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TITLE PAGE
TRADE OPENNESS AND OUTPUT GROWTH IN
NIGERIA: AN ECONOMETRIC ANALYSIS (1970-2007)
A PROJECT SUBMITTED IN PARTIAL FULFILIMENT FOR
THE COURSE REQUIREMENT FOR THE AWARD OF
BACHELOR OF SCIENCE (B.Sc) DEGREE IN ECONOMICS
BY
ALUM EMEKA .J.
EC/2006/259
DEPARTMENT OF ECONOMICS
FACULTY OF MANAGEMENT AND SOCIAL SCIENCES
CARITAS UNIVERSITY AMORJI-NIKE EMENE, ENUGU
AUGUST 2010
iv
APPROVAL PAGE
This is to certify that this project was undertaken by Alum Emeka
Japhet and duly supervised and approved as having met the
requirement for the award of Bachelors of Science (B.Sc.) degree in
the department of economics, Caritas University. Amorji-Nike, Enugu
State.
…………………………….
Ojike, R. O.
Project Supervisor
Date:………………….
………………………..
Peter. C. Onwudinjo Esq
Head of Department
Date:…………………
……………………………..
Dr. C.C. Umeh
Dean, Faculty of Management
And Social Science
Date:…………………
………………………….
External Examiner
Date:………………..
iv
DEDICATION
To God Almighty the Giver of wisdom and the creator of
heaven and earth.
iv
ACKNOWLEDGMENT
To my father and mother Mr. and Mrs. Alex, F. Alum, To
BABA God in Heaven.
To my supervisor Mr. Ojike R.O. for his kind supervision
throughout the course of this project. Thank you very much.
To my H.O.D Peter C. Onwudinjo Esq, all my lecturers,
Mrs. Okonkwo P.C, Mr. Agu S.V, Mr. Ojike R.O, Dr Umeadi
C.C, Dr Asogwa, Mr. Ugwu, Prof. Udabah and Prof. Onah
for their
inspiration throughout
the
course
of
my
studies.
May God Almighty bless them.
To my brothers and sister Eloka, Uchenna and Mercedes.
To my siblings Brother Prince, Brother Dan, Brother Godwin,
and to all my Aunties, And all the Alum Families.
To my friends Aduaka Hilary (Pojas), Ejike Ezeorah
(Madukanaya), Joseph. O. Faithful (Kpanko), David (Night
Walker), David Eme Njokwu (H.O.D),
Chibuike,
Kala,
Mgbade, K.c, and all those that I could not include their names
due to circumstances.
iv
To my class mates, Femi, Titi, Nwankwo John, Emenike,
John, Enesi, Goodness, Ezinne, Jenifer, Onyekachi Kalu, and all
my course mates, it was fun learning together.
Special thanks to all my room mates, Chidera, Richard,
Funcho, Koja, Godwin and Pastor Methusela.
Alum Emeka Japhet
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ABSTRACT
This research work studies the international competitiveness of the
Nigerian economy in the global market by analyzing the relationship
between trade openness and output growth in Nigeria. Using timeseries data over the period 1970-2007, we show that output growth of
the Nigeria economy is a function of two sets of shocks; (i) external
shocks (openness and real exchange rate) and (ii) internal shocks
(real interest rate and unemployment rate). A non-monotonic and an
ANCOVA econometric models are postulated in order to capture the
structural pattern of the relationship between openness and output
growth as well as the policy effect of structural Adjustment program
(SAP). The result shows that there is an inverted U-shape (nomonotonic) relationship between openness and output growth in
Nigeria and the optimum degree of openness for the economy is
estimated to be about 67%. Also, the liberalization policy of the SAP
has positive economic effect on the output growth. The ECM reveals
that 79% of the equilibrium error is being corrected in the next
period. We concluded that unbridled openness may have deleterious
effect on the real growth of output of the Nigerian economy.
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TABLE OF CONTENTS
Title page
i
Approval page
ii
Dedication
iii
Acknowledgement
iv
Abstract
v
Table of contents
vi
List of tables and figures
ix
CHAPTER ONE: INTRODUCTION
iv
1.1
Background of study
1
1.1.2 Trade openness and output growth
Historical Experience of the Nigeria economy
3
1.2
Statement of the research problem
14
1.3
Objectives of the study
16
1.4
Statement of the research hypothesis
17
1.5
Justification of the study
17
1.6
Significance of the study
18
1.7
Scope and limitation of the study
19
CHAPTER TWO: LITERATURE REVIEW
iv
2.1
Theoretical literature
21
2.1.2 Theory of customs union and free trade areas
37
2.1.3Models of export-led growth
40
2.2
Empirical literature
45
2.3
Limitation of previous studies
69
CHAPTER THREE: METHODOLOGY
3.1
Analytical framework
70
3.2
Model specification
71
3.2.1 Test of stationarity
74
iv
3.2.2 Test of co integration
75
3.2.3 Error correction model
76
3.3
Justification of the model
78
3.4
Estimation techniques
80
3.5
Evaluation Procedure
81
3.5.1 Economic test (a priori expectation)
81
3.5.2 Statistical (first order) test
83
3.5.3 Econometric (second order) test
84
3.6
Sources of data and software for estimation
85
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CHAPTER FOUR: PRESENTATION AND ANALYSIS OF
RESULTS
4.1
Introduction
87
4.2
Presentations of regression results
87
4.2.1Test of stationarity
89
4.2.2 Test of co integration
91
4.2.3 The Error correction model (ECM)
92
4.3
Interpretation and Evaluation of result
93
4.3.1Evaluation based on economic criteria
93
4.3.2Evaluation based on statistical criteria
103
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4.3.3 Evaluation based on econometric criteria
110
4.4
Evaluation of the working Hypotheses
118
CHAPTER FIVE: SUMMARY, POLICY PRESCRIPTION
AND CONCLUSION
5.1
Summary
122
5.2
Policy Recommendations
123
APENDIX
I
APENDIX
II
APENDIX
III
(A)
APENDIX
III
(B)
APENDIX
III(C)
iv
APENDIX
III
(D)
APENDIX
III (E)
APENDIX
III (F)
APENDIX
IV
APENDIX
V
APENDIX
VI
APENDIX
VII
APENDIX
VIII
APENDIX
IX
APENDIX
X
APENDIX
XI
APENDIX
XII
LIST OF TABLES AND FIGURES
Figure 1:
Growth Rate of Real GDP
iv
Figure 2: Trend of Real GDP
Figure 3: Growth of Export and Import
Figure 4: The Degree of Openness
Table 1: Openness Indicators
Table 2: A Priori Expectation
Table 3: Results of Model 1
Table 4: Results of Model 2
Table 5: Results of Stationarity test
Table 6: Results of Co integration test
Table 7: Results of the Error Correction Model
Figure 5: Non- Monotonic Relationship between TPN and RGDP
Table 8: Summary of the T-Test
Table 9: Pair-Wise Correlation Matrix
CHAPTER ONE
INTROUDCTION
iv
1.1
BACKGROUND OF STUDY
The current period in the world economy is regarded as period
of globalization and trade liberalization. In this period, one the crucial
issues in development and international economics is to know whether
trade openness indeed promotes growth. With globalization, two
major trends are noticeable: first is the emergence of multinational
firms with strong presence in different, strategically located markets;
and secondly, convergence of consumer tastes for the most
competitive products, irrespective of where they are made. In this
context of the world as a “global village”, regional integration
constitutes an effective means of not only improving the level of
participation of countries in the sub-region in world trade, but also
their integration into the borderless and interlinked global economy.
(NEEDS, 2005).
Since 1950, the world economy has experienced a massive
liberalization of world trade, initially under the auspices of the
General Agreement on Tariffs and trade (GATT), established in 1947,
and currently under the auspices of the World Trade Organization
iv
(WTO) which replaced the GATT in 1993. Tariff levels in both
developed and developing countries have reduced drastically,
averaging approximately 4% and 20% respectively, even though the
latter is relatively high. Also, non-tariff barriers to trade, such as
quotas, licences and technical specifications, are also being gradually
dismantled, but at a slower rate when compared with tariffs.
The liberalization of trade has led to a massive expansion in the
growth of world trade relative to world output. While world output (or
GDP) has expanded fivefold, the volume of world trade has grown 16
times at average compound rate of just over 7% per annum. In fact, it
is difficult, if not impossible, to understand the growth and
development process of countries without reference to their trading
performance. (Thirlwall, 2000).
Likewise, Fontagné and Mimouni (2000) noted that since the
end of the European recovery after World War II, tariff rates have
been divided by 10 at the world level, international trade has been
multiplied by 17, world income has quadrupled, and income per capita
has doubled. Incidentally, it is well known that periods of openness
iv
have generally been associated with prosperity, whereas protectionism
has been the companion of recessions. In addition, the trade
performance of individual countries tends to be good indicator of
economic performance since well performing countries tend to record
higher rates of GDP growth. In total, there is a common perception
that even if imperfect competition and second best situations offer the
possibility of welfare improving trade policies, on average free trade
is better than no trade.
From the ongoing discussion, it is evident that trade is very
important in promoting and sustaining the growth and development of
an economy. No economy can isolate itself from trading with the rest
of the world because trade act as a catalyst of growth. Thus Nigeria,
being part of the world, is no exemption. For this reason, there is a
need to thoroughly examine the nature of relationship between trade
openness and output growth in Nigeria.
1.1.2
TRADE OPENNESS AND OUTPUT GROWTH:
HISTORICAL
ECONOMY
EXPERIENCE
OF
THE
NIGERIA
iv
Today, Nigeria is regarded to have the largest economy in subSaharan Africa, excluding South Africa. In the last four decades there
has been little or no progress realized in alleviating poverty despite
the massive effort made and the many programmes established for
that purpose. Indeed, as in many other sub-Saharan Africa countries,
both the number of poor and the proportion of poor have been
increasing in Nigeria. In particular, the 1998 United Nations human
development report declares that 48% of Nigeria’s population lives
below the poverty line. According to the report (UNDP, 1998). The
bitter reality of the Nigerian situation is not just that the poverty level
is getting worse by the day but more than four in ten Nigerians live in
conditions of extreme poverty of less than N320 per capita per month,
which barely provides for a quarter of the nutritional requirements of
healthy living. This is approximately US 8.2 per month or US 27 cents
per day.
Doug Addison (unpublished) further explained that the Nigeria
economy is not merely volatile; it is one of the most volatile
economies in the world (see figure 1 below). There is evidence that
iv
this volatility is adversely affecting the real growth rate of Nigeria’s
gross domestic product (GDP) by inhibiting investment and reducing
the productivity of investment, both public and private. Economic
theory and empirical evidence suggest that sustained high future
growth and poverty reduction are unlikely without a significant
reduction in volatility. Oil price fluctuations drive only part of
Nigeria’s volatility policy choices have also contributed to the
problem. Yet policy choices are available that can help accelerate
growth and thus help reduce the percentage of people living in
poverty, despite the severity of Nigeria’s problems.
Figure 1: growth rate of real GDP
Nigeria real GDP Growth Rate
Real GDP growth Rate (%)
50
40
30
20
10
0
10
iv
Year
During the period 1960-1997, Nigeria’s growth rate of per
capital GDP of 1.45% compares unfavorably with that reported by
other countries, especially those posted by china and the Asian Tigers
such as Hong Kong, Singapore, Taiwan, and south Korea, viewed in
this comparative perspective, Nigeria’s per capita income growth has
been woefully low and needs to be improved upon. (Iyoha and
Oriakhi, 2002). In like manner, ogujiuba, Oji and Adenuga (2004)
wrote that the Nigerian economy has severally been described as a
difficult environment for business with a population growth of about
3%, it has been acknowledged that the current average output growth
rate of less than 4% will see the country being poorer in the next
decade.
iv
A study conducted by Iyoha and Oriakhi (2002) on Nigeria’s
per capita GNP from 1964 to 1997 show that it rose steadily from
US$120 to US$780 in 1981. Thereafter, it fell almost steadily to
US$280 in 1997. Thus, between 1964 and 1981, income per capita
increased by 550% or at an annual average rate of 32.3% while
between 1981 and 1997, it fell by 64.1% or at an annual average rate
of 4%. It is worth noting that if income per capita had continued to
increase beyond 1981 as it did before then, Nigeria’s GDP per capita
would have equaled US$1,279 in 1997. The difference between US
$280 and US$1,279, i.e, approximately, US$1,000.00, is a rough
measure of the cost to the average Nigerian of domestic macro
economic policy mistakes and adverse international economic shocks.
Likewise in 1960 agricultural exports accounted for only 2.6%.
Exports of other commodities like tin and processed goods amounted
to 26.6% of total exports. By 1970 agricultural exports only accounted
for 33% of total exports while petroleum exports had started to
establish dominance by exceeding 58% of total exports. By the time
the oil boom began in earnest in 1974, petroleum exports accounted
iv
for approximately 93% of all exports. The relative share of
agricultural exports in total exports had shrunk to 5.4% while other
products accounted for the remaining 1.9%. Since 1974, with the
exception of 1978 when the relative share of petroleum in total
exports has exceeded 90%. In deed, since 1990, the relative share of
petroleum in total exports has exceeded 96%. Agricultures
contribution has fluctuated between 0.5% and 2.3% while the share of
other products has fluctuated between 0.5% and 1.7%. Thus
petroleum exportation has totally dominated the economy and indeed
government finances since the mid-1970s.
Meanwhile, a puzzling and disturbing aspect of Nigeria export
boom is that the growth it generated did not seem to be lasting or to
have had a significant effect in changing the structure of the economy.
For instance, in the 1970’s there was a major increase in measured
GDP but the structure of the economy remained basically unchanged
(see figure 2 below). This led professor Yesufu (1995) to describe the
Nigerian economy as one that had experienced “growth without
development’’.
iv
Figures 2: trend of real GDP
-.-RGDP –
linear
(RGDP)
Real GDP
300000
250000
200000
150000
100000
500000
Year
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
During the period of 1970 – 1985, import substitution
industrialization (ISI) strategy was a dominant feature of trade policy
in Nigeria. The trade policy was generally inward oriented. Under this
ISI strategy, “Infant” manufacturing industries were protected using
high tariffs, import quotas, and other trade restrictions like import
licensing. Non-tariff barriers to trade such as import prohibitions were
iv
also utilized. During this period, trade policy was also adjusted in
response to the exigencies of the balance of payments.
Also, Nigeria was operating a fixed exchange rate regime under
which the value of the Naira was essentially tied to US dollar and
gold. It is worth noting that the trade policy pursued during this period
resulted in a rapid increase in manufacturing production and
employment, particularly during the era of the oil boom (1975 -1980)
and that led to a rise in the share of manufacturing in Gross Domestic
product (GDP) from 5.6% in 1962/63 to 8.7% in 1986. (Iyoha and
Oriakhi, 2002).
In 1986, Nigeria adopted the structural adjustment programme
(SAP) of the IMF/World Bank. With the adoption of SAP in 1986,
there was a radical shift from inward-oriented trade policies to out
ward –oriented trade policies in Nigeria.
These are policy measures that emphasize production and trade
along the lines dictated by a country’s comparative advantage such as
export promotion and export diversification, reduction or elimination
of import tariffs, and the adoption of market-determined exchange
iv
rates some of the aims of the structural adjustment programme
adopted in 1986 were diversification of the structure of exports,
diversification of the structure of production, reduction in the overdependence on imports, and reduction in the over-dependence on
petroleum exports. The major policy measures of the SAP were:

Deregulation of the exchange rate

Trade liberalization

Deregulation of the financial sector

Adoption of appropriate pricing policies especially for
petroleum products.

Rationalization and privatization of public sector enterprises
and

Abolition of commodity marketing boards.
