The impact of crude oil production on economic growth
in Nigeria
1
ABSTRACT
The paper investigates the impact of crude oil production on
economic growth in Nigeria. Crude oil which is believed to be a
gift of nature to a nation, like Nigeria and others who are blessed,
has become a controversial subject among scholars and
researchers worldwide. Over the years, the issue of whether
crude oil production translate to economic growth or not has
been a burning question to many as well as a global subject of
considerable interest and debate as a bone of contention. The
major objectives of the paper are: To examine the impact of crude
oil production on economic growth in Nigeria, To examine the
impact of crude oil export revenue on economic growth in Nigeria,
etc.
Concerning methodology, secondary sources of data was used for
the study. The research design used for the study was the Quasiexperimental research design. Data was analyzed using E-views
statistical tool. Key findings from the study showed that oil
revenue maintained a positive and statistically significant
relationship with economic growth both in the short run and long
run regression results. Also, white foreign reserve shows a
positive but not statistically significant effect on Nigeria economic
growth. Recommendations for the study include; Government
should be rational in the utilization of foreign reserve generated
from crude oil proceeds by reinvesting it into the economy rather
than using it for uneconomic purposes.
TABLE OF CONTENTS
Title Page -
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i
Approval Page -
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ii
Declaration
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iii
Dedication -
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iv
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Acknowledgement
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Abstract
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Table of Contents
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CHAPTER ONE – INTRODUCTION
1.1
Background of the Study
1.2
Statement of General Problem
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1.3
Objective of the Study -
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1.4
Research Questions
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1.5
Hypothesis -
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1.6
Scope and limitations of the study-
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1.7
Significance of the Study
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1.8
Definition of Terms
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CHAPTER TWO – REVIEW OF RELATED LITERATURE
2.1
Conceptual Review
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2.1.1 Challenges Facing Crude Oil Production and Oil Producing
Communities in Nigeria
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2.1.2 Oil Revenue and Economic Growth in Nigeria2.2
Empirical Review
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2.2.1 Crude Oil Production, Exchange Rate and Economic Growth
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2.2.2 Crude oil Production, Foreign Reserves and Economic
Growth
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CHAPTER THREE – RESEARCH METHODOLOGY
3.1 Introduction
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3.2
Research Design
3.3
Data Collection and Sources
3.4
3.5
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Methodology and Estimation Procedure
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Model Specification -
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CHAPTER FOUR – DATA PRESENTATION AND ANALYSIS
4.0 Introduction
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Data Presentation and Analysis -
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4.2
4.3
Data Analysis Testing Hypothesis
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4.4
4.5
Summary of Findings Discussion of Findings
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CHAPTER FIVE – SUMMARY, CONCLUSION AND
RECOMMENDATION
5.0 Introduction
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5.1
Summary -
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5.2
Conclusion -
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5.3
5.4
Recommendations
Contributions to Knowledge-
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References Appendix -
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4
CHAPTER ONE
INTRODUCTION
1.1. Background to the Study
Crude oil is one among other natural resources endowment
in a nation by nature. Natural resources are often regarded
as free gifts of nature. All over the world, different countries
are endowed differently with different resources, both in
quality and quantity, to some less and others in abundance.
Nigeria is one among these countries that is richly blessed
with vast natural resources, such as: forests, lands, fresh
and
salt
water,
sands,
coal,
Iron-ore,
natural
gas,
aluminum, non- mineral energy source of solar, crude oil
which is our subject matter among others.
Crude oil was first discovered in united state (US) in 1859,
which was sold on a large scale in the 1860s. In Nigeria, the
search for crude oil started within 1905 and 1908 by the
Nigerian Bitumen Corporation (NBC) who on their search
found 16 shallow wells, confirming a line of oil seepage in
the Eastern Dohomey Basin in Okitipupa, Western Region
of Nigeria. The NBC could not go far with its search due to
5
the outbreak of the First World War in 1914 which distorted
their activities.
However, after the war, the Roral/Dutch Company took over
and continued with the search from Ondo State to Abia
State and finally narrows down their search to Niger Delta
Region where they first discovered oil in large commercial
quantity in 1956 at Oloibiri specifically in the present
Bayelsa State. Nigeria oil hit. The international market in
1958 with approximately 5,000 barrels per day. Nigeria
produces about 30% of the total oil production in the Africa
region. As of September 2004, she was ranked the largest
producer in the sub- Saharan Africa, the 5th largest
petroleum exporting country in organization of petroleum
exporting countries (OPEC) and the 5th largest oil exporting
country to the united state of America, amounting to about
8% of USA crude oil imports. Here current production
capacity is over 2 million barrels per day on average.
Although Nigeria for over 30 years has established herself as
a leading producer of crude oil, she is known in energy
circles as a “gas province with only a little pool of oil”. The
oil producing states in Nigeria so far discovered include:
6
(Abia, Akwa Ibom, Bayelsa, Cross River, Delta, Edo, Ondo
and Rivers) state, nine
in number with a common
nomenclature known as the “Niger Delta region”. The
formulation and implementation of the Nigerian oil sector is
under three actors which are:
i.
The ministry of petroleum resources, established in
1972 with four departments functioning differently.
ii.
The Nigeria national petroleum corporation (NNPC),
established in 1977 under decree No. 33 as government
owned
company
together
with
the
petroleum
inspectorates as its integrate part under six directors.
iii.
The private sector, which comprises of multinational oil
companies, which produces about 98% of the total
production and indigenous companies producing about
2%. The oil sector is categorized into up and down
stream, connected with forward and backward linkages.
Over the past 30 years, different people have commence
differently in the activities of oil production in Nigeria, to
some it has made a Variety of contributions to the Nigerian
economy, such of which include: the creation of employment
7
opportunities, the supply of energy to industries, supporting
the transportation system, source of revenue generation to
the government, etc. while to others, oil production does
more harms than good to the environment and the economy
as
a
whole,
which
call
for
environmental-resource
accounting.
In terms of output production and product contribution, oil
witnessed steady progress throughout the period under
review. Crude oil production increased from 1.9 million
barrels in 1958 to 152.4 barrels in 1966. Production
increased from 395.7 million barrels in 1970 to 660.1 and
845.5 million barrels in 1975 and 1979 respectively. The
increase in production witnessed during this period was
precipitated by Middle East crisis and the 1973/74 oil
embargo which caused a sharp reduction in world oil
supply. The increased oil prices that the crisis generated
helped to boost local oil production in the country. However,
this was short-lived as the early 80s witnessed a glut in the
international crude oil marketing to over-supply, which
culminated in sharp drop in prices and central reduction in
the
production
quotas
by
8
OPEC
member
countries.
Consequently, oil production in Nigeria dropped from 0. 1
million barrels in 1980 to 535.9 and 383.3 million barrels in
‘1986 and 1987 respectively. The situation improved in the
90s as crude oil output rose from 383.3 million barrels in
1987 to 711.3, 742.3 and 772.9 million barrels in 1992,
1996 and 1998 respectively. The trend continued between
the year 2000 and 2009. The cumulative crude oil
production
for
the
country
increased
from
20,575881mi11ion barrels in 2000 to 27,052, 0677 million
barrels in the 2009. In general, crude oil production
witnessed appreciable increase over the period under study.
Finally, the production of oil in Nigeria is not totally free
from challenges; rather it has been plagued by various
problems which undermined its optimal development over
the years. In general term, from 1990s till date, public
control and bureaucracy, poor funding of investments,
communal
disturbances,
petroleum
products,
smuggling
fraudulent
and
diversion
domestic
of
marketing
practices, and product adulteration, oil theft among others
has in identified as the challenges facing crude oil
production in Nigeria.
9
1.2. Statement of Problem
Crude oil which is believed to be a gift of nature to a nation,
like Nigeria and others who are blessed, has become a
controversial subject among scholars and researchers
worldwide. Over the years, the issue of whether crude oil
production translate to economic growth or not has been a
burning question to many as well as a global subject of
considerable interest and debate as a bone of contention.
While some strongly opine that crude oil production is the
life-wire of a producing country’s economy, maintaining that
its export has a positive relationship with economic growths,
spill-over effect on foreign reserve as well as determining the
rate at which her currency is exchanged for in international
market etc, to others, the reverses is the case, as the argued
that it has done more harms than good.
Affirming their argument, they point at environmental
degradation, pollutions, deprivation of means of livelihood,
over dependence on oil revenue, socio economic conflict
associated with crude oil production activities among
others. To be specific, the words of Juan Perez Pablo
Alfonso, fully support the latter when he says “I call
10
petroleum the evil’s excrement. It brings trouble…waste,
corruption, consumption, our public services fall apart and
debt, a debt we shall have for years” (the economist, May
22, 2003).
Research-wise,
this
contradictory
argument
“for
and
against” the subject matter, has create a gap which keep
both end from reaching a consensus. Objectively, these
hypothesize arguments is what necessitate the conception of
this study as an attempt to ascertain which assertion.
1.3 Objective of the Study
The objective of this research work is sub-divided into two,
the main and specific.
Main Objective
To examine the impact of crude oil production on economic
growth in Nigeria.
Specific Objective
i.
To examine the impact of crude oil export revenue on
economic growth in Nigeria.
11
ii.
To examine the transmission channel through which
exchange rate is affected by crude oil export and thus
economic growth in Nigeria.
iii.
To examine the relationship between Nigerian foreign
reserve and her economic growth through crude oil
export.
