THE
IMPACT OF TRADE LIBERALISATI0N ON ECONOMIC GROWTH IN NIGERIA (1970- 2009)
BY
IGBANI
JOHN OKORO
2007/147656
BEING
A RESEARCH PROJECT SUBMITTED TO THE DEPARTMENT OF ECONOMICS, IN PARTIAL
FULFILLMENT
OF THE REQUIREMENTS FOR THE AWARD OF A BACHELOR OF SCIENCE DEGREE IN
ECONOMICS
DEPARTMENT
OF ECONOMICS
UNIVERSITY
OF NIGERIA NSUKKA
AUGUST
2011
TITLE PAGE
THE
IMPACT OF TRADE LIBERALISATI0N ON ECONOMIC GROWTH IN NIGERIA (1970- 2009)
APPROVAL
PAGE
This
project has been supervised and approved as having satisfied the conditions for
the award of a Bachelor of Science Degree in the Department of Economics,
University of Nigeria, Nsukka.
DEDICATION
This work is
dedicated to God Almighty the most high the owner of the universe.
ACKNOWLEDGMENTS
I
am grateful to my supervisor Dr. Mrs.Gladys Aneke who ensured the ultimate
success of this study.
I
also appreciate the invaluable support and prayers made for me by my mother, Mrs.
Grace Igbani, Mr Samuel Igbani, Miss Elisabeth Igbani, Miss Lucy Igbani and my
other brothers and sisters.
I am thankful to Dr. Ada Ezeogu and Ms Christy
Inwerogu for supporting me. Finally, I acknowledge my most cherished friends Peter
Chiejile, Paul Duru, Ben Eke, Philip Mebo ,Izuchukwu Akawor, Chima Eme, Chimobi
Ahuekwe, Macdonald Ukah, Tony Ozoemena, Chukwudi Ezeani, Ositadimma, Ebube Dim,
Ifoma Anwunna, Ngozi Ibe, Awele Onyeka, Amaka Okafor, Jane Nwachukwu, Nneka
Ukwuani and Nneoma Obi.
ABSTRACT
Trade policy has
been a very contentious issue in the development of Nigeria. Using data
spanning the period 1970-2009, we examine the relationship between trade
liberalisation and economic growth in Nigeria. We focus on instabilities in
regime, trade policy, and exchange rate using both single and system estimation
techniques. We find substantial evidence that trade liberalisation has a
systematic impact on growth in Nigeria. Fiscal policy is a determinant of
macroeconomic instability in the country. The paper also argues that
policymakers in Nigeria can reduce macroeconomic instability and vulnerability
to shocks by diversifying the export structures as well as increasing export.
TABLE
OF CONTENTS
Title
Page…………………………………………………………………………………………….………………..i
Approval
Page……………………………………………………………….……………………….……………….ii
Dedication
………………………………………………………………………………………….………….…..…iii
Acknowledgement………………………………………………………………………………….…………......….iv
Abstract……………………………………………………………………………………………..…….…………..v
Table of
Contents……………………………………………………………………………………………………..vi
CHAPTER
ONE: INTRODUCTION………………………………………………….……….………….………1
1.1
BACKGROUND OF THE STUDY………………………………………………………………………….…1
1.2 STATEMENT OF
PROBLEM…………………………………………………………………………………3
1.3 OBJECTIVE OF THE
STUDY………………………………………………………………………………..4
1.4 STATEMENT OF
HYPOTHESIS…………………………………………………………………………….4
1.5 SIGNIFICANCE OF THE
STUDY……………………………………………………………………………5
1.6
SCOPE AND LIMITATION OF THE STUDY………………………………………………………………6
CHAPTER
TWO: LITERATURE REVIEW…………………………………………………………………….7
2.1 THEORETICAL LITERATURE
REVIEW………………………………………………………………….7
2.2
THE THEORY OF CUSTOMS UNIONS AND FREE TRADE AREAS…………………………………..9
2.3 REVIEW OF
NIGERIA’S TRADE POLICIES…………………………………………………………..….9
2.3.1
PRE-SAP TRADE
POLICIES…………………………………………………………………………….10
2.3.2
TRADE POLICIES DURING
SAP………………………………………………………………………..13
2.4
EMPIRICAL LITERATURES……………………………………………………………………………....15
CHAPTER THREE: METHODOLOGY……………………………………………………………………….22
3.1ANALYTICAL
FRAMEWORK……………………………………………………………………………..22
3.2 MODEL
SPECIFICATION…………………………………………………………………………....…….23
3.3EXPLANATION
OF VARIABLES THAT ENTERED THE
MODEL………………………………….25
3NATURE
AND SOURCES OF DATA………………………………………………………………………...26
3.5DATA
DESCRIPTION AND TRANSFORMATION……………………………………………………...26
3.6 ESTIMATION
PROCEDURE……………………………………………………..………………..………..27
3.6.
1UNIT ROOT TEST……………………………………………………………..……………….....………..27
3.6.2
TEST OF COINTEGRATION………………………………………………..……………………….…..28
3.7 EVALUATION
TECHNIQUES………………..……………………………..……………………………..28
3.7.1TEST
BASED ON ECONOMIC CRITERIA……………………………………………………………..28
3.7.2.TEST
BASED ON STATISTICAL CRITERIA………………………………………………………….29
3.7.3TEST
BASED ON ECONOMETRIC CRITERIA………………………………………………………..30
CHAPTER
FOUR: PRESENTATION AND DISCUSSION OF RESULTS…………………………………32
4.4
PRESENTATION
AND ANALYSIS OF THE REGRESSION RESULTS…………..…………………32
4.1.1
EVALUATION BASED ON ECONOMIC CRITERIA…………………………………………………33
4.2 EVALUATION BASED ON STATISTICAL CRITERIA
(FIRST ORDER TEST)………...……….34
4.2.1
COEFFICIENT OF DETERMINATION……………………………………………………….……….35
4.2.2
T- TEST..…………………………………………………………………………………………….……..35
4.2.3 THE
F-TEST...……………………………………………………………………………………………..36
4.3
EVALUATION BASED ON ECONOMETRIC CRITERIA
(SECOND ORDER TEST)…....………..37
4.3.1
NORMALITY TEST……………………………………………………………………………..………..37
4.3.2.
RESULT FOR UNIT ROOT TESTS…………………………………………………………….………38
4.3.3.
RESULT FOR COINTEGRATION TEST………………………………………………………..…….39
4.3.4 TEST FOR
MULTICOLLINEARITY………………………………………………………….…...….40
4.3.5 TEST FOR
HETEROSCEDASTICITY………………………………………………………..……....40
4.3.6. TEST FOR
AUTOCORRELATION…………………………………………………………………...41
4.3.7. PAIRWISE GRANGER
CAUSALITY TEST…………………………………………………………42
4.4 EVALUATION OF RESEARCH HYPOTHESIS………………………………………………………42
4.5 CHAPTER
SUMMARY………………………………………………………………………….………..44
CHAPTER
FIVE…………………………………………………………………………………………...….45
5.1
SUMMARY RECOMMENDATION AND CONCLUSION OF THE RESEARCH FINDINGS……45
5.2.
RECOMMENDATION AND CONCLUTION………………………………………………………….46
BIBLOGRAPHY
APPENDIX
CHAPTER ONE
‘The causes
which determine the economic progress of nations
belong to the study of international trade’(A.