However, as a result of trade liberalization gospel of the SAP,
the Nigeria external sector really experience dramatic growth. For
instance, the total domestic exports of Nigeria in 2006 amounted to
N755141.32 million against N6621303.64 million in 2005 showing an
increase of 14.10%. Domestic exports recorded negative growth rates
iv
in 1993 (7.70%), 1994 (45.5%), 1997 (2.03%), 1998 (38.48%) and
2001 (27.06%); while it recorded positive growth rates in other
periods. The largest increase in domestic exports was witnessed in
1995 (448.42%). Total imports (C.I.F) stood at N2922248.46 in 2006
as against N1779601.57 million in 2005 recording an increase of
64.20%. Total imports also recorded negative growth rates in
1994(45.72%),1998(9.41%) and 2004(18.07%) while it is positive all
through other years. The value of total merchandise trade amounted to
N10477389.78 million in 2006 as against N45272.24 recorded in
1987. External trade was dominated by domestic exports between
1987 and 2006
averaging 67.17% while imports (C.I.F) averaged
32.82% (see figure 3 below), consequently, the trade balance was
positive between 1987 and 2006. Oil export remains the dominant of
export trade in Nigeria between 1987 and 2006 accounting for about
93.33% of total domestic exports. On the other hand, non oil exports
accounted for a small value of 6.67% over the same period. (NBS
report, 2008).
iv
FIGURES 3: GROWTH OF EXPORT AND IMPORT
NIGERIA IMPORT AND EXPORT
Import and export
9000000
8000000
7000000
6000000
5000000
4000000
3000000
2000000
1000000
0
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
iv
Therefore, it could be understood that the SAP involved the
deregulation and liberalization of the Nigerian economy. This policy
thrust of this program dovetailed nicely with the emerging
international orthodoxy to the effect that deregulation and economic
liberalization would yield the optimal allocation of scarce resources,
reduce waste, and promote rapid economic growth in developing
countries. Unfortunately, there has been no significant progress made
in the achievement of these objectives. The openness of the economy
has significantly increased in the past four decades, with the tradeGDP ratio rising from 31.54% in 1970, to 46.91% 1980, 57.23% in
1990, 88.16% in 1995, 85.26% in 2003 and 57.63% in 2007 (see
figure 4 below) indeed, in the 1990s the ratio of trade to GDP has
averaged 70%. This extreme openness of the economy could be
disadvantageous in that it makes the country highly susceptible to
internationally transmitted business cycles, and, in particular
international transmitted shocks (like commodity price collapse). A
good example of this effect on the Nigerian economy is that of the
iv
global food crisis of 2007 and the current global economic/financial
crisis.
FIGURES 4: THE DEGREE OF OPENNESS
NIGERIA IMPORT AND EXPORT
100
Degree trade openness (5)
90
80
70
60
50
40
30
20
1.2
STATEMENT OF THE RESEARCH PROBLEM
10
Nwafor
Manson
(unpublished)
the 1995
Nigeria’s
0
1965
1970
1975 1980 not
1985that1990
2000 trade
2005
policy over the years has been determined by one/ more of the
following.
 Need to protect and stimulate domestic production (import
capital goods at low prices etc)
 Need to ameliorate/prevent balance of payment problems.
2010
iv
 Need to boost the value of the naira
 Need to be competitive and enjoy the benefits of openness.
 Need to increase revenue and
 International agreements
Today, as part of moving with the trend of globalization and
trade liberalization in the global economic system, Nigeria is a
member of and sygnatory to many international and regional trade
agreements such as international monetary fund (IMF), world trade
organization (WTO), economic community of West African States
(ECOWAS), and so many others. The policy response of such
economic partnership on trade has been to remove trade barriers,
reduce tariffs, and embark on outward-oriented trade policies. Despite
all her effort to meet up with the demands to these economic
partnerships in terms of opening up her border, according to the 2007
assessment of the trade policy review, Nigeria’s trade freedom was
rate 56% making her the worlds 131st freest economy while in 2009, it
was ranked 117th freest economy, the country’s GDP was also ranked
161st in the world in February, 2009. The economy has struggled
iv
vigorously to stimulate growth through openness to trade, In fact, it
seems that as the country put greater effort to boost her economic
growth by opening up to trade with the global economy the more she
becomes worse-off relative to her trading partners in terms of country
output growth.
Having reviewed the related literatures and considering the
structure of the Nigerian economy as related to trade openness and
output growth, we may then ask the following questions.
 Does trade openness have any significant impact on out put
growth in Nigeria?
 Is there any other macroeconomic variable that has significant
impact on output growth in Nigeria?
 Is there any linear association (correlation) between trade
openness and output growth in Nigeria?
 Is there long run relationship between trade Openness and
output growth in Nigeria?
 Has there been any significant structural change in output
growth between the pre-SAP and post-SAP period in Nigeria?
1.3OBJECTIVES OF THE STUDY
iv
The broad objective of this research work is to study, in its
entirely, the relationship between trade openness and output growth in
Nigeria. This broad objective can be subdivided into the following
smaller objectives:
 To examine the impact of trade openness on output growth in
Nigeria.
 To identify other internal and external macroeconomic shocks
that determine output growth in Nigeria.
 To identify other international and external macro economic
shocks that determine output growth in Nigeria.
 To determine the linear association (correlation) between trade
openness and output growth in Nigeria.
 To ascertain the possibility of long run relationship between
trade openness and output growth in Nigeria.
 To determine the possibility of structural changes (if any) in
output growth between the pre-SAP and post-SAP period.
1.4
STATEMENT OF THE RESEARCH HYPOTHESES
iv
In view of the foregoing study, with respect to trade openness
and output growth in Nigeria, the following null hypothesis will be
tested:
Ho:
Trade openness does not have any significant impact on output
growth in Nigeria.
Ho: There is no other macroeconomic variable (internal and
external) that have significant impact on output growth in
Nigeria.
Ho: There is no linear association (correlation) between trade
openness and output growth in Nigeria.
Ho: There is no long run relationship between trade openness and
output growth in Nigeria.
Ho: There is no significant structural change in output growth
between the pre-SAP and post-SAP period.
1.5
JUSTIFICATION OF THE STUDY
Nigeria is currently undergoing a series of transformation in
every sector of the economy, including the external sector of the
economy. The country’s economic policy in the last two decades had
iv
one dominating theme which is an integral part of the structural
Adjustment programme (SAP) – trade liberalization. This policy was
espoused on the argument that it enhances the welfare of consumers
and reduces poverty as it offers wider platform for choice from among
wider variety of quality goods and cheaper imports. Today, there are
many existing literature on the topical issue of trade openness and
growth of which some support the axiom that openness is directly
correlated to greater economic growth with the main operational
implication being that governments should dismantle the barriers to
trade. The focal point of this research work is to identify the short
comings and benefits of this argument as well as check the validity of
this mainstream axiom I Nigeria in the presence of various internal
and external shocks.
1.6
SIGNIFICANCE OF THE STUDY
The role of international trade in the developmental journey of
an economy can not be over emphasized, especially with the current
trend of globalization. Nigeria. Being part of the global village, is not
left out of this world development. This research work is carried out
iv
to study how trade openness has influenced the performance of the
Nigeria economy through output growth in the presence of other
internal and external shocks. The findings of this research work
transcend beyond mere academic brainstorming, but will be of
immense benefit to federal agencies, policy makers, intellectual
researcher and international trade think tanks that occasionally
prescribe and suggest policy options to the government on trade
related issues. It will also help the government to see the effectiveness
of trade liberalization policy on the economic growth of the nation
over the years. This research work will further serve as a guide and
provide insight for future research on this topic and related field for
students who are willing to improve it. It will also educate the public
on various government policies as related to trade issues.
1.7
SCOPE AND LIMITATION F THE STUDY
This research work span through the period of 1970-2007 (38
years), and is within the geographical zone of Nigeria. Thus, it is a
country-specific research. This research exercise, like every other
research work, is really a rigorous one that consumes much time and
iv
energy especially in the area of data sourcing, data computation and
modeling. This work is relatively limited base on time and financial
constraints, data availability precision of data and data range, and
methodology adopted which could further be verified by future
research. Nevertheless, the researchers have properly organized the
research so as to present dependable results which can aid effective
policy making and implementation at least for the time being.
CHAPTER TWO
LITERATURE REVIEW
“Openness” refers to the degree of dependence of an economy
on international trade and financial flows. Trade openness measures
the international competitiveness of a country in the global marked.
Thus, we may talk of trade openness and financial openness. Trade
openness is often measured by the ratio of import to GDP or
alternatively, the ratio of trade to GDP. It is now generally accepted
that increase openness with respect to both trade and capital flows will
be beneficial to a country. Increased openness facilities greater
integration into global markets. Integration and globalization are
beneficial to developing countries although there are also some
iv
potential risks. (Iyoha and Oriakhi, 2002). Trade openness is
interpreted to include import and export taxes, as well as explicit non
tariff distortions of trade or in varying degrees of broadness to cover
such matters as exchange-rate policies, domestic taxes and subsides,
competition and other regulatory policies, education policies, the
nature of the legal system, the form of government, and the general
nature of institution and culture (Baldwin, 2002).
2.1
THEORETICAL LITERATURE
The issue of whether trade and increased openness would lead
to higher rate of economic growth is an age-old question which has
sustained debate between pro-traders and protectionists over the years
from classicalists like Adam Smith, John Stuart mill, to John Maynard
Keynes, Raul Prebisch, Hans Singer, Paul Krugman and many others.
Theorists from both theses have influenced policy many countries and
at various stage of development there has also been a huge policy
debate about what constitute “good” and “bad” policies for these
countries, especially the developing countries such as Nigeria should
iv
these countries completely open up to international trade? Or should
they instead, at least temporality, protect some or all of their industries
from the world marked forces? Form arguments have been developed
pro and con of both theses. These arguments were discussed
extensively by Maskus (1998) thus:
Argument One: Economies Will Grow Faster If They Protect
Domestic Industry From Import Competition
This is a general statement of the infant-industry hypothesis”,
which states that manufacturing sectors in underdeveloped economics
must be sheltered from competition in order to have the incentive to
invest capital, learn how to produce goods efficiently, take advantage
of scale economies through large scale production, and develop
innovative or distinctive products that can be sold on world markets.
The broadest application of the infant-industry argument for world
markets. The broadest application of the infant-industry argument for
isolation from global markets emerged in the widespread use of
import substitution policies in developing countries.
iv
A policy of import substitution for industrialization purpose
(ISI) involves extensively controlling virtually all components of the
economy in order to direct resources into manufacturing. It is an old
idea, but its modern origins come from economists writing in the
1950s and 1960s (Arthur Lewis, Raul Prebish, Hans singer, Gunnar
Myrdal., and others), who claimed that developing economies faced
two fundamental problems. First, their status as primary-commodity
exporters left them vulnerable to world swings in commodity prices
(e.g. oil, sugar, tin, copper, etc) and also that over a long-run,
commodity prices would decline relative to manufacturing prices and
costs of new technologies. Second, because developing countries have
high population growth rates and abundant labor supplies, it would be
difficult to absorb workers into primary production. Rather than
waiting for comparative advantage to push resources into laborintensive manufacturing, it would be better to force industrialization
through ISI policies. Such programmes become common in the 1950s
throughout Latin America, Africa, the Middle East, South Asia and
Southeast Asia; they are still much in evidence in many countries.
iv
Policies imposed in a thorough ISI programme include the
following:
 Escalating tariffs, or tariff rates that rise with the stage of
processing. Thus, low tariffs on primary goods, medium tariffs
on industrial inputs and machinery, and high tariffs on final
goods, particularly consumers goods such as food products,
clothing, cosmetics, automobiles, and so on. Such tariff
structures established very high effective rates of protection for
final goods, meaning that auto factories and so on were strongly
protected.
 Considerable taxes on production of primary commodities in
other to push labor out of the country’s side and into the cities
for developing manufacturing. Such taxes include tariffs on
imported fertilizer price ceilings at very low rates for crops,
export taxes on farm goods, and so on. For these reason ERPs
in agriculture were often strongly negative, vastly reducing
output and productivity in farming.
iv
 Fixing exchange rates at expensive levels (i.e. “overvaluing”
the domestic currency), again in order to discourage primary
exports and production and also to reduce the cost of imported
inputs for manufacturing sectors. Such exchange rates tended to
generate large trade deficits, forcing governments to borrow
from abroad and build up debt. It also required setting and
controlling multiple exchange rates, so that capital and input
transactions could take place at cheaper rates than goods
imports in order to protect domestic industry.
 Extensive systems of quotas and licensing for imports and
production.
 Rigorous controls on FDI coming into the country, requiring
foreign firms to meet certain performance requirements. Also
controls on imported technologies, with governments placing
restrictions on costs of technology and under what terms it
would be transferred to local firms.
 Extensive nationalization of industry to establish state-owned
enterprises (SOEs) in key sectors, such as petroleum, steel,
iv
chemicals, construction, banking, and airlines. These “industry
champions” received government subsides and were favored in
the process of capital allocation, typically being allowed to
borrow at very low rates from state banks (usually at negative
real interest rates).
To
some
degree
these
policies
successfully
pushed
industrialization, but rarely of an efficient kind. Developing countries
are full of large manufacturing operations that operate at inefficiently
low scales because market sizes are small and product quality is not
good enough to penetrate export markets, which is a costly activity.
These operations are partly supported by government subsidies,
generating rested interests in keeping them going and opposing
liberalization. Relative prices of goods are heavily distorted by the
various subsidies, trade restrictions, and licenses. Other unintended
effects include massive shifts of workers into the cities and worsened
sanitation and health problems.
However, the question is whether such policies have limited
growth. Evidently many other factors are at work. What seems clear is
iv
that such countries have not performed well in terms of acquiring and
improving technologies, have lagged significantly behind in product
innovation and adaptation, have inefficient and distorted agricultural
and manufacturing sectors, and have not performed well in building
human capital, physical capital, and infrastructures. Some relevant
figures are given later. Thus, these sources of growth have likely been
limited in countries pursing ISI program.
ARGUMENT TWO: COUNTRIES WILL GROW FASTER IF
THEY ARE OPEN TO INTERNATIONAL COMPETITION
This is the basic hope underlying trade-reform programmes that
involve extensive liberalization of trade and investment barriers,
unification of tariff rates and domestic tax rate, removal of
consumption and production subsidies, and deregulation of industry
and privatization of state owned enterprises. It is the essential
philosophy behind World Bank loans to facilitate restructuring and
IMF lending packages that require microeconomic structural reforms.
It is also a very old idea (going back to Adam Smith and David
Ricardo at least) but its modern translation into trade liberalization
iv
largely began with the reforms in Chile in the 1970s advocated by the
“Chicago School” of economists (e.g. Milton Friedman, George
Stigler).
A somewhat different version of this approach is (to contrast it
with ISI) called export promotion, which is the policy followed
largely by East Asian and Western countries. These approaches are
not necessarily liberal in the sense of free competition. There are
many examples of sheltered and subsidized domestic firms or
industrial groupings; much of this protection was designed to
encourage infant industries to mature and export. However, the key
component of export promotion programs is not to discourage exports,
as is done under ISI programs. The basic policies under export
promotion include the following.
 Properly valued exchange rates, meaning exchange rates that
do not discriminate between imports and exports. This is
accomplished either through flexible rates or pegged exchange
rates that are allowed to move gradually to account for
inflation differences between the country in question and major
iv
export markets. In this sense the exchange rate did not impose
any tax on exports.
 Remove taxes on export production and, indeed make the tax
and tariff systems as neutral as possible across sectors of
production. Thus, while in most of these nations agricultural
production was protected from import competition, in
manufacturing there were relatively little discrimination across
types of goods. It is for this reason that export- promotion
policies are far closer to open trade policies than are ISI
policies. There were certainly major exceptions to this rule in
many export- promotion countries, however.
 Rather than rely largely on import protection to promote infant
industries, some active forms of export promotion in
manufacturing and high-tech sector were taken, including
favorable allocation of loans and subsides and rebates of
import tariff paid on imported industrial inputs.
 Recognizing that exporting is harder than cutting off import
because export require improving levels of quality and
iv
considerable foreign marketing cost, East Asia firms have
emphasized quality control and access to foreign technology
on favourable terms. Government have supported
this by
ensuring strong public educational effort, investments in
infrastructure for export, and technology transfer policies that
attempted to force inward technology flows at cheap price.
