1. A
PROJECT REPORT
ON
“IMPACT OF EXPORTS ON ECONOMIC GROWTH OF
ECOWAS COUNTRIES: A COMPARATIVE ANALYSIS”
Submitted to
Punjabi University, Patiala
In partial fulfillment of the requirement for the award of degree of
Master of Business Administration
By:
Kodjane Jean Michel
Univ. Roll No: 12975
Registration No: GBC (P) 2005-209
Under the guidance of:
Dr. Surendar Singh
Senior Lecturer, Deptt. Of Management
DESH BHAGAT INSTITUTE OF MANAGEMENT AND COMPUTER SCIENCES
MANDI GOBINDGARH
2013
1

2. DECLARATION
I declare that the Project entitled “Impact Of Exports on Economic Growth of
Ecowas Countries: A Comparative Analysis” is a record of independent work carried out
by me under the supervision and guidance of Dr. Surendar Singh, Senior Lecturer. This
has not been previously submitted for the award of any other diploma, degree or other
similar title.
________________
Kodjane Jean Michel
Univ. Roll No: 12975
2

3. CERTIFICATE
Certified that the Project Report entitled “Impact of Exports on Economic Growth
of Ecowas Countries: A Comparative Analysis” submitted to the Punjabi University,
Patiala for the award of degree of Master of Business Administration is a record of
independent work carried out by Kodjane Jean Michel, under my supervision and
guidance. This has not been previously submitted for the award of any diploma, degree or
other similar title.
__________________
Dr. Surendar Singh
Senior Lecturer
Deptt. of Management
3

4. ACKNOWLEDGEMENTS
I owe a great many thanks to a great many people who helped and supported me
during the preparation of this project report.
My deepest thanks to Dr. Surendar Singh, Senior Lecturer, Deptt. of
Management the Guide of the project for guiding and correcting various documents of
mine with attention and care. He has taken pain to go through the project and make
necessary corrections as and when needed.
I express my thanks to the Mrs. Nidhi Gupta, Director, Desh Bhagat Institute of
Management and Computer Sciences, Mandi Gobindgarh for extending her support
throughout my studies.
I would also thank my Institution and my faculty members without whom this
project would have been a distant reality.
I also extend my heartfelt thanks to my loving parents for their ever encouraging
moral support and inspiration that really kept me going.
All might not have been mentioned, but none is forgotten.
________________
Kodjane Jean Michel
Univ. Roll No: 12975
4

5. CONTENTS
Chapter
Title
Page No.
No.
1.
INTRODUCTION
1-5
2.
BACKGROUND OF STUDY
6-15
3.
REVIEW OF LITERATURE
16-25
4.
RESEARCH METHODOLOGY
26-29
5.
DATA ANALYSIS & INTERPRETATION
30-35
6.
FINDINGS, CONCLUSION &
36-39
RECOMMENDATIONS
BIBLIOGRAPHY
i-ii
APPENDICES
a-d
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6. LIST OF ABREVIATION
CFA: Communauté Française d'Afrique (in French)
ECOWAS: Economic Community of West African States
ELG: Export Led Growth
ERP: Economic Recovery Programme
GDP: Gross Domestic Product
LDCs: Least Developed Countries
OLS: Ordinary Least Squares
OPEC: Organisation of the Petroleum Exporting Countries
UEMOA: Union Economique et Monétaire Ouest-Africaine (in French)
US: United States of America
WAEMU: West African Economic and Monetary Union
6

7. Abstract
An assessment of the role of export in economic growth is of obvious importance, it
is in this regards that the study has been conducted. This study investigates the
relationship between exports and economic growth in a group of three developing
countries selected from ECOWAS (Cote d’Ivoire, Ghana and Nigeria). For analysis,
secondary data for the period of 1980 to 2011 are used; the data have been collected from
World Bank databank. Simple linear regression model and ordinary least squares (OLS)
technique have been used for empirically estimation of the impacts of exports on
economic growth. During the study period, the impacts of exports on economic growth
have been found statistically significant for Cote d’Ivoire, Ghana. However, the
magnitude of impact of exports on economic growth for Nigeria has been found
comparatively highest. Thus, the outcomes of this study recommend that the policy
makers of each country incorporated in this study needs to expand level of exports in
order to improve socio-economic development.
Keywords: Exports, Economic Growth, Regression analysis, Developing countries,
ECOWAS, Cote d’Ivoire, Ghana, Nigeria.
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8. 8

9. INTRODUCTION
Economic development is one of the main objectives of every society in the world
and economic growth is fundamental to economic development. There are many factors
affecting economic growth and export is recognised as one of the very important factors
as exports of goods and services represent one of the most important sources of foreign
exchange income that ease the pressure on the balance of payments and create
employment opportunities. It was also recognised that exports provide the economy with
foreign exchange needed for imports that cannot be produced domestically. Therefore,
management authorities and governments usually intend to encourage expansion in
exports through various incentives such as, for instance, export subsidies etc...
Nevertheless, the role of exports in the economies of developing countries has been
subject to a wide range of empirical and theoretical studies. There have been
disagreements among economists concerning the contribution of export to economic
development; this divergence of opinion goes back to the classical economic theories by
Adam Smith and David Ricardo, who argued that international trade plays an important
role in economic growth, and that there are economic gains from specialization. While
many economists view export as a powerful engine of growth, there are some very
renowned economists who highlight the deleterious effect of trade on developing
countries.
1. Statement of the problem
Trade in West Africa has gone through various phases. Before the 1960, West
African countries’ trade policy was defined by her colonial masters. Essentially, trade
was a two-way relation whereby primary commodities were exported and manufactured
products imported. Trade structure during this period was driven by the interests of the
colonial masters. The GDP growth was reasonably high during this period.
In the period from 1960 to 1980’s the trade policies were informed by the doctrine
of import substitution industrialization. During this period, an inward oriented policy
9

