Energy is critical to the survival and expansion of any economy. In Nigeria, energyconsumption has been skewed towards household use, and below thresholds for sector-driven growth. The article updates, in time and methodology, those studies highlighting the significance of energy use for economicgrowth, using the Bound test and the Auto Regression Distributed Lag (ARDL) to establish the long- and short-run relationships between disaggregated energyconsumption and economicgrowth in Nigeria from 1990 to 2016. The variables considered are real GDP, energyconsumption decomposed into electricity and petroleum consumption, labour and capital. The findings show that, in the short and long run, petroleum consumption and labour have a significant positive relationship with GDP. Furthermore, the causality results show that feedback causation between economicgrowth and energyconsumption as well as labour exists, while one-way causation runs from labour to economicgrowth. The study recommends diversification of the power-generation portfolio in the country, as this will improve energyconsumption. Also, full deregulating policies in the energy sector would encourage industrialization and move energy demand towards increasingly productive uses. Finally, a strong institutional framework is needed to ensure energy policies achieve their objectives and targets.
In contrast to aggregate energyconsumption, there have been few studies specifically addressing the causal relationship between nuclear energyconsumption and economicgrowth (Yoo and Ku, 2009). Some of them employ panel data models while others apply time series analysis. For instance, Naser (2014) examines the relationship between oil consumption, nuclear energyconsumption and economicgrowth in four emerging economies (Russia, China, South Korea, and India) by using Granger non-causality and Toda-Yamamoto tests over the period from 1965 to 2010. The results propose that nuclear energy stimulates economicgrowth in both South Korea and India. In another panel data analysis, Chu and Chang (2012) searched whether energyconsumption promotes economicgrowth by using specifically oil and nuclear energyconsumption data for G-6 countries over the period of 1971-2010. The results indicate that nuclear energyconsumption causes economicgrowth in Japan, UK, and the US; economicgrowth causes nuclear energyconsumption in the US; nuclear consumption and economicgrowth have no causal relation in Canada, France and Germany.
It appears to be of particular importance in this context if this kind of relationship exists between economic activity and renewable component of energyconsumption. Renewable energy is expected to be the fastest growing world energy resource (International Energy Outlook, 2010). Besides a general public interest in cleaner and alternative energy resources, this expected increase in renewable energyconsumption can be attributed to several government policies such as renewable energy production tax credits, installation rebates for renewable energy systems, renewable energy portfolio standards, and the creation of markets for renewable energy certificates (Kaygusuz 2007, Sovacool 2009, Apergis and Payne 2012). Due to the importance of renewable energy, it is crucial to examine the underlying dynamics between renewable energyconsumption and economicgrowth. However, while there is a tremendous number of studies on energyconsumption and economicgrowth in the literature (Ozturk 2010, Payne 2010), studies focusing on renewable energyconsumption have only recently emerged (Apergis and Payne 2012, Tugcu et al. 2012). We aim to make a further attempt to close this gap in the literature by addressing a potential shortcoming of previous studies.
in the literatures because of its high importance. There are two kinds of view exist in the literatures, first, a neo-classical view that is, the economicgrowth of a country can be ‘neutral’ to the energyconsumption, therefore, the country can set energy conservation policy to reduce CO2 emissions for saving environmental degradation without compromising the pace of the economicgrowth which is defined as a ‘neutrality hypothesis’. Second, the country’s economicgrowth can be highly associated with the energyconsumption; therefore, like any other factors of production, the energyconsumption can be a limiting factor to the economicgrowth. Stern (1993, 2000) found that energy is a driving factor to the economicgrowth in US; the similar results found by Mashi and Mashi (1996) in India, Wolde-Rufeal (2005) in Algeria, Cameron, Congo DR, Egypt, Nigeria; Wolde-Rufael (2004) in Shanghai; Soyatas and Sari (2003) in France, Germany and Japan; Chontanawat, et al., (2006, 2008) in Kenya, Nepal and the Philippines, therefore, reduction in energy tends to reduce output growth. In this case, energy conservation policies might be harmful to the economy and in a way ‘neo-classical’ hypothesis that energy is neutral to the economicgrowth can be rejected. Payne (2010a) and Payne (2010b) provide a comprehensive survey on the literatures of causal relationship between energyconsumption, electricity consumption and economicgrowth. Mozumder and Marathe (2007) also list a detail review of literatures on the energyconsumption and economicgrowthnexus.