Recent problems in some countries (especially Asian countries)
indicate that while export promotion strategies may have contributed
to growth, they ultimately cause serious problems of over production
(excess capacity) relative to the economy’s ability to consume
commodities. (Maskus, 1998).
The World Bank favors lifting the protectionist measures that
have locked low income countries out of rich- country export market
infact most international bodies (WTO,IMF World Bank etc) strongly
support the case for trade openness and financial liberalization when
setting up programmes for developing countries or when multilateral
meetings occur. Some of the arguments put forward in favor of
increased openness to trade include the following:
iv
 Specialization: Gains from specialization in the good in which the
country has a comparative advantage such as productivity gains,
lower costs of production etc.
 Variety: Greater variety of goods available to consumers thus
increasing the consumer surplus and satisfying the consumers
“demand of difference”.
 Increasing Returns: Economies of scale justify any market
enlargement. However, conclusions are quite ambiguous. For
instance the gain is by large dependent of the process of firms’
issue. A fixed market structure inhibits such gains in the many
firms complete specialization scheme of monopolistic competition.
In the same way, imposing consumers to buy a greater quantity of
domestic products can be optimal. Domestic firms increase their
output and achieve economies of scale, while the variety is not
reduced. Notwithstanding such argument economies of scale are
generally referred to as a key objective of integration policies.
 Pro-competitive effect: When an economy is open, there will be
more intense competition which obliges local firms to operate
iv
more efficiently than under protection. There will also be drive for
innovation and efficiency in production in a smaller of goods. The
country Can thus compete internationally.
 Positive Externality: The technology is spread over the
boundaries through trade and open countries benefit a better access
to a world-wide basket of technology. Also, there will be Adoption
of sound policies to make sure the country is attractive to
investors: trade openness acts as a watch dog for politicians as bad
economic performances are blamed on them. Good governance
should thus be fostered.
On the other hand, some arguments were put forward by
protectionist against trade openness Apoteker and Crozet (2003) have
put forward five reasons that can at least under line the potential risks
in opened trade.
 Fluidity: All products do not have the same fluidity, meaning
that some may be easily relocated while some others are stickier
and cannot be as easily moved.
iv
 Multiple Comparative Advantages: As many countries with
similar resources are opening up to trade, they bring at the same
time their same comparative advantage on the market. This will
create an excess supply of that product and its world price will
decrease, thus harming all the providers.
 Instability as regards Financial Volatility: Implementing
financial liberalization implies allowing financial flows to
freely move in or out of a country. However, in a country which
lacks political credibility or monetary strength and power,
capital mobility and volatility can make economic policies
useless, thus preventing a country from using fiscal or monetary
tools to try to solve domestic economic problems. This means
greater dependence on the international environment.
 Investor Size versus Market Size: If concentration on a small
market is high, the issue of market efficiency becomes critical.
Indeed if one of the large and few investors on a small market
withdraw its funds, it can threaten the whole market
iv
equilibrium, and even create panic among other investors
without any fundamental” reasons behind it.
 Time Frame: A country’s development process is a long-term
one, while financial investors usually have a short-term
approach. Thus there are potential conflict of interest between
public authorities and private investors/companies, which can
be harmful for development goals.
The unananimous agreement on the beneficial effects on growth
and development of trade liberalization goes back to the emergence of
the Washington consensus in the early 1980s. The consensus emerged
in response to economic crisis affecting most developing countries at
the time, triggered by the debt crisis. Nonetheless long-term economic
growth is generally seen as being dependent on openness to trade.
But, literature on trade theory and policy has since the time of Adam
Smith debated whether openness and trade liberalization provide the
necessary ingredient for economic growth (miller and Upadhya,
2000). Thus, in order to effectively understand the relationship
between trade openness and output growth we need to review and
iv
understudy the trade theory, the theory of customs union and free
trade areas and models of exported growth.
THEORY OF TRADE
The doctrine that trade enhances welfare and growth has a long
and distinguished ancestry dating back to Adam Smith (1723-90). In
his famous book, and inquiry into nature and causes of the wealth of
nations (1776), Smith stressed the importance of trade as a vent for
surplus production and as a means of widening the market thereby
improving the division of labor and the level of productivity. He assert
that “between whatever places foreign trade is carried on, they all of
them derive two distinct benefits from it. It carries the surplus part of
the produce of their land and labour for which there is no demand
among them, and brings back in return something else for which there
is a demand. It gives value to their superfluities, by exchanging them
for something else, which may satisfy part of their wants and increase
their enjoyments.
iv
By means of it, the narrowness of the labour market does not
hinder the division of labour in any particular branch of art or
manufacture from being carried to the highest perfection. By opening
a more extensive market for whatever part of the produce of their
labour may exceed the home consumption, it encourages them to
improve its productive powers and to augment its annual produce to
the utmost, and thereby to increase the real revenue of wealth and
society”. (Thirl Wall, 2000). We may summarize the absolute
advantage trade theory of Adam Smith, thus, countries should
specialize in and export those commodities in which they had an
absolute advantage and should import those commodities in which the
trading partner had an absolute advantage. That is to say, each country
should export those commodities it produced more efficiently because
the absolute labour required per unit was less than that of the
prospective trading partners. (Appleyard and Field, 1998).
In the 19th century, the Smithian trade theory generated a lot of
arguments. This led to David Ricardo (1772-1823) to develop the
theory of comparative advantage and showed rigorously in his
iv
principles of political economy and taxation (1817) that on the
assumptions of perfect competition and the full employment of
resources, countries can reap welfare gains by specializing in the
production of those goods with the lowest opportunity over domestic
demand, provided that the international rate of exchange between
commodities lies between the domestic opportunity cost ratios. These
are essentially static gains that arise from the reallocation of resources
from one sector to another as increased specialization, based on
comparative advantage, takes place. These are the trade creation gains
that arise within customs to trade are removed between members, but
the gains are once-for-all. Once the tariff barriers have been removed,
and no further reallocation takes place, the static gains are exhausted.
The static gains from trade stem from the basic fact that countries are
differently endowed with resources and because of this the
opportunity cost of producing products varies from country to
country. Opportunity cost is measured by the marginal rate of
transformation between one good and another, as given by the slope
of the production possibility curve; that is, by how much one good has
iv
to be sacrificed in order to produce another. The law of comparative
advantage states that countries will benefit if they specialize in the
production of those goods for which the opportunity cost is low and
exchange those goods for other goods, the opportunity cost of which
is higher. That is to say, the static gains from trade are measured by
the resource gains to be obtained by exporting to obtain imports more
cheaply in terms of resources given up, compared to producing the
goods oneself.
In other words, the static gains from trade are measured by the
excess cost of import substitution, by what is saved by not producing
the imported good domestically. The resource gains can then be used
in a variety of ways including increased domestic consumption of
both goods (Thirl Wall, 2000).
On the other hand, the dynamic gains from trade continually
shift outwards the whole production possibility frontier of countries if
trade is associated with more investment and faster productivity
growth based on scale economies, learning by doing and the
acquisition of new knowledge from abroad, particular through foreign
iv
direct investment. The essence of dynamic gains is that the shift
outwards the whole production possibility frontier by augmenting the
availability of resources for production through increasing the
productivity of resources and increasing their quantity. One of the
major dynamic benefits of trade is that export markets widen the total
market for a country’s producers. If production is subject to increasing
returns, export growth becomes a continual source of productivity
growth. There is also a close connection between increasing returns
and the accumulation of capital. For a small country with no trade
there is very little scope for large scale investment in advanced capital
equipment; specialization is limited by the extent of the market. But if
a poor country can trade, there is some prospect of industrialization
and of dispensing with traditional methods of production. It is the
dynamic gains from trade that are focused on in modern trade theory
such as the Heckscher-Ohlin trade theory.
2.1.2
THEORY OF CUSTOMS UNIONS AND FREE
TRADE AREAS
iv
Since the end of the World War II, there had been several
attempts to promote trade through the creation of international and
regional trade agreements in the form of customs unions and free
trade areas. Free trade area is a form of economic union in which all
members of the group remove tariffs on each others products, while at
the same time each member retain its independence in establishing
trading policies with non-members.
In other words, the members of a free trade area can maintain
individual tariffs and other trade barriers on the outside world. That is
to say, in a free trade area, barriers to trade are brought down within
the area, but there is no common external tariff. Also, free trade areas
create trade, but the extent of trade diversion is likely to be much less,
with the presumption that on narrow economic grounds free trade
areas are superior.
On the other hand, a customs union is a form of economic
integration in which all tariffs are removed between members and the
group adopts a common external commercial policy toward nonmembers. Furthermore, the group acts as one body in the negotiation
iv
of all trade agreements with non-members. The existence of the
common external tariff takes away the possibility of transshipment by
non-members. Customs unions create trade, but also divert it from
lower cost suppliers to higher cost suppliers within the union. Thus,
the question is whether the benefits of trade creation exceed the costs
of trade diversion.
Apart from trade creation and trade diversion, customs unions
may also have other important effects associated with the enlargement
of the market which are neglected by the static analysis. Firstly, the
larger market may generate economies of scale. Secondly, integration
is likely to promote increased competition which is likely to affect
favorably prices and costs, and the growth of output. Thirdly, the
widening of markets within a customs union is likely to attract
international investment. Producers will prefer to produce within the
union rather than face a common external tariff from outside. Finally
if the world supply of output is not infinitely elastic, there are terms of
trade effects to consider. Specifically if there is trade diversion, the
world price of the good will fall, moving the terms of trade in favor of
iv
the customs union. This term of trade effect represents a welfare gain
which may partly off set the welfare loss of trade diversion.
The two forms of economic integration discussed above are
likely to be interior to a policy of unilateral tariff reductions, and
therefore need to be justified on other economic or non-economic
grounds. Thus, De Melo, Panagariya and Rodick (1993) suggest three
channels through which regional integration could alter economic
outcomes for the better.
Firstly, a regional trade agreement entails a larger political
community which might lessen the scope for adverse discretionary
actions by governments, and particular restrict the power of growthretarding political interest groups, unless politically powerful lobbies
can form alliances across countries.
Secondly, when a regional institution is set up ab nitio, better
choices may be made than at the nation-state level, where policymakers have to contend with existing institutions that accommodate
factional interests. Thirdly, when participating countries have
different economic institutions, policy-making at the regional levels
iv
will entail a compromise between those institutions and may lead to a
superior outcome for at least some member countries. For example, if
a customs union adopts as its common external tariff, the average
tariff of the union, at least some members must benefit. Nevertheless,
the World Bank is generally hostile to regional trading blocs, despite
the potential political –cum-economic benefits, because of their
relatively inward-looking nature. (Thirlwall, 2000).
2.1.3
MODELS OF EXPORT –LED GROWTH
The three main models of export-led growth that will be
discussed are the neo classical supply –side model, the balance of
payments constrained model which is also known as the Hicks supermultiplier model, and the virtuous circle model.
The Neoclassical Supply-Side Model: This model shows the
relationship between exports and growth, and assumes that the export
sector confers externalities on the non export sector, because of its
exposure to foreign competition; and secondly that the export sector
has a higher level of productivity than the non export sector. Thus, the
share of exports in GDP, and the growth of exports, matter for overall
iv
growth performance. Feder (1983) was the first to prove a formal
model of this type to explain the relation between export growth and
output growth. The output of the export growth sector is assumed to
be a function of labour and capital in the sector, the output of the nonexport sector is assumed to be a function of labour, capital and the
output of the export sector (so as to capture externalities), and the
ratio of respective marginal factor productivities in the two sector is
assumed to deviate from unity by a factor d. Feder tests the model
taking a cross section of 19 semi industrialized countries and a larger
sample of 31 countries over the period1964-73. He finds that there are
substantial differences in productivity between the export and nonexport sector are also evidence of externalities. The externalities
conferred are part of the dynamic gains from trade which are
associated with the transmission and diffusion of new ideas from
abroad relating to both production techniques and efficient
management practices. The cross-section work on exports and growth
assumes, however that all countries in a sample conform to the same
model, with the same intercept and coefficient parameters linking
iv
exports and growth. In practice, this is highly unlikely to be the case;
and it transpires, in fact, that when time series studies are conducted
for individual countries, the relation between exports and growth is
much weaker.
BALANCE OF PAYMENTS CONSTRAINED GROWTH MODEL:
No country can grow faster than rate consistent with balance of
payments equilibrium on current account in the long run, unless it can
finance ever-growing deficits which, in general, it cannot. Ratios of
deficit to GDP of more than 2%-3% to make the international
financial markets nervous and all borrowing eventually have to be
repaid. A country’s balance of payments equilibrium growth rate can
be modeled by stating the balance of payments equilibrium condition
specifying multiplicative (constant elasticity) import and export
demand functions in which imports and exports are a function of
domestic and foreign income, respectively, and of relative prices, and
substituting these functions in the equilibrium conditions. Since
imports are a function of domestic income, the model can be easily
solved for the growth of income consistent with balance of payments
iv
equilibrium. Nureldin-Hussain (1995) applied this model to Africa to
contrast the experience of slow growing African countries with the
faster growing countries of Asia over the period 1970-90. He uses an
extended model which also includes terms of trade effects and the
effects of capital flows. The major explanation of the difference in
growth rates between Africa and Asia turns out to be the difference in
the growth of exports. He finds that the average growth of the African
countries, excluding oil exporters, was 3.4 percent per annum, and of
the Asian countries 6.6 percent. The contribution of export growth in
Africa was 1.99 percentage points and in Asia 5.91 percentage points.
Differences in capital flows and terms of trade movements
made only a minor contribution to growth rate differences. Thus, he
concluded that exports are unique as a growth inducing force from the
demand side because it is the only component of demand that
provides foreign exchange to pay for the import requirements for
growth. In this sense, it allows all other components of demand to
grow faster in a way that consumption-led growth or investment-led
growth does not.
iv
Virtuous Circle Models of Export-Led Growth
There is need to recognize the fact that export and growth may
be interrelated in a cumulative process. This raises the questions of
casualty; but more importantly, such model provide and explanation
of why growth and development through trade tends to be
concentrated in particular areas of the world, while other regions and
countries have been left behind. These models provide a challenge to
both orthodox growth theory and trade theory which predict the long
run convergence of living standards across the world. A simple
cumulative model, driven by exports as the major component of
autonomous demand, is to assume that (i) output growth is a function
of export growth, (ii)export growth is a function of price
competitiveness
and
foreign
income
growth,
(iii)
price
competitiveness is a function of wage growth and productivity
growth, and (iv) productivity growth is a function of output growth
(this is referred to as verdoorn law which works through static and
dynamic returns to scale, including learning by doing). It is this
induced productivity growth that makes the model circular and
iv
cumulative’ since if fast output growth (caused by export growth)
induces faster productivity
growth this makes goods more
competitive and therefore induces faster export growth. The verdoorn
relation not only makes the model ‘circular and cumulative’; but also
gives rise to the possibility that once an economy obtains a growth
advantage it will tend to keep it. Suppose, for example, that an
economy obtains an advantage in the production of goods with a high
income elasticity of demand in world markets, such as high
technology goods, which raises its growth rate above other countries.
Through the verdoorn effect, productivity growth will be higher and
the economy will retain its competitive advantage in these goods,
making it difficult, without protection or exceptional industrial
enterprise, to establish the same commodities.
In such a cumulative model, it is the difference between the
income elasticity characteristics of exports (and imports, if balance of
payments equilibrium is a requirement as argued earlier) that is the
essence of divergence between industrial and agricultural economies,
or between centre and periphery. (Thirl Wall, 2000).
iv
From the ongoing, we can conclude that trade liberalization
does not necessarily imply faster export growth, but impractical the
two appear to be highly correlated. Impact of the liberalization on
economic growth probably works mainly through improving
efficiency and stimulating exports which have powerful effects on
both supply and demand within an economy. There are several
different measure of trade liberalization or trade orientation, and all
studies seem to show a positive effect of liberalization on economic
performance.
