exports and economic growth in ecowas : evidence … · 2016. 3. 11. · diversifying export...
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UNITED NATIONS NATIONS UNIES
AFRICAN INSTITUTE FOR ECONOMIC DEVELOPMENT AND PLANNING
INSTITUT AFRICAIN DE DEVELOPPEMENT ECONOMIQUE ET DE PLANIFICATION
(IDEP)
By
Mohammed M. SHERIF
Submitted in partial fulfilment of the requirements for the award of Master of Arts
Degree in Economic Policy and Management at the UN African Institute for
Economic Development and Planning (IDEP)
Supervisor: Dipo T. BUSARI (PhD)
April, 2008
EXPORTS AND ECONOMIC GROWTH IN ECOWAS :
EVIDENCE FROM POOLED DATA ANALYSIS
i
ii
DEDICATION
This research work is dedicated to my beloved wife Mrs. Fanta S. Sherif and my
Children: Makanvine M. Sherif, Manyamoe M. Sherif and Abubakar M Sherif Jr.
iii
ACKNOWLEDGEMENT
All praise are due to Allah the most merciful, the most beneficent, the king of all kings
and master of the Day of Judgment whom by his infinite mercy bestowed upon me the
ability and wisdom to start and complete this research work successfully. First and
foremost, I'm very grateful to my able supervisor Dr. Dipo T. Busari (MA Coordinator)
who patiently accommodated my behaviors and me during the course of the research
work. Further, I must extend my sincere thanks and appreciations to him for his tireless
efforts in guiding me in the right path through out the stages that led to the successful
completion of this research work. My gratitude goes to the Director, the Deputy Director,
Administrator, professors and the entire staff of UNIDEP for their guidance and supports.
Words are inadequate to express my sincere thanks and appreciations to Dr. Toga G.
McIntosh (Minister of Planning and Economic Affairs) for securing the sponsorship for
my MA degree programme. Through God the Almighty and him, I found myself where I
am today. Further, I would like to sincerely express my gratitude to the entire steering
committee of the Liberia Emergency Capacity Building programme for their supports.
Over and above, I salute the government of Liberia for all the supports. My special
thanks and appreciations also go to Mr. Wilmot Reeves (National Economist, UNDP-
Liberia), Monique Cooper (Pro poor Economist, UNDP-Liberia) and Mr. Alusine Sheriff
(Data Analyst UNDP-Liberia) for accommodating me and my behaviors in ensuring that
the fees of my studies are paid on time.
I would like to express my profound thanks and appreciations to my parents Mr. Mulibah
Sherif (late) and Mrs. Ma-Nyamoe Kamara(late) whose means, I was brought to this
wonderful world for their good will prayers. My special and lovely recognition go to my
wife for being there for me through out the entire research work. Her insightful
comments and suggestions are worth mentioning.
It will be unfair if I failed to acknowledge the significant role my friends and colleagues
played during the course of this research work. I offer my heartfelt gratitude to all my
colleagues of the 2006/2007 MA Trainees for their very useful suggestions and
comments; to name but few: Angella Rwabutomize (Uganda), Evans Nyako Abosi
(Ghana) and Esther Nakayima (Uganda), Mamade Conde (Guinea), Oui Karim Diakite
(Cote D’Ivoire), Houdomta Momtamra (Chad), Kossi Sogpho (Togo), Amadu Gueye
(Senegal), Papa Layte (Senegal) and Malami Sadio (Senegal). Gratitude goes to my
mentor Mr. Sekou B. Korleh (Purchasing Manager, Free Port of Monrovia). His words of
courage and instrumental role for obtaining my sponsorship cannot be quantified. Hey! I
almost forgot; many thanks and appreciations go to my friend (Dad) Sheikh M.A Swaray
for his useful suggestions and comments. Also, I recognized the significant role played
by my friend Mohammed F. Konneh in the entire research work. Omaru F. Siryon
(Aston University, UK), thank you very much for your contribution. Gratitude to all that
played a part in this research work but were not mentioned. Finally, I take full
responsibility for whatever mistakes or error that maybe in this research work.
iv
Abstract
Over the years, there has been little or no structural transformation in ECOWAS’
exports. The domination of these exports by primary commodities and their low
international prices continue to make economies of the region more unstable and
vulnerable to external shocks. The share of ECOWAS in world trade remains very
insignificant.
This paper therefore uses Pooled fixed effects estimation methods to examine the impact
of exports on economic growth in ECOWAS from the period 1987 to 2004. The results
suggest that significant negative impacts of exports on economic growth are robust
empirical results. These results confirm the Prebisch (1959) and Sachs et al. (1995)
significant negative impacts of primary products exports on economic growth. The
findings also suggest that physical capital, labor, exchange rate and terms of trade are
important determinants of growth in the region. Human capital plays a negative role
indicating inadequate mechanisms to absorb the technologies associated with exports.
Free Trade Area plays a negative role reflecting loose nature of trade integration in the
region’s FTA. Finally, the study recommends that member states redirect efforts towards
diversifying export products to knowledge-based products, build the region’s human
resources and incorporate into their national plans not by mere signing but by full
implementation of the various trade agreements to foster a larger regional market.
v
RESUME
Au fil des ans, les exportations de la CEDEAO ont connu peu, voire aucune
transformation structurelle. Le fait que ces exportations soient dominées par des produits
de base, de même que leur faible prix au niveau international contribuent à rendre les
économies de la sous région instables et vulnérables aux chocs externes. La part de la
CEDEAO dans le commerce international est infime.
Cet article utilise les méthodes d’estimation à effets fixes groupés, afin d’étudier
l’impact des exportations sur la croissance économique de la CEDEAO de 1987 à 2004.
Les résultats suggèrent que l’impact négatif important des exportations sur la croissance
économique se traduit par de solides résultats empiriques. Ces résultats confirment
l’impact négatif significatif des exportations des produits de base sur la croissance
économique, tel que souligné par Prebisch (1959) et Sachs-Warner (1995). Les résultats
suggèrent également que le capital physique, la main d’œuvre, le taux de change et les
termes de l’echange sont des déterminants importants de la croissance dans la sous
région. Le capital humain joue un rôle négatif qui indique la présence de mécanismes
inappropriés d’absorption des technologies associées aux exportations. Les zones de
libre -échange ont un rôle négatif qui est une indication de la nature relâchée de
l’intégration commerciale dans la zone de libre-échange de cette région. Enfin cette
étude recommande que les Etats membres réorientent leurs efforts vers la diversification
des produits d’exportation en produits impliquant du savoir, qu’ils renforce les
ressources humaines de cette région et l’intègrent dans leurs plans nationaux, non pas
simplement en y apposant leur signature, mais en mettant totalement en œuvre les
différents accords commerciaux afin de favoriser l’émergence d’un marché régional
plus large.
vi
EXECUTIVE SUMMARY
Export of goods and services exploit the opportunities to create high rate of economic
interactions with the rest of the world. This speeds the absorption of frontier
technologies, world best practices, and increasing returns to scale. Exports are also
considered to be source of foreign exchange earnings. Grossman et al (1991) asserted that
technological spillovers could come through imports and exports.
There has been little or no structural transformation in the export commodities of West
Africa. About 90 percent1 of these exports are primary commodities and their low
international prices have over the years made economies of the region more vulnerable in
the multilateral trading system. The multilateral trading system is directly or indirectly
compelling countries to adopt the doctrine of comparative advantage (liberalized
economies). Traditionally, West Africa has comparative advantage in primary
commodities, so that free trade implies it exports more of these primary commodities,
and imports more of manufactured commodities.
In terms of trade flow, trade between ECOWAS and the rest of Africa was steady around
29 percent of total exports and imports from 1996 to 2001. However, intra-ECOWAS
trade was very sluggish, registering the least rate of 24 percent of total value of exports
and imports. There were some sort of equilibrium in trade between ECOWAS and the
rest of Africa, but significant disequilibrium in trade between ECOWAS and countries
outside Africa, registering 154 percent (see figure 2.4 in chapter two). Imports into
ECOWAS constitute bulk of the total trade with countries outside Africa. This reflects
that countries in ECOWAS are more dependence on imported commodities (in most
cases consumer goods). Also the region’s trade integration is loose. Exports in the region
have been concentrated on the following primary commodities: petroleum, cocoa or
beans, gold, cotton, boxile, woods, café and iron ore.
Average growth rate of GDP per capital in ECOWAS has been fluctuating around the
neighborhood of negative 1 percent from 1987 to 2 percent in 2003; and the average
growth rate of export has also been fluctuating from negative 0.4 percent in 1988 to 15
percent in 1997 and from 3 percent in 1998 to 11 percent in 2003. On the whole,
ECOWAS average growth rate of GDP per capital from 1987 to 2004 stood at 0.4
percent, third highest among the five African regional organizations (see annex 2). The
fluctuations in the growth rates reflect poor economic performance in the region and are
largely influenced by external and internal factors. The internal factors include the
prolonged civil unrest in the region during the earlier parts of the 1990s particularly in
Liberia, Sierra Leone, Guinea and Cote d Ivoire respectively; and mono culture
production with no value added. The external factors include the low international prices
for the primary commodities produced by the region; the Asian crisis that affected world
demand and supply; and the wait and see attitudes of development partners in releasing
1 The data were extracted from the official websites of ECOWAS, UNCOMTRADE and the works of Remi
Lang of UN Economic commission for Africa and O. J. Nnanna of the West African Monetary Institute in
Accra, Ghana.
vii
official development assistance to the region. On the overall, economies in the region
remained stagnant; hence the following concerns are raised: Have the fluctuations in the
export of goods and services negatively or positively affected growth in the region over
the period under review or are there some institutional factors responsible for the
persistent economic stagnancy? This paper addresses these concerns and the objective of
the study is to examine the impact of exports on Economic growth in ECOWAS from
1987 to 2004.
The period 1995 to 2004 registered an average current account balance of negative 6.6
percent of GDP in ECOWAS compared to Africa average of negative 1.2 percent of
GDP. ECOWAS registered the second highest current account deficit among the regional
organizations in Africa after CEMAC (negative 15.4 percent). In terms of fiscal balance,
The average budget deficit in ECOWAS for the period 2000 to 2003 was negative 4.4
percent of GDP and for 2004 the average stood at negative 2.4 percent of GDP as
compared to Africa average of negative 1.7 percent from 2000 to 2003 and negative 0.5
percent in 2004 (see table 2.2 and annex 2). ECOWAS registered the third best
performance in terms of fiscal balance from 2000 to 2003 after SADC that registered
negative 3.1 percent of GDP during the same period. In 2004, ECOWAS became second
best performer after CEMAC that registered a surplus of 3.2 percent of GDP. On the
average, the inflation rate in ECOWAS from 1990 to 2004 was 11.2 percent, the second
best performer in Africa after CEMAC that registered 4.4 percent on average. The
average inflation in ECOWAS was 7 percentage point lower than Africa’s average of
18.9 percent during the same period.
Many theoretical and empirical results show that the relationship between exports and
growth still remains a subject of controversy. This has further created an open debate on
the subject and this paper is motivated by the open debate. The study relies on the theory
of International trade which dates back to Adam Smith, David Ricardo, James Mill and
John Stuart Mills. Adam Smith’s theory states: a country H (Home) is said to have
Absolute Advantage over country F (Foreign) in the production of commodity X if the
required unit of labor to produce commodity X in home country is less than the required
unit of labor to produce commodity X in the foreign country. In addition, if the marginal
productivity in producing X in home country is greater than the marginal productivity of
producing X in foreign country. In this theory, the basis for trade is labor productivity.
David Ricardo considered the above theory as over generalization. He further asserted
that when a country has absolute advantage in producing the two commodities as claimed
by Adam Smith, than there is no need for trade. This is the limitation of the Adam Smith
theory. To account for this limitation, Ricardo now said that even when a given country
has absolute advantage in producing the two commodities there should be basis for trade.
He redefined the theory to Comparative Advantage. That is, each country specializes in
what it has comparative cost advantage in. In this theory, emphasis is on specialization.
Grossman et al (1991), Matsuyama (1992), and Walde et al (2005), concluded that the
effects of exports on growth have shown to be positive or negative under different
circumstances.
viii
Pooled fixed effects estimation methods were used and the results suggest that negative
effects of exports on growth are robust empirical results. This is in part due to the low
international prices for the region’s export products that have over the years made it
unstable and more vulnerable to external shocks. The result confirms the Prebisch (1959)
and Sachs et al. (1995) significant negative impact of primary products exports on
economic growth. It is also broadly consistent with the results of Sohn’s et al. (2006)
statistically significant negative impact of natural resource exports on growth. Gross
fixed capital formation as proxy for physical capital, labor, exchange rate and terms of
trade proved to be important determinants of growth. Free Trade Area plays a negative
role showing the loose nature of trade integration in the region’s FTA; gross secondary
school enrollment as proxy for human capital also plays a negative role indicating
inadequate mechanisms to transfer or absorb the technologies associated exports.
