Objective: This study examined the relationship between oil price and economic growth in Nigeria using annual time series data for the period 1974-2014 sourced from Central Bank of Nigeria (CBN) statistical bulletin, OPEC and world bank for the year 2014. Methodology: Non-probability sampling method in the form of availability sampling technique has been applied in selecting the number of years covering this study. Dickey-fuller generalised least squares unit roots test has been applied in testing for stationarity of the variables and granger causality test adopted for testing the direction of causality. Results: The findings indicate that, there is no long-run relationship among the variables. However, granger causality test indicate a significant unidirectional causality running from oil price to economic growth in the short run. In addition, there is a significant positive unidirectional causality running from human capital to economic growth in Nigeria. Also, the findings indicate a significant positive unidirectional causality running from oil price to total exports in Nigeria. Conclusion: The study therefore, recommends stability of oil price in order to achieve high economic growth in the short run, substantial amount of government budgetary allocation should be directed towards educational sector in order to strengthen economic growth through human capital in the short run. Finally, measures to maintain higher oil price and stability in the world market should be adopted so as to increase the volume of oil export which will eventually lead to increase in total exports.
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The trends and dwindling of oil price in the global market has become a source of concern for oil producing countries. The price of crude oil had dropped precariously from a peak of $104 per barrel by the third quarter of 2014. Specifically, the OPEC average monthly basket price of oil peaked at $107.89 per barrel in June, 2014 dwindled very sharply to $59 per barrel at end-December, 2014. It further decelerated to $54.4 by end-March, 2015, resulting in Nigeria experiencing a sudden and significant drop in revenue inflow from oil sales1. Nigeria, a mono-cultural and a hydrocarbon economy depends largely on revenue realized from oil to sustain her teeming population and the economy in order to foster physical, political and socio-economic development. Despite the fact that Nigeria is the 6th largest oil producer, the country also imports oil from other countries. The surplus of exporting value over the importing value makes Nigeria a net oil exporting country2.
Oil prices have witnessed profound fluctuations and this has implications for the performance of macroeconomic variables, posing great challenges for policy making. The transmission mechanisms through which oil prices have impacted on real economic activity include both supply and demand channels. The supply side effects are related to the fact that crude oil is a basic input to production and consequently an increase in oil price leads to a rise in production costs that induce firms to lower output. Oil price changes also entail demand side effects on consumption and investment3-4. Thus the impact (positive or negative) which oil price volatility could have on any economy, depends on what part of the divide such economy falls into and of course the nature of such price change (rise or fall). However, the Nigerian economy uniquely qualifies as both an oil exporting and importing economy by reason of the fact that she exports crude oil, but imports refined petroleum products5.
However, most of the empirical studies carried out have focused on the oil importing economies, particularly the developed economies6-9. Few studies exist yet on the effect of oil price on key macroeconomic variables for an oil exporting country like Nigeria. Alley et al.10 study empirically the impact of oil price shock on economic growth in Nigeria using aggregate denand model and applied Generalized Method of Moment (GMM). Despite the robustness of the study by Alley et al.10, it is flawed by the sample size used (1981-2012) concentrates more on price shock and does not show clearly the direction of relationship among the variables studied. This study intends to fill this gap that the oil-macroeconomics literature lacks by examining empirically the impact of oil price on economic growth as well as show how changes in oil price affect key macroeconomic variables in Nigeria within the framework of policy objectives.
Deducting from the above, the study seek to answer the following questions:
|•||Does oil price have any significant impact on economic growth in Nigeria?|
|•||What other factors influence economic growth in Nigeria?|
|•||What is the direction of relationship between oil price and economic growth?|
|•||What are the policy implications?|
The following hypotheses have been tested in order to achieve the objectives of the study:
|•||Ho : Oil price has no significant impact on the economic growth of Nigeria|
|•||H1 : Other factors do not have any significant influence on the economic growth of Nigeria|
A significant number of studies have been reviewed to support and complement the efficacy of this study. Oil, the most internationally contributing factor of production in modern-economy, its price tends to be volatile, at least due to business cycle. Hamilton11 using granger causality test showed that oil price changes are the cause of GDP fluctuation in US. Burbidge and Harrison12 conduct a study using vector autoregression (VAR) on monthly data from January, 1961 to June, 1982 they found that, the effect of oil price rise on inflation in US and Canada is more than in Japan, Germany and England. Cunado and de Gracia13 also investigate oil price impact on fifteen European countries and find mixed results. They conclude that, the use of either world oil price index or a national real price index is part of the explanation to the difference between oil prices and outputs. Moreover, they could not find any long-run relationship between oil prices and economic activity except for the United Kingdom and Ireland. Therefore, they suggest that the impact of oil price shocks on economic activity is limited to the short-run.