Likewise there are several different studies of the
relation between exports and growth and the evidence seem over
whelming that the two are highly correlated in a causal sense, but the
relative importance of the precise mechanisms by which export
growth impacts on economic growth are not always easy to discern or
qualify.
2.2
EMPIRICAL LITERATURE
The relationship between trade openness and growth is a highly
debated topic in the growth and development literature, yet this issue
is far from being resolved. There is a long history of research, both
iv
theoretical and empirical, that provides at least an answer to the
question: does openness to trade result in the growth of output (say,
GDP)? But currently there is no consensus, either empirically to
theoretically, on the nature of the relationship between trade openness
and output growth. In fact, this is because the mechanisms behind it
are not well understood. The existing empirical literature however
does not provide clear evidence on relationship between trade
openness and growth. Many studies provide evidence that increasing
openness has a positive effect on GDP growth. On the other hand
some studies report that it is difficult to find robust positive
relationships or even that there is negative relationship between
openness and growth. Some studies, among other Rodriguez and
Rodrik (1999) and Rodriguez (2006), critically argue that trade policy
variables are mostly uncorrelated with growth, while the trade shares
can correlate with income levels and growth rates. But the complexity
of links of causality and endogeneity among trade shares, growth and
other sources of growth make a difficulty to define a strong effect of
openness on economic growth. Theoretical growth studies suggest
iv
very complex and different relationships between openness and
growth and the empirical evidence is not unambiguous. The growth
theory supposes that “a country’s openness to world trade improves
domestic technology, and hence an open economy grows faster than a
closed economy through its impact on technological enhancement”
(Jin, 2006). Harrison (1996) asserted that openness to trade provides
access to imported inputs, which embody new technology, increases
the size of the market faced by the domestic producers, which raises
the return to innovation, and facilitates a country’s specialization in
research intensive production.
In line with potential dynamic gains of trade openness, most
early empirical studies have examined a set of trade openness
measures and
with their correlation with each other and with
economic growth and found a clear positive link. For example,
Harrison (1996) looked at a number of openness indicators that turned
out to have a positive ‘association’ with economic growth and
produced evidence in support of bi-directional casualty between
openness (trade share) and economic growth. Recent research,
iv
however, has questioned the robustness of the relationship. For
instance, Harrison and Hanson (1999) show that the often quoted
Sachs and Warner (1995) openness and growth link as claimed.
Rodriguez and Rodrik (1999) confirm the Harrison –Hanson
critique and argued that much of the work to correlate trade openness
and economic growth has been plagued with subjective and collinear
measures of openness that, though positively related with economic
growth, arrive at their conclusion through problematic econometric
methodologies. Harrison (1996) and Pritchett (1996) show that the
various measure of trade openness tend to be only weakly correlated
and are often of the wrong sign.
In general, empirical studies suffer from a number of short
comings, and as a result they have not resolved the questions
surrounding the correlation between openness and growth. Baldwin
(2000) offers explanation for the differences among researchers of the
openness growth nexus. According to him, while econometric
analyses based on quantitative data are limited by the scope and
comparability of available quantitative data, differences in what
iv
investigators regard as appropriate econometric models and tests for
sensitivity of the results to alternative specifications that may be based
in part on the personal policy predilections of authors and can also
result in significant differences in the conclusions reached under such
quantitative approaches. If these studies used measures that were even
slightly correlated, then empirical literature together could be taken as
proof of a positive relation between openness and growth.
Baliamoune-lutz and Ndikumana (2007) observed that, from a
methodological stand point, the weak link between trade liberalization
and growth may be attributed to measurement imperfections: the
indicators used in empirical analysis may not capture the true essence
of openness. Indeed, due to lack of data on indicators of trade
openness as a policy empirical studies (as this one does) resort to
measures of trade outcomes i.e. trade volume, as proxies for trade
openness it is assumed that positive trade outcomes are an indication
of a policy environment that is at least not anti-trade. Moreover, a
high trade volume indicates exposure to international markets with the
associated benefits (e.g. technological transfer) which openness
iv
policies seek to achieve. Thus, to some extent trade outcomes do carry
some indication of the effects of trade liberalization. Nonetheless,
results from analyses using trade volume as a measure of trade
openness have to be interpreted consciously. Indeed, variations in the
volume of trade do not always reflect actual government policies that
promote or hinder trade. For instance, fluctuations in commodity
prices result in changes in trade flows even in the absence of shifts in
trade policy.
The weak empirical evidence on the link-between trade
liberalization and growth can also be due to problems of
misspecification. In particular, the effects of trade liberalization may
materialize only with a lag. In the short run, liberalization may have
negative effects, especially by undermining domestic production
because of competitive import, retarding growth (Mukhopadhyay
1999). Hence, to the extent that these negative short-run effects and
the expected delayed positive effects occur consecutively, growth
would exhibit a J-curve of response to trade openness (Greenaway etal
2002). Therefore, empirical studies may yield inconclusive and even
iv
misreading results if these dynamic and counter balancing effects are
not fully taken into account.
Another explanation relates to the structure of trade. Whether a
country benefits from trade liberalization or not in terms of growth
depends on the composition of trade. Mazumdar (1996) hypothesized
that the composition of trade determines the strength of the engine of
growth.” Indeed lower and Van Den Berg (2003) final evidence
supporting the view that countries that import capital goods and
export consumer goods growth faster than those that export capital
goods. The evidence suggests that African countries and developing
countries in general would benefit from trade most by promoting
exports of labour-intensive goods and services while encouraging
imports of capital goods. (Lopez 1991). This implies that the current
export boom which is driven by capital-intensive growth that is
sustainable, especially because of the low gains in employment
creation and limited spill over effects on non-oil sectors.
iv
Dollar (1992) brought an important contribution to the trade
and growth debate. The author defines openness as the combination of
two diversions:
i.
A low level of protection, hence of trade distortions and
ii.
A stable real exchange rate so that incentives remain constant
over time.
From that very definition, follow two measures openness: a
trade distortion index, and a real exchange rate variability index. The
distortion index measures the deviation from the law of one price after
controlling for the impact of non-tradable. The variability index
captures the variance of the real exchange rate. The author considers a
sample of 95 countries over the period 1976 -1985 and regresses
average per capital growth upon his openness indexes and the average
investment rate. Both the distortion index and the variability index are
significantly negatively correlated with growth and the investment
rate comes out with a significantly positive coefficient.
Dow Rick (1994) tests whether trade openness affects output
growth and /or investment. He considers a sample of 74 countries over
iv
the period 1960-1990. As openness indicator, the author considers the
residuals of an OLS cross-country regression of the average trade
intensity upon a constant and average population. In a second stage,
the author runs cross-country OLS regressions of average per capita
GDP growth upon the average investment rate, the initial GDP level
and his openness indicator. The coefficient on openness is significant
and positive. More over, dropping the investment rate considerably
lowers the overall fit of the model but enhance the coefficient on
openness, which according to the author “suggests that openness
works partly through increased investment rates”.
In a third stage, the author computes decade averages for his
variables and turns to panel data techniques, gauging that such
techniques “enable some control for time invariant country-specific
factors such as institutional arrangements that might be correlated
with the explanatory variables”. The author uses labour productivity
growth as dependent variable and estimates both fixed-effects and
random-effects models. He reports that the coefficient on openness is
still significant and positive, but its point estimate is much lower than
iv
in the OLS specification. In a fourth set of regressions, the author also
considers growth in openness instead of openness itself.
The author interprets this as reflecting the fact that “static
efficiency effects of trade liberalization are negligible for countries
with well-developed markets”. Finally, in its conclusions, the author
cautions that his results, showing the beneficial effects of increased
openness, hold on average, but are not a universal truth, valid always
and every where.
In particular, he stresses that “trade liberalization can indeed
stimulate growth in the aggregate world economy. Whilst trade may
have such positive effects for some countries, it may conversely lock
in other countries into a pattern of specialization in low-skill, lowgrowth activities.”
Sachs and Warner (1995) brought a seminal contribution to that
literature. Their central hypothesis is that some developing countries
fail to grow rapidly enough as to converge because they are simply
not open to trade. In their own wards: “convergence can be achieved
by all countries, even those with low initial level of skill, as long as
iv
they are open and integrated in the world economy”. To check their
hypothesis, the author first carefully, build and discuss an openness
measure. Building upon a sample of 135 countries over the period
1970-1990, they construct and openness dummy variable that is zero
if any of the 5 following conditions is true:
 Non-tariff barriers covering 40% or more of trade
 Average tariff rate above 40%
 Black market premium above 20%
 The economy is ruled by a socialist system, or
 There is a state monopoly on exports.
Otherwise, if none of these 5 conditions is fulfilled, the
openness dummy is one. The authors first divide their countries
sample into open ones and closed ones, and show that closed countries
have grown at about the same rate (essentially about 0.7% a year), no
matter whether they are developed or not. By contrast, open
developing countries have grown much faster than their developed
counter parts (4.49% versus 2.29%). Going beyond these stylized
facts the authors re-do the same regressions as in Barro (1991) and
iv
add their openness dummy to them without the dummy, the results are
sensibly the same as in Barro (1991). After adding the openness
dummy in the regresses list, it appears its coefficient is highly
significant. The points estimates suggest that open economies grow on
average 2.45% faster than closed ones.
Moreover, educational attainment variables become even less
significant than in Barro (1991), which leads the authors to think that
“….growth rate over this period was determined less by initial human
capital levels than by policy choices”. They also address a
specialization-related issue. Specifically, they test whether trade
openness condemns raw materials exporters to non-industrialization
and whether closed trade promotes industrial exports in the long run.
To do this, they regress the change in the share of primary exports
more rapidly from being primary-intensive to manufactures-intensive
exporters. The difference in speed of adjustment is statistically
significant”.
Harrison (1996) starts from the judgment that “it should be
evident that no independent measures of so-called ‘openness’ is free
iv
from methodological problem”. Therefore, to make her point, she
collects as many different openness indicators as she can, about 7 of
them, and she checks the consistency of the results across all these
indicators. She uses various samples, whose time spans range from
1960-1998 to 1978-1987,and the country coverage varies from 51 to
17.she first runs typical cross-country growth regressions. It appears
that only one measure of openness out of 7, namely the black market
premium, has a significant impact on growth. To explain this weak
result the author argues that a pure cross-section specification, based
upon long-run averages, is not an adequate one. Indeed, though the
use of long run averages appears as the most natural way to capture
the determinants of long-run growth, they may also hide significant
variations in individual countries performances and policies over time.
To test this idea, the author re-does her regressions using annual data
for the same variables. She uses a panel fixed-effects specification to
take into account unobserved country specific differences in growth
rates. Results show a stronger link between openness and growth
since 3 indicators become significant at the conventional 5% level.
iv
The author next argues that such a yearly frequency is too high if one
is interested in long-run growth, since results may be affected by
short-term conjectural, variations. She therefore considers a third“intermediate”- specification, based on five-year averages and reports
that, again 3 indicators come out with a significant coefficient. The
message from these results, as the author states, is that “the choice of
the time period for analysis is critical”. However, an interesting
regularity appears across all specifications: When openness is
significant; it is always in the sense that greater openness is associated
with higher growth.
Edwards (1998) also uses an important number of openness
indexes to investigate the trade and growth relationship. He considers
a sample of 93 advanced and developing countries, and estimates a
growth equation with a panel data random effects model. From that
model, he computes factor shaves, which are then used to get TFP
estimates. Concentrating on a cross-section of 1980s averages, TFP
growth is finally regressed upon initial income level, initial human
capital level, and no less than 9 openness indicators, each one of them
iv
in turn. The author reports that “in all but one of the 18 equations the
estimated coefficient on the openness indicator has the expected sign
and in the vast majority of cases it is significant”. Moreover, the
coefficient on initial human capital is always significant and positive.
Regarding the initial income level, the coefficient is always negative
and in 16 cases out of 18, it is significant though very low, which can
be interpreted as evidence in favor of conditional convergence. To
summarize, the authors concludes that his results “are quite
remarkable, suggesting with tremendous consistency that there is a
significantly positive relationship between trade openness and
growth”.
An important paper that is able to cast serious doubts about the
consistency of the trade-growth relationship is the one by Rodriguez
and Rodrik (1999). These authors consider a series of previous
research results, among which Dollar (1998). Sachs and Warner
(1995), and Edwards (1998). The re-do the computations in these
papers, but slightly change the specifications (through the addition of
some dummies, e.g.), add newly available data to the sample, or
iv
slightly change the estimation methods. They are able to demonstrate
a fundamental lack of robustness of the results in the paper they
reviewed.
Frankel and Romer (1999) claim that openness, as measured by
the ratio of total trade to GDP, should not be used as explanatory
variable in the growth regressions. The trade ratio, the authors argue,
is endogenous, and needs to be instrumented. To construct their
instrument, the authors first argue that “as the literature on the gravity
model of trade demonstrates, geography is a powerful determinant of
bilateral trade. And they claim this is also true for total trade.
Moreover, geography is completely exogenous. Therefore, the authors
consider a database of bilateral trade between 63 countries for 1985
and they regress bilateral trade upon purely geographical indicators.
For each country, the fitted values of trade are aggregate over all
partners, and this aggregate is finally turned into an “ideal” trade share
that can be used as an instrument for the observed one. The authors
then estimate growth equations for a cross-section of 150 countries in
1985. They report a substantial impact of trade openness on income
iv
growth: increasing the trade share by 1% should raise income by
between 0.5% and 2%. These findings are robust to various changes
in specifications. The results also suggest that, controlling for
openness; larger countries tend to experience higher growth rates,
which could simply reflect that citizens living in larger countries
engage more in within country trade.
Baldwin and Sbergani (2000) argue that the reason why
researchers failed to find a robust relationship between trade and
openness is because that relationship is fundamentally non linear and
non-monotonic. They raise the point that the fundamental engine of
growth is human and physical accumulation, and that the link between
capital accumulation and trade barriers is, in nearly all models, non
linear and often even non-monotonic. They provide a formal 2x2x2
dynamic model with imperfect competition that gives rise to (i) allshaped relationship between ad-valorem tariffs and growth and (ii) a
bell-shaped relationship between specific tariffs and growth. This
model is then confronted to the data, i.e. for a variety of openness
indicators (actually, 10 of them are considered), a quadratic model is
iv
estimated. It turns out that, in this new specification, for 6 of the 10
proxies both the linear and the quadratic terms are significant
individually. The authors conclude that: “allowing for non-linearity
does have a big empirical impact”.
A number of other studies have looked at the relationship
between average tariff rates and growth. Lee (1993), Harrison (1996)
and Edwards (1998) found negative relationship between the tariff
rates and growth. The studies of Edwards (1992), Sala-i- Martin
(1997) and Clemens and Williamson (2001) conclude that the
relationship is weak. Rodriguez and Rodrick (1999) tried to replicate
the result of Edwards (1998) and found that average tariff rates had a
positive and significant relationship with total factor productivity
(TFP) growth for a sample of 43 countries over the period 1980-1990.
In a recent study Vanikkaya (2003) used a large number of
openness measure for a cross-section of countries over the last three
decades. His analysis found a significant positive correlation between
trade shares and growth. However, this study observed that different
measures of trade barriers are positively associated with growth in the
iv
less developed countries. In recent empirical studies, one or more of
the following indicators of openness in the table below are used:
Measure
Definition
Trade
dependency The ratio of exports and import to GDP
ratio
Growth rate of exports The growth rate of exports over the specified
period
Tariff Averages
A simple or trade-weighted average of tariff
levels.
Collected Tariff Ratios The ratio of tariff revenues to imports.
Coverage
of The percentage of goods covered by quantitative
Quantitative
restrictions.
Restrictions
Black market premium The black market premium for Foreign
exchange, a proxy for the overall degree of
external sector distortions.
Trade Bias Index
The extent to which policy increases the ratio of
importable goods’ prices relative to exportable
goods prices compared to the same ratio in world
markets.