10. with significant trade restrictions was adopted. As a result, trade policies during this
period were characterized by extensive state involvement in the economy both in the
production and marketing. The period was characterized by trade restrictions through
tariffs and taxes that were justified on account of infant industry protection argument.
In view of the continued deterioration of West Africa’s economic performance since
1970s, an Economic Recovery Programme (ERP) was launched from 1980’s. The
objective was to achieve higher rates of economic growth by increasing the efficiency of
resource allocation, in particular by aligning domestic prices more closely with
international prices. This period marked the beginning of trade liberalization and export
promotion growth strategy.
Exports of the ECOWAS rose from US$10.4 billion in 1983 to US$29 billion in
1996 and US$36.4 billion in 2000. In the year 2005, it was US$73 billion and again rose
to US$93.6 billion in 2007. It then went up in 2011 to US$ 136.6 billion (World Bank).
At the same time, GDP seems to have increased steadily as it rose from US$57.5
billion in 1983 to US$77 billion in 1996 and US$82.2 billion in 2000. In 2005, it was
US$ 175.9 billion and rose to US$ 257.9 billion in 2007. In 2011, it went up to US$ 373
billion (World Bank).
From the above, exports and GDP appear to be moving upward together after 1983.
But is there a reason for us to believe that growth in GDP is due to growth in exports?
Again, is a positive trend in exports not due to a rise in GDP? Furthermore, is the rise in
GDP not due to other factors apart from exports? In any case, is there any link between
exports and economic growth?
To this end, an empirical assessment of the linkage between exports and economic
growth is important. However, there is no recent empirical evidence assessing the impact
of exports on economic growth.
2. Objectives of the study
Since exports of goods and services account for significant portion in African
developing countries income, the objective of this study is to examine the impact of
exports on economic growth of ECOWAS countries.
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11. The objectives of this study are spelt out into two, i. e. general objective and
specific objectives. The general objective of this study is to examine the impact of
exports on economic growth of ECOWAS countries. While the specific objectives are:
1. To examine the relationship between exports growth and economic growth.
2. To find out if fluctuations in exports affect the economic growth of the countries in
the same manner.
3. Hypotheses of the study
This study is designed to investigate the impact of export on economic growth of
ECOWAS countries. The hypothesis is therefore postulated as follow:
Ho: There is no statistically significant relationship between exports and economic
growth of ECOWAS countries.
Hi: There is statistically significant relationship between exports and economic
growth of ECOWAS countries.
4. Methodology
In this research work, the econometric technique used is ordinary least square
(OLS) in form of simple linear regressions. The data used are purely obtained from
secondary sources, only from World Bank Databank for the time period ranging from
1980 to 2011.
5. Organisation of the study
This research work has been divided into six chapters as follows:
Chapter one which is the general introduction of the entire study comprises of the
statement of problem, objectives of the study, hypothesis of the study, methodology and
organization of the study.
Chapter two gives a detail the background information on the study which includes
the historical background of exports, its composition, and challenges faced and
performances of export sector.
11

12. Chapter three is the literature reviews, which covers conceptual, theoretical and
empirical framework.
Chapter four consists of the research methodology which shows the model
specification, sources of data, econometrics techniques and sampling techniques.
Chapter five presents the data and show the analysis and interpretation of findings
which as well as hypothesis testing and discussion of results.
Chapter six which is the last chapter deals with the summary of findings,
conclusions and recommendations.
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13. 13

14. I.
OVERVIEW OF ECOWAS
The Economic Community of West African States (ECOWAS) is a regional trade
bloc created on May 28, 1975 by the Treaty of Lagos. It headquarter is located in Abuja,
Nigeria.
There are officially three co-equal languages; French, English, and Portuguese in
ECOWAS and eight Currencies; Cape Verde-Escudo, Ghana-Cedi, The Gambia-Dalasi,
Guinea Franc, Liberia Dollar, Nigeria-Naira, Sierra Leone-Leone and W. African CFA
franc.
ECOWAS aims at promoting cooperation and integration with the establishment of
a West African economic union as an ultimate goal. It is aimed at improving the living
standard of the people, ensuring economic growth and strengthening relations between
Member States. In order to achieve these goals, ECOWAS has set up a number of
structures entrusted with the preparation, implementation and evaluation of the
Community programmes and projects. ECOWAS’s mission is to promote economic
integration in "all fields of economic activity, particularly industry, transport,
telecommunications, energy, agriculture, natural resources, commerce, monetary and
financial questions, social and cultural matters."
ECOWAS is not fully a custom union but it can be fully consider as a free trade
area with free visa among members. It has 15 members: Benin, Burkina Faso, Cape
Verde, Cote d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger,
Nigeria, Senegal, Sierra Leone and Togo. With a total surface of 5.112.903 km²,
ECOWAS region population is estimate to 308,659,730 inhabitants (est. 2011) with a
dominant Nigeria economy, accounting for near about half of the population and more
than half of the regional aggregate nominal GDP which is $ 373,080,195,046 (US
Dollar). ECOWAS taken as a block stands as the 28th power of the world. It consists of
4.4% of the world population however its contribution in the world total GDP and
Import-Export is lower; with 0.53% of the world GDP, 0.6% of both world import and
export of goods and services. The most performer countries are Nigeria, Ghana followed
by Cote d’Ivoire.
14

15. ECOWAS consists broadly of two distinct zones a Sahelian zone, largely
landlocked, and a more humid, forested coastal zone. Besides, this geographic specificity,
eight ECOWAS members also belong to WAEMU (also known as UEMOA from its
name in French), a customs and monetary union (Franc CFA is used as the common
currency of WAEMU). Its exports are mostly comprised of a limited range of agricultural
commodities and somehow oil. This reliance on internationally traded commodities
leaves Ecowas countries vulnerable to the external shocks of international market price
fluctuations. Since all countries but Nigeria are net oil importers, fluctuations in oil prices
on the import side are often combined with commodity price shocks on the export side.
Manufactured exports are negligible. Intra-regional trade as a share of total trade remains
marginal, at some 10 percent reflecting the lack of complementarities of the economies.
Exports of goods and services are not so diversify in Ecowas community, therefore
Ecowas’ exports depend highly on commodities.
II.
PROFILE OF ECOWAS COUNTRIES
1. Benin
With a total area of 112,620 square kilometers, Benin has a population of 8.8
million inhabitants. Its GDP is estimated to US$ 7.3 billion divided in the following way;
Agriculture 35%, Industry 14% and Service 51%.
Benin total exports and contribute to GDP up to 15% whereas exports of
commodity account for 91% of total exports. Major items exported by Benin can be
represented in the following manner; All food items 24%, Agricultural raw materials
45%, Fuels 19% and Mining 12%. The three leading items exported are cotton 38%,
Petroleum oils or bituminous minerals 17% and fruits and nut 8%.
The biggest export partners of Benin are China 25%, India 16%, EU (27) 15%, Mali
12% and Nigeria 5%.
15

16. 2. Burkina Faso
The population of Burkina Faso is estimated to 16.4 million spread on 274,220
square kilometers. Burkina Faso GDP is around US$ 10.4 billion, composed by
Agriculture 35%, Industry 24% and Service 42%.
The country of Burkina Faso has been among the major exporters of a few
important commodities in the whole world, its exports depend on commodities at 94%.
However, exports of goods and services account to 21% of the total GDP. Major items
exported can be represented in the following manner; All food items 20%, Agricultural
raw materials 45%, and Mining 35%. The three leading commodities exported are cotton
44%, Gold, non-monetary 35% and Oil seeds and Oleaginous fruits 9 %.
The major export partners of Burkina Faso are Switzerland 24%, EU (27) 17%,
China 13%, Singapore 12% and Thailand 4%.
3. Cape Verde
Known as the island of Ecowas, the total area of Cape Verde is 4,030 square
kilometers, its population of 0.5 million inhabitants. Its GDP is estimated to US$ 1.9
billion divided in the following way; Agriculture 8%, Industry 17% and Service 74%.
Commodity exports account for 70% of its total exports but total exports contribute
to GDP up to 42%. Total exported by Benin can be represented in the following manner;
All food items 98% and Mining 1%. The three leading items exported are Fishery
products 96%, Alcoholic beverages 2% and ferrous waste, scrape; remelting ingots, iron,
steel 1%.
The major export partners of Cape Verde are EU (27) 94%, United States 1% and
Brazil 1%.
4. Cote d'Ivoire
With a total area of 322,462 square kilometers, Benin has a population of 20 million
inhabitants. Its GDP is estimated to US$ 24 billion divided in the following way;
Agriculture 26%, Industry 28% and Service 45%.
16

