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UPPSALA UNIVERSITY
Department of Economics
Master’s Thesis
Author: Karl Geijer
Supervisor: Chuan-Zhong Li
Autumn 2008
Foreign Direct Investment in Mexico:
Possible Effects on the Economic Growth
1
Abstract
The purpose of this paper is to examine whether foreign direct investment, FDI, has any
impact on economic growth in Mexico. In order to find a possible connection I use a multiple
regression analysis with GDP per capita as dependent variable. Furthermore, I critically
examine previous studies of FDI and its effect on GDP per capita in Mexico as well as other
studies with several developed and developing countries. The difference between this paper
and previous studies is that the data is more up-to-date here. My results, like most of the
previous studies, do not indicate on any statistical significance that FDI has a positive effect
on economic growth. FDI do however seem to produce positive spillover effects on the
domestic economy, mainly through knowledge and technological spillovers.
Keywords: Foreign direct investment, spillover effect, economic growth, endogenous
growth, Mexico
2
Table of contents
1. Introduction ............................................................................................................................ 4
2. Theoretical framework ........................................................................................................... 5
2.1 FDI ..................................................................................................................................... 5
2.1.1 Positive effects from FDI ........................................................................................... 8
2.1.2 Negative effects of FDI ............................................................................................ 11
2.2 Economic growth ............................................................................................................ 12
2.3 Mexico ............................................................................................................................ 16
3. Data and statistical analysis ................................................................................................. 18
3.1 Results ............................................................................................................................. 19
3.2 Comparison with previous studies ................................................................................. 22
4. Discussion ............................................................................................................................. 27
5. Conclusion ............................................................................................................................ 30
References ................................................................................................................................ 32
Appendix ................................................................................................................................... 35
3
Abbreviations
DI – Domestic Investment
FDI – Foreign Direct Investment
FIAS – Foreign Investment Advisory Service
GDP – Gross Domestic Product
HFDI – Horizontal Foreign Direct Investment
IDP – Investment Development Path
IFC – International Finance Corporation
IMF – The International Monetary Fund
MNE – Multinational Enterprise
NAFTA – North American Free Trade Agreement
OECD – The Organization for Economic Cooperation and Development
UNCTAD – The United Nations Conference on Trade and Development
VFDI – Vertical Foreign Direct Investment
4
1. Introduction
The foreign direct investment (FDI) flows has increased dramatically since the last decade.
The annual average inward flows of FDI across the world during 1990-2000 was 492 605
million US dollars. The size of FDI has increased every year during this decade and was as
large as 1 833 324 million US dollars in 2007. However, the FDI is spread unevenly across the
world. The obvious action for multinational enterprises (MNEs) would be to invest more in
regions with low labour costs and large supplies of natural resources. This is not the case
though as the developing economies only received 499 747 million US dollars from FDI in
2007 (UNCTAD, 2008). Although a large portion of the FDI flows has been directed towards
developed countries, the developing countries share has increased significantly during the
last decade. The winners here are Latin America and Asia while Africa only receives
moderate amounts of FDI. In Latin America it is Argentina, Brazil, Chile and Mexico that
receive the largest amount of FDI (Ramirez, 2000). Mexico is no exception when it comes to
the increase in FDI inward flows. The annual average inward flows of FDI was 9 368 million
US dollars during 1990-2000. The increase in FDI gave an inward flow of 24 686 million US
dollars in 2007 (UNCTAD, 2008).
Many studies on whether or not FDI affect economic growth have been done through the
years. These studies all come to varied conclusions. Some find that FDI indeed affect the
economic growth while others find no such connection. The earlier studies focus on country
case studies and industry level cross sectional studies. Overall, they find that there is a
positive correlation between average value added per worker and the productivity of a MNE.
Later studies gave up on country case studies and instead shifted the focus to firm level
panel data. Typical for these studies is that the majority find no effect from FDI on economic
growth. Moreover they find negative spillover effects from MNEs in developing countries
while positive spillover effects only are found in developed countries. Since older studies are
found inadequate, more recent studies have adopted another approach. These argue that
spillovers should be thought of as exchanges between different industries which mean that
focus should shift to vertical (inter-industry) externalities. This refers to the contacts
established between domestic suppliers and the foreign firms (Alfaro et al, 2006).
5
The purpose of this paper is to study possible effects on the economic growth in Mexico
from FDI. In order to achieve this we shall conduct regression analyses with data on FDI and
GDP per capita in Mexico during the period 1993-2007. Furthermore we shall examine
earlier studies that deal with FDI and its effect on economic growth in Mexico as well as in
general. My own results will be interesting in the way that the data is very recent. We will
therefore be able to see if any changes have occurred during the last years, compared to
earlier studies. It is a fact that the results vary much among the previous studies. Therefore
recent studies have put focus on explaining why this is the case. We will examine some of
these results in this paper since they are relevant to my own results. In this paper FDI will be
expressed in millions of US dollars and the economic growth as GDP growth per capita. GDP
per capita has endured a lot of criticism for not including effects on the environment and
distribution of income. Nevertheless, it is the measure most commonly used and that is why
we shall use it as well.
The remaining part of this thesis is structured as the following: Section 2 present’s available
theories on FDI and its effect on the economy. It also contains information on growth
models and the theoretical impact from FDI. Finally economic information concerning
Mexico is presented. Section 3 present’s my own result and compares it with earlier studies.
Section 4 contains interpretations and a discussion of the results. Finally section 5
summarizes the paper.
2. Theoretical framework
2.1 FDI
There are two forms of foreign investment. The first is when foreign investors purchase
stakes in a domestic enterprise, an indirect investment or foreign portfolio investment as it
is known. The other is FDI and it is when a foreign owner finance the enterprise but is also
directly involved in the management of the enterprise. The International Monetary Fund
(IMF) defines the share to be 10 percent or more of the equity of the enterprise by the
owner. This includes eventual loans from the foreign owner to the local company (IFC and
FIAS, 1997).
6
In most papers FDI is only mentioned as a certain level of inward or outward flow to or from
a country. FDI can however be narrowed down to vertical and horizontal FDI. Vertical FDI
(VFDI) aims at efficiency seeking while horizontal FDI (HFDI) aims at market seeking. HFDI
emerges when MNEs seeks to cut costs that arises with exporting their goods. By
establishing the production closer to the customer, costs associated with transportation and
trade barriers are avoided. HFDI is believed to have a greater impact on spillover effects due
to its intense use of knowledge while VFDI is believed to affect the local labour demand to a
greater extent. To this date, there are mostly theoretical papers available about HFDI and
VFDI and hardly any empirical studies. This is the case due to difficulties associated with
distinguishing HFDI and VFDI in FDI data (Beugelsidjk et al, 2008). The FDI can also be divided
into greenfield and brownfield FDI. The difference between the two is that MNEs construct
new factories, invest in distribution or research in the host country with greenfield FDI
whereas brownfield FDI acquires factories that already exists in the host country. Therefore,
greenfield FDI stand for the largest inflow of physical capital between the two types
(Johnson, 2005).
Like IMF the Organization for Economic Cooperation and Development (OECD) proclaim that
10 percent ownership give the foreign owner an “effective voice” in the company. However,
if 10 percent is not enough to ensure an effective voice, it should not count as FDI according
to OECD. Conversely, if the owner’s share is less than 10 percent and the owner still has
management control in the company, it will count as FDI. Since there are different opinions
of how to calculate FDI, OECD has formulated four components that should be included
when calculating the flows. These are retained earnings, equity capital, intra-company loans
and intra-company borrowing (Jones and Wren, 2006).
These definitions make it possible to compare FDI flows between countries. There are
several difficulties when calculating FDI though. The reason for this is due to different
regulations and laws between countries when measuring components of FDI (Jones and
Wren, 2006).
