Download Table 4: Augmented Dickey-Fuller Unit Root Test

The Effect of Trade Openness on Economic
Growth: The Albanian case
By
Dionis Seni, MSc
Thesis submitted for the degree of Master of Science
Department of Banking and Finance
Epoka University
July 2015
Approval Page
Thesis Title
:
The Effect of Trade Openness on Economic Growth: The
Albanian case
Author
:
Dionis Seni, B.A.
Qualification
:
MSc. Degree
Program
:
Banking and Finance
Department
:
Banking and Finance
Faculty
:
Economics and Administrative Sciences
Thesis Date
:
July 2015
I certify that this thesis satisfies all the legal requirements as a thesis for the degree of MSc.
Assist. Prof. Dr. Urmat RYSKULOV
Head of Department
I certify that I have read this study that is fully adequate, in scope and quality, as a thesis for the
degree of MSc.
Assist. Prof. Dr. Urmat RYSKULOV
Supervisor
i
Exam Board of Thesis
Thesis Title
:
The Effect of Trade Openness on Economic Growth:
Albanian case
Author
:
Dionis Seni. B.A.
Qualification
:
Degree of MSc
Date
:
July 2015
Members
Prof. Dr. Abdylmenaf SEJDINI
……………………….
Assist. Prof. Dr. Urmat RYSKULOV
……………………….
Assist. Prof. Dr. Eglantina HYSA
……………………….
ii
Abstract
The main purpose of this study is to evaluate and determine the effects of trade
liberalization on the economic growth in Albania. The factors included in this project are,
Foreign Direct Investment (FDI), Exchange Rate (ER), and Trade openness. Trade openness was
computed as the ratio of total of imports and exports to total exports. The methodology
comprises the use of the above mentioned macroeconomics indicators data which are all
gathered by official institution database for an interval time of ten years measured in quarterly
bases. Secondly, the Johansen co-integration method is implemented in order to understand the
impact and relationship of trade openness with economic growth (GDP). Finally based on the
result of the analysis the trade openness and the factors deriving from it have positive impact on
economic growth.
Key words: trade openness, economic growth, gross domestic product, foreign direct
investment, exchange rate
iii
Abstract
Qëllimi kryesor i këtij studimi është të masim dhe të përcaktojmë efektet e liberalizimit të
tregut në rritjen ekonomike të Shqipërisë. Faktorët e përfshirë në këtë projekt janë: Investimet e
huaja direkte (FDI), kursi i këmbimit (ER) dhe tregu i hapur. Tregu i hapur është përllogaritur si
raporti i totalit të importeve dhe exporteve me totalin e eksporteve. Metodologjia përmban
përdorimin e të dhënave të indikatorëve makroekonomik të sipërpërmendur, të dhënat e të cilëve
janë mbledhur nga databaza zyrtare për një interval kohor dhjetë vjecar të matura në baza tre
mujore. Së dyti do të implementohet metoda e bashkë-integrimit të Johansen për të kuptuar
impaktin dhe marrëdhënien e tregut të lirë me rritjen ekonomike (GDP). Së fundmi bazuar në
rezultatet nga të gjitha modelet statistikore, është treguar që tregu i lirë dhe faktorët që derivojnë
prej tij kanë një impakt pozitiv në rritjen ekonomike.
Fjalët kyçe: tregu i lirë, rritja ekonomike, produkti i përgjithshëm bruto, investimet
direkte të huaja, kursi i këmbimit
iv
Dedication
I dedicate this thesis to my loving parents for being with me on each and every step of my
life with their unconditional love and endless support and encouragement. They always motivate
me to set higher targets and to gear up and reach them.
This thesis is also dedicated to my little brother Ardit whose love and support gave me
forces to make this work.
v
Acknowledgements
Primarily and especially I want to thank my family that had been supported me morally
and economically all these years that I was studying.
Also other important thanks go to all the FEAS professors, about the commitment and
reliability that have shown for the last five years.
And lastly, but not less important, I give a lot of thanks to my supervisor Assist. Prof. Dr.
Urmat Ryskulov , for his support, help and the time that he dedicated to me.
vi
Declaration Statement
1. The material included in this thesis has not been submitted wholly or in part for any academic
award or qualification other than that for which it is now submitted.
2. The program of advanced study of which this thesis is part has consisted of:
i) Research Methods course during the undergraduate study
ii) Examination of several thesis guides of particular universities both in Albania and abroad as
well as a professional book on this subject.
Dionis Seni
July 2015
vii
Table of Contents
Approval Page ........................................................................................................... i
Exam Board of Thesis .............................................................................................. ii
Dedication ................................................................................................................ v
Acknowledgements ................................................................................................. vi
Declaration Statement ............................................................................................ vii
List of Tables .......................................................................................................... ix
List of Graph ............................................................................................................ x
List of Abbreviations .............................................................................................. xi
List of Appendices ................................................................................................. xii
Introduction .............................................................................................................. 1
Chapter One: Literature Review .............................................................................. 3
Chapter Two: International Trade and Openness .................................................. 10
2.1 The Importance of Trade ........................................................................................ 10
2.2. International Trade .......................................................................................... 11
Chapter Three: Data, Methodology and Analysis.................................................. 13
3.1 Data Description ..................................................................................................... 13
3.2 Methodology ........................................................................................................... 15
3.3 Analysis and results ................................................................................................ 16
Conclusion ............................................................................................................. 33
References .............................................................................................................. 34
Appendices ............................................................................................................. 36
viii
List of Tables
Table 1: Descriptive statistics of all variables .................................................................. 21
Table 2: Estimated equation output .................................................................................. 22
Table 3: Augmented Dickey-Fuller Unit Root Test on GDP ........................................... 23
Table 4: Augmented Dickey-Fuller Unit Root Test on FDI ............................................. 23
Table 5: D (FDI) Augmented Dickey-Fuller .................................................................... 24
Table 6.Augmented Dickey-Fuller Unit Root Test on IMP/EXP ..................................... 25
Table 7.D (IMP/EXP) Augmented Dickey-Fuller test statistic ........................................ 26
Table 8.D (IMP/EXP) Second difference ......................................................................... 26
Table 9.Augmented Dickey-Fuller Unit Root Test on EU/ALL ...................................... 27
Table 10.Augmented Dickey-Fuller Unit Root Test on D (EU/ALL) .............................. 28
Table 11.Johansen co-integration test among all variables: ............................................. 29
Table 12.Johansen co-integration test between GDP and FDI ......................................... 31
ix
List of Graph
Graph 1: GDP and FDI .................................................................................................... 17
Graph 2: Scatter plot for GDP and FDI ............................................................................ 17
Graph 3: GDP, Exchange rate, Ex/Im Ratio, FDI............................................................. 18
Graph 4: GDP Histogram.................................................................................................. 18
Graph 5: Exchange rate histogram .................................................................................... 19
Graph 6: FDI Histogram ................................................................................................... 19
Graph 7: Export/Import Histogram ................................................................................... 20
Graph 8: Normal distribution for GDP ............................................................................. 20
x
List of Abbreviations
GDP: Gross Domestic Product
FDI: Foreign Direct Investment
ER: Exchange Rate
BoA: Bank of Albania
WB: World Bank
NX: Net Export
INSTAT: Instituti i Statistikave
ISI: Import Substitution Industrialization
R&D: Research & Development
OECD:
NTB: Non-Tariff Barriers
TFP: Total Factor Productivity
BPA: Bilateral Payments Arrangements
WTO: World Trade Organization
DDA: Doha Development Agenda
xi
List of Appendices
Appendixes of FDI, IMP/EXP, EU/ALL, GDP
xii
Introduction
The performance of the Albanian economy in the communist regime was in the worst and
unproductive conditions that the country’s economy has faced. In this period the economic
model was centralized and closed which mean that we couldn’t not export nor import any
resources, goods or innovative technology in order to increase the countries production and
efficiency in satisfying the needs for goods and services that were needed in other words we
were isolated and depending only in our own forces which as time and history has testimonies
left our country in the group of the undeveloped and poor countries. This situation start to change
when the period of the communist regime was over passed and left behind in 1990 time when
Albania changed philosophy in how to lead and direct the country. In this period in Albania was
establish the democracy and the free open trade economy, fact that lead to a very positive step
for the Albanian economy and to the entering to a new stage of evolution for Albanian economy
because Albania was now a developing country try to enter to a new phase of improving its
welfare and the wellbeing of the Albanian citizens. This short historical introduction was made
in order to make an overall picture and comparison of the changes that the Albanian economy
has faced during the transition period between two different ideological and economic models in
order to make it more easy to understand and clarify how trade openness and the advantages that
comes from it affect the growth economic GDP and how this factors reflects in the improving of
the overall macroeconomic indicators. In the time when open trade economy was implemented in
Albania the country was focused on growth enhancing policies including promotion of exports,
in this period a flow of the foreign investment was noticed in the economy whose trend was in a
rapid increase year by year, fact that was reflected in the increase of the GDP and in an overall
improving of the macro situation of the country.
