Foreign Direct Investment and economic growth in small island developing states- A panel data analysis.

Foreign Direct Investment and economic
growth in small island developing states- A
panel data analysis
Submitted by:
Jhary Yadav Nandishwar
&
Bacorisen Prabhat Singh
In partial fulfillment of the requirements of
The
Bachelor in Science (Honours)
In
Economics and Finance
University of Mauritius
Faculty of Social Science and Humanities
Department of Economics and Statistics
April 2013

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TABLE OF CONTENTS
Chapter 1: Introduction................................................................................................................... 1
1.1 Introduction......................................................................................................................... 1
1.2 Why FDI and economic growth?........................................................................................ 2
1.3 Objectives ........................................................................................................................... 2
1.4 Problem Statement.............................................................................................................. 2
1.5 Outline of chapters.............................................................................................................. 3
Chapter 2: Review of Theoretical and Empirical Literature ....................................................... 4
2.1 Introduction......................................................................................................................... 4
2.2 OLI...................................................................................................................................... 5
2.2.1 Other determinants of FDI .......................................................................................... 6
2.3 FDI and Economic Growth................................................................................................. 7
2.3.1 Growth models............................................................................................................ 8
2.3.2 Theoretical Review.................................................................................................... 10
2.3.3 Empirical Review....................................................................................................... 13
2.4 Small Island Developing States and FDI......................................................................... 16
2.4.1 SIDS ........................................................................................................................... 16
2.4.2 Economic characteristics of SIDS............................................................................... 16
2.4.3 Environmental, economic and society challenges.................................................... 17
2.4.4 SIDS and FDI: A theoretical perspective .................................................................... 18
2.5 Conclusion ........................................................................................................................ 19
Chapter 3: Assessment and Analysis............................................................................................. 21
3.1 Introduction....................................................................................................................... 21
3.2 Model................................................................................................................................ 21
3.3 Trend of key variables ...................................................................................................... 22
3.3.1 GDP ........................................................................................................................... 22
3.3.2 FDI............................................................................................................................. 23
3.3.3 GCF............................................................................................................................ 24
3.3.4 Trade Openness......................................................................................................... 25
3.3.5 Inflation..................................................................................................................... 26
3.3.6 Infrastructure............................................................................................................ 27

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3.4 Inflows of FDI to SIDS..................................................................................................... 27
3.5 Trends of FDI inflow to SIDS .......................................................................................... 29
3.6 Conclusion ........................................................................................................................ 31
Chapter 4: Methodology ................................................................................................................ 33
4.1 Introduction...................................................................................................................... 33
4.2 Hypotheses....................................................................................................................... 33
4.3 Model................................................................................................................................ 33
4.3.1 GDP ........................................................................................................................... 33
4.3.2 FDI............................................................................................................................. 34
4.3.3 GCF............................................................................................................................ 34
4.3.4 Trade openness......................................................................................................... 34
4.3.5 Inflation..................................................................................................................... 34
4.3.6 Infrastructure............................................................................................................ 35
4.4 Data Sources ..................................................................................................................... 35
4.5 Panel data approach .......................................................................................................... 36
4.5.1 Fixed Effect Model..................................................................................................... 37
4.5.2 Random Effect Model ............................................................................................... 38
4.5.3 Fixed or Random Effect............................................................................................. 39
4.6 Model Specification for panel........................................................................................... 40
4.7 Empirical procedure......................................................................................................... 40
4.8 Conclusion ........................................................................................................................ 40
Chapter 5: Interpretation of results.............................................................................................. 41
5.1 Introduction....................................................................................................................... 41
5.2 Empirical results for SIDS............................................................................................... 41
5.3 Conclusion ........................................................................................................................ 46
Chapter 6: FDI and economic growth in Mauritius.................................................................... 47
6.1 Introduction....................................................................................................................... 47
6.2 FDI inflows in Mauritius .................................................................................................. 47
6.2.2 FDI inflows by country............................................................................................... 50
6.3 Overview of FDI and Economic Growth in Mauritius ..................................................... 51
6.3.1 Export Processing Zone (EPZ).................................................................................... 53
6.4 Empirical Review for Mauritius ....................................................................................... 53

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6.5 Time series analysis.......................................................................................................... 55
6.5.1 Model specification for time series........................................................................... 55
6.5.2 Empirical procedure.................................................................................................. 56
6.6 Empirical results for Mauritius ......................................................................................... 57
6.7 Conclusion ........................................................................................................................ 62
Chapter 7: Conclusion and Policy recommendations.................................................................. 63
7.1 Summary of study............................................................................................................. 63
7.2 Policy Recommendations ................................................................................................. 63
7.3 Recommendations for SIDS ............................................................................................. 63
7.4 Recommendations for Mauritius....................................................................................... 64
7.5 Limitation of study............................................................................................................ 65
REFERENCES................................................................................................................................ 66
APPENDICES................................................................................................................................. 75

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Note: The synopsis and the log book are attached in the appendices

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LIST OF TABLES
Chapter 2: REVIEW OF THEORETICAL AND EMPIRICAL LITERATURE
Table 2.1: Other determinants of FDI................................................................................................. 7
Table 2.2: Challenges of SIDS............................................................................................................ 17
Chapter 3: ASSESSMENT AND ANALYSIS
Table 3.1: SIDS, estimated FDI inflows, 2010 (US$ million).............................................................. 28
Chapter 4: RESEARCH METHODOLOGY
Table 4.1: Variable’s specification and expected sign ...................................................................... 35
Table 4.2: Sources of data................................................................................................................. 36
Chapter 5: INTERPRETATION OF RESULTS
Table 5.1: Summary statistics ........................................................................................................... 41
Table 5.2: CORRELATION MATRIX..................................................................................................... 42
Table 5.3: HST and BP-LM test.......................................................................................................... 42
Table 5.4: REM results ...................................................................................................................... 43
Table 5.5: Heteroscedasticity test .................................................................................................... 46
Chapter 6: FDI AND ECONOMIC GROWTH IN MAURITIUS
Table 6.1: FDI inflows by sectors ...................................................................................................... 48
Table 6.2: FDI inflows by country...................................................................................................... 50
Table 6.3: Unit Root results .............................................................................................................. 57
Table 6. 4: ARDL lag estimates.......................................................................................................... 58
Table 6.5: Long-run using ARDL approach based on Akaike Information Criterion (AIC) ................ 59
Table 6.6: ECM for selected ARDL..................................................................................................... 60

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LIST OF FIGURES
Chapter 2: REVIEW OF THEORETICAL AND EMPIRICAL LITERATURE
Figure 2.1: MNCs & the OLI paradigm ................................................................................................ 6
Chapter 3: ASSESSMENT AND ANALYSIS
Figure 3.1: GDP Growth (annual %), 1980-2010............................................................................... 22
Figure 3.2: FDI inflows (% of GDP), 1980-2010................................................................................. 23
Figure 3.3: GCF (% of GDP), 1980-2010 ............................................................................................ 24
Figure 3.4: Trade openness, 1980-2010 ........................................................................................... 25
Figure 3.5: Inflation rate (%), 1980-2010.......................................................................................... 26
Figure 3.6: Infrastructure, 1980-2010............................................................................................... 27
Chapter 6: FDI AND ECONOMIC GROWTH IN MAURITIUS
Figure 6.1: FDI inflows in Mauritius, with trend (US$ million).......................................................... 47
Figure 6.2: FDI and GDI in Mauritius, 1980-2000 ............................................................................. 52
Figure 6.3: CUSUM Plot..................................................................................................................... 61
Figure 6.4: CUSUMSQ Plot................................................................................................................ 61

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ACKNOWLEDGEMENT
First and foremost, this work has been able to be completed by the grace of god who gave
us the strength to write through the dissertation and our supervisor, Dr. B.Nowbutsing who
has been an outstanding mentor, to whom we would like to express our heartfelt gratitude
and appreciation for his guidance which was the major driving force behind our
dissertation. His wide knowledge of econometrics and global issues such as FDI is highly
admired and regarded. We are also thankful to our programme coordinator, Dr.
V.Tandrayen from whom we have learned so much through our years of study. We seize
the opportunity to thank all the lectures we have worked with.
We are very much indebted to our close ones, friends and people with whom we have come
across throughout our dissertation period who in one way or the other have helped us with
constructive comments and advices. Our special thanks go to Arvin Ramsohok, who has
always been responsive to our queries.
Bacorisen Prabhat Singh
&
Jhary Yadav Nandishwar

viii
ABSTRACT
Despite the worldwide record of FDI inflows experienced lately, inflows to SIDS were
among the lowest, acquiring only 1.2% of the total share of developing countries. The role
FDI has in SIDS is an issue hardly discussed in the economics literature given the low
absolute amount of capital involved. The smallness and vulnerabilities of SIDS make it
difficult for them to attract FDI even though FDI is a major driver of economic growth in
these islands. This dissertation is aimed at analysing the effect foreign direct investment
(FDI) has on economic growth of small island developing states (SIDS) and Mauritius.
Taking a sample of 24 SIDS to econometrically assess the impact of FDI on economic
growth, panel data regression is used with the random effect model for the period 1980-
2010. The result indicates that FDI, GCF, trade openness, inflation and infrastructure are all
statistically significant. Even though many SIDS were not taken into consideration due to
data constraints, our results are consistent with the empirical finding available for SIDS
such as Armstrong et al., (1998); Armstrong & Read, (1998a); Armstrong & Read, (2002);
Read (2002).For Mauritius, the ARDL-ECM approach is used and it has been found that
GCF only has short-run significance and not long-run. This dissertation also presents
extensive examination of theoretical and empirical evidence on the factors influencing FDI
and economic growth. Most studies conclude that FDI is conducive to growth.
KEYWORDS: Foreign Direct Investment, FDI, SIDS, Panel Data Regression, Random
Effect Model, ARDL-ECM, Mauritius

