Oil has been the
economy stay of Nigeria for the past two decades and economists have studied
extensively on the impact that oil price volatility have on GDP growth. The
present government is in dire need of revenue and also there is a global dip in
oil price which has become a nightmare for the present government. This study
finds out that there is a direct relationship between Nigeria GDP and oil price.
INTRODUCTION
Oil
is the world currency. From the distance past of commercial use of olive oil to
shark oil and now to crude oil, never for once has oil ever lack demand.
According to Ghalayini, oil has always been an indicator of economic stability
in modern times due to the world’s high dependence on it and its price is
importance because it is the largest internationally traded product both in
volume and value terms creating what some analysts have called a hydrocarbon
economy. Crude oil has metaphorically been referred to as the ‘black gold.’ According
to Bamisaye and Obiyan in 2006, oil has redefined the global economy in general
and the Nigerian economy in particular.
In
September 1960, at the Baghdad Conference, OPEC was formed by five countries
that were able to project the huge impact that crude oil will have on the
world’s economy. OPEC was form with the objective to ‘co-ordinate and unify
petroleum policies among member countries in order to secure fair and stable
prices for petroleum producers; an efficient, economic and regular supply of petroleum
to consuming nations; and a fair return on capital to those investing in the
industry.’ In 1971, Nigeria joined OPEC. Sales of Nigeria oil has resulted into
huge revenue for the country up to the point that our then president made the
statement ‘lack of money is not the problem but the lack of project to invest
it in.’ The price of oil has steadily increased over the years but market
shocks has always been part of the process.’ The conquest of Saudi Arabia, the
way between Iraq and Iran, the war between Iraq and Kuwait are some of the
instances when oil prices have gone up in history. The presence dispensation
now witness the massive exportation of oil from Saudi Arabia, USA, Iraq and
other non-OPEC members which is bound to reduce the price of oil due to much
supply. Also the discovery of alternative energy is reducing world’s reliance
on oil as the only source of energy.
THEORETICAL REVIEW
Oil Price volatility and Nigeria
Oil
price volatility is not a new phenomenon; it has been a dominant feature in the
oil market during the last two decades (Baumeister and Peerman, 2009). The
market has been characterised with erratic movement of oil price since the 1970
and changes in oil price automatically leads to changes in oil revenue. Oil
revenue does not respond immediately to changes in oil price due to the
presence of time lag between productions of oil and the impact of oil price
change. According to Sauter and Awerbuch in 2003, immediate oil shocks does not
immediately affect price also oil price change after a period of equilibrium
affects more than constant upward and downward swing in price. There have been
very large and sharp swings in the nominal price of oil since the collapse of
oil price in 1986. Baumeister and Peerman (2009) further identify shift in
contractual arrangement from longer term to short term as another cause of
volatility. They note that oil market transactions in 1960s were based on
long-term contracts with predetermined price but transition to the current
market based system of spot market trading leads to quicker translation of oil
demand and supply variations into price changes. Ubogu (1984) sought to
establish the impact of oil on the Nigerian economy by examining the growth and
development of the oil industry, government participation, industry development,
government revenue, foreign exchange earnings, employment generation and
industry linkages effects; he noted that oil has been responsible for the
radical increase in revenue and further buttressed the stronger dependence on
oil revenue as envisaged in our development plans due to the unanticipated
decline in oil earnings. He was however, strongly in support of diversification
and the need for judicious use of the current limited revenue. In Oriakhe and
Iyoha 2013, Adelman (2000) notes that crude oil prices have been more volatile
than any other commodity price although in principle it ought to be less
volatile. He also notes that though oil price movements have always occurred
mainly due to seasonal changes in demand, such movements were small, between
1948 and 1970; nominal prices fluctuated between $2.50 and $3 per barrel. He
noted that between 1998 and March 2000 international oil prices rose from $10
to $31 per barrel, it further rose to $37 in September 2000, before declining
to less than $18 per barrel in November 2001. Since then there has been an upward
movement in the prices of crude oil reaching about $147 per barrel in 2008,
before averaging $90 per barrel in 2010. He adduces this volatility of crude
oil prices to the fixation of prices by collusion in the OPEC cartel and the
unrest in the Middle East at various times. Kolawole (2002) seems to be in full
agreement with Adelman (2000), pointing out that disagreements on production
quotas and members mistrust have fuelled volatility. Ayadi (2005) does not
think differently either, in his opinion, speculation surrounding OPEC meetings
can also induce volatility. He revealed that whenever OPEC meetings approach,
volatility drifts upwards and therefore blames the frequency of OPEC meetings