7
The most important factor for FDI is MNEs. The formal definition of MNEs by OECD is
“companies or other entities established in more than one country, and so linked that they
may co-ordinate their operations in various ways”. Some argue that MNE activity is the same
as FDI. Those who are against this assumption point out that this is not a perfect measure of
MNE activity. A firm will only invest in a foreign country if the investment fulfills three
conditions. First of all, the firm must have an advantage over the domestic firms, an owner-
specific asset. Then an advantage must exist in the setting-up production instead of relying
on exports. The third condition is that the firm must internalize its assets (Jones and Wren,
2006).
FDI is a source for financing a domestic firm. It is not in itself the firm nor its assets. A
common misinterpretation is that many benefits generated by the domestic firm are
attributed to FDI. The firm can borrow money from domestic banks or apply new
technologies from their foreign owners, but this is not FDI. Should the foreign owner buy out
the equity position of the domestic owner however, this would be considered FDI (de
Macedo and Iglesias, 2001). Something that is not discussed much in the literature on FDI is
the exploitation of the domestic cultural environment. It is somewhat frowned upon by
authors of the subject but nonetheless an important factor for MNEs. Those MNEs that do
take advantage of these differences and exploit it to their gain get a competitive advantage
compared to those that refrain from it (Hosseini, 2005).
The impact of FDI on economic growth in a country depends on the degree of development.
The investment development path (IDP) suggests five stages that a country goes through and
which affect the level of investment. During the first stage a country is considered to be
almost unable to attract inward direct investment. This is the case due to low per capita
income, underdeveloped economic systems and governmental policies, poor infrastructure
and communication, and above all, a labour force with low human capital. The few direct
investments made are mainly in the labour-intensive manufacturing and primary sector like
agriculture. In the second stage, inward direct investment starts to rise. The investments are
still mostly located in natural resources and primary commodities. In this stage, the host
government is beginning to change policies in order to stimulate FDI. The domestic firms
begin to move their production towards semi-skilled and knowledge-intensive consumer
8
goods. The third stage is characterized by rising domestic income which causes an increase
in demand for high quality goods, partly enhanced by an increased level of competition
among firms. The rising incomes cause a decrease in growth of inward direct investment and
an increase in the growth of outward direct investment towards countries with lower levels
of IDP. The competition between domestic and foreign firms increases as well when the
domestic firms acquire competitive advantages. The enlarged market and increased
innovation will enable economies of scale and encourage technology-intensive
manufacturing. When the stock of outward direct investment exceeds the stock of inward
direct investment, the country has reached the fourth level. The domestic firms can only
compete with foreign firms in sectors where they have a competitive advantage. Instead
they invest abroad in markets where the labour is cheaper. In the domestic market the
capital-intensive production increases in turn. The fifth stage characterizes by a continuous
increase in outward and inward direct investment. This is the stage where advanced
industrial nations find themselves. The importance of MNEs is clear here. The domestic
supply of natural resources is of less importance and instead the ability to exploit markets in
other countries is significant (Dunning and Narula, 1996).
2.1.1 Positive effects from FDI
We have previously mentioned that MNEs stand for the largest share of FDI. In comparison
to a domestic firm it is presumed to have more skilled labour and better access to advanced
technology which in turn gives a greater output than the smaller firms. The obvious positive
effects from FDI are a decrease in unemployment and an increase in investment and output.
There are also other positive effects on the domestic economy from positive externalities,
known as spillovers. Jones and Wren (2006) present four transmission mechanisms that
identify a spillover: “the movement of labour between MNEs and indigenous plants;
purchase and supply linkages between MNEs and domestic firms; imitation of MNE-specific
technology by domestic firms; and competition effects that force domestic firms to become
more efficient”. The first type is productivity spillover which increases the productivity of
domestic firms. The second one is market-access spillover which makes it possible for
domestic firms to use export markets and distribution networks for their own gain. When a
MNE establishes in a foreign market it is possible for domestic firms to learn directly from
9
them through linkages. A forward linkage enables the domestic firm to use another firm’s
output for its input and the other way around for a backward linkage. The domestic firm can
also profit from movement of labour. The worker has often acquired knowledge and specific
competence from the MNE which benefits the domestic firm. Both of these mechanisms
make it possible for productivity and market-access spillovers. Besides these effects MNEs
also improve the degree of technology and competition in the domestic market. Domestic
firms often imitate MNEs use of technology to increase their productivity, something which
is known as “demonstration effect”. This is an indirect technological transfer. A direct
transfer of technology occurs when a MNE passes information to its local suppliers or when
it licenses the technology to a domestic firm. The increase in competition forces the
domestic firms to improve the efficiency of their production techniques. Those that do not
adapt are forced out of the market. FDI also improves the connection between firms and
institutions and improve the market diversity in many cases. There is nonetheless a danger
involved with large gaps in productivity between MNEs and domestic firms according to
Glass and Saggi (1998). A large gap in technological knowledge might indicate that there is a
large potential catch-up effect. If the gap is too large though, the case may instead be that
the domestic economy does not have the capacity to absorb the technology. To low levels of
human capital and infrastructure makes it impossible to learn and use higher levels of
technology. A fifth mechanism is proposed by Crespo and Fontoura (2006) and that is
exports. MNEs usually have a positive effect on distribution networks, infrastructure etc
which in turn increase the export capacity of domestic firms.
The effect of the positive spillover depends on how well the host country can absorb it, the
absorptive capacity hypothesis. If the country has a low level of technology and human
capital, it will not be able to acquire and use the knowledge that MNEs produce. This is
commonly accepted as a fact and explains why developed countries receive more positive
spillovers from FDI than developing countries. A large technological gap should then be
negative for absorbing the positive spillovers. However, in recent empirical studies, evidence
has been found that this may not be the case. Here, economies with a large gap in the
technological level between domestic firms and foreign firms are the ones that get the most
effect from positive spillovers. The most plausible explanation here is that the domestic
10
economy increase structural and policy changes in order to attract FDI and to be able to
absorb the positive spillovers that come along with it (Jordaan, 2005).
Furthermore, spillovers can be voluntary or involuntary. They are voluntary when a MNE
interacts with a domestic firm and a positive spillover is taking place. The domestic firm may
then increase its quality of labour etc which is beneficial for the MNE as well. With an
involuntary spillover on the other hand the domestic firm applies the technology that the
MNE is using, often by imitation or hiring experienced workers from the MNE. Thereby the
competition gap decreases to the advantage of the domestic firm (Johnson, 2005).
Obviously the size of the benefits from FDI on a country’s economy depends on several
factors. One of these is the export-rate of domestic firms. Firms that are more export-
oriented have adapted to foreign competition and are therefore better prepared to absorb
the positive spillovers generated by MNEs. The smaller the firm is, the harder it is to imitate
the production pattern of the MNE due to its large production scale. Another important
factor that has recently gained in importance is the regional effect. This implies that the
further away the source for the FDI is, the lesser effect it has on the domestic economy. The
reason for this is rising transport costs and limited labour turnover among other things. One
of the most discussed factors is the absorptive capacity of domestic firms previously
mentioned. The domestic firm must possess basic technological and knowledge skill in order
to absorb new skills generated from FDI. This idea can also be applied at the macroeconomic
level. MNEs tend to invest more in advanced technology in countries with a certain level of
knowledge and human capital. These are all factor that has been examined and discussed
thoroughly. The following factors are somewhat less discussed though. One is the notion
that FDI generates different spillover effects depending on the source country. Here culture,
language, laws, transfer distance and structures of FDI is of importance. The more alike the
countries are, the better the chance for a larger effect from the spillovers (Crespo and
Fontoura, 2006).
11
2.1.2 Negative effects of FDI
As mentioned before, FDI might have positive effects on the level of employment on the
domestic market. The level of employment does not have to rise though. If the MNE is
capital intensive and forces domestic firms out of the market due to competition, the rate of
unemployment might actually rise instead. When MNEs invests in a new region they tend to
set the wages above the domestic firms in order to attract the most competent workers of
the labour force. This in turn forces the domestic firms to raise their wages in order to keep
their workers. A high increase of the wages might have negative effects on the economy
though. Some fear that MNEs only invest in sectors with low-skill production and low-wage
jobs. These investments tend to focus on producing at a low cost and do not generate any
investment in research and development. The notion on whether or not this is the case goes
apart. Another implication of FDI on the level of employment is that MNE firms are
“footloose”. It means that if the production turns out to be less costly in another country, it
is easier for a MNE to move the production to that country than for a domestic firm to
relocate their production. This may cause instability to the regional economy in the country.