17. Cote d'Ivoire is the world's largest producer and exporter of cocoa beans; it
produces 30% of the world production. Similarly, it is a significant producer and exporter
of coffee and palm oil. Consequently, the economy is highly sensitive to fluctuations in
international prices for these products, and, to a lesser extent, in climatic conditions.
Cocoa, oil, rubber and coffee are the country's top export revenue earners, but the country
is also exporting gold, significant amount of crude oil (30 % of total exports), coffee,
palm oil, timber, cotton, natural rubber, fish and gold. Exports has significant
contribution in the country GDP and Commodity exports account for 85% of its total
exports whereas total exports contribute to GDP up to 44%. Items exported by Cote
d’Ivoire can be represented in the following manner; All food items 53%, Agricultural
raw materials 9%, Fuels 36% and Mining 2%. The three leading items exported are cocoa
39%, Petroleum oils or bituminous minerals 17% and bitumen materials, crude 15%.
Cote d’Ivoire’s major export partners are EU (27) 46%, United States 11%, Nigeria
7%, Ghana 5% and Canada 3%.
5. Gambia
The population of The Gambia is estimated to 1.7 million spread on 11,300 square
kilometers. The Gambia GDP is around US$ 0.9 billion, composed by Agriculture 28%,
Industry 17% and Service 54%.
The Gambia’s exports depend on commodities at 82%. However, Total exports
account to 29% of the total GDP. Items exported can be represented in the following
manner; All food items 78%, Agricultural raw materials 3%, and Mining 19%. The three
leading items exported are Fruits and nuts 42%, Vegetable fats and oil 13% and Fishery
products 8%.
The export major partners of The Gambia are India 41%, EU (27) 26%, China 10%,
Senegal 5% and Guinea 4%.
17

18. 6. Ghana
Like all the country in West Africa, export is the main source of foreign exchange
earnings. Ghana population is around 24.3 million over a total area of 238,540 square
kilometers, its GDP is US$ 39 billion divided as follow; Agriculture 36%, Industry 28%
and Service 37%.
Commodities exports account to 90% of total exports and represent 38% of GDP.
Commodities export is composed by All food items 60%, Agricultural raw materials 8%,
Fuels 4% and Mining 28%. The major exports of Ghana are listed as; Cocoa 49%, Gold
14% and Ores and concentrates of base metals 10%.
The major export partners of Ghana are EU (27) 43%, South Africa 12%, Ukraine
9%, United States 5% and India 4%.
7. Guinea
The population of Guinea is estimated to 9.9 million spread on 245,860 square
kilometers. Guinea GDP is around US$ 5 billion, composed by Agriculture 25%,
Industry 41% and Service 34%.
The country has been among the major exporters of a few important commodities in
the whole world, its exports depend on commodities at 85%. However, total exports
account to 30% of the total GDP. Items exported can be represented in the following
manner; All food items 9%, Agricultural raw materials 4%, Fuels 18% and Mining 70%.
The three leading items exported are Aluminum ores and concentrates 51%, Petroleum
oils, oils from bitumen materials, crude 17% and Gold, non-monetary 10.
The major export partners of Guinea are EU (27) 40%, India 19%, Russian
Federation 12%, United States 8% and Ukraine 5%.
8. Guinea-Bissau
With a total area of 36,130 square kilometers, Guinea-Bissau has a population of
1.5 million inhabitants. Its GDP is estimated to US$ 0.9 billion divided in the following
way; Agriculture 45%, Industry 14% and Service 42%.
18

19. Commodity exports account for 99% of its total exports whereas exports contribute
to GDP up to 18%. Items exported by Guinea-Bissau can be represented in the following
manner; All food items 92%, Agricultural raw materials 1%, Fuels 6% and Mining 1%.
The three leading items exported are Fruits and nuts 91%, Petroleum oils, oils from
bitumen materials, crude 6%, Ferrous waste, scrape; remelting ingots, iron, steel 1%.
The major export partners of Guinea-Bissau are India 89%, United States 6%,
Singapore 2%, and EU (27) 1%.
9. Liberia
The population of Liberia is estimated to 3.9 million spread on 11,300 square
kilometers. The Gambia GDP is around US$ 1.5 billion, composed by Agriculture 64%,
Industry 13% and Service 24%.
Liberia’s exports depend on commodities at 62% and total exports account to 27%
of the total GDP. Liberia’s exported items can be represented in the following manner;
All food items 3%, Agricultural raw materials 56%, Fuels 19% and Mining 22%. The
three leading items exported are Natural rubber & similar gums 54%, Gold 13%,
Petroleum oils, oils from bitumen materials, crude 10%,
The export partners of Liberia are United States 35%, EU (27) 19%, United Arab
Emirates 12%, South Africa 10% and Canada 9%.
10. Mali
With a total area of 1,240,190 square kilometers, Mali has a population of 15.3
million inhabitants. Its GDP is estimated to US$ 10.8 billion divided in the following
way; Agriculture 39%, Industry 20% and Service 40%.
Mali’s exports depend on commodities at 88%. However, total exports account to
25% of the total GDP. Items exported can be represented in the following manner; All
food items 9%, Agricultural raw materials 30%, Fuels 1% and Mining 60%. The three
leading items exported are Gold 59%, Cotton 30%, and Live animals other 4%.
The major export partners of Mali are South Africa 55%, China9%, EU (27) 6%,
Thailand 5% and Senegal 4%.
19

20. 11.Niger
Niger has a population estimated to 15.5 million inhabitants spread on 1,267,000
square kilometers. Its GDP is around US$ 6 billion, composed by Agriculture 44%,
Industry 16% and Service 40%.
Niger’s exports depend on commodities at 68%. However, total exports account to
18% of the total GDP. Items exported can be represented in the following manner; All
food items 42%, Agricultural raw materials 6%, Fuels 18% and Mining 33%. The three
leading items exported Ores and concentrates of uranium or thorium 28%, Live animals
26%, Petroleum oils or bitumen materials 11%.
The major export partners of Niger are Nigeria 33%, United States 23%, EU (27)
22%, Japan 6% and Ghana 4%.
12. Nigeria
Nigeria is a member of OPEC, with a total area of 923,770; it has a population of
160 million of inhabitants. Nigeria GDP is 243.9 Billion composed by Agriculture 37%,
Industry 34% and Service 29%.
As an OPEC member, Nigeria’s exports depend on commodities at 97%. Similarly,
its total exports account to 40% of the total GDP. Exported items can be represented in
the following manner; All food items 3%, Agricultural raw materials 1%, Fuels 95% and
Mining 1%. The three leading items exported are Petroleum oils, oils from bitumen
materials, crude 83%, Natural gas 5% and bituminous minerals 6%. Exports of oil and
natural gas are the main factor behind Nigeria's growth.
Nigeria's main exports partners are United States 36%, EU (27) 24%, India 10%,
Brazil 8%l and South Africa 3%.
20