Marsall,1890)
INTRODUCTION
1.1
BACKGROUND
OF THE STUDY
The
impact of trade on the economic performance of a country is a highly discussed
issue in the political debate of both developing and advanced economies. And
for the last two decades, trade liberalisation has been a prominent component
of policy advice to developing countries. Economic growth has been the most
important claim that springs from it, advocates of trade liberalisation state
several chains like higher foreign direct investment (FDI) through which trade
promotes the growth of income per capita. In general, they back up their
hypothesis by referring to the high growth rates of South Asian countries like
the Tiger states and China, which aggressively implement outward oriented
strategies.
On the other hand, sceptics doubt that trade
liberalisation promotes long and sustainable growth. They assume that there are
economic situations in which things get even worse if a country liberalises
trade. They often refer to the negative growth rates of some countries in
Eastern Europe and Africa, which followed the advices of the World Bank and the
International Monetary Funds to open up their markets, Stiglitz (2002)
The Nigerian main trade policy
instrument shifted remarkably away from tariffs to quantitative import
restrictions, particularly import prohibition and import licensing from the mid
1970s. This gave rise to the Nigerian customs legislature establishing an
import prohibition list for trade item and an absolute import prohibition list
for non trade items, Oyejide (1975). The customs legislation empowered the
government to modify this list at its discretion by adding or subtracting items
through customs and excise notices and government announcement. And over the
years there have been several modifications on this list targeted to protect existing
domestic industries and reducing the country’s dependence on imports.
There are three international organisations
that have expressed views on Nigerian’s import prohibition policy, these are
the World Trade Organisation, the World Bank and the International Monetary
Funds. They have advisory role with respect to trade and other policy matters
in Nigeria and had advised a more liberal trade policy regime in Nigeria which
was initiated in the 1980s. The World Bank and the International Monetary Funds
did support this via its lending programme
Prior to the introduction of the
structural administration programme (SAP) in 1986 in Nigeria, imports were
subjected to quantitative controls implemented through a combination of ban on
agricultural and some manufactured goods and a licensing system. But under the
SAP, import and export licensing was abolished, price and distribution control
on agricultural exports was removed and the prohibited list of imports was
reduced.
This issues of whether trade
liberalisation would lead to economic growth has become a debate for both
pro-traders and protectionists. This has led to a growing change in the trend
of world trade. Mostly, African countries have become more careful in embarking
in liberalisation of policies.
1.2 STATEMENT OF
PROBLEM
Trade reforms, even if beneficial for a country
overall, may negatively affect some industries or some jobs and many
commentators worry about negative effects on the environment. For developing
countries the first possible effect of trade liberalisation is the reduction in
revenue accrued to tariffs which is a major source of income in most developing
countries. It is also perceived to deteriorate primary export, lead to
excessive dependency and will be detrimental to less developed countries (LDCs)
industrialisation. But to most international organisation like IMF it is the
condition for granting aid to LDCs. However, it should not be viewed as
flooding the market with imported goods rather; it should be understood as the procedure
of removal of import licenses, rationalisation of export control exchange rate
and provision of revenue.
The extent to which trade liberalisation affects
the economy remain unclear and forms part of the problem which the researcher
intend to study considering the following questions
a) What are the problems facing
trade liberalisation policies in Nigeria?
b) What policy instrument rather
than trade liberalisation affects economic growth?
1.3 OBJECTIVE OF THE STUDY
This state of discussion proves that the
influence of trade liberalisation on the income per capita cannot simply be
captured by intuition. Due to these reasons, it is necessary to use econometric
approaches to get aware of the overall influence of trade liberalisation on
economic growth and development in Nigeria. The specific objectives are:
a)
To find the relationship between trade liberalisation
and macroeconomic variables in Nigeria.
b)
To examine the trends of trade liberalisation in developing
Nigeria
1.4 STATEMENT OF
HYPOTHESIS
In carrying out this study, the
following hypotheses would be tested.
a)
Trade liberalisation has no significant relationship with the
economic growth in Nigeria.
b)
Trade liberalisation has no significant relationship on
macroeconomic variables in Nigeria.
c)
Trade liberalisation has no impact on trend in Nigerian
economic growth.
1.5 SIGNIFICANCE OF THE
STUDY
This
study shall act as a basis for understanding the rationale for trade
liberalisation and its significance on Nigerian economic growth. It would also
show the direction of policy flow that would be beneficial to the achievement
of a rapid economic growth. Also, it will add to the stock of knowledge on
international trade policy and its impact on LDCs. At the individuals’ level, it
will help them to understand the way the government formulates policies and
programs also, to know how to respond to certain trade policies of the
government. For governments, it will help them to be more responsible and
responsive to trade policy needs of the people since they would be aware of the
extent of intervention that is needed to leverage the trade and commercial
sector for rapid advancement. For other researchers on international trade
policy it will pose a challenge for further research in area of trade policies
regimes.
1.6 SCOPE AND LIMITATION OF THE STUDY
The
scope of this study covers the Nigeria economy and will only review the impact
of liberal trade policy on Nigerian economy.
This study shall cover a period of 39 years which is, 1970-2009.
CHAPTER TWO
LITERATURE REVIEW
2.1 THEORETICAL LITERATURE REVIEW
Many
theoretical models and theories support that international trade enhances
economic growth. They suggest several chains through which higher trade shares
positively influence income per capita. For example, the mercantilist theories
are made possible only in the face of a liberal trade though to a certain
degree. Also, the Ricardian trade theory and the Heckscher-Ohlin model both
predict that trade promote the specialization of a country so that it can
realize trading gains. In Ricardo’s opinion, even when one country has absolute
advantage in the production of two goods against another country, it might
still be more beneficial to both countries if each of them specialized in the
production of only one of the goods. With this, both countries can enjoy the
benefits of comparative advantage and enhance the process of exchange between
them. While Heckscher-Ohlin model, depicts that trade arises from differences
in comparative cost which in turn arises from inter-country differences in
relative factor endowment. As a result, real income per capita rises then the
standard of living would increase. Though a rise in per capita income is not
necessarily an increase in welfare, but it is a key factor that determines
increased welfare.
Trade
has acted as an important engine of growth for countries at different stages of
development, not only by contributing to a more efficient allocation of
resources within countries, but also by transmitting growth from one part of
the world to another. Not all countries, however, necessarily share equally in
the growth of trade or its benefits. This will depend on the production and
demand characteristics of the goods that a country produces and trades, the
domestic economic policies pursued, and the trading regime it adopts. For example,
taking the developing countries as a whole, the volume of exports has grown
slower than for developed countries since 1950 – 5 percent per annum compared
to 8 percent – because developing countries still largely produce and export
primary commodities and low value-added manufactured goods with a relatively
low income elasticity of demand in world markets. The discrepancy in rates of
growth of exports has been even wider in value terms because the terms of trade
of developing countries has deteriorated vis-à-vis developed countries causing
the developing countries’ share of the total value of world trade to have
fallen from 30 percent in 1965 to 20 percent today, Thirlwall (2000).
To
further illuminate trade liberalisation and its impact on economic growth in
Nigeria, we would analyse other theories that encapsulates trade liberalisation
policies.
