only a small
Prior to 2009, China has traditionally invested in key economies within the EU and
geographically clustered its capital flows around countries such as Germany, France
and the UK (Clegg & Hinrich, 2012), all of which had to offer strong prospects for
Chinese investors to get know-how, technology and efficiency. Its OFDIs were thus
by no means evenly distributed amongst the 27 EU member states. Not only the
‘western European core’ (highly developed economies such as Germany) has seen
Chinese OFDI, but also peripheral and less progressive economies of the EU (such as
Spain, Greece or Italy) have experienced Chinese FDI investments (Hanemann &
This investigation proposes that there is a parallel narrative developing in the EU.
The crisis has opened up new opportunities for China to cheaply expand its quest
for investment in European countries. While key economic players in the region will
continue to attract capital (Hanemann & Rosen, 2012), it is assessed whether China
will also divert capital to a new frontier of less developed, crises stricken countries
within the EU, as such countries offer a comparatively inexpensive avenue for
Chinese consolidation within countries. Additionally, the post-crisis economic
landscape provides an opportunity for China’s intentions of rebalancing its economy
from an outdated growth model with a heavy focus on manufacturing towards a
more service-based economy. With its strong dependence on production, China has
a gravely underdeveloped service sector (Farrell & Grant, 2005; Hope, Yang, & Li,
2003, p208), a disadvantage it could decimate through strategic investments in the
European Union after the crisis.
This paper will delve into the idiosyncrasies of this modified approach and identify
how the 2009 crisis changed the Chinese investment attitude compared to their pre-
crisis objectives. In this sense, the main research question this paper will answer is
How has the Chinese Foreign Direct Investment behavior changed after the
2009 European Sovereign Debt Crisis relative to before?
No paper in the academic literature has thus far attempted to comprehensively
disentangle the change in Chinese foreign direct investment behavior post-crisis. On
the one hand, this analysis will determine whether, geographically, the destinations
for Chinese capital have been diversified and broadened to increasingly cater the
financial needs of peripheral European economies. On the other hand, additional
focus is put on the approach. In particular, it will be investigated, across the
European Union, to what extent a shift has occurred from a strategy revolving
around manufacturing investments to adopting a strategy that supports Chinese
efforts to mature as an economy and realign their global growth strategy with the
demands of the 21st century. It is crucial to appreciate the intentions and
motivations of massive Chinese capital flows within the European Union. Much of
the economic stability within the European Union depends on how China will
allocate its resources across the member states. Investment decisions of the
People’s Republic will undoubtedly steer the direction and pace of the economic
recovery and future prosperity of the European Union, and an intricate
understanding of such decisions is thus essential.
The investigation is structured the following way. The subsequent section will delve
into the theoretical grounding of this paper and discuss the factors that lead to
foreign direct investments as well as the decisions of domestic Chinese companies
to go abroad and seek out international opportunities. The third section will
organically build upon these decisions and reason more specifically why and how
China uses OFDIs in the European Union. Embedded the most recent academic
literature, the hypotheses of this investigation will be derived. The fourth and fifth
section will explain the methodology of the analysis in tandem with the data sources
utilized in this context, as well as the results that have been found in the course of
this analysis. Finally, section six will conclude the investigation and add
recommendations for further research.
2. Theoretical Framework
2.1 The eclectic (OLI) paradigm
China’s motives for expanding overseas and venturing beyond their domestic
borders through outbound investments are diverse. Most notably, however,
Dunning’s (1993) OLI paradigm provides a solid theoretical foundation for
addressing the questions of why multinational enterprises (MNEs) decide to invest
abroad through FDIs. The acronym OLI stands for ‘Ownership’, ‘Location’ and
‘Internalization’, and each letter in the acronym represents a possible advantage
that can arise due to a firm deciding to invest abroad through FDIs. The OLI
paradigm therefore highlights how MNEs stand to gain a competitive edge. For one,
some forms of ownership (O) are more conducive to business abroad than others,
and the burden of operating costs in foreign territory may be alleviated through a
firm’s ownership idiosyncrasies. This ‘ownership related effect’ (Dunning, 2001) is
often intangible in nature (e.g. a particular brand name may provide broader access
to financial capital). Further, distinct advantages can be derived from the location of
the host country (L). Factors such as labor costs are non-transferrable factors
unique to the country that a MNE decides to invest in. Finally, the internalization of
an MNE refers to the benefits reaped from a particular entry mode into a foreign
economy, through which cross-border activities and untapped synergy effects may
2.2 Recent theoretical extensions
However, often countries and companies feature unique characteristics that make
this elementary theoretical framework somewhat inadequate to describe its
intentions and actions of going abroad. Dunning himself has addressed this
insufficiency in his most recent work (Dunning & Lundan, 2008), which adds the
element of ‘institutional analysis’ to the existing OLI framework. In their work,
Dunning & Lundan propose that certain governmental and institutional procedures
directly impact every aspect of the OLI paradigm, either through incentive
structures, or how these are enforced. Specifically, they propose four
microeconomic factors that prompt firms to engage in outward foreign direct
investment, namely 1) Securing Natural Resources, 2) Exploring New Markets, 3)
Buying Strategic Assets, 4) Improving Efficiency of Operations across borders. This
extension is especially applicable to Chinese MNEs, which are tightly woven into a
market economy that is prone governmental sophistry. The OLI theoretical
framework has thus been suitably refurbished to account for the institutional reality
of Asian economies. Sun et al. (2010) have further highlighted the role the state
plays in influencing the OLI factors of Chinese MNEs, while Liang, Ren, & Zhu (2011)
have extended Dunning’s work by adding an institutional dimension. Such
extensions are a testament to the fact that the OLI theory is a solid starting point for
iliciting the motivation behind FDI investments, but that it has to be complemented
with various layers of explanation to account for the ideosycrasies of China and its
MNEs (Lu, Liu, & Wang, 2011).
2.3 OLI paradigm applied to Chinese MNEs in Europe
For this investigation, the question of how far Dunning’s OLI framework is able to
explain the choices made by Chinese MNEs to invest in Europe is paramount. In
Europe, China has few ownership advantages (O) and can rarely capitalize on
intangible abilities such as management and marketing skills. They often operate in
a knowledge vacuum, as their understanding and appreciation of foreign business
practices is at best, limited (Child & Rodrigues, 2005; Rugman & Li, 2007). Given this
lack of operational proficiency in foreign territory and a slow cultural integration
process of Chinese MNEs, China tries to compensate for this disadvantage by
strategically positioning themselves in Europe. Chinese investments are therefore
predominantly geared towards strengthening their market presence (Buckley et al.