During a recession, it is particularly harmful for the region if the foreign firms shut down,
which are just what they might to do on these occasions. Empirical evidence indicates that
foreign firms exit the market one-and-a-half times more often than domestic firms.
Moreover, FDI may decrease the diversification of firms in a market. Agglomeration in a
region tends to increase the average risk for the economy and population in case of a
shutdown (Jones and Wren, 2006).
Other negative effects arise from a market stealing effect. It means that foreign firms enter
the domestic market and take over part of the market which causes domestic firms to exit
the market as a result (Jordaan, 2005). There are those who believe that domestic
investments are better for the local economy since domestic firms are supposed to have
better knowledge and access to domestic markets. The evidence from the positive spillovers
by MNEs and their FDI goes against this presumption though (Borensztein et al, 1998).
A problem with FDI in developing countries is that it is argued only to be a transfer of assets.
When foreign firms conduct mergers and acquisitions of domestic firms it does not
automatically lead to an increase in the capital stock. Since developing countries tend to be
12
capital-scarce, an increase in the capital stock is of great importance for future economic
growth. If capital accumulation takes place as a positive effect from FDI, it is required that
the FDI does not crowd out investment from domestic sources in order for economic growth
to increase (Herzer et al, 2008). A problem with the use of spillovers arises when the MNEs
export their products. The domestic firm is usually a producer for the domestic market,
which implies that the production process is not the same between the two. This in turn
makes it difficult for the domestic firm to imitate the MNE and its production process and
thereby gaining positive spillovers (Crespo and Fontoura, 2006).
2.2 Economic growth
Economic growth within a country can be derived from several growth models. The best
known growth model is the Solow-Swan model which was formulated in 1956. In this model,
production is generated through capital and labour under the assumption of constant
returns to scale. This is a neoclassical growth model and it explains growth partially by
exogenous improvements in technology (Gylfason, 1999). The effect from FDI on growth in
this model in the medium and long run depends on increases in the volume of investment or
its efficiency level (Nair-Reichert and Weinhold, 2001). Domestic investment (DI) plays an
important role in neo-classical growth models where it enhances production growth and
technological progress. FDI is also an investment but differs from DI. First of all FDI increases
the technological inventions and especially general purpose technologies. These innovations
are breakthroughs which all countries can adopt, but at different pace. The second
difference is that FDI include more advanced technological aspects. These advantages
transfer to domestic firms in due time, increasing the level of output (Yao and Wei, 2007). A
model that explains growth endogenously was developed during the 1980s and 1990s. It was
the endogenous growth model or as it is also known as, the new growth model (Gylfason,
1999). When considering the different models and the effect from FDI, the result differs. FDI
increases the volume of investment in an economy and may increase its efficiency in a
neoclassical growth model. In the endogenous growth model FDI can increase the economic
growth mainly through technology transfer and the previously mentioned spillover effects
(Nair-Reichert and Weinhold, 2001). Since the technological progress in the neoclassical
growth model is determined exogenously, the model fails to explain growth or the
13
technological change itself satisfactory. Therefore we shall focus on the endogenous growth
model.
In neoclassical growth models, FDI only has a short-run growth effect. In endogenous growth
models on the other hand, FDI is believed to have a greater impact on economic growth than
domestic investments. The production function in the receiving country incorporates the
technological advances from FDI and thereby increases growth. These technological
spillovers make it possible for a long-turn growth to take place by counteracting the effects
of diminishing returns to capital. Beside capital accumulation, knowledge spillovers from FDI
can also enhance the economic growth. This takes place when alternative management
practices and organizational changes occur alongside an increase in knowledge stock
through skill attainment and labour training. The accumulation of capital through FDI
generates positive spillover which enhances economic growth. Due to this, we can not only
study flow variables in order to understand the connection between FDI and economic
growth (Herzer et al, 2008).
One of the first endogenous growth models was constructed by Marvin Frankel (Carlin and
Soskice, 2006). By starting with a Cobb-Douglas production function his aim was to retain
desirable properties of the neoclassical production functions, but not the limitations:
�� � ��������� (2.1)
where �� is output for each firm, ���is the aggregate capital, A is the outcome of aggregate
capital accumulation in the economy and �� is labour. The difference from the Solow-Swan
model is that A is not an exogenous productivity factor. Labour enables knowledge in the
production function which increases labour productivity, also known as “learning by doing”.
This phenomenon occurs due to the accumulation of capital. It is assumed that each firm’s
knowledge is a public good which gives an expression for knowledge in the whole market:
� � ��� (2.2)
14
where � is a positive constant. The production function for all the firms on the market when
taking A as given is:
� � ������� � ������ ��� � ����� �������� (2.3)
Since A is constant for the firm, there are diminishing returns to capital and constant returns
to scale. There are increasing returns to scale for the economy (��1 � � � � � 1 � � � 1).
If the knowledge spillover from capital accumulation, �, is 1, then returns to aggregate
capital accumulation are constant:
� � �������� (2.4)
What is interesting with this production function is that the economy grows at a rate
independent of the savings/investment rate if � < 1, but unlike the Solow-Swan model, its
output per capita does grow. This is obvious if we take the production function � ���
��� �������� and then apply logs and differentiate with respect to time:
�� � ����1 � � � ���� � �1 � �� (2.5)
Along a balanced growth path �� � ��. This in turn gives us:
�� � �� � ����� � ��� � ����
����� � ��� (2.6)
Since the growth rate of output per capita is in steady state, then �� � � � ��� � � which
gives us:
�� � � � (2.7)
Since technological progress is endogenous it is the only cause for growth of per capita
output. Beside technological progress and its impact on economic growth, we encountered
15
other spillover effects from FDI. One of these is the accumulation of human capital. The
growth rate for human capital in an economy is:
�� � ��� � �1 � ! (2.8)
where �� is the growth of human capital, "� is the change of human capital, " is the amount
of human capital per person, is a scaling parameter and �1 � ! the fraction of labour
hours spent in education in order to learn new skills that can be used in production
�0 % ! % 1). Human capital is also present in the equation for the growth rate for capital
per worker:
�& � Λ (&�)
��� �* � � (2.9)
If steady state exists when capital per worker grows at a constant rate, then the ratio + / "
has to be constant. The assumption of constant returns to human capital accumulation
needs to be held in order for the endogenous growth to emerge. The spillovers from human
capital accumulation are important for the productivity and are sometimes referred to as
“social capital”. This is not only the notion of sharing information and innovations but also of
reciprocity and behaviour (Carlin and Soskice, 2006). Some of the models consider domestic
investments to be of little importance for economic growth. Direct investments from other
countries are somewhat different though. Due to the spillovers from FDI, they may have a
positive effect on economic growth (Gylfason, 1999).
It is commonly believed that developing countries can have a high growth rate due to the
catch-up effect. Since their technological level is much lower than developed countries they
can implement already available technology and thereby increasing the growth rate. In order
for the country to absorb the new technology, a certain level of human capital is necessary.
Since MNEs are the largest contributor of new technology, their presence in a country may
be important for the economic growth. A large amount of FDI may cause positive spillovers
which in turn enables for the country to raise the growth rate (Borensztein et al, 1998).