and quota adjustments in recent years as a crucial causal factor. Whatever the
cause however, as Osije (1983) remarks, oil prices like other market
commodities is dictated fundamentally by market trends and therefore subject to
price volatility. Baumeister and Peerman (2009) explain that oil price shocks
results from low price elasticity of demand and supply. The result of this is
that large price variation is required to clear the market, that is, to restore
the market to equilibrium. Hamilton (2008) and Fattouh (2007) agree that crude
oil price elasticity is very low especially in the short run. This is due to
technology lock-up; that is, it takes some time before energy-consuming
appliances/capital stocks are replaced with more energy-efficient substitutes. However,
substitution takes place in the longrun and price elasticity is thus much
larger. Notwithstanding, price elasticity is yet less than one (Hamilton,
2008). Baumeister and Peerman (2009) further explain that the demand function
is recently getting less elastic (probably due to increasing growth in demand from
emerging economies, relative to availability of substitutes such as bio-fuels
and green energies), and this explains higher shocks in oil prices. Similarly,
supply of crude oil is price inelastic. This results from time lag between
exploration and production activities, making supply less responsive to price
changes (Fattouh, 2007). Income elasticity also contributes to oil price
volatility. Income elasticity higher than unity means that percentage rise in
quantity demanded of oil is greater than percentage rise in income. Thus income
variation causes demand for oil to shift in the same direction but at a higher
magnitude, thus leading to oil price volatility. Reporting Darl (1991) Hamilton
(2008) reports positive income elasticity for crude oil demand in developing
countries from where most of the growth in world consumption of crude oil
emanates. This agrees with Fattouh’s (2007) report of Ibrahim and Hurst (1990)
and Pesaran, Smith and Akiyama’s (1998) estimated crude oil income elasticity
for developing and Asian countries. However, shifts in supply function are mild
except for periods of political disturbance in oil-producing countries. This
points out that the current rising trend in oil price resulting from supply
disruption may not be sustained. This thus bears a policy implication for
governments in oil exporting countries with respect to tying budgetary plans
too closely to crude oil revenues.
Oil Price Volatility and GDP growth
in Nigeria
GDP
is the market value of all goods produced within a country and usually within a
time frame, which is usually a year. GDP growth is expected in a country like
Nigeria with population growth of 2.66% (World Bank data) because the expanding
population will contribute to the production of goods and services. GDP growth
is affected by change in exchange rate, inflation rate and production increase.
Gordon in 1989 shows that oil price volatility has an indirect and marginal
impact on real GDP in Nigeria. This contradicts Farzanegan and Markwardt, 2007
findings that oil price shocks tend to lower real GDP and impacts significantly
on it but rather confirms the findings of (Barsky and Kilian, 2004) as well as
(Akpan, 2009), that oil price shocks had marginal impact on real GDP. An
explanation for the rather weak causality between oil price volatility and real
GDP as demonstrated by the result is suggested. Oil price volatility may not
have a direct impact on real GDP in Nigeria; rather it works through real
government expenditure and real exchange rate as indicated by the result.
Characteristically, government has remained the major driver of the Nigerian
economy; therefore through its expenditure it dictates the growth trend and
speed of the economy. The implication of this result therefore is that at the
prevailing exchange rate, oil prices determine government’s expenditure which
in turn determines growth in Nigeria. Another explanation which can be put
forth is the difference in estimation periods. Some related studies such as;
(Akpan, 2009; Aliyu, 2009), which employed estimation periods of 1980-2009 and
1981-2008 respectively, reported a direct significant impact on real GDP by oil
price volatility. But the studies of (Olomola, 2006) that used an estimation
period similar to this study, reported a weakly significant impact of oil price
volatility on real GDP. This implies that the period chosen for the analysis
could be considered as a likely factor. Another likely explanation is the
recent economic diversification goal being pursued by policy makers at all
levels in the country. There has been a lot of effort geared towards reducing
the dependence on oil. Some state governments have improved their tax
collection mechanisms so as to reduce their reliance on the oil determined
revenue allocations from the Federal government. If these efforts are anything
to go by the implication ordinarily will be that the direct causality between
oil price volatility and real GDP should expectedly fade away. A fourth
consideration in this direction is the significant impact of oil price
volatility on inflation rate. The findings of Barker and Paul (2004), that oil
price changes can significantly affect inflation rate confirms the results of
this study. In line with economic theory, we expect a positive relationship
between crude oil price and output growth, although a large body of empirical
study indicates that oil price increases have a significant negative effect on
real GDP growth in oil importing countries.