2.2 THE THEORY OF CUSTOMS UNIONS AND FREE TRADE
AREAS
There
have been several attempts for over five decades to promote trade via the
creation of unilateral, bilateral and multilateral trade agreements in several
forms with the most dominants being in form of customs unions and free trade
areas.
The
theory of customs unions dated as far back as the pioneering work of Viner in
1950 which shows that customs unions can cause trade creation. The theory does
this as it liberates trade between members of the union and as external tariffs
are unified on imported goods from the rest of the world.
In free
trade areas, there are no common external tariffs but trade barriers are
brought down within the areas, yet this is not without the incorporation of
domestic content restriction (i.e., the restrictions that defines the quality
to qualify for the zero tariffs between the countries) into the trade agreement
to avoid complications. These theories show how the removal of trade barriers
could be favourable and lead to an increase in welfare for nations.
2.3
REVIEW OF NIGERIA’S TRADE POLICIES
Nigeria’s
trade policies could be analysed under two broad trade regimes, that is, the
period before the introduction of the Structural Adjustment Programme (SAP),
and the period after its adoption. Throughout these regimes, trade policies
exhibited identical characteristics of being short-term in nature (operational
within each fiscal year and reviewed thereafter), and directed at meeting
specific objectives such as, ensuring balance of payments viability and export
promotion. They were also meant to complement other policy initiatives, such
as, industrialisation policy, employment creation and self-sufficiency
policies, etc. The trade policies implemented under the two regimes were as
follows:
2.3.1 PRE-SAP TRADE POLICIES
At
independence, Nigeria’s economy was in many respects, rural and relatively
purely agrarian with narrow industrial base. In an effort to modernize the
economy, the early political leaders adopted development planning strategy as a
move for securing a steady and rapid growth of the economy. Emphasis was placed
on accelerated development of the economy through expansion in the nation’s
industrial base. The idea was for the country to be able to at least produce
some of her consumables locally and in effect reduce dependence on external
sources for the supply of such items. To be able to finance the imports
necessary for the implementing of the industrialisation programme, exports of
cash crops which were then the main source of foreign exchange had to be
enhanced. Thus, farmers were encouraged to expand their production of cash
crops with guaranteed external markets by the Marketing Boards.
The
export items consisted of cocoa, palm produce, rubber, groundnut, ginger, and
some solid minerals, coal and tin. The insatiable urge to quicken the pace of
development gave rise to heightened demand for imports, which in turn exerted
pressures on the balance of payments. Consequently, the trade policies had to
be restrictive in order to moderate the demand pressures. Exchange control
measures were then introduced to adjust the demand for foreign exchange to the
available supply so as to maximise the use of reserves by ensuring that
essential imports were accorded priority over other imports in the use of
foreign exchange resources. Also, in order to give effect to the import
substitution industrialisation policy, trade barriers in the form of imports
licensing was put in place to complement imports tariffs in the control of
import, as well as protect domestic industries that were set up to produce
import substitutes.
The
customs tariff structure was deliberately discriminatory, biased in favour of
capital goods and raw materials, Analogbe (2000). Items considered as luxury
goods were either put on import prohibition list or had very high import
tariffs placed on them.
The
second National Development Plan (1970-74) came on the heels of the termination
of Nigeria’s civil war. The major strategy of the plan was to secure economic
growth through the replacement of destroyed assets and restoration of the
productive capacity of the country, as well as ensure equitable distribution of
the fruits of development. It was also envisaged that by the end of the plan
period, Nigeria would have been able to produce its own goods and services,
finance its development, rely on its own labour, as well as strive for the best
terms for its exports. Plan was designed to incorporate and enhance the
priority areas of the 1962 - 68 plans. That is, enhance agricultural and
industrial production, as well as develop high level and intermediate level
manpower. Additional inputs were therefore required for the execution of the
plan. To moderate the pressures, restrictive trade policies were retained and
strengthened. Exchange control measures became stringent with the introduction
of foreign exchange budgeting in 1971/72 to relate aggregate foreign exchange
expenditure, by category, to income. Similarly, import licensing was
intensified and increasing number of non-essential items were placed under ban,
while some finished consumer items considered not too essential were placed
under specific license so as to keep their importation within specified quota.
Mid-way into the execution of the second development plan the external reserves
position of the country witnessed dramatic change for the better, following
increases in the international price for crude oil. CBN (1979), “the sudden and
unexpected increase in the prices of crude petroleum in 1973 coupled with the
country’s low absorptive capacity, and the existence of various production
bottlenecks in the economy had by 1974 led to a situation whereby the country
was faced with surfeit of funds for which it had no immediate investment outlet
internally. In the circumstance, it was thought that the exchange control regulations
needed further liberalisation”. Consequently, the restrictions on import
payments were removed in 1974. The boom from the crude oil export earnings
spilled into the Third National Development Plan (1975- 80).
The
design of the Third National Development Plan was very ambitious, predicated on
enhanced earnings from the oil sector of the economy. Trade policies were
accordingly relaxed. By the time the Fourth National Development Plan (1981
-85) came up, the economy had started experiencing declines in foreign exchange
earnings which reached its nadir by the oil shock of the early 1980s. Oil price
fell precipitously, but the demand for imports maintained the upward direction.
The external reserves level which could finance about 24 months of imports in
1974, could only support 1.8 months by the end of 1978, and less than one month
in the early 1980s. This was a reflection of the fact that import demand had
become price inelastic, and the resultant effect manifested in balance of
payments deficits. Concerted efforts were then made to control the import trend
through imposition of stricter trade restrictions. The mounting level of
controls administered by innumerable persons further created administrative
bottlenecks.
2.3.2 TRADE
POLICIES DURING SAP
The
grandeur of the misalignment in the economy ushered in by the culture of
controls made it imperative for government to take urgent and drastic actions
to ameliorate the situation. Thus, in July, 1986, the Structural Adjustment
Programme (SAP) was introduced to tackle the problem of imbalances in the
economy and thereby pave the way for stable growth and development. The main
elements of the programme include:
a)
Restructure and diversify the productive base of the economy so as to reduce
the dependence on the oil sector and on imports;
b)
Achieve fiscal and balance of payments viability over time;
c) Lay
the basis for sustainable, non-inflationary growth; and
d) The
Diminishing of the dominance of unproductive investments in the public sector,
improve the sector’s efficiency and intensify the growth potential of the
private sector.
A number
of strategies were enunciated to achieve the broad objectives of the SAP.
Specific to international trade, the primary focus was on liberalization of
trade and the pricing system, with emphasis on the use of “appropriate price
mechanism for the allocation of foreign exchange”. The Second-tier Foreign
Exchange Market (SFEM) was then introduced, under which the exchange rate of
the naira was to be determined by the market forces of demand and supply. The
price determination mechanism provided the means for ultimate allocation of
foreign exchange to end-users as against the former use of administrative
discretion. The application of import and export licensing were consequently
abolished. To encourage export activities, the policy which required exporters
to surrender their export proceeds to the Central Bank of Nigeria, was
abolished. Consequently, exporters were allowed to retain 100 percent of their
export earnings in their domiciliary accounts from which they could freely draw
to meet all their eligible foreign exchange transactions. Furthermore, under
the revised duty scheme, exporters as well as producers could import raw
materials and intermediate products free from import duty and other indirect
taxes and charges. The Export Incentive and Miscellaneous Provisions Decree of 1986
were promulgated to encourage exports.