However, Berument and Ceylan14 studied the effect of oil price shocks on economic growth in MENA region covering 1960-2003, they applied dynamic vector autoregressive (DVAR) model to investigate this relationship, the results show a positive effect on Iran, Iraq, Algeria, Jordan, Kuwait, Oman, Syria, Tunisia and United Arab Emirate, while on other case including Bahrain, Djibouti, Egypt, Morocco and Yemen, there was no significant relation statistically. In the same vein15-18, investigate on the impact of oil price on economic growth and other macroeconomic variables, the studies established significant relationship among the variables using econometric analyses based on long-run and short-run frameworks.
Ayadi et al.19 examine the effect of oil production shocks on the net-exporting country (Nigeria) using a standard VAR which includes oil production, output, real exchange rate and inflation over 1975-1995 period. The impact response show that a positive oil shock (high oil price) is followed by rise in output, reduction in inflation and a depreciation of the domestic currency. This tallies with the findings of Olomola and Adejumo6. Olusegun20 investigate the impact of oil price shocks on the macroeconomic performance in Nigeria using seven key Nigerias macroeconomic variables, which are: Real GDP, CPI, real oil revenue, real money supply, real government recurrent expenditure, real government capital expenditure and real oil price. An annual data set between the periods 1970 and 2005 has been employed, johansen cointegration test indicates at least four cointegrating vectors among the variables, the forecast error variance decomposition estimated from the VAR model shows that oil price shocks significantly contributes to the variability of oil revenue and output. The study also reveals that the variability in the price level apart from its own shock is explained substantially by output and money supply shocks. Also, the variability in money supply is equally explained by price level and output. These findings confirm, thus, that oil price shock may not be necessarily inflationary especially, in the case of an open developing country like Nigeria, the policy implication of this is that, fiscal policy may be used more effectively to stabilize the economy after oil shock. In their quest2,21-23, establishes a positive relationship between oil price and real GDP in Nigeria using different methodology and econometric analysis.
MATERIALS AND METHODS
Sources of data, sampling technique and sample size: The data for this research work were obtained mainly from secondary sources, particularly from Central Bank of Nigerias24 statistical bulletin from 1974-2014 covering the period of 41 years of OPEC and the world bank data banks. Given the time series nature of the data set for this study, non-probability sampling method in the form of availability sampling techniques has been applied in selecting the number of years that constitute the sample size for this study. This sampling technique has been applied because selection of a given year depends on the availability of the data on all the variables required for this study.
Oil price: The real oil price is measured by annual average price of oil in US dollars per barrel. Therefore, this study made use of the annual average price of oil in US dollars per barrel as a proxy for oil price.
Economic growth: The real GDP has been used as a measure of economic growth as measured by Olomola and Adejumo6, Farzanegan and Markwardt15, Aliyu21, Omoniyi and Omobitan25 and Adelakun26. Thus, this study will make use of real GDP as a proxy for economic growth.
Total export: Total export is proxy by the total value of goods and services exported. Therefore, this study will make use of total value of export as a proxy for export.
Economic openness: Economic Openness is proxy by the ratio of the sum of exports and imports to GDP [100×(export+imports)/GDP] as measured by Obida and Abu27, Anyanwu et al.28 and Babalola et al.29. Thus, this study will make use of the ratio of the sum of exports and imports to the GDP as a proxy for economic openness.
Foreign Direct Investment (FDI): The FDI is measured as the total inflows of FDI into Nigeria as a percentage of GDP as measured by Anyanwu et al.28 and Obida and Abu27. Therefore, this study will make use of total inflows of FDI as a percentage of GDP as a proxy for Foreign Direct Investment (FDI).
Human capital: Human capital is proxy by annual total expenditure on education following the works by Adelakun26. Therefore, this study will make use of the annual total expenditure on education as a proxy for human capital (annual total expenditure on education).
Method of data analysis: Both descriptive and inferential methods of data analysis were used for this study. Descriptive method will be used in the form of mean, frequency, minimum and maximum in order to describe the nature of the data set. For the inferential method, unit root test will be conducted to establish the stationarity of all the variables. Vector autoregressive (VAR) model will be used to establish the short-run relationship and the direction of causality on the impact of oil price on economic growth using the above listed key macroeconomic variables, if there is no evidence of cointegration. If cointegration exists among the variables, Vector Error Correction (VEC) will be applied.