METHODOLOGY
Following
the classical schools, GDP can be calculated through three different
approaches: output, income and the expenditure approach. Using expenditure
approach the GDP is calculated thus:
GDP
= C + I + G + (X – M), where GDP=Gross Domestic Products, C = Aggregate
Consumption;
I
= Aggregate Investment, G = Government Expenditure, X = Exports, M = Imports;
export
and import is divided into non oil and oil.
Y
= β0 + β1C1t + β2I2t + β3ΩG3t + β4XOIL4t + β5XNON-OIL5t + β6MOIL6t +
β7MNON-OIL7t + µt
But
for this study, I will use a simple relationship between GDP and Oil revenue in
Nigeria at 1990 constant prices to test the direct impact of oil revenue on
GDP.
Y
= β0 + β1OR1t + µt
Y
= GDP, µt = error term, β0 = Y intercept, β1= co-efficient of oil revenue, OR =
oil revenue
The
apriori expectation is that β1 >
0, because it is expected that higher oil revenue should lead to higher GDP
Limitation
The
total revenue made from oil exported and oil sold within the country is used.
Total oil revenue is inclusive of oil price and oil quantities produced.
According to monetary economists, inflation is always increased when price of
oil goes up leading to inflationary tendencies in the country. Shocks in
exchange rate is also not considered but the revenue in Naira terms is used.
The indirect effect of oil price volatility on GDP through inflation, exchange
rate, balance of payment which has been established by other research is not
also measured in this study.
Data Analysis
Ordinary
Least Squire (OLS) method is adopted in this study work, because it is most
appropriate in view of test for fitness and simplicity in understanding.
Emphasis will be made on simple regression analysis. The time series data from
1981 to 2013 will be used. The f. test and t. test will be conducted
Data collection
The
data used for the study were collected from annual statistical bulletins of
Organisation for Petroleum Exporting countries (OPEC), Central Bank of Nigeria,
(CBN) Annual Report and National Bureau of Statistic report.
EMPIRICAL ANALYSIS
The
result from the regression analysis is given below. The statistical result is
shown under the appendices.
i From the
result the equation for RGDP can be written has: Y = -255.454 + 7.090Oil
Revenue + µt
ii Test for
Goodness of Fit shows that R square is 0.643 which means that Oil revenue gives
a 64.3% explanation of RGDP
iii The F. value
is 58.53, which means we can make a good forecast of RGDP from Real oil revenue.
The F-statistic value (421.528) shows that the overall model is statistically
iv The Pearson
correlation shows a strength of .809 Both the RGDP and the real oil revenue are
strongly linked and correlated.
TAKE AWAY FROM THE STUDY
i
Since it is proven that Nigeria’s GDP is responsive to oil
revenue, the Nigeria government has to devise a mean of increasing oil revenue
or steadying the amount of revenue generated from it.
ii
A link of 64.3% is established between oil revenue and
Nigeria GDP, we will have to ensure that other industries maintains their
consistency or increase their contribution to GDP
iii
The study shows that oil price volatility affects Nigeria GDP
directly, which means an increase in oil price leads to increase in GDP and a
decrease in oil price leads to decrease in GDP.
iv
The government has to find a way of reducing oil pipeline
vandalism being witness in the country in other to salvage the drop in revenue
being already witnessed in the country.
v
As other past researchers have found out we need to diversify
the economy to achieve GDP growth as dip in oil price might slowly roll out all
GDP being received from oil price.
vi
With the discovery of alternative means of energy and the
discovery of oil in many countries we have to diversify our source of income to
ensure revenue to feed our country and achieve the ongoing change mantra.
REFERENCES
Abubakar
Adamu, (2015) The Impact of Global Fall in Oil Prices on the Nigerian Crude Oil
Revenue and Its Prices. Proceedings of the Second Middle East Conference on Global
Business, Economics, Finance and Banking (ME15Dubai Conference) ISBN:
978-1-941505-26-7 Dubai-UAE, 22-24 May, 2015 Paper ID: D508 1
www.globalbizresearch.org
Biodun
Adedipe, (2004) the impact of oil on nigeria’s economic policy formulation Text
of a paper presented at the conference on Nigeria: Maximizing Pro-poor Growth:
Regenerating the Socio-economic Database, organized by Overseas Development
Institute in collaboration with the Nigerian Economic Summit Group, 16th / 17th
June 2004.