2007). Yet, China has been able to wield influence and bridge this knowledge-gap
through an ethnicity-based support system, which operates by sharing information
and know-how of the host country’s business milieu (Redding, 1995). Through such
a network, Chinese MNEs are able to, at least partially, overcome the information
asymmetry in foreign countries such as Europe. The ultimate goal is to facilitate a
firm embedding of Chinese MNEs in the economic sphere of the European Union.
The location of Europe (L) bears a heavy weight in the case of this investigation, as
one of the key drivers of Chinese FDI there are the unique local circumstances. The
European debt crisis and concomitant business environment can be interpreted as a
‘non-transferable’ factor exclusively present in the EU. China could inexpensively
situate itself in the very center of Europe and reorganize their business activities
beyond the Chinese borders. Greenfield investments in the EU after the crisis gives
China an opportunity to organically grow at a fraction of the cost compared to
entering Europe during times of economic prosperity. The reasoning behind this
will be elaborated upon in the following section. The crisis has thus been a window
of opportunity for establishing a business in line with companies’ long-term growth
strategies. The situation of Europe as host country goes hand in hand with the
Internalization (I) aspect of Dunning’s paradigm. Without delving deeper into the
technicalities of whether the key investment instigator is the Chinese government,
or whether there are overarching political motives regarding the FDI streams into
certain industries, the OLI framework provides a convincing motivation for why
Chinese MNEs seek investment opportunities in the European Union.
2.4 Beyond the eclectic paradigm
Despite the OLI paradigm, there are also more compact theories that aim to explain
the motivations behind sending capital abroad. Brezis, Krugman, & Tsiddon (1993)
coined the term ‘Leapfrogging’ in connection with technological innovation and the
cyclical development of international competition. This term encompasses the
systematic process through which ‘lagging countries’ replace the ‘leading countries’
in an industry by applying a novel breakthrough technology. The lagging country
leapfrogs past the leading country. However, since its inception, leapfrogging has
been used in a variety of ways and is attached liberally to any mechanism in which a
country or company is able surpass a current market leader through not just a
breakthrough technology, but an ability to avoid the pitfalls of earlier adopters of a
particular technology, business plan, incentive structure etc. For instance, the
academic literature has used leapfrog developments of China in areas such as
sustainable innovation (Watson & Sauter, 2011), energy technologies (Gallagher,
2006) and particularly, how China uses OFDI in Europe to leapfrog Research &
Development processes (Di Manina, Zhang, & Gammeltoft, 2012).
Interestingly, the motivations of going abroad defined by the OLI paradigm are
almost identically reflected in China’s ‘going out’ policy of the 21st century. Their
12th Five Year Plan states that China must promote ‘outbound investments’
(Robinson, 2013). The theoretical framework of this investigation is thus mainly
comprised of Dunning’s eclectic (OLI) paradigm, which is instrumental in describing
the motivations behind Chinese FDI streams to the EU, but naturally, elements of
leapfrogging are also inherent in the Chinese approach to economic expansion.
Together, they build a theoretical framework for this investigation and explain the
causes of Chinese economic involvement in the European Union.
3. Hypothesis development
3.1 Geographic choice of FDI in the European Union
As Chinese investments in the European Union are of major geo-political interest, a
considerable proportion of the literature in this field has been comprised of
extensive, often government subsidized, reports. The academic literature, however,
also covers aspects of Chinese OFDIs. The findings of these expansive reports as well
academia point to the same direction and draw a similar picture of where the Sino-
European economic relationship stands. However, there is no unified indication of
what to expect in the future and how the crisis has impacted Chinese investment
Fundamentally, it is crucial to acknowledge that FDIs originating from China are
unequally distributed in the EU. Countries differ substantially in their ability to
court capital from Chinese investors (Drogendijk & Blomkvist, 2015), and there are
consolidated patterns of investment streams. The consensus in the academic
literature is that Chinese FDIs are concentrated on a small fraction of the 27
European Union member states, and is confined to ‘a few leading member states’
(Clegg & Hinrich, 2012), especially referring to economies such as Germany and the
UK. These sentiments are echoed by the China Council for the Promotion of
International Trade (2010), which concludes that there is a ‘strong preference’ on
the People’s Republic side towards countries that already have strong economic ties
with China, such as France, Germany and the UK. European Union Chamber of
Commerce in China (2013) similarly stresses that Chinese ‘investments are
concentrated in Western Europe’. While acknowledging the apparent clustering of
investments, the European Union Chamber of Commerce in China has also
mentioned in their report Chinese Outbound Investments in the European Union
that particular technologies and labor skills are responsible for China gravitating
towards key economic payers in the European Union. UK’s expertise in high
technologies and financial services or Germany’s manufacturing capabilities,
automotive expertise and advances in electronics are frequently cited as major pull
factors for China (The European Union Chamber of Commerce in China , 2013).
Investments are hence allocated strategically around countries and industries that
are deemed most useful for the expansionary intensions of China.
There is, nonetheless, a mounting body of evidence in the academic literature that
indicates a shift away from this clear-cut agglomeration of FDIs around key
economic players in the EU. FDI streams are not only a function of how strategic it is
to invest, but also a function of economic strength of the country. While a strong
economy may signal the prospect of gaining know-how and other valuable
resources, weak economies similarly attract investments (Kottaridi, 2005). This can
be through the prospect of, for instance, company bargains or cheap land and labor
supply. Similarly, an in depth Financial Times series has investigated these new
streams of allocation of capital within the European Union. Research conducted by
Anderlini (2014) highlights that, given the ramifications of the 2009-crisis, cash is
‘flowing from China into some of the hardest-hit countries of the Eurozone
periphery’, a clear indication for a shift in geographical preferences. Xu, Thieß and
Tianlong (2012) also conclude in their lengthy report that China’s outward foreign
direct investment strategy towards Europe has changed. While the wealth of
academic research conducted on Chinese geographical preferences concurs on the
distribution of investments, a new research frontier that questions this distribution
has emerged. Yet, given that the sovereign debt crisis is very recent occurrence, the
research is still relatively scarcely populated with purely academic sources, and to a
larger extent based on institutional and governmental research.