Model specification: The model for this study is specified thus in Eq. 1 as:
|RGDP||=||Real Gross Domestic Product|
|OILPRICD||=||Oil Price as measured by annual average price of oil in US dollars per barrel|
|FDI||=||Foreign Direct Investment (FDI/% of GDP)|
|ECOOPEN||=||Economic Openness (100×(Exports+imports)/ GDP)|
|HUMANCAP||=||Human Capital (annual total expenditure on education)|
where, real GDP is the dependent variable, OILPRICDt, FDIt, TOEXPt, ECOOPENt and HUMANCAPt are the independent variables.
The vector autoregressive (VAR) model is specified as follows in Eq. 2:
|yt||=||An n×1 vector of non-stationary I (1) variable|
|n||=||Number of variables in the system, in this study eight in each case|
|A0||=||n×1 vector of constant terms|
|Ak||=||n×n matrix of coefficients|
|et||=||n×1 vector of error terms, which is independent and identically distributed|
|p||=||The order of autoregression or number of lags|
Descriptive analysis and interpretation of results: Obviously, aggregate output (real GDP) and the price of oil have been increasing over the years in Nigeria. Thus, a summary of the descriptive statistics for real GDP, oil price, total exports, human capital, foreign direct investment and economic openness in the form of mean, minimum and maximum for forty one observations covering the period 1970-2010 is presented in Table 1.
The results in Table 1 show that, for the period 1970-2010, average real GDP for Nigeria was 268,168.8 in millions of naira, with 42.19 being the minimum and 776,332.2 as the maximum. Similarly, on the average, the oil price stood at 26.2 per barrel in US$ while 1.21 was the minimum and 94.10 was the maximum. The mean value of total exports was 1,767,411.2 in millions of naira, while 885.67 and 11,035,794.53 were the minimum and maximum, respectively. Furthermore, the average value of expenditure on education (human capital) was 28,022.1 in millions of naira, while the minimum stood at 0.90511 and the maximum was 6.300677879. In addition, the mean value of FDI stood at 2.68412 as a percentage of GDP while 3.94 and 164,00.0 were the minimum and maximum values respectively. Also, the average ratio of total trade to real GDP trade share was 58.0 while the minimum was 42.1 and the maximum was 97.3.
Inferential analysis and interpretation of results: In order to find the impact relationship between oil price and economic growth and between other control variables and economic growth, this study, thus, uses unit roots, cointegration and granger causality tests. However, to know the presence of unit root, two hypotheses are tested: Null hypothesis which states the presence of unit root, that is a series variable is not stationary and which is rejected when the calculated test statistic is greater in absolute value than the critical absolute value. However, the null hypothesis should be accepted when the calculated test statistic is less in absolute value than critical absolute value. Also, stationarity exists when the test statistic is greater in absolute value than the critical absolute value.
The results in Table 2 show that all the series variables are not stationary at level value at 1 and 5% level of significance with exception of human capital which is significant at 1% level of significance, suggesting the acceptance null hypothesis which states that series variables are not stationary. Though, the variables total export and foreign direct investment were stationary at 10% level of significance, but they are weak stationarity.
|Table 1:||Descriptive statistics|
Stata software version 9.1, GDP: Gross domestic product and FDI: Foreign direct investment
|Table 2:||Results of dickey-fuller generalized least square (DF-GLS) unit root tests with trend|
STATA software, version 9.1, *,** and ***Indicate levels of significance at 10, 5 and 1%, respectively, the numbers of lags are in parentheses
Results of cointegration test for real GDP, oil price, total export, foreign direct investment, human capital and economic openness
STATA software, version 9.1, *Indicates that the trace statistic value is not significant at 5% level, suggesting that there is no cointegration
However, by taking the variables in their first difference, results show that all the variables are stationary at either 1 or 5% level of significance. For consistency, thus, the entire series variables were considered as I (1). This is because to conduct cointegration analysis, all variables must be integrated of the same order so as to test for cointegration.
From the aforementioned, the stationarity of the variables is at I (1) which may lead to the examining the presence or otherwise of cointegration relationship among the variables. When there is the presence of cointegration relationship, it means that the variables share a common trend and long run equilibrium. Therefore, Johansen30 tests for the number of cointegration ranks have been conducted and one lag has been included in the cointegration regression.
Table 3 presents the results of Johansen tests for the number of cointegrating ranks. The results of the test indicate the rejection of the alternative hypothesis which states that there is cointegrating vector and accept the null hypothesis which states that there is no cointegrating vector. This is because the value of the trace statistic at zero rank is 84.5671, which is less than its critical value of 94.15 at 5% level of significance.