CBN
statistics
Gbadebo
Olusegun ODULARU (2007) Crude oil and the Nigerian economic performance
department of economics and development Studies, College of Business and Social
Sciences, Covenant, University, http://www.ogbus.ru/eng/
Ibeh
Francisca Ujunwa (2013) The impact of oil revenue on the economic growth in
Nigeria (1980-2010) Caritas University, Amorji-Nike Enugu. Unpublished study
Iyoha
Daniel Osaze and Oriakhi D.e (2013) oil price volatility and its consequences
on the growth of the nigerian economy: an examination (1970-2010) Asian
Economic and Financial Review, 2013, 3(5):683-702
Latife
Ghalayini (2011) The Interaction between Oil Price and Economic Growth. Middle
Eastern Finance and Economics ISSN: 1450-2889 Issue 13 (2011) © EuroJournals
Publishing, Inc. 2011 http://www.eurojournals.com/MEFE.htm
Nigeria
Bureau of statistics bulletin
Oluwatosin
A. Adeniyi (2008) oil price shocks and economic growth in nigeria: are
thresholds Important? Department of Economics and Business Studies, Redeemers
University
OPEC
statistical bulletin
Remi
Babalola: 2009 (Global Melt-down Federal Government Maintain stance on
repositioning Economy from over dependence on Oil.
APPENDICES
Regression
Descriptive
Statistics
|
|
Mean
|
Std.
Deviation
|
N
|
RGDP
|
448.6453
|
204.30983
|
33
|
OILREVENUE
|
99.3036
|
23.29844
|
33
|
Correlations
|
|
RGDP
|
OILREVENUE
|
Pearson
Correlation
|
RGDP
|
1.000
|
.809
|
OILREVENUE
|
.809
|
1.000
|
Sig.
(1-tailed)
|
RGDP
|
.
|
.000
|
OILREVENUE
|
.000
|
.
|
N
|
RGDP
|
33
|
33
|
OILREVENUE
|
33
|
33
|
Variables
Entered/Removeda
|
Model
|
Variables
Entered
|
Variables
Removed
|
Method
|
1
|
OILREVENUEb
|
.
|
Enter
|
a.
Dependent Variable: RGDP
|
b. All
requested variables entered.
|
Model
Summaryb
|
Model
|
R
|
R
Square
|
Adjusted
R Square
|
Std.
Error of the Estimate
|
Change
Statistics
|
R
Square Change
|
F
Change
|
df1
|
1
|
.809a
|
.654
|
.643
|
122.14516
|
.654
|
58.532
|
1
|
Model
Summaryb
|
Model
|
Change
Statistics
|
Durbin-Watson
|
df2
|
Sig. F
Change
|
1
|
31a
|
.000
|
.171
|
a.
Predictors: (Constant), OILREVENUE
|
b.
Dependent Variable: RGDP
|
ANOVAa
|
Model
|
Sum of
Squares
|
df
|
Mean
Square
|
F
|
Sig.
|
1
|
Regression
|
873257.590
|
1
|
873257.590
|
58.532
|
.000b
|
Residual
|
462502.617
|
31
|
14919.439
|
|
|
Total
|
1335760.208
|
32
|
|
|
|
a.
Dependent Variable: RGDP
|
|
b.
Predictors: (Constant), OILREVENUE
|
|
Coefficientsa
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
B
|
Std.
Error
|
Beta
|
1
|
(Constant)
|
-255.454
|
94.456
|
|
-2.704
|
.011
|
OILREVENUE
|
7.090
|
.927
|
.809
|
7.651
|
.000
|
|
|
|
|
|
|
|
|
Coefficientsa
|
Model
|
95.0%
Confidence Interval for B
|
Correlations
|
Collinearity
Statistics
|
Lower
Bound
|
Upper
Bound
|
Zero-order
|
Partial
|
Part
|
Tolerance
|
1
|
(Constant)
|
-448.100
|
-62.809
|
|
|
|
|
OILREVENUE
|
5.200
|
8.981
|
.809
|
.809
|
.809
|
1.000
|
Coefficientsa
|
Model
|
Collinearity
Statistics
|
VIF
|
1
|
(Constant)
|
|
OILREVENUE
|
1.000
|
a.
Dependent Variable: RGDP
|
Coefficient
Correlationsa
|
|
Model
|
OILREVENUE
|
|
1
|
Correlations
|
OILREVENUE
|
1.000
|
|
Covariances
|
OILREVENUE
|
.859
|
|
a.
Dependent Variable: RGDP
|
|
Collinearity
Diagnosticsa
|
Model
|
Dimension
|
Eigenvalue
|
Condition
Index
|
Variance
Proportions
|
(Constant)
|
OILREVENUE
|
1
|
1
|
1.974
|
1.000
|
.01
|
.01
|
2
|
.026
|
8.771
|
.99
|
.99
|
|
|
|
|
|
|
|
a.