Over the past three decades, numerous empirical studies have been done on the causal relationship between energyconsumption and economicgrowth. However, relatively smaller number of empirical studies has been carried out on the causal relationship between coal consumption and economicgrowth. Empirical findings on the causal relationship between coal consumption and economicgrowth vary depending on the country or empirical methodology used. Therefore, no consensus has yet been reached. For instance, Yoo (2006) suggests bidirectional causality between coal consumption and growth in Korea; in contrast, Wolde-Rufael (2010) finds unidirectional causality from growth to coal consumption. Wolde-Rufael (2010) reports unidirectional causality from growth to coal consumption in India, while Apergis and Payne (2010a) suggest bidirectional causality, and Li and Li (2011) report a unidirectional causality from coal consumption to growth. For South Africa, Wolde-Rufael (2010) finds unidirectional causality from coal consumption to growth, while (Apergis and Payne, 2010a) suggest bidirectional causality. On the other hand, Odhiambo (2016) reports unidirectional causality from growth to coal consumption in South Africa. Kim and Yoo (2016) find bidirectional causality running from coal consumption to economicgrowth in Indonesia whereas (Irwandi, 2018) reports no causality. Zhang and Broadstock (2016) find bidirectional causality between coal consumption and growth in China; in contrast, Tian and Cui (2013) find co causality. In the case of Turkey, Ocal et al. (2013) and Bildirici and Bakirtas (2014) provide no causality between coal consumption and growth whereas (Apergis and Payne, 2010b) reveal bidirectional causality.
In the short run, the relationship is mixed. In the first period, a 1% increase in renewable energyconsumption increases real GDP by 0.085% (Table 4). Nevertheless, this effect is weak since the associated coefficient is significant at 10%. In the second period, the effect of renewable energyconsumption on economicgrowth is negative and significant at the 5% level. A computation of the short-run overall effect (-0.093+0.085= -0.008) show that the impact of renewable energyconsumption on economicgrowth is a negative and very weak one. The mixed short-run effects (positive and negative) suggest that the transition between non-renewable energy and renewable energy is not effective but is ongoing. In fact, the transition would have been effective if the short-run coefficients were positive and statistically significant. Moreover, the mixed result could be associated with the fact that energy production from renewable sources has a great variability from year to year. Hence, the effect is not constant throughout the time. To comfort this explanation, we compute the coefficient of variation (CV) of all the variables under study. The results show that the renewable energyconsumption variable has the greatest value for this indicator, 30.4% (the CV for the real GDP, labor force and capital are respectively: 16.9%, 12.6% and 26.5%). Regarding the control variables, in the long run, economicgrowth is positively and significantly affected by both capital and labor. Specifically, a 1% increase in capital raises GDP by 0.379% and a 1% increase in labor force raises GDP by 1.289%. This shows that capital and labor play a great role in the renewable energy-economicgrowthnexus. The short-run estimates also reveal positive impacts of capital and labor on economicgrowth. In short-run, a 1% increase in capital and labor leads to a raise of 0.173% and 0.549% on economicgrowth respectively.
In recent times, the world has experienced energy shortage. This phenomenon is due to the abrupt increase in global energy demand (Sekantsi & Okot, 2016; Tamba et al., 2017). This is because of the pivotal role energy (electricity) consumption plays in the stimulation of socioeconomic and economic activities of both developed and developing economies. The debate is still heated in the energy economics literature as to whether economicgrowth precedes energyconsumption or vice versa. However, much has been documented in the energyeconomic literature for decades, mostly in developed economies. Little is known about this very interesting dynamic interaction in developing economies, more precisely in Sub-Saharan Africa (SSA). Thus, this current study focuses on Nigeria, which is faced with a huge and alarming electricity deficit. Recent statistics for the case of Nigeria reveal that an overwhelming 95,500,000 inhabitants of the population are without electrification, with 55 per cent of the total population without access to electricity while 45 per cent reside in urban centres and 63 per cent in rural areas (CIA, 2018). Given this backdrop, the country relies on load shedding to meet its electricity demand. Further, statistics shows that electricity consumption rose from 13.72billion Kwh in 2000 to 24.57 billion KWh in 2018 (CIA, 2018).