This investigation identifies with the new body of research. The analysis aims to
build upon the new stream of literature developing and intends to contradict the
historic distributional investment pattern. It is argued that post the 2009 sovereign
debt crisis, geographical investments have turned more opportunistic in nature.
Given the near break down of the European financial system, China’s intentions
have strayed from solely investing strategically, to geographically seizing
opportunities elsewhere in the European Union that have surfaced after the crisis.
This investigation argues that especially financially constrained countries have been
pushed to the center of attention of Chinese investment aspirations, as they provide
an environment where they can drastically increase their presence in the European
market and explore this market cheaply and with a competitive edge. In an
environment of fringe economies where the crisis either forced companies out of
business, or those remaining in business, are unwilling to invest (Lin, 2013), China’s
financial commitments are welcome sources of capital. Peripheral countries are
seeking the potential benefits Chinese Greenfield investments yield for them.
Whether through knowledge spillovers, technology transfers or job creation, it is
evident that crisis stricken economies are very receptive to foreign direct
investments from China. Consumers stand to benefit not just through such factors,
but also through the increased competition a Chinese presence induces as well as
access to one of the largest and fastest growing economies in the world.
Yet China similarly sees the value of using Greenfield investments to operate more
efficiently in the European Union by specializing, increasing its economies of scale
and hence reducing production costs. For instance, Hanemann & Rosen (2012)
argue that Europe has workforce skills that are desperately required for Chinese
production chains. This mutually beneficial situation, where countries that have
been severely impacted by the crisis identified the need for such investments, and
the People’s Republic that uses this receptiveness and need as an opportunity to
integrate their business practices and facilities in the European market as an
integral economic driver. These claims will be substantiated through empirical
research and econometrically strengthen the observations that fringe economies
receive relatively more investments after than crisis than their core-country-
counterparts. Given the prospect of synergies for both involved parties, in addition
to China’s willingness and need for deeper European market penetration, the first
hypothesis proposed by this investigation is the following:
Compared to the pre-crisis period, the post-crisis period is more likely to see
Chinese Greenfield investments in fringe economies1 as opposed to core
3.2 Industry-specific choice of FDI in the European Union
However, assuming that the root cause of China’s willingness to invest in more
peripheral economies is solely based on the country’s favorable financial
environment and countries’ responsiveness to financial and economic stimuli, is
unrealistic. It is of great importance to reason further and appreciate the intentions
of Chinese foreign direct investments. While there is evidence that China has shifted
its geographical focus and loosened its hardline approach to only a select few
economies, this may not only be a result of cheap access to fringe economies. The
flipside of being able to inexpensively set up a physical presence in Europe through
Greenfield investments is that the countries in which these investments occur may
be qualitatively inferior to their ‘core’ counterparts. Such qualitative differences
pose varying degrees of risk for the investing country (Bouchet, Clark, &
Groslambert, 2003). In this sense, the macroeconomic shock of the sovereign debt
crisis may have exposed or magnified countrywide structural weaknesses, yet is it
by no means the only reason for the grim situation some countries in the European
Union find themselves in. There are country level heterogeneities that decisively
influence the decision of Chinese MNLs to invest. China does not simply send FDI
streams to capital deprived fringe economies in hope of finding attractive deals.
Much rather, this paper proposes that Chinese firms were able to capitalize on the
crisis and invest strategically in various industries according to their expansion
desires. This investigation therefore suggests that the drivers of Chinese Greenfield
investments in peripheral economies of the European Union are specific industries.
1 Portugal, Italy, Ireland, Greece, Spain
2 Germany, France, Great Britain, Netherlands
Hence, it is not just the geographical destination of investments that has changed in
the course of the sovereign debt crisis, but also the industries in which foreign direct
investments are made. A general trend, even before the crisis has hit Europe, has
been that China is in a transitioning phase of its economy. Domestically, China is
experiencing a move away from low value adding manufacturing activities, and a
significant transition to a higher echelon in the value chain. The focus has shifted
from the mere provision of goods, to providing value added products. Thus, China is
rebalancing away from manufacturing to services (Jen, 2013), and this has been
evident through Chinese inward FDI. The growth of FDI in the service sector in
China has been hailed as ‘the most significant development’ in the Chinese economy
(KPMG, 2015), and surpassed the manufacturing FDI in 2014. This domestic
development will naturally be mirrored by Chinese investment intentions beyond
their domestic borders. The IMF frequently stresses the importance of China’s
‘process of rebalancing’ the economy ‘from manufacturing to services’. (Lagarde,
2015). The economic consensus is firm on its conclusion that services are to become
the most important and economically decisive sector in the Chinese economy (The
Economist, 2013; Broadman & Sun, 1997). These domestic developments have been
on their way since the trade liberalization of 2001 and Going Global policies of 2000,
yet are only starting to manifest themselves in Chinese outward FDI recently.
Overall, a major channel for this transformation will be OFDI streams into western
The momentum of rebalancing the economy towards services and away from
manufacturing has been reflected in OFDI investment strategy in the second half of
2000-2010. Outward Greenfield FDI has been boosted by service enhancing
investments in the European Union. For one, the need for more sophisticated
distribution networks, which are required for the export of higher quality goods
arose. Therefore, ports such as the one in Piraeus (Van der Putten, 2014) but also in
Naples and Antwerp have become an important destination for Chinese
investments. Greenfield OFDI is however not only required for such pragmatic
solutions to the export constraints for the market of high quality goods. Beyond
trade facilitating infrastructure, China is also aiming to explore the European market
itself and compete with local, western service providing firms. In this sense, modern
sales infrastructure is a key area for growth of service firms, as they provide
branding and after-sales services (see Huawei, China Unicom, Covec etc.) Banks,
telecommunication companies, but also real estate and construction companies
have identified the need to invest abroad and strengthen their competitiveness
through Greenfield FDI in Europe (Hanemann & Rosen, 2012). Hanemann & Rosen
(2012) further find out in their research that China is entering Europe increasingly
through Greenfield investments. Accordingly, China stands to benefit significantly
from the service-oriented environment of the European Union, not only for the
fiercely competitive environment in China itself, but also for starting to compete in
the European market. Therefore, this investigation expects a move away from the
manufacturing industries such as low-, mid- and high tech manufacturing, and focus
on realigning their intentions in Europe in accordance with domestic Chinese
economic development towards services.