Dependent Variable: RGDP
|
Casewise
Diagnosticsa,b
|
|
Case
Number
|
Std.
Residual
|
RGDP
|
Predicted
Value
|
Residual
|
|
1
|
-.092
|
251.052
|
262.2826
|
-11.23030
|
|
2
|
.319
|
246.727
|
207.7439
|
38.98262
|
|
3
|
.526
|
230.381
|
166.1250
|
64.25580
|
|
4
|
.069
|
227.255
|
218.7804
|
8.47429
|
|
5
|
-.026
|
253.013
|
256.1306
|
-3.11729
|
|
6
|
.093
|
257.784
|
246.4804
|
11.30408
|
|
7
|
.181
|
255.997
|
233.8866
|
22.11039
|
|
8
|
.234
|
275.410
|
246.8116
|
28.59792
|
|
9
|
.309
|
295.091
|
257.3350
|
37.75583
|
|
10
|
-.088
|
328.606
|
339.4072
|
-10.80114
|
|
11
|
-.519
|
328.645
|
391.9957
|
-63.35119
|
|
12
|
-.581
|
337.289
|
408.3064
|
-71.01777
|
|
13
|
-.550
|
342.540
|
409.6943
|
-67.15384
|
|
14
|
-.387
|
345.228
|
392.5165
|
-47.28803
|
|
15
|
-.451
|
352.646
|
407.7563
|
-55.11004
|
|
16
|
-.721
|
367.218
|
455.2782
|
-88.06012
|
|
17
|
-.720
|
377.831
|
465.7573
|
-87.92655
|
|
18
|
-.761
|
388.468
|
481.4022
|
-92.93411
|
|
19
|
-.270
|
393.107
|
426.1380
|
-33.03080
|
|
20
|
-.734
|
412.332
|
501.9931
|
-89.66108
|
|
21
|
-.899
|
431.783
|
541.6274
|
-109.84421
|
|
22
|
-.363
|
451.786
|
496.1405
|
-44.35482
|
|
23
|
-1.480
|
495.007
|
675.7717
|
-180.76451
|
|
24
|
-1.465
|
527.576
|
706.5022
|
-178.92612
|
|
25
|
-1.223
|
561.931
|
711.2870
|
-149.35556
|
|
26
|
-.588
|
595.822
|
667.6672
|
-71.84555
|
|
27
|
.069
|
634.251
|
625.7740
|
8.47710
|
|
28
|
.827
|
672.203
|
571.2451
|
100.95746
|
|
29
|
1.179
|
718.977
|
574.9803
|
143.99702
|
|
30
|
1.292
|
776.332
|
618.5686
|
157.76364
|
|
31
|
1.754
|
834.001
|
619.8098
|
214.19099
|
|
32
|
2.268
|
888.893
|
611.8156
|
277.07738
|
|
33
|
2.799
|
950.114
|
608.2855
|
341.82851
|
|
a.
Dependent Variable: RGDP
|
|
b.
When values are missing, the substituted mean has been used in the
statistical computation.
|
|
Residuals
Statisticsa
|
|
Minimum
|
Maximum
|
Mean
|
Std.
Deviation
|
N
|
Predicted
Value
|
166.1250
|
711.2869
|
448.6453
|
165.19473
|
33
|
Std.
Predicted Value
|
-1.710
|
1.590
|
.000
|
1.000
|
33
|
Standard
Error of Predicted Value
|
21.280
|
42.612
|
29.351
|
6.637
|
33
|
Adjusted
Predicted Value
|
157.2211
|
729.6138
|
448.4872
|
167.11021
|
33
|
Residual
|
-180.76451
|
341.82852
|
.00000
|
120.22149
|
33
|
Std.
Residual
|
-1.480
|
2.799
|
.000
|
.984
|
33
|
Stud.
Residual
|
-1.551
|
2.886
|
.001
|
1.018
|
33
|
Deleted
Residual
|
-200.24039
|
363.44894
|
.15812
|
128.64461
|
33
|
Stud.
Deleted Residual
|
-1.588
|
3.319
|
.021
|
1.080
|
33
|
Mahal.
Distance
|
.002
|
2.925
|
.970
|
.862
|
33
|
Cook's
Distance
|
.000
|
.263
|
.035
|
.062
|
33
|
Centered
Leverage Value
|
.000
|
.091
|
.030
|
.027
|
33
|
|
|
|
|
|
|
|
a.
Dependent Variable: RGDP
|