The study conducted sensitivity analyses on the original model in order to ascertain
whether the variable of interest, real exports to GDP ratio is robust to the exclusion of
certain conditioning variables (factor input variables of physical capital, human capital
and labor). Though factor inputs of gross fixed capital formation (proxy for physical
capital) and total labor proved to be important determinants of growth in the region
during the period under review, the results indicated that exclusion of these variables do
not significantly affect the signs and magnitudes of real exports to GDP ratio in the
region. Hence, the variable remains robust at five percent level of significance implying
that physical capital, human capital and labor did not jointly drive real exports to GDP
ratio over the period under review. Similarly, the study conducted the second test by
adding factor input variables (physical capital, human capital and labor) one at a time in
order to further ascertain the contribution of each factor input to the signs and magnitudes
of real exports to GDP ratio (from column two through five in table 4.8). The test results
indicated that among the three factor-input variables, only total labor drove exports to
GDP ratio over the period under review (see table 4.8). This implies that the region
exports were labor intensive.
The study recommends that member states redirect their efforts to diversifying export
products to knowledge based products. However, private sectors should be actively
involved in the diversification programme and also the process should be complemented
by other none trade factors such as sounds macroeconomic policies, institutional
framework, and so forth. The study further recommends that in order to derive the
technological transfers associated with exports, member states should exert efforts in
building the human resources of the region and improve the mechanisms necessary to
ease the transfers of technologies and learning-by-doing. Member states should also
incorporate not by mere signing but by implementing agreements governing free trade
area. This will create the facilities and mechanisms necessary to expedite the free
movements of goods and services in ECOWAS. It will also create an expanded market
which can allow for economic of large scale production (trade creation), fostering of
specialization, attracting foreign direct investment (FDI) and having access to other larger
markets.
ix
TABLE OF CONTENT Pages
DEDICATION ............................................................................................................................................... I
ACKNOWLEDGEMENT ......................................................................................................................... III
ABSTRACT.................................................................................................................................................. IV
RESUME ....................................................................................................................................................... V
EXECUTIVE SUMMARY ........................................................................................................................ VI
LIST OF FIGURES, TABLES AND ANNEXES ...................................................................................... X
LIST OF ACRONYMS AND ABBREVIATIONS .................................................................................. XI
CHAPTER ONE GENERAL BACKGROUND ........................................................................................ 1
1.1 INTRODUCTION............................................................................................................................. 1 1.2 STATEMENT OF THE PROBLEM ..................................................................................................... 2 1.3 OBJECTIVE OF THE STUDY ............................................................................................................ 3 1.4 JUSTIFICATION AND SIGNIFICANCE OF THE STUDY ....................................................................... 3 1.5 ORGANIZATION OF THE STUDY ..................................................................................................... 4
CHAPTER TWO TRADE AND ECONOMIC PERFORMANCE IN ECOWAS ................................. 5
2.1 OVERVIEW ................................................................................................................................... 5 2.2 MACROECONOMIC PERFORMANCE IN ECOWAS (1987 – 2004) .................................................. 6 2.3 RECENT EFFORTS TO FOSTER ECONOMIC INTEGRATION THROUGH TRADE .................................14
CHAPTER THREE REVIEW OF LITERATURE .................................................................................16
3.1 THEORETICAL PERSPECTIVE........................................................................................................16 3.2 EMPIRICAL PERSPECTIVE .............................................................................................................19
CHAPTER FOUR METHODOLOGY, RESULTS AND DISCUSSIONS ...........................................22
4.1 DATA CHARACTERISTICS AND SCOPE OF STUDY ..........................................................................22 4.2 THEORETICAL SOURCE FOR MODEL SPECIFICATION ...................................................................22 4.3 MODEL SPECIFICATION AND ESTIMATION TECHNIQUES..............................................................24 4.4 HYPOTHESIS OR RESTRICTION .....................................................................................................26 4.5 VARIABLE DEFINITIONS AND JUSTIFICATIONS .............................................................................26 4.6 RESULTS, DISCUSSIONS AND DIAGNOSTIC TESTS ........................................................................29
4.6.1 Stationary Test .......................................................................................................................29 4.6.2 Specification Test ...................................................................................................................30 4.6.3 Diagnostic Tests ....................................................................................................................31 4.6.4 Pooled regression Results and Discussions ...........................................................................33 4.6.5 Sensitivity Analysis ................................................................................................................38
CHAPTER FIVE POLICY RECOMMENDATIONS AND CONCLUSION .......................................40
5.1 SUMMARY OF FINDINGS ..............................................................................................................40 5.2 POLICY RECOMMENDATIONS .......................................................................................................41 5.3 AREAS OF FURTHER RESEARCH AND LIMITATIONS OF THE STUDY ...............................................42 5.4 CONCLUSION ...............................................................................................................................43
REFERENCES ............................................................................................................................................44
ANNEXES ....................................................................................................................................................47
x
LIST OF FIGURES, TABLES AND ANNEXES
Pages
A: FIGURES
FIGURE 2.1: AVERAGE GROWTH RATE OF REAL GDP PER CAPITAL VS AVERAGE GROWTH RATE OF REAL
EXPORTS ................................................................................................................................................ 7
FIGURE 2.2: AVERAGE CURRENT ACCOUNT BALANCE IN ECOWAS: 1995 – 2004 .................................... 9
FIGURE 2.3: ANNUAL AVERAGES OF CPI INFLATION IN ECOWAS: 1990 - 2004 .......................................11
FIGURE 2.4: INFLOW AND OUTFLOW OF TRADE IN ECOWAS: 1996 – 2001 ...............................................12
FIGURE 2.5: TREND OF AVERAGE TERMS OF TRADE IN ECOWAS .............................................................13
B: TABLES
TABLE 2.1: SECTORAL SHARE IN GDP AT CURRENT PRICES IN ECOWAS: 2000 -2004............................. 8
TABLE 2.2: FISCAL BALANCE IN THE ECOWAS SUB-REGION (% OF GDP) ..............................................10
TABLE 4.1: EXPECTED SIGNS AS DICTATED BY THEORY ............................................................................26
TABLE 4.2: RESULTS OF THE UNIT ROOT TESTS .......................................................................................30
TABLE 4.3: F-TEST RESULTS FOR EXCLUSION OF CONTROLLED VARIABLES ..............................................31
TABLE 4.4: BREUCH-GODFREY LM TESTS FOR CROSS-SECTIONAL HETEROSKEDASTICITY AND CROSS-
SECTIONAL CORRELATION ....................................................................................................................32
TABLE 4.5: TWO-WAY REDUNDANT FIXED EFFECTS TEST (CROSS-SECTION & PERIOD) ...........................32
TABLE 4.6: HAUSMAN CORRELATED RANDOM EFFECTS TEST (CROSS-SECTION & PERIOD) .....................32
TABLE 4.7: EXPORTS AND GROWTH IN ECOWAS: POOLED FIXED EFFECTS ESTIMATES ..........................33
TABLE 4.8: EXPORTS AND GROWTH IN ECOWAS: SENSITIVITY ANALYSIS .............................................38
C: ANNEXES
ANNEX 1: DATA DEFINITION AND SOURCES (1987 -2004) .......................................................................47
ANNEX 2: PERFORMANCE SCORE-CARD OF SOME REGIONAL GROUPINGS IN AFRICA ..............................48
ANNEX 3: PRINCIPAL EXPORT PRODUCTS IN ECOWAS ..........................................................................50
ANNEX 4: AVERAGE GROWTH RATE OF REAL GDP PER CAPITAL (ECOWAS VS SADC) .......................51
ANNEX 5: RESIDUAL-ACTUAL AGAINST FITTED .....................................................................................52
ANNEX 6: STABILITY TEST ......................................................................................................................53
ANNEX 7: EXPORTS AND IMPORTS IN ECOWAS (% OF TOTAL TRADE IN VALUE TERMS) .......................54
ANNEX 8: SUMMARY STATISTICS OF SERIES FOR INDIVIDUAL COUNTRIES: 1987 – 2004 .......................55
ANNEX 9: RESIDUAL-CORRELATION MATRIX .......................................... ERREUR ! SIGNET NON DEFINI.
ANNEX 10: RESIDUAL-COVARIANCE MATRIX ........................................... ERREUR ! SIGNET NON DEFINI.
xi
LIST OF ACRONYMS AND ABBREVIATIONS
ADB African Development Bank
CEEB Central and Eastern Europe and the Baltic region
CEMAC Central African Economic and Monetary Community
COMESA Common Market for Eastern and Southern Africa
ECOWAS Economic Community of West African States
EPA Economic Partnership Agreement
FTA Free Trade Area
GLS Generalized Least Squares
LDV Lagged Dependent Variable
NICs Newly Industrialized Countries
PLS Pooled Least Squares
S/N Serial Number
SADC Southern African Development Community
SADC Southern African Development Community
SUR Seemingly Unrelated Regression
TCP Trade and Custom Policy
TFP Total Factor Productivity
VAT Value Added Tax
WAMU West African Monetary Union
1
CHAPTER ONE
GENERAL BACKGROUND
1.1 Introduction
The relationship between trade and economic growth has become increasingly debated in
the policy and academic circles where policy makers, researchers and other development
practitioners have argued that, expanded trade holds the key to economic growth in
developing countries. According to Frankel et al. (1999), expanded trade is the conduit in
expanding the choices of consumers and firms.
The spectacular growth performances of the Far East Asian economies through trade
have also triggered the interests of many researchers to further examine the relationship
between trade and economic growth. To this end, few pertinent questions arise: first, does
trade positively or negatively affect economic growth? Second, is that growth import-led
or export-led? Conventionally, the answer would be that the growth is export-led. Despite
this conventional wisdom, results from many empirical studies remain mixed thereby
opening up the debate for further studies on the subject. Cyrus et al. (1996) raised the
problem of endongeneity: Does trade as measured in openness (import plus export,
divided by GDP) lead to growth or does growth lead to openness? They found out that
the effect of trade in openness on growth turns out even stronger when correcting for the
simultaneity, as compared to standard estimates.
In the mist of this debate, this study responds by looking at trade in export- oriented way.
In particular, the study examines the impact of exports on economic growth in the
Economic Community of West African States (ECOWAS).
Exports of goods and services exploit the opportunities to create high rate of economic
interactions with the rest of the world which speeds the absorption of frontier
technologies, world best practices, and increasing returns to scale. Exports are also
considered to be source of foreign exchange earnings. Grossman et al. (1991) asserted
that technological spillovers could come through imports and exports.
2
Over the past decades, growth rates of exports and GDP per capital in ECOWAS have
been fluctuating. About 90% of the region’s exports are primary commodities and the
low international prices for these commodities reflect negative implications on its current
account balance. The average growth rate of GDP per capital from 1987 to 1995 is
negative 0.22 percent and from 1995 to 2004 is 0.39 percent showing an increase of 0.17
percent. The average growth rate of exports from 1987 to 1995 is 8.07 percent and from
1995 to 2004 is 6.21 percent declining by 1.86 percent (detail in chapter two).
In its thirty years of existence, the Economic Community of West African States has
undertaken many initiatives to stimulate economic growth through the integration of
member states’ economies. Some of these initiatives include the declaration of Free
Trade Area (FTA), preparation for the adoption of custom union by end 2007 and
adoption of common currency for the Anglophone countries in the region by the year
2009. In the revised treaty, the FTA was declared to remove all trade barriers among
member states but each member maintains its external barrier with countries outside
ECOWAS.
Despite all these efforts, economies in the region remain weak, exports of goods and
services continue to fluctuate and there is significant amount of trade diversion. This
paper therefore investigates these and other related concerns.
1.2 Statement of the Problem
ECOWAS’s share (less than 1 percent) in World Trade in terms of value remains very
insignificant while trade keeps growing2. West Africa has over the years been more
vulnerable in the multilateral trading system. This is largely reflected in its insignificant
role. The multilateral trading system is directly or indirectly compelling countries to
adopt the doctrine of comparative advantage (liberalized economies). Traditionally, West
Africa has comparative advantage in primary commodities, so that free trade implies it
exports more of these primary commodities, and imports more of manufactured
2 See the official website of the WTO for detail http://www.wto.org/english/res_e/statis_e/statis_e.htm
3
commodities. Low international prices for these primary commodities are making the
region unstable and more vulnerable to external shocks.
The average term of trade from 1987 to 2004 is 108.21 (2000 = 100 index). Average
growth rate of GDP per capital in ECOWAS has been fluctuating around the
neighborhood of negative 1 percent from 1987 to 2 percent in 2003; and the average
growth rate of export has also been fluctuating from negative 0.4 percent in 1988 to 15
percent in 1997 and from 3 percent in 1998 to 11 percent in 2003 (see chapter two).
Hence, the following concerns are raised: Have the fluctuations in the export of goods
and services caused the persistent economic stagnancies in the region from 1987 to 2004
or caused some improvements in economic growth? Are there some institutional factors
responsible for these persistent economic stagnancies? The study addresses the foregoing
concerns.
1.3 Objective of the Study
The objective of the study is to examine the impact of exports on Economic Growth in
the Economic Community of West African States (ECOWAS).
1.4 Justification and Significance of the Study
Justification of the study is in twofold: First, the study seeks to investigate the effects of
exports on economic growth so as to ascertain what has endangered growth in the past
and what would further stimulate growth in the future. Second, the study responds to the
open debate on Export-Growth relationship in order to further investigate its validity and
robustness.