Through
it, the CBN could provide refinancing and rediscounting facilities to banks to
encourage them to provide export financing to their customers. Also, the
Nigerian Export Credit Guarantee and Insurance Corporation came on stream in
1988, and was subsequently renamed Nigerian Export-Import Bank, to provide
credit and risk bearing facilities to banks, so as to encourage them to support
exports.
2.4 EMPIRICAL LITERATURES
Sachs
and Warner (1995) made comparative analysis between countries with open economy
and those with closed economy. They constructed a dummy for liberalisation on
protective measures which includes tariff, non-tariff barrier and the role of
the state in the economy. Their evidence showed liberal economies grow faster
on the average of 1.5% than their close counterparts.
Vamvakidis
(1999) estimated the relationship between trade and growth by correlating a
time series data over a period of time. He discovered that trade liberalisation
impacted positively on economic growth. In his discovery, trade impacted
negatively because of restrictions but at more liberal policies growth rate
increased. His results, based on a forty-year panel for over one hundred
countries, are more convincing than those of purely cross-section studies. He
concluded that multilateral liberalisations over the period 1950–89 were
associated with increases in rates of growth, while discriminatory regional
trading agreements were not.
Rodrik
(1998) examined the link between trade liberalisation and income growth. His
objective was to examining the
correlation between trade and economic growth. He found out that economic
growth could be explained by a few fundamental factors: human resources,
demographic and fiscal policies in Africa and that trade have a quantitatively
large and robust, though only moderately statistically significant, positive
effect on economic growth
Baro and Sala-Martins 1995 estimated the impact of
trade protection on growth. Using tariff on capital goods and intermediate good
as measure of protection, their result indicated negative impact between trade
liberalisation and growth. Countries with low tariffs according to them grow
faster than those with high tariffs.
Andersen
and Babula (2008) reviewed the most cited empirical analyses of the
relationship between international trade and economic growth and more recent
empirical analyses of the link between trade and productivity growth. They
conclude that there is a positive relationship between international trade and
economic growth. There are, however, two caveats as they found out. First, is
concerned about the way problems of measurement error and endogeneity are
handled in much of the empirical literature. The second caveat relates to the
ability of developing countries to gain productivity growth through trade
liberalisation. To do so, it may very well be necessary to invest in, e.g.,
education facilities, to ensure property rights and to build up institutions.
In other work, Vamvakidis (1998) has tried to
estimate the effect on growth of the size and liberalisation of neighbouring
countries, and finds that countries which have neighbours with large liberal
economies experience faster growth. Liberalisation matters more than size.
Being near a developed country also has a positive spill-over effect. In both
respects, sub-Saharan Africa is at a disadvantage, consisting as it does of
mainly small and highly protected economies, relatively remote from the
industrialised economies of Europe and North America.
Nwafor
et al (2005) using the computable general equilibrium model, they found that
poverty was relatively low in the urban areas in the 1980s but grew gradually
to make urban poverty a fact in Nigeria. By 1996 over half of the urban
dwellers were poor .Comparatively high level of poverty is new to the urban
area. The rural dwellers experienced high level of poverty as high as 50% as
far as 1985.during the structural adjustment programme (SAP) the level of
poverty dropped faster in the rural area than in the urban areas. This gives
support to the argument that trade liberalisation policies alone will not
improve welfare as their measurement showed an overall increase in poverty
(living below 2/3 of the mean monthly household expenditure) between 1980 and 1996;
from 28.2% of the population in 1980 to 70% of the population in 2001 and these
were the period of structural adjustment programmes in Nigeria. Though this
result is valid but it has been because all through the reviewed period the
general experience of regional trade agreements in developing countries of
which Nigeria is one has been disappointing because they have been highly inward-looking
and protectionist.
Establishing
an empirical link between liberal trade and growth has not been easy as it
faces at least four difficulties;
First, there is the definition of
‘liberalisation’. In the context of policy advice, it is most directly
associated with a liberal trade regime (low tariffs, very few non-tariff
barriers etc.) but in fact that is rarely the concept used in empirical work.
Thus, for example, Dollar’s (1992) results rely heavily on the volatility of
the real exchange rate, while Sachs and Warner (1995) combine high tariff and
non-tariff measures with high black market exchange rate, socialism and the
monopolisation of exports to identify non-liberal economies. Pritchett (1996)
shows the trade indicators are only poorly correlated with other indicators of
liberalisation, while Hanson and Harrison (1999) and Rodriguez and Rodrik
(2001) show that most of Sachs and Warner’s explanatory power comes from the
non-trade components of their measure.
Second,
once one comes inside the boundary of near autarchy, measuring trade stances
across countries is difficult. For example, even aggregating tariffs correctly
is complex – see Anderson and Neary (1996), whose measure depends on imports
being separable from domestic goods and services and on an assumed elasticity.
Then one needs to measure and aggregate quantitative restrictions and make
allowances for the effectiveness and predictability of enforcement and
collection. Such measurement problems are less significant for panel data
measuring changes in trade policy for a single country, although even here
Anderson (1998) shows that different measures point in different directions.
Third,
causation is extremely difficult to establish. Does trade liberalisation result
in, or from, economic growth? Frankel and Romer (1999) address this problem by
examining the effects of the component of liberalisation that is independent of
economic growth. This is the part of bilateral trade flows that is explained by
the genuinely exogenous variables: population, land area, borders and
distances. This component appears to explain a significant proportion of the
differences in income levels and growth performance between countries, and from
this the authors cautiously suggest a general relationship running from
increased trade to increased growth. The problem, however, as Rodriguez and
Rodrik (2001) observe, is that such geographical variables could have effects
on growth in their own right and that this alone could explain the significance
of the instrumental estimate of trade constructed out of them. For example,
geography may influence health, endowments or institutions, any one of which
could affect growth.
The
fourth complication is that for liberal trade policies to have a long-lived
effect on growth almost certainly requires their combination with other good
policies such as those that encourage investment, allow effective conflict
resolution and promote human capital accumulation. Unfortunately the linear
regression model, which is standard to this literature, is not well equipped to
identify the necessity of variables rather than their additives in the growth
process. Hints of the importance of these policies, however, can be found in
exercises identifying the structural relationships through which liberalisation
effects growth. Thus, for example, Taylor (1998) and Wacziarg (2001) both find
that investment is a key link and thus imply that poor investment policies
could undermine the benefits of trade liberalisation.
So far,
the past works reviewed indicated that trade liberalisation relates positively
with the growth in productivity, therefore our effort will focus on using
models to analyse the impact of trade liberalisation on the Nigerian economy.
CHAPTER
THREE
METHODOLOGY
3.1 ANALYTICAL
FRAMEWORK
In chapter two, we have seen that the
impact of trade on income per capita is widely discussed in theoretical models
and empirical studies. Despite the strong theoretical foundation, there is not
much clarifying empirical evidence for the impact of trade on income. Because
of the high interest in trade, this seems to be astounding especially if we
take into account that income and trade data are easily available for most
countries of the world, Osterfeld (2007).This is basically the reason why this
study will used ordinary least square (OLS) estimators. It is pertinent to note
that the major area of divergence of this work from previous work is in the
introduction of regime of government proxy by a dummy variable, as well as the
period before and after the liberalisation policy in Nigeria also using a proxy
(dummy variable) and exchange rate.