16
2.3 Mexico
Mexico has received FDI for several decades. Up until the mid-1940s the country could
hardly attract any FDI and was therefore considered a stage-one-country in the IDP. From
the 1950s to the 1970s the direct investment increased continuously. The metal-mechanical
and the chemical industries were where most of the investments ended up. The basic
infrastructure and the human capital were upgraded and the domestic market increased in
size. This made it attractive for MNEs to invest in the country. Although Mexico has large
domestic firms and increasing outward direct investment, the country has not reached the
third stage. The debt crisis in the 1980s and the financial crisis in 1994 have left them in the
second stage, well advanced though. Today, Mexico relies more on FDI than on the domestic
producers in order to modernize the industry. 1994 was not only a year of crises. Mexico
also became a member of the OECD and was approved for the North American Free Trade
Agreement (NAFTA). Mexican exports grow constantly and it is especially positive that the
exports are rather diversified. Mexico’s forward development has resulted in one of the
most open economies in the world. The average tariff in modern time is only about 10
percent (Dunning and Narula, 1996). The reason why the FDI increased so much after the
financial crisis in 1994 is that Mexico implemented macroeconomic stabilization measures as
well as several reform programs. All these measures together with an attractive investment
policy increase the FDI into the country. According to Ramirez (2000) FDI inflows account for
more than 15 percent of the gross fixed capital formation.
17
Fig. 1. FDI inflows in Mexico in million US dollars, 1993-2007.
Source: UNCTAD, See Appendix 2
Fig. 2. GDP per capita in Mexico in US dollars, 1993-2007.
Source: UNCTAD, See Appendix 2
Since Mexico has received FDI for a very long time, the country has learned to handle these
flows in a good way. The government has changed its policies during these years in order to
be able to direct the FDI. The government is now able to direct these investments to priority
sectors that exhibit high production capacity, improve the infrastructure and use new
technologies (Ramirez, 2000). However, the inflows of FDI are not evenly spread across the
0
5000
10000
15000
20000
25000
30000
35000
US
DFDI
0
2000
4000
6000
8000
10000
12000
14000
US
D
GDP per capita
18
Mexican states. Instead most of the investments are placed in states bordering the United
States. The United States is the biggest contributor of FDI to Mexico with over 60 percent of
the total foreign investment in the world. The vast majority of FDI to Mexico originates from
developed countries, with over 95 percent from the OECD.1 The developing countries are
hardly considered due to the low investments from them. The main part of the FDI in Mexico
goes into the manufacturing and services sectors.2 When turning to agriculture and mining,
these sectors receive negligible shares of the investment from other countries (Jensen and
Rosas, 2007).
Mexico is the country in Latin America that receives most of the private foreign capital
inflow, almost 50 percent. The main reason why the country receives such a large share is
first of all because that they are located next to the United States. Mexico is also rather open
and is improving the possibilities for foreign investment (Dunning and Narula, 1996). There is
empirical evidence that for Mexico and other developing countries the rates of return to
capital are high. It is also the case that the level of FDI is not higher in developing countries
than in industrialized countries. So even though FDI has increased dramatically in Mexico
during the last two decades, the level of FDI is still higher in more developed countries
(Banerjee and Duflo, 2005).
The next section presents my own results as well as previous studies and their results.
3. Data and statistical analysis
Several studies have been made on FDI and its impact on economic growth. Some of these
studies concern Mexico alone but most include several countries. One difference between
these studies and my own is that mine includes data up to year 2007, which makes it more
up-to-date than the previous studies. Many of the previous studies do not find that FDI have
any significant effect on economic growth.
1 Appendix, table A1.a-A1.b
2 Appendix, table A2.a-A2.b
19
3.1 Results
The measurement of inward FDI flows in Mexico gives slightly different results from different
sources. Therefore we use two sources for the data on FDI. This data has been calculated by
the OECD and the UNCTAD. The data differs somewhat which indicate on different methods
of measurement. When comparing the data to the domestic measurement (Secretaría de
Economía, Mexico) the data from UNCTAD differ the least. 3
Nevertheless we shall perform
two regression analyses, one with data on FDI from OECD and one with data on FDI from
UNCTAD. This way we will find possible differences between the two data sets. The first
variable, the dependent variable, is Ln(GDP) per capita. As independent variables we use
Ln(FDI) and the lagged variables Ln(GDP) per capita the previous year and Ln(FDI) the
previous year.4 In order to achieve this we shall use a dynamic adjustment model by Verbeek
(2004):
��,-./ � 0 � 1��,-./� � ��2-3/ � 4��2-3/� � 5/ (3.1)
where t-1 is the previous year. The reason why we compare with the previous year is
because FDI might affect GDP per capita, not only the present year, but also in the longer
run. No dummy variables are used in the model in order to observe the difference from
before and after NAFTA. The reason for this is that the data is mainly from after Mexico
joined NAFTA in 1994. Suppose that 1 � 1 and 4 � � , then we have:
��,-./ � ��,-./� � 0 � ���2-3/ � ��2-3/� (3.2)
which is a difference-in-difference model. In this case, � ∆% in GDP by a % increase in FDI.
The long-run expression of (3.1) is:
��,-. � 8�9 � :�;
�9 ��2-3 (3.3)
By using the model (3.1), we obtain the results as shown in Tables 2 and 3.
3 Appendix, table A3
4 Appendix, table A4
20
Table 2. Regression Analysis: LnGDP t versus LnGDP t-1; LnFDI t UNCTAD; LnFDI t-1 UNCTAD
Predictor Coefficient SE T-value P-value
Constant -0,319 1,102 -0,29 0,778
LnGDPt-1 0,9585 0,1848 5,19 0,000
LnFDIt 0,07899 0,08947 0,88 0,398
LnFDIt-1 -0,0028 0,06226 -0,04 0,965
S = 0,06903 R-Sq = 91,2% R-Sq(adj) = 88,6%
Notes: Own calculations, FDI data from UNCTAD.
Table 3. Regression Analysis: LnGDP t versus LnGDP t-1; LnFDI t OECD LnFDI t-1 OECD
Predictor Coefficient SE T-value P-value
Constant -0,433 1,029 -0,42 0,682
LnGDPt-1 0,9384 0,1965 4,78 0,001
LnFDIt 0,10539 0,09267 1,14 0,282
LnFDIt-1 0,00137 0,05825 0,02 0,982
S = 0,06761 R-Sq = 91,6% R-Sq(adj) = 89,1%
Notes: Own calculations, FDI data from OECD.
95 percent confidence intervals are used in the tests. The P-value of Ln(FDIt) in the first test
is 0,398 and 0,282 in the second test. The corresponding P-value for Ln(FDIt-1) is 0,965 and
0,982. Evidently the result is not significant at any conventional level (95 % - 99 %) and we
cannot reject coefficient c or coefficient d in neither test. According to the tests, there is a
difference between the two sources. However, both values are very high and therefore we
conclude that FDI does not have any significant effect on economic growth in Mexico here.
We have also tested other model variants, for example, without the lagged FDI term, and
find that the insignificant result remains. Fig.3 and 4 show the correlation between Ln(GDP)
per capita and Ln(FDI). Both figures, with data from UNCTAD and OECD, display a positive
correlation.
21
9,0 9,5 10,0
8,8
8,9
9,0
9,1
9,2
9,3
9,4
9,5
LnFDI UNCTAD
LnG
DP
per
cap
ita
LnGDP per ca = 4,79347 + 0,446510 LnFDI UNCTAD
S = 0,128712 R-Sq = 63,4 % R-Sq(adj) = 60,4 %
Regression Plot
Fig. 3. Regression Plot with data from UNCTAD
Source: UNCTAD, See Appendix 4
9,2 9,3 9,4 9,5 9,6 9,7 9,8 9,9 10,0 10,1 10,2
8,8
8,9
9,0
9,1
9,2
9,3
9,4
9,5
LnFDI OECD
LnG
DP
per
cap
ita
LnGDP per ca = 4,11746 + 0,515873 LnFDI OECD
S = 0,131736 R-Sq = 61,7 % R-Sq(adj) = 58,5 %
Regression Plot
Fig. 4. Regression Plot with data from OECD
Source: UNCTAD and OECD, See Appendix 4
22
When looking at these regression plots, we could draw the conclusion that GDP per capita
and FDI are correlated. Even though a positive correlation might exist, this does not mean
that there is causality in the test. The earlier opinion was that an increase in FDI leads to an
increase in economic growth. This is not the general belief today and there are those that
claim that instead it is an increase in economic growth that causes an increase in FDI flows.