Sachs And Warner A composite index that uses several trade-related
Index
indicators tariffs, quota coverage, black market
premiums, social organization and the existence
of export marketing boards.
Learner’s
Openness An index that estimates the difference between
Index
the actual trade flows and those that was
expected from a theoretical trade model.
Table1: openness indicators.
iv
(Rodriguez and Rodrik, 2000; Ogujiuba, Oji and Adenuga,
2004).
Gross man and Helpman (991) and Matsuyama (1992) provide
theoretical models where a technological backward country
specializes in a non-dynamic sector as result of openness, thus losing
out from the benefits of increasing returns. Underlying this result,
there is an imperfection in contracts or in financial markets that makes
people obey a myopic notion of comparative advantage.
Dollar and Kraay (2004) and Loayza, Fajnzylber, and Calderon
(2005) run growth regressions on panel data of large samples of
countries. Both papers use openness indicators based on trade on trade
volumes and control for their joint endogeneity and correlation with
country-specific factors through GMM methods that involve taking
differences of data and instruments. This implies that, although they
continue to use cross –country data, these papers favors withincountry changes as the main sources of relevant variation. Both papers
conclude that opening the economy to international trade brings about
significant growth improvements. Wacziarg and Welch (2003) arrive
iv
to a similar, though more nuanced, conclusion from a methodological
different stand point. Using an event-study methodology –where the
event is defined as the year of substantial trade policy liberalization--,
they find that liberalizing countries tend to experience significantly
higher volume of trade, investment rates, and most importantly,
growth rates. However, in an examination of 13 country-case studies
Wacziarg and Welch find noticeable heterogeneity in the growth
response to trade liberalization. Although their small sample does not
allow for definite conclusions, it appears that the growth response
after liberalization is positively related to conditions of political
stability.
Also, various empirical literatures offer some examples of nonlinear specifications considering interaction effects. On the related
topic of foreign direct investment, Borensztein, De Gregorio and Lee
(1998) find that the growth effect of FDI is significantly positive only
when the host country has, respectively, sufficiently high human
capital and financial depth. Specifically in the analysis of grow effects
of trade openness, an important antecedent of our work is the
iv
empirical study by Bolaky and Freund (2004). Using cross-country
regressions in levels and changes of per capita GDP and controlling
for simultaneity via external instruments, they find that trade opening
promotes economic growth only in country’s that are not excessively
regulated. They argue that in highly regulated countries, growth does
not accompany trade openness because resources are prevented from
flowing to the most productive sectors and firms, and trade is likely to
occur in goods where comparative advantage is actually missing.
Calderon, Loayza, and Schmidt –Hebbel (2004) interact in their
panel growth regressions a measure of openness (volume of trade
/GDP) with linear and quadratic terms of GDP per capita, which they
regard as proxy for overall development. They find that the growth
effect of trade opening is nearly zero for low levels of per capita GDP,
increases at a decreasing rate as income rises, and reaches a maximum
at high levels of income.
Chang, Kaltani and Loayza (2005) study how the effect of trade
openness on economic growth depends on complementary reforms
that help a country take advantage of international competition. They
iv
presented some panel evidence on how the growth effect of openness
depends on a variety of structural characteristics. They use non-linear
growth regression specification that interacts a proxy of trade
openness with proxies of educational investment, financial depth,
inflation, stabilization, public infrastructure, governance, labourmarket flexibility, ease of firm entry, and ease of firm exit. They find
that the growth effects of openness are positive and economically
significant if certain complementary reforms are undertaken.
Giles and Stroomer (2005) develop flexible techniques for
measuring the speed of output convergence between countries when
such convergence may be of an unknown non-linear form. They then
calculate these convergence speeds for various countries, in terms of
half lives, using a time-series data-set for 88 countries. These
calculations are based on both non parametric kernel regression and
‘fuzzy’ regression and the results are compared with more restrictive
estimates based on the assumption of linear convergence. The
calculated half-lives are regressed, again in various flexible ways, on
cross-section data for the degree of openness to trade. They find
iv
evidence that favors the hypothesis that increased trade openness is
associated with a faster rate of convergence in output between
countries.
Joffrey (2003) in his work, tries to clarify a number of issues
related to the “trade openness and growth debate”. He considers a
number of sector specialization indicators and examine whether they
indeed affect the link between openness and growth. Using both
cross-section and panel data techniques, he finds that both its pattern
are likely to affect significantly the link between openness and
growth.
On research studies that relate to Africa and Nigeria in specific,
Sarkar (2007) examines the relationship between openness (tradeGDP ratio) and growth. The cross-country panel data analysis of a
sample 51 countries of the South during 1981-2002 shows that for
only 11 rich and highly trade-dependent countries a higher real growth
is associated with a higher trade share. Time series study of individual
country experiences shows that the majority of the countries covered
in the sample including the East Asian countries experienced no
iv
positive long-term relationship between openness and growth during
1961-2002. He finds that the experience of various regions and groups
shows that only the middle income group exhibited a positive longterm relationship.
Also, Baliamoune-Lutz and Ndikumana (2007) explore the
argument that one of the causes of the limited growth effects of trade
openness in Africa maybe the weakness of institutions. They also
control for several major factors and, in particular, for export
diversification, using a newly developed data set on Africa. Results
from Arellano-Bond GMM estimations on panel data from African
countries show that institutions play an important role in enhancing
the growth effects of trade. They find that the joint effect of
institutions and trade has U-shape, suggesting that as openness to
trade reaches high levels, institution play a critical role in harnessing
the trade-led engine of growth. The results from this paper are
informative about the missing link between trade liberalization and
growth in the case of African countries. Likewise, Ogujiuba, Oji and
Adenuga (2004) test the validity of trade openness for Nigeria’s long-
iv
run growth using a co-integration approach. They preferred the VAR
approach for some reasons and their econometric results show that
there is no significant relationship between openness and economic
growth, and that unbridled openness could have deleterious
implications for growth of local industries, the real sector and
government revenue.
Moreover,
Addison
and
Wodon
(2007)
study
the
macroeconomic volatility, private investment growth, and poverty in
Nigeria. Using cross-sectional data for 87 countries, they show that
real per-capita growth over the period 1980 -1994 was a function of
productivity growth and investment rates, both of which were
negatively affected by volatility (in terms of trade, real exchange rate,
and public investments). When comparing Nigeria to high growth
nations, they find that most of the growth differential can be attributed
to Nigeria’s higher macroeconomic volatility. Simulations suggest
that if Nigeria had lower levels of volatility and better macroeconomic policies, poverty would have been much lower than
observed.
iv
Nwafor (unpublished) examines the effects reduction of import
tariffs will have on poverty in Nigeria, using information on Nigeria’s
past experience with trade liberalization he examined the possible
impacts on the economy with a view to making the reductions propoor.
Kandiero and Chitiga (2003) investigate the impact of openness
to trade on the FDI inflow to Africa. Specifically, in addition to
economy wide trade openness, they analyze the impact on FDI of
openness and manufactured goods, primary commodities and services.
The empirical work is conducted using cross-country data comprising
of African countries observed over four periods: 1980-1985, 19851990, 1990-1995, and 1995-2001, they find that FDI to GDP ratio
responds well to increased openness in the whole economy and in the
services sector in particular.
Finally, Njikam, Binam and Tachi (2006) assess the factors
behind differences, in total factor productivity (TFP) across subSahara Africa (SSA) countries over the period 1965-2000. The crosssection, fixed effects using annual data, fixed-effects using data in 3year averages as well as the seemingly unrelated regression (SUR)
iv
results show that (i) openness to world trade is conducive to TFP in
SSA region only if issues related to supply conditions such as poor
transport and communication infrastructure, erratic supply of electric
energy. Corruption and bad governance, insufficient education of the
labour force etc are adequately addressed, (ii) physical capital
accumulation is important for TFP, (iii) the size of the financial sector
mattes for TFP, in some SSA countries and negative for TFP in other
SSA countries.
2.3
LIMITATION OF PREVIOUS STUDIES
The literatures of previous studies are plagued with a lot of
problems. First of all, it is worthwhile to note that the theoretical
growth literature has given more attention to the relationship between
trade policies and growth rather than the relationship between trade
volumes and growth. Therefore the conclusion about the relationship
between trade barriers and growth cannot be directly applied to the
effects of changes in trade volumes on growth. There was also no
consensus on the nature of the relationship and nature of linear
association (correlation) between openness and growth. Likewise,
there is no generally accepted measure of openness indicators as it suit
and please the researcher(s). Moreover, many of the existing empirical
iv
literature are not country-specific, that is they deal with crosssectional analysis, thus they did not provide for differential in nature
and structure of various economies. Hence, developing countries like
Nigeria are recommended policies which are based on research
conducted for industrially advanced countries or even mixture of both.
CHAPTER THREE
METHODOLOGY
3.1
ANALYTICAL FRAMEWORK
The primary aim of every economic research is to arrive at a
conjunction of economic theory, actual measurement using the theory
and techniques of statistical inferences as the matching bridge
(Haavelmo, 1994). The economic theory makes statement or
postulates hypothesis that are mostly quantitative (and some cases
qualitative) in nature and as such, it is the choice of the modeler or the
researcher to validate these hypothesis using appropriate models in
line with current development and betting method of estimation and
inference.
iv
Economic theory and some empirical research argue that
openness (trade or financial) will definitely increase output growth
while others opened that the relationship between the two is
ambiguous. In order to contribute empirically to this argument, this
study will employ econometric method as the research technique. The
choice of method is necessitated by the nature of the study which in
this case is an analysis of relationship among variables.
3.2
MODEL SPECIFICATION
An economic model is a representation of the basic features of
an economic phenomenon; it is an abstraction of the real world
(Fonta, Ichoku and Anumudu, 2003). The specification of a model is
based on the available information relevant to the study in question.
This is to say, the formulation of an economic model is dependent on
available information on the study as embedded in standard economic
theory and other major empirical works, or else, the model would be
theoretical. Two models are postulated in this research work; the first
is a non-monotonic model to capture the first and second objective of
iv
the study, while the second is an analysis of covariance (ANCOVA)
model. The functional form of these models can be specified as
follows:
Model I:
RGDPt = (TPNt,TPNt2, RERt, RIRt, UNEMPt, TREND)…..(i)
Mode II:
RGPt = f (DUMt, TREND, (DUMt*, TREND))…….(ii)
The mathematical form of the model can be expressed as:
Model I:
RGDPt: o + 1TPNt + 2TPNt2 + 3RERt + 4RIRt +5UNEMPt +
6TREND
Model II:
RGDPt = o + iDUMt + 2TREND + 3(DUM*t TREND) ------------------------------------------------------------------------(iv)
But equations (iii) and (iv) above are exact or deterministic in nature.
In order to allow for the inexact relationship among the variables as in
the case of most economic variables stochastic error term “μ t” is
iv
added to both equations. Thus, we can express the econometric form
of the models as:
Model I:
RGDPt = o + 1TPNt + 2TPn2t + 3RERt + 4RIRt +
5UNEMPt + 6TREND + μit -------------------------------------(v)
Model II:
RGDPt = β0 + β1DUMt + β2TREND + β3(DUM*t TREND) +µ2t
------------------------------------------------------------------(vi)
Where RGDP =
Real Gross Domestic Product which is a proxy for
the real output of the economy.
TPN =
The Degree of openness measured as trade – GDP
ratio i.e. (import + Export)/GDP
TPN2 =
Real exchange rate
RIR =
Real Interest Rate
UNEMP = Unemployment Rate
DUM =
O for pre-SAP period observations
I for post –SAP period observations
TREND = The chronological arrangement of time
iv
µ
=
The stochastic error term
In order to properly estimate the parameters of the postulated
models, we rescale the dependent variable by logging it, thus,
transforming them into a log-line models as follow:
Model I:
LOG (RGDPt) = o+ 1TPNt + 2TPN2t +3RERt + 4RIRt +
5UNEMPt +6TREND + µit -------------------- --------------(viii)
Model II:
LOG (RGDPt) = β0+β1DUMt+β2TREND +β3 (DUM*tTREND)
+µ2t
-------------------------------------------------(viii)
Also, in order to avoid a spurious regression, we subject each of
the variables used to unit root (or stationary) test so as to determine
their orders of integration, since unit root problem is a common
feature of most time-series data.
3.2.1
TEST OF STATIONARY
A stochastic process is said to stationary if its mean and
variance are constant overtime and the value are auto-covariance
between the two time period depends only on the distance or lay
iv
between the two time periods and not the actual time at which the
covariance is computed (Gujarati, 2003). In other word, a stationary
stochastic process is one with constant mean, variance and covariance.
Hence, stationarity
test is carried out to verify whether a time series
is stationary or time-invariant so as to avoid a spurious regression.
The Phillips-perron (pp) unit roof test will be employed. The
choice of this test is to correct for some anomalies associated with the
conventional Augmented Dickey-Fuller (ADF) test. The Phillipsperron test use non-parametric statistical methods to take care of the
serial correlation in the error terms without adding lagged difference
terms. This test is specified thus:
∆Yt = +∆Yt-1+ μt
Where ∆ = difference operator
Yt = Time series
μt =Pure white noise.
Under the null hypothesis that  = 1 for stationarity, we use the PP
test statistics to verify the presence of unit root in the series.
3.2.2
TEST OF COINTEGRATION
iv
Economically, two (or more) variables will be co integrated if
they have a long term, or equilibrium, relationship between (or
among) them (Gujarati, 2003).
Individual time – series in a model may be spurious but their
linear combination may not. This is the purpose of co-integration test.
The augmented Engle-Granger (AEG) test will be employed to
validate this hypothesis. This hypothesis is of two stages:
 We will run the regression of equation (vii) and generate the
residual.
 The residual generated to unit root test.
If the generated residual is stationary at level form or integrated
of order zero i.e. 1(0), then the variables of the model are cointegrated. The AEG test is specified as:
∆t = t -1-+i∑ ∆t-1 +ℓt
Where t=errors generated from congregating regression
t-1= one period lag of the co-integrating-digression error.
∑ = summation sign
P = amount of lag used
iv
ℓt = white noise error.
If
is statistically significant at the chosen level, then the
variables of model 11 in equation (vii) are co integrated.
3.2.3 ERROR CORRECTION MODEL
An important issue in econometric is the need to integrate short
run dynamics with long run equilibrium. The analysis of short run
dynamics is often done by first eliminating trends in variables, usually
differencing. But this differencing procedure, however, throws away
potentials valuable information about long run relationship which
economic theories have a lot to say about. The error correction model
(ECM) is an extension of short run disequilibrium models, which also
incorporates past period’s disequilibrium.
The Granger representation theorem states that if two (or more)
variables, Y and X (s), are co-integrated, the relationship between (or
among) then can be expressed as error correction mechanism. The
ECM requires that each time-series is included into the model to the
model at its order of integration. Also added to the ECM is the one
period lay of the error term generated from the co-integrating
iv
regression whose variables are integrated of the same order. The
generated error term is treated as the equilibrium error” and can be
used to link the short run dynamics with the long run equilibrium. The
ECM for model I of equation (vii) is specified as:
∆ko LOG (RGDPt) =Ø0+Ø1∆k1TPNt+Ø2∆k2TPN2t+ Ø3∆k3RER+
Ø4∆k4RIRt+ Ø5∆k5UNEMPt+ECMt-1+∑t ---(ix)
The variables are co-integrated if and only if
K0 = k1, k2, k3, k4, k5
Where ∆ = difference operator
Ki = order of integration of a particular series.
ECMt-I= error correction mechanism which is the last
Period equilibrium error.
∑ = pure white noise error.
3.3
JUSTIFICATION OF THE MODEL
The choice of a non-monotonic model in this work is triggered
by the fact that, though, trade openness at the early stage of
iv
introduction into a developing country like Nigeria would certain have
a different structure and pattern where compared with its long run
effect on the economy’s output performance. This fact is embedded in
the standard development economic theory and buttress by
Baliamoune- Lutz and Ndikumana (2007). The explanation follows
suit: at the early stage, when a developing country like Nigeria open
up its economy for trade, its domestics firms will face intense
competition with the “tiger” foreign firms as the entire market will be
flooded with imported products which are cheaper and relatively
better in terms of qualify than the domestically produced products.