middle and low income countries. Their findings reveal that energyconsumption is Granger cause of trade openness 5 . Nasreen and Anwer  investigated the relationship between trade openness and energyconsumption by incorporating oil prices and economicgrowth in energy demand function using data of Asian countries. In case of Thailand, they found that trade openness increases energyconsumption but statistically insignificant. Oil prices reduce energy demand in Thailand. Their panel causality analysis reveals that the feedback effect is found between trade openness and energyconsumption. Sbia et al.  examined the relationship between clean energy, foreign direct investment, trade openness, carbon emissions, and economicgrowth in case of UAE. They applied the ARDL bounds testing for long run and the VECM Granger causality to test the causality between the variables. They noted that foreign direct investment and trade openness are negatively linked to energyconsumption and the bidirectional causality exists between trade openness and energyconsumption. Farhani et al.  examined the relationship between natural gas consumption and economicgrowth by incorporating trade openness as potential determinant of gas consumption and economicgrowth in case of Tunisia. They found the existence of cointegration between the variables and trade openness Granger causes natural gas consumption. Shahbaz et al.  used Chinese time series data to investigate the relationship between economicgrowth, financial development, trade openness and energyconsumption. They noted that trade openness (measured by trade, exports and imports) Granger causes energy demand. Shahbaz et al.  used production function for Pakistan to examine the relationship between economicgrowth, natural gas consumption and exports. Their analysis indicated that natural gas consumption causes economicgrowth and
Kaker et al. (2011) applied production function to examine the relationship between economicgrowth, financial development and energyconsumption using Pakistani data. They concluded that neutrality hypothesis between financial development and economicgrowth exists but energyconsumption Granger causes financial development. Shahbaz and Lean, (2012) examined the impact of financial development on energyconsumption applying energy demand function in case of Tunisia. They concluded that financial development increases energy demand by boosting stock market development and stimulating real economic activity. The results show that financial development and energyconsumption Granger-cause each other. However, financial development impacts magnitude on energyconsumption is greater. In case of Malaysia, Tang and Tan (2014) investigated the relationship between financial development and energyconsumption by incorporating relative prices and foreign direct investment energy demand function. The empirical results reveal positive impact of economicgrowth, foreign direct investment and financial development on energyconsumption. Feedback hypothesis is found between financial development and energyconsumption, both in short and long runs. Islam et al. (2013) exposed that financial development and economicgrowth have positive impact on energyconsumption. They found bidirectional causality between financial development and energyconsumption in long run. In short run, financial development Granger causes energyconsumption. Shahbaz et al. (2013) investigated the production function by incorporating financial development and energyconsumption in case of China. They applied the ARDL bounds testing approach to cointegration and the VECM Granger causality to examine long run and causality relationship between the series. Their results indicated that energyconsumption and financial development exert positive impact on energyconsumption. They also noted that financial development is Granger cause of energyconsumption. Ozturk and Acaravci (2013) examine the causal relationship between financial development, trade, economicgrowth, energyconsumption and carbon emissions in Turkey for 1960–2007 period. The bounds F ‐ test for cointegration test yields evidence of a long-run relationship between variables. The results show that an increase in foreign trade to GDP ratio results an increase in per capita carbon emissions and financial development variable has no significant effect on per capita carbon emissions in the long- run. These results also support the validity of EKC hypothesis in the Turkish economy.
data. Second, as noticed before, the causal relationship between energyconsumption and economicgrowth has investigated in the most existing studies at the national or aggregate-level data and few empirical studies investigate on the energy-growth issue with focusing on industrial sector. Therefore, due to great differences in energy use observed across industries, it would be valuable to investigate the energy-growthnexus at the industrial level and may provide new insights. Third, to reach to robust energy conservation policy implications, we test the relationship between various forms of industrial energyconsumption (Diesel fuel, Natural Gas, Gasoline, Kerosene, LPG&LNG, Petroleum and Electricity) and economicgrowth by focusing on regional level data. The results of this study may have important implications for both regional policy makers and industries ownerships. Based on our results, the amount of natural gas and electricity consumption improve the manufacturing sector’s contribution to the regional growth in Iran. If these types of energy appear to be significant in explaining regional growth, then manufacturing industries should attention to expanding generation capacity and/or using advances technologies with a more efficient usage of natural gas and electricity.
The literature on Granger causality has grown considerably, following his seminal work in 1969, slowly during the first years and more rapidly in recent years. Granger causality test suggests which variables in the models have significant impacts on the future values of each of the variables in the system. Among recent applied studies, a significant amount of work has been devoted to addressing the above mentioned question of causality between energyconsumption and economicgrowth. This paper studies the time series properties of energyconsumption and GDP and reexamines the causality relationship between the two series in the top 10 emerging markets excluding China due to lack of data and G-7 countries 1 . Soytas and Sarı (2003) show that there is a bi-directional causality in Argentina, causality running from GDP to energyconsumption in Italy and Korea, and from energyconsumption to GDP in Turkey, France, Germany and Japan.