The research will include an
evaluation that would take into cognizance economic/theoretical a priori tests,
statistical test of significance and econometrics or second order tests. We shall employ computer software packages
like: Microsoft word, Microsoft excel, E-views and Stata 10.
3.2 MODEL SPECIFICATION
We will employ the single equation technique of
econometric simulation for this study. This has a plausible theoretical
explanatory, estimating and forecasting ability, Gujarati (2006). Using the
ordinary least square (OLS) method which is the best linear unbiased estimator
especially for testing specific hypotheses in order to get an estimate for the
trade effect has been the tradition for works on trade liberalisation and trade
openness . But, there have been very little studies which got rid of the
causality problem between trade and income, Osterfeld (2007). As a result of
this basic difficulty, it is necessary to find an appropriate variable which is
correlated with trade as highly as possible and which is at the same time
uncorrelated with income or government policies which aim to raise income.
Hence, the model is specified as follows:
The functional form of
the model is specified as;
RGDP= F (RGDP, TROP, EXR, REGIM,
BFSAP)…………………………...……………. (1)
The
mathematical form of the model is specified as:
RGDPt
= β0 + β1TROPt + β2EXRt
+ β3REGIMt + β4BFSAPIt………………..……………..
(2)
This
econometric form of the model is specified as:
RGDPt=
β0 + β1TROPt + β2EXRt +
β3REGIMt + β4BFSAPt + µt…………………………..
(3)
For
estimation purpose model 3 is re-specified as:
Ln
(RGDPt) = β0 + β1ln (TROPt)
+ β2 ln (EXRt) + β3 (REGIMt) + β4
( BFSAPt) +µt….……(4)
Where:
RGDP=
Economic growth proxy by Real Gross Domestic Product
TROP=Trade
Liberalisation
EXR
= Exchange rate
REGIM=
Regim1 if military regime 0 if otherwise (civilian regime)
BFSAP=Before
the structural adjustment programme 0 if before 1 if otherwise (after).
t
= time from 1970-2009
β0=
Intercept Term.
β1,
β2, β3, β4, are the relative slope
coefficients and partial elasticity of the parameters.
µt
= stochastic error term
Guajarati
(2009) defines µt as a random variable that has well defined
probabilistic properties. The stochastic error term represents other variables
affecting the dependent variable but not explicitly taken into account by the
above model.
3.3 EXPLANATION OF VARIABLES THAT
ENTERED THE MODEL
The
choice of variables we have chosen for the model was based on the advice from
the work of, Osterfeld (2007). The growth rates of the variables were adopted
to eliminate the effects of trend and irregular movements. This is because most
macro-economic time series follow an upward trend as the years go by.
Following
these, the variables below were chosen for inclusion. It is however noted that
this is not an exhaustive list of variables.
TABLE 3.1
VARIABLE DEFINITION TABLE
|
VARIABLES
|
DEFINITIONS
|
A priori sign
|
|
RGDP
|
Gross Domestic
Product adjusted at current basic prices. It is the money value of goods and
services produced in an economy during a period of time.
|
Dependent
variable
|
|
TROP
|
The ratio of
total trade (exports + imports) to GDP is the standard measure used in much
of the ‘new’ growth theory literature for evaluating the degree of trade
liberalisation/trade openness in an economy.
|
+
|
|
EXR
|
Exchange rate
is regarded as the value of one country’s currency in terms of another
currency. Here we took the value of naira with respect to the US dollar. The
nature of the relationship is determined by the imports and exports
elasticity.
|
+/-
|
|
REGIM
|
The régime is
widely acknowledged as the type of government obtainable in a country over a
period of time that when a country is politically unstable its economic
growth is hindered. Political risk is usually measured by the probability of
a change of government, as well as political violence as measured by the sum
of frequency of political assassinations, violent riots and politically
motivated strikes.
|
-
|
|
BFSAP
|
Before the
introduction of the Structural Adjustment Programme (SAP) and Stabilization
programme (SP) of the World Bank and the IMF in early 1980s The SAP measures
included amongst others cuts in government expenditure, removal of subsidies,
liberalization of the economy, privatization of government parastatals, etc.
(an integral part of trade liberalization policies).
|
+
|
3.4
NATURE AND SOURCES OF DATA
The
data are annual time series data gotten from various secondary data sources as
shown in table 3.3.2 below:
Table
3.2 TABLE FOR VARIABLES AND
THEIR SOURCES
|
RGDP
|
Central Bank
Of Nigeria (CBN) Statistical Bulletin 2009 Edition.
|
|
TROP
|
Central Bank
Of Nigeria (CBN) Statistical Bulletin 2009 Edition.
|
|
Exchange Rate
(EXR)
|
Central Bank Of Nigeria (CBN) Statistical
Bulletin 2009 Edition.
|
|
REGIME
|
Assigned the
value of 1 for military and 0 otherwise(civilians)
|
|
BFSAP
|
Before the
structural adjustment programme 0 if before 1 if otherwise (after).
|
3.5 DATA DESCRIPTION AND
TRANSFORMATION
The
obtained data were transformed into logarithm to evaluate growth rates. The
following are the transformed data; RGDP, Trade Liberalisation/Trade openness
(TROP), and exchange rate.
3.6 ESTIMATION
PROCEDURE
3.6.1 UNIT ROOT TEST
The
first step of the estimation process is to examine if our time series possesses
the properties of the time series data. We look at patterns and trends in the
data and test whether the time series variables are stationary (time invariant)
i.e. constant mean, constant variance and by extension constant covariance.
This will test the order of integration of the
individual series under consideration. The procedure adopted the Phillip-Perron
(PP) due to Phillips (1987). The test relies on rejecting a null hypothesis of
unit root (the series are non-stationary) in favor of the alternative
hypothesis of stationarity. The tests are conducted for each of the time series
variables. The general form of Phillip-Perron (PP) test is estimated by the
following regression:
Where ; Y is a time series, t is a linear time trend, D is the first difference
operator, β1 is the constant, n is the optimum number of lags in the
dependent variable, Σ is the summation sign, and εt is a pure white
noise error term.
3.6.2
TEST
OF COINTEGRATION
Econometrically
speaking, two variables will be cointegrated if they have a long term relationship
between them. As Granger notes “A test for co-integration can be thought of as
a pre-test to avoid spurious regressions situations” (Granger, 1986:226) as
cited in Gujarati and sangeetha (2007:841). The test that will be employed here
is the two-step residual based Engle-Granger test. The procedure will be as
follows:
First, we estimate our regression
in equation (4), and obtain the residuals, and use the ADF test to test whether
this residual is stationary at level form and if it is we then conclude that
the variables are cointegrated.
3.7 EVALUATION
TECHNIQUES
3.7.1 TEST BASED ON ECONOMIC
CRITERIA
This
has to do with the sign expectation set by economic theory. It looks at the
signs and sizes of parameters of economic relationships. According to Koutsoyiannis
(1979), the parameters in a given model are expected to have signs and sizes
that conform to economic theory. If they did they are accepted, if otherwise
they are rejected. The a priori signs are shown in table 3.3.1 above.
3.7.2
TEST
BASED ON STATISTICAL CRITERIA
a) The
Co-Efficient of Determination Test (R2 and 
): This is used to measure the goodness of fit
of a regression equation. It gives the proportion or amount of total variations
in the regressand explained by all the explanatory variables jointly.