1.4 Research Hypothesis
i.
Ho: There is no significant relationship between oil
revenue and economic growth in Nigeria.
ii.
Ho: There is no significant relationship between
exchange rate and economic growth in Nigeria.
iii.
Ho: There is no significant relationship between
Nigerian foreign reserve and her economic growth.
1.5 Scope and Limitation of the Study
This research work focus on the impact of crude oil
production on economic growth in Nigeria, with time series
date from 1980-2011, which cover a period of thirty-two (32)
years to examine the relative impacts of oil revenue,
12
exchange rate and foreign reserve as the regressors on the
regressed (economic growth represented by G-DP). This
choice of time space is believed to be long enough to capture
and explain the long-run relationship that exist between the
variables noted above in the growth of Nigerian economy.
On its limitation, source of gathering data was the major
constraint encountered in the cause of conducting this
study, together with the difficulty in accessing the internet
in Amassoma due to poor network services. Also financial
constrain and time factor as well as academic stress among
others, as well contributed to the limitation of this work.
1.6 Significance of the Study
 It will provide useful information to government and
policy makers.
 It will also provide an econometric basis upon which to
examine the impact of crude oil production on
economic growth in Nigeria.
 It will as well add to existing literature and knowledge.
1.7 DEFINITION OF TERMS
13
Crude Oil: is a naturally occurring, unrefined petroleum product
composed of hydrocarbon deposits and other organic materials.
Production: the action of making or manufacturing from
components or raw materials, or the process of being so
manufactured.
Economic Growth (GDP): an increase in the amount of goods
and services produced per head of the population over a period of
time.
Revenue: The income generated from sale of goods or services, or
any other use of capital or assets, associated with the main
operations of an organization before any costs or expenses are
deducted.
14
CHAPTER TWO
REVIEW OF RELATED LITERATURE
This chapter is design to review a number of related
literatures in two dimensions; first, by looking at theoretical
consideration or conceptualization on the subject matter
from the point of different scholars and researchers.
Secondly, by bringing to light some empirical findings or
research work previously done by others in relation to the
topic at hand.
2.1 Conceptual Review
Obadan (1987) defined crude petroleum as a mixture of
hydrocarbon oil obtained below the earth surface. He opined
that oils in Nigeria, generally occurs at depths below 1,500
meters. According to him, it is the raw material around
which a chain of commercial activities known as the
petroleum industries revolves. It is a major source of energy
in the world marketed today and has infect become the
bedrock of man’s progress and civilization.
15
Iyoha (2000), states that the “white products” namely
Premium Motor Spirit (P.M.S), Dual Purpose Kerosene
(D.P.K), Automatic Gas Oil (A.G.O) and Aviation Tobin
Kerosene (A.T.K) arc sub-products from the bulk of crude
petroleum. The major types of products concerned at depot,
according to him are the first three mentioned. The other
A.T.K is being transported through pipeline from the Misimi
depot to Murtala Mohamed Airport Lagos. Others include:
Liquefied Petroleum Gas (L.RG) Law Pour Fuel Oil (L.P.F.O)
and High Pour Fuel Oil (L.P.F.O).
Anyanwu (1997) noted that the presence and activities of oil
companies in Nigeria has led to government involvement in
oil industry as well as the birth of NNPC. He explained that
the role of government in the oil industry as gradually
progressed from regulation to direct involvement in oil
exploration.
Oladele
(1991)
posits
that
provision
of
employment
opportunity is one of the positive sides of oil industry.
Therefore, the presence and activities of the oil industries
have create more opportunities for employment in Nigeria.
16
Olopoenia (1991) opined that the crude oil boom led to some
structural changes such as the decline of non oil tradable
goods sector, the expansion of non traded goods production,
and the ‘de-agricuituralization of the economy.
Maaji (2008) affirms that the enormous increase in the oil
revenue created unprecedented and unplanned wealth for
Nigeria that, our leaders even once remarked that money
was not the nation’s problem but how to spend it. “The false
sense of economic self-sufficiency generated by oil boom of
the 1970’s led to the neglect of the agricultural sector since
the nation had access to cheap money to import all sorts of
things including foodstuffs, raw material and manufactured
goods”.
Maaji (2008), also underline that of all natural resources, oil
has been found to have the highest risk of civil conflict
because of the large rents it offers and the shocks to which
the government and the national economy are exposed to.
According to collier and Hoeffler (2002), 23 per cent of states
that dependent on oil exports have experienced civil war in
any five-year period. Crude petroleum has remained the
17
world oil market and us declining share in GDP (Anyanwu,
1997).
Anyanwu (1997), Oil a very versatile and flexible, nonreproductive,
depleting,
natural
(hydrocarbon)
is
a
fundamental input into modern economic activity, providing
about 50% of the total energy demand in the world.
Anyanwu (1997) further explained that petroleum or crude
oil is an oily, bituminous liquid consisting of a mixture of
many substances, mainly the clement of carbon and
hydrogen known as hydrocarbons. It also contains very
small amounts of non-hydrocarbon elements, chief amongst
which are sulphur (about 0.2 to 0.6% in weight), them
nitrogen and oxygen.
Doscher (2009) sees crude oil as a naturally occurring oily,
bituminous liquid composed of various organic chemicals. It
is found in large quantities below the surface of the earth
and is used as a fuel and as raw material in the chemical
industry.
Yakubu (2009), view that high technical cost of production,
due to low level of domestic technological development is a
18
factor that influences crude oil production in Nigeria
negatively.
To Osuntogun, Edordu and Oramah (1998), the oil boom
rather than contributing positively to the living standard
has afflicted the Nigerian economy with the so-called ‘Dutch
disease’.
2.1.1 Challenges
Facing
Crude
Oil
Production
and
Oil
Producing Communities in Nigeria
Odularu (2008) noted public control and bureaucracy as
one of the challenges facing crude oil production in Nigeria,
maintaining that the Nigerian oil sector lacks autonomy
because
the
Nigerian
National
Petroleum
Corporation
(NNPC) is control by the ministry of petroleum resources
which as a result, decision is always bureaucratic and
delayed.
Therefore,
characterized
by
the
operation
inefficiency,
of
the
especially
NNPC
in
is
refining
operations, distribution and marketing.
Odularu (2008), further noted poor funding of investment as
a problem, stressing that insufficiency of funds constrained
adequate maintenance and efficient refinery operations by
19
the Nigerian National Petroleum Corporation (NNPC) as well
as discouraging increase in the level of investment by the oil
companies due to frequent oil delays in the payment of cash
by the Federal Government in relation to Joint Venture (JV)
agreement.
Oil
and
Gas
Business
(2007),
pinpointed
product
adulteration and fraudulent domestic marking practice as a
major problem facing the Nigeria oil industry, noting that
price differential of some product and proliferation of illegal
sales outlets where some adulterations occur create space
for some marketers to hoard petroleum products in other to
sell in the black market at higher prices.
Odularu
(2008),
observe
the
effect
of
communal
disturbances in crude oil production stressing that there
has been frequent communal disturbances which disrupts
crude oil production due to restriction imposed by crisis and
production disruptions caused by host communities as they
clamor for higher slake in oil operations to compensate their
degrade environment.
Oil and Gas business (2007), holds that smuggling and
diversion of petroleum products by producers across the
20
borders in quest for foreign exchange to lake undue
advantage of the lower domestic prices vis-à-vis neighboring
countries
prices,
remains
a
big
problem
facing
oil
production in Nigeria.
OPCE annual report (1983), assert that the suddenness of
economic difficulties of the 1980s “bust years” has an
adverse effect on class relation and the oil workers who
understood the dynamics of the industry. As if to capture
the labour crisis, writing on oil workers during this period
covered so many interrelated issues, notably working
conditions, strikes, and state labour relation. To be sure,
labour issues were not new in the 1980s, since the leftoriented scholars had made a point of exposing labour
relations in the colonial era. What was new after 1980 was
the focus on oil workers, unions, and class conflict.
Al-moncef
(2006),
oil
sector
can
also
contribute
to
development in the oil rich economies through provision of
intermediate Inputs to the economy. These intermediate
inputs include; crude oil, gas and liquid feed stocks, as well
as oil and gas into the refining, petrochemical and electricity
and energy industries respectively.
21
Ramirez (2006), oil activity often leads to inflow of foreign
resources such as FDI and portfolio investment. Indeed, the
bulk of FD1 into majority of the countries that export oil are
concentrated in the oil sector.
Nwezeaku (2010) maintained that despite the fact that
crude oil has been the source of Nigeria economy, the
economy is faced with high rate of unemployment, wide
spread oil spillage, increasing poor standard of living as a
result of decreasing gross domestic product, per capita
income and high rate of inflation which led to the effect of
economic development.
Adeyemi (2004) in his own contribution viewed the oil
exploration as a damaging instrument rather than for it to
be a contributing factor to the welfare of the residents.
Whereas activities such as flaring of natural gas and seismic
surveys constitute great damages to the environment, more
far reaching environmental destruction result from oil
spillage. Soil, plants, animals and water resources are ad
vastly affected, usually because of the toxicity of oil. This
view was collaborated by Kinako and Odu (1996) who
argued that the resultant environmental problem arising
22
from oil spillage is well above the benefits that are derived
by the resident especially in the Niger Delta areas.
Biodu (2004), the greatest challenge is when Nigeria
generates more revenue from crude oil sales than it
budgeted, like now.