21. 13. Senegal
The population of Senegal is estimated to 12.5 million spread on 196,720 square
kilometers. Its GDP is around US$ 14.3 billion, composed by Agriculture 19%, Industry
21% and Service 61%.
Senegal’s exports depend on commodities at 66%. However, total exports account
to 25% of the total GDP. Items exported can be represented in the following manner; All
food items 47%, Agricultural raw materials 2%, Fuels 38% and Mining 13%. The three
leading items exported are Petroleum oils or bituminous minerals 37%, Fishery products
21%, Gold 7%,
The export major partners of Senegal are EU (27) 26%, Mali 19%, Côte d’Ivoire
4%, Switzerland 3% and China 3%.
14. Sierra Leone
Sierra Leone area is 71,740 square kilometers and it has a population of 5.8 million
inhabitants. Its GDP is estimated to US$ 3.6 billion divided in the following way;
Agriculture 58%, Industry 5% and Service 37%.
Commodity exports account for 69% of Sierra Leone total exports whereas total
exports contribute to GDP up to 17%. Items exported by Sierra Leone can be represented
in the following manner; All food items 24%, Agricultural raw materials 3%, Fuels 1%
and Mining 72%. The three leading items exported are Pearls, precious & semi-precious
stones 35%, Aluminum ores and concentrates 18% and Ores and concentrates 13%.
The major export partners of Sierra Leone are EU (27) 14%, United States 10%,
China 4%, India 2% and Côte d’Ivoire 2%.
15. Togo
The total area of Togo is 56,790 square kilometers and its population of 6 million
inhabitants. Its GDP is estimated to US$ 2.9 billion divided in the following way;
Agriculture 47%, Industry 19% and Service 34%.
Commodity exports account for 61% of its total exports and total exports contribute
to GDP up to 41%. Exported items by Togo can be represented in the following manner;
21

22. All food items 40%, Agricultural raw materials 14%, Fuels 20% and Mining 25%. The
three leading items exported are cocoa 19%, Crude fertilizers 18% and Petroleum oils or
bituminous minerals 18%.
The major export partners of Togo are EU (27) 25%, India 14%, Mali 10%, Burkina
Faso 7% and Benin 6%.
22

23. 23

24. I.
CONCEPTUAL REVIEW
Export can be defined as goods and services which are sent from a country to other
countries in the world for sale. There are two types of export: visible export and invisible
export. Visible export consists of commodities which are tangible and can be seen and
touched. They appear in a country balance of trade as crude oil, coal, tin, palm oil, cotton,
rubber, gold, livestock etc…
Invisible export consists of intangible commodities that cannot be physically seen
or touch, such as services. The services are calculated in terms of money. They are
insurance, civil aviation, banking services, and tourism, audio-visual services etc...
An increase in the capacity of an economy to produce goods and services, compared
from one period of time to another. Economic growth can be measured in nominal terms,
which include inflation, or in real terms, which are adjusted for inflation. Similarly,
growth in output can be divided into two major categories; growth through increased
input i.e. labor and capital inputs cannot be increased indefinitely without encountering
diminishing marginal returns., and growth through improvement in productivity i.e.
technological progress is needed to increase the standard of living in the long-run.
Growth domestic product can be defined as all products that are produce in a
country irrespective of the nationals that produce it. For example, all goods and services
produced in USA regardless of the nationality. If Indian based in USA produced output it
is usually included in the GDP of USA. GDP is calculated without deductions for
depreciation.
II.
THEORITICAL REVIEW
One of the most enduring questions in economics is how a country can achieve high
economic growth. In Harrod-Domar model, growth depends on the amount of capital
invested. More physical capital would generate economic growth according to the model.
For any take off, the model suggests that there should be mobilization of domestic and
foreign saving in order to generate sufficient investment to accelerate economic growth.
24

25. Economic growth therefore requires policies that encourage saving and /or generate
technological advances which lower capital-output ratio (Gillis et al 1991).
However, in Arthur Lewis’s two-sector model, growth stems from capital
accumulation in the modern sector. In this model, the underdeveloped economy consists
of two sectors: a traditional, overpopulated rural subsistence sector characterized by zero
marginal labour productivity a situation that permits Lewis to classify this as surplus
labour in the sense that it can be withdrawn from the agricultural sector without any loss
of output and a high productivity modern urban industrial sector into which labour from
the subsistence sector is gradually transferred. The primary focus of the model is on both
the process of labour transfer and the growth of output and employment in the modern
sector. Both labour transfer and modern-sector employment growth are brought about by
output expansion in that sector. The speed with which this expansion occurs is
determined by the rate of industrial investment and capital accumulation in the modern
sector. Such investment is made possible by the excess of modern sector profits over
wages on the assumption that capitalists reinvest all their profits. Finally, the level of
wages in the urban industrial sector is assumed to be constant and higher than that in
traditional sector so as to induce people to leave traditional sector and work in urban
industrial sector. An increase in the amount of capital in the modern sector would
therefore increase the marginal product of labour and hence total output in the sector
without affecting the traditional sector. For Lewis, capital accumulation in the modern
sector is the method for growing a less developed economy without doing any real
damage to the traditional sector (Todaro, 1997).
In the Lewis-Ranis-Fei model, saving and investment are drivers of economic
growth. This is consistent with the Harrod-Domar model but in context of less-developed
countries. The model is an improvement over Lewis’s model of unlimited supplies of
labour because Lewis failed to present a satisfactory analysis of the growth of the
agricultural sector. Ranis and Fei (1961) formalized Lewis’s theory by combining it with
Rostow’s (1961) three “linear-stages-of-growth” theory. They disassembled Lewis’s twostage economic development into three phases, defined by the marginal productivity of
agricultural labour. They assume the economy to be stagnant in its pre-conditioning
stage. The breakout point marks the creation of an infant non-agricultural sector and the
entry into phase one. Agricultural labour starts to be reallocated to the non-agricultural
25