The thesis comprised of three chapters. Where, the chapter one is dedicated to the
literature review on trade openness, in this section the thesis is concentrated in the opinion and
the research that different authors have made on how trade openness and the components
deriving from it affect the economic growth. This chapter attempts to give information on trade
openness and to create a better view of the impact that it has on enhancing growth in the short
run and long run.
1
The chapter two includes trade openness and the international trade as one of the
outcomes of openness in itself, this chapter is concentrated on trade in the international level as a
result from openness and how the economy of the countries applying it has enhanced by rapid
increase on growth due to the injection of money came from this result and the sharing of ideas
goods and service in an global market giving fruit to a collaboration of the nation’s economy.
This chapter reflects the positive sides of openness and it crucial outcome that is trade in a global
market without barriers or boundaries and the benefits of the economy especially growth on itself
has by this process.
The chapter three is dedicated for the data, methodology and the analysis. In this chapter
the analytic part takes place by first gathering the data’s to perform a regression analyses in order
to find proves that hold the fact that trade openness has a big impact on economic growth. After
the gathering of data from different reliable sources a model is constructed where the depended
variable is the economic growth expressed as the GDP and the undependable variables are trade
openness computed as a ratio of imports and exports and other factor that derive from openness
like Foreign Direct Investment FDI and the exchange rate. All this variables are processed in eview by the model that was explained and the results or outcomes are illustrated in this chapter
along with their respectful explanation.
Finally in this thesis it is aimed to explain the effect and the relationship that trade
economic openness has had on the growth economic of Albania this associated with all the other
factors that might have played a role in the improvement of the economic situation of the country
as GDP, FDI, Ratio (Imports, Exports) and Exchange Rate. All the factors mentioned above are
taken in consideration in my research through gathering all the data’s implied and associated
with this macroeconomic factors in a defined interval of time. After the processing of this data’s
through different application techniques and methods of econometric models were intended to
show the statistical evidence that support this thesis hypothesis that trade openness and the
factors deriving from this event has a significantly positive impact on economic growth and that
exist a strong relationship between this variables.
2
Chapter One: Literature Review
In spite of the wave of liberalizations faced in the last 30 years, the topic on the links and
causality between trade openness and growth and is still open (Rodriguez, 2001). The
relationship between trade openness and growth is a highly debated topic in the growth and
development literature. Theoretical growth studies suggest a complex and ambiguous
relationship between trade openness and growth. The growth literature has been diverse enough
to provide a different range of models in which trade openness can decrease or increase the
worldwide rate of growth (Romer, P.M., 1990). Note that if trading partners are asymmetric
countries in the sense that they have considerably different technologies and endowments, even
if economic integration raises the worldwide growth rate, it may adversely affect individual
countries (Grossman, G.M, Helpman, E, 1990). It is worthwhile to note that the theoretical
growth literature has given more attention to the relationship between trade policies and growth
rather than the relationship between trade volumes and growth. Therefore, the conclusion about
the relationship between trade barriers and growth cannot be directly applied to the effects of
changes in trade volumes on growth. Even though these two concepts, trade volumes and trade
restrictions, are very closely related, their relationship with growth may differ considerably. This
is because there are several other very important factors that affect a country’s external sector,
such as geographical factors, country size, and income.
In this section each measures of openness will be discussed. In the theory of international
trade, the static gains from trade and losses from trade restrictions have been examined
thoroughly. Yet, trade theory provides little guideline as to the effects of international trade on
growth and technical progress. On the contrary, the new trade theory makes it clear that the gains
from trade can arise from several fundamental sources: differences in comparative advantage and
economy-wide increasing returns. During most of the 20th century, import substitution
industrialization (ISI) strategies dominated most developing countries’ development strategies.
While developing countries that followed ISI strategies experienced relatively lower growth
rates, countries that employed export-promotion policies, consistently outperformed other
countries. This probably explains why a growing body of empirical and theoretical research has
shifted towards examining the relationship between trade liberalization and the economic
performance of countries. However, the most serious problem facing researchers today is the
3
lack of a clear definition of what is meant by ‘‘trade liberalization’’ or ‘‘openness’’. Over time,
the definition of openness has evolved considerably from one extreme to another. Even today it
is not unambiguous as to what describes ‘‘openness’’. On the one hand, (Krueger, A.O, 1978)
discussed how trade liberalization can be achieved by employing policies that lower the biases
against the export sector.
It is even more striking that according to her definition one country can have an open
economy by employing a favorable exchange rate policy towards its export sector and at the
same time can use trade barriers to protect its importing sector. This is best described in (1978, p.
78) that regime could be fully liberalized and yet employ high tariffs in order to encourage
import substitution.’’ On the other hand, (Harrison, A, 1996) stated that the concept of openness,
applied to trade policy, could be synonymous with the idea of neutrality. Neutrality means that
incentives are neutral between saving a unit of foreign exchange through import substitution and
earning a unit of foreign exchange through exports. Clearly, a highly export oriented economy
may not be neutral in this sense, particularly if it shifts incentives in favor of export production
through instruments such as export subsidies. It is also possible for a regime to be neutral on
average, and yet intervene in specific sectors. A good measure of trade policy would capture
differences between neutral, inward oriented, and export- promoting regimes. Recently, the
meaning of ‘‘openness’’ has become similar to the notion of ‘‘free trade’’, that is a trade system
where all trade distortions are eliminated. Therefore, it is crucial to understand this definition
problem because various openness measures have different theoretical implications for growth
and different linkages with growth. However, empirical studies are not usually clear on this issue
as (Edwards, 1993) stated, the literature on the subject has not always been successful in dealing
with precise definitions of trade regimes, nor has it been able to handle successfully the difficult
issue of measuring the type of trade orientation followed by a particular country.
A large number of empirical studies have made use of a variety of cross-country growth
regressions to test endogenous growth theory and the importance of trade policies. Probably due
to the difficulty in measuring openness, different researchers have used many different measures
to examine the effects of trade openness on economic growth. An ideal measure of a country’s
openness would be an index that includes all the barriers that distort international trade such as
average tariff rates and indices of non-tariff barriers. (Anderson, 1992) Have developed a ‘‘trade
4
restrictiveness index’’, which in principle incorporates the effects of both tariffs and non-tariff
barriers. However, it is not available for a large sample of countries. Thus, some studies have
used the available data to measure trade openness and some other researchers have constructed
indices that measure the openness of a country including (Leamer, 1988), (Dollar, 1992), and
(Sachs, 1995).