Evidence has shown that expanded trade holds the key to prosperity for development in
developing countries and it is the conduit of expanding the choices of consumers and
firms. In this connection, it becomes significant therefore that the study is conducted for
countries in the West African region where the need for development cannot be under
estimated. It is envisaged that the findings and conclusions drawn from this research may
provide useful policy implications for the region’s development and may also serve as
body of knowledge for other related research works.
4
1.5 Organization of the study
The rest of the study is organized as follows: chapter two discusses briefly trade and
economic performance in ECOWAS; chapter three reviews related literature; chapter four
detailed the methodology, estimation procedures and discussions of results and chapter
five gives the summary of findings, policy recommendations, conclusion, areas of further
research and limitations.
5
CHAPTER TWO
TRADE AND ECONOMIC PERFORMANCE IN ECOWAS
2.1 Overview
Since its inception, the Economic Community of West African States has undertaken
many initiatives through the Department of Trade and Customs Policy (TCP) to foster
economic integration in the region. Some of these initiatives include the declaration of
Free Trade Area (FTA), preparation for the adoption of custom union by end 2007 and
adoption of common currency for the Anglophone countries in the region by the year
2009. In the revised treaty, the FTA was declared to remove all trade barriers among
member states but each member maintains its external barrier with countries outside the
region or trade bloc. The Custom Union is to be adopted in order to have a common
external Tariff. This is basically intended to create the facilities and mechanisms
necessary to expedite the free movements of goods and services in ECOWAS. It is also
envisaged that once these agreements are fully implemented, it will create an expanded
market which will allow for economic of large scale production (trade creation),
diversification of production, fostering of specialization, attracting foreign direct
investment (FDI), and having access to other regional markets.
Despite these efforts by the community, the region is still being dominated by trade
diversions which further leads to economic of low scale production (mainly primary
commodities with no value added). Article 3 of the revised Treaty stipulates the
responsibilities of the Trade and Customs Policy Department. This Article clearly defines
the short, medium and long-terms objectives to be realized in order to ensure regional
integration. The TCP Department has always been at the center of the Community’s
integration policies since ECOWAS was established in 1975. The long-term mission of
the department is within the framework of the following fundamental basis3 of any
integration policy:
Free movement of persons and goods;
3 Extracted from the official website of ECOWA
6
Promotion of intra-Community trade through the elimination of tariff and non
tariff barriers to imports and exports;
Facilitation of intra-Community trade through the simplification and acceleration
of customs clearance procedures;
Creation of a customs union by establishing a common external tariff and
instituting a common policy on trade with third countries;
Promotion of regional trade, harmonization of trade policy, and monitoring of
bilateral and multilateral trade negotiations;
Monitoring of level of application of the ECOWAS Community levy and
payment of compensation for losses incurred by Member States;
Harmonization of customs and fiscal regulations;
Adoption of a policy to ensure effective monitoring of informal trade
Tourism development; Establishment of an ECOWAS Solidarity Fund.
2.2 Macroeconomic Performance in ECOWAS (1987 – 2004)
The average annual growth rates of real GDP per capital and real exports from 1987 to
2004 showed fluctuating trends (see figure 2.1). ECOWAS average growth rate of GDP
per capital for the same period stood at 0.4 percent, third highest among the five African
regional organizations. The fluctuating trends in the growth rates reflect poor economic
performance which was largely influenced by both external and internal factors. The
internal factors is in part due to the prolonged civil unrest in the region during the earlier
parts of the 1990s particularly in Liberia, Sierra Leone, Guinea and Cote d IVoire
respectively; and mono culture production with no value added. The external factors to a
large extent include the low international prices of the primary commodities produced by
the region; the Asian crisis that affected world demand and supply; and the wait and see
attitudes of development partners in releasing official development assistance to the
region.
Intermittently, there were some positive trends in economic performance from 1994 to
2004 spurred by some levels of improvements in the political and macroeconomic
situations in the region. Despite the sluggish start in 1987 through 1993, strong signs of
7
economic recovery started emerging in 1994 and peak in 1996. The sluggish start is
attributed to both internally and externally determined factors mentioned earlier.
Figure 2.1: Average Growth rate of Real GDP per capital Vs Average Growth rate of
Real Exports4
-10
-5
0
5
10
15
20
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Avg Growth rate of Exports
Avg GDPP Growth rate
Source: World Development Indicator, 2006
With the exceptions of 1988, 1992, 1998 and 2002 where exports declined significantly,
the study observes that for every time there is a peak in average growth rate of exports,
there is a decline in the average growth rate of GDP per capital with the sense that,
fluctuations in the average growth rate of exports are contributing to the fluctuations in
the average growth rate of real GDP per capital. The substantial negative decline in the
average growth rate of real exports in 1992 is in part attributed to the low level of exports
experienced by the region (characterized by political and macroeconomic instabilities in
some parts). On the overall, economic performance in ECOWAS remain vulnerable and
unstable during these periods.
4 These trends represent 13 countries in ECOWAS (Liberia and Niger are excluded because of data
unavailability)
8
Table 2.1 depicts the sectoral share in GDP (%) at current market prices from 2000 to
2004. The average rates of contribution of the industrial and service sectors to GDP at
current prices stood at 21.8 percent and 46.6 percent respectively. Agriculture and
manufacture accounted for 31.7 percent and 8.4 percent respectively.
Table 2.1: Sectoral share in GDP at current prices in ECOWAS: 2000 -2004
(Percentage distribution)
Agriculture Industry of which Services
Annual Aver Annual Aver Manufacture Annual Aver
__________________________________________________________________
Benin 35.9 14.1 8.9 50.0
Burkina Faso 31.3 18.6 12.6 50.2
Cape Verde 11.2 14.9 4.7 73.8
Cote d’Voire 24.7 23.3 17.5 52.0
Gambia, The 33.2 13.3 5.3 53.5
Ghana 36.0 25.2 9.8 38.8
Guinea 21.4 31.7 3.7 46.9
Guinea Bissau 42.1 15.9 11.9 42.0
Liberia - - - -
Mali 36.3 24.0 8.0 39.7
Niger 39.9 12.1 6.3 48.0
Nigeria 27.8 49.2 4.0 23.0
Senegal 19.2 21.8 13.6 59.0
Sierra Leone 46.0 21.0 2.1 33.0
Togo 38.4 19.7 9.0 41.9
ECOWAS 31.7 21.8 8.4 46.6
Source: Author’s calculation from SSOAC, 2006
Note: Annual Aver – Annual average
The period 1995 to 2004 registered an average current account balance of negative 6.6
percent of GDP in ECOWAS compared to Africa average of negative 1.2 percent of
GDP. ECOWAS registered the second highest current account deficit among the regional
organizations in Africa after CEMAC (negative 15.4 percent). Through out the period, all
the member states experienced current account deficits. However, some member states
such as Nigeria and Cote dIVoire performed relatively well in reducing their current
account deficits, registering the least deficits of 0.5 percent of GDP and 1.3 percent of
GDP respectively. This is followed by Ghana, Gambia and Senegal with deficits of 5.1
percent of GDP, 5.2 percent of GDP and 5.3 percent of GDP respectively. Other member
9
states experienced high and deteriorating current account deficits (see figure 2.2). The
low deficits experienced by Nigeria is attributed to export earnings from oil revenue
during the period while that of Cote dIVoire is attributed to export earnings from the
cocoa revenue, being one of the world largest suppliers of cocoa.
Figure 2.2: Average Current Account Balance in ECOWAS: 1995 – 2004
(%GDP)5
-12
-10
-8
-6
-4
-2
0
BEN BFA CPV CIV GMB GHA GIN GNB LIB MLI NER NGA SEN SLE TGO
Source: Author’s computation from SSOAC6, 2006
The average budget deficit in ECOWAS from 2000 to 2003 was negative 4.4 percent of
GDP and for 2004 the average stood at negative 2.4 percent of GDP as compared to
Africa average of negative 1.7 percent from 2000 to 2003 and negative 0.5 percent in
2004 (see table 2.2 and annex 2). ECOWAS registered the third best performance from
2000 to 2003 after SADC that registered negative 3.1 percent of GDP during the same
5 BEN-BENIN; BFA-BURKINA FASO; CPV-CAPE VERDE; CIV-COTE D’VOIRE; GMB-GAMBIA;
GHA-GHANA; GIN-GUINEA; GNB-GUINEA BISSAU; LIB-LIBERIA; MLI-MALI; NER-NIGER;
NGA-NIGERIA; SEN-SENEGAL; SLE-SIERRA LEONE; TGO-TOGO 6 Selected Statistics on African Countries, African Development Bank annual statistical publication.
Volume XXV, 2006
10
period. In 2004, ECOWAS became second best performer after CEMAC that registered a
surplus of 3.2 percent of GDP. Table 2.2 further revealed that only Nigeria and Togo
registered surpluses in their fiscal balances in 2004 with 7.7 percent of GDP and 1.9
percent of GDP respectively. Again, the exports earnings from the oil revenue played
significant role in reducing Nigeria’s fiscal and external gaps.
The issue of budget deficit sustainability is not a new phenomenon in ECOWAS member
states. Over the years, efforts have been exerted by many member states to reduce their
budget deficits through “demand” and “Supply”. The demand side has to do with the
control of current and capital expenditures through vigorous implementation of ‘Public
Financial Management System. The supply side has to do with increase in the state
resources through tax reforms which include broadening the tax base to make taxation
progressive and improvement in the tax collections. Given the level of commitments by
member states to provide basic social services or to eradicate poverty, attempts made to
have budget deficit at a sustainable level so far yielded no fruitful results.
Table 2.2: Fiscal Balance in the ECOWAS sub-region (% of GDP)
Surplus (+)/Deficit (-) Surplus (+)/Deficit (-)
Average
2000-2003 2004
Benin -1.9 -1.9
Burkina Faso -3.9 -4.3
Cape Verde -7.6 -1.5
Cote d’Voire -1.1 -1.8
Gambia, The -6.2 -5.7
Ghana -5.9 -3.1
Guinea -4.4 -4.9
Guinea Bissau -12.4 -8.4
Liberia - -
Mali -2.8 -2.7
Niger -3.3 -3.5
Nigeria -1.1 7.7
Senegal -0.8 -2.0
Sierra Leone -8.3 -3.5
Togo -0.8 1.9
ECOWAS -4.4 -2.4
Source: Author’s calculation from SSOAC, 2006
11
Consumer price index as depicted in figure 2.3 shows changes (inflation) in the cost of
acquisition of a basket of goods and services purchased by the average consumer in
individual member state from 1990 to 2004. On the average, the inflation rate in
ECOWAS for the period was 11.2 percent, the second best performer after CEMAC that
registered 4.4 percent on average. The average inflation in ECOWAS was 7 percentage
point lower than Africa’s average of 18.9 percent during the same period. The study
further observes that during these periods, the region experienced relative stability in
average CPI inflation rates particularly the WAMU countries (except Guinea Bissau).
This is spurred by their vigorous implementation of the macroeconomic stabilization
policies. Some of the non WAMU countries like Ghana, Liberia, Nigeria and Sierra
Leone did little to reduce the double digit inflation rates with average inflation rates of
25.9 percent, 10.5 percent, 25.4 percent and 31.2 percent respectively.
Figure 2.3: Annual averages of CPI Inflation in ECOWAS: 1990 - 2004
0
5
10
15
20
25
30
35
BEN BFA CIV GNB MLI NER SEN TGO CPV GMB GHA GIN LIB NGA SLE
Source: Author’s computation from SSOAC, 2006
12
In terms of trade, ECOWAS traded significantly outside Africa from 1996 to 2001
registering a rate of 154 percent of the total value of exports and imports (see figure 2.4).
Trade between ECOWAS and the rest of Africa was steady around 29 percent of total
exports and imports. However, intra-ECOWAS trade was very sluggish registering the
least rate of 24 percent of total value of exports and imports. There is some sort of
equilibrium in trade between ECOWAS and the rest of Africa but highly significant
disequilibrium in trade between ECOWAS and countries outside Africa. Imports into
ECOWAS constitute bulk of the total ECOWAS trade with countries outside Africa
reflecting negatively on the region’s trade balance (see annex 7 for detail on the share of
exports in the region’s total trade). This further suggests that the region is more
dependence on imports and in most cases consumer goods.
Figure 2.4: Inflow and outflow of Trade in ECOWAS: 1996 – 2001
(As percentage of total value of exports and imports)
Source: Author’s computation from ECOSTAT, 2006
In addition, there is loose trade integration in ECOWAS’ FTA. That is, over the years
there have been more road blocks to trade in the region which can be attributed to
24 29
154
Intra-ECOWAS trade Trade with other African Countries
Trade outside Africa
13
member states failure to implement at the fullest various agreements reached on trade.
Exports in the region have been concentrated on few products and in particular primary
commodities including petroleum, cocoa or beans, gold, cotton, boxile, café and iron ore.
Among these products, petroleum constitutes 70 percent of total exports (1996 – 2004)7.
Terms of trade on average tend to worsen or deteriorate over time as shown in Figure 2.5
below. This is consistent with the assertion made by Prebisch (1960): “expanding
primary production capacity in least developed countries would worsen the terms of trade
of these countries than they would otherwise be, reflecting negatively on their balance of
payments which would also have trickle down effects on their economic growths”.