There are a lot of arguments on which is true and the opinion differ. One explanation is
spurious regression. This is when the t-value suggests a significant relationship between two
variables when there in fact is no significant relationship to be found (Verbeek, 2004). More
about the causality between economic growth and FDI is presented in section 3.2,
comparison with previous studies.
3.2 Comparison with previous studies
The results on whether or not FDI is positive for economic growth differ between different
studies. One conclusion can be made when comparing these studies and that is that it
depends on if it is a microeconomic study or a macroeconomic study. The microeconomic
studies at the firm-level often end up with the result that FDI does not increase economic
growth and does not produce positive spillover effects. No technological transfer from MNEs
to domestic firms is taking place according to this. When we look at the studies with
aggregate FDI flows for a broad cross section of countries that is at the macroeconomic level
the result is another. Here, FDI should have a positive effect on economic growth. Even
though the macroeconomic studies show a positive effect from FDI, we must look at these
studies a bit skeptically. One reason is that they do not control for different country-specific
effects. Another is the use of lagged dependent variables such as regressors. This can cause
inaccurate coefficient standard errors (Carkovic and Levine, 2002). In Carkovic and Levine’s
(2002) study they use a macroeconomic method that excludes many of the earlier
macroeconomic problems. Here they find that FDI is not independent in changing the
economic growth. Even though FDI may cause an increase in economic growth, other growth
determinants and a developed financial market are necessary for the effect to be effective.
23
Waldkirch (2008) has studied the effects from FDI on the economic growth in Mexico after
NAFTA was implemented in 1993. The result show that the level of FDI has increased
substantially since Mexico joined NAFTA. However, the investments are often placed in
sectors with unskilled workers. One of the reasons with the paper was to see if FDI from
more distant countries had a larger effect on various economic indicators in Mexico. The
conclusion is that there is not enough evidence for this presumption.
Ramirez (2000) has also studied data on the impact of FDI flows on economic growth
specifically for Mexico. Generally the FDI in the country can be said to give large positive
spillover effects and yield strong international trade links. Moreover, the econometric
evidence indicates that the variables in the production function in the study do not fluctuate
much in relation to each other in the long run. When using Error Correction Models (ECMs)
the author find a positive and statistically significant effect on the labour productivity from
the growth rate of private and foreign capital stock. One important aspect with FDI is the
question if the gain is larger than the negative side-effects. Even though positive spillovers
will occur, there are also costs for Mexico such as subsidies and tax concessions.
Another study of FDI and the effect of its spillover in Mexico have been made by Jordaan
(2005). He concludes that FDI do result in positive externalities which are positive for the
economic growth. Furthermore, the FDI tend to focus on labour-intensive and low
productivity industries in the manufacturing sector. He also finds proof, contradictory to the
theory, that the economy is positively affected by agglomeration. These geographical
concentrations of domestic and foreign firms increase positive externalities through
imitation, labour turnover and inter-firm linkages. Industries that are less agglomerated thus
receive less positive externalities. In highly agglomerated sectors Jordaan (2005) discovers,
unlike previous studies, that firms with a large technological gap compared to foreign firms,
are the ones that gain the most on positive externalities. He is of the opinion that the
absorptive possibilities of a firm might not be as large an issue as believed earlier. The
empirical evidence clearly indicates this. Tuan and Fung-Yee (2007) also find positive effects
from FDI and agglomeration, but in China. The FDI is mainly focused in the southern and
eastern regions and is believed to contribute to the sustained growth in the regions.
24
A larger and more recent study has been made by Alfaro et al (2004). They use more
explanatory variables than the previous study, such as population growth, inflation rate,
government consumption etc. They find that FDI affect the economic growth positively. For
the positive effects to take place though the local financial market has to be developed in
the receiving country. A poorly developed financial market cannot make use of neither
short-term capital flows nor long-term stable flows. With this, they claim to have proven
that the link is causal between FDI and economic growth. Furthermore they found that most
countries, including industrialized ones, have special policies with fiscal and financial
incentives in order to attract FDI. In a later study by the same authors (Alfaro et al, 2006)
they use both microeconomic and macroeconomic empirical literature in order to acquire
satisfying results. They find that the growth rates appear to be almost twice from FDI in a
country with developed financial markets compared to countries with poorly developed
markets. They also find larger growth effects when the domestic firms and MNEs produce
substitutes. Balasubramanyam et al (1996) find a statistically significant result at the 1
percent level in their study of 46 countries, which are classified as developing. Since the
study focus on trade, their result indicates that FDI accelerate economic growth faster in an
economy that promotes export.
Borensztein et al (1998) use a large number of explanatory variables in a cross-country
regression framework like the study by Alfaro et al (2004). Their study includes data from 69
developing countries that receive FDI. Although their result is not statistically significant,
they believe that FDI do have positive effects on the economic growth of a receiving country.
This positive effect mainly takes place through improvements of the technological
knowledge. Like many other studies they use human capital as an explanatory variable. Just
like the rate of technological progress, the rate of human capital is crucial for a country’s
economic growth. A country with a low level of human capital cannot utilize the FDI that
flow into its economy. The authors conclude that a minimum threshold of human capital
stock is required and that a higher level of human capital enables a country to put the FDI to
better use, and thereby facilitates for economic growth.
As we observed in the theory, FDI can be divided into horizontal FDI (HFDI) and vertical FDI
(VFDI). Previous studies have not made this important distinction though according to
25
Beugelsidjk et al (2008). They test respectively effects from HFDI and VFDI on economic
growth by using gross fixed investment stock, level of schooling, black market premium and
population growth as explanatory variables. When the sample includes both developed and
developing countries, the results indicate that neither HFDI nor VFDI affect the economic
growth. When using the traditional FDI variable though, the result is significant. Still, this
result changes when separating the countries into a sample of developed countries and
another sample of developing countries. The sample with developed countries now shows a
positive and significant result for both HDFI and VFDI. The sample with developing countries
on the other hand does not show a significant impact on economic growth from neither
HDFI nor VFDI. There is still a positive effect from traditional FDI on economic growth here as
well as before. The result from the empirical research in the study shows that HFDI has a 50
percent larger impact on growth in developed countries than VFDI. Even though HFDI and
VFDI are important for different types of development, it is clear that HFDI is more
important for economic growth.
Herzer et al (2008) study 28 developing countries and do not find any evidence that FDI has a
positive effect on GDP for most of the countries. Noticeably they cannot find a single country
with a positive long-term effect from FDI on GDP. One argument from earlier studies is that
a positive effect on the economy in the domestic country comes from an increase in the
demand for raw materials. Foreign firms that establish factories will need raw material in
order to produce their products. Yet in this study the authors find evidence that this might
not be the case. MNEs that use a lot of raw material in their production do not purchase
these from the local suppliers. Instead they tend to acquire them within the enterprise and
thereby from foreign suppliers. The political situation and governmental actions also have a
great impact and might explain the deviations in some countries according to Fung-Yee and
Tuan (2006) in their single country study of China. Moreover they conclude that FDI in areas
with high agglomeration of specific sectors does not increase GDP as much as in more
diversified areas. Instead local firms, especially in the manufacturing sector, seem to affect
GDP directly to a greater extent than foreign firms.
One important probable effect from FDI on economic growth is the knowledge spillover as
mentioned before. Görg and Greenaway (2004) however find evidence that this might be a
26
false assumption. From a 25 firm-level studies from both developed and developing
countries, only 6 show positive effects from spillovers to the domestic firms. Some of these
actually show negative effects on the domestic firms as a result from FDI spillovers. One
explanation for this is that foreign firms have lower marginal costs from firm-specific
advantages. This competition forces domestic firms out of the market since they cannot
compete. Crespo and Fontoura (2006) present empirical evidence of the extent that the
domestic firms are able to absorb them and find that the effect from positive spillovers
appear to be greater in developed regions.