This means that while there has been a wealth of investment targets available in the
European Union, China may selectively seize the opportunities left by the sovereign
debt crisis. It can be argued that if China’s economy has been transforming
domestically to a service based economy, they have used Greenfield FDI in the
service sector of western economies all along, without the occurrence of a crisis.
This investigation does not debate this. However, this is not the focus of this paper.
Much rather, it is argued that given the Chinese orientation towards a service-based
economy, the sovereign debt crisis has served as an opportunity to materialize this
orientation and invest accordingly in the European Union. Through the very
definition of Greenfield investment, it is argued that because machinery, land and
means of production (Wang, 2009) can be acquired more economically, the
investments into particular industries in the service sector have been exacerbated.
The analysis of this paper is directed towards identifying this behavior post crisis
and pointing out that the change in investment behavior is in line with China’s long-
term needs of taking its economy from a labor intensive one to a more service based
one. Europe’s advanced industries and developed economies served China through
service provision opportunities and an ability to establish new operating platforms
through Greenfield investments. Ultimately, this allowed China to develop its
competitive economic edge. Given this background, this investigation’s second
hypothesis is derived to be the following:
Compared to the pre-crisis period, the post-crisis period is more likely to see
Chinese FDI investments in service industries as opposed to manufacturing
While academia has made it clear that investments have increased in quantity and
value, no paper has thus far comprehensively looked at where and how this wealth
of capital has been distributed in the European Union post the 2009 crisis.
Essentially, the picture has changed in the last half decade, but it is still unclear how
exactly. So far, the literature has made clear that 1) China has a strong geographical
focus in the EU on developed economies and that 2) China’s economy is undergoing
a transformation from manufacturing focused to service focused. The changes in
types of industries that has been invested in and geographical destination of OFDI
are scrutinized. This paper will address the duality of deviations that have occurred
after the crisis in Chinese investment behavior and will empirically assess the
validity of the hypotheses derived.
4.Data and Methodology
4.1. The European Sovereign Debt Crisis and Data sub-sampling
The 2008 financial crisis exposed and magnified the deeply rooted financial
problems of the European Union. Historically, before the monetary union has
formed, yields on government bonds3 have been radically different. Investors and
banks knew that yields have to converge once the Euro currency is shared, and thus
saw an arbitrage opportunity, essentially a ‘free lunch’. Once the 2008 financial
crisis evolved, the same bonds that increased substantially in value due to yield
convergence now lost nearly all of their value through yield divergence. Banks,
investors and governments were left with a worthless position on peripheral debt,
and as this debt was often bought with a high leverage factor or used on balance
sheets as assets, the situation in Europe was a seemingly insolvable conundrum. At
this point, a cash abundant Chinese Republic became involved in the European
Union. While the whole of Europe was pulled into a downward spiral of systemic
risk and financial distress, a more isolated and remote financial system in China has
stepped into to alleviate the consequences of unsustainable budget deficits and
bankrupted balance sheets. Therefore, amidst the ensued sovereign debt crisis, the
role of China has been to provide the financial investment many countries were
In light of how the data is segmented in this paper, it is vital to realize how different
the economic environment has been pre and post the crisis. Before it, investors
seemed oblivious to the fundamentals of peripheral economies, seeing only a
currency union and not the individual member states that comprised it. Yet after
late 2009, the overspending and over borrowing has been exposed, and the financial
system nearly collapsed, as both banks and countries were holding large amounts of
worthless peripheral debt. This investigation thus splits the dataset into two
subsamples. The first will capture the somewhat tranquil period from 2003-2009,
while the second will contain the tumultuous scramble for financing from 2010-
3 They represent the risk factor associated with lending money to a country. The
higher the yield, the higher the risk of not recouping the money
4.2. Investment Data
This paper’s data sample is composed of Chinese Greenfield foreign direct
investments to the European Union between 2002 and 2013. To put the investments
into the EU into perspective, one has to appreciate that only around 5% of all
Chinese outward foreign direct investments are targeted at the EU, while a large
part (72%) stays mostly within Asian boundaries (Xu, Thieß, & Tianlong, 2012). The
analysis uses exclusively Greenfield data for some key reasons. As the European
Chamber for Commerce in China points out, Chinese investment profile in the EU is
more common as FDI in the form of Greenfield investments, as opposed to M&A and
other forms (The European Union Chamber of Commerce in China , 2013) Further,
M&A only comprises as small fraction of Chinese outward FDI compared to
Greenfield (Salidjanova, Going Out: An Overview of China’s Outward Foreign Direct
Investment , 2011). Overall, Greenfield has been the most common and
predominant form of FDI for China, which is why this paper uses the relative wealth
of data for such investments. Contrasting this, the amount of instanced of M&A deals
in the European Union are highly limited, and do not necessarily provide a
comprehensive and accurate representation of any trends forming after the crisis. In
addition to the lack of M&A deals in the region, these deals would have been
gathered from a separate database. Consequently, industry specifications and names
are different to the Greenfield dataset used in this investigation. Efforts to merge
and match respective industries would have, in addition to the restricted number of
deals, increased the scope for errors and imprecision.
The Greenfield dataset used in this paper encompasses all 28 EU-member states
except for Malta, Slovenia and Austria. After cleaning the dataset and removing all
irrelevant (non-EU countries) observations, 764 deals remained to be scrutinized.
The Greenfield data on investment projects has been gathered from fDi Markets
(2003-2013), which covers the broadest spectrum of cross border Greenfield
investment activity and provides information for all countries and the respective
sectors. As a service provided by the Financial Times, it is highly reputable source of
data with absolute reliance. The database provides essential information on deal
specifications and especially the fact that fDi markets is amongst the most utilized
Greenfield databases in the industry adds weight to the quality it represents.
Data on FDI flows are recorded on a deal-by-deal basis, as opposed to deal-values.
This means that a one-off multibillion-dollar deal between China and an EU member
state will not make the respective country a number one recipient of FDI. Rather
than detailing the investment value, this dataset records the instances of the deal
itself. No matter how substantial China’s financial commitment is across the deals,
this bears no significance for this investigation. Only the fact that a deal has been
made in the first place between China and EU counterparty is recorded. The
intuition behind a deal-by-deal analysis is that even if a country receives a
substantial amount of funding in a single deal after the sovereign debt crisis, this
does not represent the attractiveness of this country. Much rather, the frequency of
deals is the focus of this paper’s data analysis. An increase in frequency is hence
indicative of an increase in attractiveness. While this approach by no means proves
causality, the data sample allows for a meaningful interpretation of the data in a
post-crisis economic environment.