26. sector. Due to the abundance of surplus agricultural labour, its marginal productivity is
extremely low and average labour productivity defines the agricultural institutional wage.
When the redundant agricultural labour force has been reallocated, the agricultural
marginal productivity of labour starts to rise but is still lower than the institutional wage.
This marks the shortage point at which the economy enters phase two of development.
During phase two the remaining agricultural unemployment is gradually absorbed. At the
end of this process the economy reaches the commercialization point and enters phase
three where the agricultural labour market is fully commercialized (Ercolani and Wei
2010).
Finally, according to Pack (1988), there is potential for no causal relationship
between exports and economic growth when the growth paths of the two time series are
determined by other unrelated variables in the economic system.
III.
EMPIRICAL REVIEW
1. Export and economic growth
Numerous articles on the correlation between trade and growth have been written
and large numbers of those studies established positive relationship between exports
expansion and economic growth. There are several influential studies that provide a
useful framework for analyzing the relationship between exports and economic growth,
i.e., Baldwin and Forslid (1996), Feenstra (1990), Segerstrom, Anant and Dinopoulos
(1990), Grossman and Helpman (1990), and Rivera-Batiz and Romer (1991). The basic
idea of this literature is that exports increase total factor productivity because of their
impact on economics of scale and other externalities such as technology transfer,
improving skills of workers, improving managerial skills, and increasing productive
capacity of the economy. Another advantage of export-led growth is that it allows for a
better utilization of resources, which reflects the true opportunity cost of limited
resources and does not discriminate against the domestic market.
There are also many studies analyzing the role of exports in the economic growth
specifically for developing countries. Most of these studies conclude that there is a
26

27. positive relationship between exports and economic growth, for example, Balassa (1978
and 1985), Jung and Marshall (1985), Ram (1985 and 1987), Chow (1987), Shan and Sun
(1988), Bahmani-Oskoee, Mohtadi and Shabsigh (1991), Bahmani-Oskoee and Alse
(1993), Jin (1995), Levin and Raut (1997), and Khalifa Al-Youssif (1997). Vohra (2001)
investigated the role of export-growth linkage in India, Pakistan, Philippines, Malaysia,
and Thailand respectively. Time series data for the period from 1973-1993 was used.
Most of this literature attributes the effects of exports on economic growth to several
factors. One of the key factors however is that exports promote thresholds effects due to
economies of scale, increased capacity utilization, productivity gains, and greater product
variety. It is also argued that exports of goods and services provide the opportunity to
compete in the international markets that leads to technology transfer and improvement
in managerial skills. Indeed, a recent review by Gunter, Taylor and Yeldan (2005)
concludes that any gains from trade liberalization are often associated with external
effects that are dynamic in nature.
Michaely (1977) finds an optimistic association sandwich between export and
growth of economics. Vohra (2001) investigated the role of export-growth linkage in
India, Pakistan, Philippines, Malaysia, and Thailand respectively. Time series data for the
period from 1973-1993 was used. The empirical results shows that exports have a
positive and significant impact on economic growth. Young (2002) found that export
growth is a positive contributor to economic development in low-income countries as
well as middle-income countries. Though, the impact is somehow stronger in middleincome countries than in low-income countries. Hadass and Williamson (2003) find the
empirical evidence between economic growths, terms of trade and exports over the
period 1870-1940. They find strong disassociation between economic growths, terms of
trade and exports. Abou-Stait, (2005) described that there are large numbers of empirical
studies that confirm the strong association between exports and economic growth.
2. Export led economic growth
The notion of trade as an engine of growth is given much emphasis by many
economists. The ideal that international trade brings economic growth increases the
27

28. welfare of a nation started during the 17th century by a group of merchants, government
officials and philosophers who advocated on economic philosophy known as
mercantilism. For a nation to become and powerful, it has to export more than it imports
where the resulting export surplus is used to purchase precious metals like gold and
silver. The government in its power has control imports and stimulates the nation’s
exports.
Adam Smith attacked the main mercantilist’s views and proposed the classical
theory of international trade based on the concept of absolute advantage model.
According to him, stock of human, man-made and natural resources rather than stock of
precious metals were the true wealth of a nation and argued that the wealth of a nation
can be expanded if the government would abandon mercantilist controls. In addition, he
showed that trade can make a nation better off without making another worse off (Debel
2002).
A model of comparative advantage was later articulated by David Ricardo to
replace the principle of absolute advantage. According to this model, a country will
specialized in the production of which it’s had in abundant and export the commodity i.e.
the commodity that it can produce at the lowest relative cost. Also, J.S. Mill formulated a
theory, the principle of reciprocal demand and later developed by Edgeworth and
Marshall. Both demand and supply conditions which determine the terms of trade and
hence trade between countries.
The proponents of the traditional theory of trade argues that trade can contribute
largely to the development of primary exporting countries. However, other economists
strongly believe that the accrual of the gains from international trade is biased in favour
of the advanced industrial countries and that foreign trade has inhibited industrial
development in poor nations. These economists contend that international trade as being
irrelevant for developing nations and the development process. There are two policies
adopted by many developing countries namely, import substitution and export promotion.
Portents of the view that trade brings development policies encourage outward
looking development policies (Export promotion). According to Todaro (1994), the
outward looking development policies “encourage not only free trade but also free
28

29. movement of capital, workers, enterprises and students, the multinational enterprises, and
open system of communication”.
In contrast, opponents of the traditional view advocate an inward-looking
development policy. This policy stresses the need for less developed countries to
implement their own styles of development and adopt indigenous technologies
appropriate to their resource endowment.
The factor endowment theory of Eli Hecksher and Berti Ohlin (H-O), of external
trade evolved. According to this theory, different relative proportions and countries have
different endowments of factors of production. Some countries have large amounts of
capital (capital abundant) while others have little capital and much labour (labour
abundant). This theory argued that each country has a comparative advantage in that
commodity which uses the country’s abundant factor. Capital abundant countries should
specialize in the production and export of capital-intensive goods while labour abundant
countries should specialize in the production and export of labour-intensive commodities.
This theory encouraged third world countries to focus on their labour and land intensive
primary product exports.
However, it was argued that by exchanging these primary products for
manufactured goods of the developed countries, third world nations could realize
enormous benefits obtained from trade with the richer nations. (Debel 2002)
Afxentiou and Serletis (1991) examine the validity of ELG in 16 industrial
countries. The study covers the period from 1950 to 1985. The countries included in the
sample are Austria, Belgium, Canada, Denmark and Finland. Others are Germany,
Iceland, Ireland, Japan and Netherlands. The rest are Norway, Spain, Sweden,
Switzerland, UK and US.
After testing for unit root and cointegration, vector autoregressve (VAR) model is
used to test for causality. Afxentiou and Serletis (1991) find no export –led growth in any
of the 16 countries. However, they find unidirectional causality from output growth to
export growth in Norway, Canada and Japan. The other causal relationship they find is
bidirectional causality in the US.
29