The existing openness measures are divided into five categories and review each category
separately in the rest of the section. First, the most basic measure of openness is the simple trade
shares, which is exports plus imports divided by GDP. A large number of studies used trade
shares in GDP and found, as reviewed in (Harrison, A, 1996), a positive and strong relationship
with growth. Furthermore, controlling for the endogenous of trade with the geographic variables,
(Frankel, 1999) and (Irwin, 2002) recently reported that comparing the fourth estimates of crosscountry regressions of income on trade and other factors with the OLS estimates indicated that
the OLS estimates understate the effects of trade on income. (Rodriguez, 2001) And (Irwin,
2002), however, showed that significant and higher for estimates of trade shares are not robust
the inclusion of geographical variables such as latitude and tropical climate. More importantly,
(Rodrik, 2002) reported that neither geographical variables nor trade shares hold their
significances when entered growth regressions with institutional quality variables measured by
the rule of law and property rights. In addition, export shares and import shares in GDP are also
used and enter positively in cross-country growth regressions.
Our results for these variables are consistent with these existing studies. Hence, we
believe that the inclusion of export and import shares in the growth regressions has been an
important step towards understanding of the relationship between international trade and growth
proposed by the new growth and new trade theories. Because, as discussed in (Edwards, 1993),
one of the distinct characteristics of earlier literature is that it put too much emphasis on exports.
From the standpoint of international trade theory, this view is hard to defend because, according
to theory of comparative advantage, international trade leads to a more efficient use of a
country’s resources through the import of goods and services that otherwise are too costly to
produce within the country. Thus, it is probably safe to conclude that imports are as important as
exports for economic performance. As a matter of fact, these two should be considered
complementary to each other rather than alternatives.
5
New growth theory has provided important insights into an understanding of the
relationship between trade and growth. For example, if growth is driven by R&D activities, then
trade provides access for a country to the advances of technological knowledge of its trade
partners. Further, trade allows producers to access bigger markets and encourages the
development of R&D through increasing returns to innovation. Especially, trade provides
developing countries with access to investment and intermediate goods that are vital to their
development processes.
Finally, if the engine of growth is the introduction of new products, then trade plays an
important role in growth by providing access to new products and inputs. Therefore, we may
well argue that developing countries can receive more benefit from trade with developed
countries, which are technologically innovative countries, than from trade with developing
countries, which are non-innovating countries. For this purpose, we use trade with OECD
countries, which are generally technologically innovative countries, and trade with non-OECD
countries to test this hypothesis. Our results do not provide support for this hypothesis since they
both enter the growth regressions positively and significantly. Nevertheless, one may argue that
not all OECD countries are technologically innovative. Densities have been used in the literature
as a measure of openness due to the belief that countries with higher densities are more likely to
be open and have more international contacts (Sachs, 1995). Consistent with earlier studies, the r
estimation results of the authors indicate that countries with higher densities tend to grow faster
than those with lower densities.
The second category includes measures of trade barriers that include average tariff rates,
export taxes, total taxes on international trade, and indices of non-tariff barriers (NTBs).
Needless to say, none of these measures of trade restrictions is free from measurement errors.
More importantly, if we focus on collected tariffs, defined as the ratio of tariff revenues to import
values, although these rates may be misleading because they tend to underestimate the actual
tariff rates, tariffs are one of the most direct indicators of trade restrictions. For example, (Rodrik
D. , 2000) documented the wide divergence between collected rates and official tariff rates. They
then argued that one natural implication of this is that the interpretation of protection provided by
tariffs is considerably difficult. Furthermore, they claimed that to use collected rates as the
‘‘effective’’ tariffs might even be more appropriate depending on the factors that cause the
6
divergence between these two rates. However, one should keep in mind that collected rates are
far from being ideal for capturing trade policy due to the little systematic relation between the
official rates and the collected rates. A number of studies have looked at the relationship between
average tariff rates and growth in the last several decades. They reported mixed empirical results.
For example, (Lee, 1993), (Harrison, A, 1996), and (Edwards S. , 1998) found a significant and
negative relationship between tariff rates and growth. However, (S, 1992), (Sala-i-Martin, 1997),
and (Clemens, 2001) concluded that this relationship is weak.
An important shortcoming of these studies is that the majority of the empirical literature
ignored the fact that there is no conclusive theoretical evidence on the growth effects of trade
restrictions. As a result, most of these studies hypothesized and tested that trade restrictions are
always detrimental for growth regardless of the countries’ development level and size. In their
critique of (Edwards S. , 1998) paper, (Rodriguez, 2001) also pointed out this problem. When
they tried to replicate his results using average tariffs from the World Bank, Rodriguez and
Rodrik actually found that average tariff rates had a positive and significant relationship with
total factor productivity (TFP) growth. Our results contradict the conventional view on the issue
and confirm that trade barriers in the form of tariffs can actually be beneficial for economic
growth. Note that although there exists a near consensus in the literature about the negative
growth effects of trade barriers for the Post-War era, a number of studies (such as (O’Rourke,
2000), (Clemens, 2001), (Irwin, 2002)) reported the positive correlation between tariffs and
growth for the late 19th and the early 20th century. (Clemens, 2001), argued that decline in
trading partners’ protection levels along with changes in partner growth and effective distance to
partners was the primary factor explaining for the reversal of the direction of the relationship
between growth and tariffs.
The growth effects of other forms of taxes on trade are largely ignored in the growth
literature. Thus, in this study export taxes and total taxes on international trade are also used to
measure trade restrictiveness of countries. Our estimation results for these variables with the
exception of fixed effect estimates that show a significant and positive association between trade
barriers and growth are similar to those for average tariffs. Moreover, due to data limitations,
empirical studies tend to ignore the effects of NTBs on growth even though NTBs have been
increasingly employed for the last several decades. However, (S, 1992) and (Edwards S. , 1998)
7
used NTBs as a measure of trade restrictions and reported an insignificant relationship with
growth. He concluded that NTBs are poor indicators of trade orientation because broad coverage
of NTBs does not necessarily mean a higher distortion level.
The third category includes bilateral payments arrangements (BPAs) as a measure of the
trade orientation of countries. A BPA is an agreement that describes the general method of
settlement of trade balances between two countries. Several studies such as (Trued, 1955),
(Triffin, 1976), and (Auguste, 1997) argued that BPAs could be considered important steps
towards more liberal trading and payments regimes since in the early years of the post-war era,
there were severe restrictions on international trade and payments. Thus, it is probably safe to
conclude that most countries have been using BPAs to expand or maintain export markets by
discriminatory trade policies. (Trued, 1955), provided examples of these discriminatory
practices. (Auguste, 1997), examined the effects of BPAs on economic welfare within the
context of customs union theory. He argued that under the assumption of the existence of
exchange rate misalignment and currency inconvertibility, BPAs can actually be welfare
improving, even though BPAs discriminate against non-member countries. This positive effect is
a result of the trade creation effect of the BPAs.
Fourth measure that uses exchange rates is movements in the real exchange rate.
Although it is hard to estimate the equilibrium real exchange rate level, a real depreciation can be
used to infer trade liberalization. Ceteris paribus, trade liberalization is expected to lower this
variable (see (Levine, 1992), (Andriamananjara, 1997).
Finally, we consider indices of trade orientation (such as (Leamer, 1988) openness index,
(Dollar, 1992) price distortion and variability index, and (Sachs, 1995) openness index) that are
constructed by some authors to test the effects of trade openness on growth. The basic claim of
these studies is that outward-oriented economies have consistently outperformed inward-oriented
economies. The need for these indices is partly due to the fact that most trade openness measures
are uncorrelated or weakly correlated with each other and no single measure of openness is
superior to the others. And also, as (Rodriguez, 2001) suggested, partly it is an attempt to deal
with the measurement error problem that is very common in this literature. These indices
received a great deal of attention from the economics profession and multinational institutions.