An important aspect we have to consider is the causality between FDI and GDP. Hardly any
older studies test for the causality. One causality test that has been made is by Herzer et al
(2008). They test for weak exogeneity and thus for long-run Granger non-causality which
was presented earlier. In order to get accurate results they do this “(i) by using several
alternative methods for estimating the cointegrating parameters; (ii) by using other methods
to test for causality; and (iii) by including several control variables, such as labour, domestic
investment, and export” (Herzer et al, 2008). The result indicates that only four countries
show a long-run positive impact of FDI on GDP. However, the long-run causality is bi-
directional which signify that FDI causes growth as well as it is a cause of it. Furthermore in
the long run only one country is found to have unidirectional influence from FDI on GDP. This
unidirectional influence is negative though. The authors also study the short run and here
they find that in five of the countries FDI affect GDP positively while it affects GDP negatively
in four countries. Hence they come to the conclusion that FDI cannot be proven to have a
positive impact on GDP in developing countries since they are not able to find any statistical
significant long-turn impact. Liu et al (2002) also find proof of bi-directional causality in the
long run from FDI on GDP in China. Beside FDI and economic growth they also include
exports and imports in their study. Yet another study on causality between economic growth
and FDI has been made by Chakraborty and Nunnenkamp (2007). They put data from India
to Granger causality tests but conclude that there is no causal relationship between the two.
An interesting observation made however is that cross-section spillovers take place from the
service sector to the manufacturing sector. FDI in the service sector thus causes growth in
the manufacturing sector.
27
One reason why these studies differ so much in the result could be that some assume
heterogeneity across countries in the panel studies while others assume homogeneity
according to Nair-Reichert and Weinhold (2001). Their study of 25 developing countries
differs substantially from traditional panel data causality results. They allow the strength of
causality to vary from country to country and permit for heterogeneity. They find that the
relationship between FDI and economic growth is highly heterogeneous and that the effect
from FDI on economic growth is more efficient in open economies. In Johnson’s (2005) study
of 90 developed and developing countries the direction of causality is from FDI to the
economic growth. From cross-section and panel data analyses the study show that FDI do
have a positive effect on the economic growth in the receiving country. What really differ
between this and the majority of previous studies is that FDI seem to improve the economic
growth in developing but not in developed countries. The result should be viewed critically
though due to the small sample of developed countries.
In the fourth section we will discuss my result and the results from previous studies.
4. Discussion
The results presented in this paper indicate on different results from different studies. How
should we be able to acquire the correct answer of the possible connection between FDI and
economic growth? In order to come to a conclusion there are several factors to be
considered.
We have to remember to critically analyze the methods these results are based on. All
different studies suffer from some sort of problems which makes it possible to question the
result. A common method is cross-country studies which often show that FDI has a positive
impact on the economic growth. The greatest problem here is the assumption of identical
production functions from the different countries included in the study. This may give a false
result since the policies and production technologies differ to a large extent between the
countries. For a correct study to take place, we would have to take all these differences into
account. Furthermore, if the coefficient of FDI in the growth equation is statistically
28
significant, this does not automatically indicate a connection between FDI and economic
growth. In fact, “cross-country studies may suffer from serious endogeneity biases” and
“unobserved heterogeneity due to omitted variables may lead to biased parameter
estimates” (Herzer et al, 2008). Since FDI is supposedly more effective when the economic
growth is high, a positive correlation can be compatible with causality running from growth
to FDI. Theoretically, the FDI should have a positive effect on economic growth according to
the endogenous growth model, at least greater than domestic investment (Herzer et al,
2008).
Another common method is panel studies which eliminates the previous problem by using
unobserved country-specific effects. This method makes it possible to control for
endogeneity bias due to the use of lagged explanatory variables (Herzer et al, 2008). By using
time-series and cross-section panel data estimation the researcher can control for “country-
specific, time-invariant fixed effects and include dynamic, lagged dependent variables” (Nair-
Reichert and Weinhold, 2001). Of course, this method also suffers from various problems.
One problem is when the coefficients of the lagged dependent variables are homogeneity
imposed, even though the dynamics are heterogeneous (Herzer et al, 2008). This can lead to
biases which later on cannot be corrected with instrumental variable estimation (Nair-
Reichert and Weinhold, 2001). Another problem is that the relationship between FDI and
GDP is restricted to growth rates or first differences which also can bias the result. A level
relationship would be required in order to get correct results (Herzer et al, 2008).
Finally, many of the available studies should be critically examined since only system-based
cointegration procedure is used to test for cointegration between FDI and economic growth.
This may lead to a rejection of the result where the cointegration and the causality between
FDI and GDP are presented (Herzer et al, 2008).
As concluded before, the result depends on if it is a microeconomic or macroeconomic
study. Furthermore, most studies also fail to consider country-specific effects from FDI.
However econometrically FDI should have a positive effect on economic growth. This cannot
be statistically proven according to my study and several of the previous studies. Still, FDI do
produce several positive spillovers. One of the most important is technological spillovers
29
which domestic firms can adapt. More studies are required on this subject though since
there are different opinions whether a large technological gap between MNEs and domestic
firms is positive or negative. Of course, the technological spillover effect is positive on the
economic growth both with a small and a large technological gap. If FDI is to affect the
economic growth positively, the effects from the positive spillovers must be larger than the
negative spillovers. The governments yearning for FDI might actually harm the economic
growth through large subsidies and tax concessions.
We must also deal with the causality issue. Only one of these studies (Johnson, 2005) shows
a positive causality, that FDI do effect economic growth and not the other way around. The
other studies that do test for causality in the long run only find proof for this for some of the
countries in the samples. The main part of the countries show no or bi-directional causality
between FDI and economic growth. An interesting thought is that FDI has no effect on
economic growth and that this is only a belief among the countries that try to attract it.
Instead, in their efforts to attract FDI, they enable for economic growth themselves through
reforms and policies.
Despite the fact that most studies cannot find any statistic evidence that FDI do effect
economic growth positively in the long run the authors are overall still positive towards FDI.
They believe that FDI have a positive effect on GDP per capita but that it is only one factor
among many others. The spillover effect is an abstract concept and not directly measurable.
The empirical literature use econometric analysis to see the effect from spillover effects on
economic growth. It is therefore not easy to get accurate answers on this subject (Crespo
and Fontoura, 2007).
An interesting point to consider is if it is at all realistic to consider FDI to affect the economic
growth in a country. If we look at Mexico, the amount of FDI has risen greatly since the
1980s. Still, this is only a marginal of the GDP. Can we thus expect FDI to have any sort of
impact on the economic growth in Mexico? Since FDI only is a fraction of a countries total
investment, it is hard to find the evidence of to which extent FDI affect economic growth.
Interestingly FDI may in fact be harmful for the regional economy but positive for the
national economy (Jones and Wren, 2006).
30
The effect from FDI on economic growth in Mexico cannot apparently, like for the other
countries, be statistically proven. The studies do however show an increase in labour
productivity and other positive spillovers. The inflow of FDI is relatively high in the country
and a rising level of human capital and level of knowledge encourages the flow to continue
and increase. Since FDI inflows have existed for a long time in Mexico the government has
learned to handle it effectively through policies and institutions. Their financial market has
also been developed, something that is fundamental in order for FDI to affect GDP per capita
effectively. Furthermore it is a known fact that FDI inflows in Mexico tend to increase the
agglomeration of firms. Whether this is positive or negative for the economic growth is
disputed though.
Finally, we must consider the fact that even though we cannot find any statistical
significance in our study, it is only the result for the data in our study. Although the null
hypothesis is rejected, this might not reflect the reality. Our regression analysis did not find
any statistical significance when we used the variables in (3.1) and neither when we
performed the test without the lagged variables. It is important to remember that other
important variables can be used and possibly give another result. An interesting variable
here is domestic investment. Further research should be made concerning domestic
investment and the possible connection to FDI.