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LIST OF ABBREVIATIONS
ADB Asian Development Bank
ADF Augmented Dickey Fuller Test
ARDL Autoregressive Distributed Lag
BP-LM Breusch Pagan Lagrange Multiplier
CUSUM Cumulative Sum
CUSUMQ Cumulative Sum of Squares
ECM Error Correction Model
EPZ Export Processing Zone
EU European Union
FDI Foreign Direct Investment
FEM Fixed Effect Model
GCF Gross Capital Formation
GDI Gross Domestic Investment
GDP Gross Domestic Product
GFCF Gross Fixed Capital Formation
GMM Generalised Methods of Moments
HST Hausman Specification Test
IRS Integrated Resort Scheme

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JAMPRO Jamaica Promotions Corporations
LDC Least Developing Country
LLDC Landlocked Developing Country
LSDV Least Square Dummy Variable
M&A Mergers and Acquisitions
MDGs Millennium Development Goals
MNE Multinational Enterprise
OECD Organisation for Economic Co-operation and Development
OLI Ownership, Location and Internalisation
OLS Ordinary Least Square
PP Philip Peron Test
R&D Research and Development
REM Random Effect Model
SEM Simultaneous Equation Model
SIDS Small Island Developing States
UNCTAD United Nations Conference on Trade and Development
UNCED United Nations Conference on Environment and Development
UN United Nations
US United States

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WIR World Investment Report

Chapter 1: Introduction
1
1.1 Introduction
The role of FDI as a contributor to development and economic growth has been the centre
of one of the major debates ever since the creation of the UN in the 1960s. Many FDI-
growth related studies have been carried with outcomes which have been in favour and
against FDI. Some of the studies concluded that FDI indeed leads to economic growth and
increases productivity in the whole economy whereas others found that FDI was risky in
the sense that it could hinder host countries’ development potentials and exploit local
natural resources without any proper compensation to poor economies.
The level of FDI varies over time, where the level of FDI was high in the early 2000,
plummeted in the middle and became rigorous towards the end. Also, FDI varies
considerably across countries and regions, where recently developing countries have
witnessed a rise in FDI inflows. However these inflows were concentrated only towards a
handful of countries which enjoy sound economic wealth accompanied by proper policies.
The major factor responsible to attract FDI is policy barriers to investment and trade but
nonetheless, FDI is seeking for countries with appropriate market size and growth, proper
quality and skills accompanied by a well-established infrastructure and high level of
domestic technological know-how.
There was a significant rise in FDI inflows to developing economies as from the 1980s
with US$7.5 billion to $35.1 billion in 1990 reaching up to US$256.5 billion and US$478.3
billion in 2000 and 2009 respectively. 2010 was the first time in history where global FDI
flows to developing countries exceeded that of developed countries by nearly 52%. This
remarkable rise in FDI flows classifies FDI as being one of the most important sources of
global capital flows compared to foreign aid, remittances and trade. However for the small
island developing states (SIDS), in contrast with inflows from 2010, FDI inflows to these
economies dropped by 2% in 2011 even if FDI proved to be a vital contributor to capital
formation (23 % in 2011). When compared globally, the group’s FDI inflows stayed
miniscule.

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1.2 Why FDI and economic growth?
Throughout the past three decades, FDI has become a major concern for governments and
the latter put in a lot of effort to attract FDI. Many of them have started to adopt a
liberalised trade regime in order to be more competitive in successfully capturing
technological spillovers and capital that comes along with FDI. In the race to gaining FDI,
countries are not only implementing more liberal investment policies but also using
strategies such as assisting FDI via guaranteed funds, matchmaking and other measures.
For SIDS themselves, FDI inflows, despite being small in amount, represents an important
source of capital which drives their economy by promoting both human and physical
capital and increasing their competitiveness on the global scenario. Due to characteristics
such as limited resources, economic reliance on international markets and vulnerability to
external shocks, SIDS depend a lot on FDI so as to keep their economy afloat (Ghina,
2003).For these small states, being small in size does not act as a barrier to receiving FDI
inflows and this is proved by the study of Armstrong and Read (2003) who find size to be
insignificant in allowing growth to take place.
1.3 Objectives
The main objective of this study is to carry out an empirical analysis in order to find
whether there is any FDI-economic growth relationship in SIDS and Mauritius. Also, it
aims at looking at the determinants of FDI an economic growth and whether they actually
hold for SIDS and Mauritius. In order to make this possible, the research investigates the
FDI-growth nexus focusing specially on FDI inflows, gross capital formation, trade
openness, inflation and infrastructure.
1.4 Problem Statement
Even if in the recent years, the global economy has witnessed unforeseen records of FDI
inflows where the majority of flows are going to the developing countries i.e. more than
50% than developed countries, in turn increasing the gap of inflows across developed and
developing economies (UNCTAD 2011, p.3), LDCs and SIDS experienced a continuous

3
fall in FDI inflows even if FDI was the key contributor to capital formation in SIDS at 23%
in 2011 (WIR 2012, regional trends in FDI). Due to the small amount of inflows that are
directed to SIDS, there is a dearth of research concerning its impact and that of other key
economic key variables on growth of SIDS.
In order to proceed with our study, we cope with the minimum research available by
associating SIDS with other economies where much study has been carried out and sharing
similar characteristics.
1.5 Outline of chapters
The study is broken down into seven chapters and is classified as follows:
Chapter 1 examines the background and objectives of the research.
Chapter 2 focuses on the literature and empirical review of previous research on FDI and
its influence on economic growth, growth models and the determinants of FDI and
economic growth.
Chapter 3 assesses the trends of the key variables in our study and focuses of FDI inflows
to SIDS.
Chapter 4 presents the empirical model and methodology where the econometric model is
specified for SIDS.
Chapter 5 deals mainly with the interpretation of the results based on the econometric
regression for SIDS.
Chapter 6 focuses on FDI and economic growth of Mauritius, where the impact of FDI on
economic growth is analysed using time series and ARDL-ECM approach.
Chapter 7 concludes the study based on the empirical findings and policies are
recommended for each sample analysed.

Chapter 2: Review of Theoretical and Empirical Literature
4
2.1 Introduction
The role that FDI has in encouraging economic growth is one of the most debatable
subjects in economics literature. Foreign direct investment (FDI) is viewed as a growth
catalyst since it offers the capital required for investment, increases competitiveness in the
home country industries and helps local companies in becoming more productive by
implementing better technology or by investing in human capital and physical assets. FDI
is a potential contributor to economic growth in a considerable way due to its stability
compared to other forms of capital flows and its advantages consist of the creation of
capital and employment, smoothing the right of entry to foreign markets and engendering
technological and efficiency spillover to home-grown firms. It is anticipated that due to
these benefits, FDI will without doubt progress the incorporation of the home country into
the global economy and raise growth. FDI is viewed as “a key driver of economic growth
and development. FDI does not only increase capital but also enriches the quality of capital
stock.”
According to the Solow growth model, FDI allows host economies to increase investment
which are higher than local saving and also stimulates capital formation. Nevertheless, this
theory states that the positive impact that FDI has on growth is limited only to the short-
run, not the long-run because of diminishing marginal returns to physical capital where the
economy would experience stable growth rate and it would appear as if FDI did not take
place, with no significant impact on growth (De Mello, 1997). The endogenous growth
models (e.g. Romer, 1999; Lucas, 1988; and Barro and Sala-i-Martin, 1997), on the other
hand, suggests that for FDI to be beneficial to growth rate in generating increased returns
through externalities and spillovers, it is vital to improve efficiency, technology and
productivity.
The nature and volume of FDI are responsible for the way that the latter affects growth and
progress. Therefore, in order to comprehend the influence of FDI on growth, it is vital to

5
determine what drives FDI, its modifications overtime and the fluctuations in the
determinants affecting growth.
2.2 OLI
The most complete economic theory of the determinants of FDI is the OLI framework
developed by John Dunning in the early 1970s (Dunning 1979). The OLI framework tries
to clarify the existence, activities and the strategies of multinational enterprises (MNEs)
throughout the combination of macro- and micro- economic determinants of FDI flows. It
identifies three bases of advantages that are pre-requirements for firms to fit into
international production to become MNEs; namely ownership (O) advantage, location (L)
advantage and internalization (I) advantage.
Ownership advantage refers to the need for MNEs to seize firm-specific competitive
advantages over domestic firms in supplying particular markets. The advantages may
consist of both tangible and intangible sources of benefit and arise from the monopoly
control of these assets by MNEs. The “O” advantages propose the prospective for
considerable increasing returns to scale consequential from the comparatively low or zero
marginal cost incurred in transferring them across international borders.
The Location advantage provides MNEs with an encouragement to situate at least some
part of their transactions in host countries rather than at domicile. MNEs location decisions
are consequently founded leading the actual and apparent competitive advantages of
possible host countries. These include:
 The accessibility of low-cost raw materials, above all natural resources, transitional
inputs and low cost labour
 High quality human capital, including Research and Development
 Agglomeration economies-clusters of producers and suppliers
 Favourable government policies and political constancy
 A favourable business culture.