8
Rodriguez and Rodrik examined the recent empirical literature, including (Dollar, 1992), (Sachs,
1995), (Harrison, A, 1996), (Edwards S. , 1998), and (Frankel, 1999) that investigated the effects
of trade policies on growth and concluded that the empirical literature is mostly
‘‘uninformative’’ on the growth effects of trade policies. They also stated that there is a
significant gap between the message that the consumers of this literature derived and the ‘‘facts’’
that the literature has actually demonstrated. The gap emerges from a number of factors. In many
cases, the indicators of ‘‘openness’’ used by researchers are problematic as measures of trade
barriers or are highly correlated with other sources of poor economic performance. In other
cases, the empirical strategies used to ascertain the link between trade policy and growth has
serious shortcomings, the removal of which results in significantly weaker findings.
Consequently, the emerging conclusion from these studies is that these indices have crucial
shortcomings in measuring the trade orientation of countries. Hence, the relationship between a
number of openness measures and growth is not as robust as previously suggested. Thus, we will
not rely on these indices to measure the effects of trade policies. Rather, this study uses averages
of import and export taxes, total taxes on international trade, bilateral payments arrangements,
current account restrictions, and various measures of trade intensity ratios to measure the trade
openness of countries. Although these measures have their own problems, as discussed above,
they are much more direct measures of trade policies.
9
Chapter Two: International Trade and Openness
In this chapter the theses tries to give information about why trade matters that is one of
the primary outcomes of openness. The chapter explains how trade on itself promotes growth,
and act as intermediate in the process of sharing goods and service and thus increasing the
competitiveness. Furthermore the chapters give facts on how countries that have embraced
openness have had an increasing boost on growth.
2.1 The Importance of Trade
Trade promotes exploitation of economies of scale and specialization helps transfer
innovation, and improves consumer choice. The openness of markets to competition can provide
a powerful incentive for allocation of resources towards their most productive use. Overall, the
results can be tangibly measured in terms of economic growth, productivity, a higher standard of
living, further innovation, stronger institutions and infrastructure, and even promotion of peace.
Open economies grow faster than closed economies. The World Bank (OECD, 2010) has
reported that per capita real income grew more than three times faster for developing countries
that lowered trade barriers.
Productivity growth is at the heart of economic progress. Recent OECD analysis (OECD,
2003) highlights the benefits of openness and lower trade costs. At the sartorial level, trade
drives the reallocation of resources toward more productive firms, leading to their expansion and
the contraction or exit of relatively unproductive firms from the market. Studies of openness also
show that increased competitive pressures induce organizational change and production
upgrading, which in turn boost within-firm productivity.
In east developing countries, where virtually all countries have embraced outwardoriented development strategies, both trade and GDP have grown hand-in-hand. This impressive
performance was accompanied with equally impressive poverty reduction.
Imports play an important role in achieving this type of economic performance, in part
because they serve as an important channel for technology transfer. Openness to trade provides
access to a greater variety of imported capital goods and intermediate inputs that embody new
technology. More broadly, openness to imports and exports increases the effective size of the
markets for intermediate suppliers and final goods producers, raising the returns to innovation for
those engaged in production networks. The ability to market innovations globally makes it
10
possible to profit from greater specialization and to engage in research-intensive production.
OECD analysis (Miroudot, 2009) shows that for 29 industries in 11 OECD economies a higher
inflow of foreign intermediate goods was associated with higher productivity. Part of this effect
was due to more advanced technologies embodied in foreign inputs and part was due to reduced
inefficiencies as final goods producers moved closer to the technology frontier.
2.2. International Trade
Trade did not cause the current crisis, and it is already contributing to recovery. It will be
an essential component of any realistic policy framework for continued, sustainable
development. This is because the economic well-being of a nation is linked closely to the
availability of resources and the productivity of its workforce. Trade operates in a variety of
ways to positively affect both, notably through promotion of competition, specialization and
innovation; it also provides an important channel for international technology transfer. With
appropriate complementary policies, trade can contribute on a sustained basis to productivity
growth, quality job creation, and increased consumer choice. Protectionism simply cannot
deliver the goods - or the services - in any of these areas. An immediate opportunity for further
trade liberalization already exists: conclusion of the WTO Doha Development Agenda (DDA).
Much of the framework for such a multilateral accord has been negotiated over the past nine
years. The remaining negotiating issues are not insurmountable. Action to conclude the DDA
would increase business confidence, solidify the essential role of a rules-based, multilateral
trading system that promotes the interests of all trading nations, and deliver new economic
opportunities.
As the world economy shifts from crisis to recovery, the OECD is working concretely to
support successful conclusion of the WTO Doha Development Agenda through provision of
timely analysis, a forum for policy dialogue, and evidence-based advocacy analyze the trade
effects of policy actions taken and provide advice on appropriate next steps to enable trade to
contribute more to the recovery; support the goals of Aid for Trade initiatives and contribute to
associated analysis of binding constraints to trade, and help ensure rules-based disciplines on
government-supported export credit measures.
11
OECD is also pursuing a trade policy research agenda with short and long term
dimensions. In the short term, more can be done to clarify the relationship between trade and
employment, and the relationship between trade and growth more broadly. Governments today
are confronted with skeptical publics who, in the face of economic shocks and future uncertainty,
quite naturally look for “protection” and greater security for themselves and their families. The
benefits of a policy mix that provides short term relief through active labor market and social
policies, alongside medium and longer term opportunities through more open economies, must
be better articulated.
The OECD is also looking beyond the recovery, with a view to preparing for the “new
normal”. The post-crisis environment is not likely to be a return to “business as usual” – but what
will that new environment look like? There are essential trade-related issues that warrant
investments now in order to anticipate and prepare for future opportunities and challenges: How
will global trade imbalances be addressed? How will global production networks evolve? How
will economic, environmental and social interests be pursued by governments? How can we
ensure that policies that regulate activity in the services sectors – by far the largest part of our
economies – are conducive to trade, growth and ultimately societal well-being? These are some
of the questions that the OECD Trade Committee is addressing with the overriding objective of
ensuring that trade plays its vital role in the recovery, and beyond.
12
Chapter Three: Data, Methodology and Analysis
In the data and methodology this thesis tries to construct a statistical regression by which
tries to settle the dependable variable Economic Growth (GDP) in an equation with all the
components that derive from open trade as Import, Exports, Foreign direct Investment (FDI) and
Exchange rate in order to see what relationship exist between these variables and what effect
does trade openness has on Growth.
There are used data’s from official institution like INSTAT, Bank of Albania (BoA),
World Bank (WB). The interval time of the data taken in consideration is ten years and they are
computed in quarterly bases.
3.1 Data Description
Data used in this study are GDP, FDI, import/export ratio, and exchange rate which have
been derived from Bank of Albania and other institutional database like INSTAT and World
Bank. The time line of the data’s observed is from 2005 to 2014 quarterly basis. The data used in
this thesis firstly are tested if they have unit root meaning if they are stationary or not. For these
reason Augmented Dickey Fuller test is applied in order to differentiate the data’s into stationary
one for avoiding any errors from the results of the regression. Below has been shown the
explanation of data’s used in this regression where for every data observed has been written a
short definition.
GDP - The monetary value of all the finished goods and services produced within a
country's borders in a specific time period, though GDP is usually calculated on an annual basis.
It includes all of private and public consumption, government outlays, investments and exports
less imports that occur within a defined territory. GDP = C + G + I + NX
Where: "C" is equal to all private consumption, or consumer spending, in a nation's
economy’s" is the sum of government spending “I" is the sum of all the country's businesses
spending on capital "NX" is the nation's total net exports, calculated as total exports minus total
imports. (NX = Exports - Imports)
13
Import - The word "import" is derived from the word "port," since goods are often
shipped via boat to foreign countries. Countries are most likely to import goods that domestic
industries cannot produce as efficiently or cheaply, but may also import raw materials or
commodities that are not available within its borders. For example, many countries have to
import oil because they either cannot produce it domestically or cannot produce enough of it to
meet demand.