Such excesses have always been monetized, creating market
distortions and inflationary pressure.
The Economist (May 22, 2003), Alfonso in his view calls
petroleum “the evil of excrement. Brings trouble…waste,
corruption, consumption, our public services fall apart and
debt, a debt we shall have for years”.
Gary and Karl (2003), argued that apart from the loss in the
oil production, there have been accompanying financial
losses to oil companies to begin to redirect their attention to
offshore oil activities.
Karl
(1997) maintained
that oil
companies
including
domestic ones, come to pray a disproportion in the decision
making of oil export countries, a role that would permit
them
to
something
manipulate
23
legal
in
their
favor.
Scany (2004), people are worried about the link between the
excessive residuals generated as a result of depletion of
natural resources with oil exploration been more intense in
meeting energy demand, create
more
danger to
the
environment and ecosystem.
Adeniji (2005), advice the petroleum operators to take
precaution by using up-to-date equipment to prevent
pollution of land and water by oil any other fluid or
substance.
Nwilo and Bedejo (2005), point out that the people of the
Niger Delta were the oil is been produce are protesting
against their inability to participate in the affair of the oil
found in their communities and government, inability to
enforce the environmental regulations in the Niger Delta
region that has led to environmental damages and brought
severe hardship on the in inhabitants.
Atakpu (2007) maintained that oil producing communities
has been stigmatized with conflict. The reasons for the crisis
in the region stem from environment pollution, human right
abuses and the decade-long neglect by the multinational oil
24
companies, couple with government’s attitude with regard to
impoverishment which plagues the region.
Olaja and Abdulsalami (2008), noted that aside from
cleaning up of the oil and chemical spills which the oil
companies has taking the initiative to manage their wastes
adequately
friendly
by
establishing
landfill sites
and
permanent
cleaning
up
environmental
existing
sites
containing chemical waste and sludge, the oil industry in
the Niger Delta region has joined in drawing up spill
response contingency plans. Pointing that the most recent
action taking is the creation of the Niger Delta Ministry by
President Umaru Musa Yar’ Adua to address the issue of
negligence of the oil producing region which has escalated
crisis in the region.
Perrow (1970), the oil industry in the oil producing region is
dominated mainly by the government and the oil companies,
since the constitution empowers the federal government to
negotiate terms of the oil exploration in the country with the
oil companies, ignoring the natives whose land, water and
forest are being exploited.
25
Eweje (2006) argued that the underlying issue in oil
producing communities is the present of abject poverty as
feeling of marginalization and exclusion from political
decisions and benefits, which accrue from oil exploration.
Eweje further stress that the oil companies in the region are
after their bottom-line and nothing else (i.e. only looking for
what “they can get from the region and not what they can
plough back”).
Carter (2007) asserts that in many countries, especially
developing countries like Nigeria; pollution is a serious
concern and has left the communities with enormous
societal cost. According to Carter, oil as natural resource for
energy, offers particular benefit but poses particular
problems where its presence is discovered.
Okoro, Robson, Jarosz, and Laurue (1999), concluded that
the impact of oil development on the environment is
immense,
maintaining
that
oil
exploration
entails
destruction of the vegetation within operating vicinity.
Igho (2002) identified wastes from petroleum drilling to
include
cuttings,
mud/chemical,
26
oil
spills,
cement
slurry/dust, condemned pipes, filters, and machinery part
which
are
indiscriminately
(lumped
on
land
and
surrounding river.
UNEP (1999), opined that the region where people made
living from productive mangrove forest by farming and
fishing prior to oil production, the mangroves’ and the
marine lives that depend on them has been destroyed due to
oil leaks and spillages thereby making survival very difficult
for the natives.
Salie, Liqinan and Adullahi (2007), identify that since the
inception oil exploitation in Nigeria and Niger Delta Region
specifically, the social life of the people has been that of
misery, deprivation and poverty, stressing that the incidence
of violence, destruction and conflict by the youths of the
region one byproducts of inflicted poverty as a result of oil
production by the oil industry.
2.1.2 Oil Revenue and Economic Growth in Nigeria
Azaike and Shagari (2007) relate oil revenue and Nigerian
economic growth to the total oil revenue generated into the
27
federation account from 2000 to 2009 which amounted to
N34.2 trillion while non-oil was N7.3 trillion, representing
82.36%
and
17.64%
respectively.
According
to
CBN
statistical Bulletin (2009), the mean value of oil revenue for
the ten years period was N3.42 trillion compare to non-oil
revenue at N732.2 billion, while average crude oil and
condensates
production
for
this
period
as
well
was
832,866,752.1 barrels from 2000 to 2009.
Binda and Wiknbergen (2008) noted similarly that Nigeria
gain an extra $390 in oil related fiscal revenue between
1971 and 2005 or 4.5 times Gross Domestic Product (GDP)
of 2005.
Ekaette (2009) argued that irrespective of Nigeria’s huge oil
wealth, the country has remained one of the poorest in the
world. In particular, the Niger Delta which produces the oil
wealth that accounts for the bulk of Nigeria’s earnings have
also emerged as one of the most environmentally degraded
regions in the world, evidenced from the World Wildlife
Fund report released in 2006.
28
Yakub (2008) traced the problem of Nigerian economy to
failure of successive governments to use oil revenue and
excess crude oil income effectively in the development of
other sector of the economy.
Bawa and Mohammed (2007) assert that “Nigeria with all its
oil wealth has performed poorly, with gross domestic
product (GDP), per capita income today not higher than at
independence in 1960”, which means that an average
Nigerian was better off before independence in 1960.
Odularu (2008), oil revenue which supposed to be a source
of finance for economic development has turned out to be a
bone of contention between many interest groups, precisely
the government and oil and gas companies. To him, if many
have hoped that oil would turn Nigeria into an industrial
power and a prosperous country based on a large middle
class, they were to be disappointed when a formally rich
country became a debtor nation by the 1980s.
Bakare and Fawehinmi (2008), holds that the revenue
generated from the sales of crude oil, has the capacity of
increasing real wage which in turn will 1ead to increase in
29
savings when properly utilized. The positive and tremendous
increase in gross domestic product (GDP) and consequently
increase in supply of foreign currencies; the exchange rate
will appreciate in favour of the local currency.
Etikerentse (1985), noted that the offshore oil revenue
Decree No. 9 of 1971 abrogated the right of regions/states
to own minerals and the title to rents and other revenue
derive from petroleum, except the federal government.
Usman (2009) states that huge inflow of oil revenue in
Nigeria are more often associated with expansion in the level
of government spending while periods of dwindling oil
revenue arc usually accompanied by budget deficits. There
is no gain saying that Nigeria relies so much on revenue
from oil exports but, it equally massively imports refined
petroleum and other related products.
2.2 Empirical Review
Odularu (2005), investigated the relationship between ‘crude
oil and the Nigerian economic performance’, the study
reveals that there exist a positive relationship between
30
crude oil sector and Nigerian economic performance,
maintaining that crude oils consumption and export
contribute to the improvement of Nigerian economy.
Orubu, and Willian (2004), conducted a study on “the
Nigeria
oil
industry:
environmental
management
strategies
and
need
diseconomies,
for
community
involvement” they found that oil industry’s activities in
Nigeria have to a large extent contributed to the lingering
crisis in the Niger Delta area, which denotes inverse
relationship with economic growth.
Oyefusi (2007) carried out a study similarly on “oil
dependence”
and
concluded
that
government
over
dependence on oil revenue leads to civil conflict in the
country (Nigeria) especially in the Niger Delta region, which
influence economic growth.
Still in line with the above argument, a study carried out by
Bakare (2008), on an econometric study of the contribution
of oil sector to the standard of living in Nigeria (1975-2008)
confirmed that there exists a significant and negative
relationship between oil revenues and standard of living in
31
Nigeria. His study confirms also, the existence of growth
without development and “Dutch disease” in Nigeria.
Emmanuel (2004) also conducted a study on oil revenue
and economic growth in Nigeria. The study traced the
revenue that was generated from the sales of crude oil in
Nigeria between January 2001 and March 2004 in billions
of US dollars. He found lots of inconsistencies and
discrepancies
in
the
reports
published
by
different
government agenesis such as Central Bank of Nigeria (CBN),
Nigerian
National
Petroleum
Corporation
(NNPC)
and
Accountant General of the Federation. Whereas the CBN
reported US $21.9 billion and the Accountant General of the
Federation reported US $ 20.5 billion. From the above
values, he concluded that the inconsistencies discovered as
evidence in the cumulative discrepancies among the three
series suggest that the oil revenues must have been
mismanaged. And rather for the government to utilize these
revenues to cater for the welfare of the people, the major
part of it was stolen. According to Emmanuel, the people of
Nigeria remains poorer that the international poverty
average despite the huge revenue generated from oil, has
32
estimates shows that more that 70% of Nigeria lived in
abject poverty. The country is still characterized by
infrastructure inadequacy, low level of income, high level of
poverty,
high
mortality
rate,
poor
accommodation,
malnutrition and high level of water-borne diseases after
years of oil record.
Baghebo and Atima (2013), researched on the impact of
petroleum on economic growth of the Nigerian economy,
using data covering a period of 1980-2011. The study found
that oil revenue impacts negatively and significantly on real
Gross Domestic product (GDP), confirming the existence of
the Dutch disease phenomenon in Nigeria.