This implies, Vector Error Correction (VEC) model cannot be applied. In view of this, Granger31 causality test will be conducted using vector autoregressive (VAR) model to get the direction of causality in the short run. Also, since no cointegrating among the variables but they are integrated of the same order, their first difference values will be used in running the VAR model for causality test. Thus, zero lag has been included in the VAR model because majority of the criteria indicated zero lag to be included in the model.
Results of the VAR model: The results indicate a significant and positive unidirectional causality running from oil price to real GDP, suggesting that an increase in oil price promotes economic growth in the short run. Furthermore, the results show a significant and positive causality running from human capital to real GDP. This indicates that, in the short run, human capital facilitates economic growth in Nigeria. Similarly the results of Granger causality test indicate a significant and positive causal relationship running from oil price to total exports in Nigeria. However, all other variables captured in the model do not have causal relationship with economic growth and oil price.
Properties of the VAR model: Basically, the following tests were carried out in order to test for the properties of the model of oil price and economic growth: Langrange-multiplier test for autocorrelation, Jarque-bera test, skewness test, kurtosis test and eigenvalue stability condition. Thus, the results of robustness of the VAR model for granger causality test indicate that there is no autocorrelation problem. But hetroscedasticity exist and residuals are not normally distributed. The model satisfies the stability condition since the eigenvalues are less than one, suggesting that the model is statistically adequate.
The results obtained from the Johansen30 cointegration test by show the non-existence of long-run relationship among the variables used in this study. Consequently, granger causality test has been applied to test for the causal relationship among the variables in the short run. The findings show that causality runs from oil price to economic growth. Results show that the coefficient related to economic growth in the VAR model results (not reported) is, positively and statistically significant. It means that an increase in oil price increases economic growth in the short run which coincides with the finding of Olusegun20 and contradicts that of Berument and Ceylan14. Moreover, a positive causal relation is observed from human capital to real GDP and from oil price to total exports in the short run. The results show that the coefficients related to human capital and oil price are positive and statistically significant. The findings conforms that of Jafiya32 and Adelakun26. This means that the increase in human capital leads to increase in real GDP. Furthermore, an increase in oil price leads to increase in total exports in Nigeria. This is because oil export constitutes the largest proportion of Nigerias total exports. Thus, the finding goes along with conventional law of supply which states that "the higher the price, the higher the quantity supplied".
From the aforementioned, these findings go along with a priori expectation that there is a positive relationship between human capital and real GDP and between oil price and exports. The findings are not in conformity with the findings of Amir et al.33 whose findings show a long run positive relationship between human capital and economic growth. Finally, the result is in conformity with the findings of Ayadi et al.19, Cunado and de Gracia13, Burbidge and Harrison12, Lescaroux and Mignon16, Aliyu21, Umar and Kilishi23, Oyeyemi3 and Okeke1 whose findings indicate strong and positive relationship between oil price and real GDP (economic growth). However, the findings contradict those of Bernanke et al.7, Olomola and Adejumo6, Chuku et al.9, Mordi and Adebiyi34 and Iklaga and Evbuomwan8.
CONCLUSION AND POLICY RECOMMENDATIONS
The empirical findings of this study guide our conclusions on the direction of relationship among the variables studieed. With no significant long run relationship between oil price and economic growth in Nigeria, a significant short-run relationship exist between them (oil price and economic growth) thus, fluctuations in oil price distorts economic growth. Also, there is no significant long run relationship between human capital and real GDP, but short run relation is observed from human capital to real GDP thus, human capital hampers real GDP. In the short run, oil price contributed positively to rise in total exports in Nigeria through increased in oil export.
Based on the findings of this study, the following recommendations are made:
|•||All measures to be taken by the government and other stakeholders in the oil sector should be on short-run basis because the study cannot establish any long-run relationship between oil price and other macroeconomic variables Nigeria|
|•||With a significant positive effect between human capital and real GDP in the short run, substantial amount of government budgetary allocation should be directed towards the education sector which in turn supply the necessary man power with skills and capacity to produce more output for economic growth|
|•||Also, there is the need to maintain a stable oil price in the world market so as to achieve sustain economic growth through foreign exchange. This is paramount as fluctuations in oil price (especially decrease in oil price) negatively affect Nigerias earnings from the international market and cause severe economic hardships as witnessed in the early 2014|
|•||Finally, the government need to diversify the economy by freeing it from the shackles of mono-cultural economy that depends solely on oil. The dwindling oil revenue is a signal that oil can no longer sustain the national economy, exploiting other potentials especially agriculture, mining and manufacturing is an "Urgency of now"|
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AJAYI BABAJIDE A Reply
Suitable for my study.
But I need the economic theory upon which this study is based,and the full text of this study