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MNEs benefit from the “I” advantage the own production rather than manufacturing
through a partnership arrangement such as licensing or a joint venture. Thus, MNEs can
better exploit the “O” and “L” advantage since the international transaction costs are
minimised.
Dunning points out that the control of OLI advantages is an essential pre- requirement for
FDI to occur, though they remain insufficient, given possible financial and managerial
resource restrictions as well as high level strategic aims.
Figure 2.1: MNCs & the OLI paradigm
Source: Traça, 2008
2.2.1 Other determinants of FDI
Earlier studies have analysed the link between FDI and numerous macroeconomic
variables. Several that might be said to have a relationship with FDI flows are the size and
growth prospective of the home market, economic stability, the degree of openness of the

7
host economy, the income level and the quality of institutions and level of development.
Below, the determinants that are likely to affect FDI have been summarized into table 2.1.
Table 2.1: Other determinants of FDI
Effects on FDI
Potential
Determinants of FDI
Insignificant /Non-
effect
Negative effect Positive effect
Growth rates Tsai (1994) Hansen (2004),
Gani and Sharma
(2003)
Openness Wheeler and Mody
(1992)
Easterly and
Kraay (2000),
Shrivastava (2006)
Market Size Parletun (2008),
Dauda (2008)
Labour force Gounder and
Xayavong (2002)
Rehman, Orangzab
and Raza (2011)
Labour costs Tsai (1994) Ramasamy and
Yeung (2004)
Zheng (2009)
Infrastructure/
Domestic investment
Rehman, Orangzab
and Raza (2011)
Kok and Ersoy
(2009)
Tax Blonigen and Davis
(2004)
Chakrabarti (2001) Swenson (1994)
Govt effectiveness,
political stability,
other economic and
social policies
Adams (2009)
Source: Authors’ compilation
2.3 FDI and Economic Growth
Foreign direct investment has been extensively recognised as an essential part leading to
economic growth and development in developing countries – partly because the very
essence of economic development is the rapid and efficient transfer and cross-border
adoption of “best practice” (Ajayi, 2006). One way through which this occurs is by
upgrading human capital (Klein et al., 2001).
Growth is a vital ingredient known to cause a reduction in poverty. Since growth can be

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promoted by FDI, then it is essential to poverty alleviation especially for African nations in
achieving their millennium development goals (MDGs). There are also conflicting views in
the theory of FDI. According to Addison and Mavrotas (2005) there are many ways in
which FDI play a role in the general growth process. One of them is physical and human
capital accumulation: well implemented FDI projects lead to an increase in growth and jobs
which diminishes income-poverty gap.
The contribution of FDI to economic growth is perhaps far more substantial as such capital
flows represent new technologies, larger knowhow and supplementary managerial
expertise. These characteristics produce additional growth effects in the host countries.
Many developing economies face several constraints that arise from the lack of internal
research and development, technology and human capital. FDI has been perceived to be a
contributor to their growth, in the way that it accelerated the transmission of new
technologies, helped to attain their goals and augment their internal stock of capital, leading
to an increase in their global competitiveness.
There is a multitude of theoretical and empirical explanations for the impact and influence
of FDI on economic growth. The review aims at providing a comprehension of the
theoretical and empirical background, views and present thought to find the nexus between
FDI and economic growth. The empirical analysis of the relationship between FDI and
growth is often said to rely on factors like “absorptive capacity” of the host country and
takes into consideration the level of human capital development, types of trade system and
degree of openness.
2.3.1 Growth models
So as to understand the relationship between FDI flows and economic growth, it is
important to look at the major theories of investment and growth. The theories relating to
FDI flows and growth are founded upon Harrod-Domar, neoclassical and endogenous
growth models. The revolutionary growth model of Harrod (1939) and Domar (1946)
pointed out that capital formation is a catalyst to the standard of living, which therefore
leads to higher growth. The model principally differentiates between the natural and the

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warranted growth rate. It focuses on the natural growth rate as being the outcome of a rise
in labour force without technological change and on the other hand, the warranted growth
rate as being dependent on the investment and saving practices of households and firms.
Nonetheless, the Harrod-Domar model makes use of short-run tools to assess the long-run
glitches in the economy. The model received criticism from the neoclassical economist
Solow (1956) owing to its hypothesis of fixed amount of factors of production and
alternation between capital and labour. Solow’s proposal was based on the idea that labour
efficiency is increased by capital formation in the vigorous process of investment growth.
He agrees with the hypothesis of the Harrod-Domar model of long-run progress void of
fixed proportion. Solow takes into account an economy with a combination of capital and
labour, which produces a single identical product via savings, in proportion to income and
labour efficiency. The Solow model considers knowledge to be a vital part in the course of
production.
However, the Harrod-Domar model examines the long-run problems of the economy by
using the short-run tools. Harrod-Domar model was criticised by the neoclassical
economist Solow (1956) due to its assumption of fixed proportion of factors of production
and substitutability between labour and capital. Solow argued that capital formation
increases labour productivity in a dynamic process of investment growth. He accepts the
assumptions of the Harrod-Domar model of long-run growth without any fixed proportion.
Solow considers an economy that combines capital and labour to produce a single
homogenous commodity through savings, which are proportional to income and labour
productivity. Knowledge has been considered as an important input in the production
process in the Solow model.
In the neoclassical Solow growth model, with decreasing returns to physical capital, and
technological change being exogenous, FDI is said to have no effect on the long-run rate of
growth. These theories forecast that economies with the same level of preferences and
technology will move towards the same levels of income and have a convergent growth
rate based on the lack of global capital movements. The prediction of capital flows moving
from countries where capital is abundant to where it is limited is enforced by factor

10
mobility. The latter leads to long run stability accompanied with a balance in the capital-
labour ratio and factor prices.
In the mid 1980’s when the endogenous growth theories emerged, it stretched the role of
capital in order to include knowledge as a key element of capital along with plant and
machinery. In contrast with the neoclassical growth theories, the new growth theories
concentrated on the formation of technological knowhow and its spillovers.It starts from
the observation that technological progress takes place through innovations, in the form of
new products, processes and markets, many of which are the result of economic activities.
For example, because firms learn from experience how to produce more efficiently, a
higher pace of economic activity can raise the pace of process innovation by giving firms
more production experience. Also, because many innovations result from R&D
expenditures undertaken by profit-seeking firms, economic policies with respect to trade,
competition, education, taxes and intellectual property can influence the rate of innovation
by affecting the private costs and R&D.
2.3.2 Theoretical Review
Economists have recently paid much attention to the disparity in FDI inflow and economic
growth fluctuations experienced by developing countries. There is vast amount of studies
relating to the theoretical and empirical aspect on the influence of FDI on economic
growth. However, evidence from these studies show mixed results. Theoretically, FDI is
known to have a positive influence on the host economy through the resource transfer
effects, creation of employment, amelioration of the balance of payment and transfer of
technology.
Studies carried out by Findlay (1978), Lall (1974), Loungani and Razin (2001), and Romer
(1999), point out that FDI conveys the necessary physical capital, modern technology,
marketing and managerial skills, and exposure to international business practices and leads
to an increase in competition. Resources acquired through FDI have the ability to be
transmitted into local firms, leading to increased innovation and productivity. FDI, both
directly and indirectly contributes to job creation in the host country and the new rise in

11
employees increases spending in the economy. These turn of events take the form of
positive multiplier effects in the economy. The improvement in the balance of payment of
the host country is due to the flourishing of the capital account through the large amount of
capital pooling in and because of the fall in the import of goods and services which
contrarily would have to be imported. Also, surplus taxes obtained from multinational
companies may also aid to ameliorate budgetary position of the local economy.
Hymer (1976) proposed that the benefits of technological transmission, amongst others,
came in the form of benefits from product adoption, innovations in the process and
organisation in local firms which was introduced by the parent company termed as “firms
specific assets”, and the effects of indirect spillover on the whole economy.
Economic growth in LDCs is highly dependent on whether they have the absorptive
capacity to implement new technologies, particularly in the race to globalisation. FDI
affects economic growth via knowledge transmissions; increase in knowledge in the
beneficiary countries, influencing training of labour and upgrading labour skill. The more
the amassed knowledge, the quicker technological growth takes place; expenses go down
as the level of knowledge goes up [Campos and Kinoshita (2002); Findlay (1978)].
Balasubramanyam et al. (1996) highlight that innovative ideas and entrepreneurial skills
associated with FDI are spread throughout different management systems and
organisational processes.
The absorptive ability of a country is known to influence the volume and type of inward
FDI flows. The category of FDI has a dependence on institutional aspects, for instance, the
beneficiary country’s trade system, legislation, political firmness and scale factors, such as
balance of payment restraints and the size of the local market for goods produced in the
course of FDI.
Balasubramanyam et al. (1996) analyse whether the position of FDI in improving growth is
influenced by the trade policy regime in a country. They concluded that a country with an
outward trade strategy give confidence to competition from either international trade or

12
domestic sources and therefore research and development and investment in human capital
is steady with the endogenous growth theory.
De Mello (1999) found the relationship of FDI and economic growth to be twofold. Firstly,
growth is attained via capital accumulation in the home country. FDI inflows may raise the
stock of locally accessible physical capital and so the economic growth of the beneficiary
country. In this context, the rise of physical capital via FDI may have merely temporary
impact on the economic growth of the beneficiary country. FDI is also capable of
improving growth through the adoption of new ideas and equipment, as well as foreign
technologies in the production function of the beneficiary country (Borensztein et al. 1998).
Borensztein, De Gregario, and Lee (1998) argue that FDI positively affects the economic
growth of a country with a highly educated workforce, allowing them to fully benefit from
FDI spillovers. In contrast, Blomström, Lipsey and Zejan (1994) find no confirmation that
education is vital. Instead, they argue that FDI has an encouraging growth effect when the
economy is healthy. Additionally, Alfaro et al. (2003) suggest that FDI stimulates
economic growth in countries with well-developed financial markets, while
Balasubramanyam, Salisu and Sapsford (1996) argue that trade openness is vital for
attaining the growth effects of FDI.
In spite of the various evidence provided by recent studies, many theoretical arguments
explain the inability of developing economies to gain from FDI. Krugman (1998) states that
the control transfers from local to overseas firms might not always benefit the local
economy due to the problem of adverse selection. In case of “Fire Sale” during crises,
ownership may be transferred from local to overseas firms that are inefficient.
Saltz (1992) and Agosin and Mayer (2000) find that in cases of unfair competition, FDI
might lead to the “crowding out” of local firms. The potential spillover contribution from
FDI to the host country could be reduced because of the minimum linkage of foreign firms
to the local economy. Moreover, a consequent repatriation of earnings to parent firms from
subsidiaries could handicap the host nation’s balance of payment. In order to earn higher