Akanni (2007) examines if oil exporting countries grows as
their earnings on oil rents increases, using ordinary least
squares regression. The result shows that there is a positive
and
significant
relationship
between
investment
and
economic growth and also on oil rents. In conclusion, he
noted that oil rents in most rich oil developing countries in
Africa do not promote economic growth.
33
Hadi (2009), investigate the impact of income generated
from oil exports on economic growth in Iran using cobdouglas production function. He observed that the economy
of Iran adjusts fast to there is progress in technology in
Iran.
Oil
exports
real
income
through
real
capital
accumulation.
Mohammed and Amirahi (20 1 0), examines if lactors such
as oil rice, world oil supply and demand, production
capacities enhanced export growth in Iran using Error
Correction Version of ARDL. They found that there exist a
direct relationship between oil products, consumption and
oil export revenues.
Offomah (2009) concentrated her study on the impact of oil
revenue on economic growth performance in Nigeria within
the period 1970-2006. A multiple regression analysis was
employed to capture the influence of oil revenue on GDP
and also determine the trend effect, that is, the effect of time
as variable. The results revealed a positive relationship
between the variables.
Akanni (2007). Examines if oil exporting countries grows as
their earnings on oil rents increases, using pc-GIVE10,
34
(ordinary lest squares regression). The result shows that
there is a positive and significant relationship between
investment and economic growth also on oil rents. In
conclusion, he argued that oil rents in most rich oil
developing countries in Africa do not promote economic
growth.
Idowu (2005), using a causality approach examines that
there is a relationship between exports and economic
growth in Nigeria. Also applying Johansens multivariate cointegration technique, the result shows that there is
stationary relationship between exports and Gross Domestic
Product (GDP). Pointing that there is feedback causality
between exports and economic growth.
Odularu (2010) used Harrod-Domar theory and solow’s
theory of economic growth with Ordinary least Square
regression
and
cob-douglas
production
function
were
employed to test the impact of crude oil on Nigeria economic
performance. The result shows that crude oil production
contributed to economic growth, but has no significant
improvement on economy growth of Nigeria.
35
Orubu, Odusola, and Ehwarieme (2004), in their study on
“the impact of oil gas exploration on the environment’ made
five important observations as follows:
i. Every aspect involved in oil and gas operation has
significant negative implication for the environment.
ii. In all cases, all that constitute the environment are
affected in one single operational line.
iii. The effects of the various aspects of oil operations on
the environment are not mutually exclusive, rather
reinforcing.
iv. The environment consequences have economic effects
on the people and the community.
v. Social tension arises as a result of compensation
disagreements
from
damage
claims
by
host
communities.
Ikorukpo (1983), A study on the social-economic and
environment in Nigeria indicated that fishermen in the oil
producing region are experiencing decline in the well-being
which they attribute to oil pollution. In the same study, it
36
was reported that local farmers and fisherman have resolved
to change occupation or take on second occupations in
order to make ends meet. The study concluded that these
things were never heard or thought of in the region before
the discovering of oil.
Chong and Tan (2008), empirical analysis revealed that the
exchange
in
macroeconomic
fundamentals
for
the
developing economics. Exchange rate fluctuation influence
domestic prices through their effects on aggregate supply
and demand. In general, when a currency depreciates it will
result in high import prices if the country is an international
price
taker,
while
lower
import
prices
result
from
depreciation.
Baghebo and Atima (2013) concluded that all in all, while
there are strong theoretical grounds to suspect a broad
correspondence
between
natural
resource
abundance
especially oil and low growth, the nature of the linkage is
neither direct nor simple. Empirical literature has not
provided conclusive answer to whether abundant natural
resource is a curse or blessing. Even among studies that
claimed the curse of natural resources actually exist, there
37
is no recent on what exactly drives the curse of the natural
resources and on how it exactly plays out. This explains
why further research should be focused on the causal link
between natural resource abundance and growth in the
resource rich economies.
2.2.1 Crude Oil Production, Exchange Rate and Economic
Growth
Odularu (2008) points out that in Nigeria, the booming oil
export and the influx of foreign exchange from it created a
surplus of foreign currency thus driving down the naira
price of foreign exchange. The result, of course, was an
extra ordinary increase in import while export declined. Due
to the fact that the high oil income created greater demand
for all goods and services in the economy, this demand
translated into more imports (whose prices were relatively
stable since their prices depend on the entire world market
and not solely on Nigerian demand). Since a good portion of
the oil boom demand was for domestic non tradable goods
(such as utilities, transport, construction, food crops and
staples) which were heavily protected and isolated from
38
external competition, there were significant increases in
their prices leading to domestic inflation, given their limited
supply especially the few years of the boom”.
Al-Mulali (2010), on the study “the impact of oil price on the
exchange rate and economic growth” in Norway with time
series data from 1975-2008, established that the increase in
oil price is the reason behind Norway’s increase in Gross
Domestic product (GDP) and her competitiveness to trade by
its real exchange rate depreciation. Al-Mulali further
express that the oil price in this case is a blessing due to
two reasons. First, Norway uses the floating exchange rate
regime which is good shock absorber, to increase the
freedom
of
the
monetary
authority
and
makes
the
adjustment smoother and less expensive. Secondly, that
Norway has more flexible labour markets, improvements in
monetary policy and smaller share of oil in production.
39
2.2.2 Crude oil Production, Foreign Reserves and Economic
Growth
Dooley (2003), the huge foreign exchange earnings from oil
exports, apart from being used for importing raw material,
intermediate and capital goods for production in the non oil
sectors could equally assist in boosting the foreign reserves
of the oil exporting countries. The accumulation of foreign
reserves can be seen as collateral which the oil producing
economies can use in attracting foreign investment.
Moreover, such holding can be seen as a costly selfinsurance strategy to smooth the vulnerability impacts of
domestic and foreign shocks and to intervene in the foreign
exchange market.
Odularu (2008), one of the important aspects of the oil
industry’s contribution to the Nigeria economy, is noted in
its contribution to foreign reserve. This could not have come
at a more opportune moment because the country is
embarking upon a massive programs of industrialization
and economic development which postulate huge imports of
capital goods and specialized services, involving massive
40
expenditure of foreign exchange, noting that in many
underdeveloped countries especially those that depend
heavily on a narrow range of primary commodities, acute
shortages of foreign exchange, often exacerbated by massive
declines in the world commodity prices, constitute a major
obstacle to effective economic development. But through
crude oil production, Nigeria now has substantial foreign
reserves and is in the healthy position of being able to
finance the foreign exchange cost of her development
programs. He also noted that the contribution of oil to
foreign reserve is not measured by the gross value of crude
oil exports because the practice followed by the oil
companies is to retain the entire proceeds from exports
abroad, and to remit to the producing country only the
amount need to sustain their local operation.
41
CHAPTER THREE
RESEARCH METHODOLOGY
This chapter looks at methodologies which are considered to
be significant in the study. These include research design,
method and sources of data collection, model specification,
analytical technique, and test for stationary (i.e. unit root
and co-integration) as well as specification of a priori
expectation detailed below.
3.1 Research Design
Research
design
is
the
structure
and
strategy
for
investigating the relationship between the variables of the
study. The research design adopted in this work to
investigate and explain the behavioural pattern of both the
dependent and independent variables in the model is the
quasi-experimental research design. The reason for using
the above noted design approach is due to the fact that
economic variables unlike other natural science variables
are unstable in nature as they changes with time. Secondly,
42
the quasi-experimental design combines the theoretical
consideration with empirical observation which enables the
researcher to observe the effect of the explanatory variables
on the dependent variable.
3.2
Data Collection and Sources
The data used in this research work were obtained from
secondary sources particularly from Central Bank of Nigeria
(CBN) publications, (CBN statistical bulletin, CBN Economic
and Financial Review Bulletin). The data in used, covers a
period of thirty-two (32) years, from 1980-2011. This time
series period is believed to be long enough to capture the
long-run
relationship
between
the
dependent
and
independent variables.
3.3 Methodology and Estimation Procedure
The research work makes used of econometric approach in
estimating the relationship between oil revenue, exchange
rate, foreign reserve and Nigerian economic growth. The
dependent variable is real gross domestic product while the
43
independent variables are oil revenue, exchange rate and
foreign reserves.
The Ordinary Least Square (OLS) technique was used in
obtaining
the
numerical
estimates
of
the
variables
(independent) coefficients in the model by running a
multiple regression via e-views. The OLS method was
chosen because it is believe to be the best linear unbiased
estimator, secondly, its computation is fairly simple and
also, many research works in social sciences has adopted it
overtime and obtained proven results.
3.3.1 Stationarity Test
The test for unit root in statistics, tests whether a time
series data is non-stationary using an autoregressive model,
i.e. if any or some of the explanatory variables has the same
order with dependent variable, which may result to cointegration
between
the
dependent
and
independent
variable(s) that have the same order. This was tested for
using the augmented Dicky Fuller test which is a well
known and valid test.
44
3.3.2 Co-Integration Test
This test was conducted to check whether there is evidence
of co-integration between the explanatory variables having
the same order of stationarity with the dependent variable.
The time series data are said to be co-integrated if two or
more series share a common stochastic drift with some of
their linear combination having a lower order of integration.