Figure 2.5: Trend of Average terms of trade in ECOWAS
0
20
40
60
80
100
120
140
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Terms of trade
Source: World Development Indicator, 2006
7 Nigeria is an outlier in this case. The data were extracted from the official websites of ECOWAS,
UNCOMTRADE and the work of Remi Lang of UN Economic commission for Africa.
14
However, the study assumes that the shift in world demand would also affect negatively
or positively the terms of trade in the region.
2.3 Recent Efforts to foster Economic Integration through Trade8
At the Accra meeting in 2004, the Department of Trade and Customs Policy of the
ECOWAS commission was mandated by the Council of Ministers to prepare the
negotiations toward the signing of an economic partnership agreement (EPA) between
the European Union and ECOWAS (to be signed before 1st January 2008). The EPA
covers all the areas of activity of the Department of TCP and others. It would appear to
be a catalyst that can give added force to all the programmes currently implemented by
the Department (free trade zone, common external tariff, customs union, policy
harmonization, competition and investment policy, and so on). Since the beginning of
2007, the main challenge of the Department had been the adequate preparation for the
negotiations. To this end, this activity was given priority in the 2007 budget.
At the Ouagadougou meeting in January 2008, the Heads of State and Government had
reaffirmed their willingness to sign the EPA that is development-oriented to promote
regional integration. At the meeting held in Nouakchott on February 15, 2008, the
ECOWAS Ministers reiterated the need for the development dimension of the EPA and
underscored the followings:
Improvement of the productive sectors in the agricultural, industrial, cottage
industry and service sectors;
The development of infrastructure (energy, roads, railways);
The upgrading of the enterprises;
Building of the capacities of the private sector and facilitation of its access to
financial resources;
Compensation for losses of tax revenue
Other elements were also given priority in the 2007 budget, namely adoption of three
texts that were crucial to efforts of deepening regional integration in the ECOWAS
8 This section benefits greatly from the official website of ECOWAS
15
zone, to conduct a study on informal trade, and the organization of the 5th ECOWAS
Trade Fair in Ouagadougou.
At the fifth ECOWAS Trade Fair in Ouagadougou on March 15, 2008, the need for
effective information dissemination in order to facilitate true intra-community trade was
underscored. This is consistent with the theme of the fair: “Consolidating Intra
Community Trade through Information, communication and Technology (ICT)”.
16
CHAPTER THREE
REVIEW OF LITERATURE
Despites numerous studies by many researchers, the relationship between Trade and
Growth remains a subject of controversy particularly in the empirical literature. This
section reviews the theoretical and empirical literature of the relationship between
Exports and Economic Growth.
3.1 Theoretical Perspective
The study relies on the theory of International trade which dates back to Adam Smith ,
David Ricardo, James Mill and John Stuart Mills who presented the nature of trade in a
simplified terms like, two countries; two products; and domestic values proportional to
labor time. Their models explained the gains to be derived from specializations and trade.
Adam Smith’s theory (Absolute cost Advantage) states: a country H (Home) is said to
have Absolute Advantage over country F (Foreign) in the production of commodity X if
the required unit of labor to produce commodity X in home country is less than the
required unit of labor to produce commodity X in the foreign country. In addition, if the
marginal productivity in producing X in home country is greater than the marginal
productivity of producing X in foreign country. In this theory, the basis for trade is labor
productivity.
David Ricardo considered the above theory as over generalization. He further asserted
that when a country has absolute advantage in producing the two commodities as claimed
by Adam Smith, than there is no need for trade. This is the limitation of the Adam Smith
model. To account for this limitation, Ricardo now said that even when a given country
has absolute advantage in producing the two commodities there should be basis for trade.
He redefined the theory to Comparative Advantage. That is, each country specializes in
what it has comparative cost advantage in. In this theory, emphasis is on specialization.
Grossman et al. (1991), Matsuyama (1992), and Walde et al. (2005), concluded that the
effects of exports on growth have shown to be positive or negative under different
circumstances.
17
Hultman (1967) concluded that this conventional International trade theory is based on a
number of static assumptions that may be inconsistent with the dynamic export models.
He further asserted that most of the export models imply that the major line of causation
is from exports to internal economic growth while the conventional trade theory
emphasized on exports occurring as a result of domestic conditions.
The Traditional Trade Theory known as the Classical and Neoclassical models
maintained that trade between countries take effect as a result of reallocation of resources
between the home and export sectors. These models further maintained that trade
occurred within the static framework of productive resources and constant technical
knowledge in quantity and quality. In order to incorporate these assumptions into the
dynamic version of exports models that allow for growth, modification is required for
such static assumptions.
The ‘Factor Intensity Theory’ (Hechsher-Ohlin) emphasized trade between regions. The
theory states: “a region (or country) tends to export items the production of which
requires relatively large amount of the factors of production that the region possesses in
relative abundance; it imports items which embody the scarce factor of production”.
Ohlin conviction was that “trade promoted growth through local adaptation of industry to
the basic conditions of production”. He further believed that trade contributes
significantly to production and in the process each trading region reaps some gains.
Following the spectacular success story of many emerging countries that became newly
industrialized countries (NICs) in the 1970s and 1980s, theoretical consensus on exports
and growth emerged among the neoclassical economists. This consensus is referred to as
the causal link between exports and growth. The neoclassical economists stress the
hypothesis that exports are a key factor in promoting productivity growth. However,
some explanations on the relationship between exports and growth were forwarded as
follows:
18
First, they believe that exports concentrate investment in the sector of a given country in
which it has comparative advantage. If such country specializes in this sector,
productivity will increase. Second, the interactions of the domestic economy with the rest
of the world in higher exports growth will allow a country to gain from economies of
scale. Third, the growth of exports is seen to have a significant influence on the
productivity of a given economy through externalities of exports on other sectors,
Bhagwati (1978). Fourth, strong presence of a country in the international competition by
higher exports provides the incentives for the introduction of technological change. Giles
et al. (2000) argued that outward oriented trade policy may as well give access to
advanced technologies via learning by doing and management best practices.
Additionally, two approaches have been put forward regarding the relationship between
exports and growth: The first is the Keynesian approach which states that output level
will improve via multiplier effect if aggregate exports are injected into the circular flow
of income of a given economy. The second approach maintains that higher level of
exports increases foreign exchange earnings which has positive implications on a balance
of payment or allow the imports of essential inputs into the production system that will
yield higher value.
According to the Endogenous growth theory, trade via exports and Foreign Direct
Investment increase knowledge spillovers across countries through which productivity of
physical capitals as well as human capital can also be increased. With additional learning-
by-doing effects, productivity of endogenous growth factors can be further expanded.
19
3.2 Empirical perspective9
The debate in the empirical literature regarding the relationship between trade and
economic growth cannot be over emphasized. In the works of Grossman et al (1991),
Matsuyama (1992), and Walde et al. (2005), it became theoretically clear that the effects
of trade on growth have shown to be positive or negative under different circumstances.
Sohn et al. (2006) paper on Trade Structure, FTA and Growth: implications to East Asia,
responded to the open debate on the relationship between trade and growth by following
the lead of Lederman et al. (2003) in removing some of the confusions that arose. They
argued that the mixed results of the econometric evidence on the link between trade and
growth come due to two main aspects. First, the problem of definition of trade; second,
many of the empirical estimation attempts so far failed to isolate the pure impact of trade
on economic growth, arguing that measures in trade openness or volume are significantly
influenced by non-trade factors such as macroeconomic variables and institutional
variables. Trade structure variables (primary products exports over total exports or GDP,
FTA index, Human capital over labor, physical capital over labor and Export Herfindahl
index) were introduced by them to examine trade on growth. They found out that those
trade structure variables representing the Hecksher-Ohlin type of trade-growth
relationship show strong evidence of positive effects on growth. However, when natural
resource abundance variable is combined with the Hecksher-Ohlin variable, it shows a
significantly negative impact on economic growth. Free Trade Area also enhances growth
in their studies in the global economy but show very weak role in the East Asian region.
They maintained that there could be loosest trade integration in the East Asian region
regarding their FTA.
Nath (2005), in his paper on Trade, Foreign Direct Investment and Growth in 13
transition Economies of the CEEB region, indicates that among the variables of interest,
trade has significant positive effect on per capital real GDP growth. He used pooled Time
9 Parts of this empirical review were selected from the work of Sebastian Edwards who
selected some empirical works on exports, GDP growth and world market conditions: University of California, Los Angeles, -Journal of Economic Literature, Vol. XXXI(sept.1993)
20
Series Cross-section estimation with the sample period of 1990 – 2003. Kohli et al.
(1989) used Feder’s model to estimate the relationship between exports and GDP growth
for 41 countries using the sample period 1960- 70 and 1970 -81. The sample was
basically divided into “outward oriented” and “non-outward oriented” countries. Their
findings were that, exports always significant for earlier period and not significant in the
later period.
Gray et al. (1988) adopted Kavoussi’s 1985 exports decomposition techniques on the
sample period 1967 – 73 and 1973 – 83. They divided the countries in two fronts: those
facing “above average” represent high world demand and those “below average”
represent low world demand. Their findings indicate that the spearman coefficient show
significantly positive sign for those countries above average world demand; and
insignificant for those facing low would demand conditions. Rana, (1988) comments on
the paper of Balassa (1985) by adopting a pooled time series estimation procedures on a
balanced sample of 43 countries for before and after 1973. He used OLS and random
effects procedures and the findings indicate that all estimates of exports are significantly
positive; those for post 1973 period are smaller than those for earlier period.
Ram (1987), adopted a production function approach on time series and cross sections
with a sample period of 1960 – 1973. He divided the sample in “before oil shock” (1960
– 72) and “after oil shock” (1973 – 82). The sample was also divided between low and
middle income countries. The findings concluded that in the majority of cases, the
estimated coefficient of exports for the period 1973 – 82 exceeds that of the earlier
period.
Kavoussi (1985) decomposes sources of exports growth using sample period 1967 -
1977. The study constructs outward orientation ranking and classified countries between
those facing “favorable” and “unfavorable” market conditions. The study compute
spearman rank coefficient between outward orientation and GDP growth in two periods:
1967 – 73 and 1973 – 77. The findings show that countries facing favorable market
conditions exhibited a significant stronger correlation between exports and GDP growth
21
than those facing unfavorable conditions. Ram (1985) used the production function
framework on 73 countries for the sample period of 1960 – 70 and 1970 – 77. The
breakdown of sample was justified by oil shock. The findings indicate that for both
periods the coefficient of exports was significantly positive; but higher for the period
1970 – 77.
Balassa (1985) adopted the production function approach with exports as regressor by
comparing results for sample of 11 countries in 1960 – 73 with results of sample of 43
countries (that were adversely affected by the 1973 oil shock) for the period 1973 – 79.
He found out that the coefficient for exports is positively significant and higher in the
1973 – 79 period than the earlier period.
22
CHAPTER FOUR
METHODOLOGY, RESULTS AND DISCUSSIONS
This section contains the over all description of the methodological framework adopted
for the study.
4.1 Data Characteristics and scope of study
Due to the unavailability of enough data point, it is difficult if not impossible for the
study to conduct any meaningful time series analysis. Hence, pooled time-series and
cross-sectional data is used10
. Documentary secondary data for the period 1987 – 2004 is
used. This period is chosen for the study due to data availability and reliability. During
the period, the sub-region under went many economic transformations starting with the
Structural Adjustment Programme in the 1980s followed by the outward oriented growth
strategies in the 1990s. The study considers thirteen countries11
in the West African sub-
region taken into account individual country’s peculiarities. Annex 1 presents the
principal sources of data for the study.
4.2 Theoretical Source for Model Specification
The study adopts it framework from the traditional Neoclassical Growth Theory of Solow
(1956), revisited recently by many researchers among which is Barro (1991). Barro
included human capital (H) and defined it as average level of skilled labor.
Hornstein et al. (1996) asserted that growth in total-factor productivity (TFP) is usually
well thought-out to represents output growth not accounted for by the growth in inputs.
Considering the macro model ),,( HLKFAY tttt , Total Factor Productivity (TFP) is
equal to ),,(/ HLKFY ttt . Similarly, considering the model ),,,( XHLKFAY tttt , TFP
is equal to ),,,(/ XHLKFY ttt ; where Y, K, and L are measures of output, capital stock,
labour and human capital respectively. X measures real exports over GDP ratio, A is the
measure of TFP and F (.) is the production function. The above implies that the Solow
residual is a measure of TFP and this TFP is presumed to change over time. There is
10
Following the lead of Hiranya Nath, (2005) 11
Benin, Burkina Faso, Cape Verde, Cote d’Voire, The Gambia, Ghana, Guinea, Guinea Bissau, Mali,
Nigeria, Senegal, Sierra Leone and Togo
23
however disagreement in the literature over the question of whether the Solow residual
measures technology shocks. Efforts to change the inputs, like Kt, to adjust for utilization
rate and so forth, have the consequence of changing the Solow residual and thus the
measure of TFP. Nonetheless, the idea of TFP is well defined for each model of this kind.
