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 relationshipbetweenenergyconsumption 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.
This study has investigated the relationshipbetweenenergyconsumption and economicgrowth in Brazil during the period of 1980-2008. The co-integration test indicates a long-run equilibrium relationshipbetween variables, and energyconsumption appears to be real GDP elastic. This elas- ticity suggests that energyconsumption has a great positive influence on changes in income. The causality results from the error correction model reveal a unidirectional short-run causality from energyconsumption to economicgrowth and a bidirectional strong causality between them. These findings suggest that Brazil should adopt a dual strategy of increasing investment in energy infra- structure, and stepping up energy conservation policies to reduce any unnecessary waste of ener- gy, in order to avoid having a negative effect on economicgrowth by reducing energyconsumption. In contrast, energy conservation is expected to increase the efficient use of energy and, therefore, enhance economicgrowth.
Energy is increasingly becoming the main driver of sustainable economic development (Adebola & Shahbaz 2013 and Khobai and Le Roux 2017). The neoclassical economics is neutral about the impact of energy on economic development but energy is increasingly revealing its importance on livelihoods and as a result indirectly boosting economicgrowth. The oil embargo that took place in the 1970s prompted the policy makers to extensively investigate the relationshipbetweenenergyconsumption and economicgrowth (Ghosh 2009). Shahiduzaman and Alam (2012) stated that to the interest in the subject has mostly been motivated by the emission of greenhouse gases into the atmosphere which causes climate change. Therefore, to formulate environmental policies, it is important to recognise the role of energy on economicgrowth.
The final step in this study is to verify the direction of causality betweenenergyconsumption (Enuse_ pc) and economicgrowth (GDP_pc) using the Toda and Yamamoto causality test. The empirical results of Granger Causality test based on methodology is estimated through MWALD test and reported in Table 7. According to Toda Yamamota causality test “Enuse_pc does not Granger Cause GDP_pc” null hypothesis rejected and also “GDP_pc does not Granger Cause Enuse_pc” null hypothesis rejected. Consequently, there is observed bi-directional causality betweenenergyconsumption and economicgrowth. Our finding of bidirectional causality is the same with the findings of Apergis and Payne (2009) and Senturk and Sataf (2015) and differs that of Bildirici and Kayıkçı (2012) and Tang and Abosedra (2014), who found unidirectional causality running from energyconsumption to economicgrowth and differs Kalyoncu et al. (2013) result of no causal relationship and also, that of Hasanov et al. (2017) finding with causality running from gdp to energy consumption.This may be because of using different methods and periods.
Part 1 of this study is to compare the energyconsumption projections and economicgrowth in Turkey that was constructed more than 27 years ago with the observed data for the year of 2007. Part 2 of this paper presents a summary of Turkey’s energy sources. The main energy sources are shown as a table. Part 3 shows the growth rates and energyconsumption literature review. In Part 4, the relationshipbetweenenergyconsumption and economicgrowth is determined by the model. The actual GDP growth rates that are the principal determinants of energyconsumption are important over the long-term. In addition, the last section of this part of the paper provides an overview of the changing global energy environment and the resulting modifications in the projected use of energy that was expected over the 20-year interval ending in 2007. Part 4 presents the energyconsumption from 1970–2007 and compares them with the observed 2007 data (http://www.enerji.gov.tr/) for Turkey. The tables and figures in paper provide a detailed picture of the changing patterns of energyconsumption over the 20-year interval.
Recently, the relationshipbetweenenergyconsumption and economicgrowth has been extensively investigated in a non-stationary setting by using a Vector Error Correction Model (VECM) to test for Granger causality (Cheng and Lai 1997, Stern 2000, Narayan and Singh 2007, Ghosh 2009). For example, Cheng and Lai (1997) confirm the presence of a unidirectional Granger causality running from economicgrowth to energyconsumption for Taiwan in the period from 1955 to 1993. In a similar study, Dhungel (2008) found unidirectional causality running from per capita energyconsumption using Granger causality test to determine the relationshipbetweenenergyconsumption and economicgrowth in Nepal during 1980-2004. The same causal relationship is obtained by Narayan and Singh (2007) when applying a production function, in which they incorporate the labor factor as an additional component of the relationship on Fiji for the period from 1971 to 2002. Thure Traber (2008) expressed relationshipenergy and economicgrowth using Granger Causality results asserted that energy demand is likely to increase as long as we experience economicgrowth.