3.4 Model Specification
Based on the objectives of the study and the tested
hypothesis, econometric method was employed to ascertain
the relationship between-crude oil production and economic
growth in Nigeria. To determine these relationships the
models were specific as follows:Model (1)
Mathematically,
Where;
RGDP = F (ORV, EXR, FR) -
45
-
-
-
-
-
(1)
RGDP = Real Gross Domestic Product
ORV = Oil Revenue
EXR = Exchange Rate
FR =Foreign Reserve
Model 2
Econometrically
Log(RGDP) = aO + a1Log(OVR) + a2 Log(EXR) + a3 Log(FR) + U - (2)
Where:
RGDP = Real Gross Domestic Product
ORV = Oil Revenue
EXR = Exchange Rate
FR = Foreign Reserve
aO = Intercept
a1 = Co-efficient of oil revenue
a2 = Co-efficient of exchange rate
a3 = co-efficient of foreign reserve
46
U = Error term
3.4.1 A Priori Expectation
The expected signs of the co-efficient to the explanatory
variables are: a1>0, a2><0 and a3>0.
47
CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS OF RESULTS
This chapter focuses on data presentation, analysis and
interpretation
of
findings
resulting
from
empirical
investigation which include: the short-run regression result,
unit root, co-integration and granger causality test results,
parsimonious error correction result, generated from the
over-paramatized error correction result.
4.1 Data Presentation
Appendix 1 shows the data employed in this study. With the
help of E-view soft ware, the data were ara1yzed via the
ordinary
least
square
(OLS)
techniques.
obtained are presented and discussed below
48
The
results
4.1.1 Short-Run Regression Model Result
The table below shows the estimated short run model result,
follow by statistical and theoretical analysis considered to
be relevant in this study.
Dependent Variable: LOG(RGDP)
Method: Least Squares
Date: 07/15/13 Time: 00:55
Sample: 1980 – 2011
Included Observations: 32
Variable
C
LOG(ORV)
LOG(FR)
LOG(EXR)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
2.278394
0.929977
0.018382
-0.002558
0.984393
0.982721
0.304578
2.597503
-5.227070
1.020727
Std. Error t-Statistic
0.556558
4.093721
0.043424
21.41612
0.085891
0.214014
0.026672
-0.095912
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
Prob.
0.0003
0.0000
0.8321
0.9243
14.03657
2.317052
0.576692
0.759909
588.6842
0.000000
Source: Author’s Computation with the Use of E-View
The statistical significance of the parameter estimate
obtained from the short-run regression model was verified
as follows:
49
Standard Error Test
For the model, when compare half of each coefficient with
its standard error, it was found that the standard error of
foreign reserve (FR)and Exchange rate (EXR) were greater
than half of the value of their respective co-efficient
exception of oil revenue (ORV) which reverse was the case.
This shows that the estimated values for all the independent
variables
excluding
oil
revenue
are
not
statistically
significance. This is also evidence in their respective
probability values of 0.8321, 0.9243 and 0.000.
Adjusted R-square (R2)
The value of the adjusted R-square (R2) for the model is very
high, pegged at 0.982721. It implies that ORV, FR and EXR,
explained about 98% systematic variations in the growth
rate of Nigerian economy over the observed years while the
remaining
2%
variations
is
accounted
for
by
other
determining variables outside the model, which is taken
care of by the stochastic term. The fitness of ever regression
result is based on its R-square. Thus, the model is adjudged
a good fit.
50
F-Statistic
The entire model is proven to be statistically significant
given its F-statistic with probability value of 0.000000,
which shows overall significance of the model.
S.E of Regression
Given its numerical value of 0.304578, it implies that in
exactly two-third of the time, the explanatory variables
predicts the dependent variable by 30%.
Durbin Watson Stat.
The Durbin Watson statistic with numerical value 1.020727
indicates the present of auto correlation or multi colinearity. While the
explanatory
later explains correlation of the
variables,
the
former
explains
temporal
dependence of successive valuable of a variable. Thus, this
result gives justification for unit root test.
Theoretical Significance of the Parameter Estimate
The theoretical significance of the overall estimate was
evaluated with respect to signs and magnitude of the
variables’ co-efficient. The result shows a positive and
51
statistically significant effect of ORV, positive but not
statistically significant effect of FR while EXR has negative
both
in
sign
and
coefficient
with
numerical
values
0.929977, 0.0 18382 and -0.002558 respectively. This
implies that a unit increase in ORV and FR will lead to
0.929977
and
0.018382
unit’s
increases
in
RUDP
respectively while a unit increase in EXR will lead to
0.002558 unit decreases in RGDP. All the variables used in
this model conform to the theoretical expectation, as
increase in ORV will mean more wealth to the nation’s
economy as well as FR when adequately use, but FR though
positive appear to be insignificant which means that our FR
over the years under observation has not been properly or
adequately used, for the nation’s economy advantage as
should. In the case of EXR, increase in EXR will mean a
leakage to the economy as the foreign currency will
appreciate against the local currency thereby leading to a
decrease in RGDP as more local currency will be exchange
for very little foreign currency especially for a country like
ours that depends mostly on imported goods.
52
4.1.2 Unit Root Test (Augmented Dicky Fuller Test)
Table 2 below shows the summary of the computed
augmented Dicky Fuller unit Root Test for each of the
variable used in the model.
Table 2: Unit Root Test Result (Augmented Dicky Fuller
Test)
Variable
Level
LOG (RGDP)
1st Difference
2nd Difference
Decision
-0.426050 -3.471918
-6.058282
I(1)
LOG (ORV)
-0.357926 -4.572034
-6.384450
I(1)
LOG (FR)
-1.295551 -5.270212
-6.535196
I(1)
LOG (EXR)
-1.588089 -4.110091
-6.579861
I(1)
ECM (-1)
-4.242741 -5.385119
-6.358497
I(0)
Critical Value @ 5%
-2.9627
-2.9705
-29665
Source: Author’s Computation with the Use of E-View
From the above table, it shows that all the variables
(dependent and independent) used in the model were all
integrated at first difference symbolized with 1(1), all at 5%
significance level. Theoretically, a variable is said to be
stationary i.e. has no unit root problem if the test statistics
in absolute terms is greater than the critical value. The next
test in order to establish whether the non-stationary
53
variable could be co-integrated after identi1ring the order of
integration leads to co-integration test.
4.1.3 Johansson Co-Integration Test
The co-integration of two time series data suggests that
there exist a long-run relationship between them. The above
named test was employed in this study to examine this
relationship between all the I(1) variables shown in table 2
above. The result obtained from this test proves the
existence of this relationship as it indicate 1 co-integration
equation(s) at 5% significance level as summarized in table
3 below.
54
Table 3: Johansson Co-integration Test Result
Date: 07/12/13 Time: 12:14
Sample: 1980 2011
Included Observations: 30
Test Assumption: Linear deterministic trend in the data
Series: LOG (EXR) LOG(FR) LOG(ORV) LOG(RGDP)
Lags interval: 1 to 1
Likelihood 5 Percent 1 Percent Hypothesized
Eigenvalue Ratio
Critical
Value
Critical
Value
No. of CE(s)
0.588023
52.55848
47.21
54.46
None*
0.393481
25.95483
29.68
35.65
At most 1
0.229752
10.95426
15.41
20.04
At most 2
0.098865
3.122995
3.76
6.65
At most 3
Source: Author’s computation with the use of E-View
*(**) denotes rejection of the hypothesis at 5% (1%)
significance
level
L.R.
test
indicates
1
co-integrating
equation(s) at 5% significance level.
The test result above, shows one co-integrating equation at
5% significance level, thus there is the probability of longrun relationship existing between the variables used in the
model.
55
4.1.4 Granger Causality Tests
This is a statistical hypothesis test for determining whether
one time series data is useful in predicting or forecasting
another as a measure of direction of causality between
variables. Table 4 below shows the summary of this test.
Table 4: Granger Causality Test Result
Paitwise Granger Causality Tests
Date: 07/12/13 Time: 12:13
Sample: 1980 2011
Lags: 2
Null Hypothesis
LOG(FR) does not Granger Cause LOG(EXR)
LOG(EXR) does not Granger Cause LOG(FR)
LOG(ORV) does not Granger Cause LOG(EXR)
LOG(EXR) does not Granger Cause LOG(ORV)
LOG(RGDP) does not Granger Cause LOG(EXR)
LOG(EXR) does not Granger Cause LOG(RGDP)
LOG(ORV) does not Granger Cause LQG(FR)
LOG(FR) does not Granger Cause LOG(ORV)
LOG(RGDP) does not Granger Cause LOG(FR)
LOG(FR) does not Granger Cause LQG(RGDP)
LOG(RGDP) does not Granger Cause
LOG(ORV)
LOG(ORV) does not Granger Cause LOG(RGDP)
Obs
30
30
30
30
30
30
30
F-Statistic
0.30049
2.19299
0.60059
1.87061
0.63924
3.89155
9.65390
0.01311
8.57131
0.1335
6.17732
0.00051
0.30049
Probability
0.58792
0.14981
0.44485
0.18228
0.43072
0.05848
0.00430
0.90967
0.00671
0.71803
0.01918
0.98210
0.58792
Decision
Accept
Accept
Accept
Accept
Accept
Reject
Reject
Accept
Reject
Accept
Reject
Accept
Source: Author’s computation with the use of E-View
The test results above judging from our decision column
with “Reject” denoting statistically significance and “Accept”
non- statistically significance, shows that there exist a unit
directional causalities between: EXR and RGDP; ORV and
FR; RGDP and FR; RGDP and ORV, depicting that one is
useful in forecasting the other.