TFP is not necessarily a measure of technology since the TFP could be a function of other
things like exports, or monetary shocks, or the political party in power and even
institutional factors. In the context of this study, TFP represents the variable of interest
and other conditioning variables (these conditioning or controlled variables are defined in
section 4.3). Generally, in the context of neoclassical spirit, the aggregate production
function is typically specified as
),),(),(()( ttLtKFtY (1)
The above expression is an analytical simplification which makes it possible to
summarize detailed information about complex process of economic growth within a
simple unified framework. Differentiating the logarithm of equation (1) with respect to t,
we obtain
Ft
F
L
L
F
L
L
F
K
K
F
K
K
F
Y
Y 1...
; (2)
dtdXX /.
is the time derivative of the respective variable.
Specifying equation (1) in the Hicks neutral form, we have
))(),(()()),(),(( tLtKFtAttLtKF (3)
where A(t) represents total factor productivity (TFP) and measures the shift in the production
function F at given levels of inputs. Taking log derivatives with respect to time yields the
following expression:
A
A
L
L
F
L
L
F
K
K
F
K
K
F
Y
Y
....
(4)
Consequently, the last term on the right hand side of equation (2) is interpreted in equation (4) as
the growth rate of TFP. This implies that equation (4) can be written as
,TFPof
rategrowth
labourof
rategrowth
capitalof
rategrowth
GDPof
rategrowth
LK (5)
24
4.3 Model Specification and Estimation Techniques
Base on the foregoing theoretical framework of the Neoclassical Growth Model, the
study builds on the Pooled Time-Series Cross-Section estimation model used by Nath
(2005)12
, by the inclusion of institutional variable of FTA and the use of exports to GDP
ratio instead of exports plus imports over GDP. In particular, ordinary least squares
technique is used with the help of eviews6 software.
The Pooled Time-Series model is implicitly specified as follows:
itititiit zxy ''; (6)
Where, ity is the growth rate of per capital real GDP; i is the country fixed effect; itx is
a variable of interest (total exports over GDP), itz is a vector of control variables (Terms
of trade, exchange rate, CPI inflation, gross fixed capital formation over GDP, gross
secondary school enrollment ratio, Labor, government final consumption and FTA
index); i represents individual country and t represents time period.
Explicitly we have the model as:
itititititititiit LNERTOTLTLGSSEGDPGFCFLFTAGDPRXLGrowth //
ititit UGOVCPI (7)
The results of the Hausman test for fixed versus random effects (see tables 4.5 and 4.6)
showed that the fixed effect has no redundancy in the model as oppose to the correlated
random effect; hence, the study adopts the country fixed specific effects.
Many issues and concerns have been raised regarding the empirical methodology on
exports and growth. One of such is the use of time invariant initial conditions. Barro
(1991), concluded that time invariant initial conditions are important for subsequent
growth. Berg et al. (1999) asserted that inclusions of more than one initial condition may
be important for growth and macroeconomic performance in transition economies.
12
He looked at 13 transition economies in the CEEB region whereas this study looks at 13 economies in
the ECOWAS sub region.
25
Even though these time invariant initial conditions have been prominent in many
empirics of growth particularly in dynamic panel estimation, this study leaves them out in
favor of country specific fixed effects13
. Inclusion of too many initial conditions may
render coefficients estimates of the model useless. The effects of initial conditions taper
off as time passes; hence, their inclusion may not be appropriate in the long-run
investigation. In addition, this study leaves time invariant initial conditions because the
cross sections are less than the time period. Arellano and Bond (1991)’s method is
appropriate when the cross sections are greater than the time period or when there are
large size of cross sections.
According to Nath (2005), country specific fixed effects model takes care of time
invariant country specific factors but the model may still surfer from omitted variable
problem; this may arise as a result of not including some important time variant control
variables. While exclusion of some important variables lead to omitted variable problem,
inclusion of some may as well lead to the problem of colinearity. Subsequently, the issue
of multicollinerity may arise thereby rendering individual coefficient insignificant with
high R2. Evidence from both the theoretical and empirical perspectives suggest that, the
short coming of including too many variables in the model may lead to lack of degree of
freedom that may eventually lead to imprecise estimation of the model coefficients. To
address all of these concerns, the study adopts David Hendry’s “general-to-specific”
approach by applying sequence of redundant variables test (F-tests) to arrive at the
parsimonious specification suitable under the data set. The general-to-specific approach
is not applied to the variables of interest instead; it is applied only to the control
variables. The study tests for the redundancy of each controlled variable by observing the
F-test results of such variable and the behaviors of the coefficients of the variable of
interest. This process continues until a parsimonious specification is arrived at.
13
As asserted by Nath(2005), there may be country specific fixed effects that may capture some of the
differences in institutions that are evolved across economies in a given region. Further, individual country-
specific intercepts i capture any combination of time invariant variables that have been omitted
knowingly or not from the regression model.
26
In the region, there are differences in growth experiences which may give rise to
variations of variables in the model. There may also be common factors that affect
countries in the region given the similarities in political, cultural and geographical
systems. These concerns are addressed by testing GroupWise heteroskedasticity and
cross-sectional correlation. To address the issue of serial autocorrelation, pooled Durbin-
Watson (DW) and LM test statistics are used.
4.4 Hypothesis or restriction
Table 4.1: Expected signs as dictated by theory
S/N Variable Restriction
1 Total Exports/GDPit (theory not conclusive) 1
2 Log FTA Indexit (theory not conclusive) 2
3 GFCF/GDPit 03
4 GSSEit 04
5 Log Total LABORit 05
6 TOTit 06
7 Log Nominal exchange rateit (theory not conclusive) 7
8 CPI Inflationit (theory not conclusive) 8
9 GOV/GDPit (theory not conclusive) 9
4.5 Variable definitions and Justifications
Growth Rate of per capital real GDP: The Growth Rate of per capital real GDP is
calculated by taking the first log differences of per capital real GDP and multiplied by
100. This variable is used as the dependent or left hand side variable and it is denoted in
the model as LGrowth.
Total real exports over GDP: The ratio of total real exports to GDP ratio reflects the
Rybzynski and Hecksher-Ohlin type of trade-growth relationship. This measure tests the
“Dutch Disease” or “Sachs et al. (1995)” assertion that explains the negative effect of a
given country’s natural resource exports on economic growth. Consistent with this
27
assertion, a negative sign is expected. When exports are diversified (with value), then a
positive sign is envisaged; and when exports are dominated by natural resources (with no
value or not competitive on the international market), then a negative relation with
economic growth is envisaged. For this study, a negative relation with economic growth
is expected since 90 percent14
of the region’s exports are dominated by primary
commodities.
Free Trade Area (FTA) Index: Sohn et al. (2006) measured FTA index in their studies
by taking the ratio of the sum of FTA member countries’ GDP to the GDP of each
country within the bloc. If a given country has no FTA, the index remains 1. In their
study, they found that FTA enhances growth. Joseph Nye theory on Regional integration
indicates that FTA can foster specialization, and economic of large scale production. This
variable is used to validate the robustness of this claim. However, trade diversion can
distort FTA that may reflect negatively on economic growth. Consequently, the study
examines the positive or negative role of FTA in ECOWAS.
Factor Abundance Exports (Human Capital): According to Barro (2001), human
capital enhances growth. Consistent with this, the study uses Human capital under factor
abundance. To construct Human capital, gross secondary school enrollment ratio is used
as proxy and it is denoted in the model as GSSE. A positive relationship with economic
growth is expected. It should however be noted that there are still disagreements on the
usage of gross secondary school enrollment ratio as proxy for human capital. Some
believed that spending in secondary education does not have immediate impact on
growth; that is, it has lagged periods.
Factor Intensity Exports (Physical Capital): As dictated by theory (Hechsher-Ohlin),
factor intensity of a given country entails the ratio of capital- intensive goods to ratio of
labor-intensive goods exports. However, given the peculiar situation of the sub-region on
14
The data were extracted from the official websites of ECOWAS, UNCOMTRADE and the works of
Remi Lang of UN Economic commission for Africa and O. J. Nnanna of the West African Monetary
Institute in Accra, Ghana.
28
the unavailability of data on exports of both capital intensive and labor intensive goods,
we use gross fixed capital formation over GDP ratio as proxy for Physical Capital and it
is denoted in the model as GFCF. The study expects a positive relationship with
economic growth.
Terms of Trade: In the model, terms of trade is denoted as TOT and is defined as the
ratio of price of exports to imports calculated on the same base year. According to the
Prebisch-Singer theory, there was and would continue to be a secular decline in the terms
of trade of primary-commodity exporters due to a combination of low income and price
elasticities of demand. The ECOWAS’ terms of trade for its primary products exports on
average tend to worsen over time. Evidence has shown that an increase in a given
country’s terms of trade may stimulate factor accumulation and prolonged its economic
growth, Broda (2003). Consistent with the above, the variable is suitable for the study
and a positive relationship with economic growth is expected.
CPI Inflation: CPI inflation is denoted in the model as CPI. Mankiw (2003) asserted that
CPI inflation measures prices level that reflects the cost of consumer goods relative to the
same basket of goods in the base year. CPI inflation is used as proxy for inflation in order
to examine the macroeconomic stabilization policy in the ECOWAS region. According to
theory, inflation makes the value of money worthless and it has a negative effect on
growth. It is expected that CPI will have a negative relationship with economic growth in
the study.
Total Labor: TL represents total labor in the model and it is adopted in the study
because of its important role in the export-growth relationship. According to the
neoclassical growth theory, as labor, capital and total factor productivity of a given
economy increase, total output increases. This variable is important for the study in that
majority of the region exports are labor intensive. It is expected that total labor force will
have a positive relationship with economic growth.
29
Government final consumption: Gov represents government final consumption in the
model and it measures the size of government which affects economic growth through a
short run aggregate demand stimulus. Nath (2005) in his study found size of government
to be statistically significant and positively correlated with economic growth.
Nominal Exchange rate: According to the International trade theory, devaluation of
exchange rate can stimulate economic growth but only under the condition that supply
response is effective. Exchange rate variable is included in the model to reflect price
competitiveness in the international markets and examine its influence on economic
performance via export channel in ECOWAS. However, there are still disagreements in
the empirical literature on the positive influence of exchange rate on economic growth in
developing countries given that, gestation periods for their traded goods are very long.
Others maintained that it depends on the measurement of exports (when measured in
value a positive sign is expected and a negative sign is expected when measured in
quantity). The study measured export variable in value terms and to this end, a positive
correlation between economic growth and exchange rate is expected.
4.6 Results, Discussions and Diagnostic tests
4.6.1 Stationary Test
Table 4.2 presents the results of the unit root tests for all the variables under the data set.
These results indicate the absence of a unit root, as LLC (Levin, Lin, Chu), IPS (Im,
Pesaran, Shin), ADF (Augmented Dickey Fulley) and PP (Philip Peron) reject the null
hypothesis of a unit root at the conventional 5 percent level of significance. The variables
are stationary and there are no substantial variations in each unit over time. The data
show good time series and cross sectional properties in level; hence, the use of
cointegration and ECM (Error Correction Model) do not arise. In carrying out the unit
root tests, the following assumptions were considered under the common and individual
roots. The common root is associated with the LLC and HZ type of tests and it estimates
with the assumption that all the series have common autoregressive structure whereas the
individual root is associated with the IPS, ADF and PP tests type and these tests type
assume different autoregressive coefficients in each series during estimation. The
30
variables are all stationary in levels after controlling for the specification of the unit root
tests by choosing between sets of exogenous regressors to be included.
Table 4.2: Results of the Unit Root Tests
Variable Test method/Type
HZ LLC IPS ADF PP
LGROWTHit -8.3453
*** -6.4328
*** 90.0530
*** 108.765
***
RXit -3.5815***
-4.2028***
59.9606***
37.3876*
GFCFit -9.7116***
-8.3673***
107.464***
118.842***
LFTAit -3.0272***
-2.5403***
48.9538***
LLABORit -1.8706**
37.3638*
GSSEit -1.8997**
37.3533* 36.7397
*
CPIit 7.4441***
GOVit -8.2506***
-5.2577***
69.2871***
93.8655***
LNERit 5.3572***
TOTit -4.9753***
-3.1851***
45.6855***
39.5630***
Source: Author’s computation
Note: * significant at ten percent; ** significant at five percent and *** significant at one
percent. HZ: Hadri Z-statistic; LLC: Levin, Lin, Chu; IPS: Im, Pesaran, Shin; ADF:
Augmented Dickey Fulley and PP: Philip Perron.
4.6.2 Specification Test
As mentioned earlier, David Hendry’s general-to-specific approach is adopted by
applying a sequence of redundant variable tests (F-Tests) to arrive at the parsimonious
specification. The study estimates the general model that includes all the variables;
thereafter, tests the redundancy of each controlled variable or group of controlled
variables. It is importance to note here that while growth theory provides some sort of
guidance, there are differences in growth experience across countries in West Africa;
hence, the choice of appropriate controlled variables seems to be a difficult task. Previous
empirical works showed that growth in transition economies may be affected by many
factors some of which include, initial conditions, macroeconomic, institutional, and
structural reform factors. This study is concerned with the macroeconomic and
institutional factors.
The F-test results revealed that all the controlled variables proved significant to be
included in the pooled regression model (see table 4.3). However, government final
31
consumption proved to be redundant in the model as it makes the study to suspect the
possibility of a linear relationship with any other variable in the model; hence, the pooled
regression model is estimated without government final consumption.