30. Marin (1992) presents a vector autoregressive (VAR) analysis of data for four
countries (Germany, United Kingdom, the United States and Japan). He uses quarterly
data for manufactured exports, the terms of trade, OECD output and labour productivity.
To verify whether exports and productivity have a long-run equilibrium relationship,
Marin (1992) performs preliminary tests for the cointegration. He finds no conclusive
evidence of cointegration between these two variables. However, he does find evidence
of a cointegrating relationship among exports, productivity and the terms of trade in the
United States, Germany and Japan. He tests for optimal lag-length of past information
using Beyesian Information Criterion (BIC). To determine the causal relationship
between exports and economic growth, he performs Granger-Causality test. His tests
support the export-led growth hypothesis for the four countries. However, he finds that
the “quantitative impact of exports on productivity is negligible” on the basis of the sum
of the autoregressive coefficients on lagged values of exports in the productivity
equation.
Al –Yousif (1997), tests the export-led-growth (ELG) hypothesis in four Arab Gulf
oil producing countries. These countries are Saudi Arabia, Kuwait, United Arab Emirates
and Oman. The study covers the period 1973 -1993.
In order to examine the relationship between exports and economic growth, Al –
Yousif (1997) estimates two models for each country. One of the models has basic form
of the production function while the other is a sectoral model.
To determine the long run relationship between exports and economic growth, Al –
Yousif (1997) performs cointegration. He finds no long –run relationship between
exports and economic growth. However, export is found to have positive and significant
impact on economic growth in all the countries. The Durbin –Watson and BrueschGodfrey statistics show no evidence of serial correlation. Again, he tests for structural
stability of the series using the Farely-Hininch test and finds that the growth equations for
the four countries are structurally stable. Finally, he performs a specification test using
White’s and Hausman’s specification tests and both models are found to be correctly
specified.
30

31. Ram (1985) investigates the role of exports in economic growth using the
production function model that treats exports as similar to a production input. His
objective is to shed new light on the relationship between exports and economic growth
using fairly standard models but employing larger data sets, focusing on certain specific
issues, and handling some econometric questions relevant to such empirical work. His
study adopts the specification used by Bala Balassa, William Tylor etc. He conducts the
investigation for 1960 -70 and 1970 -77 separately so as to determine whether the
importance of exports for economic growth increase over the 1970s.
Again, he takes a closer look at the differential in the impact of exports in the low income and the middle income LDCs for both periods, thus examining the widely held
belief that exports are probably not important for growth in the low-income LDCs. He
conducts a test to see whether the assumption of homoscedasticity is reasonable and
whether a single equation model is adequate. The results of the study indicate that export
performance is important for economic growth. Besides, the impact of export
performance on growth is small in the low-income LDCs over the period 1960 -70 but
the impact differential almost disappears in 1970 -77.
Finally, he used the test statistics proposed by White to test for heteroscedasticity
and other specification errors and the result indicates the absence of both problems.
Njikam (2003) tested for the ELG hypothesis in 21 sub-Saharan African countries.
These countries are Benin, Burkina Faso, Cameroon, Central Africa Republic, Cote
d’Ivoire, Democratic Republic of Congo (DRC) and Gabon. Others are Ghana, Kenya,
Madagascar, Malawi, Mali, Nigeria and Niger. The rest are Republic of Congo, Senegal,
Sierra Leone, Sudan, Tanzania, Togo and Zambia.
The study aims at: (a) testing the causal relationship between exports and economic
growth. (b) establishing the direction of causality if the relationship in (a) above exists
and (c), examining whether the direction of causality is reversed when countries change
from import –substitution strategy to exports promotion strategies.
To examine whether agriculture and manufactured exports cause economic growth
and vice versa in the above countries, Njikam (2003) employs autoregressive models.
The author tests for stationary on the series using the ADF test. The minimum final
prediction error (FPE) and Schwarz–Bayesian (SBC) Criteria are used by Njikam (2003)
31

32. to determine the optimum lag –length of past information. Again, he uses the Granger –
causality technique to determine the direction of causation.
To verify the direction of causation and to test the significance of the restricted
coefficients, Njikam (2003) uses the wald test (WT) and the likelihood ratio test (LRT).
He finds that, real GDP and real exports are stationary in all countries during the exports
promotion period. The optimum lag length for all variables is found to vary across
countries. In Burkina Faso, Cameroon, Cote d’Ivoire, DRC, Ghana, Madagascar, Malawi
and Zambia, unidirectional causation is found from agricultural exports to economic
growth. In Cameroon, Mali and Malawi however, he finds unidirectional causation from
manufactured exports to real GDP growth.
Again, the author finds unidirectional causation from real GDP to agricultural
exports in Mali, Nigeria, Kenya, Senegal and Tanzania. Besides, he finds unidirectional
causation from real GDP to manufactured exports in Benin, Cote d’Ivoire, Gabon,
Ghana, Madagascar and Togo. This implies that total export growth depends on the
economic growth in these countries.
Finally, bidirectional causation between agricultural exports and economic growth
is found in Burkina Faso, DRC and Madagascar. This therefore leads to an acceptance of
the ELG and the economic growth led export hypotheses in these countries.
To conclude, it can be deduced from the above studies that most of the authors saw
the need to adopt time series approaches because the question on export –led growth is
essentially dynamic one. However, the results remain mixed and ambiguous. This may be
due to either specification bias or exclusion of import or different time periods. This
thesis corrects these problems.
32

33. 33

34. A research methodology is a framework or blueprint to conduct a research project;
it details the procedures necessary to carry out a research and answer decision regarding
what, when, where, how to do a particular research work. For any research work to be
conducted in a scientific way, it is necessary to have a method through which information
will be obtained or collected and variables will be analysed and measured. Therefore, this
chapter seeks to explain the sample size, the procedures and method employed in data
analysis of the study.
I.
UNIVERSE
In the methodological language, the universe is defined as the place where relevant
data is collected. Selection of the universe is very important in a research study as it
provides more accuracy and precision. In statistical sense, the tern “universe” means the
aggregate of person or objective of study. Universe is theoretical or hypothetical
aggregation of all elements as defined for a given research (Babbie, 2001. In this optic,
the universe has been made simple considering the countries which are considered as the
pillar of ECOWAS economy with the highest annual GDP (More than US$ 20 Billion).
Thus, out of fifteen countries members of ECOWAS, only three countries having GDP
over US$ 20 billion have been selected as universe of the study according World Bank
data, 2011. Those countries are namely; Cote d’Ivoire, Ghana and Nigeria. These three
country together represent 67% of ECOWAS total population, 82% of ECOWAS total
GDP, and 89% of ECOWAS total exports value.
II.
SAMPLE DESIGN
The selection of the research sample has important consequences on the validity of
research findings (Vaus, 2001). The major purpose of conducting a research is to be able
to make some claims about the larger population. Therefore, it is essential to choose a
sample that enable to generalise findings to the larger population. In order to represent
the population, the sample size of 31years has been drawn from 1980 to 2011.
34