13
profits, foreign firms provide tailored products which are aimed at only the rich portion of
the local economy, widening the inequality gap.
Some theoretical evidences contradict the hypothesis that technology, channeled by FDI,
stimulates economic growth. Haddad and Harrison (1993) studied Morocco, Aitken and
Harrison (1999) studied Venezuela, Djankov and Hoekman (2000) evaluated data for the
Czech Republic, and Konings (2001) observed Poland and Bulgaria, and all these studies
were unsuccessful to find proofs about technology spillovers arising from FDI. Rodrik
(1999) wrote that: “today’s policy literature is filled with extravagant claims about positive
spillovers from FDI but the evidence is sobering.”
Other conflicting theories predict that in the existence of prevailing trade, financial and
other alterations will hurt resource allocation and will end up in slow growth (Boyd and
Smith 1992). Abstractly, some theories provide vague views about the growth effects of
FDI, while others propose that FDI will encourage economic growth only under certain
policy conditions.
Many studies conclude that the link between FDI and economic growth is multifaceted.
Given that we are not yet persuaded about the growth effects of one precise form of
international investment like FDI, the lack of an agreement on international investment’s
broad role in the development of economic growth is not unforeseen.
2.3.3 Empirical Review
The influence that FDI has on economic growth has been often evaluated through various
research and studies and econometric model specifying the rate of growth of real GDP or
GDP per capita as a function of the inflow of FDI. Similarly, the link between FDI and
domestic investment has been evaluated using crowding–in/crowding-out hypothesis.
Evidence shows varied results on the impact of FDI on economic growth and domestic
investment. The important findings are elaborated below.
Nair Reichert and Weinhold (2001), use a mixed fixed and random panel data estimation
method to enable for cross country heterogeneity in the causal relationship. They find some

14
evidence that the efficiency of FDI to promote growth rate, in spite of being heterogeneous
across countries, is greater for economies which are more open.
Borenszteinet.al (1998) studied the effect of foreign direct investment on economic growth
using a cross country regression structure, making use of data on FDI inflows from
industrialised countries to 69 developing countries over the previous two decades. The
result of the study concluded that FDI is an imperative medium for the transfer of
technology, supplying moderately more to growth than local investment.
Bengoaet al. (2003) used the panel data analysis for a sample of 18 Latin American
countries for 1970-99. The results show that FDI is positively correlated with economic
growth in host countries.
De Mello (1999) applied time series and panel data analysis on a sample of OECD and
non-OECD countries for the period 1970-90. He stated that FDI has a positive impact on
growth whenever FDI and domestic investment are complements. Roy and Van den Berg
(2006) apply a time series data to a simultaneous equation model (SEM) that precisely
captures the two-way relationship between FDI and growth in the US. Their results state
that FDI has an important, positive and economically significant effect on growth. The
SEM approximations also reveal that FDI growth is income inelastic. The study entails that
even for a technologically advanced country like the U.S; benefits from FDI are very
extensive in the long run.
Alternatively, Zhang (2001) and Choe (2003) studied the causal relationship between FDI
and economic growth. Zhang (2001) made use of eleven developing countries’ data in East
Asia and Latin America. Through the use of cointegration and Granger causality tests, he
came to the conclusion that in five cases, economic growth is improved by FDI but the host
country’s trade regime and macroeconomic stability are important. In accordance with the
results of Choe (2003), causality between FDI and economic growth run in either way but
with an affinity towards growth enhancing FDI. There is little evidence about the opposite.
Rapid economic growth could lead to an increase in FDI inflows.

15
Further studies done by Chowdhury and Mavrotas (2003) scrutinise the causality between
FDI and economic growth through the use of time series data from 1969 to 2000 for three
developing countries, Chile, Malaysia and Thailand, all three being the major beneficiaries
of FDI with diverse history of macroeconomic policy regimes and growth trends. The
empirical results clearly concluded that it was GDP that encouraged FDI in Chile, not the
opposite whereas for Malaysia and Thailand, there was strong evidence of a bi-causality
between the two variables.
Furthermore, Frimpong and Abayie (2006) studied the causal relationship between FDI and
GDP growth for Ghana for the pre and post structural adjustment program periods and the
course of the causality between the two variables using annual time series data from 1970
to 2005. The analysis found no causal relationship between FDI and growth for the whole
sample period and the pre structural adjustment program period. FDI nonetheless caused
GDP growth during the post structural adjustment program period.
Carkovic and Levine (2002) used a panel database enclosing 72 developed and developing
countries, in an attempt to study the link between FDI and economic growth. The analysis
carried out both cross sectional OLS analysis plus a dynamic panel data analysis through
the use of GMM. The conclusions were that there was no vigorous connection from inward
FDI to host country economic growth.
Quite the opposite to the earlier studies, De Mello (1999) stumble on only weak indications
of a positive link between FDI and economic growth, even though he used both time series
and panel data fixed effects estimations for a sample of 32 developing and developed
countries. Few analyses for instance Saltz (1992), uncover an unenthusiastic link between
FDI and economic growth. Nevertheless, most of the studies conclude that FDI increases
total productivity and economic growth.
After having looked at the major theories relating to FDI and economic growth, we will
now move on to analysing their validity in SIDS and also look closer at these small states.

16
2.4 Small Island Developing States and FDI
The impact that FDI has in SIDS is an issue that is very less talked about because of the
low absolute amount of capital flows implicated. This is also due to the fact that issues
concerning SIDS have been overlooked in the conventional theoretical and empirical
economics literature. However, for these developing small island states, FDI symbolises a
rather significant and supplementary source of investment capital and has the potential to
contribute to growth and development. This is so because FDI can speed up the transfer,
acquisition and absorption of new technologies and improve the human capital stock in the
host countries. This enhances their international competitiveness. The growth effects of
FDI may therefore be greater in developing countries than industrialised countries with the
same amount of investment flows.
2.4.1 SIDS
SIDS were recognised as a group of developing islands which face specific social,
economic and environmental vulnerabilities at the United Nations Conference on
Environment and Development (UNCED) , also known as the Earth Summit, held in Rio de
Janeiro, Brazil (3-14 June 1992). Currently, the United Nations Department of Economic
and Social Affairs list 52 small island developing states, broken down into three categorical
regions, namely the Caribbean, the Pacific and Africa and the Indian Ocean. SIDS are
mostly low lying coastal countries that share almost same sustainable development
challenges which includes the problem of malthusianism, limited resources which make
them dependent on international trade and vulnerability to natural disasters. SIDS also
share very high level of intrinsic vulnerabilities, especially to external shocks.
2.4.2 Economic characteristics of SIDS
There is now quite a considerable amount of literature regarding the nature and the
implication of the vital economic characteristics of small states in general for their growth
performance (reviewed in Armstrong and Read 2003). The summary of these
characteristics are as follows:

17
 Small size of the home market;
 Limited domestic resource availability (both natural resources and supply of
labour);
 Narrowness of domestic output, exports and export market;
 High degree of structural openness to trade; and
 Surplus cost of transport and communications of being islands, land-locked or
archipelagos.
These crucial characteristics have important implications for the economic performance of
small economies in the framework of key variables found in endogenous growth models:
 Openness to trade;
 Human capital formation
 The quality of endogenous policy; and
 Convergence clubs.
2.4.3 Environmental, economic and society challenges
There are major challenges and constraints faced by SIDS which can be broadly classified
in three categories, namely environmental, economic and society. Table 2.2 below
categorises the different obstacles faced by the small states.
Table 2.2: Challenges of SIDS
Environmental Economic Society
Climate change Inadequate sustenance in
agriculture and fisheries
Lack of human resources
and education
Fragile ecosystems Lack of technological
capacity
Lack of institutional
building
Soil erosion Lack of durable housing
and physical infrastructure
Social tensions
Land degradation Over dependence on Inadequate governance

18
imports
Land-based pollution Lack of market access Lack of viable
participatory frameworks
Limited freshwater
resources
Lack of finance Lack of cultural
innovations and integration
Untreated sewage
These challenges cannot be ignored anymore by the island sustainable societies. SIDS are
devising ways such as broadening their economic base while preserving the ecology,
reducing poverty and tackling the health issues. Genuine foreign aid, with proper terms and
conditions to prevent dependency, plays a major role in making it possible for SIDS to
integrate the global framework.
2.4.4 SIDS and FDI: A theoretical perspective
The global distribution of FDI has been very much in the limelight in the economics
literature over the last four decades. The majority of the literature was concentrated towards
developed countries which account for more than 80% of FDI inflows compared to
developing countries which account for less than 20% of all flows. China is presently the
highest recipient of FDI inflows. FDI analysis in developing economies has been given
little attention and many of these are residuals of global FDI analysis or concentrated on a
particular developing country, mainly China.
In this context, it is not surprising to find that inflows of FDI to SIDS have almost been
neglected in the literature due to their smallness, the lack of absolute values of FDI inflows
and the insignificance of these inflows in the global context. However, for SIDS
themselves, FDI is known to be an important contributor to their economic advancement
and therefore it is unwise to neglect these inflows despite their seemingly low value. The
consequences of FDI inflows to SIDS are generally inadequate in their possible depth and
multiplier effects. Nonetheless, FDI in SIDS tend to be highly productive when concerned

19
with the exposure of SIDS to international levels making them more competitive in terms
of technological knowhow and the generation of positive externalities.
Empirical analysis of the performance of small states shows that there is a positive
relationship between growth and sectorial structure of their domestic economic activity in
addition to being influenced by their location. Being an island or archipelago is not a major
barrier to growth performance for SIDS. Furthermore, many small states including several
SIDS have shown resilience to adverse growth implications of their critical economic traits.
They have been able to work out suitable domestic policies that encourage growth
effectively (Armstrong et al. 1998; Armstrong and Read 1998, 2002; Read 2002).
The irregular flows of capital to SIDS are due to various forms of push and pull factors in
the global financial framework in the last two decades. In theory, financial integration,
accompanied with high absorptive capacity, depending on human capital, viability of local
financial market, good governance and macroeconomic policies are the ingredients for
economic growth through FDI (Mine Tükenmez et al., 2004). Also, a modern financial
legislation is vital to attract FDI.
Gani (1999) examined the contribution of FDI on Fiji’s growth. His results concluded that
there exists a positive relationship between FDI and economic growth in Fiji and thus
strategies to raise the flow of FDI ought to be believed seriously. He also argued that
determinants like market size, degree of openness and real exchange rate were vital for
attracting FDI into Fiji.
2.5 Conclusion
While the contradictory relationship between FDI and economic growth remain unsolved,
most theoretical and empirical studies mentioned above find that FDI affects economic
growth positively depending on the host country’s absorptive capacity. This depends on
multiple factors such as a good level of human capital, a good infrastructure, a developed
financial system as well as a liberalised trade system that draw FDI towards the developing
states. While environmental, economic and society factors are major deterrent to FDI
inflows in SIDS, it cannot be excluded from our study as FDI plays an important role in the

20
growth of these economies. We now move to the next section of our study where the trend
key variables will be analysed.