The final section summarizes the paper and presents my conclusion on whether or not FDI
affect economic growth in Mexico.
5. Conclusion
Whether or not FDI has any effect on economic growth is widely argued in both previous and
present studies. Some come to the conclusion that FDI does have a positive effect on GDP
growth per capita. Others cannot find any evidence that this is the case. These different
results depend on whether the authors have used microeconomic methods or
macroeconomic methods but also on different data and different explanatory variables.
31
Herzer et al (2008) take causality into account and test for long-run Granger non-causality.
Their result indicates that there are hardly any countries that show a long-run positive effect
from FDI on GDP per capita. Those countries where FDI does have a positive effect on GDP
growth per capita show a bi-directional causality, which means that FDI might as well cause
economic growth as well as it is a cause of it. Other studies on causality from Liu et al (2002)
and Chakraborty and Nunnenkamp (2007) only find proof of either bi-directional causality or
no causal relationship at all.
In this paper, we use a dynamic adjustment model to study the dependence of Ln(GDP) per
capita on Ln(FDI). Furthermore we use more recent data than previous studies, from 1993 to
2007 and from two different sources in order to see if the result differs. The multiple
regression analysis indicates that the coefficient for Ln(FDI) and its lagged variable are not
statistically significant at the 5 percent level in neither of the tests. We also perform an
analysis without the lagged FDI term, but find that the insignificant result remains.
Even if my results and several other studies show that FDI does not have a positive effect on
economic growth, most authors argue that FDI may have a positive effect on GDP per capita
at least in certain sectors. We cannot only study flow variables in order to understand the
connection between FDI and economic growth. Positive spillover effects from FDI are
important but the importance of country specific absorptive opportunities are disagreed
upon. Available studies fail to observe important factors that might affect the economic
growth, such as political and cultural differences. Future studies should focus more on
specific countries in order to get more reliable results.
32
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35
Appendix
Table A1.a. FDI flows in the host economy, by geographical origin, USD in millions, 1994-1998
Region/economy 1994 1995 1996 1997 1998
Total world 15 045,2 9 646,4 9 943,1 14 159,7 12 169,6
Developed countries 8 321,6 7 844,7 7 057,7 11 220,1 7 638,7
Western Europé 1 988,4 2 038,1 1 219,4 3 197,5 2 047,3
European Union 1 934,5 1 837,9 1 137,9 3 168,3 1 998,8
Austria 2,3 0,2 0,4 0,6 5,9
Belgium -7,1 54,2 1,5 46,2 30,7
Denmark 14,5 19,0 17,6 18,9 68,1
Finland 4,6 - - 0,1 1,0 1,7
France 90,5 125,9 124,0 59,8 127,8
Germany 307,5 548,6 201,4 481,1 136,9
Ireland 4,4 0,5 19,6 15,0 -3,9
Italy 2,7 10,5 18,3 29,1 17,2
Luxembourg 10,4 7,2 14,9 - 6,5 7,8
Netherlands 757,6 742,8 487,4 358,6 1 052,8
Portugal 0,1 - 0,1 0,6 3,4
Spain 144,3 49,6 73,5 326,9 307,8
Sweden 9,3 61,1 96,6 7,2 59,7
United Kingdom 593,4 218,7 82,7 1 829,8 182,9
Other Western Europé 53,9 200,2 81,5 29,2 48,5
Switzerland 53,9 200,2 81,5 29,2 48,5
North America 5 702,2 5 650,8 5 696,1 7 669,6 5 491,4
Canada 740,7 170,1 515,5 237,6 202,8
United States 4 961,5 5 480,7 5 180,6 7 432,0 5 288,6
Other developed countries 631,0 155,8 142,2 353,0 100,0
Japan 631,0 155,8 142,2 353,0 100,0
Developing economies 2 266,4 438,1 573,7 837,5 400,9
Latin America and the Caribbean 1 028,6 257,3 161,0 572,9 272,8
South America 8,6 23,7 4,1 52,5 25,0
Chile 2,6 8,2 3,4 42,9 7,1
Uruguay 6,0 15,5 0,7 9,6 17,9
Other Latin America and
Caribbean 1 020,0 233,6 156,9 520,4 247,8
Bahamas 89,7 53,5 9,2 6,0 33,4
Bermuda 2,0 1,8 5,9 93,3 41,6
Cayman Islands 93,0 28,6 48,8 330,3 108,8
Netherlands Antilles 468,5 70,3 62,8 9,1 5,7
Panama 338,2 59,6 18,1 16,5 18,2
Virgin Islands 28,6 19,8 12,1 65,2 40,1
Asia 1 237,8 180,8 412,7 264,6 128,1
South, East and South-East Asia 1 237,8 180,8 412,7 264,6 128,1
China 1,5 5,4 10,0 4,9 10,8
India 1 218,7 50,5 285,7 28,7 -
36
Philippines - 6,1 - 4,0 -6,5
Republic of Korea 15,1 103,8 85,8 199,2 51,4
Singapore - 12,3 28,6 20,0 40,9
Taiwan Province of China 2,5 2,7 2,6 7,8 31,5
Unspecified 51,8 42,0 - 68,2 87,3
Note: Data refer to materialized FDI notified to the National Foreign Investment Register (RNIE).
They do not include profit reinvestment and transfer among companies.
Source: UNCTAD (http://www.unctad.org/Templates/Page.asp?intItemID=3198&lang=1, 081110)
Table A1.b. FDI flows in the host economy, by geographical origin, USD in millions, 1999-2002
Region/economy 1999 2000 2001 2002
Total world 12 856,0 15 484,4 25 334,4 9 696,4
Developed countries 12 458,3 14 895,0 24 763,0 9 184,9
Western Europé 3 732,2 2 544,3 3 917,4 1 986,0
European Union 3 612,4 2 413,9 3 813,3 1 725,5
Austria 1,8 1,1 2,2 -0,5
Belgium 33,6 17,0 68,4 39,7
Denmark 173,9 146,1 179,3 139,3
Finland 28,2 216,2 83,4 25,7
France 167,0 -2 565,9 354,8 150,0
Germany 742,6 342,8 -195,5 476,0
Ireland 1,1 4,9 2,7 116,3
Italy 35,8 31,6 15,2 9,5
Luxembourg 13,6 34,7 120,5 14,6
Netherlands 918,0 2 392,9 2 644,7 485,9
Portugal 4,2 -0,2 0,2 0,7
Spain 995,4 1 890,3 585,3 239,8
Sweden 690,5 -334,9 -139,0 -40,9
United Kingdom -193,5 237,3 91,1 69,3
Other Western Europé 119,8 130,4 104,1 260,5
Switzerland 119,8 130,4 104,1 260,5
North America 7 488,9 11 927,9 20 677,7 7 103,1
Canada 584,3 564,0 865,6 31,7
United States 6 904,6 11 363,9 19 812,1 7 071,4
Other developed countries 1 237,2 422,8 167,9 95,8
Japan 1 237,2 422,8 167,9 95,8
Developing economies 327,7 463,0 479,8 214,8
Latin America and the Caribbean 196,4 323,7 370,8 163,9
South America 17,0 39,3 24,6 19,3
Chile 6,4 4,3 3,8 27,4
Uruguay 10,6 35,0 20,8 -8,1
Other Latin America and Caribbean 179,4 284,4 346,2 144,6
Bahamas 18,7 5,7 121,3 3,5
Bermuda 17,1 46,1 30,8 2,4
Cayman Islands 85,3 84,1 99,8 111,2
37
Netherlands Antilles 16,1 67,5 36,8 13,2
Panama -24,3 3,5 28,0 7,1
Virgin Islands 66,5 77,5 29,5 7,2
Asia 131,3 139,3 109,0 50,9
South, East and South-East Asia 131,3 139,3 109,0 50,9
China 3,2 2,9 1,4 2,1
India 0,1 27,4 3,1 -
Philippines 3,2 0,1 0,1 -
Republic of Korea 46,0 21,5 35,7 22,1
Singapore 66,1 80,8 53,8 22,6
Taiwan Province of China 19,1 6,6 14,9 4,1
Unspecified 70,0 126,4 91,6 296,7
Note: Data refer to materialized FDI notified to the National Foreign Investment Register
(RNIE). They do not include profit reinvestment and transfer among companies.