Table 4.3: F-test results for exclusion of controlled variables
Category Variable F-statistics Degree of P-value
Freedom
1 2 3 4
Macroeconomic LCPI Inflation 22.93 (1,212) 0.00
Variables Govt. consumption 4.40 (1,212) 0.04
Terms of trade 16.81 (1,212) 0.00
LNominal exchange rate 6.11 (1,212) 0.01
Other controlled LFTA 26.05 (1,212) 0.00
Variables Gross secondary sch. 16.42 (1,212) 0.00
Enrollment
LLabor 32.26 (1,212) 0.00
Gross fixed capital 40.55 (1,212) 0.00
Formation
Source: Author’s computation Note: FTA-Free Trade Area
4.6.3 Diagnostic Tests
The test results for cross-sectional heteroskedasticity and cross-sectional correlation are
presented in Table 4.4. The result for cross-sectional heteroskedasticity was based on the
variance-covariance matrix of the estimated residuals obtained from the feasible GLS
estimation (see annex 10). The cross-sectional correlation result was based on the
correlation matrix of the estimated residuals obtained from the feasible GLS estimation
(see annex 9) with cross-section variances as weights. Though the two results accept the
null hypothesis of no heteroskedasticity across countries and no cross-sectional
correlation, there is still presence of correlation across observations and differing
variances from the residuals of correlation matrix and covariance matrix. For example,
the variance of Guinea Bissau (2.64) is twice higher than that of Benin (0.10). To correct
for these, the study uses “cross-section seemingly unrelated regression (SUR)” as
weights.
32
Table 4.5 presents the two way redundant fixed effects results and it revealed that the
three statistic values and their associated P-values strongly reject the null hypothesis that
the effects are redundant. Table 4.6 presents the Hausman test results for correlated
random effects. The results accept the null hypothesis that the correlated random effects
are redundant in the model. Hence, the fixed effects model is maintained for the study.
Table 4.4: Breuch-Godfrey LM Tests for cross-sectional heteroskedasticity and
Cross-sectional correlation
Null Hypothesis F-Statistics Degree of P-value
Freedom
1. There is no cross-sectional 0.52 (12, 5) 0.84
Heteroskedasticity
2. There is no cross-sectional 2.42 (2, 3) 0.24
Correlation
Source: Author’s computation
Table 4.5: Two-way Redundant Fixed Effects test (cross-section & period)
Effects Testing F-Statistics Degree of P-value
Freedom
Cross-section/Period 1.79 (29,196) 0.011
Cross-section only 11.08 (12,213) 0.000
Cross-section/period chi 54.55 29 0.003
Squares
Source: Author’s computation
Table 4.6: Hausman Correlated Random Effects test (cross-section & period)
Effects Testing Chi-square Chi-square d.f P-value
Cross-section Random 0.00 8 1.00
Period Random 0.00 8 1.00
Cross-section and Period Random 12.55 8 0.12
===============================================================
Source: Author’s computation
Independent Variables Test Method
33
4.6.4 Pooled regression Results and Discussions
Table 4.7: Exports and Growth in ECOWAS: Pooled Fixed effects Estimates
Sample period: 1987 – 2004
Dependent variable: 1st log difference of real GDP per capital growth rate
Source: Author’s computation
Note: The numbers in parentheses are the t-statistics. * Significant at ten percent; **
significant at five percent and *** significant at one percent.
In Table 4.7, the pooled regression results are presented and include coefficient estimates,
t-statistics and other relevant statistics obtained from two different estimation methods.
Column 1 represents estimates obtained from the pooled Least Squares (PLS) without
weights assigned. Column 2 includes estimates from the Feasible Generalized Least
Squares (GLS) with seemingly unrelated regression (SUR) as weights and column 3
PLS GLS(SUR) GLS(SUR)
Lagged log of real GDP per
capital growth rate
-0.138***
(-2.432)
Real Exports/GDP ratio (RX) -0.003
[-0.712]
-0.002***
[-2.236]
-0.003***
[-3.045]
Gross fixed capital
formation/GDP (GFCF)
0.012
[1.427]
0.012***
[6.176]
0.011***
[5.431]
Consumer price Inflation (CPI) -0.004
[-1.114]
-0.005***
[-5.032]
-0.005***
[-4.960]
Gross secondary school
enrollment (GSSE)
-0.009
[-1.111]
-0.009***
[-3.677]
-0.010***
[-4.512]
Log of Free Trade Area (LFTA) -1.427***
[-2.956]
-1.776***
[-5.289]
-2.010***
[-5.413]
Log of Labor force (Llabor) 1.172*
[1.607]
1.657***
[5.470]
1.122***
[3.527]
Nominal Exchange rate 0.243*
[1.674]
0.158***
[3.027]
0.277***
[5.238]
Terms of Trade Index (TOT) 0.004
[1.289]
0.005***
[4.059]
0.004***
[3.412]
R2
0.17 0.66 0.65
Adjusted R2 0.09 0.62 0.61
S.E of Regression 0.81 1.03 1.04
F-Statistic 2.26 20.30 17.49
Prob(F-statistic) 0.01 0.00 0.00
D-W statistic 2.20 2.10 ----
LM-Statistic ----- ----- 0.33
No. of observations 234 234 221
34
represents the inclusion of the lagged dependent variable (LDV) under the Feasible
Generalized Least Squares. The standard errors are estimated using Panel Corrected
Standard Errors that are robust to contemporaneously correlated errors and panel
heteroskedastic errors.
The results indicate that under the simple Pooled Least Squares, the variable of interest,
real exports over GDP ratio in the presence of other controlled variables is negatively
correlated with real GDP per capital growth rate, but the coefficient is insignificant.
However, under the feasible Generalized Least Squares method, real exports variable is
statistically significant and negatively correlated with growth. After including the lagged
dependent variable (LDV), the variable also shows a statistically significant and negative
relationship with real GDP per capital growth rate. In the three cases, the magnitudes of
the coefficients are very small.
A one percent point increase in exports to GDP ratio Under the GLS, reduces real GDP
per capital growth rate by 0.002 percentage point while under the GLS with lagged
dependent variable, a one percent point increase in exports to GDP ratio reduces real
GDP per capital growth rate by 0.003 percentage point. This is in part attributed to
exports of the region being dominated by primary commodities and the low international
prices for these primary commodities over the years made the region more unstable and
vulnerable to external shocks. This result confirms Prebisch (1959) and Sachs
et al.(1995) significant negative impact of primary products (natural resource) exports on
economic growth. It is also broadly consistent with the findings of recent empirical
works. In particularly, Sohn et al. (2006) found natural resource exports to be statistically
significant and negatively correlated with growth. Lederman et al. (2003) also confirms
the same results in their works on trade structure and economic growth.
Among the controlled variables, Gross fixed capital formation (GFCF) is statistically
significant and has positive effect on per capital real GDP growth rate under the GLS and
GLS with lagged dependent variable (LDV). Under both the GLS and LDV, a one
percent point increase in gross fixed capital formation to GDP ratio, leads to a 0.01
35
percentage point increase in real GDP per capital growth rate; implying that factor input
of capital accumulation is very significant in explaining the growth of the sub-region.
This result is consistent with the neoclassical growth framework.
A highly significant positive effect of labor is robust to any estimation method. Under the
PLS, a ten percent point increase in total labor leads to 117.2 percentage point increase in
real GDP per capital growth rate whereas under the GLS and GLS with LDV, a one
percent point increase in labor will increase real GDP per capital growth rate by 165.7
percent and 112.2 percentage points respectively. From the magnitudes of the
coefficients, the study observed that growth in the region has been along labor expansion
path. Further, the products in the region over the years have been labor intensive. As
dictated by the neoclassical growth theory, this result also confirms that factor input is
very significant in explaining growth in the sub-region.
Gross secondary school enrollment ratio used as proxy for human capital is statistically
highly significant under the GLS and GLS with LDV but negatively correlated with
growth and the magnitudes of the coefficients are much smaller. This is not consistent
with the insights provided by the growth framework. However, the negative effects of
human capital on growth in the region are in part due to the inadequate mechanisms for
transferring new knowledge and promoting learning –by-doing. In addition, secondary
school education is a low human productivity in the region given the high demand for
highly skilled and trained human resource to compete with the speed of globalization.
This result is broadly consistent with the results of Hausman, et al (2005); whose findings
revealed that low human capital and weak mechanisms for technology transfer and
learning-by-doing in developing countries have been shown to hamper productivity.
Furthermore, spending in the secondary education sector in developing countries does not
have immediate impact on growth. In other words, this proxy has lagged periods. There is
however, disagreement on the use of gross secondary school enrollment ratio as proxy for
human capital in least developed and developing countries.
36
This study disprove the growth enhancing effects of Free Trade Area in ECOWAS as it is
statistically highly significant but negatively correlated with economic growth. The
negative impact of FTA on economic growth in ECOWAS is to a large extent the lack of
binding commitments of member states to implement the FTA agreement reached. That
is, there is loose trade integration in ECOWAS which has over the years seen more road
blocks to trade. There are lots of road blocks to free movements of goods and services in
the region. This result accords well with recent empirical works of Sohn et a.l (2006),
whose findings revealed that FTA enhances growth and is relevant in the global economy
but in the case of East Asian region, it plays a weak role due to the loosest trade
integration of Asian Free Trade Area.
Among the macroeconomic variables, consumer price inflation is significant under the
GLS and GLS with LDV. It is negatively correlated with real GDP per capital growth
rate but the magnitude of the coefficient is very small. The small magnitude is spurred by
the vigorous implementation of the macroeconomic stabilization policies in the region
particularly the WAMU countries.
Nominal exchange rate is statistically significant and positively correlated with growth.
The study can however jump into logic by concluding that the exchange rate devaluation
adopted by many member states in the late 1980s and the early 1990s might have had
some positive effects on economies in the region though the supply response of many
countries for their traded goods are very long. Further, the fact that export is measured in
value terms, might have contributed to the positive correlation on growth.
Terms of trade shows statistically highly significant positive effects on growth under
GLS and GLS with LDV. However, the magnitudes of the coefficients are very small.
This is largely attributed to the level of deterioration experienced by the region during the
period. Further, the low international prices for the region’s exports caused serious
deteriorations over the years. This result shows the growth enhancing effects of the
region’s openness to trade. The result also accords well with previous studies such as
Broda (2003).
37
The lagged dependent variable was included to determine the long-run effects of the
independent variables on growth15
. This can be calculated by multiplying the estimated
coefficient of each of the independent variables by
)1(
1
where
is the estimated
coefficient of lagged dependent variable. The results of the long run effects show that the
magnitudes of the coefficients of many of the exogenous variables are relatively larger as
compare to the static model.
The study reports the R2, standard error of regression, F-statistics, D-W statistics and LM
–Statistics for the regression results. The R2
results under the GLS (66 percent) and GLS
with LDV (65 percent) show that the model is adequate and it explains more than two-
thirds of the variation in economic growth of member states in ECOWAS. The standard
error of regression (1.03) represents approximately three percent of the mean value of
real GDP per capital growth rate. The D-W and L-M statistics all fall within the zone of
no serial correlation suggesting a good model fit.
15
Since the Time period is relatively large (consistent with T ), the LS estimates is consistent for the
dynamic error panel model.
38
4.6.5 Sensitivity Analysis
Table 4.8: Exports and Growth in ECOWAS: Sensitivity Analysis
Dependent variable: 1st log difference of real GDP per capital growth rate
Independent Variables Number of tests conducted
1 2 3 4 5
Lagged log of real GDP per
capital growth rate
-0.138***
[-2.432]
Real Exports/GDP ratio
(RX)
-0.002**
[-1.886]
-0.004***
[-3.584]
-0.003***
[-2.804]
-0.002***
[-2.363]
-0.003***
[-3.045]
Gross fixed capital
formation/GDP (GFCF)
0.011***
[5.554]
0.012***
[6.176]
0.011***
[5.431]
Consumer price Inflation
(CPI)
-0.003***
[-3.249]
-0.006***
[-6.662]
-0.005***
[-4.933]
-0.005***
[-5.031]
-0.005***
[-4.960]
Gross secondary school
enrollment (GSSE)
-0.008***
[-3.677]
-0.010***
[-4.512]
Log of Free Trade Area
(LFTA)
-1.622***
[-5.188]
-1.484***
[-5.079]
-1.543***
[-5.225]
-1.776***
[-5.281]
-2.010***
[-5.413]
Log of Labor force (Llabor) 1.340***
[4.490]
1.336***
[4.787]
1.657***
[5.470]
1.122***
[3.527]
Nominal exchange rate 0.288***
[7.315]
0.219***
[4.846]
0.186***
[3.680]
0.158***
[3.027]
0.278***
[5.238]
Terms of Trade Index
(TOT)
0.003***
[2.889]
0.005***
[4.354]
0.005***
[4.067]
0.005***
[4.059]
0.004***
[4.412]
R2
0.58 0.68 0.67 0.66 0.65
Adjusted R2 0.54 0.65 0.64 0.62 0.61
S.E of Regression 1.03 1.03 1.03 1.03 1.03
F-Statistic 17.39 24.97 23.19 20.30 17.49
Prob (F-statistic) 0.000 0.00 0.00 0.00 0.00
D-W statistic 2.01 2.08 2.09 2.10 ------
LM-Statistic ------ --- ---- 0.12
No. of observations 234 234 234 234 234
Source: Author’s computation using Eviews6
Note: The numbers in parentheses are the t-statistics. * Significant at ten percent;
** significant at five percent and *** significant at one percent.
As represented in column one of table 4.8 above, the study conducted sensitivity analysis
on the original model in order to ascertain whether the variable of interest, real exports to
GDP ratio is robust to the exclusion of certain conditioning variables (factor-input
variables of physical capital, human capital and labor).