35. III.
DATA
1. Data collection
In this study, the data used are purely obtained from secondary sources. Secondary
data are data which have been already collected by someone or an organisation. For this
study, data have been sourced only from World Bank Databank for the time period
ranging from 1980 to 2011.
2. Data analysis
Once data has been collected, the next step usually involves the analysis of those
data. The choice of analytical procedure depends on several factors, including type of
research question which was asked originally and the characteristics of the data which
was collected (Sowel & Casey, 1982). So for the study, Simple linear regression model
and the ordinary least squares technique have been used as an analytical technique for
parameters estimation. Minitab statistical software has been used for computation
analysis.
IV.
MODEL SPECIFICATION
The model employed in this study is simple linear regression models. The model is
expressed as follows:
GDP = f (Export)
(1)
Symbolically equation (1) can be expressed as follow:
G = α + βExp + µ
(2)
Where;
G: GDP growth rate (annual gross domestic product growth rate in %age),
Exp: exports as %age of gross domestic product,
α: Intercept,
35

36. β: coefficient (β>0),
µ: stochastic term (shows effect of the other factors).
Equation (2) states that the impact of exports on economic growth expected to be
positive.
Several empirical studies reveal that exports contribute to GDP growth more than
just the change in the volume of exports. Many researchers, highlighting many beneficial
aspects of exports, such as greater capacity utilization, economies of scale, incentives for
technological improvements and efficient management due to competitive pressures
abroad (Balassa, 1978; Al-Youssif, 1997). Voivodas, (1973) and Ram, (1987) described
that trade, particularly exports, may encourage competition. According to Salvatore and
Hatcher (1991) exports is a key explanatory variable contributing in the process of
economic growth. Thus, an increase in exports expected to promote economic growth
and expand market for the domestic producers and forces them to be more efficient in the
wake of increased competition. Therefore, this study hypothesises positive relationship
between exports and economic growth.
36

37. 37

38. I.
PRESENTATION OF RESULT
1. Results for Cote d’Ivoire
 The regression equation is: G = - 2.16 + 0.074 Exp (a)
Predictor
Coef
SE Coef
T
P
Constant
-2.161
4.179
-0.52
0.609
Exp
0.0740
0.1024
0.72
0.475
Table 1
S = 3.70233 R-Sq = 1.7% R-Sq (adj) = 0. 0%
 Analysis of Variance
Source
Regression
DF
SS
MS
1
7.17
7.17
Residual Error
30
411.22
31
0.52
P
13.71
Total
F
0.475
418.39
Table 2
38

39. 2. Results for: Ghana
 The regression equation is: G = 0.66 + 0.150 Exp
Predictor
Coef
Constant
(b)
SE Coef
T
P
0.659
0. 49
0.630
0.14981
Exp
1.356
0.04933
3.04
0.005
Table 3
S = 3.40208 R-Sq = 23.5% R-Sq (adj) = 21.0%
 Analysis of Variance
Source
Regression
DF
SS
MS
1
106.76
106.76
Residual Error
30
347.22
31
9. 22
P
11.57
Total
F
0.005
453.99
Table 4
39

40. 3. Results for: Nigeria
 The regression equation is: G = 19.9 + 0,576 Exp
Predictor
Coef
(c)
SE Coef
T
P
Constant
19.935
1.101
18.10
0.000
Exp
0. 5759
0.1875
3.07
0.004
Table 5
S = 5.18456 R-Sq = 23.9% R-Sq (adj) = 21.4%
 Analysis of Variance
Source
Regression
DF
SS
MS
1
253.62
253.62
Residual Error
30
806.39
31
9.44
P
26.88
Total
F
0.004
1060.01
Table 6
40

41. II.
INTERPRETATION & DISCUSSION OF RESULTS
Empirical results of this study are given for Cote d’Ivoire in Table 1, and Table 2,
for Ghana in Table 3 and Table 4 and for Nigeria in Table 5 and Table 6 respectively.
1. Cote d’Ivoire
From the Table 1, the positive sign of the coefficient shows a positive relationship
between the explanatory variable (Exp) and the response (G), it means that both exports
and GDP move in the same direction. And the regression equation (a) indicates that the
export coefficient is 0.074; it means that if exports increase by 1%, the GDP of Cote
d’Ivoire will also increase by 0.074% on average when all other factors are held constant,
vice versa.
However, the ANOVA Table 2 shows that the F statistic is equal to 7.17/13.71 =
0.52. The distribution is F (1, 30), and the probability of observing a value greater than or
equal to 0.52 is greater than 0.01, so the evidence that β is not equal to zero is very less.
Similarly, F-test tells that Exports do not explain a larger part of the variance observed in
GDP compared to the null model (intercept only). Therefore, the significant quantity of
Exports is less in the GDP variability.
In the other side, the R-Square term is equal to 0.017, indicates that 1.7% of the
variability in GDP is explained by Exports.
2. Ghana
By analysing the Table 3, the positive sign of the coefficient shows a positive
relationship between the explanatory variable (Exp) and the response (G), it means that
both exports and GDP move in the same direction. And the regression equation (b)
indicates that the export coefficient is 0.165; it means that if exports increase by 1%, the
GDP of Ghana will also increase by 0.165% on average when all other factors are held
constant, vice versa.
Nevertheless, the ANOVA Table 4 shows that the F statistic is equal to
106.76/11.57 = 9.22. The distribution is F (1, 30), and the probability of observing a
41

42. value greater than or equal to 9.22 is less than 0.01, so there is strong evidence that β is
not equal to zero. Similarly, F-test tells that Exports explain a larger part of the variance
observed in GDP compared to the null model (intercept only). Therefore, the significant
quantity of Exports is strong in the GDP variability.
In the other side, the R-Square term is equal to 0.235, indicates that 23.5% of the
variability in GDP is explained by Exports.
3. Nigeria
From the analysis of the Table 5, the positive sign of the coefficient shows a
positive relationship between the explanatory variable (Exp) and the response (G), it
means that both exports and GDP move in the same direction. And the regression
equation (c) indicates that the export coefficient is 0.165; it means that if exports increase
by 1%, the GDP of Nigeria will also increase by 0.165% on average when all other
factors are held constant, vice versa.
Nevertheless, the ANOVA Table 6 shows that the F statistic is equal to
253.62/26.88 = 9.44. The distribution is F (1, 30), and the probability of observing a
value greater than or equal to 9.44 is less than 0.01, so there is strong evidence that β is
not equal to zero. Similarly, F-test tells that Exports do explain a larger part of the
variance observed in GDP compared to the null model (intercept only). Therefore, the
significant quantity of Export is very strong in the GDP variability.
In the other side, the R-Square term is equal to 0.239, indicates that 23.9% of the
variability in GDP is explained by Exports.
42