): This is used to measure the goodness of fit
of a regression equation. It gives the proportion or amount of total variations
in the regressand explained by all the explanatory variables jointly.
In
this study would be used for this evaluation since it
adjusts for degrees of freedom associated with the sums of squares entering
into R2 (unadjusted). R2 are overall measure of how the chosen model fits a
given set of data.
would be used for this evaluation since it
adjusts for degrees of freedom associated with the sums of squares entering
into R2 (unadjusted). R2 are overall measure of how the chosen model fits a
given set of data.
b) The
Student t-test: This is used to test for individual significance of the
variables used in the model. It involves comparing the absolute value of the
estimated t-statistic with the absolute value of its tabulated value at a
chosen level of significance.
c) The
F-test: This is used to test for the joint significance of the variables used
in the model. It involves testing significance of the regression results as
against individual significance of the regressors. This test tells us whether
or not there is a strong relationship between the regressand and the
regressors.
3.7.3
TEST
BASED ON ECONOMETRIC CRITERIA
1. Normality
Test: This study will carry out a normality test to check if the residual, a
proxy for stochastic error term follows a normal distribution or not.
Symbolically, whether µt ~ N (0, δ2). The normality test
that would be used in this study is Jarque-Bera (JB) test of normality
2. Multicollinearity
Test: This is one of the assumptions that must hold before we can make use of
OLS estimation technique. It shows the linear relationship between two or more
explanatory variables. In this study, the collinearity of the variables used in
the model would be performed. The essence of this is to see if there is high
collinearity among the variables or not. The correlation matrix table would be
used for this test.
3. Heteroscedasticity
Test: One of the assumptions of the random variable µt is that its
probability distribution should be constant over all observations of Xi,
that is, the variance of each disturbance term is the same for all values of
the explanatory variables. The aim of this test is to see whether the error
variance of each observation is constant or not. Non-constant variance can
cause estimated model to yield a biased result. White’s general
heteroscedaticity test would be adopted for this purpose.
- Autocorrelation Test: Another most useful assumption about the random variable µt is that there is no serial autocorrelation entering the Population Regression Function (PRF). Gujarati (2009:413). The aim of this test is to see whether the errors correspond to different observations are serially correlated or not. Uncorrelated errors are desirable, symbolically, E(ui,uj)=0. Nevertheless, if it exists, Newey-West HAC (heteroscedasticity- and autocorrelation-consistent) Standard Error would be used to correct it.
5. Granger
Causality test: This test is used to examine the causal behavior among
variables. It tells whether there is a causal relationship among variable.
CHAPTER FOUR
PRESENTATION AND DISCUSSION OF RESULTS
This
chapter presents the regression results based on the objectives and hypothesis
stated in chapter one above. Its evaluation is based on findings and the model
framework set in it and the previous chapter. The regression results shall be
subjected to economic, statistical and econometric tests aforementioned in the
previous chapter.
4.1 PRESENTATION AND ANALYSIS OF THE REGRESSION
RESULTS:
The
result of the model presented in chapter 3 is presented in the table below:
Table 4.
REGRESSION RESULT TABLE
|
VARIABLE
|
MODEL 1
|
|
CONSTANT
|
10.09969
(0.1512987)
[66.75]
|
|
LOG(TROP)
|
2.571913
(0.1993157)
[12.90]
|
|
LOG(EXR)
|
-.2085518
(0.776254)
[-2.69]
|
|
REGIM
|
-0.1105451
(0.1811974)
[-0.61]
|
|
BFSAP
|
0.2821251
(0.3569083)
[0.79]
|
|
R squared
|
0.9493
|
|
Adj R squared
|
0.9436
|
|
F(4, 35)
|
164.00
|
|
Prob > F
|
0.0000
|
|
Durbin Watson
|
1.038649
|
In the
table above, the topmost value in each cell of the right column is the
regression coefficient. The values in the parenthesis (***) are the standard
errors while the t-values are given by the values enclosed in the second
parenthesis, [***].
4.1
.1
EVALUATION BASED ON ECONOMIC CRITERIA:
This
section is concerned with the evaluation of the regression results based on a
priori expectations and the magnitude of our estimated coefficients.
As the
result shows, the sign of the TROP to GDP ratio conforms to a priori
expectation. If the ratio TROP to GDP increases by a unit, say, the growth rate
of the economy is increased by 2.57% on the average holding all other variables
constant. Above the degree of liberalisation, further liberalisation of trade
will actuate output growth rate. This confirms to a priori expectation. As the
degree of liberalisation increase above its present level by a percentage
point, the mean of the real growth rate of the economy increases by 2.57%
ceteris paribus. This shows that the net impact of the trade liberalisation
levels is positive to the economy.
The above result also shows
that exchange rate does not follow a priori expectation in that a percentage
increase in its ratio to GDP will reduce the rate of growth of the GDP by 20%
on the average holding other variables constant.
Also, it is clear that the
environment is better and favourable for growth when there is a democracy. The
result shows a dwindling growth rate of 11% during military regime. This
equally confirms to a priori expectation.
The era before the
introduction of the structural adjustment programme shows that the growth rate
of the economy was at a slower pace but, the introduction of the liberal
policies increased the ratio of GDP growth rate by about 28% as other variables
are held constant. Cumulatively the impact of the regime and the structural
adjusted programme are statistically insignificant but these are positive
stance which could stimulate increase in the rate of growth of the economy
confirming the a priori reasoning of most researchers.
4.2 EVALUATION BASED ON STATISTICAL
CRITERIA
(FIRST
ORDER TEST)
This sub
chapter resorts to the R2, t – test and the F- test used to
determine the statistical robustness of the model. The tests are performed as
follows:
4.2.1.
COEFFICIENT
OF DETERMINATION (R2 and The
Adjusted R2 (
)
will be used for this test. This is because it has been adjusted for the
degrees of freedom. The value of the R2
from our regression result is 0.9493 while the adjusted is 0.9436. It entails
that the 94% of the variations in the dependent variable is accounted for by
the independent variables.
)
will be used for this test. This is because it has been adjusted for the
degrees of freedom. The value of the R2
from our regression result is 0.9493 while the adjusted is 0.9436. It entails
that the 94% of the variations in the dependent variable is accounted for by
the independent variables.
4.2.2.
T-
TEST:
Through this test we shall determine the
variables that affect growth significantly. Since the magnitude of effect is
not certain, we adopt a 2-tailed test.
H0: β1 = β2 = β3
= β4 = 0
Decision rule: reject H0 if the t –
statistic of individual variable is greater than the critical value. i.e reject
if |t cal|> |ttab| at n-k degrees of freedom and 5%
level of significance where n is the number of observations and k = number of
parameters including the intercept term. n-k = 40-5=35.
The result of the above test is presented in table 4.2 below
Table 4.2. THE T-VALUE TABLE
SUMMARY
|
Variables
|
t-values
|
conclusion
|
|
Constant
|
66.75
|
Statistically Significant
|
|
LOG(TROP)
|
12.90
|
Statistically Significant
|
|
LOG(EXR)
|
-2.69
|
Statistically Significant
|
|
REGIM
|
-0.61
|
Statistically insignificant
|
|
BFSAP
|
0.79
|
Statistically insignificant
|
4.2.3
THE F-TEST:
The F-test is used to measure the
overall significance of the variables used in the model.