Further, an important aspect of this research is the time-parameter. The period
from 2003-2013 has been chosen for two factors. One factor is the undeniable surge
in Chinese interest and OFDI in Europe in this time period. China’s Going Global
policy and membership of the World Trade organization in 2001 started to
economically reform the country and the policy truly started to unfold in the first
decade after its initiation. Annualized inflow of capital increased threefold from
2006-2009, and tripled again from 2009-2011 to EUR7.4 billion (Hanemann &
Rosen, 2012). The main focus of this paper gyrates around the 2009 sovereign debt
crisis, it is paramount to properly assess the timing of investments after the crisis.
Firstly, it is crucial to pinpoint the exact date of the crisis. While many scholars
agree that the sovereign debt crisis arose in late 2009 (Moody & Sandri, 2012), it
was Greece’s new government’s revelation of a more than double increase in their
adjusted budget deficit from 6% to 12.7% that ultimately sparked the sovereign
debt crisis (Gibson, Hall, & Tavlas, 2012). Thus, the consensus on when the
sovereign debt crisis started is the point at which Greece publicly announced its
technical bankruptcy, which will also be used in this paper as the starting date of the
crisis. As the crisis only fully unfolded during 2010 and commenced near the end of
2009, this investigation will include the deals from 2010 onwards as the post crisis
period, yet still count the 2009 period to the pre-crisis sub-sample. The economic
intuition behind this is that all deals for which the sovereign debt crisis has been a
decisive factor and where it has been explicitly taken into account will
predominantly come into existence after 2010. A ‘break’ or reorientation in
investment behavior forms not immediately after the actual occurrence of the shock,
but only once opportunities for China have crystallized from the crisis. Negotiations
and preliminary talks will have occurred after suitable areas for Chinese FDI
investments have been identified in 2010, once the extent and severity of the crisis
has been accurately determined. The four-year time span after 2010 is thus an
extensive period in which China processes and evaluates the economic standing of
the respective EU-member states and implements its FDI investing strategy that this
investigation aims to capture. On the other hand, the pre-2009 period in this sample
offers enough time for a solid Chinese investment pattern to have formed on a non-
macroeconomic-shock-basis. This will be China’s FDI investment behavior that is in
line with their going global investment policy of 2000. It is essential to work with
this ‘base standard’ of investments, which can be seen as a benchmark and
compared to any anomalies arising after the crisis.
As this paper works with Chinese investments data, it is also important to touch
upon the caveats that accompany the collection and interpretation of deals
originating from China. Clarification of where this paper’s data sample comes from,
what it measures and how it measures it, is vital. Yet, there is one principal concern
with Chinese outbound FDIs. The nature and methodology of data collection varies
drastically amongst countries and institutions, and can often be opaque due to
disclosure constraints. For instance, while UNCTAD, the IMF or OECD give a general
overview of international investment flows, Central Banks across the world attempt
to give a more disaggregated perspective on FDI flows. The National Bureau of
Statistics in China yet again draws a biased picture of their investment activities.
Eurostat in the EU only provides Europe-related FDI activity from abroad. Given the
complexity of international financial markets (i.e. tax optimization, shell companies
etc.) and multitude of players involved, only seldom is a similar account of FDI flows
produced by two independent parties. This leads to incomplete or heavily delayed
statistical data and inference. What China claims to invest in Europe and Europe
claims to have received in FDI from China is, in the majority of cases, dissimilar.
Linking these concerns of working with investment data of the people’s republic of
China back to the analysis of this paper, it is important to appreciate that even if this
investigation only consulted a high quality data source, accuracy and reliability of
this data can be skewed. The picture drawn by this investigation is based upon data
that may not be entirely representative of Chinese investments in the European
4.3. Methodology: choice of model
This paper will evaluate the relationship between the deal frequency between China
and an EU member state, and the particular region in which these deals occur, i.e.
the higher the amount of deals, which region is most likely to receive these deals.
This investigation then goes beyond merely assessing the region in which deals
occur, and delves into analyzing which industries amongst these regions were more
or less likely to be the recipient of Chinese FDI flows. This paper uses a categorical
dependent variable of nominal nature, with more than two outcome categories, yet
there is no intrinsic order in these categories. It is assumed that China will invest in
regions and industries that will maximize the benefit they derive from making such
investments. Thus, according to utility maximization theory, the discrete choice
model that offered itself for the purpose of this analysis is a Multinomial Logit Model
(MNL) (Wrigley, 1985). From a technical perspective, a key assumption of this
model is the property of independence of irrelevant alternatives, or IIA. It
essentially demands that with any particular set of choices for the dependent
variable, alternatives within this set must be independent from one another (for a
more detailed picture, see Wrigley, 1985). Applying this property to the choice of
investments for China within the EU, it must hold that any country must be different
from its alternatives and equally competitive. Through a re-estimation with a
multinomial probit model (MNP), it will be assessed how severe the impact of the
IIA assumption is on the MNL model results. With similar outcomes, it can be
assumed that the IIA properties are no hurdle for robust results and a robust model.
Although all countries in this data set exist in a union (the European Union) with
one another, and some of them even operate through a uniform monetary policy
regime (Eurozone), this paper stipulates that they the countries as investment
choices are independent from one another. Fiscal policy is unique for every country
in the EU and each individual country has exclusive perks to offer to its investors.
From varying market saturation levels, to particular resources, skills, knowledge
and technology, the European Union could not be more diverse as a destination for
Chinese investments. Therefore, it is assumed that random components of all the
alternatives in this investigation’s sample are indeed independent and not
correlated with one another. As an additional note to the particulars of the IIA
assumption, one has to realize that when the alternative choices are fixed in nature,
the impact of an IIA violation is negligible but often overestimated. As this paper’s
data set fully meets the requirements of the MNL regression, it is the model of
choice for this investigation. Further, in order to establish whether the pre- and
post- crisis periods are significantly different in this model, a likelihood ratio test
will be performed. This is a key insight that will further drive the answer to the main
question of this paper of whether or not Chinese investment is different for the two
4.4. Dependent variable
The dependent variable for this investigation will be the choice between three
distinct types of aggregated countries. Each type of country is composed of EU-
member states that fall into a certain category. This means that each of the 25 EU
member states used in for this investigation is categorized into one of three types.