56
4.1.5 Parsimonious Error Correction Model Result
The estimation of error correction model (ECM) is made
possible by present of co-integration. FCM is meant to solve
the problem of spurious results associated with estimating
equations that involves time series variables as well as to
adjust the short-run dynamics to the long-run. In view of
this an attempt was made to estimate the over-paramatized
error
correction
(parsimonious)
model
error
from
correction
where
model
a
preferred
was
obtained.
Appendix 2.0 contains the over-paramatized ECM of this
study. The ECM is essential because it establishes a link
between long-run and short- run approaches to economic
modeling. With the ECM, all information associated with the
first differencing variables are save since the modeling
gather
both
the
short-run
dynamics
and
long-run
information through the error correction term. The table
below shows the parsimonious error correction model
result.
57
Table 5: Parsimonious Error Correction Model Result
Dependent Variable: LOG(RGDP)
Method: Least Squares
Date: 07/12/13
Time: 12:09
Sample (adjusted): 1985-2011
Included observations: 27 after adjusting endpoints
Variable
C
LOG(ORV)
LOG(ORV(-2))
LOG(EXR)
LOG(RGDP(-1))
LOG(FR)
ECM(-1)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
1.577999
0.222479
0.126841
-0.028518
0.626486
0.032608
-0.067121
0.976194
0.965052
0.142227
0.404568
18.39909
2.099326
Std. Error t-Statistic
0.721219
2.187960
0.081828
2.718865
0.085192
1.488887
0.125025
-0.228097
0.116951
5.356817
0.052459
-0.621595
0.054610
-2.229091
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob (F-statistic)
Prob.
0.0407
0.0032
0.1521
0.8219
0.0000
0.5412
0.0033
14.62630
2.022019
-0.844377
-0.508420
872.5196
0.000000
Source: Author’s computation with the use of E-View
The above result shows the error correction term. ECM (-1)
is well stated with its variable having the correct a priori
sign as well as being statistically significance. Its numerical
value 0.067121 in absolute term indicates the speed of
adjustment. This means that about 6% of deviation from
RGDP’s long-run in the previous year(s) is corrected in
current year by the ECM. Deducing from the long-run
(parsimonious) result above changes in the current RGDP
were accounted for by the changes in the present and past
two years’ ORV (Lagged twice), present year’s EXR, past
year’s RGDP (lagged once) and present year’s PR with the
58
numerical
values:
0.222479,
0.126841,
-0.028518,
0.626486 and 0.032608 respectively. These values shows
the rate at which each of the variables can induce changes
in RGDP given their respective numerical sizes and signs,
where the positive signs depicts a proportional increase of
the numerical sizes in RGDP and the negative sign a
proportional decrease of 0.28518 in RGDP for every one unit
attempt to increase either. Also, the R-square (R2) 0.976194
and adjusted R2 0.965052 shows that about 96% of
variations in the dependent variable was accounted for by
variations in the explanatory variable which confirms that
the model indeed is reliable for economic forecasting or
prediction given its level of fitness.
The F-Statistic with probability value 0.000000, further give
justification that the entire model is statistically significant.
Concluding with the Durbin Watson Statistic, its value
(2.099326) falls within the determinate region of ≥ 2.00
which implies that there is a negative first order serial
autocorrelation among the explanatory variables in the
model.
59
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
This chapter summarized the entire research work by
drawing conclusions from empirical findings made in the
study. It recommends some policy measures and area for
further studies as well as its contributions to knowledge.
5.1 Summary
The study examines the impact of crude oil production on
economic growth in Nigeria with time series data ranging
from 1980-2011. It noted different views held by different
individuals on crude oil production and its effects on the
economy. Also, the trend of crude oil production was
observed to have witnessed an appreciable increase over the
period under review. Furthermore, some challenges that
undermined production activities over the years were as well
revealed in the cause of the study. Data were analyzed via
econometric assessment to determine the relationship
between economic growth and crude oil production proxied
60
by oil revenue, foreign reserve and exchange rate as its
associate variables.
5.2 Conclusion
In this research work, we have empirically verified and
discussed the impact of crude oil production on economic
growth in Nigeria. From our data analysis in the preceding
chapter, it is observed that oil revenue maintained a positive
and statistically significant relationship with economic
growth both in the short run and long run regression
results, white foreign reserve shows a positive but not
statistically significant effect on Nigeria economic growth.
This indicates a mismatch in the utilization of foreign
reserve from crude oil proceeds on the nation’s economy.
Exchange rate on the other hand which could either be
positive or negative depending on the economic situation in
the economy, maintained a negative relationship with
economic growth both in the short run and long run
regression results, which means that the rate at which naira
was exchanged for in international market was restively
61
high over the years under review, which placed the nation’s
economy at a disadvantageous position.
Drawing
a
conclusion
from
the
above
findings,
the
researcher therefore reject H0 of hypothesis (i) and (iii), and
accept H1, while H0 of hypothesis (ii) was accepted and H1
rejected as stated in chapter one. Thus the study concluded
that there exist positive relationships between oil revenue,
foreign reserve and economic growth in Nigeria respectively,
while there exist a negative relationship between exchange
rate and economic growth in Nigeria during this period.
5.3 Recommendations
Based on the findings of this study, it is inevitable to
provide a set of policy recommendations that would be
applicable to the Nigerian economy.
62
5.3.1 Recommendations for Policy
i.
Government should be rational in the utilization of
foreign reserve generated from crude oil proceeds by
reinvesting it into the economy rather than using it for
uneconomic purposes.
ii.
Government through the monetary authorities should
provide means to reduce and stabilize the high and
fluctuating rate which here currency is exchange for in
the international market to curtail the huge local
currency exchange for few foreign currency.
iii.
Government and policy makers should be sincere and
politically willing to ensure that any policy whether in
form of an act or a bill formulated to reshape the
regulation of the petroleum industry in Nigeria are
fully implemented to the letters, unlike the case of the
petroleum industry bill which has been stuck in the
exclusive and legislative pipeline since 2008 when it
was first introduced till date, with no insight to why it
is yet to win the executive and the legislature approval
of passing it to law, given its under listed objectives
63
which clearly spell-out it expected benefits to the
petroleum sector and the Nigerian economy generally
if finally pass into law. The 2012 PIB objectives:
 Create a conducive business environment for
petroleum operations.
 Enhance exploration and exploitation of petroleum
resources in Nigeria for the benefit of the Nigeria
people.
 Optimize domestic gas supplies, particularly for
power generation and industrial development.
 Establish a progressive fiscal framework that
encourages further investment in the petroleum
industry while optimizing revenues accruing to
the government.
 Establish commercially oriented and profit driven
oil and gas entities.
 Deregulate and liberalize the downstream sector.
 Create efficient and effective regulatory agencies.
64
 Promote
transparency
and
openness
in
the
administration of the petroleum resources of
Nigeria.
 Promote the development of Nigeria content in the
petroleum industry.
 Protect health, safety and the environment in the
course of petroleum and
 Attain such other objectives to promote a viable
and sustainable petroleum industry in Nigeria
(The Petroleum Industry Bill, 2012).
iv.
The Nigerian government should make effort to repair
and maintain the existing refineries in the country,
and also build new ones especially in the oil producing
regions to boost production of refined product for
export, and discourage the exportation of crude at low
cost and importation of finished product at high cost
presently obtained in the country.
v.
Other
than
the
Nigerian
National
Petroleum
Corporation (NNPC), as government agent in the oil
65
sector, government should establish other companies
to fully participate in both upstream and downstream
production activities as well as encouraging private
individuals who are able and willing to compete
squarely with the foreign actors in the sector to
increase supply and cut down the excess profit earn by
the foreign companies.
vi.
Nigerian government should at all cost provide lasting
solution to the existing challenges facing the oil sector
as reviewed in chapter two above, to allow maximum
level of production in the sector.
vii.
Government should establish an institution that will
ensure that the multinational oil companies are
socially responsible to their host community.
viii.
There is an urgent need for Nigeria to move from a
mono-economy system to diversify one, not to solely
depend on oil proceeds.
ix.
Government should do all it takes to train and develop
indigenous specialist in the oil sector to expose them
to the needed technology and techniques in the sector
66
for sustainability should the foreign ones decide to quit
for any reason.
x.
Government should implement policies to adjust the
wide gap of production ratio of 98:2 % between the
multinational oil companies and the indigenous ones
to at least 80:20 %.
5.3.2 Recommendation for Further Studies
In the course of the study, reviews were extensively made on
various literatures and existing works regarding the topic at
hand, it was noted that several works had been done on the
impact of crude oil production and economic growth without
economic development. Knowing that economic growth only
entails sustainable increase in a nation’s gross domestic
product (GDP) or output without structural changes in
social, political, cultural and economic system. Thus, the
researcher recommends that further research should go
beyond economic growth to determining the impact of crude
oil production on economic development by including other
67
variables in the model that would best capture development
indices.
Secondly, how long from now would crude oil production
last in Nigeria, given the fact that crude oil is a nonrenewable or an exhaustible natural resource. This is
another area that should give greater concern to researchers
to research on alternative or close substitute, if eventually it
is exhausted in the near further.
5.4 Contributions to Knowledge
i.
The findings of this study will pave the way for further
research on the subject matter or related issues in
Nigeria economy.
ii.