The previous studies on this subject maintaining different results depending to the country considered advance various explanations of their empirical findings: If the electricity usage determines economicgrowth; this indicates that the economy depends on energyconsumption, implying that a deficiency in the energy supply can have a negative impact on economicgrowth (e.g. Masih and Masih (1998), Asafu-Adjaye (2000) and Jumbe (2004)). In addition, if the causal mechanism is reversed (i.e. growth hypothesis), it suggests hat the considered economy is less dependent on energy. Thus, implementing energy-saving policies may have little effect or have no impact on income (e.g. Jumbe, 2004). Further, a lack of causality in one direction or the other, or the neutrality hypothesis (e.g. Yu and Choi, 1985) means that the energy saving policies do not affect economicgrowth. In this case, a policy of energy saving can be done without damaging economic dynamics, development and growth.
(2012) emphasized the role that energy has played in economicgrowth and the limit to continued growth given our reliance on fossil fuels. Stern (2010) opined that when energy is scarce it impos- es a strong constraint on the growth of the econo- my but when energy is abundant its effect on eco- nomic growth is much reduced. This explains the industrial revolution as a releasing of the constraints on economicgrowth due to the development of methods of using coal and the discovery of new fos- sil fuel resources. Also it was found that the elastici- ty of substitution between a capital-labour aggre- gate and energy is less than unity, which implies that when energy services are scarce they strongly constrain output growth resulting in a low income steady-state. When energy services are abundant the economy exhibits the behaviour of the ‘modern growth regime’ with the Solow model as a limiting case (Stern, and Kander, 2012).
The second issue in panel data analysis is to decide whether or not the same coefficients are applied to each individual. It is a standard F test, based on the comparison of a model obtained for the full sample and a model based on the estimation of an equation for each individual. The F test is valid for the case where the cross section dimension (N) is relatively small and the time dimension (T ) of panel is large; the explanatory variables are strictly exogenous; and the error variances are homoscedastic. In the case where (N, T ) −→ ∞ , (Pesaran and Yamagata, 2008) propose a ˜ ∆ test, without any restric- tion on the relative expansion rate of N and T when the error terms are normally distributed. The ˜ ∆ test approach includes two steps. First step is to compute the following statistic:
The first step of the analytical approach is to study the stationarity of the variables used in our study in order to avoid misleading regressions. Indeed, in the presence of unit roots (cases of non-stationary series), the statistical properties of estimation methods are no longer valid (Sims et al, 1990). Accordingly, we study the stationarity of each variable using the Augmented Dickey-Fuller unit root test (Dickey and Fuller, 1981) ADF, as well as Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (1992) (KPSS) unit root tests. By definition, a variable is stationary when it contains neither tendency nor seasonality. In order to investigate the existence of long run relationship between financial development, economicgrowth and energyconsumption sources, we use the autoregressive distributed lag (ARDL) bounds testing approach to cointegration developed by Pesaran et al. (2001). In fact, the Approach has numerous econometric advantages compared to other methods of cointegration test such as Johansen cointegration test (for I(1) variables). First, ARDL bounds testing approach is suitable for small sample size. Second, this approach does not need all variables to be integrated to the same order I(1) meaning that it is suitable for I(0) or I(1) variables also in the case of mixture of I(0) and I(1) variables. Finally, ARDL approach assumes all variables to be endogenous estimating simultaneously the short-run and long-run dynamics of the model. However, this approach is not applicable for variables being integrated of order 2, I(2).
This belief is generally described as the ‘neutrality hypothesis’ as propounded by Yu and Choi (1985). Their belief rests on the premise that energyconsumption represents a much smaller portion than labour and capital in the production process and thus, the gross domestic process (GDP) and that this portion is so small that it should not affect economicgrowth. Paradoxically, while Nigeria is blessed with an abundance of energy resources, particularly oil; its people and economy suffer from scarcity of electricity. This is manifested by the epileptic supply of electricity and continuous shortage of most petroleum products. This trend calls for an enquiry to find out the nature of relationship between electricity consumption and economicgrowth in the Nigerian context. The nature of the causal relationship would prove extremely useful because an economy heavily dependent on electricity, government policies on energy conservation could prove to have adverse effects on economicgrowth. This rest of study is organized into four sections beginning with section two which reviews some literature in the area of study whilst section three involves the methodology adopted for the study. Section four is the analysis and presentation of data. The concluding section summarizes the findings of the study and provides some policy recommendations.