39
Though factor inputs of gross fixed capital formation (proxy for physical capital) and
total labor proved to be important determinants of growth in the region during the period
under review, the results indicated that exclusion of these variables do not significantly
affect the signs and magnitudes of real exports to GDP ratio in the region. Hence, the
variable remains robust at five percent level of significance implying that physical
capital, human capital and labor did not jointly drive real exports to GDP ratio over the
period under review. The study however noted that the reduction in the model fitness as
shown by the results in column one is attributed to the exclusion of the aforementioned
traditional factor input variables.
Similarly, the study conducted the second test by adding factor input variables (physical
capital, human capital and labor) one at a time in order to further ascertain the
contribution of each factor input to the signs and magnitudes of real exports to GDP ratio
(from column two through five). The test results indicated that among the three factor-
input variables, only total labor drove exports to GDP ratio over the period under review
(see table 4.8). This implies that the region exports were labor intensive. Further, the
overall fitness of the model increased as the R2 of the original model increased from 66
percent to 68 percent and the DW statistic is within the zone of no serial correlation. The
increase in the robustness of real exports to GDP ratio is in part attributed to the region
exports being labor intensive or labor driven over the period under review. On the other
hand, gross fixed capital formation (proxy for physical capital) and gross secondary
school enrollment (proxy for human capital) proved to have no much impact on the
robustness of real exports to GDP ratio (though their inclusions reduced slightly the sign
and magnitude of the real exports to GDP ratio).
Since column two represents the robust model, its dynamic version was estimated by
adding the LDV. The signs and magnitudes of the coefficients of real exports to GDP
ratio and the controlled variables remain robust. The overall fitness of the model also
remained robust. Even though there were some slight reductions and increments in the
signs and magnitudes of real exports to GDP ratio, it remains robust to the entire
sensitivity test.
40
CHAPTER FIVE
POLICY RECOMMENDATIONS AND CONCLUSION
5.1 Summary of findings
In the presence of controlled variables, the pooled regression results indicate that
significant negative effect of real exports to GDP ratio on economic growth are robust
empirical results for countries in the ECOWAS region. This is largely attributed to the
fact that exports of the region are being dominated by primary commodities and the low
international prices for these commodities over the years had made economies of the
region unstable and more vulnerable to external shocks. The result confirms the Prebisch
(1959) and Sachs et al. (1995) significant negative impact of primary commodities
(natural resources) exports on economic growth. It is also broadly consistent with the
results of Sohn’s et al (2006) and Lederman et al (2003) statistically significant negative
impact of natural resource exports on growth.
Gross fixed capital formation, total labor force, exchange rate and terms of trade appear
to be important determinants of growth in the region as they show positive signs and
proved statistically highly significant. Human capital showed a negative impact on
growth which is contrary to the insights provided by the growth theory. The negative
impact of human capital suggests that there are inadequate mechanisms for transferring
new knowledge into the region and promoting learning-by-doing. In addition, secondary
school education is a low human productivity in the region given the high demand for
highly skilled and trained human resource to compete with the speed of globalization.
This result is broadly consistent with the results of Hausman, et al. (2005) whose findings
revealed that low human capital and weak mechanisms for technology transfer and
learning-by-doing in developing countries have been shown to hamper productivity.
Furthermore, spending in the secondary education sector in developing countries does not
have immediate impact on growth. In other words, this proxy has lagged periods. There is
however, disagreement on the use of gross secondary school enrollment ratio as proxy for
human capital in least developed and developing countries.
41
Significant negative impact of consumer price inflation was also robust in the region but
the magnitude was much smaller implying that inflation in the region was battled to some
minimum level through sounds macroeconomic stabilization policies (particularly the
WAMU countries).
The study conducted sensitivity analysis on the original model in order to ascertain
whether the variable of interest, real exports to GDP ratio is robust to the exclusion of
certain conditioning variables (factor input variables of physical capital, human capital
and labor). Though factor inputs of gross fixed capital formation (proxy for physical
capital) and total labor proved to be important determinants of growth in the region
during the period under review, the results indicated that exclusion of these variables do
not significantly affect the signs and magnitudes of real exports to GDP ratio in the
region. Hence, the variable remains robust at five percent level of significance implying
that physical capital, human capital and labor did not jointly drive real exports to GDP
ratio over the period under review. Similarly, the study conducted the second test by
adding factor input variables (physical capital, human capital and labor) one at a time in
order to further ascertain the contribution of each factor input to the signs and magnitudes
of real exports to GDP ratio (from column two through five). The test results indicated
that among the three factor-input variables, only total labor drove exports to GDP ratio
over the period under review (see table 4.8). This implies that the region exports were
labor intensive.
5.2 Policy recommendations
The results of the study have important policy implications for the region. In order for the
region to derive and improve the growth enhancing effects of exports, the study
recommends the followings:
Diversification of export products to value added: Member states in the region
should redirect their efforts by transforming the current export products into
knowledge based products. This can be done through sound diversification
programme. However, in this diversification programme, emphasis should be
made on the involvement of the private sectors. It is however important to note
42
that diversifications need to be complemented by other none trade factors such as
sounds macroeconomic and institutional policies.
Building the region’s human resources: In order to absorbed new technological
transfers and learning-by-doing associated with exports, efforts should be exerted
by member states in the sub-region to build the human resources and also increase
the mechanisms for technological transfers. Concentration should not only be on
secondary education but also tertiary education given the high demand for highly
skilled and trained human resources in the region to compete with the speed of
globalization.
Incorporation of Free Trade Agreement into National Plans: Member states
should incorporate not by mere signing but by full implementation of agreements
governing Free Trade Area. This will create the facilities and mechanisms
necessary to expedite the free movements of goods and services in ECOWAS. It
will also create an expanded market which can allow for economic of large scale
production (trade creation), fostering of specialization, attracting foreign direct
investment (FDI) and having access to other larger markets.
5.3 Areas of further research and limitations of the study
The paper did not address the problem of endongeneity. Literatures suggest that when
taking into account endongeneity, appropriate instruments should be included in the
growth equations. The limited number of cross section in the study did not permit
estimation of the dynamic version of the model and there is no suitable data for such
instruments for now. Hence, it is left for future studies. Arellano and Bond (1991)
method is appropriate when there is large N and smaller T [N<T]. In this case, N is less
than T (where N is number of cross sections and T is time period), so the Arellano and
Bond 1991’s method is not appropriate for this study. Further areas of study could be the
re-estimation of the dynamic models using the appropriate instruments as suggested by
Arellano and Bond (1991). Another area of study could be examining sectoral
contributions to exports growth in ECOWAS.
43
Additional limitation of the study is the unavailability of long time series data for all the
fifteen countries in West Africa which led to the exclusion of the Republic of Liberia and
Niger Republic. Also due to the aggregate nature of the study, there may be some short
comings in explaining the peculiarities in individual country’s trade policy. However, the
study ensured that these limitations will not cause any significant disparities in the
findings.
5.4 Conclusion
The conclusion drawn from the empirical analysis is that over the years, fluctuations in
exports have negatively affected economic growth in the sub-region. This is in part
attributed to the region’s export structures being concentrated on primary commodities
such as petroleum, cotton, iron ore, and gold.
Pooled estimation technique was used to examine the effects of exports on economic
growth using data for 13 countries in the ECOWAS region. Applying fixed effects
estimation methods for the period 1987 - 2004, the results revealed that negative effects
of exports to GDP ratio and Free Trade Area on growth are robust results for the region.
Gross fixed capital formation, total labor force, exchange rate and terms of trade proved
to be important determinants of economic growth in the region. Gross secondary school
enrollment ratio is statistically highly significant but negatively correlated with economic
growth. The negative impact of gross secondary school enrollment on growth in the
region is in part attributed to the inadequate mechanisms to transfer or absorb new
technologies. Consumer price Inflation negatively affected growth but the magnitude is
much smaller indicating sounds macroeconomic stabilization policies.
The broader implication of the results is that if member states failed to redirect their
efforts in diversifying export products to knowledge-based products, economic growth
will be affected negatively both in the short run and long run.
44
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47
ANNEXES
Annex 1: Data definition and sources (1987 -2004)
Variable Definition Sources
Real GDP (constant 2000 US$) World Development Indicators
Real GDP per capital “ World Development Indicators
RX/GDP Real exports/GDP World Development Indicators
(Constant 2000 US$)
GFCF/GDP Gross fixed capital World Development Indicators
Formation/GDP
TL Total Labor force World Development Indicators
FTA index FTA member countries’ total World Development Indicators
GDP/GDP
Terms of Trade Export price index/import World Bank Africa Database,
Price Index (2000=100) 2006
CPI inflation Consumer price inflation ADB Selected Statistics for
All items (2000 = 100) African countries, 2006
GSSE Gross Secondary School ADB Selected Statistics for
enrollment African countries, 2006
NEER Nominal exchange rate ADB Selected Statistics for
(Annual average) African countries, 2006
48
Annex 2: Performance score-card of some regional groupings in Africa (Annual Av.)
Real GDPP growth (%) C/A (%GDP) F/B (%GDP) CPI Inflation
[1987-2004] [1995-2004] [2000-03] [04] [1990 -2004]
===============================================================
ECOWAS 0.4 -6.6 -4.3 -2.4 11.2
Benin 0.4 -6.8 -1.9 -1.9 6.0
Burkina Faso 0.7 -9.1 -3.9 -4.3 3.6
Cape Verde 2.7 -9.6 -7.6 -1.5 5.3
Cote d’Voire -1.3 -1.3 -1.1 -1.8 4.9
Gambia 0.3 -5.2 -6.2 -5.7 6.9
Ghana 2.0 -5.1 -5.9 -3.1 25.9
Guinea 1.0 -5.9 -4.4 -4.9 8.1
Guinea Bissau -0.8 -11.2 -12.4 -8.4 25.7
Liberia - - - 10.5
Mali 1.5 -7.3 -2.8 -2.7 2.8
Niger -6.3 -3.3 -3.5 3.8
Nigeria 1.4 -0.5 -1.1 7.7 25.4
Senegal 0.6 -5.3 -0.8 -2.0 3.3
Sierra Leone -3.1 -8.5 -8.3 -3.5 31.2
Togo -0.5 -9.7 -0.8 1.9 5.0
SADC 1.0 -4.2 -3.1 -3.9 185.5
Angola 0.5 6.6 4.6 5.1 12.8
Botswana 5.0 8.7 2.1 -0.7 9.7
DR Congo -5.3 -3.4 -3.4 -3.8 2300.9
Lesotho 3.2 -20.6 -1.2 3.3 9.8
Malawi 0.5 -7.7 -6.4 -8.2 26.1
Mozambique 4.7 -16.8 -5.9 -4.4 26.4
Mauritius 4.4 0.2 -7.1 -20.4 6.7
Madagascar -0.8 -6.2 -3.5 -4.8 14.2
Namibia 0.8 4.8 -4.0 -3.4 9.3
Swaziland 1.5 -2.0 -2.9 -2.7 9.4
Tanzania 1.3 -6.3 -1.9 -3.5 16.9
Zambia -0.6 -12.5 -4.8 -2.8 58.2
Zimbabwe -1.3 -2.4 -7.2 -7.0 88.6
South Africa 0.2 -1.1 -1.7 -1.5 8.5
CEMAC 2.0 -15.4 2.6 3.2 4.4
Cameroon -1.6 -2.7 1.9 -0.6 4.3
Central African Rep. -1.6 -3.9 -1.8 -2.3 3.3
Equatorial Guinea 11.5 -57.8 12.2 12.5 6.8
Gabon -0.5 9.0 6.5 7.5 3.8
Chad 2.2 -21.4 -5.6 -1.2 4.0
Source: Author’s computation from SSOAC16
, 2006
Note: C/A – Current Account; F/B – Fiscal Balance; CPI – Consumer Price Inflation
16
Selected Statistics on African Countries, African Development Bank annual statistical publication.