Source: UNCTAD (http://www.unctad.org/Templates/Page.asp?intItemID=3198&lang=1,
081110)
38
Table A2.a. FDI flows in the host economy, by industry, USD in millions, 1994-1998
Sector/industry 1994 1995 1996 1997 1998
Total 15 045,2 9 646,4 9 943,1 14 159,7 12 169,6
Primary 108,6 90,2 115,5 140,2 71,1
Agriculture, hunting, forestry and fishing 10,8 11,1 31,7 10,0 28,7
Mining, quarrying and petroleum 97,8 79,1 83,8 130,2 42,4
Secondary 6 187,0 4 848,7 4 706,1 7 282,9 5 100,0
Food, beverages and tobacco 1 807,8 651,2 501,9 2 952,4 730,7
Chemicals and chemical products 645,5 573,1 1 196,9 813,0 1 159,2
Non-metallic mineral products 51,2 89,6 29,7 5,8 14,2
Metal and metal products 1 342,3 142,5 324,8 105,7 51,2
Machinery and equipment 1 888,7 2 892,6 2 209,6 2 749,7 2 323,5
Other manufacturing 451,5 499,7 443,2 656,3 821,2
Tertiary 4 344,2 3 385,9 2 882,0 4 702,7 2 955,8
Electricity, gas and water 15,2 2,1 1,1 5,2 26,6
Construction 259,4 26,2 25,5 110,4 81,6
Trade 1 250,7 1 008,6 726,8 1 899,4 938,3
Hotels and restaurants 722,5 102,1 166,5 563,3 199,2
Transport, storage and communications 719,3 876,3 428,0 681,5 435,9
Finance 715,5 951,8 1 109,9 968,2 626,7
Business activities 488,0 203,3 273,9 201,6 354,5
Real estate 221,7 64,7 64,2 58,6 56,7
Other business activities 266,3 138,6 209,7 143,0 297,8
Other services 173,6 215,5 150,3 273,1 293,0
Unspecified 4 405,4 1 321,6 2 239,5 2 033,9 4 042,7
Note: Data refer to materialized FDI notified to the National Foreign Investment Register (RNIE).
They do not include profit reinvestment and transfer among companies.
Source: UNCTAD (http://www.unctad.org/Templates/Page.asp?intItemID=3198&lang=1, 081110)
Table A2.b. FDI flows in the host economy, by industry, USD in millions, 1999-2002
Sector/industry 1999 2000 2001 2002
Total 12 856,0 15 484,4 25 333,4 9 696,4
Primary 208,0 269,3 37,8 95,5
Agriculture, hunting, forestry and fishing 80,9 88,2 4,6 4,8
Mining, quarrying and petroleum 127,1 181,1 33,2 90,7
Secondary 8 750,2 8 865,1 4 798,7 4 092,9
Food, beverages and tobacco 988,5 1 190,0 870,0 306,0
Chemicals and chemical products 951,8 1 311,3 200,8 490,3
Non-metallic mineral products 230,9 143,3 96,2 -86,5
Metal and metal products 270,3 290,1 180,6 22,1
Machinery and equipment 5 283,2 4 056,1 2 620,7 2 578,9
Other manufacturing 1 025,5 1 874,3 830,4 782,1
Tertiary 3 897,8 6 350,0 20 497,9 5 508,0
Electricity, gas and water 139,5 116,8 268,9 24,6
Construction 129,0 168,4 73,0 99,8
39
Trade 1 196,9 2 175,9 1 542,2 1 126,5
Hotels and restaurants 294,9 337,9 306,5 197,6
Transport, storage and communications 278,3 -2 371,9 2 912,9 750,3
Finance 350,3 4 250,4 13 229,6 2 861,5
Business activities 835,7 1 255,0 1 787,1 240,9
Real estate 169,8 269,6 118,3 52,1
Other business activities 665,9 985,4 1 668,8 188,8
Other services 673,2 417,5 377,7 206,8
Unspecified - - - -
Note: Data refer to materialized FDI notified to the National Foreign Investment Register (RNIE).
They do not include profit reinvestment and transfer among companies.
Source: UNCTAD (http://www.unctad.org/Templates/Page.asp?intItemID=3198&lang=1, 081110)
40
Table A3. FDI inflows from different sources and GDP per capita, 1980-2007
FDI (USD at current prices in millions) GDP per capita, PPP
(USD)
Year Secretatía de Economía UNCTAD OECD OECD
1980 2 099,3 4 338,3
1981 3 075,9 5 043,8
1982 1 900,3 5 192,4
1983 2 191,6 5 050,3
1984 1 541,0 5 310,6
1985 1 983,6 5 506,4
1986 2 400,7 5 307,0
1987 2 634,6 5 443,4
1988 2 880,0 5 586,9
1989 3 175,5 5 924,5
1990 2 633,2 6 341,1
1991 4 761,5 6 563,5
1992 4 392,8 6 831,9
1993 4 388,8 4 389,0 6 998,6
1994 10 972,5 15 069,1 7 331,9
1995 9 526,3 9 678,8 6 883,8
1996 9 185,4 10 086,7 7 262,9
1997 12 829,6 14 164,8 7 769,7
1998 12 656,3 12 408,6 8 136,5
1999 13 826,0 13 728,2 13 631,2 8 447,3
2000 17 972,9 17 976,7 17 587,8 9 152,3
2001 29 749,8 29 483,1 27 150,9 9 246,7
2002 23 679,1 23 048,6 18 274,7 9 484,4
2003 16 245,7 16 594,3 14 183,8 9 918,7
2004 23 753,7 22 883,3 22 300,9 10 525,3
2005 22 751,3 20 945,4 19 642,7 11 299,0
2006 19 626,4 19 290,6 19 037,4 12 104,2
2007 27 038,9 24 686,4 23 768,3 12 774,0
Note: The data available from the sources does not cover all years.
Sources: Secretatía de Economía (http://www.economia.gob.mx)
OECD (http://stats.oecd.org/wbos/Index.aspx?DatasetCode=CSP2008, 081110)
UNCTAD (http://stats.unctad.org/FDI/TableViewer/tableView.aspx?ReportId=1254,
081110)
41
Table A4. Logarithmic calculations from table 3, 1993-2007
FDI GDP per
capita, PPP FDIt-1 GDPt-1 per
capita, PPP
Year UNCTAD OECD OECD UNCTAD OECD OECD
1993 8,4 8,4 8,9
1994 9,3 9,6 8,9 8,4 8,4 8,9
1995 9,2 9,2 8,8 9,3 9,6 8,9
1996 9,1 9,2 8,9 9,2 9,2 8,8
1997 9,5 9,6 9,0 9,1 9,2 8,9
1998 9,4 9,4 9,0 9,5 9,6 9,0
1999 9,5 9,5 9,0 9,4 9,4 9,0
2000 9,8 9,8 9,1 9,5 9,5 9,0
2001 10,3 10,2 9,1 9,8 9,8 9,1
2002 10,0 9,8 9,2 10,3 10,2 9,1
2003 9,7 9,6 9,2 10,0 9,8 9,2
2004 10,0 10,0 9,3 9,7 9,6 9,2
2005 9,9 9,9 9,3 10,0 10,0 9,3
2006 9,9 9,9 9,4 9,9 9,9 9,3
2007 10,1 10,1 9,5 9,9 9,9 9,4
Note: Own calculations
Sources: OECD (http://stats.oecd.org/wbos/Index.aspx?DatasetCode=CSP2008, 081110)
UNCTAD (http://stats.unctad.org/FDI/TableViewer/tableView.aspx?ReportId=1254,
081110)