Hypothesis Testing:
H0: β0 = β1
= β2 = β3 = β4 = 0
H1: β0
≠ β1 ≠ β2 ≠ β3 ≠ β4 ≠ 0
At α = 5% with k-1 (numerator) and n-k (denominator) degrees of
freedom.
Where k = number of
regressors used in the regression and n = number of observations.
Decision Rule:
Reject H0 if
Fcal > F0.05, Accept otherwise.
From the regression results,
F = 164 From the F-table, F0.05 = 2.69 at 4/35 degrees of freedom.
Thus, since F-value = 164> F0.05 = 2.69, we reject H0 and conclude that
the variables are jointly statistically significant different from zero at 5%
level of significance.
4.3.
EVALUATION BASED ON
ECONOMETRIC CRITERIA
(SECOND ORDER TEST):
This
subsection deals with post mortem tests of the regression results which are:
4.3.1
NORMALITY
TEST: The normality test conducted here is
Jarque-Bera (JB) normality test.
Hypothesis Testing:
Ho: δ1=0 (the error term follows a normal
distribution)
H1:
δ1
The
level of significance is 5% and the degree of freedom is 2.
The JBcal
is given as;
……………………………………………… (1)
Where n = no of observations,
s= Skewness =-0.5273389 and k = the Kurtosis =4.488532
Decision Rule:
Reject
H0 if JBcal
> JB0.05 (2) df, accept otherwise.
From the statistic given above JBcal
= 5.547
While
from the Chi-square table JBtab = 5.992
Therefore, since JBcal
< JBtab, we do not reject H0 and
conclude that the error term follows
normal distribution at 5% level of significance.
4.3.2. RESULT FOR UNIT ROOT TESTS:
Table 4.3 THE PHILIP-PERRON UNIT ROOT TABLE
|
Variable
|
Philip-Perron unit root Test Value
|
Order of integration
|
|
LOG(RGDP)
|
-5.740
[-3.662]
|
l(1)
|
|
LOG(TROP)
|
-11.13
[-3.655]
|
I(0)
|
|
LOG(EXR)
|
-5.036
[-3.655]
|
I(1)
|
|
REGIM
|
-6.053
[-3.662]
|
l(1)
|
|
BFSAP
|
-6.166
[-3.662]
|
l(1)
|
Note:
the figure in parenthesis represent phillips-perron critical value at 1%.
From
table 4.1 above, all the variables are stationary at 1% phillips-perron
critical value. The log(trop) variable is stationary at level form. But, the
other variables are stationary at 1st difference.
Ho: δ=1
(the variables are non-stationary)
H1: δ<1 are="" span="" stationary="" the="" variables="">
Decision
Rule:
Reject H0
If |τcal| > |τtab|
4.3.3. RESULT FOR COINTEGRATION TEST:
The
literature thus reviewed indicates a long run relationship between the
variables under consideration. Via the Augmented Engel Granger’s approach we
shall seek to find out if such long run relationship exists in the Nigerian
context. It involves generating the residuals from regression and then
performing stationary test on it.
Hypothesis
Testing:
Ho: δ=0
(the variables are not cointegrated)
H1: δ<0 are="" cointegrated="" span="" the="" variables="">
Decision
Rule: reject H0 If |τcal| > |τtab|
Table 4.4 THE T-VALUE TABLE FOR RESIDUALS
|
VARIABLE
|
τ –
calculated value
|
τ-
tabulated value
|
Order
of integration
|
|
Residuals
|
-4.206
|
-3.655
|
l(0)
|
Note***
the variables are cointegrated at 1% level of significance.
Conclusion:
since |τcal| > |τtab|, we reject H0 and
conclude that the variables may be cointegrated in the long run.
4.3.4 TEST FOR MULTICOLLINEARITY
In
carrying out this test, a simple rule of thumb is used to search for high pair
wise or zero order correlation between any two regressors. If the correlation
coefficient is in excess of 0.8 then multicollinearity is a serious problem
(Gujarati and Sangeetha 2007: 367). Following this rule, there is high
multicollinearity between TROP and EXR, between TROP and BFSAP and between EXR
and BFSAP. These variables are core to the study and thus dropping them would
amount to specification bias.
See
correlation matrix in appendix C2 for the details.
4.3.5 TEST FOR HETEROSCEDASTICITY
The white General Heteroscedasticity test detection approach is adopted
as stated in chapter 3 above. The test which follows a chi square distribution
is conducted as follows;
1.
Generate the
residuals
2.
Square the
residuals.
3.
Square the
independent variables.
4.
Regress the
residuals on the variables and their squares.
5.
Obtain the R2
6.
Multiply the R2
by n (the no of observations).
The 6th item above
is the 
cal.
cal.
H0: α1= α 2= α
3 … α k = 0
H1: α1 ≠ α2
≠ α3… αk ≠ 0
Decision
Rule:
Reject H0 if 
cal >tab at 5% level of significance.
cal >tab at 5% level of significance.
R2 from auxiliary
regression = 0.6014, n =40
n.R2 = 40* 0.6014=
24.056, tab at 5% = 12.5916
tab at 5% = 12.5916
Since cal >tab at 5%, we reject the null hypothesis
and conclude that at 5% level of
significance there is heteroscedasticity. We will adopt Newey-West HAC (heteroscedasticity- and autocorrelation-consistent)
standard errors to correct this.
cal >tab at 5%, we reject the null hypothesis
and conclude that at 5% level of
significance there is heteroscedasticity. We will adopt Newey-West HAC (heteroscedasticity- and autocorrelation-consistent)
standard errors to correct this.
4.3.6.
TEST FOR AUTOCORRELATION
Established
lower limit dL and upper limit dU of durbin Watson based
on 5% level of significance and k-degrees of freedom.
Where:
k=number of explanatory variables excluding the constant.
Table 4.5 DURBIN WATSON D-TEST DECISION RULES
TABLE
|
NULL
HYPOTHESIS
|
DECISION
RULE
|
CONDITION
(IF)
|
|
No
positive autocorrelation
|
No
Decision
|
dL
≤ d ≤ dU
|
|
No
negative autocorrelation
|
Reject
|
4 - dL
< d < 4
|
|
No
negative autocorrelation
|
No
Decision
|
4 - dU
≤ d ≤ 4 - dL
|
|
No
autocorrelation, positive or negative
|
Do not
reject
|
dU
< d < 4 - dU
|
Hypothesis
testing:
a) Ho:
ρ = 0 (no autocorrelation) versus H1: ρ > 0,
Decision rule: Reject H0 at α level if d < dU, that is, there is statistically
significant positive autocorrelation.
b) H0:
ρ = 0 versus H1: ρ < 0.
Decision rule:
Reject H0 at α level
if the estimated (4 − d)
< dU, that
is, there is statistically significant evidence of negative autocorrelation.
c) H0:
ρ = 0 versus H1: ρ ≠ 0.
Decision
rule: Reject H0 at 2α level
if d < dU or (4 − d) <
dU, that is, there is statistically significant evidence of
autocorrelation.
Since
Durbin Watson d-statistic = 1.038649 which is lower than dL that is
D-stat< dL We therefore conclude that there is presence of
positive auto-correlation. . We will also adopt Newey-West HAC (heteroscedasticity- and autocorrelation-consistent)
standard errors to correct this.
