Report DeSanto Fiorina

Spatial Patterns in US Foreign
Direct Investment
International Master in Public Finance – 2019/2020
Alessia DE SANTO, Camilla FIORINA

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Table of contents
1. Introduction ......................................................................................................................................... 3
2. Theoretical background and sources of spatial interdependence. ...................................................... 4
3. Data and methodology ........................................................................................................................ 5
4. Descriptive statistics ............................................................................................................................ 8
4.1 Standard descriptive statistics ....................................................................................................... 8
4.2 Spatial descriptive statistics ......................................................................................................... 12
5. Choice of the econometric model and results: full sample ............................................................... 15
5.1 The choice of the spatial model ................................................................................................... 16
5.2 Results .......................................................................................................................................... 19
5.3 Robustness check: alternative weight matrix .............................................................................. 21
6. Choice of the econometric model and results: Europe and Central Asia .......................................... 22
7. Conclusions and limitations ............................................................................................................... 24
Appendix A ............................................................................................................................................. 26
Appendix B - Codes ............................................................................................................................ 28
Appendix C - Database: full sample ................................................................................................... 28
Appendix D – Database: ECA countries .............................................................................................. 28
References ............................................................................................................................................. 28

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1. Introduction
Foreign Direct Investments are a very dynamic phenomenon at the lead of the globalization wave which
has characterized all markets in the last decades. In this context of international integration, the activity
of multinational enterprises (MNEs) has increased relentlessly. As reported by Dharmapala and Riedel
(2013), from 1990 to 2004, Foreign Direct Investment by MNEs grew at an average annual rate of 12,4%,
which is more than double than the 5% growth rate of economy.
As the share of international transactions represented by FDI increases, so does the research interest
for its determinants, as all countries, especially developing ones, are eager to take steps to attract
foreign funds.
While a substantial body of literature exists about factors driving FDI patterns, no consensus has been
found, meaning that there is not a universally accepted set of variables which can be considered as the
true determinants of FDI.
Moreover, most of existing empirical and theoretical findings rely on a bilateral framework which most
of the time fails to take into account the inherent complexity of FDI decisions, which are multilateral by
their own nature. For example, an investment abroad could be addressed to a geographical position
which enables the company to strategically outsource their production in different countries in order
to exploit factor cost differences. Or, a host country could serve the parent as a base to operate in
neighboring economies. Agglomeration externalities and imperfect capital mobility - limiting the funds
that MNE can invest abroad - can also create interdependent FDI decision across host countries.
Standard econometric techniques cannot take into account multilateralism of FDI dynamics, since the
latter implies that observations across countries are not independent, a violation of the most
fundamental assumption of traditional econometrics.
Spatial econometrics models help to overcome this problem allowing for spatial autocorrelation
between observations, thus capturing potential spillover effects or the impact of market potential on
the level of FDI in one country.
Last years have seen a development of the literature on spatial determinants of FDI patterns.
Coughlin and Segev (2000) were the first to apply a spatial econometric model to study the
determinants of US FDI in Chinese provinces, and found that volumes of FDI in one region were
correlated with those of neighboring regions. Subsequent studies made on different parent countries
- among others Baltagi et al. (2007) Blonigen et al. (2007) for US outward FDI, Garretsen and Peeters
(2009) for Dutch outward FDI, Ledyaeva (2009) for Russian inward FDI, and Chou et al. (2011) for
Chinese outward FDI - find spatial correlations across FDI levels in neighbor countries.
Our work fits into this latest line of research, implementing a spatial econometric analysis on the
determinants of US outbound FDI in 2013 on a sample of 85 developed and developing countries.
It is structured as follows: section 2 introduces the reader to the main existing models about FDI
patterns. It includes a literature review on the most important theoretical and empirical works on the
topic. Section 3 provides a description of the database and the weight matrix used for the analysis , and
is completed by section 4 which presents the descriptive statistics. Sections 5 and 6 include the spatial
econometric analysis performed over the full sample and over a selected subsample of countries,
respectively. Section 7 concludes and presents the limitations of the research.