The intuition behind this is based largely upon the academic literature about the
European Sovereign Debt Crisis and Chinese investment behavior in the EU. The
first region (Region 1) is comprised of countries that have suffered majorly form the
sovereign debt crisis. This is in line with this investigation’s first hypothesis that
China will divest from most common recipients of FDI to peripheral economies that
have been severely affected by the ensuing credit crunch of the crisis.
In particular, the clustering of Region 1 is done in accordance with the
contemporary academic literature on the weak peripheral economies of the
European Union and the relation to the European sovereign debt crisis; Portugal,
Ireland, Italy, Greece and Spain, the so called ‘PIIGS’ or ‘GIIPS’. While Byström
(2011), Melander et al. (2011) and Pu & Jianing (2012) use the term ‘PIIGS’ in their
more technical papers as an established phenomenon, Pitelis (2012, p. 83) uses
PIIGS more holistically to trace down the root causes of the crisis through Greece,
and Hallet and Jensen (2011) explain how the term PIIGS has become a synonym for
severely impacted economies of the sovereign debt crisis (for the earliest accounts
of variations of this clustering see Borzel, (2001, p12) and for an etymological and
critical account of this clustering, see Brazys and Hardiman (2013). Clare (2008) is
said to have been the father of the term PIGS, although with one ‘I’, and stresses that
this ‘I’ can be used for both Italy and Ireland. The analysis of this paper will thus use
the clustering of Region 1 in tandem with the existing academic literature and
aggregate Region 1 as such.
The second region (Region 2) will be composed of the so-called ‘core’ recipients of
Chinese FDI Investment concentrated in Europe. These are the countries that have
received the largest amount (not value) of deals in the European Union historically.
The data on this is, unfortunately, different for Chinese and EU official sources.
However, detailed independent research specifically conducted to explore China’s
investments in the European Union (either commissioned and certified by
representative bodies of the European Union4 or in close collaboration with
representatives of various European bodies5) revealed a clear consensus on which
countries receive the largest share of Chinese OFDI (see The European Union
Chamber of Commerce in China , 2013; Hanemann & Rosen, 2012, ). They are
Germany, France, the UK and the Netherlands. Together, these countries will build
the second type of region (Region 2). This region will also be the baseline outcome
for the MNL regression analysis, as results should reflect how likely it is that China
has diverted from these core investment regions to other regions. Region 2 is
purposely chosen as the pivotal element of this investigation, and any result will be
interpreted in comparison to the baseline outcome of it.
The third region (Region 3) will be comprised of the remaining countries in the
European Union, which have neither been as severely impacted by the sovereign
debt crisis as Region 1, nor have they had the significant trade relationship with
China as Region 2. This does not mean that these countries have not been affected
by the crisis, or that they have no trade relations with China. Rather, Region 3 is a
region of moderation, which has not been created according to particular attributes,
4 The European Union Chamber of Commerce in China
5 Hanemann & Rosen, 2012
but emerged by default. With moderate amounts of Chinese trade relations and
being moderately impacted by the sovereign debt crisis, it has been comparatively
ordinary. In this sense, Region 3 can be interpreted the normal; a standard region
contrasting two more volatile ones6.
As can be seen in Table 1, the distribution of deals in the European Union according
to respective regions in a particular time frame already gives a first indication of
how the above-mentioned Regions behave. Particularly, Region 1 transitions from a
mostly single digit deal frequency to double digits post-2009. Region 3 has also
experienced very strong growth and consistent increase in deals, which doubled
from the pre-crisis to the post-crisis environment. Table 2 further highlights how
manufacturing at any level is China’s industrial foundation for investments. They
clearly outnumber the other investment industries. Interestingly, Table 3 shows
how after the crisis, Region 2 experienced vast reductions in deal frequency. Region
1 and 3 on the other hand see almost exclusively increasing numbers of deal
frequencies. Particularly Region 3 has experienced a surge in investments. These
frequency distributions already suggest that there is momentum towards the
periphery and less established economies, and immense downscaling of deal
frequencies within the core economies.
6 For an overview of regional aggregation see Appendix B
4.5. Independent variables and data aggregation
The independent variable of this investigation will be based on the different sectors
China invests in. Given the popularity of fDi Markets as a data source for Greenfield
investments, many useful classification schemes have been developed and applied
in the academic literature, and thus proven themselves. While initially the
Greenfield deals have been allocated to very specific industries in the dataset,
methodologies of aggregating these individual industries into broader categories
have been devised. The reasoning behind this categorization is that individual
industries are so distinctive and idiosyncratic, that no meaningful interpretation of
Chinese investment patterns and trends would be possible when leaving the data
compartmentalized into unnecessarily specific industries. In this sense, Burger et al.
(2013) have devised a categorization template which groups the industry sectors of
the fDi Market database into larger categories7. However, as this analysis is
particularly interested in how the service industries fair relative to the
manufacturing industries, Karreman, Burger and Van Oort (2015) have adopted a
slightly modified version of Burger’s initial categorization and used both
‘Commercial Services’ and ‘Consumer Services’ in a unified ‘Commercial & Other
Services’ category. As this dataset has only recorded five deals in the ‘Consumer
Services’ industry, this analysis adopted the categorization of Karreman et. al (2015)
7 See Appendix A for an overview of the categorization
and merged the respective deals into the ‘Commercial & Other Services’ category.
The data of the dependent variable in this investigation has therefore been grouped
in a way that is conducive to discovering meaningful trends in Chinese investment
behavior in the European Union.
Additionally, it is crucial to control for unobserved exogenous shocks that occur in
the macro environment of this analysis, and which are not relevant to this
investigation. It is possible that the phenomenon of Chinese investment behavior
varies due to reasons that lie beyond the scope of this paper’s focus, and that such
reasons may not be fully accounted for the industry explanatory variables. However,
even if such factors are not properly captured by the independent variables, the
inclusion of time fixed effects in the regression will allow the investigation to absorb
external shocks and better assess Chinese investment behavior.