Export - Most of the largest companies operating in advanced economies will derive a
substantial portion of their annual revenues from exports to other countries. The ability to export
goods helps an economy to grow by selling more overall goods and services. One of the core
functions of diplomacy and foreign policy within governments is to foster economic trade in
ways that benefit both parties involved.
FDI - An investment made by a company or entity based in one country, into a company
or entity based in another country. Foreign direct investments differ substantially from indirect
investments such as portfolio flows, wherein overseas institutions invest in equities listed on a
nation's stock exchange. Entities making direct investments typically have a significant degree of
influence and control over the company into which the investment is made. Open economies
with skilled workforces and good growth prospects tend to attract larger amounts of foreign
direct investment than closed, highly regulated economies.
Exchange Rate - The price of a nation’s currency in terms of another currency an
exchange rate thus has two components, the domestic currency and a foreign currency, and can
be quoted either directly or indirectly. In a direct quotation, the price of a unit of foreign
currency is expressed in terms of the domestic currency. In an indirect quotation, the price of a
unit of domestic currency is expressed in terms of the foreign currency. An exchange rate that
does not have the domestic currency as one of the two currency components is known as a cross
currency, or cross rate.
14
3.2 Methodology
The regression model has been used in this thesis. This model has been used in order to
observe the relationship that exist between growth (GDP) represented as the dependent variable
in the regression model and the other independent variables which derives from openness such as
foreign direct investment (FDI), imports/exports and exchange rate (EU_ALL). However, the
data used in this study are time series scale which may lead for certain errors like co integration
and autocorrelation. In order to avoid such errors in the analysis the Augmented Dickey Fuller
test is conducted.
Firstly all the variables are tested if they have a normally distribution. A normal
distribution means a symmetric distribution and it has a bell shape with a peakness leading to a
Skewness of 1 and a tail-thickness leading to a Kurtosis of 3. If the Skewness is not near to 0 and
Kurtosis is not near to 3 the normality distribution is rejected. After doing this on all variables is
applied Augmented Dickey Fuller unit root test meaning that all variables are examined if they
have a unit root so if they are non stationary.
Non stationary means that a series does not fluctuates around a mean value and does not
have a tendency of coverage toward mean value. If for 1%, 5% and 10% level the probability is
greater than 0.05 it means that the variable has a unit root (non stationary) so it is first
differenced becoming stationary meaning that for 1%, 5% and 10% level the probability is lower
than 0.05.
After turning non stationary variables into stationary one by applying the Augmented
Dickey fuller test the Johansen co integration test will be applied in order to observe the
correlation and the relationship of the variables in the long run. The Johansen test is a test for co
integration that allows for more than one co integrating relationship but this test is subject to
asymptotic properties, i.e. large samples. If the sample size is too small then the results will not
be reliable. The Johansen Co integration test allow to observe whither the co integration between
the variables resulted from the regression has the same impact even in the long run.
15
The model of the thesis is:
𝑌 = 𝛼 + 𝛽1 𝑋1 + 𝛽2 𝑋2 + 𝛽3 𝑋3
Where;
𝐺𝐷𝑃 = 𝛼 + 𝛽1 𝐹𝐷𝐼 + 𝛽2 𝐸𝑥𝐼𝑚𝑝𝑟𝑎𝑡𝑖𝑜 + 𝛽3 exchange rate
GDP: is the dependent variable, which shows the performance of the Albanian economy.
FDI: is independent variable that shows the foreign direct investment in Albania.
Ratio (import/export): is independent variable that is computed as the sum of total import
plus total export to total export in order to understand the effect of the trade openness.
Exchange rate: is the currency taken in consideration to understand the impact that the
changes in the exchange rate over the years have had on the GDP.
These are the data used in the regression model the results of which will be
explained in more detail in the Analytical and result chapter where each relationship
among the variables will be shown by the respective graph and tables. All the steps above
mentioned in the data and methodology will be applied in practice throughout E-Views
program and the results will be all explained the chapter below.
3.3 Analysis and results
In this chapter all the data observed for the creation of the model of the regression line
will be applied throughout E-Views and will be shown all the empirical results of the outcomes
of this equation. After finding the empirical evidence of the regression model all the relationship
among the variable will be shown in the respective graph and tables.
Secondly the Augmented Dickey Fuller test will be applied in order to turn the data
observed into stationary one in order to overpass the errors of that may arise n the results from
the data’s that have unit root.
Finally in this chapter will be applied even the Johansen co integration test and the table
with the empirical finding will be explained. The Johansen test is used in order to observe the
long run relationship among the variables used in this model.
16
In graph 1 is showed the relationship of GDP and FDI and how this relationship has
changed in the interval of time taken into consideration. From the graph we can easily notice that
GDP has a lot of fluctuations but have persevered almost the same trend while FDI has an
increasing trend with a clear tendency of increasing year by year.
Graph 1: GDP and FDI
12
10
8
6
4
2
0
-2
-4
5
10
15
20
GDP
25
30
35
FDI
In graph 2 is showed the scatter graph of GDP and FDI. In this graph is showed the
connection that these variables have with one another and how this connection has changed
through the years.
Graph 2: Scatter plot for GDP and FDI
12
10
FDI
8
6
4
2
0
-4
-2
0
2
4
6
8
GDP
17
In graph 3 is showed the relationship between all the data’s used in this model as GDP,
FDI, Exchange Rate and Export/Import through the years. From the tables we observe the
observed data have a linear structure and those they are correlated.
Graph 3: GDP, Exchange rate, Exp/Imp Ratio, FDI
160
120
80
40
0
-40
5
10
15
20
EU/ALL
GDP
25
30
35
FDI
imp/ex
In graph 4 is showed a histogram of GDP. From the histogram we see that the skewness
for GDP is 0.341184 which is near to 0 and kurtosis is 3.029592 which is near to 3 meaning that
the GDP has a normal distribution.
Graph 4: GDP Histogram
10
Series: GDP
Sample 1 36
Observations 36
8
6
4
2
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
0.936111
1.050000
6.000000
-2.600000
2.058592
0.341184
3.029592
Jarque-Bera
Probability
0.699754
0.704775
0
-3
-2
-1
0
1
2
3
4
5
6
7
18
In graph 5 is showed the histogram of exchange rate (Euro). From the histogram we see
that the skewness for the Exchange rate (Euro) is 0.115165 which is equal to 0 and kurtosis is
1.606980 which is near to 3 meaning that the euro has a normal distribution.
Graph 5: Exchange rate histogram
14
Series: EU_ALL
Sample 1 36
Observations 36
12
10
8
6
4
2
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
132.5108
134.3946
149.9364
122.4279
8.051973
0.115165
1.606980
Jarque-Bera
Probability
2.990332
0.224211
0
120
125
130
135
140
145
150
In the graph 6 is showed the histogram of FDI. From the histogram we see that the
skewness for FDI is 1.180000 which is near to 0 and kurtosis is 3.123946 which are near to 3
meaning that the FDI has a normal distribution.
Graph 6: FDI Histogram
12
Series: FDI
Sample 1 36
Observations 36
10
8
6
4
2
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
4.524167
3.550000
11.10000
1.200000
2.769457
1.180000
3.123946
Jarque-Bera
Probability
8.377444
0.015166
0
1
2
3
4
5
6
7
8
9
10
11
12
19
In graph 7 is showed the histogram of Exp/Imp. This graph shows that for the ratio
(imp/exp), the skewness is 0.515518 which is near to 0 and kurtosis is 1.593612 which is near to
3 meaning that this ratio has a normal distribution.