Chapter 3: Assessment and Analysis
21
3.1 Introduction
Transitioning from the theoretical literature to the analytical part, we define which
economic variables should be incorporated in the model and in what form. Prior to the
presentation of our econometric model and results of our estimations, we will define our
model and illustrate the trend of the variables we will be using from year 1985 to 2010.
3.2 Model
Here we consider economic growth as being a function GDP, foreign direct investment,
trade openness, inflation, infrastructure and GCF).
GDP Growth =f (FDI, GCF, TRAO, INFLA, INFRAS)
Where
GDP =Gross domestic product growth (annual %)
FDI =Foreign direct investment net inflows (% of GDP)
GCF = Gross capital formation (% of GDP)
TRAO = Trade openness
INFLA= Inflation
INFRA= Infrastructure
We will look more closely at the definition and implication of our key variables used in our
model in the next chapter.

22
3.3 Trend of key variables
This section will focus on the trend of the different variables that will be used in the
econometric model. The movements of the variables are calculated using data from World
Bank Database and UNCTAD where a special section for SIDS has been allocated.
3.3.1 GDP
GDP is representative of the monetary worthiness of a country which results from
economic activities. In our model, we will be using GDP growth (annual percentage) for
the years 1980 to 2010. The GDP growth has been experiencing several fluctuations; they
have been rising (highest point-6.7% in 2004) and falling (-1.3% in 2010), but the SIDS
faced two major declines in the years 1989 and 2006. The reasons for the several declines
as well as the major fall in 1989 (-0.3%) were because of the impacts of the food fuel and
financial calamities, as well as the natural disasters that hit the SIDS. Moreover the public
debt of several SIDS increased sharply from mid-year 2006 to 2010. Many SIDS benefited
from the emergency financial support from the IMF which helped to rebuild their economy.
Figure 3.1: GDP Growth (annual %), 1980-2010
Source: World Bank, WDI
-2
-1
0
1
2
3
4
5
6
7
8
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
GDP
Growth
(annual
%)
Years

23
3.3.2 FDI
Despite the small size of SIDS, FDI remains a vital determinant of investment capital. In
our model, we will be using FDI as a percentage of GDP for the years 1980 to 2010. FDI
seems to be increasing for the first years (2.79% for 1981), facing some declines (lowest
point- 0.73%) and increases till 1998. Thereafter, FDI has been growing at an increasing
rate up to 2009 (highest 7.16%), where it started to fall. The seasonal rise and fall of the
FDI inflows are due to the vulnerability of the SIDS to external shocks. According to
UNCTAD (2010), the fall of FDI in 2009 can be attributed to the global recession brought
on by the world financial and economic crisis.
Figure 3.2: FDI inflows (% of GDP), 1980-2010
0
1
2
3
4
5
6
7
8
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
FDI
inflows
(%
of
GDP)
Years

24
3.3.3 GCF
Gross capital formation is comprised of outlay on additions to the fixed assets of the
economy plus net changes in the level of inventories. GCF affects economic growth by
increasing the physical capital stock. GCF, here measured as a % of GDP, fluctuates
around 21.6% and 30% as shown on figure 3.3. These oscillations may be subject to
structural adjustments as each stage of development has particular requirements such as
machinery.
Figure 3.3: GCF (% of GDP), 1980-2010
0
5
10
15
20
25
30
35
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
GCF
(%
of
GDP)
Years

25
3.3.4 Trade Openness
Trade openness is a crucial determinant of economic growth in SIDS. In the 1980s, SIDS
economies were highly open to trade with their highest point at 60 in 1981. Here trade
openness fluctuates between 60 and 23.6 as shown in figure 3.4 below. Trade openness is
the means through which the effects of external shocks are intensified and therefore cause
volatility in the index calculation. Trade openness however is a key determinant of
economic growth in the small states and consequently a major source of resilience.
Openness to trade is defined as the total of exports and imports as a share of GDP.
Figure 3.4: Trade openness, 1980-2010
0
10
20
30
40
50
60
70
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Trade
openness
Years

26
3.3.5 Inflation
Inflation rate was at its highest peak, at 15.4% in the year 1980 and was at 3.4% in 2010.
The high inflation rate in 1980 may be due to the sugar boom era and the tendency of fast
tourism growth which is accompanied by inflationary pressures. The other significant rise
in inflation in 2008, at 8.9%, was due to the financial crisis where the price of consumer
goods and petrol rose, affecting SIDS which are major importers of food and fossil fuels.
Fiscal and monetary policymakers had to intervene to control inflation through tightening
of monetary policies and this can be seen by the decline to 3.4% in 2010. This shows the
willingness of the government to prevent further erosion of the purchasing power. High
inflation is highly deterrent to investment and may decrease international competitiveness.
Figure 3.5: Inflation rate (%), 1980-2010
0
2
4
6
8
10
12
14
16
18
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
Inflation
rate(%)
Years

27
3.3.6 Infrastructure
Today, rapid and reliable means of communications is a prerequisite to modern trade. The
infrastructure model used here is the number of mainline telephone available per 100
people. There was a rapid progression in infrastructure from 1980 (2.4) to 2001 (10.4) and
this may have been caused by the introduction of new technologies and intelligent
infrastructures. There was a constant and gradual decline from 2002 (10.3) to 2010 (9.5)
which may have been caused by the use of other alternatives of telephone lines and
communication such as the internet.
Figure 3.6: Infrastructure, 1980-2010
Source: World Bank, ADI
3.4 Inflows of FDI to SIDS
Any analysis of the flow of FDI to SIDS is prone to strict lack of data and consequently the
relevant statistics on FDI are only available for a restricted set of SIDS. This in turn is most
likely to result in sample selection bias. It is thus informative to provide an overview of the
available data on FDI inflows to SIDS before moving on to more profound statistical
analysis.
0
2
4
6
8
10
12
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
Telephone
lines
per
100
people
Years

28
Table 3.1: SIDS, estimated FDI inflows, 2010 (US$ million)
SIDS FDI inflow,
2010
FDI inflow share of
SIDS total (%)
FDI inflow/GDP,
2010 (%)
Antigua & Barbuda 96.7 1.4 8.4
Aruba
Bahamas
Bahrain
Barbados
Belize
Cape Verde
Comoros
Cuba
Cyprus
Dominica
Dominican Rep
Fiji
Grenada
Guinea-Bissau
Guyana
Haiti
Jamaica
Kiribati
Maldives
Mauritius
Papua New Guinea
Samoa
Sao Tome Principe
St Kitts & Nevis
St Lucia
St Vincent &Grenadines
Seychelles
Solomon Islands
Suriname
Tonga
Trinidad & Tobago
Tuvalu
Vanuatu
Total SIDS–51
Singapore (SIDS-52)1
96.7
159.6
872
155.8
668.8
96.4
111.8
3.9
85.5
70.7
24.3
2094.3
196.2
60.2
1.5
269.5
150
185.8
3.7
216.5
430
28.8
5.3
50.6
133.7
110
103
155.8
121.6
-247.7
8.5
549.4
1.5
41.5
48636.7
7015.2
1.4
2.3
12.4
2.2
9.5
1.4
1.6
0.1
1.2
1.0
0.3
29.9
2.8
0.9
0.0
3.8
2.1
2.6
0.1
3.1
0.4
6.1
0.1
0.7
1.9
1.6
1.5
2.2
1.7
-3.5
0.1
7.8
0.0
0.6
100
87.4*
8.4
3.7
11. 2
0.7
16.7
6.9
6.7
0.7
2.1
0.3
5.2
4.1
6.2
7.7
0.2
11.9
2.3
1.4
2.6
10.4
4.4
0.3
0.9
25.2
19.9
9.1
15.3
16.2
19.9
-5.7
2.3
2.6
4.7
16.1
_
22.8
1
Inflows of FDI being gigantic to Singapore, it has been calculated separately from the other SIDS so as not to
bias our analysis.

29
Source: Authors’ compilation, UNCTAD
Data inflows of FDI to SIDS for the year 2010 are presented in Table 3.1. The disparity in
FDI inflows to SIDS is clearly due to their size which was mentioned in the definition of
SIDS and this is shown in the table. Singapore alone was the recipient of more than 87% of
inflows of FDI to SIDS-52: US$48.6 billion out of a total of US$55.7 billion. Inflows to
SIDS-51 were dominated by The Bahamas, Barbados, the Dominican Republic, Guyana,
Maldives, Mauritius and Trinidad and Tobago which among them were recipients of about
US$5.1 billion of a total of US$7 i.e. more than 72%.
The extent of inequality of these flows makes it problematic for the statistical analysis as
most flows are deviated to Singapore and to a lesser extent to the other larger SIDS. It is
also important to point out that in Suriname, the FDI was negative and to a large extent. In
our next section, 3.5, the trends of FDI inflows will be analysed and explained more
profoundly.
3.5 Trends of FDI inflow to SIDS
The flow of FDI to SIDS is multi-faceted but mostly weak which may be due to their
smallness and their exposure to vulnerabilities. Whilst, FDI towards LLDCs increased
vigorously, LDCs and SIDS were receiving comparatively lower inflows of FDI. The
decline of FDI in the SIDS is thoroughly examined below.
FDI in the small states is low. The collective FDI inflows in 2009 totalled to just $ 60
billion- 1.2% of the total share in developing countries. The vulnerability of SIDS (small
size of markets, limited resources and transaction costs) has placed them in a bad position
to attract FDI.
Despite of all these disadvantages, FDI still is a vital source of investment for SIDS. The
relative amount of FDI inflows to GDP in SIDS was 81% in 2009 accounting for above
150% of GDP in the countries such as Antigua and Barbuda, Saint Vincent and the
Grenadines, Saint Kitts and Nevis, Kiribati, Saint Lucia, Grenada, Vanuatu and Dominica.