5.1 The MNL Model: Drivers and interpretation of model
In the MNL model of this investigation, Region 2 is used as the base outcome. It is
important to note that the regression output of the coefficient’s magnitude is not to
be interpreted. Only the sign, positive or negative, indicates whether, based on the
industry, a particular region is more or less likely to be invested in by China
compared to the baseline. The decision to invest into a particular kind of region by
China is explained by the category of industries it invests in. Therefore, a change in
the independent variable affects the probability of which region China will invest in,
relative to the probability of China investing in the base outcome of Region 2.
Table 4 shows the outcomes of the MNL regression. The first model in table 4
provides the results of the total data sample period, that is, from 2003-2013. It is
interesting to see that on an overall basis, China, compared to low-tech
manufacturing, is significantly more likely to invest in the Processing Industries and
Natural Resources/Energy relative to the core countries. This may be due to the fact
that especially Poland and Sweden are very resource rich countries. In particular,
Poland’s silver reserves, as well as their sulfur and copper sources are in high
demand with Chinese still very dominant manufacturing industry. Sweden with high
Zinc, Lead, Copper and Iron Ore are similarly attractive targets for Chinese
industries active in the natural resource business (National Geographic, 2015).
Further, compared to low-tech manufacturing, China is significantly more likely to
invest in Region 3’s Software and ICT industries.
However, this picture changed when looking at model 2 and 3 and the situation that
persisted before and after the 2009 crisis, as opposed to looking at the overall
situation of both sub-samples combined. The pre- and post- crisis environment is
the primary focus of this investigation. A comparison between these two periods
reveals several significant differences between them. Firstly, Region 3 has yielded
very surprising results. For all investigated industries, Region 3 has seen positive
and highly significant coefficients for the post-crisis period. This indicates that,
compared to low-tech manufacturing, China has been significantly more likely to
invest in Region 3 relative to the baseline of Region 2 after the sovereign debt crisis.
This vast breadth of investing interest in this region on China’s side has been
unexpected and runs against the rational of this paper’s first and second hypothesis.
Region 3 has not been expected, relative to Region 2, to attract such wide scope of
investments. As Table 1 indicates, after 2009, there have been overall more
investments in each Region, irrespective of the particular industries targeted.
Clearly, the attitude towards Europe has changed to being a more attractive
destination for Chinese investments across the board. Given that, except for a
decreased likelihood of Chinese investment in Region 3 compared to Region 2 pre-
crisis, Model 2 of the pre-crisis results shows none of these positive and significant
coefficients of Model 3, these results question the rationale of hypothesis 1 and 2.
These ‘post-period-only’ findings in Model 3 imply that after the crisis, China has not
cherry-picked various industries in Region 3 that may or may not coincide with
their long-term objectives of establishing a more service-focused economy. An
interpretation of this feature could be that the post crisis period has seen a ‘new’
China emerge; a China that is not driven by political motives or ambitions to further
strategic placements of investments that may contribute to ulterior agendas of
China as a country. It seems that the single most important motive that Chinese
investors are striving after is commercial success. Given the variety of industries
China invests in, the immense geographic breadth of their interests and
investments, the findings of this paper suggest that Chinese investors are seeking
profits above all other considerations through their Greenfield investment
Secondly, after the sovereign debt crisis, the financial services industry in Region 1
is positive and highly significant, in contrast to before the crisis, where it is not. This
means that compared to the low-tech manufacturing industries, China is
significantly more likely to invest in Region 1 post-crisis compared to the baseline of
Region 2. These results are in line with both hypotheses of this investigation,
expecting that the peripheral economies will be pushed into the center of Chinese
investment intentions, and that these intentions are expressed through investments
in the service industry. Especially the financial service industry has received a large
quantity of Greenfield investments, as the sovereign debt crisis has left a debilitated
and paralyzed financial services system.
Further, the industry of Software & ICT has a positive and significant coefficient,
meaning that compared to low-tech manufacturing, China has also been more likely
to invest in this industry in Region 1 as opposed to Region 2. Given that a majority of
this industry is comprised of areas such as Software & IT services as well as
Communications, it could be implied that these results are in line with the
expectations of this paper and reiterate the hypothesis of service-oriented
investments in severely impacted economies of Region 1. Additionally, running the
Likelihood Ratio test for the models of this investigation revealed a significant
difference between the pre- and post crisis period. This is a key indication for a
changed investment behavior on the side of the People’s Republic and positively
answers the question of whether China has changed its investment behavior after
the crisis. Thus, the fact that China behaved differently in the pre- and post- periods
can be established. See Appendix C for relevant values.
5.2. Hypotheses evaluation
5.2.1. Hypothesis 1
Particularly Region1 in Model 3 strongly suggests that Chinese investment behavior
has changed in the post-crisis environment in line with what this investigation has
predicted. China is, compared to Region 2, significantly more likely to invest into the
peripheral economies of Region 1 through particular industries. It is however
important to also consider the implications of Region 3’s results. The vastness
across industries of investments in Region 3 suggest that it is certainly not merely
Region 1 that has been pushed to the center of attention of China. Region 3 has
become a major recipient of investments. While these results do not negate the first
hypothesis of this investigation, they shine light on how attractive the whole of
Europe has become for Chinese investors. The results do not point towards a
uniform interpretation of why exactly China’s investment approach to the European
Union has changed; yet they nonetheless provide significant evidence for the fact
that it has changed. Among this, China has become significantly more likely,
compared to Region 2, to invest in peripheral economies of Region 1, and therefore,
this paper does not reject Hypothesis 1.
5.2.2 Hypothesis 2
While it is apparent that there has been an overall surge in investments post crisis,
and that this surge has manifested itself in both the peripheral and normal regions
of the European Union, the reasons for this are diverse. Nonetheless, Region 1 in
Model 3 confirms the hypothesis that the service industry is of particular interest to
China, as it is more likely compared to Region 2 to invest in these industries in
Region 1. Therefore, the second hypothesis of this investigation is also not rejected.
Yet, the drivers of China’s investment intentions are also of interest for this
investigation, and this paper proposed that the main driver of the decision to invest
in a particular region is the different industries targeted. However, the question of
why China is more likely to invest in a particular region is a matter of high
complexity. Certainly, the contradictory results of Model 3 are a testament to this
multifaceted problem of disentangling or establishing the driving forces behind this
decision making process.