Graph 7: Export/Import Histogram
20
Series: IMP_EX
Sample 1 36
Observations 36
16
12
8
4
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
1.336792
1.290000
1.480000
1.250000
0.086008
0.515518
1.593612
Jarque-Bera
Probability
4.561445
0.102210
0
1.25
1.30
1.35
1.40
1.45
1.50
In graph 8 is showed the normal distribution graph for GDP. This graph shows that all
variables have normal distribution as it observed from the graph above with a significance of 5 %
and as we can see it has a bell shape.
Graph 8: Normal distribution for GDP
20
15
10
5
0
-5
-10
-15
-20
6
8
10
12
14
16
18
CUSUM
20
22
24
26
28
30
32
34
36
5% Significance
20
Table.1 shows the group statistic where for each variable is made the same analysis as in
the series statistics(mean, median, maximum, minimum, standart Deviation Skewness, kurtosis,
Jarqua-Bera, probability, sum, sum Sq. Dev) and again is seen that all variables are normally
distributed.
As we can see from the results, the effect of FDI over GDP is negative. This means that
an increase in GDP with 1% leads FDI to a decrease with 0.09 or 9%. While for 1% increase in
GDP leads Euro to a decrease of 6% because the increase of the GDP leads to an appreciation of
Albanian currency and devaluation of the Euro.
Finally 1% increase in GDP leads in 34% increase in the trade openness ratio which has
actually a great significant and positive impact on the Albanian growth economy. In this table are
showed all the empirical findings from the regression model and are all represented in these
table.
Table 1: Descriptive statistics of all variables
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
EU/ALL
132.5108
134.3946
149.9364
122.4279
8.051973
0.115165
1.606980
2.990332
0.224211
FDI
4.524167
3.550000
11.10000
1.200000
2.769457
1.180000
3.123946
8.377444
0.015166
GDP
0.936111
1.050000
6.000000
-2.600000
2.058592
0.341184
3.029592
0.699754
0.704775
IMP/EX
1.336792
1.290000
1.480000
1.250000
0.086008
0.515518
1.593612
4.561445
0.102210
Sum
Sum Sq. Dev.
4770.389
2269.199
162.8700
268.4463
33.70000
148.3231
48.12450
0.258908
Observations
36
36
36
36
21
In table 2 is showed the outputs of the estimated equation for the independent variable
GDP. The results of the equation are all illustrated in this table.
Table 2: Estimated equation output
Dependent Variable: GDP
Method: Least Squares
Date: 04/02/15 Time: 11:04
Sample: 1 36
Included observations: 36
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
FDI
IMP_EX
EU_ALL
5.430694
-0.096183
3.433914
-0.065277
8.811874
0.253943
13.01640
0.095902
0.616293
-0.378758
0.263814
-0.680662
0.5421
0.7074
0.7936
0.5010
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.045702
-0.043764
2.103156
141.5445
-75.72549
0.510830
0.677680
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.936111
2.058592
4.429194
4.605141
4.490604
2.469499
In table 3 and the following tables the augmented Dickey Fuller unit root test is
performed on all the variables below in order to analyze if they have a unit root or not meaning.
If the variables are non stationary or stationary in other words if they are integrated in the same
order. From the results of Augmented Dickey Fuller Unit Root Test is showed that some of the
variables have a unit root so it’s not required for them to take first difference. For the other
variables that have unit root meaning that they are non stationary, first difference even the
second one is required, because the value of probability is greater than 0.05 but when they are
differenced they become stationary because their probabilities are lower than 0.05.
22
Table 3: Augmented Dickey-Fuller Unit Root Test on GDP
Null Hypothesis: GDP has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-6.704856
-4.252879
-3.548490
-3.207094
0.0000
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(GDP)
Method: Least Squares
Date: 04/02/15 Time: 11:09
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
GDP(-1)
D(GDP(-1))
C
@TREND(1)
-1.665612
0.382803
2.527600
-0.054065
0.248419
0.153702
0.776505
0.032248
-6.704856
2.490552
3.255096
-1.676554
0.0000
0.0185
0.0028
0.1040
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.688882
0.657770
1.724215
89.18751
-64.63838
22.14210
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.108824
2.947353
4.037552
4.217123
4.098791
1.884789
GDP has no unit root. Therefore taking first difference is not required.
Table 4: Augmented Dickey-Fuller Unit Root Test on FDI
Null Hypothesis: FDI has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-2.464204
-4.252879
-3.548490
-3.207094
0.3426
*MacKinnon (1996) one-sided p-values.
23
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(FDI)
Method: Least Squares
Date: 04/02/15 Time: 11:11
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI(-1)
D(FDI(-1))
C
@TREND(1)
-0.155042
0.564773
0.081054
0.037772
0.062918
0.138484
0.241213
0.017200
-2.464204
4.078267
0.336028
2.196034
0.0197
0.0003
0.7392
0.0360
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.448486
0.393334
0.634306
12.07032
-30.63852
8.131900
0.000413
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.176471
0.814374
2.037560
2.217132
2.098799
1.737192
FDI has unit root, therefore taking first difference as follows
Table 5: D (FDI) Augmented Dickey-Fuller
Null Hypothesis: D(FDI) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 3 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-4.758988
-4.284580
-3.562882
-3.215267
0.0032
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(FDI,2)
Method: Least Squares
Date: 04/02/15 Time: 11:14
Sample (adjusted): 6 36
Included observations: 31 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(FDI(-1))
D(FDI(-1),2)
D(FDI(-2),2)
-1.219403
0.702525
0.551397
0.256232
0.214601
0.207962
-4.758988
3.273640
2.651434
0.0001
0.0031
0.0137
24
D(FDI(-3),2)
C
@TREND(1)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.488037
-0.552085
0.040313
0.488934
0.386720
0.614676
9.445672
-25.56642
4.783463
0.003333
0.200562
0.305223
0.015562
2.433352
-1.808794
2.590552
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.0224
0.0825
0.0158
0.006774
0.784905
2.036543
2.314089
2.127016
1.895925
FDI does not have unit root. Meaning that variable is stationary.
Table 6.Augmented Dickey-Fuller Unit Root Test on IMP/EXP
Null Hypothesis: IMP_EX has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-2.151393
-4.252879
-3.548490
-3.207094
0.5001
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(IMP_EX)
Method: Least Squares
Date: 04/02/15 Time: 11:16
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
IMP_EX(-1)
D(IMP_EX(-1))
C
@TREND(1)
-0.085150
0.499261
0.102121
0.000783
0.039579
0.156948
0.047154
0.000339
-2.151393
3.181066
2.165693
2.310217
0.0396
0.0034
0.0384
0.0279
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.401308
0.341439
0.006883
0.001421
123.1590
6.703077
0.001349
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.0
06206
0.008482
-7.009351
-6.829780
-6.948112
2.166622
25
IMP_EX has unit root, therefore taken first difference follows:
Table 7.D (IMP/EXP) Augmented Dickey-Fuller test statistic
Null Hypothesis: D(IMP_EX) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-2.971312
-4.252879
-3.548490
-3.207094
0.1546
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(IMP_EX,2)
Method: Least Squares
Date: 04/02/15 Time: 11:17
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(IMP_EX(-1))
C
@TREND(1)
-0.492740
0.000820
0.000110
0.165832
0.002666
0.000138
-2.971312
0.307387
0.797706
0.0057
0.7606
0.4311
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.224197
0.174145
0.007275
0.001641
120.7198
4.479305
0.019550
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.000412
0.008005
-6.924695
-6.790017
-6.878766
2.036899
IMP_EX first difference has unit root, therefore taken second dif as follow:
Table 8.D (IMP/EXP) Second difference
Null Hypothesis: D(IMP_EX,2) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
t-Statistic
Prob.*
-8.515923
0.0000
26
Test critical values:
1% level
5% level
10% level
-4.262735
-3.552973
-3.209642
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(IMP_EX,3)
Method: Least Squares
Date: 04/02/15 Time: 11:19
Sample (adjusted): 4 36
Included observations: 33 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(IMP_EX(-1),2)
C
@TREND(1)
-1.400468
0.001923
-0.000109
0.164453
0.002872
0.000135
-8.515923
0.669616
-0.803356
0.0000
0.5082
0.4281
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.709417
0.690045
0.007391
0.001639
116.6942
36.62036
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
3.03E-05
0.013276
-6.890555
-6.754509
-6.844780
2.187102
IMP_EX second dif does not have unit root. Meaning that with taking the second differences the
variable now is stationary.