The study will serve as a good policy tool in the hands
of
government
and
policy
makers
in
providing
solutions to challenging issues in the oil sector.
iii.
It is believed that the findings of this work will
contribute to existing literature as well as quantitative
research knowledge.
68
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71
APPENDIXES
Year
RGDP
ORV
EXR
1980
49,632.32
12,353.30
106.28
1981
47,619.7
8,564.40
110.39
1982
49,069.3
7,814.90
109.86
1983
53,107.4
7,253.00
109.84
1984
59,622.5
8,269.20
113.2
1985
67,908.6
10,923.70
99.90
1986
69,147.0
8,107.30
51.89
1987
105,222.8
19,027.00
14.72
1988
139,085.3
19,831.70
12.97
1989
216,797.5
39,130.50
8.88
1990
267,550.0
71,887.10
7.72
1991
312,139.7
82,666.40
6.34
1992
532,613.8
164,078.10
3.74
1993
683,869.8
162,102.40
2.97
1994
899,863.2
160,196.40
2.96
1995
1,933,211.6
324,547.60
0.74
1996
2,702,719.1
480,783.00
0.78
1997
2,801,972.6
416,811.10
0.81
1998
2,708,430.9
324,311.20
0.81
1999
3,194,015.0
724,422.50
0.20
2000
4,582,127.3
1,591,675.80 0.20
2001
4,725,086.0
1,707,562.80 81.25
2002
6,912,381.3
1,230,851.20 88.94
2003
8,487,031.6
2,074,280.60 100.94
2004
11,411,066.9 3,354,800.00 107.06
2005
14,572,239.1 4,762,400.00 106.57
2006
18,564,594.7 5,287,566.90 105.03
2007
20,657,317.7 4,462,910.00 106.41
2008
24,296,329.3 6,530,630.10 100.31
2009
24,794,238.7 3,191,937.98 121.54
2010
33,984,754.1 5,396,091.05 96.57
2011
37,543,654.7 8,848,615.00 155.57
Source: Central Bank of Nigeria Statistical bulletin
72
FR
54,806.00
56,194.80
12,324.30
7,171.40
5,419.70
11,781.70
18,922.05
62,554.26
72,266.83
43,953.22
40,293.19
48,620.03
33,391.94
58,824.15
95,329.02
32,345.00
25,895.56
73,492.11
93,776.74
63,709.20
91,089,20
123,329.83
103,104.08
91,701.66
144,753.06
291,849.31
449,473.06
544,731.68
701,674.60
536,428.25
448,268.46
390,963.35
OVER-PARAMATIZED ERROR CORRECTION RESULT
Dependent Variable: LOG(RGDP)
Method: Least Squares
Date: 07/12/13 Time: 12:04
Sample(adjusted): 1985 2011
Included observations: 27 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
C
1.028516
0.941754
1.092128
LOG(ORV)
0.250300
0.092955
2.692712
LOG(ORV(-1))
-0.159254
0.115219
-1.382193
LOG(ORV(-2))
0.148308
0.104818
1.414912
LOG(EXR)
0.019257
0.160964
0.119634
LOG(EXR(-1))
-0.153330
0.181058
-0 .846857
LOG(EXR(-2))
0.1 39446
0.1 89037
0.737664
LOG(RGDP(-1))
0.973147
0.246437
3.948860
LOG(RGDP(-2))
-0.247026
0.221132
-1.117098
LOG(FR)
-0.085841
0.087850
-0.977139
LOG(FR(-1))
0.1 54444
0.118242
1.306166
LOG(FR(-2))
-0.069521
0.143461
-0.484596
ECM(-1)
-0.050395
0.116789
-0.431501
R-squared
0.997612
Meandependent var
Adjusted R-squared 0.995565
S.D. dependent var
S.E. of regression
0.134656
Akaike info criterion
Sum squared resid 0.253852
Schwarz criterion
Log likelihood
24.691 02
F-statistic
Durbin-Watson stat 2.484030
Prob(F-statistic)
Source: Author’s computation with the use of E-View
73
Prob.
0.2932
0.0175
0.1 886
0.1790
0.9065
0.4113
0.4729
0.0015
0.2828
0.3451
0.2125
0.6355
0.6727
14.62630
2.022019
-0.866001
-0.242080
487.3846
0.000000
ADF Test Statistic
-0.426050
1% Critical Value*
-3.6661
5% Critical Value
-2.9627
10% Critical Value
-2.6200
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(RGDP))
Method: Least Squares
Date: 01/20/14 Time: 16:02
Sample(adjusted): 1982 2011
Included observations: 30 after adjusting endpoints
Variable
LOGRGDP(-1))
D(LOG(RGDP(-1)))
C
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
ADF Test Statistic
Coefficient
Std. Error
t-Statistic
0 .006408
0.161046
0.277198
0.030689
-0.041112
0.1 79310
0.868102
10.57149
2.077566
0.01 5041
-0.426050
0.185528
0.868041
0.212307
1.305645
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob (F-statistic)
Prob.
0.6734
0.3930
0.2027
0.222334
0.175734
-0.504766
-0.364646
0.427421
0.656525
-3.471918
1% Critical Value* -3.6752
5% Critical Value
-2.9665
10% Critical Value -2 .6220
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(RGDP) 2)
Method: Least Squares
Date: 01/20/14 Time: 16:03
Sample(adjusted): 1983 2011
Included observations: 29 after adjusting endpoints
Variable
Coefficient
D(LDG(RGDP(-1)))
-0.858428
D(LOG(RGDP(-1)),2)
-0.045235
C
0.197447
R-squared
0.455568
Adjusted R-squared
0.413689
SE. of regression
0.1 80370
Sum squared reside
0.845867
Log likelihood
10.10378
Durbin-Watson stat
2.018059
74
Std. Error
t-Statistic
0.247249
-3.471918
0.188874
-0.239497
0.064044
3.082990
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwauz criterion
F-statistic
Prob (F-statistic)
Prob.
0.0018
0.8126
0.0048
0.002400
0.235559
-0.489916
-0.348471
10.87812
0.000369
ADF Test Statistic
-6.058282
1% Critical Value*
5% Critical Value
10% Critical Value
-3 .6852
-2 .9705
-2 .6242
MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(RGDP)3)
Method: Least Squares
Date: 01/20/14 Time: 16:03
Sample (adjusted): 1984 2011
Included observations: 28 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
D(LOG(RGDP(-1)),2)
-1.954734
0.322655
-6.058282
D(LOG(RGDP(-1)),3)
0.348998
0.193527
1.803358
C
0.007674
0.039528
0.194131
R-squared
0.754461
Mean dependent var
Adjusted R-squared
0.734818
S.D. dependent var
S.E. of regression
0.208857
Akaike info criterion
Sum squared resid
1.090527
Schwarz criterion
Log likelihood
5.707326
F-statistic
Durbin-Watson stat
2.124425
Prob(F-statistic)
ADF Test Statistic
-0.384621
1% Critical Value*
5% Critical Value
10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(ORV))
Method: Least Squares
Date: 01/20114 Time: 16:03
Sample(adjusted): 1982 2011
Included observations: 30 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
LOG(ORV(-1))
-0.012355
0.032124
-0.384621
D(LOG(ORV(-1)))
-0.094591
0.186900
-0.506107
C
0.403930
0.403206
1.001796
R-squared
0.016609
Mean dependent var
Adjusted R-squared
-0.056235
S.D. dependent var
S.E. of regression
0.409342
Akaike info criterion
Sum squared reside
4.524147
Schwarz criterion
Log likelihood
-14.19163
F-statistic
Durbin-Watson stat
2.086315
Prob(F-statistic)
75
Prob.
0.0000
0.0834
0.8476
-0.009457
0.405580
-0.193380
-0.050644
38.40844
0.000000
-3.6661
-2.9627
-2.6200
Prob.
0.7035
0.6169
0.3253
0.231347
0.398296
1.146109
1.286229
0.228009
0.797635
ADF Test Statistic
-4.753010
1% Critical Value*
5% Critical Value
10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(QRV) 2)
Method: Least Squares
Date: 01/20/14 Time: 16:04
Sample(adjusted): 1983 2011
Included observations: 29 after adjusting endpoints
Variable
Coefficient
D(LQG(ORV(-1 )))
-1 .349444
D(LOG(ORV(-1)),2)
0.174186
C
0.314799
R-squared
0.591 957
Adjusted R-squared
0.560569
S.E. of regression
0.404076
Sum squared resid
4.245219
Log likelihood
-13.28743
Durbin-Watson stat
2.054182
ADF Test Statistic
-6.4781 99
Std. Error
t-Statistic
0.283914
-4.753010
0.186791
0.932517
0.095429
3.298761
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
1% Critical Value*
5% Critical Value
10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(ORV),3)
Method: Least Squares
Date: 01/20/14 Time: 16:04
Sample(adjusted): 1984 2011
Included observations: 28 after adjusting endpoints
Variable
Coefficient
D(LOG(ORV(-1 )),2)
-2.176602
D(LDG (ORV(-1 )) 3)
0.463984
C
0.030230
R-squared
0.789617
Adjusted R-squared
0.772786
S.E. of regression
0.510517
Sum squared resid
6.51 5700
Log likelihood
-1 9.31 842
Durbin-Watson stat
2.287061
ADF Test Statistic
-2.118526
Std. Error
t-Statistic
0.335989
-6.478199
0.199887
2.321229
0.096542
0.313123
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
1% Critical Value
5% Critical Value
10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root
76
-3.6752
-2.9665
-2.6220
Prob.