The service-focused investments of China in Region 1 may follow a different
rationale that the one outlined in this paper, namely that such investments have
been made in an effort to take the Chinese economy from a manufacturing to service
providing economy. It seems like no coincident that China has filled the void of an
inadequately capitalized financial system after the credit crunch (Acharya et al.,
2014) through establishing its financial service business in severely hit economies.
Has it been China’s intention to push into the service industry in Region 1 as part of
their efforts to create a more service oriented economy, or was the service industry
merely the industry most urgently requiring capital investments after the crisis, and
thus most attractive to enter? The results for Region 3 in model 3 make the latter
interpretation a more reasonable alternative, implying pragmatic and need-oriented
investment decisions, as opposed to ones that are guided by the imperative of
making the Chinese economy a more sophisticated service provider.
Overall then, Region 1 in Model 3 provides evidence to believe that China has used
the opportunities after the sovereign debt crisis to establish itself as a market force
within the financial (and other) service industry. However, with regards to Region 3
in Model 3, there is also evidence that China has simply increased their quantity of
investments, without a particular agenda in mind and merely attempting to extract
as much revenue as possible from any industry in any of the region’s countries.
Bearing the novelty of the sovereign debt crisis and its consequences in mind, there
are also very few schools of thought in the academic literature explaining Chinese
investment behavior and intentions. Hence, few reference points offer themselves as
guiding principles among which the results of this analysis could be situated,
meaning that few scientific investigations exists that could add weight to - or
question - the conclusions drawn by this analysis.
In order to ensure the robustness of this investigation’s results, additional steps
have been taken. On the one hand, a multinomial probit model (MNP) has been
estimated, to see if the IIA properties are a serious problem to the estimation of the
MNL regressions. As can be seen from Table 5, the results of the MNP re-estimation
lead to extremely similar results to the MNL regression. This suggests that that IIA is
no obstacle to the results found in the MNL regressions, and poses no problem for
this paper’s finings. On the other hand, two separate cut-off dates were used to
estimate the MNL regressions and investigate how valid the results are when
alternating the cut-off point. Both 2008 and 2011 have been used as break-dates.
2008 has been chosen because in late 2007, the global financial crisis ensued and
also affected the European economies. 2011 has been chosen because it could be
argued that the transition time it took for China to adapt to the new economic
reality in the EU and act upon the opportunities it presented. As can be seen from
Table6, the results of 2011 point to the same findings of the originally used cut-off
date, 2009, thus confirming the results of the MNP re-estimation. The 2008 model of
Table7 on the other hand has some anomalies that have to be elaborated upon. In
particular, the highly significant negative coefficient for the financial services
industry in Region 1 of Model 2 stands in contrast to the other estimated models.
The interpretation of this that the Financial Service industry is, compared to the
baseline of Region 2, significantly less likely to receive Greenfield investments from
China. As 2008 is as an earlier cut of date than 2009, it could be argued that the
global financial crisis originating in the United States already had an adverse impact
on PIGGS countries in the time period from 2008-2009. The significant coefficient
could suggest that before 2008, China actively avoided investments in these regions,
as they did not present any opportunities, but that this aversion dissipated in the
year from 2008 to 2009. However, given the unusually large negative coefficient of
15.387, it can also be argued that this coefficient is simply the result of a dataset
anomaly, such as a zero-observation. Given that neither the MNP re-estimation nor
the 2 alternative cut-off dates share this result, this coefficient is deemed unreliable
and does not impact the overall interpretation of this investigation’s results.
Therefore, given that with the remaining alternative cut-off dates as well as the MNP
re-estimation similar results are found, the robustness of the results as well as the
chosen cut-off date of 2009 can be established.
The topic of this investigation is one of relative novelty. The recent financial as well
as sovereign debt crisis have thrown the financial system in the European Union
into grave economic difficulties, and the response of especially central banks has
been equally novel. Zero-bound monetary policies pushed central banks to the brink
of their ability to intervene in financial markets. Quantitative easing and negative
bound interest rates are all phenomena that have never been seen in the European
Union, and the effects are unpredictable, despite a compelling narrative central
banks lay upon the economic development. In this sense, the implications of this
paper are to be interpreted with caution.
This investigation sought out to examine how Chinese investment behavior in the
European Union has changed after the sovereign debt crisis. In particular, the
analysis aimed to find the drivers of Chinese Greenfield FDIs for specific
geographical regions in the European Union before and after the sovereign debt
crisis. It has been argued by this paper that China’s decision of where to invest is
predominantly driven by the different industries that are targeted, i.e. China is more
likely to invest in a given region, depending on the industry they target. Overall,
while this study has been able to establish that a change in investment behavior
occurred, the rationale behind why it has changed only partially aligns with the
hypotheses of this investigation. It is clear, however, that the results for the post-
crisis period indicate a break in Chinese investment behavior, even if this break
cannot be classified further through establishing the main drivers of Chinese
investment decisions. Thus, overall the characteristics of Chinese investment
behavior have changed. Through this papers analysis, and the acceptance of
hypothesis 1 and 2, the main research question of how Chinese Foreign Direct
Investment behavior has changed after the 2009 European Sovereign Debt Crisis
can be answered. Relative to the pre-crisis main recipients of Chinese Greenfield
OFDI, Region 2, it has been shown that industries in Region 1 and the majority of
industries in Regions 3 are significantly more likely to receive Chinese Greenfield
investments in the post-crisis environment. Therefore, Chinese investment behavior
has changed in that it diverted its investment focus to peripheral economies8 as well
as ‘normal’ economies, as opposed to a continuation of core economic investment
focus, which is the main finding of this investigation. China’s heightened interest in
the European Union as a whole is indisputable, and it investment behavior has
evidently changed, while its intentions behind this change remain ambiguous.
This investigation could have been made more conclusive through several aspects.
Most importantly, the data sample could have been enlarged to include an even
greater variety and number of deals. While practical and logistical reasons made it
unreasonable to use Mergers and Acquisitions data in the analysis, the conclusions
drawn would have benefitted from additional observations. Further, it can be
argued that the first hypothesis is based upon a trend that may be too vast and
continuous in nature to be observed in a time frame as short as this investigation’s
time parameter. The re-orientation of China towards a service economy may be in
progress, yet is it difficult to determine how advanced China as a transitional
economy has come thus far, and how relevant its ambitions to expand into the
European service sector actually are.
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Appendix A: Taxonomy of investments by sector.