Meanwhile, in terms of energy formation, Jacobsen (2007) did the input-output tables for Malaysia in 2000 and the energy goods domestically supplied as well as imported. His study took three energy commodities/sectors in the Malaysia’s input- output tables. According to Table 2, we extract that crude petrol, natural gas, and coal as the main contributors for output formation, accounted for RM 46 billion, meanwhile electricity and gas is a small amount, around RM 15 billion. Interestingly, those three energy commodities/sectors are mainly impetus for Malaysian growth since they are used to supply either for domestic intermediate or domestic final goods. In other words, Malaysian economicgrowth is highly dependence on the energyconsumption, particularly crude oil, natural gas, coal, petrol, and coal product. This phenomenon was explained by Ang (2008) who explores long run relationship and causality among output, energyconsumption and pollutant emissions for Malaysia over the period 1971-1999. He found pollution and energyconsumption positively affect output in the long run. The causality runs from economicgrowth to energyconsumptiongrowth, both in the short and the long- run. More specifically, Shaari et al (2012) concluded that there is a long-run relationship between energyconsumption and GDP. However, once the granger causality model is used, the oil and coal consumption do not granger cause economicgrowth and vice versa. A unidirectional relationship exists between gas and economicgrowth in Malaysia.
Figure 2 above shows the evolution of oil consumption in transport and the economicgrowth of Cameroon from 1975 to 2014. We can observe that these two variables show similar long-run trends characterized by upward trends, with slopes of 0.0248 for the logarithm of GDP and 0.0271 for the logarithm of oil consumption in transport. Also, there is an equilibrium relationship or plausible co-integration between these two series. Moreover, statistical analysis confirms a strong positive correlation between oil consumption in transport and GDP (Figure 3). This correlation is not perfect, and the points on the graph do not completely align with the fitting line. However, the scatter plot is fairly flat, with the adjustment coefficient of 92.18%. Furthermore, a joint analysis of the growth rates of oil consumption in transport and GDP growth shows that the two variables evolve in synchronism (Figure 4). Thus, Figure 4 shows three distinct periods. The first was from 1975-1985, which corresponds to the period when fluctuations of greater amplitudes were recorded. They are positive. Also, the fluctuations in the growth of oil consumption in transport are broader than those of economicgrowth. During the second period of 1986- 1994, the fluctuations are smaller, with the particularity of being relatively negative, especially those of GDP. During the third period, 1995-2014, GDP fluctuations are positive but very flat compared to the consumption of oil in transport. This analysis may suggest that economicgrowth is responding to fluctuations in oil consumption in transport and vice versa. As a result, it is important to know whether oil consumption in transport cause economicgrowth or whether economicgrowth leads to more oil consumption.
Based on either the FMOLS or DOLS estimators, using renewable energy helps to reduce CO 2 emissions for Australia, Chile, Japan, Mexico, New Zealand, and Peru. The estimates unexpectedly confirm that consumption of renewable energy is positively related to CO 2 emissions for Malaysia and Vietnam, while no statistically significant effect is seen for Canada. Similarly, the use of alternative and nuclear energy is found to be negatively associated with CO 2 emissions in six of the nine countries, with Mexico, Malaysia and Japan being the exceptions. In general, using a cleaner source of energy, namely renewable, alternative and nuclear, has beneficial effects on the environment.
GDP in Ghana during 1970-2014 based on the Cobb-Douglas growth model. Unit root testing was conducted to depict the stationarity status of the data and the data series are non-stationary at level, hence necessitating the incorporation of first differencing. The time series data for the variables were found to be stationary at first differencing. The study found the existence of long-run equilibrium co-integration among output, labor, capital and electricity consumption. The VECM shows a likelihood of a long-run con- vergence with high speed of error correction. The Granger causality test indicates that there exists Granger causality running from GDP to electricity consumption implying that the conservation hypothesis is appropriate for the Ghanaian data. The policy im- plication is that electricity consumption is not a limiting factor to economicgrowth of Ghana. In other words, electricity consumption has no adverse impact on economicgrowth. Therefore, electricity conservation policy is favorable for the Ghanaian econo- my.