30
Inward FDI flows to SIDS dropped by 35% in 2009, ending the consecutive increase for
four years. Nonetheless, at $5 billion, it was the second ever largest inflows recorded. Yet,
the ratio of FDI in GFCF dropped from 40% in 2009 to 30% in 2010.
The distribution of FDI in SIDS was unequal in 2009. Despite the fact that Latin America
and Caribbean islands inward FDI dropped by 45%, Oceania received twice the amount,
$900 million since investment was done in the mining sector of Papua New Guinea. The
Bahamas, Trinidad and Tobago and Jamaica received almost half of the SIDS FDI, since
these states were considered as tax haven. Nevertheless, with the squeezed fiscal policies
prevailing in these economies, FDI towards tax haven SIDS failed.
Cross border M&A sales of SIDS companies sunk in 2009, following a large acquirement
in 2008 (Royal Bank of Canada obtained Royal Bank of Trinidad and Tobago for $2.2
billion). Recently, interest was driven in the mining sector. Investment of $400 million in
the oil and gas industry in Papua New Guinea in 2009 was made by ExxonMobil (United
States).
FDI inflows to Jamaica dropped drastically by 62% in 2010 reaching US$185 million,
according to the WIR 2011.Jamaica Promotions Corporation (JAMPRO) president
explained that this was due to the financial crisis and the fall of FDI inflows into SIDS.
There is significant deterioration (86%) of FDI when compared to the record inflow of
US$1.4 in 2008 which occurred before the global recession.
Jamaica’s performance in the Caribbean was infamous, which dropped by 26% each year to
US$48 billion. The largest recipients of FDI in the Caribbean were Cayman Islands,
Dominican Republic and The Virgin Island. This was mainly because of investments in the
financial services sector.
Among the Caribbean countries which recorded increases in FDI were Haiti
(321%,US$150 million), Cuba (260%, US$86 million), Aruba (120%, US$161 million),
Bahamas (48%, US$872 million), St Kitts and Nevis (40 %, US$134 million), Netherland
Antilles (17.9%, US$138 million).

31
The Bahamas was the leading recipient of FDI inflows in SIDS with US$1.533 billion in
2011, as reported by a UN body and even though with this breakthrough, it was pointed out
that they needed ‘a bit more’2
to pull back their economy.
Bahamas’ 2011 FDI which was a 34.2% year-over-year increase from 2012’s US$1.142
billion, was due to the project ‘Baha Mar Cable Beach’ redevelopment which accounted for
US$2.6 billion. The factor that mainly impeded Bahamas’ economy to turn their economy
around was the lack of ‘greenfield’ FDI3
. The total amount of these investments received
between 2006 and 2011 only totalled to US$86 million. Bahamas’ economy is heavily
dependent of FDI to boost its growth rate. The recession in 2008 and 2009 had an adverse
effect on their GDP growth as FDI inflows dried up.
According to the WIR 2011, Mauritius witnessed its highest ever flow of FDI in 2010. The
inflows amounted to a stunning US$430 million and outflows US$129 million which
classified the island as a vital FDI recipient along with being a source for outward
investment. The inward investments made up for 19.1% of Gross Fixed Capital Formation
and the total FDI stock was estimated around US$2,319 million. Furthermore, The
UNCTAD FDI Attraction Index 2011, which classifies countries according to FDI received
relative to their size, placed Mauritius in the Top 5 SIDS which were said to be in line with
expectations. The economy had the second largest amount of Greenfield investment
received among the SIDS and this was due to the investments of Atterbury Property
Developments (South Africa). Nonetheless, Mauritius is still on its way to recovery after
the financial crisis and is still fragile.
3.6 Conclusion
Forecasts for FDI were mixed. Due to strong fiscal policies, FDI to tax haven states fell
while other countries benefited from more FDI due to investment in the mining sector. Due
to SIDS disadvantage of being small, it is very probable that FDI varies extensively with
only a big FDI transaction. Nevertheless, the fact that post-crisis effects still linger in the
business environment, the future is still fraught with uncertainties. Risk factors such as the
2
Criticism from a senior private sector official (2011)
3
Greenfield investments amounted to only US$2 million in 2011

32
fickleness of international economic governance, the possibility of worldwide debt crisis
and signs of rising inflation in emerging markets may deter the FDI recovery.

Chapter 4: Methodology
33
4.1 Introduction
In this chapter we will be taking into consideration the econometric part of our research.
The various tests that we are going to perform are thoroughly examined. We will be using a
balanced panel model for the analysis of the 24 countries forming part of the SIDS. The
variable and country selection is based on the availability of data used in our study.
4.2 Hypotheses
Since our purpose is to see whether FDI affects economic growth in SIDS, we would test
the following hypothesis:
H1: Whether FDI is responsible for economic growth in SIDS
H2: Is there any relationship between the selected variables and economic growth in SIDS.
H3: Is there any relationship between the selected variables and economic growth in
Mauritius.
4.3 Model
The functional form of the model we will be using in our study is written as follows:
GDP Growth =f (FDI, GCF, TRAO, INFLA, INFRAS)
Where the variables we will be using are defined below.
4.3.1 GDP
GDP is defined as the total value of goods and services produced in an economy for a
particular period. GDP is one of the major determinants of economic growth. This
relationship can be explained through the income convergence hypothesis. The latter states
that countries with comparatively low levels of GDP per capita have experienced faster
growth than countries with comparatively high levels.

34
4.3.2 FDI
The role of foreign direct investment has recently been a very important one to the internal
economic activity through its ability of technology transmission and economic growth. This
key ability is detailed in many models of the new growth theory. Empirical literature
focusing on the impact of FDI on economic growth has more-or-less found a significant
positive relationship between them (e.g. Borensztein et al., 1998; Hermes and Lensink,
2000; Lensink and Morrissey, 2006).
4.3.3 GCF
In national accounts, GCF is measured as any supplement to fixed assets, changes in
inventories and acquisitions less disposal of valuables. Theoretically, the gross capital
formation affects the economic growth either increasing the physical capital stock in
domestic economy directly, Plossner (1992) or promoting the technology indirectly, Levine
and Renelt (1992).
4.3.4 Trade openness
Another key factor determining growth is trade openness. This factor has been widely
utilised in the economic literature. Openness influences growth via various channels such
as comparative advantage exploitation, technology transmission and knowledge diffusion,
leading to economies of scale and involvement in competition. Furthermore, a significant
share of the literature has proved that economies which are more open to trade have higher
economic growth (Petrakos et al., 2007).
4.3.5 Inflation
Inflation is an indicator of growth stability and prospect. High inflation rate is indicative of
instability and volatility and thus diminishes the level of investment and growth. It may
also lead to a decrease in international competiveness by making exports more expensive.
On the other hand, low inflation being a stability index, decreased systematic risk and
stimulates investment, trade and economic growth.

35
4.3.6 Infrastructure
Infrastructure is the capital stock that provides public goods and services. In the economic
writings, numerous channels throughout which infrastructure might have an impact on
aggregate GDP levels and growth have been identified. The studies find a positive
relationship between these two by adding infrastructure to the right-hand side of reduced-
form models (Barro and Sala-i-Martin. 1995).
Table 4.1: Variable’s specification and expected sign
Variable Specification of variable Expected sign
GDP Economic Growth; measured
as GDP growth (annual %)
Nil
FDI FDI Inflows; measured as a
% of GDP
+/-
GCF GCF, calculated in
percentage; as a percentage
of GDP
+
TRAO Trade openness; an index
calculated by the sum of
import and export, divided
by GDP
+
INFLA Inflation, measured in annual
percentage change
-
INFRAS Infrastructure in host
countries; measured by
number of telephone lines
per 100 persons
+
Source: Author’s Compilation
4.4 Data Sources
For our panel data analysis, we will be considering 24 SIDS out of 52 for the time period
1980-2010 due to unavailability of data. For the time series analysis for Mauritius we will
consider the same time period and variables. Table 4.2 below shows the data sources for
the variables we will be using.

36
Table 4.2: Sources of data
Variables Source for Panel/time series analysis
GDP World Bank
FDI World Bank
GCF World Bank
INFLA World Bank
INFRAS World Bank
TRAO World Bank
4.5 Panel data approach
A panel data, also known as longitudinal data, is a data set following an arranged sample of
individuals over time, and hence offer multiple explanations on each individual in the
sample (Hsiao 2003). Consequently, explanations in panel data involve at least two
dimensions; a cross sectional dimension, designated by the subscript i, and a time series
dimension, designated by the subscript t.
A general panel data regression model is written as:
yit= α+βxit+uit (1)
The use of panel data is valued due to the multiple advantages it offers and these are listed
as follows:
1. It controls individual heterogeneity.
2. It contains more degrees of freedom and sample variability compared time series
data or cross sectional data.
3. It has greater ability for seizing the complexity of human behaviour than a single
cross section or time series data.
4. Unobserved or mismeasured variables are controlled in panel data.