43. 43

44. I.
SUMMARY OF FINDINGS
A sample size of thirty six years (31) that ranged from 1980 to 2011 had been used
in this study to examine the impact of export on economic growth of ECOWAS
countries. The method of OLS regression has been adopted in carrying out the research
work. It was found that there is positive relationship between exports and GDP for all the
countries of study. Overall results found are statistically significant and support the study
hypothesis even though the significant in Cote d’Ivoire case was less.
Table 1 show that the impact of exports found positively significant and the
coefficient size of this variable found 0.074; in this case one percent change in exports
will change economic growth of Cote d’Ivoire by 0.074 percent. It means that due to
promotion of exports, economic growth of Cote d’Ivoire would increase. Table 3 reveals
that the impact of Ghana’s exports on economic growth found positively significant at
1% level of significance. The coefficient size of this variable found 0.165; in this case
one percent change in exports will change economic growth of Ghana by 0.165 percent.
Table 5 reveals that the impact of Nigeria’s exports on economic growth found positively
significant at 1% level of significance. The coefficient size of this variable found 0.576;
in this case one percent change in exports will change economic growth of Nigeria by
0.576 percent. The positive significant results of exports on economic growth also have
been found by (Khan and Saqib, 1993; Ruppel, 1997; Gopinath and Vasavada, 1999;
Abou-Stait, 2005; Chiara and Subash 2009).
In a comparative view, Nigeria comes first with the highest exports coefficient size
of the study (0.576) followed by Ghana (0.165) and Cote d’Ivoire which has the lowest
(0.074).
Therefore, it is found that the economic grow of Nigeria lies strongly on its exports.
This fact can be explained by the fact that export of agriculture, petroleum and petroleum
products are the main GDP contributors.
Similarly, Exports have also significant impact on the economic growth of Ghana as
the country economy is based on exports of mining, agriculture and recently petroleum
and petroleum products.
Unlike Nigeria and Ghana, exports growth impacts lightly on the economy of Cote
d’Ivoire. Its economy is mainly based on exports of agricultural commodities and
44

45. products, although the country tries to diversify its economy the fluctuation of
commodities prices affect its exports.
II.
CONCLUSION
Drawing from the empirical investigation into the impact of exports on economic
growth of ECOWAS pillar countries using GDP as the dependent variable and Exports as
independent variables from 1980 to 2011, it emerged from the study that there is
significant relationship between exports and GDP even though that relationship is not
equally observed in all the countries. The main objectives of this study are to analyze
empirically the impact of exports on economic growth of selected countries of ECOWAS
i.e. Cote d’Ivoire, Ghana and Nigeria. The impacts of exports on economic growth found
are statistically significant in this study during the study period. The positive impact of
exports on economic growth demonstrates that expansion in exports is highly important
for the encouragement of desirable level of economic development in all selected
countries. However, it has been observed from the empirical results that impact of
exports on economic growth for both the countries i.e. Ghana and Nigeria are high if
compared with the results of Cote d’Ivoire.
Finally, we can say that exports have significant impact on economic growth.
Therefore, it is obvious that increase in exports represents improvement in economic
development of a country and expansions in exports improve social welfare of people.
The rapid growth economies are usually characterized by speedy expansion in exports.
III.
RECOMMENDATIONS
Based on the findings of this study, it is important to provide a set of policy
recommendation that would be applicable to the ECOWAS economy.
1. The Governments should come together to establish a regional export promotion
council to provide help to exporter.
45

46. 2. The governments should encourage more private company participation in
industrialisation so that of manufacturing products will increase.
3. Security should be boosted on the high sea where crude oil products are being
smuggled. This will help reduce the loss from illegal export of crude oil products.
4. Government should give immediate attention to the indigenous of the region where
crude oil is being extracted from. This will reduce the unrest in the region in Nigeria.
5. Government should increase intra-ecowas trade in order to foster regional growth.
6. Government should improve on fighting corruption, arrest and prosecute corrupt public
office holders.
7. Stay apace with changing consumer preferences through continual introduction of new
and innovative products.
8. Reduce costs in order to stave off competition from elsewhere.
Thus, findings of the present study suggest that the policy makers of each country
included in this study needs to expand volume of exports in order to boost socioeconomic development.
46

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48

49. APENDIX
Appendix 1
Cote d'Ivoire
Year
GDP
EXPORT
1980
-10,9576973 35,00162933
1981 3,500498907 35,17500349
1982 0,200822352 36,42322868
1983
-3,90024044 36,95985992
1984
-2,70126143
45,3119277
1985 4,501223175 46,77491298
1986 3,259348768 39,49590841
1987
-0,34897291
33,4299902
1988 1,136483964 30,48812849
1989 2,948004944 32,03333564
1990
-1,09590841 31,68987467
1991 0,040925169 30,01172635
1992
-0,24456061 31,90948693
1993
-0,1924851 29,44245287
1994 0,811206686 40,52740186
1995 7,125744724 41,75929966
1996 7,729327422 41,10099509
1997 5,719058597 41,41979922
1998 4,752475248 39,41334819
1999 1,586447579
40,3505368
2000
-3,70020469 40,42768347
2001
-0,02123047 41,84292571
2002
-1,43080815 50,02829421
2003
-1,55536466 45,83661086
2004 1,793855153
48,5557976
2005 1,255967958
51,0520459
2006 0,683970709 52,65058265
2007 1,714671732
47,81593
2008 2,330000001 46,51204624
2009
3,74999317 42,19507198
2010 2,394382751 40,64433533
2011
-4,72876051 43,74003291
49

50. Appendix 2
Ghana
Year
1980
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
GDP
0,471695792
-3,50306747
-6,9236503
-4,56373772
8,647569256
5,091617972
5,199160071
4,794898732
5,628169742
5,085872512
3,328818229
5,28182614
3,87941917
4,850000004
3,299999997
4,112418933
4,602460964
4,196357871
4,700390794
4,399996543
3,699999997
4,000000001
4,500000002
5,199999999
5,599999996
5,90000385
6,4
6,45973558
8,430504083
3,991472578
8,008593189
14,38915072
EXPORT
8,466349346
4,755872469
3,338307266
5,555918086
8,044013277
10,65443227
16,5760499
19,66260909
18,1834227
16,7426186
16,87790419
16,96352652
17,22593952
20,25393002
25,25863645
24,49644054
32,11218067
32,410294
33,87135219
32,0783392
48,8022588
45,23301641
42,61625245
40,67904228
39,30332529
36,44921695
25,19271703
24,52500232
25,02942973
29,2910887
29,4046672
38,01511594
50

51. Appendix 3
Year
1980
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
Nigeria
GDP
EXPORT
14,69700373 -4,32583988
13,42787919 -4,41154627
14,32878225 -4,63765456
16,13707597 4,797966709
17,79598654
4,36960008
16,75926383 -11,3563166
15,30968767 8,435310068
16,5561591 -0,51823533
16,36907542 1,481486165
16,65948593 11,76370596
17,14942342 -1,85267599
18,2364305 1,616062863
15,43397512 8,333260143
15,83832257 -2,13940343
23,00623035 0,912162051
21,11179665 6,209004782
20,03381013 3,218406372
26,11792116 6,761093862
24,78636454 6,033114132
26,45091077 6,734813031
26,78220132
3,2
33,296959
12,1
31,87500922 4,153318941
26,42133041 7,441394993
25,37520649 2,185520239
25,62191208
6,07979435
32,11269483 5,300000005
26,17518248 4,299999999
29,19979338 5,000000003
23,74235961 4,499999997
25,99418375 5,800000001
25,13034467
2,7
51

52. Appendix 4
ECOWAS in green
52