This will make some of the infant industries to loss their sales with
less revenue along side with high cost of production. This is unlike the
foreign firms that enjoy low cost of production either economies of
large scale production. As a result, many domestic firms will be
forced out of the market. This will surely have a negative effect on the
economy.
Nevertheless, as the economy is acquiring new technologies
from abroad via openness as well as improving on its domestic
iv
infrastructure and capacity utilization of resources in the long run, this
will lead to low cost of production for the domestic infant industries
and enable them to compete favorably with the foreign products in the
marked. This will certainly have positive effect on the economy as its
domestic production capacity will increase which will further lead to
increase in export products, thus, having favorable balance of
payment. Another argument also suggests that developing countries
should look inward to achieve its development in the long run.
From the on going discussion, it is evident that fitting a
monotonic model for such a situation would either over estimate or
under estimate the actual potential of the economy; hence the need for
a non-monotonic model. The postulated model is a real model as its
variables are all in real form except unemployment. While the degree
of openness and real exchange rate represent the external shocks to
the economy, the real interest rate and unemployment rate represent
the internal shocks to the economy.
Meanwhile, the second model is constructed to test for
structural charge in the growth output before and after the introduction
iv
of the structural Adjustment Program (SAP) in 1986. Finally, the
Error Correlation Model (ECM) is postulated so as to capture the
linkage between the short run dynamics of the economy and the long
run equilibrium of the economy.
3.4
ESTIMATION TECHNIQUES
In order to develop strong, robust and reliable models that
capture the relationship before trade openness and output growth, the
research work adopts the econometric techniques of the NonMonotonic modeling and the Analysis of Covariance (ANCOVA)
modeling. In building these models, the Ordinary Least Square (OLS)
is used as the estimation technique. The method of OLS is extensively
used in regression analysis primarily because it is initiatively
appealing and mathematically much simpler than nay other
econometric technique (Gujarati, 2003).
The OLS method is based on some assumptions (see Gujarati,
2003) which make the OLS estimators to become Blue (Best linear
Unbiased Estimator). Some of the short comings of the OLS method
include the fact that while some of its assumptions are unrealistic
iv
(such
as
no
autocorrelation,
homoscedasticity
and
no
multicollinearity); a single model as well can not fully satisfy all the
assumptions at a time. Also, no single test can solve all the problems
of this method at a time. Moreover, the OLS method can not be
applied to purely non-linear models such as ones that are non-linear in
parameter. As a result of some of these short-comings, we use the
OLS method but correct the stand errors for autocorrelation by a
Newey-West method. The corrected standard errors are known as
HAC (Heteroscedasticity –and autocorrelation-Consistent) standard
errors or simply as Newey-West standard errors.
Hence, we have to apply individual initiative along side with
the empirical rules and tests so as to obtain tenable and robust results.
Thus, an econometric modeling is said to be more of an art than a
science.
3.5
3.5.1
EVALUATION PROCEDURE
ECONOMIC TEST (A Priori Expectation)
Tests shall be conducted to ascertain the a priori expectations
which examine magnitude and signs of the parameter estimates. This
iv
evaluation is guided by economic theory. The aim of this test is to
conform whether the parameter estimates conform to a priori
expectation. The variables used in the model and their a priori
expectations are analyzed below in table (2).
Variables
Definition
Expected sign
RGDPt
This is Real Gross Domestic product
which represent the real output represent
the real output of the economy. Its natural
logarithm is taken
This is the degree of trade openness in an
economy it measures the international
competitiveness of an economy in the
global marked. It is an external stock to
the economy.
This is the squared term of the degree of
trade openness. It shows the structural
pattern of openness relative to output
growth
This is the real exchange rate. It is the rate
at which the domestic currency is being
exchanged for the foreign currency with
adjustment for relative price index; it is an
external shock to the economy.
This is the real interest rate. It is the real
cost of borrowing fund in the financial
market. It is an internal shock.
This is the unemployment rate in the
It is the dependent variable
and considered to be
stochastic.
economy. It is an internal shock.
negative.
TPNt
TPNt2
RERt
RIRt
UNEMPt
It is expected
positive.
to
be
Since the structural pattern
could be of any type, it can
be positive or negative.
It is expected
negative.
to
be
It is expected be negative
It
is
expected
to
be
iv
DUMt
TREND
ECMt-1
This is a dummy variable introduced to
capture the effect of the structural
Adjustment Programme (SAP) trade
deregulation and liberalization policies.
This is the chronological arrangement of
time which captures the incremental
growth of output over time. It also serves
the purpose of detrending the fluctuations
among the exogenous variables.
This is the error correction mechanism.
Since the effect of a policy
could be favorable or
adverse, its signs can be
positive or negative.
It is expected to be
positive.
It is expected
negative.
Table 2: a priori expectations
3.5.2
STATISTICAL (FIRST ORDER) TEST
Here, various statistical tests will be carried out so as to verify
the acceptability, reliability, and robustness of the estimated
regression result. The tests include:
Student t-Test
This is used to test the statistical significance of the individual
parameter estimates in the regression models. This work will use the tdistribution to test the statistical significance of these parameter
estimates.
F-Test
to
be
iv
This is used to test for the overall significance of the model. It
tests the simultaneous null hypothesis of all the parameter to be equal
to zero in the regression model.
R2-Coefficient of Determination
This test is used to measure the goodness of fit of a regression
line. It measures the proportion of the total variation in the dependent
variable explain by the repressors in the model.
r-Coefficient of Correlation
This measures the significance of the strength of linear
association (correlation). The correlation coefficient measure the
degree of association between two variables (such as TPN and RGDP
in the case of this work). It is obtained through the product moment
correlation coefficient.
3.5.3
ECONOMETRIC (SECOND ORDER) TEST
Here, various tests will be carried out in order to verify whether
the estimated regression results conform to the classical (normal)
linear regression model assumption. This test includes:
iv
Test of Normality
This test is used to verify whether the error term is normally
distributed. The Jacque-Beva (JB) test will be used to verify this
assumption.
Test of Heteroscedasticity
This test is used to verify the assumption of equal spread of the
error variance (homoscedastic) between members of the same series
of observations. The white’s heteroscedasticity test (with no cross
term) will be employed in the test.
Test of Autocorrelation
This test is used to verify the randomness of the error term
between members of the same series of observations. As a result of
the numerous assumptions and problems associated with the
conventional Durbin-Watson (DW) test, the Breusch-Godfrey (LM)
test will be employed to verify this hypothesis.
Test of Specification Error
iv
This test is used to verify whether the econometric regression
model being estimated is correctly specified. The Ramsey’s RESET
(Regression Specification Error Test) will be employed.
Forecast Test
This test is used to verify the reliability of the estimated
regression model in forecasting future values. The Henry Theil’s in
equality coefficient will be used to evaluate the forecasting
performance of the model.
3.6
SOURCES
OF
DATA
AND
SOFTWARE
FOR
ESTIMATION
Data is the most important materials for any economic research
or analysis, and very much indispensable to the field of econometrics
indeed. Gugarati (2003 asserted that the success of any econometric
analysis ultimately depends on the availability of appropriate and
accurate data. In other words, the researcher should always keep in
mind that the results of research are only as good as the quality of the
data.
iv
The research study makes use of secondary data. The data used
are obtained from the Central Bank of Nigeria (CBN) statistical
bulletin 2007 and National Bureau of Statistics (NBS) online
publication for 2006.
The percentage ratio and real values are computes by the
researcher in order to capture the objective of the study and in
congruence with economic theory.
The econometric software packages used for the analysis of this
work are the Reviews 3.1 and SPSS 14 versions, white the Microsoft
Excel 2003 is used to enter the data.
CHAPTER FOUR
PRESENTATION AND ANALYSIS OF RESULTS
iv
4.1
INTRODUCTION
The purpose of this chapter is for presentation, evaluation and
analysis of the regression results of the models postulated as well as
verification of the various working hypothesis of this research which
are drawn from the objective of the study. The results of the OLS
regressions of the first and second models are presented below. The
parameter estimates are also subjected to various economic, statistical
and econometric tests.
Finally, we analyze our results in order to verify whether they
conform to the working hypothesis of this study.
4.2
PRESENTATIONS OF REGRESSION RESULTS
The ordinary least square (OLS) regression results for first and
second models are presented below:
Model 1:
iv
Dependent variable: LOG (RGDP)
Variable
Coefficient
C
10.18152
TPN
0.025450
2
TPN
0.000190
RER
5.67E-05
RIR
-0.006919
UNEMP
0.012686
TREND
0.019105
Table 3: results of model 1
Std. Error
0.134217
0.006052
5.00E-05
1.51E-05
0.003754
0.004581
0.002605
R2 = 0.924212
Adjusted R2 =0.909543
t-statistic
75.86839
4.205461
-3.811704
3.757570
-1.842949
2.769490
7.333272
Probability
0.0000
0.0002
0.0006
0.0007
0.0749
0.0094
0.0000
F-statistic = 63.00557
D-W statistic = 1.790166
For full detail of model 1 results see appendix (1)
Model II:
Dependent variable: LOG (RGDP)
Variable
Coefficient
C
11.21105
DUM
-0.772697
TREND
0.002437
DUM*
0.040715
TREND
Table 4: results of model II
R2 = 0.847398
Std. Error
0.136498
0.172093
0.013885
0 .014603
t-statistic
82.13329
-4.489996
0.175541
2.788147
F-statistic = 62.93409
Adjusted R2 = 0.833333 D-W statistics =0.556859
Consult appendix (II) for complete results of
Probability
0.0000
0.0001
0.8617
0.0086
iv
Mode II
4.2.1
TEST OF STATIONAIRY
In order not be run a spurious regression, we subjected the
variables of the above model to unit root test. The Phillips-Perron
(PP0) unit root test is carried out to do this. The Phillips-Perron test is
based on the OLS estimate ά of
in the model.
∆Yt = + ∆Yt-1+ μt
The hypothesis to be tested here is:
Ho:
= 1 (stationary)
H1/ / <1 (non –stationary)
Decision Rule: Reject the null hypothesis of stationarity if the
absolute value of the calculated PP-statistic is less than the absolute
value of the critical PP – statistic. Otherwise, do not reject Ho.
The stationarity test results for the variables are presented in the
table below:
Level form
First difference
iv
variable
Critical values
pp-statistic
RGDP
TPN
TPN2
RER
RIR
UNEMP
1.306661
-2.749627
-3.346943
1.482691
-1.825652
-1.690459
critical values
pp-statistic
1%
NS
NS
NS
NS
NS
NS
5%
NS
NS
NS
NS
NS
NS
10%
NS
S
S
NS
NS
NS
-6.112691
-11.03146
-12.84645
-4.042057
-9.541773
-7.306097
1%
S
S
S
S
S
S
5%
S
S
S
S
S
S
Table 5: Results of stationarity test
Where NS = non –stationarity
S = stationarity
The Mackinnon critical values are:
1% critical value = -3.6228
5% critical value = -2.9446
10% critical value = -2.6105
From the above table, it easy to deduce that all the variables are
only stationary after first difference at 1%, 5% and 10% critical levels
respectively. That is to say they are all integrated of order one i.e 1(1).
This means that the mean variance and autocovariance of each series
10%
S
S
S
S
S
S
iv
are costant overtime after difference at the chosen critical level. For
comprehensive results of the stationarity test, consult appendix (III).
4.2.2 TEST OF COINTEGRATION
Even though individual series in the models above seems not to
be stationary at level form, it is possible that their linear combination
may be stationary at level form. Hence, they will be co integrated.
That is to say, there exist a long run relationship between the
dependent variable and the independent variables. In order to verify
this hypothesis, we use the Augmented Engle-Granger (AEG)
cointegration test. This test makes use of the residuals generated from
the cointegrating regression and subjects it to unit root test using the
Augmented Dickey-Fuller (ADF) test.
The AEG test is specified as
∆μt = μt -1 +∑ i∆μt-1 + ℓt
Where μ = The generated residual series
ℓt = pure white noise error.
The hypothesis to be tested is:
Ho:
= 0 (non cointegration)
iv
H1:
≠ 0 (cointegraton)
Decision Rule: Reject Ho if the absolute value of the ADF test
statistic is greater than the absolute critical value at the chosen level of
significance for the generated residual series; otherwise, do not reject
Ho:
The result is presented below:
Variable
Residual (μt)
ADF statistic
-4.145516
1%
-3.6228
Critical values
5%
10%
-2.9446
-2.6105
Table 6: Result of Cointegration Test
From the result obtained, we therefore do reject Ho and
conclude that there exist cointegration among the variables i.e there is
a longrun relationship among the variables of the model at the chosen
critical level. For detailed result of the cointegration test, see appendix
(iv).
4.2.3
THE ERROR CORRECTION MODEL (ECM)
The existence of cointegration among the variable of the model
which we verified above necessitates the need for the postulation of
iv
the error correction model (ECM). This model aims to link the short
run dynamics with the longrun equilibrium the result of the ECM is
presented below.
Dependent variable: DLOG (RGDP).
Variable
Coefficient
Std. Error
t-statistic
Probability
C
D(TPN)
D(TPN2)
D(RER)
D(RIR)
D(UNEMP)
ECMt- 1
0.031238
0.013803
-9.41E-05
-1.08E-05
-0.003360
-0.002548
-0.1785507
0.015978
0.005890
4.40E-05
1.58E-05
0.001588
0.003612
0.72896
1.955105
2.343573
-2.140235
-0.682625
-2.115853
0.705384
-4.543232
0.0599
0.0259
0.0406
0.5001
0.0428
0.4860
0.0001
Table 7: Result of the Error correction model
R2 = 0.502682
F-statistic = 5.053938
Adjusted R2=0.403219 D-W statstic=1.407372
see appendix (v) for comprehensive result of the error correction
model.
4.3
4.3.1
INTERPRETATION AND EVALUATION OF RESULTS
EVALUATION BASED ON ECONOMIC CRITERIA
iv
In this section, we present the economic interpretation of the
regression results and verify whether parameter estimates in each
model conform to a priori expectation.
Model 1:
In the first model, the dependent variable is the log of real GDP
while the independent variables are: Degree of openness to trade, the
squared term of the openness to trade real exchange rate real interest
rate, unemployment rate and the trend value.
CONSTANT(C): In the first model, the constant coefficient of
10.18152 represent the value of log of RGDP at the beginning of the
study period i.e. LOG (RGDP) = 10.18152. By taking the antilog, we
obtain that the value of real GDP at the beginning of the study period
(i.e. 1969) is N26.410.58 million
(=e 10.18152), other factors held constant.
DEGREE OF OPENNESS TO TRADE (TPN): The sign of its
coefficient is positive. This conforms to the standard economic theory
which postulates that trade openness enhance economic growth. The
coefficient of 0.025450 implies that over the study period, on average,
iv
a one percentage (1%) increase in the degree of trade openness leads
to approximately 2.55% (0.025450 x100%) increase in output growth.
This early stage increase in output growth as a result of openness to
trade
may
be
due
to
internal
vibrancy
of
government
objectives, development of infrastructure and, indeed, the oil boom of
the 1970’s.
SQUARED TERM OF DEGREE OF OPENNESS (TPN2): The
coefficient of the squared TPN of -0.0019 implies that as an economy
continue to open its border to external trade over a longer time, output
growth begins to decline at an approximate rate of 0.02% (=-0.00019
x 100%). This result shows the effect of unregulated openness to trade
both in the short run and long run (see fig. 5 below). During the oil
boom of the 1970’s, which led to greater output growth, huge income
was generated. This realized income was further spent lavishly on
luxuries which were mostly imported goods. Also the deregulation of
the external sector during the IMF/Word Bank – Sponsored Structural
Adjustment Programme (SAP) of 1986 is another point here. Hence,
iv
the international competitiveness of the economy continues to dwindle
which further led to decline in output growth proxy by real GDP.