Volume XXV, 2006
49
Performance score-card of some regional groupings in Africa (Annual Avg)
Real GDP growth (%) C/A (%GDP) F/B (%GDP) CPI Inflation
[1987-2004] [1995-2004] [2000-2003] [04] [1990 -2004]
===============================================================
COMESA 0.4 -4.5 -4.9 -3.7 146.9
Burundi -1.4 -5.6 -3.6 -4.3 12.6
Comoros -0.7 -6.5 -3.6 -3.0 3.7
DR Congo -5.3 -3.4 -3.4 -3.8 2300.9
Djibouti -3.0 2.0 -2.3 1.0 3.6
Egypt 2.3 0.2 -5.3 -6.0 8.7
Eritrea -9.3 -31.9 -22.4 -
Ethiopia 1.3 -3.1 -7.1 -3.8 5.9
Kenya 0.1 -2.2 -0.6 0.3 13.9
Libya 1.6 9.7 8.5 5.0 7.5
Madagascar -0.8 -6.2 -3.5 -4.8 14.2
Malawi 0.5 -7.7 -6.4 -8.2 26.1
Mauritius 4.4 0.2 -4.5 -5.3 6.7
Rwanda 0.8 -6.5 -1.2 -0.2 13.0
Seychelles 2.4 -12.0 -9.4 -1.5 2.7
Sudan 3.2 -13.8 -0.4 1.2 55.9
Swaziland 1.5 -2.0 -2.9 -2.7 9.4
Uganda 3.0 -5.3 -4.4 -1.8 11.7
Zambia -0.6 -12.5 -4.8 -2.8 58.2
Zimbabwe -1.3 -2.4 -7.2 -7.0 88.6
Memorandum items:
Africa -1.2 -1.7 -0.5 18.9
Source: Author’s computation from SSOAC17
, 2006 and World Dev. Indicators, 2006
Note: C/A – Current Account; F/B – Fiscal Balance; CPI – Consumer Price Inflation
17
Selected Statistics on African Countries, African Development Bank annual statistical publication.
Volume XXV, 2006
50
Annex 3: Principal export products in ECOWAS
HS-4
lines Product description
2709 Petroleum oils and oils obtained from bituminous minerals, crude.
1801 Cocoa beans, whole or broken, raw or roasted.
2710 Petroleum oils and oils obtained from bituminous minerals, other than crude;
7108 Gold (including gold plated with platinum) unwrought or in semi-
manufactured forms, or in powder form.
5201 Cotton not carded or combed.
2711 Petroleum gases and other gaseous hydrocarbons.
8905 Light-vessels, fire-floats, dredgers, floating cranes…
1803 Cocoa paste, whether or not defatted.
2606 Aluminum ores and concentrates.
1604 Prepared or preserved fish; caviar and caviar substitutes
Source: UNCOMTRADE, and ECOSTAT.
Note: This table also benefited from the work of Remi Rang of UNECA
51
Annex 4: Average growth rate of real GDP per capital (ECOWAS Vs SADC)
-8
-6
-4
-2
0
2
4
6
8
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
SADC
ECOWAS
52
Annex 5: Residual-Actual against Fitted
-.3
-.2
-.1
.0
.1
.2
-1.00
-0.75
-0.50
-0.25
0.00
0.25
0.50
88 90 92 94 96 98 00 02 04
Residual Actual Fitted
Residual graph
-.25
-.20
-.15
-.10
-.05
.00
.05
.10
.15
.20
88 90 92 94 96 98 00 02 04
RESID_BEN Residuals
53
Annex 6: Stability test
-8
-6
-4
-2
0
2
4
6
8
2000 2001 2002 2003 2004
CUSUM 5% Significance
-0.4
0.0
0.4
0.8
1.2
1.6
2000 2001 2002 2003 2004
CUSUM of Squares 5% Significance
54
Annex 7: Exports and Imports in ECOWAS (% of total trade in value terms)
Intra-ECOWAS Trade
Year Exports Imports
1996 10.86 11.25
1997 12.66 10.93
1998 14.59 10.54
1999 10.08 12.44
2000 8.40 16.79
2001 9.25 13.61
Trade with other African countries
Year Exports Imports
1996 14.69 13.94
1997 16.20 13.02
1998 18.53 13.01
1999 13.59 15.29
2000 9.59 19.60
2001 8.70 18.53
Trade outside Africa
Year Exports Imports
1996 73.65 76.42
1997 75.44 77.22
1998 69.50 78.95
1999 76.67 82.13
2000 82.62 78.93
2001 77.12 75.98
Source: ECOSTAT, 2005
55
Annex 8: Summary Statistics of Series for individual countries: 1987 – 2004
Growth GFCF CPI Inflatio LLABOR EXPORTS TOT
BENIN
Mean 0.07 18.12 77.22 14.70 26.57 92.68
Standard dev 0.42 6.40 25.75 0.18 13.40 8.7
[Max, Min] [0.53, -1.09] [30.9,2.42] [112.5,48.1] [14.97,14.4] [58.01,9.98] [106.2,78.2]
BURKINA
Mean 0.12 19.61 83.77 15.29 23.99 117.06
Standard dev 0.55 8.93 17.80 0.15 12.32 7.69
[Max, Min] [1.02, -0.83] [48.40,5.32 [109.1,63.4] [15.54,15.1] [44.29,4.90] [131.0,100.0]
CAPE
VERDE
Mean 0.38 18.93 75.36 11.77 25.19 99.85
Standard dev 0.30 7.98 22.60 0.13 13.27 0.67
[Max, Min] [0.85, -2.3] [34.45,5.42] [104.7,44.4] [11.98,11.6] [48.92,8.87] [100.2,97.2]
COTE
D’IVOIR
Mean -2.1 18.58 80.22 15.50 25.67 104.7
Standard dev 0.47 7.66 23.11 0.15 11.39 22.56
[Max, Min] [0.73, -0.85] [39.74,7.99] [115.5,49.8] [15.71,15.2] [47.23,12.9] [131.3,66.2]
GAMBIA
Mean 0.04 17.98 81.76 13.08 24.63 99.37
Standard dev 0.47 8.70 24.31 0.19 11.16 2.59
[Max, Min] [0.91, -1.07] [43.35,5.35] [118.9,31.4] [13.37,12.8] [49.60,10.2] [100.0,88.9]
GHANA
Mean 0.36 18.28 65.77 15.86 25.17 108.68
Standard dev 0.14 7.99 68.34 0.14 11.91 11.43
[Max, Min] [0.63, 0.09] [42.44,8.50] [215.2,4.10] [16.07,15.6] [51.05,9.1] [132.2,88.95]
GUINEA
Mean 0.16 16.74 77.53 15.08 26.95 121.15
Standard dev 0.27 4.51 31.19 0.15 12.47 21.53
[Max, Min] [0.58, -0.45] [24.11,8.57] [122.7,19.8] [15.28,14.8] [53.27,9.2] [157.9,99.5]
G. BISSAU
Mean -0.22 16.37 52.66 13.09 26.15 103.98
Standard dev 1.80 4.50 46.95 0.15 11.67 29.4
[Max, Min] [1.56, -6.70] [22.78,8.50] [115.8,0.80] [13.34,12.9] [49.42,8.5] [181.1,68.6]
MALI
Mean 0.27 17.36 84.84 15.28 26.62 108.99
Standard dev 0.75 4.79 16.61 0.13 10.49 12.44
[Max, Min] [1.68, -0.92] [27.33,8.30] [106.9,62.5] [15.49,15.1] [50.37,8.5] [130.8,84.5]
NIGERIA
Mean 0.23 19.05 59.16 17.45 29.50 77.51
Standard dev 0.53 6.00 53.72 0.14 14.09 21.88
[Max, Min] [1.35, -0.62] [35.21,7.70] [161.1,3.30] [17.66,17.2] [55.06,8.6] [124.8,44.3]
SENEGAL
Mean 0.10 20.78 86.11 15.10 30.90 116.89
Standard dev 0.43 7.38 16.36 0.14 13.89 15.23
[Max, Min] [0.64, -0.82] [44.70,8.50] [106.1,67.2] [15.32,14.9] [59.90,8.9] [134.7,98.4]
S. LEONE
Mean -0.62 19.20 45.60 14.42 28.96 137.78
Standard dev 1.45 7.00 40.53 0.10 13.38 49.23
[Max, Min] [0.86, -3.87] [38.98,5.60] [105.4,0.50] [14.64,14.3] [63.64,8.9] [291.2,74.5]
TOGO Mean -0.12 18.83 77.72 14.41 28.81 118.08
Standard dev 1.23 5.21 21.63 0.17 14.38 18.54
[Max, Min] [2.14, -3.41] [29.93,10.4] [104.4,54.4] [14.67,14.1] [62.94,9.9] [144.1,91.9]
OVER ALL
Mean 0.04 18.45 72.90 14.69 26.93 108.21
Standard dev 0.85 6.78 36.39 1.38 12.49 24.98
[Max, Min] [2.14, -6.70] [48.40,2.42] [215.2,0.50] [17.66,11.6] [63.64,4.90] [291.2,44.3]
56
Annex 9: Residual-Correlation Matrix
Annex 10: Residual-Covariance Matrix
Annex 10: Residual-Covariance Matrix
BEN BFA CPV CIV GMB GHA GIN GNB MLI NGA SEN SLE TGO
BEN 1.000000 0.420717 0.187650 0.015723 -0.259762 -0.270354 0.184648 -0.112972 -0.130580 -0.103980 0.086877 -0.358677 0.005696
BFA 0.420717 1.000000 0.190696 0.338187 0.198249 0.350833 0.132107 0.330257 0.093357 0.234119 -0.089132 -0.166965 -0.039007
CPV 0.187650 0.190696 1.000000 0.080451 0.156975 -0.032347 0.427355 -0.213786 0.160155 -0.175372 -0.167231 -0.414547 -0.101268
CIV 0.015723 0.338187 0.080451 1.000000 0.160049 0.096731 0.302713 0.009189 0.324017 0.024589 0.062442 -0.389660 0.234340
GMB -0.259762 0.198249 0.156975 0.160049 1.000000 0.344414 -0.170299 0.299679 0.264491 0.432889 0.141280 -0.164130 -0.227184
GHA -0.270354 0.350833 -0.032347 0.096731 0.344414 1.000000 -0.065565 0.111082 -0.023151 0.484936 -0.277967 -0.102260 -0.354034
GIN 0.184648 0.132107 0.427355 0.302713 -0.170299 -0.065565 1.000000 -0.094733 0.129156 0.024036 0.159641 -0.552547 0.175980
GNB -0.112972 0.330257 -0.213786 0.009189 0.299679 0.111082 -0.094733 1.000000 -0.029600 0.135695 0.012332 -0.089431 0.267462
MLI -0.130580 0.093357 0.160155 0.324017 0.264491 -0.023151 0.129156 -0.029600 1.000000 0.064673 -0.086548 -0.416082 0.166451
NGA -0.103980 0.234119 -0.175372 0.024589 0.432889 0.484936 0.024036 0.135695 0.064673 1.000000 0.117045 -0.172316 -0.021475
SEN 0.086877 -0.089132 -0.167231 0.062442 0.141280 -0.277967 0.159641 0.012332 -0.086548 0.117045 1.000000 -0.123335 0.363234
SLE -0.358677 -0.166965 -0.414547 -0.389660 -0.164130 -0.102260 -0.552547 -0.089431 -0.416082 -0.172316 -0.123335 1.000000 -0.264957
TGO 0.005696 -0.039007 -0.101268 0.234340 -0.227184 -0.354034 0.175980 0.267462 0.166451 -0.021475 0.363234 -0.264957 1.000000
BEN BFA CPV CIV GMB GHA GIN GNB MLI NGA SEN SLE _TGO
BEN 0.097134 0.065718 0.017266 0.001834 -0.031566 -0.025957 0.013844 -0.057237 -0.027762 -0.016810 0.009540 -0.168063 0.001947
BFA 0.065718 0.251200 0.028216 0.063429 0.038742 0.054168 0.015929 0.269081 0.031919 0.060867 -0.015739 -0.125812 -0.021446
CPV 0.017266 0.028216 0.087155 0.008888 0.018069 -0.002942 0.030351 -0.102601 0.032254 -0.026856 -0.017394 -0.183995 -0.032796
CIV 0.001834 0.063429 0.008888 0.140038 0.023353 0.011151 0.027252 0.005590 0.082715 0.004773 0.008233 -0.219227 0.096199
GMB -0.031566 0.038742 0.018069 0.023353 0.152025 0.041369 -0.015974 0.189949 0.070350 0.087553 0.019408 -0.096212 -0.097171
GHA -0.025957 0.054168 -0.002942 0.011151 0.041369 0.094901 -0.004859 0.055629 -0.004865 0.077492 -0.030170 -0.047362 -0.119641
GIN 0.013844 0.015929 0.030351 0.027252 -0.015974 -0.004859 0.057875 -0.037048 0.021196 0.002999 0.013531 -0.199847 0.046442
GNB -0.057237 0.269081 -0.102601 0.005590 0.189949 0.055629 -0.037048 2.642683 -0.032825 0.114425 0.007063 -0.218572 0.476962
MLI -0.027762 0.031919 0.032254 0.082715 0.070350 -0.004865 0.021196 -0.032825 0.465358 0.022885 -0.020801 -0.426734 0.124560
NGA -0.016810 0.060867 -0.026856 0.004773 0.087553 0.077492 0.002999 0.114425 0.022885 0.269073 0.021391 -0.134383 -0.012220
SEN 0.009540 -0.015739 -0.017394 0.008233 0.019408 -0.030170 0.013531 0.007063 -0.020801 0.021391 0.124131 -0.065330 0.140387
SLE -0.168063 -0.125812 -0.183995 -0.219227 -0.096212 -0.047362 -0.199847 -0.218572 -0.426734 -0.134383 -0.065330 2.260313 -0.436977
TGO 0.001947 -0.021446 -0.032796 0.096199 -0.097171 -0.119641 0.046442 0.476962 0.124560 -0.012220 0.140387 -0.436977 1.203366
57