Table 9.Augmented Dickey-Fuller Unit Root Test on EU/ALL
Null Hypothesis: EU_ALL has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-1.970425
-4.243644
-3.544284
-3.204699
0.5966
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(EU_ALL)
Method: Least Squares
Date: 04/02/15 Time: 11:21
Sample (adjusted): 2 36
Included observations: 35 after adjustments
27
Variable
Coefficient
Std. Error
t-Statistic
Prob.
EU_ALL(-1)
C
@TREND(1)
-0.221320
27.02379
0.149094
0.112321
13.50217
0.088504
-1.970425
2.001440
1.684607
0.0575
0.0539
0.1018
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.108312
0.052582
2.593153
215.1822
-81.44525
1.943503
0.159736
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.425389
2.664142
4.825443
4.958758
4.871463
2.370812
EU_ALL has unit root, therefore taken first difference as follow:
Table 10.Augmented Dickey-Fuller Unit Root Test on D (EU/ALL)
Null Hypothesis: D(EU_ALL) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=9)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-7.857620
-4.252879
-3.548490
-3.207094
0.0000
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(EU_ALL,2)
Method: Least Squares
Date: 04/02/15 Time: 11:22
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(EU_ALL(-1))
C
@TREND(1)
-1.329022
0.765055
-0.009086
0.169138
0.964891
0.045924
-7.857620
0.792893
-0.197847
0.0000
0.4339
0.8445
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob (F-statistic)
0.665815
0.644254
2.627084
213.9486
-79.51329
30.88146
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.022177
4.404577
4.853723
4.988402
4.899653
2.022267
EU_ALL does not have unit root. Meaning that variable is stationary.
28
Johansen Co-integration Test
After converting non stationary variables into stationary, the Johansen co-integration test
will be applied in order to observe whether these variables are co-integrated in the long run as
the graph below will show it.
Table 11.Johansen co-integration test among all variables:
Date: 04/02/15 Time: 11:23
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Trend assumption: Linear deterministic trend
Series: GDP FDI IMP_EX EU_ALL
Lags interval (in first differences): 1 to 1
Unrestricted Co integration Rank Test (Trace)
Hypothesized
No. of CE(s)
Eigen value
Trace
Statistic
0.05
Critical Value
Prob.**
None *
At most 1 *
At most 2 *
At most 3
0.656269
0.439909
0.335547
0.047452
71.56860
35.26012
15.55180
1.652913
47.85613
29.79707
15.49471
3.841466
0.0001
0.0106
0.0490
0.1986
Trace test indicates 3 co integrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Co integration Rank Test (Maximum Eigen value)
Hypothesized
No. of CE(s)
Eigen value
Max-Eigen
Statistic
0.05
Critical Value
Prob.**
None *
At most 1
At most 2
At most 3
0.656269
0.439909
0.335547
0.047452
36.30848
19.70832
13.89889
1.652913
27.58434
21.13162
14.26460
3.841466
0.0030
0.0781
0.0570
0.1986
Max-eigen value test indicates 1 co integrating eqn (s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Co integrating Coefficients (normalized by b'*S11*b=I):
GDP
0.857299
-0.324406
0.030887
0.079100
FDI
0.223404
0.339833
-0.675650
-0.126967
IMP_EX
-10.54012
-38.57407
19.91681
-8.345638
EU_ALL
0.103388
0.371080
0.026726
-0.015891
29
Unrestricted Adjustment Coefficients (alpha):
D(GDP)
D(FDI)
D(IMP_EX)
D(EU_ALL)
-1.956094
-0.016339
0.002054
-0.067361
1 Co integrating Equation(s):
0.323848
-0.217072
0.003708
0.065639
-0.122080
0.297766
0.000999
-0.706543
Log likelihood
-46.43121
-0.030063
0.037011
0.000338
0.458726
Normalized co integrating coefficients (standard error in parentheses)
GDP
FDI
IMP_EX
EU_ALL
1.000000
0.260591
-12.29456
0.120598
(0.12713)
(7.22587)
(0.06140)
Adjustment coefficients (standard error in parentheses)
D(GDP)
-1.676958
(0.24602)
D(FDI)
-0.014008
(0.10251)
D(IMP_EX)
0.001760
(0.00101)
D(EU_ALL)
-0.057748
(0.39468)
2 Co integrating Equation(s):
Log likelihood
-36.57705
Normalized co integrating coefficients (standard error in parentheses)
GDP
FDI
IMP_EX
EU_ALL
1.000000
0.000000
13.84154
-0.131293
(5.21036)
(0.06321)
0.000000
1.000000
-100.2956
0.966613
(14.7268)
(0.17867)
Adjustment coefficients (standard error in parentheses)
D(GDP)
-1.782017
-0.326946
(0.25700)
(0.11403)
D(FDI)
0.056412
-0.077419
(0.10296)
(0.04568)
D(IMP_EX)
0.000558
0.001719
(0.00087)
(0.00039)
D(EU_ALL)
-0.079042
0.007258
(0.42184)
(0.18716)
3 Co integrating Equation(s):
Log likelihood
-29.62761
Normalized co integrating coefficients (standard error in parentheses)
GDP
FDI
IMP_EX
EU_ALL
1.000000
0.000000
0.000000
0.064787
(0.02840)
0.000000
1.000000
0.000000
-0.454182
(0.09815)
0.000000
0.000000
1.000000
-0.014166
(0.00151)
30
Adjustment coefficients (standard error in parentheses)
D(GDP)
-1.785787
-0.244462
5.693903
(0.25627)
(0.22036)
(12.4829)
D(FDI)
0.065609
-0.278605
14.47614
(0.08915)
(0.07666)
(4.34257)
D(IMP_EX)
0.000588
0.001044
-0.144786
(0.00085)
(0.00073)
(0.04145)
D(EU_ALL)
-0.100865
0.484634
-15.89405
(0.40392)
(0.34731)
(19.6748)
In table 12 the Johansen co integration test between GDP and FDI is applied in order to
observe how does change or not the relationship between these two variables in the long run.
From the results of the Johansen co integration trace test indicates 2 co-integrating equations at
the 0.05 level where the Trace statistic is greater than 5% critical value while Max-Eigen value
test indicates that there is no co-integration at 0.05 levels because Max-Eigen statistic is higher
than 5% critical value. In other words GDP and the other variable: FDI, are co-integrated to each
other but in the long run this co-integration is weak. Meaning that the positive and significant
relationship between one factor of openness such as FDI and growth GDP as showed from the
regression model in the long run seems not to be so strong and this relationship is ambiguous
meaning that in the long term openness is not the driving force behind growth.