Figure 5: Non-Monotonic relationship between TPN and RGDP.
RGDP
O observed
Quadratic
200000.000000000000
150000.000000000000
100000.000000000000
50000.000000000000
20.00
40.00
TPN
60.00
80.00
iv
REAL EXCHANGER RATE (RER): The sign of the real exchange
rate coefficient is positive. This does not conform to the theoretical
postulation which stressed that as foreign currency say (dollar)
appreciate (negative) against the domestic currency (say Naira),
exports will become cheaper while imports will be more expensive,
hence, greater net export which turn means increase in GDP (output).
Thus there should be a negative relationship between RER and
RGDP. The coefficient of 5.67E-05 means that over the period of
study, a 1% increase in real exchange rate, on average, leads to
approximately 0.006% (=0.00000567 x100%) increase in the output
growth (RGDP). Although the economic impact of RER on RGDP in
Nigeria is very small, it is however statistically significant. This result
indirectly shows the magnitude of the impact of the foreign exchange
market to the growth of the economy. The foreign exchange market is
regarded as the largest market in the world. However, the result shows
that it has little impact on the Nigerian economy. This may be as a
result of the fact that the exchange market in Nigerian is largely
dominated by the parallel market (fondly known as black market)
iv
which is regarded as part of underground economy and not accounted
in the national income computation. Also, the sign of real exchange
rate is positive. This may be as a result of inconsistency in
government policies with regard to exchange rate.
REAL INTEREST RATE (RIR): The sign of the real interest rate
coefficient is negative. This conforms to a priori expectation as
increase in rate of interest leads to rise in cost of borrowing which
discourages investors from borrowing for investment purpose, thus,
reducing investment level; hence, reducing productivity and output.
The result further shows that during the study period 1% increase in
real rate of interest will on average lead to approximately 0.69%
(=0.006919 x 100%) decrease in real GDP. But this result is not
statistically significant. This reflects the low level of development of
the financial sector in the economy especially the money and capital
markets. The result further implies that the financial sector instrument
(interest rate) does not have significant economic impact in
determining the level of output growth in Nigeria.
iv
UNEMPLOYMENT
RATE
(UNEMP):
The
coefficient
of
unemployment rate has a positive sign. This does not conform to
economic theory which postulates that a rise in unemployment level
will reduce productivity, hence output growth.
The unemployment rate coefficient of 0.012686 indicates that a
1% increase in unemployment rate, on average, leads to
approximately 1.27% increase (0.012686 x 100%) in real GDP. This
kind of result is only possible when the impact f a few highly skill
labour, employed at the expense of much unskilled labour that is laidoff is economically significant. One of the arguments in favour of
openness to trade is that new technologies and skills in the production
process may require more of capital and little labour. Hence, a branch
of undeveloped, inept and sluggish labour is retired to the labour
market causing high rate of unemployment. Hence, the simultaneous
coexistence of increased growth of output as a result of improved skill
and technology on one hand, and high unemployment rate on the other
hand in the economy. Nevertheless, the proportional relationship
between unemployment and real GDP also indicate the explosive
iv
nature of the unemployment rate which has a significant impact on
industrial development in the nation. Moreover, the result reflects the
impotence of various government policies to curb unemployment in
the face of stagnation and fluctuation of macroeconomic indicators in
the economy.
TREND: The sign of the trend value is positive which conforms to a
priori expectation. The 0.019105 trend coefficient indicates that, on
average, output growth (proxy by RGDP) increased at the rate of
1.91% (0.019105 x100%) per annum, other variables held constant.
But the compound rate of growth of output over the study period is
approximately 1.93% i.e. [(e0.019105-1) × 100%].0.02% difference
between the actual and compound rate of growth is due to the
compounding effect. Moreover, the trend coefficient is highly
significant to detrend the time relationship among the explanatory
variables.
Model II:
iv
This is an ANCOVA model which comprises of both discrete
and continuous variables at the same time. We observe that the
dummy is assigned zero (0) for pre-SAP era and one (1) for post-SAP
era. The expectations of the regression results for the pre-SAP and
post-SAP era are given as:
E [LOG (RGDPt)/DUMt = 0] = 11.21105 + 0.002437 TREND
E [LOG (RGDPt)/DUMt = 1] =10.438353 +0.043152 TREND
This shows that the median value of the LOG of real GDP for the preSAP era is N73,943.01 million (=e11.21105). Also, the 0.002437 trend
coefficient indicates that the compound rate of growth of output for
the pre-SAP period is approximately 0.244% [=(e0.002437-1) x 100%].
But this rate of output growth is not statistically significant i.e. the
trend is flat. This implies that during the pre-SAP era, there is no
significant increase in output growth for that period of time. This may
as a result of impromptu oil boom of the 1970’s and the crowding-out
effect that follows suit on the economy between late 1970’s and the
early 1890’s. Another reason may be due to political instability and
iv
policy inconsistency exhibited by various government of the
economy.
The differential intercept dummy coefficient of 0.772697
implies that there is a decline in the median value of log of real GDP
for the post-SAP era by 0.772697 when compared with that of preSAP era. This difference in median value of output growth between
the two periods under study is highly significant. The median value of
real GDP of post SAP era is N34,144.37 million i.e. (=e11.21105-0.772697).
Meanwhile, the differential (dummy* trend) slope of 0.04715 implies
that during the post –SAP era, the rate of growth of output (RGDP)
has risen to approximately 4.41%[=(e(0.002437+0.040715))×100%]
as
against growth rate of about 0.244% during the pre-SAP era. This
implies that during the period of post-SAP, output growth increase at
a cumulative rate of 4.41%. This slope differential is statistically
significant.
Since both the differential intercept and differential slope are
statistically significant. Since both the differential intercept and
differential slope are statistically significant, we therefore conclude
iv
that there is structural break in the growth of output over the sample
period. This implies that the trade liberalization policy of the SAP has
a positive impact on Nigerian economy as it leads to greater output
growth rate.
THE ERROR CORRECTION MODEL
In the ECM, the coefficient of the differenced variables reflects
the short run dynamics. In this model, all the variables conform to the
priori expectation. Also all the variables are statistically significant
except for the RER and UNEMP. The Error Correction Mechanism
(ECMt-1) is also negative which conform to a priori expectation. The
negative value of the ECM implies that output growth (proxy by
RGDP) is above equilibrium and will start falling in the next period to
correct the equilibrium error. The coefficient of -0.785507 implies
that about 79% (0.785507 x100%) of the equilibrium error will be
corrected in the next period. That is, RGDP will adjust to equilibrium
by about 79% in the next period. The speed of adjustment of the ECM
iv
is sufficiently high to correct the imbalance in the macro economic
fluctuation.
The 0.013803 coefficient of the differenced TPN implies that in
the short run, a 1% rise in degree of openness will lead to about 1.38%
(=0.013803 x100%) increase
in RGDP. The differenced TPN2
coefficient of -9.41E-05 indicates that a further 1% increase in
squared term of the degree of openness will lead to a minute decline
in RGDP by about 0.009% (see fig.5 above).
Also, a 1% increase in real interest rate (RIR) will lead to about
0.001% decline in RGDP in the short run. Nevertheless, this result is
not statistically significant. Moreover, on the short run a 1% increase
in the real interest rate (RIR) will lead to about 0.34% decline in real
GDP. Furthermore, a 1% rise in unemployment rate will cause output
growth fall by about 0.25% in the short run. However, this result does
not have much economic impact.
4.3.2
CRITERIA
EVALUATION
BASED
ON
STATISTICAL
iv
Here, the t-test, f-test and R2 (coefficient of determination) are
carried out to test the statistical reliability to the estimated parameters
and the regression results in general. In order to avoid repetition, these
tests are carried out on the regression results of the first model only.
We will also test for the degree of association between RGDP and
TPN using the product moment correction coefficient ®.
t-Test
This is used to determine the statistical significance of
individual parameter in a model. The hypothesis to be tested is:
Ho:
βi = 0 (the estimated parameter is statistically
insignificant).
Hi:
βi ≠ 0 (The estimated parameter is statistically
significant).
The test statistic is given as:
T = β^i ~t /2 (n-k)df
Se(β^i)
The critical value is obtained from the students
iv
t-distribution table at ( /2) level of significance and (n-k) degree of
freedom.
Decision Rule: Reject Ho if/t-cal/>t /2(n-k) df, otherwise do not
reject.
Alternatively, using the rule of thumb, we could reject Ho if/t -cal/>2.
At ∞ = 0.05, n-38, k=7
t /2 (n-k)df =t0.025(31)≈ 2.042.
The calculated t-values are presented below on the result obtained
from the regression on model 1.
Variable
C
t-statistic
75.868
Critical
2.042
Decision
/t/>t*:Reject H1
TPN
4.205
2.042
/t/>t*:Reject Ho
TPN
-3.812
2.042
/t/>t*:Reject Ho
RER
3.758
2.042
/t/>t*:Reject Ho
RIR
-1.843
2.042
UNEMP
2.769
2.042
/t/<*: do not
Reject Ho
/t/>*: Reject Ho
TREND
7.333
2.042
/t/>*:Reject Ho
Table 8: Summary of the t-test
Conclusion
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
insignificant
Statistically
significant
Statistically
significant
iv
From the results displayed in the table above, we conclude that
all the parameter estimates, are statistically at 5% level of significance
except for real interest rate which is statistically significant at 10%
critical level.
F-Test
This measures the overall significance of the regression model.
The F-value provides a test of the null hypothesis that the true slope
coefficients are simultaneously zero. That is:
Ho: x1 =
2
=
3
=
4
=
5
=
6=
0 (the model is statistically
insignificant)
Hi: ≠ 2≠
3
≠
4
≠ 5≠
6
≠0 (the model is statically significant)
The test statistic is given 25:
F = ESS/(k-1)~ F (k-1, n-k)df
RSS/(n-k)
Where ESS=estimated sum of square
RSS = Residual sum of square
The critical value is obtained from the F-distribution table at
significance and (k-1, n-k) degree of freedom.
Decision Rule: Reject Ho if F-statistic>f (k-1, n-k)df ;
level of
iv
Otherwise, do not reject Ho
From the regression result
F-statistic = 63.00557
At
=0.05, n=38, k=7
F (k-1, n-k)df = F0.05(6,31) ≈ 2.42.
Conclusion: Since f-statistic =63.00557 is greater than the critical
F=2.42, we thereby reject Ho and conclude that the model has a robust
fit and it is statistical significant. That means there exist a true
relationship between the regression and the regresses.
R2 (Coefficient of Determination)
This measures the goodness of fit of the estimated model. The
R2 measure the proportion of total variation in the regress and
explained by the regression model. From the regression result the R2
is 0.924212 while the adjusted R2 is 0.909543. This means that the
model explain about 92% of the total variation in real GDP (output
growth). This high R2 cannot be said to be statistically significant for
the true goodness of fit in a model unless subjected to test. The
hypothesis to be verified here is:
iv
Ho:
R2 = 0 (the R2 is statistically insignificant)
H1:
R2 ≠ 0 (the R2 is statistically significant)
The test statistic for the critical R2 is given as
R2 =
(k-1)f
(k-1)f + (n-k)
Where f is the critical-f value at
level of significance, k is the
number of parameters in the model and n is the number of
observations.
Decision Rule: Reject Ho if observed R2 is greater than the critical R2:
otherwise do not reject Ho. From the regression result;
Observed R2 ≈ 0.924
At
= 0.05, k=7, n=38
R2 = 0.319.
Conclusion: Since observed R2 = 0.924 is greater than the critical R2
= 0.319, we thereby reject Ho and conclude that the coefficient of
determination (R2) is statistically significant and a true goodness of fit
for the model.
r (coefficient of correlation)
iv
This is a measure of the degree of association between two
variables. It measures the strength of degree of linear association
between two variables. The product moment correlation coefficient is
given as
r=
n∑x1y1-(∑y1)
√(n∑x12 – (∑x1)2][n∑y12-(∑y1)2)
When the coefficient of correlation (r) between real GDP (x1) and
degree of openness (yi) is computed, it is observed that:
r = 0.594989
This result shows that there is positive relationship (or linear
association) between output growth and trade openness. The
correlation of about +0.6 implies that there is a positive modern linear
association or correlation between openness and output growth in
Nigeria. But is this correlation coefficient statistically significant?
To answer this question, we subject the correlation result to test. The
hypothesis to verify is.
Ho: 0 = 0 (true linear association does not exist between the two
variables)
H1: 0 ≠ 0 (true linear association exist between the two variables).
iv
The test statistics is given as;
Z = x –µ ~N(0,1)
б
Where x =1/2 ln 1-r
1-r
μ = ½ ln 1-0
1-0
1
=√ n-3
The critical value is obtained from the standardized normal
distribution ( /2) level of significance.
Decision Rule: Reject Ho if /Zcal/> Z ∞12, otherwise do not reject Ho.
After simple computation, we observed that
X =0.68535,. μ=0, б=0.16093
:. Zcal = 4.056
Also, zt =0.05
Z
12=Z0.025
= 1.96
Conclusion: Since Zcal =4.0546 is greater than Z /2 =1.96, we
therefore reject Ho and conclude that the correlation coefficient of
trade open and real GDP is statistically significant. This means that
iv
linear association (correlation) truly exists between the two variables
at 5% level of significance.
4.3.3
EVALUATION
BASED
ON
ECONOMETRIC
CRITERIA
Here, various tests are conducted in order to test for robustness
and reliability of results obtained from the OLS regression. These
tests will also help us to verify the fulfillment of the assumptions
underlying the classical (normal) linear regression model (CLRM) as
used within study. The tests to be conducted include. Normality test,
multi-co linearity test, Heteroscedasticity test, Autocorrelation test,
test of specification errors and forecast test.
Normal Test
One of the assumptions of the CLRM is that the error terms are
normally distributed with zero mean and constant variance i.e.
μt~N (0,б2)
The normality test is conducted to verify whether the error
terms are normally distributed. The Jacque – Bera (JB) test of
normality is used to verify this assumption. This test is based on the
iv
residuals generated from OLS. Under the null hypothesis that the
residuals are normally distributed, the JB statistic asymptotically
follows the chi-square distribution with two (2) degrees of freedom.
The test statistic given as:
JB = n
s2 +(k-3)2 Nx2
6 24
(2)df
Decision Rule: Reject the null hypothesis of normality if JB –statistic
exceeds critical JB (i.e.x2(2)df) at 5% level of significance; otherwise,
do not reject the null hypothesis of normality.
Form the result obtained, we observed that: JB –statistics
=1.1863575
While, critical JB = (X2(2)df) = 5.99147
Conclusion: Since the JB-statistic =1.18675 is less, than the critical
JB = 5.99147, we do not reject the null hypothesis of normality and
therefore conclude that the error terms are normally distributed at 5%
level of significance.
Multicollinearity Test
iv
Another assumption of the CCRM is that there is no
multiconlliearity among the explanatory variables induced in the
regression model. Multicollinearity refers to the existence of more
than one exact (or inexact) linear relationship. Multicollinearity test is
carried in order to verify the possibility of this assumption. The test is
carried out using the correlation matrix. It has been suggested that if
the pair-wise correlation coefficient between two regression is highly
present excess of 0.8, then multicollinearity is present and may pose
serious estimation problem. The result of the correlation matrix is
presented below:
TPN
TPN2
RER
RIR
UNEMP
TREND
TPN
1.0000
0.9831
0.3399
0.5811
-0.2529
0.6720
TPN2
0.9831
1.0000
0.3113
0.5536
-0.2769
0.6466
RER
0.3399
0.3113
1.0000
0.2764
-0.0068
0.6603
RIR
0.5811
0.5536
0.2764
1.0000
-0.6220
0.7576
UNEMP
-0.2529
-0.2769
-0.0068
-0.6220
1.0000
-0.5196
Table 9: pair –wise correlation matrix
From the correlation matrix above, we can confirm that there is
no pair-wise correlation coefficient that is in excess of 0.8 except
between TPN and TPN2 which is about 0.98. But the relationship
TREND
0.6728
0.6466
0.6603
0.7576
0.5196
1.0000
iv
between TPN and TPN2 is non-linear. Hence, they can not be said to
be collinear. Therefore we conclude that there is no multicollinearity
among the repressors.