4.3.7. PAIRWISE GRANGER CAUSALITY TEST
4.6 PAIRWISE GRANGER CAUSALITY TESTS TABLE
|
Direction
of causality
|
p-value
|
Decision
|
|
REGIM→LTROP
|
0.31435
|
Do not
reject
|
|
LTROP→ REGIM
|
0.61012
|
Do not
reject
|
|
BFSAP→LTROP
|
0.41776
|
Do not
reject
|
|
LTROP→BFSAP
|
0.20461
|
Do not
reject
|
|
LEXR→LTROP
|
0.20461
|
Do not
reject
|
|
LTROP→ LEXR
|
0.01771
|
We
reject
|
|
BFSAP→ REGIM
|
0.76532
|
Do not
reject
|
|
REGIM →BFSAP
|
0.78034
|
Do not
reject
|
|
LEXR→REGIM
|
0.31241
|
Do not
reject
|
|
REGIM→LEXR
|
0.24875
|
Do not
reject
|
|
LEXR→BFSAP
|
0.79755
|
Do not
reject
|
|
BFSAP→LEXR
|
0.07135
|
Do not
reject
|
This
result suggests that there is independence among the variables as there is no
causality among them and they do not Granger cause each other but for LTROP and
LEXR which shows otherwise.
4.4.
EVALUATION OF RESEARCH HYPOTHESIS:
In chapter one of this study, we stated some hypothesis which would be
evaluated below based on the findings of this work. The hypotheses thus stated
are:
. Trade liberalisation has no significant relationship with
the economic growth in Nigeria.
.Trade liberalisation has no significant relationship on
macroeconomic variables in Nigeria.
. Trade liberalisation has no impact on trend in Nigerian
economic growth.
These hypotheses will be evaluated based on the results presented
above:
The results of this study
show that trade liberalisation conformed to a priori expectation which requires
it to be both positive and statistically significant. This finding is
consistent with what previous studies (such as Adam Smith, 1776,David
Ricardo,1817, A.P. Thirlwall,
2000, etc) found. It also confirms a priori reasoning that trade liberalisation
has a positive relation with macroeconomic variables in Nigeria. Using data from 1970 – 2009, the economy would grow at the rate of
2.57% if the ratio of trop to RGDP rises marginally. Since the t-value of the
trop-RGDP variable is in excess of 2, we therefore conclude that the impact of
a trade liberalisation policy on the economy is significant following the
simple rule of thumb that if the absolute value of any of the variables in
table 4.2 is > 2 then the variable corresponding to that value is
statistically significant.
4.5 CHAPTER SUMMARY:
The
doctrine that trade liberalisation enhances welfare and growth has a long and
distinguished ancestory dating back at least to Adam Smith (1723-90) has been
proven a reality in Nigeria. In this chapter,
we evaluated the three hypothesis established in chapter one, showing the joint
impact of trade liberalisation, exchange
rate and other growth variables on economic growth in Nigeria within the period
1970 – 2009. Trade liberalisation as we saw does have notable impact on the
growth of the economy.
CHAPTER FIVE
5.1 SUMMARY RECOMMENDATION AND
CONCLUSION OF THE RESEARCH FINDINGS
The result of this research supports the
hypothesis of the dominant paradigm in literatures of trade liberalisation
theories. The objective of this research was to determine the impact of trade
liberalisation on economic growth in Nigeria and to make policies that will
improve trade environment and aid business executives, policy prescribers and
makers to analyses and project future trends as we examine the effect of trade
liberalisation on economic growth in Nigeria using annual data spanning 1970 to
2009.
In
all specifications, evidence abound that trade liberalisation has systematic
effect on GDP growth. However, there is evidence that liberalisation increases
instability in consumption and investment .The evidence is weak but it is
sensitive to the method of estimation adopted as well as the measure of trade
policy used. In particular, the impact of liberalisation on consumption and
investment volatilities is significant when we use the trade/GDP as a measure
of openness. It is not significant when we measure openness by tariff
/non-tariff barriers or by conventional wisdom. The first measurement is better
and precise as the ratio (trop to RGDP) increases by a unit. The
growth rate of the economy is increased on the average by 2.57% freezing all
other variables. This research also showed that for every one unit of increase
in other ratio of liberalizing policy to RDGP the economy, the economy grows on
an average of .2%. While taking note of
the impact of regime on the economy we discovered that the absence of a free
and democratic institution reduces the growth rate of the RGDP by a ratio of
about 1%. Though this is not statistically significant, yet we know that little
drops of water makes mighty ocean.
At this point, we will show from a policy standpoint
the results of this paper in two important ways.
First,
although deep institutional reasons play a role, to an important extent,
countries have the level of development they choose. Policy convergence to
best-practice standards is not likely to happen automatically unless the
political economy conditions for such a change are present. Identifying and
co-opting potential opponents might be necessary to ensure the political
sustainability of reforms.
Secondly, policies that on average have a liberalizing
effect on markets are not by themselves enough to guarantee their extension to
the economy. They can even worsen the situation. In this sense, understanding
the interrelation between sectorial reforms, and adjusting the timing
accordingly seems of first order importance.
5.2.
RECOMMENDATION AND CONCLUTION
There are static and dynamic gains
derived from trade between countries but there is nothing in the theory of
trade that says that the gains are equitably distributed (like the saying, “a
new wine will burst an old wine bottle” the degree and the direction of burst
may be imprecise). And the gains from trade to an individual country, based on
specialisation, may be affected by welfare losses of unemployment and terms of
trade deterioration. In this case, complete specialisation is not optimal.
Trade liberalisation and export growth
seem to be positively correlated, and exports act as an engine of growth. How
powerful is the engine, however, depends on the production and demand
characteristics of the goods produced and exported. Countries specialising in
the production and export of primary products do not perform as well as
countries specialising in the production and export of manufactured goods. This
raises the issue of whether regional trade agreements and unilateral tariff
reductions by themselves are sufficient to secure structural change in poor
countries.
Orthodox trade theory ignores the contribution
that export growth makes to the demand for output, and particularly in relaxing
a balance of payments constraint on demand by providing the foreign exchange to
pay for the import content of higher levels of consumption, investment and
government expenditure. Most developing countries are constrained in their
growth performance by a shortage of foreign exchange and could therefore grow
faster with more exports.
Export growth can also set up a virtuous
circle of growth through a process of cumulative causation working through the
induced effect of output growth on productivity growth and increased
competitiveness.
The question for Nigeria is not whether to
trade but in what to trade and the terms on which it trades with itself and the
rest of the world. Regional integration may bring some benefits if wisely
designed, but more important is to get right the growth fundamentals of high
levels investment in physical and human capital, good governance, and a
structure of production that gives scope for scale economies and high productivity
which at the same time produces goods, the world demand for which is rising
fast. If this requires elements of protection, countries must not be afraid to
deviate from free trade. There are legitimate economic grounds for protection
if it will raise income and output above what would otherwise be the case. The
classic economic arguments are: the infant-industry argument; the externalities
argument, and the case where the social cost of production is less than the
private cost because of, for example, the unemployment of labour.
It is worth remembering that historically no
country has ever developed on the basis of absolute free trade except the
United Kingdom, which was the first country to industrialise. The United
States, the countries of Europe, Scandinavia, Japan and other successful
countries in South East Asia all adopted various means of protection at one
time or another.
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