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2. Theoretical background and sources of spatial interdependence.
The first formal development of MNE theory was provided in two important theoretical works from
1984.
Markusen (1984) presents a general equilibrium model in which parent firms establish affiliates to
produce and sell in the host country, in order to gain on trade costs, which is known as “horizontal FDI”.
Since this translates in higher fixed costs, this kind of MNEs arise in countries with large markets (which
allow for economies of scale and offer many investment opportunities) and where set-up cost of
factories are low and trade costs are high.
In contrast, Helpman’s (1984) general equilibrium model assumes that affiliates are created by parent
companies to carry out some stages of the production process, in order to access cheaper input factors,
while the home market remains the main destination of the firm. This type of investment is usually
referred to by the term “vertical FDI” and is more likely to come into existence when the host country
is unskilled-labor abundant and trade costs, as well as plant set-up costs, are low.
This gravity-type framework laid the foundation for the majority of empirical studies that followed,
which generally report as the main determinants of FDI in a host country: market size, distance from
the parent country, human capital endowment, availability of infrastructure, quality of governance and
security of property rights.
However, this kind of framework fails somehow to take into account the inherent complexity of FDI
decisions, as it considers MNEs’ investment decisions as bilateral.
More recent models have tried to relax this limitation, mainly through three extensions.
First, Carr et al. (2001) and Markusen (2002) have merged the gravity-type environment into a model –
known as “knowledge-capital” model - in which the equilibrium between vertical and horizontal FDI in
MNEs is endogenously determined, depending on factor availability and barriers to trade and
investments.
“Export-platform” models (Ekholm et al. (2003), Yeaple (2003), and Bergstrand and Egger (2004))
consider the possibility that the output of foreign affiliates is rather exported than sold in the home
market. In other words, MNE invest in a particular country to use it has a “base” to reach neighboring
markets. In an empirical study from 2005, Hanson et al. consider the share of US affiliates export to
home and foreign markets and find evidence of the importance of export-platform FDI in US MNEs.
Alternatively, MNEs can fragment the vertical chain of production across multiple countries in order to
exploit the comparative advantages in costs and productivity of different markets, before the product
reaches its final destination.
Baltagi et al. (2007) named this last practice “complex-vertical” FDI and formalize the importance of
“third-country effect” in FDI patterns. They consider a model with two sectors (one homogeneous and
one differentiated), three factors of production (capital and skilled and unskilled labor) and three
countries. When more than two countries are included, the decision to invest in a host country is not
bilateral anymore, but depend also on the characteristics of the third market.
Traditional econometric techniques are not suitable for capturing a third-market effect, since the latter
implies that FDI decisions across host countries (hence FDI volumes) are not independent. Spatial

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econometric techniques allow to overcome this problem and each of the described FDI motivations has
a different implication in term of spatial relations
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.
Following Blonigen et al. (2007) in this section we fill focus on the correlation between the level of FDI
in a country and in its neighbors, and how the surrounding market potential influences the level of FDI
in a country. However, our estimation will reveal the importance of other sources of externalities.
Horizontal FDI arise with the objective to avoid high trade costs for the parent companies, which are
usually due to import barrier imposed by host countries. In pure horizontal models the only trade off
faced by companies when deciding to establish foreign affiliates is whether the trade cost avoided from
operating directly in the host market is greater than the set-up costs. In this framework, surrounding
market potential or FDI level in neighbor countries will not play any role in the final decision outcome.
For this theoretical prediction to be realistic, however, one needs to assume that all destination markets
have sufficiently high trade protection against imports from other destination markets.
When this is not the case, and the commercial protection among destination countries is lower
compared to trade costs incurred by the parent to export in those markets, it is likely that MNE will opt
for a “export-platform” type of FDI.
Establishing one affiliate in a strategic position will bring the same benefits coming from horizontal FDI
in every destination country, while saving the high set-up costs of multiple plants, since it allows the
company to rich simultaneously all the neighbor markets without incurring in important trade costs.
For this reason, it is plausible to assume that the surrounding market potential will have a positive effect
on the level of FDI in the host country of interest. At the same moment, since fixed costs coming from
setting-up multiple plants are much higher than trade costs between neighbor countries, the decision
of a parent company to establish an affiliate in a country will likely come at the cost of not establishing
in the neighbors, which translates in a negative sign of the spatial lag on the FDI.
Vertical FDI model implies that companies choose to invest in the host country which offers the lowest
production costs for the activity which needs to be relocated. Analogously to what happens for export-
platform, the decision of a pure vertical MNE to invest in a country comes at the expense of neighboring
countries. On the other hand, since in this kind of MNE the final destination of products remains the
home market, the surrounding market potential is supposed to have an insignificant effect on the
volume of FDI in the host country.
In complex-vertical MNEs the production process is “fragmented” across different countries.
Consequently, a dense supplier network in a region can decrease the costs of separating productive
activities. Moreover, there might be other agglomeration forces (e.g. location of immobile resources
as mines, IT districts) which, as long they concern the production process of parent companies, can
attract FDI. In this sense, it is plausible to expect that both spatial lag on FDI and on market potential
can have a positive impact on the FDI inflow into a host country.
3. Data and methodology
The analysis to understand the determinants and pattern of US investment abroad is performed over
85 host countries for the year 2013. The database includes 14 Asian and Pacific (AP) countries, 29
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It exists a multitude of spatial relations which will be presented in the following sections. Details on the econometric model and
techniques will be provided in section 5.