37
5. Panel data has the ability to observe effects that cannot be recognised through the
use of cross sectional or time series data.
6. Complex behavioural models are easier to construct and test on panel data than on
purely cross sectional or time series data.
4.5.1 Fixed Effect Model
Fixed Effect Model (FEM), commonly referred as the Least Square Dummy Variable
(LSDV) approach, controls for or partial out the influences of time invariant variables with
the time invariant effects. The subjects that the measurements are drawn from are assumed
to be fixed and thus the disparities between them are of any interest. The variances within
each subject can be seen as an indiscriminate mass, assuming that the subjects and their
variables are identical.
The FEM approach splits up the disturbance term, uit of equation (1), taking the form
below:
Uit= µi + vit (2)
Uit’s decomposition reflects µi capturing the individual effect that is constant over the time
and vit capturing the effects varying over time. FEM assumes a correlation between the
individual effect and the independent variables.
Thus the equation (2) can be substituted in the equation (1), taking the form below:
yit= α+βxit+µi + vit (3)
Therefore, the LSDV would be written as follows:
Yit = xit + µ1D1i+µ2D2i +µ3D3i+...+µNDNi+ vit (4)
Where,

38
D1 is the dummy for country 1; it takes the value 1 for country 1 and 0 otherwise. D2 is the
dummy for country 2; it takes the value 1 for country 2 and 0 otherwise. Dummy variables
are binary, that is, they take either the value 1 or 0. It must be noted that too many dummy
variables in an equation can lead to the ‘dummy trap’ problem.
Though, since it is complex to make an estimation of all the dummy variables, a
transformation known as within transformation is carried out.
̅ = ∑ (5)
Equation (5) illustrates how to calculate the time-mean of y. This calculation is performed
for all other variables. Then we take equation (4) minus the time means of our variables
that we have calculated previously. We will thus get equation (6) which is written below:
(yit - ̅i) = β (xit - ̅i) + (uit– ̅i) (6)
Now we demean the variables of equation (6), which takes the form below:
̃it= β̃it + ̃it (7)
Equation (7) is projected using pooled OLS on the demeaned data.
4.5.2 Random Effect Model
On the other hand, the Random Effect Model (REM), commonly referred as the errors
component model, assumes that the measurements are from a random sample drawn from a
larger population, and thus the variance among them is interesting and can reveal much
about the larger population. It regards the common intercept α in a different way since it
procures for one as cross sectional, vit and the other one as times series variable, єi.
The general form for the REM can take the following form:
Uit = єi+ vit (2)

39
We then replace equation (2) in equation (1) which gives us equation (3):
Yit= α + βxit + єi+vit (3)
No correlation is assumed to be found between the independent variables. θ is the function
of the variance that is constant over time.
1 –
√
(4)
Thereafter, we make use of the quasi-demeaned data for y and x shown below respectively
by equation (5) and (6).
= yit - θ̅i (5)
= xit - θ ̅i (6)
Substituting equation (5) and (6) in equation (1), we come to the final equation, shown
below:
= α + β + (7)
4.5.3 Fixed or Random Effect
In order to decide which model to adopt, we should perform the Hausman specification test
(HST). It tests for the following hypothesis:
H0: REM is ideal
H1: FEM is ideal
If the p value given by the HST is less than 0.05, the null hypothesis H0is rejected.
Thereafter, the Breusch-Pagan (BP-LM) test is conducted to decide whether to go for the
REM or a simple OLS model. Thus the BP-LM test looks at the following hypotheses:

40
H0: OLS is ideal
H1: REM is ideal
If the p value given is less than 0.05 for the BP-LM test, the null hypothesis is rejected.
Thus if the result of the HST show that REM is appropriate, and the BP-LM test also show
that the REM is appropriate, then we are sure that we can opt for that model as the two tests
confirm our hypotheses.
4.6 Model Specification for panel
GDPit = α + β1 FDIit + β2 GCFit + β3 TRAOit + β4INFLAit+β5INFRASit + εit
The linear model we are going to used has been conditioned into a panel one where i
represents the number of countries and t represents the year.
4.7 Empirical procedure
Firstly we set our statistical software to specify that we will be operating with panel data.
After having conducted the regression under OLS, we perform regressions for the FEM and
REM while saving the results after each test. The HST is then carried out so as to decide
which model is the most suitable for our study. If the HST shows that the REM is to be
used, we further perform the BP-LM test so as to confirm that REM is the most suitable
model. On the contrary, if FEM comes up, we move forward to conducting robustness with
the regression. If that is not the case i.e. REM is significant, we move on to testing serial
correlation and heteroscedasticity in the regression for both REM and FEM. The above
mentioned econometric steps are carried out for SIDS-24.
4.8 Conclusion
Having scrutinised the steps we are going to use for the econometrics framework for SIDS,
we will proceed to the tests mentioned and interpret the results obtained in the next chapter.

Chapter 5: Interpretation of results
41
5.1 Introduction
Based on the econometric model that has been used in this research, this chapter will
analyse the results obtained from the various tests carried out. Our main concern with the
results is whether the independent variables (FDI,GCF, INFLA, INFRAS, TRAO) used in
this model have any effect over the dependent one (GDP growth per capita) in SIDS.
5.2 Empirical results for SIDS
In order to determine which model is more appropriate for our study (FEM or REM), the
HST is carried out. To back up our result, i.e. REM is to be used, the BP-LM test is also
performed and the results are shown in table 5.3below.Table 5.1 and 5.2 show respectively
the statistical summary of the variables and also the correlation matrix using data averaged
over the years 1980-2010.
Table 5.1: Summary statistics
Variable Mean Standard
Deviation
Min Max
GDP 1.895014 4.947475 -29.48342 21.79444
FDI 5.636275 6.032364 -2.325623 39.80923
GCF 24.74837 10.65471 0 58.11789
INFLA 6.4993 9.464279 -11.44946 80.78814
INFRAS 14.27848 13.88463 0 55.11059
TRAO 112.7632 66.09601 0 460.4711
Source: Authors’ Computation
From the table above it can be observed that there is significant cross-country variation. For
example, the mean per annual growth rate for the sample is 1.9% per annum, with standard
deviation of 4.9. The highest growth rate was experienced by St. Lucia (21.8), while the
worst GDP growth was experienced by Guinea-Bissau (-29.5). The data also points out
considerable variations in FDI inflows and the other explanatory variables.

42
Table 5.2: CORRELATION MATRIX
GDP FDI GCF INFLA INFRAS TRAO
Growth
GDP 1
Growth
FDI 0.1961 1
GCF 0.2316 0.3301 1
INFLA -0.1433 -0.1940 -0.0366 1
INFRAS 0.0915 0.4622 0.2442 -0.2694 1
TRAO 0.2054 0.3856 0.3460 -0.1670 0.4139 1
Source: Authors’ computation
The correlation matrix shown in table 5.1 shows a positive relationship between FDI and
economic growth. In line with our expectations, GCF is also positively related to economic
growth and so is infrastructure and trade openness. As forecasted, inflation is negatively
correlated to economic growth. According to the matrix, there is no serious multicolinearity
issue in the data.
Table 5.3: HST and BP-LM test
Hausman Specification test (HST)
Chi 2
Prob> Chi 2
Model to use
2.46 0.7826 Random Effect model (REM)
Breusch-Pagan Lagrange Multiplier test (BP-LM test)

43
Chi 2
Prob> Chi 2
Model to use
14.58 0.0001 Random Effect model (REM)
According to the results after HST, i.e. p-value of HST is greater than 0.05, it indicates that
REM should be employed. Similarly, the BP-LM test, whose p-value is less than 0.05
confirms the diagnostic of the HST, rejects the null hypothesis and confirms the presence
of the REM. The result of REM is shown in table 5.4.
Table 5.4: REM results
Dependent Variable: Economic Growth (GDP Growth %)
Independent Variables Random Effect model
(REM)
Expected Signs
FDI 0.0863521
(0.013) **
(+;-)
GCF 0.0757037
(0.000)*
(+)
INFLA -0.0637354
(0.001)*
(-)
INFRAS -0.0267293
(0.086)***
(+;-)
TRAO 0.008721
(0.004)*
(+)
Constant -0.6569464
(0.218)
R2
Within R2
0.0939
Between R2
0.1626
Overall R2
0.0945
Number of observations 742

44
Source: Authors’ computation
Note: (p-value) is in parentheses
* Significant at 1% level
** Significant at 5% level
*** Significant at 10% level
The three R2
values obtained from our regressions, namely within R2
, between R2
and
overall R2
are very meaningful. Within R2
indicates that 9.39% of variation in GDP growth
per capita is explained by the independent variables for all the 24 countries while between
R2
indicates a 16.26% variation for a single country. Overall R2
shows that 9.45% variation
in GDP growth per capita is explained by the independent variables in our model.
As expected, the variable FDI is both positive and statistically significant at 5%. One
percent increase in FDI leads to a0.086% increase in GDP growth per capita. According to
its coefficient, FDI happens to influence GDP as a diffuser of technology which helps to
contribute to economic growth in the long-run in the form of technological progress. This is
in line with the literature by De Mello (1999) who states that growth is achieved through
capital accumulation and (Borensztein et al. 1998) who concludes that FDI promotes
economic growth through adoption of new equipment and ideas.
GCF is statistically significant and positive at 1%. A rise in one percent in GCF leads to a
rise of 0.076% in GDP. This is explained by the fact that the governments in the host
countries are willing to provide and further develop amenities that will facilitate the task of
investors and therefore become more attractive to capital. High level of capital formation
leads to an increase in employment which results in higher savings, therefore increasing
confidence in the economy and ultimately be prone to economic growth. Kormendi &
Meguire (1985), Barro (1991), Levine and Renalt (1992) are all supportive of the fact that
the rate of capital formation determines the rate of economic growth.