0.0001
0.3596
00028
0.020213
0,609562
1 .12327 1
1.264716
18.85938
0.000009
-3.6852
-2.9705
-2.6242
Prob.
0.0000
0.0287
0.7568
-0.001694
1.071 009
1.5941 73
1.736909
46.91 544
0.000000
-3.6661
-2 .9627
-2 .6200
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(EXR)
Method: Least Squares
Date: 01/20/14 Time: 16:04
Sample (adjusted): 1982 2011
Included observations: 30 after adjusting endpoints
Variable
Coefficient
EXR(-1)
-0.31 8436
D(EXR(-1))
-0.1 38037
C
6.539229
R-squared
0.207815
Adjusted R-squared
0.1491 35
S.E. of regression
4.698410
Sum squared resid
596.0266
Log likelihood
-87.40447
Durbin-Watson stat
2.066096
ADF Test Statistic
Std. Error
t-Statistic
0.150310
-2.118526
0.184427
-0.748464
3.133883
2.086622
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
-5.985375
1% Critical Value*
5% Critical Value
10% Critical Value
*MacKin non critical values for rejection of hypothesis of a unit root.
Augment Dickey Fuller- Test equation
Dependent Variable: D(EXR,2)
Method: Least Squares
Date: 01/20/14 Time: 16:05
Sample(adjusted): 1983 2011
Included observations: 29 after adjusting endpoints
Variable
Coefficient
D(EXR(-1))
-1 .755690
D(EXR(-1),2)
0.372561
C
0.204888
R-squared
0.686913
Adjusted R-squared
0.662830
S.E. of regression
4.792144
Sum squared resi
597.0809
Log likelihood
-85.00819
Durbin-Watson stat
1 .822484
ADF Test Statistic
-9.802073
Std. Error
t-Statistic
0.293330
-5.985375
0.183263
2.032931
0,892208
0.229642
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
1% Critical Value*
5% Critical Value
10% Critical Value
*Mackinnon critical values for rejection of hypothesis of a unit root
77
Prob.
0.0435
0.4607
0.0465
0.096667
5.093549
6.026965
6.167085
3.541473
0.043068
-3.6752
-2.9665
-2.6220
Prob.
0.0000
0.0524
0.8202
-0.156897
8.252877
6.069530
6.210975
28.52207
0.000000
3 6852
-2 .9705
-2 .6242
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(EXR,3)
Method: Least Squares
Date: 01120/14 Time: 16:05
Sample(adjusted): 1984 2011
Included observations: 28 after adjusting endpoints
Variable
D(EXR(-1 ),2)
D(EXR(-1 )3)
C
R-squared
Adjusted R-squared
SE. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
-2.51 8317
0.672881
-0.200269
0.864482
0.853641
5.572870
776.4221
-86.24516
- 2.309092
ADF Test Statistic
-1 .295551
Std. Error
t-Statistic
0.256917
-9.802073
0.148008
4.546255
1053330
-0.190129
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
1 % Critical Value*
5% Critical Value
10% Critical Value
*Mackinnon critical values for rejection of hypothesis of a unit root.
Prob.
0.0000
0.0001
0.8507
-2.38E-16
14.56695
6,374655
6.517391
79.73874
- 0.000000
-3.6661
-2.9627
-2.6200
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(FR))
Method: Least Squares
Date: 01/20114 Time: 16:05
Sample(adjusted): 1982 2011
Included observations: 30 after adjusting endpoints
Variable
LOG(FR(-1))
D(LQG(FR(-1)))
C
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
-0.113899.
0.277163
1.317030
0.095868
0.028895
0.569310
8.751 062
-24.08782
I .614013
ADF Test Statistic
-5.270213
Std. Error
t-Statistic
0.087915
-1.295551
0.192905
1.436785
0.983056
1.339731
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
1% Critical Value*
5% Critical Value
- 10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root
78
Prob.
0.2061
0.1623
0.1915
0.064660
0.577717
1.805855
1.945974
1 .431447
0.256525
-3 .6752
-2.9665
-2.6220
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LOG(FR),2)
Method: Least Squares
Date: 01/20/14 Time: 16:06
Sample(adjusted): 1983 2011
Included observations: 29 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
D(LQG(FR(-1)))
-1.049009
0.199045
5.270213
D(LOG(FR(-1 )),2)
0.299052
0.157108
1.903476
C
0.124827
0.089802
1.390024
R-squared
0.546235
Mean dependent var
Adjusted R-squared
0.511330
S.D. dependent var
S.E. of regression
0.476822
Akaike into criterion
Sum squared resid
5.911335
Schwarz criterion
Log likelihood
-1 8.08807
F-statistic
Durbin-Watson stat
2.105585
Prob(F-statistic)
ADF Test Statistic
-6.535198
1 % Critical Value*
5% Critical Value
10% Critical Value
MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(LQG(FR),3)
Method: Least Squares
Date: 01/20/14 Time: 16:06
Sample(adjusted): 1984 2011
Included observations: 28 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
D(LOG(FR(-1)),2)
-1.707924
0.261342
-6.5351 98
D(LQG(FR(-1))3)
0.433803
0.158259
2.741100
C
0.023001
0.114198
0.201418
R-squared
0.689442
Mean dependent var
Adjusted R-squared
0.664597
S.D. dependent var
S.E. of regression
0.602796
Akaike info criterion
Sum squared resid
9.084081
Schwarz criterion
Log likelihood
-23.97074
F-statistic
Durbin-Watson stat
- 2.117102
Prob(F-statistic)
79
Prob.
0.0000
0.0681
0.1763
0.047603
0.682101
1 .454350
1.595794
15.64922
0.000035
-3.6852
-2 .9705
-2.6242
Prob.
0.0000
0.0111
0.8420
-0.033322
1 .040847
1.926482
2.069218
27.75008
0.000000
Date: 01/20/14 Time: 16:08
Sample: 1980 2011
Included observations: 30
Test Assumption: Linear Deterministic
Trend in the Data
Series: LOG(RGDP) LOG(ORV’) LOG(FR) EXR
Lags interval: 1 to 1
Likelihood
5 Percent
1 Percent
Eigen value
Ratio
Critical Value Critical Value
0.610480
5484391
47.21
54.46
0.409658
26.55869
29.68
35.65
0.261035
10.74707
15.41
20,04
0.054207
1.671944
3.76
6.65
*(**) denotes rejection of the hypothesis at 5%(1%) level
L.R. test t 5%
indicates 1
cointegrating equation(s) at
Unnormalized
LOG(RGDP)
0.099644
-0.750270
-0.305158
-0.080140
Normalized
Cointegrating
Coefficients:
1
Cointegrating
Equation(s)
LOG(RGDP)
1.000000
Log
Likelihood
Normalized
Cointegrating
Coefficients:
2
Cointegrating
Equation(s)
LOG(RGDP)
1.000000
Hypothesized
No. of CE(s)
None **
At most I
Atmost2
Atrnost3
significance
significance level
Cointegrating
LOG(ORV)
LOG(FR)
-0.259607
0.284216
0.680663
0.053650
0.322521
-0.100696
0.111609
0.095900
Coefficients:
EXR
0.025608
-0.021420
0.025516
-0.002754
LOG(ORV)
-2.605345
(1.99387)
EXR
0.256999
(0.29454)
LOG(FR)
2.852320
(3.43549)
C
-18.70593
-87.81228
LOG(ORV)
0.000000
LOG(FR)
-1.633569
(0.14705)
80
EXR
0.093500
(0.03664)
C
6.093085
0.000000
Log
Likelihood
1.000000
-1.721803
(0.14340)
-0.134531
(0.03573)
-79.90647
Normalization
Coiritegrating
Coefficients:
3
Cointegrating
Equation(s)
LOG(RGDP)
1.000000
LOG(ORV)
0.000000
LOG(FR)
0.000000
0.000000
1.000000
0.000000
0.000000
0.000000
1.000000
Log
Likelihood
-75.36891
Pairwise Granger Causally Tests
Date: 07/12/13 Time: 12:13
Sample: 1980 2011
Lags: 2
Null Hypothesis:
Obs
LOG(FR) does not Granger Cause
30
LOG(EXR)
LOG(EXR) does not Granger Cause LOG(FR)
LOG(ORV) does not Granger cause
30
LOG(EXR)
LOG(EXR) does not Granger cause LOG(ORV)
LOG(RGDP) does not cause
30
LOG(EXR)
LOG(EXR) does not Granger cause LOG(RGDO)
LOG(ORV) does not Granger cause
30
LOG(FR)
LOG(FR) does not Granger cause LOG(ORV)
LOG(RGDP) does not Granger cause
30
LOG(FR)
LOG(FR) does not Granger cause LOG(RGDP)
LOG(RGDP) does not Granger cause
30
LOG(ORV)
LOG(ORV) does not Granger cause LOG(RGDP)
81
EXR
-1.596682
(1.78327)
-1.718904
(1.89085)
-0.920183
F-Statistic
0.300049
Probability
0.58792
2.19299
0.60059
0.1498.
0.4485
1.87061
0.63924
0.18228
0.43072
3.89155
9.65390
0.05848
0.00430
0.01311
8.57131
090967
0.00671
0.13305
6.17732
0.71803
0.01918
0.00051
0.98210
C
18.13033
22.20593
7.368682