Table 12.Johansen co-integration test between GDP and FDI
Date: 04/02/15 Time: 11:26
Sample (adjusted): 3 36
Included observations: 34 after adjustments
Trend assumption: Linear deterministic trend
Series: GDP FDI
Lags interval (in first differences): 1 to 1
Unrestricted Co integration Rank Test (Trace)
Hypothesized
No. of CE(s)
Eigen value
Trace
Statistic
0.05
Critical Value
Prob.**
None *
At most 1
0.607819
0.045420
33.40553
1.580465
15.49471
3.841466
0.0000
0.2087
Trace test indicates 1 co integrating eqn (s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
31
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Co integration Rank Test (Maximum Eigen value)
Hypothesized
No. of CE(s)
Eigen value
Max-Eigen
Statistic
0.05
Critical Value
Prob.**
None *
At most 1
0.607819
0.045420
31.82506
1.580465
14.26460
3.841466
0.0000
0.2087
Max-eigen value test indicates 1 co integrating eqn (s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Co integrating Coefficients (normalized by b'*S11*b=I):
GDP
-0.824085
0.072081
FDI
-0.128313
-0.384198
Unrestricted Adjustment Coefficients (alpha):
D(GDP)
D(FDI)
1.921231
0.021878
1 Co integrating Equation(s):
-0.088937
0.137484
Log likelihood
-96.58565
Normalized co integrating coefficients (standard error in parentheses)
GDP
FDI
1.000000
0.155703
(0.07010)
Adjustment coefficients (standard error in parentheses)
D(GDP)
-1.583258
(0.24053)
D(FDI)
-0.018029
(0.09710)
32
Conclusion
This thesis investigates the relationship among a wide variety of trade openness measures
and growth. The openness measures taken into account are trade volumes imports & exports,
FDI foreign direct investment, exchange rate EU/ALL as the independent variable and GDP as
the independent variable which represent growth. Findings of empirical evidence shows that
trade openness have a significant and positive relationship on growth. From the statistical result
is showed that exist a strong relationship and that the variables are co integrated with one another
even though that in the long run this co integration appear not to be so strong, meaning that in the
long run the impact of openness on growth seems to narrow. For this reason measures to extend
this correlation between openness and growth some are requires as for example keeping a
positive balance of net export, implementing a fiscal policy for preserving a healthy and secure
market environment in order to be attractive to the foreign investment FDI factor that even as
showed from the graphs and the empirical studies have a big impact on growth and finally
maintaining a healthy exchange rate in order to preserve the value of the native currency in order
not to diminish the purchasing power of the native currency. The scope of the thesis was to
observe the relationship between trade openness and growth and how openness impact on
growth. From the results of the empirical studies applied in the thesis conclude in the conclusion
that sustains the hypothesis of this thesis that openness and the variables deriving from it have a
positive relationship on growth.
33
References
Anderson, N. (1992). Trade reform with quotas, partial rent retention, and tariffs.
Econometrica 60 , 57– 76.
Andriamananjara, S. N. (1997). Have trade policy reforms led to greater openness in
developing countries? World Bank Working Paper Series, No. 1730.
Auguste, B. (1997). The Economics of International Payments Unions and Clearing
Houses. . St. Martin’s Press, New York .
Clemens, M. W. (2001). A tariff-growth paradox? . Protection’s impact the world around
1875–1997. NBER Working Paper Series, No. 8549.
Dollar, D. (1992). Outward-oriented developing economies really do grow more rapidly.
Economic Development and Cultural Change 40 , 523– 544.
Edwards, S. (1998). Openness, productivity and growth: what do we really know?
Economic Journal 108 , 383– 398.
Edwards, S. (1993). Openness, trade liberalization, and growth in developing countries.
Journal of Economic Literature 31 , p. 1365.
Frankel, J. R. (1999). Does trade cause growth? American Economic Review 89 , 379–
399.
Grossman, G.M, Helpman, E. (1990). Comparative advantage and long-run growth.
American Economic Review .
Harrison, A. (1996). Openness and growth: a time series, cross-country analysis for
developing countries. , p. 420.
Irwin, D. T. (2002). Does trade raise income? Evidence from the twentieth century. .
Journal of International Economics 58 , 1 – 18.
Krueger, A.O. (1978). Liberalization Attempts and Consequences. Ballinger, Cambridge.
Leamer, E. ( 1988). Measures of openness. In: Baldwin, R.E. (Ed.), The University of
Chicago Press, Chicago. Trade Policy Issues and Empirical Analysis. , 147– 204.
Lee, J.-W. (1993). International trade, distortions, and long-run economic growth. IMF
Staff Papers 40 , 299– 328.
Levine, R. R. (1992). A sensitivity analysis of cross-country growth regressions.
American Economic Review 82, , 942–963.
34
Miroudot. (2009). Trade in Intermediate.
O’Rourke, K. (2000). Tariffs and growth in the late nineteenth century. Economic
Journal 110 , 456– 483.
OECD. (2003). The Sources of Economic Growth in the OECD Countries.
OECD. (May 2010). Why open markets matter.
Rodriguez, F. a. (2001). “Trade Policy and Economic Growth: A Skeptic's Guide.
Rodrik, D. (2000). Comments on Frankel and Rose, ‘‘Estimating the Effects of Currency
Unions
on
Trade
and
Output’’.
Harvard
University.
Unpublished
paper,
http://www.ksghome.harvard.edu/f.drodrik.academic.ksg/comments%20on%20Frankel-Rose.pdf.
Rodrik, D. S. (2002). Institutions Rule: The Primacy of Institutions over Geography and
Integration
in
Economic
Development.
Harvard
University.
Unpublished
paper,
http://www.ksghome.harvard.edu/f.drodrik.academic.ksg/ .
Romer, P.M. (1990). Endogenous technical change. Journal of Political Economy 98 ,
S71–S102.
S, E. (1992). Trade orientation, distortions and growth in developing countries. Journal
of Development Economics 39 , 31– 57.
Sachs, J. W. (1995). Economic reform and the process of economic integration.
Brookings Papers of Economic , 1 – 118.
Sala-i-Martin. (1997). I just ran two million regressions. American Economic Review 87 ,
178– 183.
Triffin, R. (1976). Europe and the Money Muddle. . Greenwood Press, Westport.
Trued, M. M. (1955). Postwar bilateral payments agreements. Princeton Studies in
International Finance, vol. 4. Princeton Univ. Press, New Jersey.
35
Appendixes
QUARTERS
GDP
FDI
IMP/EXP
EU/ALL
Q1-2005
-2
4.7
1.25
124.78005
Q2
6
3.5
1.259
124.21005
Q3
-0.6
2.7
1.257
124.01005
Q4
0.1
2.8
1.259
123.96025
Q1-2006
1.1
2.9
1.26
123.87025
Q2
1
2.95
1.265
123.90025
Q3
1.8
3
1.264
123.98025
Q4
3.3
2.6
1.263
124.05338
Q1-2007
-0.3
2.2
1.264
124.10338
Q2
-0.1
2
1.2645
123.50338
Q3
1.4
1.7
1.264
123.10338
Q4
5.6
1.4
1.26
122.80338
Q1-2008
2.3
1.2
1.258
122.42789
Q2
-0.8
2.4
1.266
124.42789
Q3
1.7
3.9
1.264
126.42789
Q4
1.2
4.5
1.262
128.42789
Q1-2009
2.2
5.09
1.26
130.8946
Q2
2.2
4
1.28
133.8946
Q3
-2.6
3
1.3
134.8946
Q4
-2
3.05
1.32
136.8946
Q1-2010
3.3
3.1
1.34
137.97812
Q2
2.4
3.8
1.35
138.97812
Q3
-0.9
4.59
1.36
139.97812
Q4
1.2
3.7
1.38
141.97812
Q1-2011
3.7
3.1
1.39
142.93644
Q2
-2.6
3.4
1.4
141.93644
Q3
1.7
3.6
1.42
140.93644
Q4
-0.3
4.5
1.43
149.93644
Q1-2012
-0.3
6.1
1.44
138.89495
Q2
0.6
7.6
1.45
138.69495
Q3
2.2
9.6
1.46
138.59495
Q4
-0.8
10.4
1.47
138.35495
Q1-2013
0.7
11.1
1.48
138.18464
Q2
1
10
1.47
139.28464
Q3
-2
9.19
1.475
139.48464
Q4
2.3
9.5
1.47
139.66867
36