THE IMPACT OF CHANGES IN OIL PRICE ON GDP GROWTH IN NIGERIA

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