45
Inflation which has an adverse effect on GDP growth per capita turns out to be significant
with a negative coefficient. Inflation does not favour rapid economic growth. High inflation
means a rise in the level of prices but not in higher levels of income in the long run. The
negative correlation is due to the other factors that have been added to the analysis.
Inflation reduces level of investment and efficiency of productive factors. Inflation is
significant at 1% level in our case, where a one percent rise in inflation would lead to
0.06% fall in growth.
Infrastructure in our case is marginally significant at 10% with a negative coefficient. This
means that infrastructure inversely influences economic growth in the case of SIDS. The
reason behind this is that SIDS offer very poor quality infrastructure and investors do not
only want infrastructure but well developed infrastructures. Another reason behind the
insignificance of infrastructure is that investors bring their own related infrastructure and
technologies to carry out their projects and only use the minimum infrastructure available
in SIDS to meet their objectives. Thus, when their goal has been achieved, infrastructure
quality remains the same or worst, deteriorate.
The result for trade openness is that it is both positive and significant at 1% level and
therefore staying in line with existing literature. A one percent increase in trade openness
lead to 0.009% increase in GDP growth per capita. Acemoglu and Zilibotti (1997) and
Zhang (2001), state that trade openness is primordial as it helps in the transmission of
capital from rich countries to developing countries such as SIDS and leads to an increase in
efficiency and economic growth.
In order to ensure more reliable results and to remain in line with econometric norms, we
have performed tests for autocorrelation and heteroscedasticity. Since we have found that
there is no autocorrelation, we have shifted to heteroscedasticity using the following
assumptions:
H0: Have heteroscedasticity
H1: Do not have heteroscedasticity (Homoscedasticity)

46
Table 5.5: Heteroscedasticity test
Heteroscedasticity test
Chi2 Prob> Chi2 Implication
77.51 0.0000 Reject H0; there is no
heteroscedasticity
According to the p-value, which is less than 0.05, we reject the null hypothesis and find
that there is no presence of heteroscedasticity in our panel for SIDS.
5.3 Conclusion
In this chapter we have found results from our tests performed for SIDS. The econometrics
results are mixed, mostly favourable, where all the variables used to assess economic
growth in SIDS are significant which means they have a major influence on economic
growth. However, it is necessary for the government in these economies to maintain and
improve their policies regarding FDI so as to be internationally competitive.
We will now move to the next section of our study where we will focus on the role of FDI
towards economic growth in Mauritius, using the time series and ARDL-ECM approach.

Chapter 6: FDI and economic growth in Mauritius
47
6.1 Introduction
After having analysed the major literatures on FDI and economic growth and their
relevance in SIDS, it is ignorant not to shed light of the impact of FDI and the key variables
(GCF, trade openness, inflation and infrastructure) on Mauritius. In this particular case,
sectorial inflows will be analysed along with major countries pouring in FDI in Mauritius.
A time series procedure will be carried out separately, including the ARDL-ECM approach
so as to scrutinise whether or not FDI is conducive to growth in Mauritius.
6.2 FDI inflows in Mauritius
Figure 6.1: FDI inflows in Mauritius, with trend (US$ million)
The table above shows the inflows of FDI for Mauritius covering a period of 20 years from
1980 to 2010. From the year 1980 to 1990, the FDI inflows have been constantly increasing
due to the establishment of the EPZ in Mauritius as well as the good evolution of the
tourism sector (where FDI in 1980 stood at US$1.17 million in 1980 compared to 1990
-100
0
100
200
300
400
500
FDI
inflows
Years
FDI inflows (US$ million)
FDI inflows
Linear (FDI inflows)

48
where it reached US$41.04 million). From 1990 to 1995, the flows of FDI has dropped
(from US$41.04 to US$18.96 million), due to the fall in productivity of the manufacturing
sector over that period. The situation was reversed since inflows peaked following the fall
in 1991 reaching to US$265.5 million in 2000 (third highest point). After the financial
crisis around year 2000, inflows to Mauritius have been dramatically decreasing. After
2001, FDI have been increasing significantly up to 2008 where it stood at US$377.72
million, the second highest amount of FDI received, but falling to US$256.68 million, fall
attributed to Euro Zone crisis, but FDI peaked to reach the highest point in 2010 where it
stood at US$429.95 million.
6.2.1 FDI inflows by sectors
The inflows of FDI by sectors in the Mauritian economy have been classified in the table
below, covering a period of six years, from 2006 to 2011.
Table 6.1: FDI inflows by sectors
(Rs million)
Sector Description 2006 2007 2008 2009 2010 2011
A Agriculture, forestry and
fishing
26 18 447 - - 177
C Manufacturing 181 271 149 485 63 54
D Electricity, gas, steam
and air conditioning
supply
17 - - - 2 1
F Construction 12 45 68 211 1,292 2,094
G Wholesale and retail
trade; repair of motor
vehicles and motorcycles
198 38 103 291 125 21
H Transportation and
storage
13 - 14 10 110 4

49
I Accommodation and
food service activities
1,382 3,189 1,348 1,850 836 579
J Information and
communication
43 18 8 - 235 76
K Financial and insurance
activities
3,593 4,056 4,564 1,371 4,645 1,646
L Real estate activities 1,701 3,820 4,525 4,305 3,422 4,580
of which -
IRS/RES/IHS
1,228 2,791 2,637 2,074 2,033 3,352
M Professional, scientific
and technical activities
- - - - 404 217
P Education 55 30 74 125 18 4
Q Human health and social
work activities
2 29 120 145 2,732 -
R Arts, entertainment and
recreation
- - - - 62 3
Total 7,222 11,514 11,419 8,793 13,948 9,456
Source: Author’s compilation from Bank of Mauritius
Among all the sectors in Mauritius, the construction, financial services and the Real estate
activities sectors have been the major beneficiaries of FDI reaching Rs.2094 million,
Rs.1646 million and Rs.4580 million in the year 2011. The construction sector has been
experiencing increasing inflows of FDI for the six consecutive years, accounting for 22.1 %
of total FDI inflows in Mauritius. This was mainly due to the rise in the construction and
renovation of hotels, Integrated Resort Scheme (IRS) projects and the expansion of the
clothing and textile industries. Moreover, investment in the construction sector was also
encouraged by the tax suspension program for the sector. The financial services sector,
accounting for 17.1 % of total FDI inflows was the consequence of the financial
globalisation and financial sector development in Mauritius. In order to reap the benefits
from globalisation, Mauritius, as a SIDS has no alternative apart from developing its

50
financial architecture, attracting huge amount of FDI. Among all the sectors, the real estate
sector has been the major beneficiary of the inflows of FDI for 2011, accounting for 47.9 %
of the total inflows. This was all due to the IRS program offering a lot of incentives,
attractive huge investment from abroad, accounting for 72.2% of total inflow to the sector.
6.2.2 FDI inflows by country
The table below represents the FDI inflows in Mauritius from selected country of origin
from 1990 to 2010.
Table 6.2: FDI inflows by country
1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Total 609 325 7265 936 979 1966 1796 2807 7222 11514 11419 8793 13948
Of which:
China 17 - - - 18 33 - 6 6 - 78 348 280
France 75 17 7214 25 232 157 492 427 523 1176 1167 2333 1598
Hong Kong 55 19 9 4 7 30 18 8 24
India 78 157 2 143 150 670 160 610 1921 320 2887
South
Africa
2 1 600 333 1022 19 26 38 498 1415 510 1468
Switzerland 45 12 5 274 2 42 148 584 1287 606 448 590
UK 8 29 157 172 143 578 3821 2802 2044 1493 4632
USA 114 3 3 29 37 518 75 163 2380 1063 677 132
Memo
item: China
as a % of
total
2.80% 1.80% 1.70% 0.20% 0.08% 0.70% 4.00% 2.00%
Despite the fact that the world along with the traditional investors of Mauritius were
experiencing the effects of the Euro Zone crisis, Mauritius was still able to record its
highest amount of FDI inflows reaching Rs.13948 million in 2010. This was due to the
established reforms implemented since 2006, supported by stimulus packages and an
Economic Restructuring and Competitiveness program started by the government in 2009-

51
2010. Among the major countries investing in Mauritius, France, South Africa and UK
represent 73.3% of total FDI inflows. However, compared to 2010, in 2009, the major
countries investing in Mauritius were France, India, South Africa, Switzerland and UK,
representing 80.1% of total FDI inflows, showing that Mauritius was moving from its
reliance on its trading partners towards emerging economies.
6.3 Overview of FDI and Economic Growth in Mauritius
Mauritius, a small state in the Indian Ocean, has observed an incredible progress over the
past 30 years. The steering force of Mauritius’ progress has been its export sectors,
specifically the sugar sector, tourism and the Export Processing Zone (EPZ). The dynamic
financial sector has moreover been critical to economic growth. These sectors have all
benefited from both internal and external investments over their development years.
It is merely from the mid-1980s that Mauritius started benefiting from FDI considerably,
generally in the EPZ and in tourism. In fact, the percentage of FDI to gross domestic
investment (GDI) stayed quite low across the 1980s, denoting 6% of GDI in its highest
year, 1989 as shown in figure 6.2. UNCTAD (2001) stated that FDI in Mauritius was
effective in enabling native financiers to buy and integrate technologies and know-how and
develop internal firms in the EPZ and the tourism sector.

52
Figure 6.2: FDI and GDI in Mauritius, 1980-2000
Source: Bank of Mauritius (2000)
The presence of preferential trading agreements allowing free entrance to EU and US
markets and old historical ties with Asia and Europe became the key factors for the success
of Mauritius in attracting FDI. Some Mauritian analysts recommended that the large
percentage of private internal investment in the principal economic sectors added to the
economic progress of the island (Hein, 1989; Assidon, 1990; Dommen and Dommen, 1999;
Blin, 2004).
While the government of Mauritius seems to be open to FDI, in practice, it indirectly
welcomes specific sectors such as manufacturing, hotel development, Information
Technology (IT) management, financial and business services.
The shortage of strategic focus in FDI encouragements has been generating more expenses
than benefits. Wignaria (2001) points out that the allocation of resources for the promotion
of FDI is too restricted and encouragements for technological upgrading, local linkages and
research and development are limited. Nevertheless, in 2000 the Board of Investment was
set up for the facilitation of internal and external investment and furthermore to increase the
efficiency of Mauritius’ investment policy. The question remains whether FDI in Mauritius

Foreign Direct Investment and economic growth in small island developing states- A panel data analysis.

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