Heteroscedacity Test
One important assumption of the CLRM is that the error terms
are homoscedasticity variance i.e.
E (μi2) = 02 i = 1,2, ----------n.
The heteroscedasticity test is carried out in order to verify whether the
disturbances μi actually exhibit the equal variance (homoscedasticity)
assumption. The white’s heteroscedasticity test with (nocross term) is
used to carry out this task. This test make use of the residuals
generated from the original regression. It then runs each of the
regressors and their squared terms against the generated residuals.
The auxiliary model can be stated as:
μt = o +1TPN +2TPN2 +3 (TPN2)2 + 4RER2 + 5RER2 +6RIR +
7RIR2 +8 UNEMP + 9UNEMP2 + 10TREND +11TREND2 +Vi
Where Vi =pure white noise error
iv
This model is run and auxiliary R2 from its obtained. The hypothesis
to be tested is
Ho:
1 = 2 = 3 = --------- 11 = 0 (Homoscedasticity)
Hi: 1≠ 2 ≠ 3 ≠ --------- 11 ≠ 0 (Hoteroscedasticity
Under this hypothesis, it has been shown that the sample size (n)
times the R2 obtained from the auxiliary regression asymptotically,
follow the chi-square distribution with degree of freedom equal to the
number of regressors (excluding constant term) in the auxiliary
regression. That is:
n.R2 ~ X2 df
Decision Rule: Reject Ho if 2 cal > 2 tab at 5% level of
significance; otherwise, do not reject Ho.
From the result obtained;
Calculated X2 = 11.43079
While, critical 2 0.05 (II) = 19.6751
iv
Conclusion: Since calculated 2 = 11.43079 is less than critical 2 df
= 19.651, we therefore do not reject the null hypothesis of
homoscedasticity and conclude that the error terms have a constant
variance.
Autocorrelation (or serial correlation) Test
The CLRM also assumes that autocorrelation does not exist in
the disturbances. That is to say, the disturbance term relating to any
observation is not influenced by the disturbance term relating to any
other observation. Symbolically;
E(μi μ;) = 0 i≠j
The Breusch-Godfrey (BG) general test of autocorrelation also
known as LM-test is used to verify this assumption. This test is better
than the conventional Durbin-Watson test of autocorrelation in the
sense that it allows for non-stochastic repressors such as the lagged
values of the regress and, higher-order autoregressive schemes, and
simple or higher order moving averages of the error terms. The test
assumes that the error term generated from the original regression
follows the pth-order autoregressive, AR(P) scheme. Then, the AR (P)
iv
scheme alongside the original regresses is run against the generated
residual. For our model, we generated AR (2) for the residual. The
auxiliary model to be tested is;
μt =β0 + β1TPN + β2TPN2 + β3RER + β4RIR + β5 UNEMP +
β6TREND +p,μt-1 +pμt-2 +et.
The hypothesis to be tested is
Ho: p1 = p2 = o (No autocorrelation)
H1: p1 ≠p2 ≠0 (autocorrelation)
The test statistic is given as;
(n-p)R2 ~ x2 (p)df
Where n = number of observation
p = the order of the autoregressive scheme of μt
R2 = R2 from auxiliary regression
Decision Rule: Reject Ho if 2 and > 2(2) critical at 5% level of
significance; otherwise do not reject Ho.
From the result obtained,
Calculated X2 = 0.299777
While, critical 2(2) = 5.99147
iv
Conclusion: Since calculated 2 is less than critical 2 =5.99147, we
do not reject the null hypothesis of no autocorrelation and therefore
conclude that the error terms in the model are not serially correlated.
Test of Specification Errors
Another assumption that is fundamental to the CLRM is that
the model must be correctly specified. A general test proposed by
Ramsey called RESET (Regression specification Error Test) is used to
verify this assumption. This test follows the F-distribution. Under the
null hypothesis that the model is well-specified, our decision rule is to
reject the null hypothesis if the calculated F exceeds the critical value
F at a given level of significances.
From the Ramsey RESET result,
F-statistic = 1.57044
While, critical F0.05 (6,31) ≈ 2.42
Conclusion: Since F-statistic ≈ 1.57 does not exceed the critical F ≈
2.42, we do not reject the null hypothesis of well-specification of
model and therefore conclude that the estimated model is correctly
specified; that is, there is no specification error.
iv
Forecast Test
This test is carried out so as to evaluate the forecasting performance of
the model. Henry Theil has suggested a systematic measure of the
accuracy of the forecast obtained from an econometric model. The
measure is called Theil inequality coefficient, which is defined as:
μ = + ∑(pi –Ai)2/n
√ ∑ A2i/n
pi = predicted (forecast) change in the regress and
Ai = Actual (Realized) change in the regress and
The smaller the value of the inequality coefficient, the better is the
forecast performance of the model. From the result obtained, it is
observed that the inequality coefficient is about 0.0458. This shows
that the model has a high prediction power. Also, the bias proportion
(the difference between the predictive and the actual value of the
regress and) in the model is about 0.0016. This also indicates higher
forecasting strength of the model. Moreover, the covariance
proportion, which measures the correlation between actual and fitted
iv
values, is approximately 96%. This is also a very good result for the
forecast performance of the model.
In summary, the predictive power of the model is fairly high,
robust and reliable.
4.4
EVALUATION OF THE WORKING HYPOTHESES
In order to recap, the working hypothesis of this study includes
the following:
 Trade openness does not have any significant impact on output
growth in Nigeria.
 There is no other macroeconomic variable (internal or external)
that have significant impact output growth in Nigeria.
 There is no linear association (correlation) between trade
openness and output growth in Nigeria.
 There is no long run relationship between trade openness and
output growth Nigeria.
 There is no significant structural change in output growth
between the pre-SAP and post-SAP period.
iv
After rigorously subjecting these hypothesis to various
economic, statistical and econometric test, we hereby present the
findings. The results obtained from model one invalidates the first
hypothesis. Trade openness, in real sense; actually have significant
impact on output growth. The t-values of degree of openness and its
squared term are statistically significant both in short run and long
run. Model one regression results also invalidate the second
hypothesis as all other macroeconomic variables included in the
model are individually statistical significant using the t-test. This
implies that trade openness and other macroeconomic variables (both
internal and external) do not really have significant impact on output
growth in Nigeria. The F-statistic of the model is highly statistically
significant which indicates that the overall performance of the model
is pretty significant.
Also, the result obtained from the coefficient of correlation
indeed invalidate the third hypothesis as it shown that there truly exist
a linear association (correlation) between trade openness and output
growth in Nigeria. The result further shows that there exists a positive
iv
moderately high degree of correlation between trade openness and
output growth in Nigeria over the same period. This suggests that
trade openness is beneficial to the economy in general and to domestic
producers in particular.
The results obtained from the cointegration test, which was
later verified by the Error correction model, provided the ground for
the invalidation of the fourth hypothesis as it is shown that trade
openness (with other macro economic variable in the model) and
output growth are not only related in the short run, but have a long
term equilibrium relationship. The error correction mechanism
provides the basis for the adjustment of shortrun dynamics to long run
equilibrium. This mechanism is statistically significant which
indicates that the equilibrium error is not instantly corrected in the
short run, rather it persist, and is being fully corrected in the long run.
Further more, the regression results obtained from model two
provide the basis for the invalidation of the fifth hypothesis. As the
regression result shows, there exist statistically significant differences
in the intercepts and slope of both periods in question. The intercept
iv
of the first period is large than that of the second period; while the
slope of the post –SAP era is much larger than that of the pre-SAP
era. Therefore, we can conclude that there is statistically significant
structural change in the growth of output in Nigeria between the preSAP and post-SAP era. This structural changes in the growth of
output is as a result of trade liberalization policy of the structural
Adjustment programme (SAP), 1986.
Finally, from the estimated regression result of model 1, the
optimum degree of openness is estimated to be about 67% in Nigeria.
This is calculated as taking the derivative of the non-monotonic model
with respect to openness (TPN), equating it to zero and solving for
openness. This result further buttress the fact that trade openness is
quite high in Nigeria.
iv
CHAPTER FIVE
SUMMARY, POLICY PRESCRIPTION AND CONCLUSION
5.1
SUMMARY
This research work’s pursuit is to unravel the structural
relationship between trade openness and output growth in Nigeria
from 1970 to 2007. It aims to determine the structural impact of trade
openness on output growth in the presence of other internal and
external macroeconomic shocks using a non-monotonic approach. It
further used an Analysis of covariance (ANCOVA) model to
determine the possibility of structural change in output growth so as to
understudy the policy effect of the Structural Adjustment Programme
(SAP) of 1986 which tends to liberalize trade.
The regression results of the first model show that there indeed
exist an inverted U-Shape quadratic relationship between trade
openness and output growth in Nigerian. This is reflected in the
negative sign of the squared term of degree of openness. Also, all
iv
other macro economic variables in the model including real exchange
rate and unemployment rate are interest rate which is statistically
significant at 10%. These variables do not only exert significant
impact on output growth in the short run but also in the long run, and
various diagnostic and performance test have been conducted to verify
the reliability of these results.
Also, in the regression results obtained from the second model,
we observed that the policy thrust of the IMF/World Bank-Sponsored
Structural Adjustment Programme (SAP) does not only have a
significant impact on the output growth in Nigeria but in fact have
positively changed the trend of growth of output in the economy. This
implies that the trade liberalization policy of SAP has a significant
positive effect on output growth in Nigeria. This result is further
buttressed by the positive moderate correlation coefficient of about
0.6 obtained. This indicates that trade openness and output growth are
as well linearly associated. That is, an increased openness to trade
could as well mean a rise in output growth.
5.2
POLICY RECOMMENDATIONS
iv
Based on the finding of this research work discussed above, we
hereby proffer the following policy measures for long term sustenance
of output growth in the economy.
First of all, there should be optimal control of trade through the
borders of the economy. The underground economic activities of
bunkering, smuggling, child and drug trafficking,and other related
illegal activities should be properly checked. This will help the
economy to fully account for every trade/transaction through the
border and determine its impact on the output growth of the economy.
In order to achieve this, governments trade policy must be liberal.
Also, government should properly regulate import tariff so that it will
not be discouraging in such a way that it will aid illegal importation.
Secondly, there is a dire need for adequate infrastructural
development in the country. Nigeria has been recently noted to be one
of those Africa countries that have difficult geographic condition. The
country is the largest oil producer in Africa and the 6th largest oil
producer in the world. Yet, the country’s infrastructure is at serious
decay.
iv
This has negative effect on output growth as cost of production
is high due to high due to high transportation, communication, and
other services costs. Government should devote much of its resources
to the development of infrastructure. Excess crude oil revenue should
be properly allocated for infrastructural development such as good
roads, potable waters, standard rail system, buildings and other public
utilities.
Thirdly, there is a need stable macroeconomic policy as regard
to the exchange rate system of the country. Exchange rate is one of the
most volatile macro economic variables. But this variable has not
been properly handled in such a way that the country will derive
optimum benefit from it. As a result, the growth of output in the
economy has been thwarted. The government should put sound
machinery in place to properly monitor the movement of exchange
rate and regulate it indirectly through currency depreciation or directly
through devaluation. This will make the country’s exports to become
cheaper and imports more expensive; hence, a favourable balance of
iv
payment which will enhance output growth. The country’s reserve
also needs proper management.
Also, there is still need for greater development in the financial sector
of the economy. The financial sector is said to be hub of every
economy. The on going capital market as well as the money market
reform are examples towards the development of the financial sector.
The government needs o put in lace proper and non- partisan
machineries for supervision and regulation of this sector so as to
achieve optimum performance.
Moreover, stagnation is one of the various macro-economic
problems the economy has been facing for the past three decades. This
is a situation where the economy is simultaneously experiencing rise
in inflation and unemployment rate at the same time. Various
government efforts towards this problem have proven to be
economically insignificant and this has seriously inhibited the growth
of productivity, hence output, in the economy. Government should
redirect its priority and properly allocate its resources to combat these
problems. This could be achieved by creating conducive environment
iv
for business; give special attention to education, proper control of
government financial spending, effective expenditure switching and
expenditure reducing polices, and sound fiscal and monetary policy
objectives for the economy in a specified period.
Furthermore, there is an urgent need for diversification of the
economy. The Nigerian economy has been depending on crude oil
exportation. But today, this strange dependency has really dampened
the growth of the economy as the country is open to every
international shock associated with the oil market. Government should
look inward to seek for other fallow grounds where it can explore and
generate resources. Government should explore other sector of the
economy such as manufacturing, agriculture, mining and quarrying.
Finally, the government should vigorously seek to improve the
international stand of the economy with other economies of the world
so as to enlarge the market for Nigerian exports. It should also reorient its policy towards the external sector and ensure that the sector
contribute optimally to output growth.
5.3 CONCLUSION
iv
The contribution to be drawn from this study is that trade
openness have a significant economic impact on output growth in the
presence of other internal and external macro economic shock.
Nevertheless, to achieve a high and sustainable output growth, we
proffer
some
policy
recommendation
which
when
properly
implemented will surely stimulate greater growth of output.
Meanwhile, it is not all the areas that need proper treatment are
adequately treated due to various limitations being faced by this
research work. But we recommend that further studies be genuinely
carried out using different and more sophiscated methodologies and
choice variables in other to harmonise the structural relationship
between trade openness and output growth in Nigeria.
iv
BIBLIOGRAPHY
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Chang, R., Kaltani, L. (2005). Openness can be good for growth. The
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iv
Frankel, J.A and Rodrigilez, C. (1975). Portfolio Equilibrium and the
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Heymann, D. and Nufrid, A.L. (1995). High Inflation. London:
Oxford Clarendon Press.
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Kreuger, A. D. (1983). Exchange Rate Determination. Cambrige:
University. Press.
Melo, J. and Panagariya, A. (1993). The New Regionalism. A country
perspective. Cambridge: Cambridge University press.
Joffrey, M. (2008). Trade Openness and Growth. Florida, Thonmpson
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Empirical Analysis. Chicago: The University of Chicago press.
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Growth: Theory and Evidence. Abidjan: Mustafa Printing Press.
iv
JOURNALS
Anderson, J. E., & Neary, J. P. (1992). Trade Reform with Quotas,
partial Rent, Retention, and tariffs Econometrica 60: 57-76.
Baldwin, R.E (2000). Trade and growth: still Disagreement about the
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of openness to trade and the role of institution: New evidence from
African countries working paper N0 2007-05. Department of
economics, University of Massachusetts, Amherst, February
Barro, R. (1991). Economic growth in a cross-section of countries the
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iv
APPENDIX A: DATA PRESENTATION
Year
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
BP
CB
5223.3
63252.5
8712.6
76589.1
7565.2
79652.8
4606.4
86534.2
10067.6
89936.6
7453.5
98564.1
6767
159190.8
31192
226162.8
40444
295033.2
22695
385141.8
49751
458777.5
42661.5
584375
52993.8
694615.1
193412.9 1070020
285294.4 1568839
192731.8 2247100
435601
276680
434299
3047856
677957.4
3753278
834522.9
4741125
1651513
6400784
2028220.03 7612568.3
SM
13934.1
18676.3
23249
23601.3
29651.2
37738.2
55116.8
85027
100460.6
108490.3
134503.2
177648.7
200066.1
277667.5
385190.9
488045.4
592004
655739.7
797557.2
1316957
1739636
2226795.5
GDP
71859
108183
142618
220200
271908
316670
875342.5
1089680
1399703
2907358
4032300
4189250
3989450
4679212
6713575
6895198
7795758
9913518
11411067
14610882
18564595
22015709
Source: central Bank of Nigeria (CBN) Statistical Bulletin (2007)