 tests the causal nexus between the use of energy and GDP in the United States for the period 1960-2005, employing Markov-switching vector autoregres- sive models. Results from the model show evidence of bi-directional Granger causality between the variables in the first regime, while there is no causality between the variables in the second regime. Another study, which focuses on the relation between volatility in energyconsumption and uncertain variations in real GDP product in the United Kingdom, based on Markov regime-switching modeling perspective is conducted by . By the findings developed through Markov regime-switching ARCH design, energyconsumption volatility has no significant co-existing and contemporaneous relation with Gross Domestic Product in the first (low-volatility) regime, however, in the second (high-vola- tility) regime there is an important positive relation between GDP volatility and energy usage volatility. , apply the momentum-threshold autoregressive (M- TAR) co-integration method to examine the long-term equilibrium relationshipbetween the growth of output and energy use, The results indicate that there is a nonlinear cointegration relationshipbetweenenergyconsumption and GDP ex- cept the residential sector in Taiwan.
This paper investigates the relationshipbetweenenergyconsumption and economicgrowth of Pakistan. A time series data has been used for the period of 1973-2006. GDP is taken as dependent variable and energyconsumption as independent variable. Augmented Dicky Fuller test has been used to check the stationary of the variables and both variables found stationary at level. The results of Granger causality test show uni- directional causality running from GDP to energyconsumption. The results of ordinary least squares test show positive relation between GDP and energyconsumption in Pakistan. One percent increase in energyconsumption will raise GDP by 1.23%. Diagnostic tests confirm that residuals are normally distributed, coefficients are stable and there is no ARCH effect. Pakistan economy is energy dependent. Shortage of energy means lower the economicgrowth of Pakistan. We should utilize our own sources to meet the needs of energy like by constructing biogas plants in villages and solar energy is also alternative source. This can reduce the dependency on foreign sources.
Our analysis of the relationshipbetweenenergyconsumption and economic activity is based on a sample of 25 OECD countries from 1981 to 2007 and uses recently developed panel-econometric methods. We explore an additional channel of causality by introducing energy prices. As energy prices have been neglected in many previous studies, the long-run parameters and the evidence of causality may be biased, see Masih and Masih (1997) and Asafu-Adjaye (2000). But in contrast to these two studies, we examine the original energy price index rather than the consumer price index (CPI) as a proxy. Income and price elasticities provide policy makers a suggestion of the extent to which prices need to increase, in the form of energy taxes, in order to reduce energyconsumption and the potential for the market to conserve energy (Lee and Lee, 2010). Additionally, energy companies need this information to design their demand management policies. But only a few papers have esti- mated income and price elasticities for energyconsumption in a panel framework. Furthermore, the long-run equilibrium relationship is studied in both directions, i.e. with either energyconsumption or real GDP as a dependent variable (Costantini and Martini, 2010).
In Russia Zhang (2011) also evaluated the causal relationship on the data period of 1990-2008, applied standard Granger Causality Test and found no causality in electricity consumption and economicgrowth. In more recent studies Shahbaz and Lean (2012) in Pakistan run causal relationship tests through the Vector Error Correction Model (VECM) & Granger Causality test for the period of 1972- 2000 and found bidirectional relationship in economicgrowth and electricity consumption. Behera (2015) applied Vector Autoregression on Indian data, Tang, Tan, and Ozturk (2016) applied co-integration on Vietnam data for the period of 1970-2011, and similarly, Tursoy and Resatoglu (2016) applied VAR & Granger Causality Test in Russia for the period of 1990-2011 Behera (2015) and Tursoy and Resatoglu (2016) found same results of bidirectionality, which concluded both electricity consumption & economicgrowth affects each other in respective countries whereas Tang et al. (2016) pointed out unidirectional relationship showing that electricity consumption affects economicgrowth.
This study examined the causal relationshipbetween electricity consumption and economicgrowth in Uganda during the period 1960–2014. Inasmuch as there have been similar studies done on the African continent on this relationship, none has been done in Uganda. The objectives of the study were threefold: 1) to estimate the short--run and long--run relationshipbetween electricity consumption and economicgrowth in Uganda; 2) to examine the direction of the causal relationship; and 3) to propose policies to guide future decision making of government. To achieve these objectives, the study adopted the Auto Regressive Distributed Lag bounds approach in analysing the level of relationship. In addition, the study used the pairwise Granger Causality testing procedures to determine the direction of causation between the study variables. Results from the study indicated that there is a valid long-run level relationshipbetween electricity consumption and economicgrowth. In addition, the pairwise Granger causality tests indicated that the relationship is unidirectional, running from electricity consumption to economicgrowth. Overall, the study found that energyconsumption spurs economicgrowth in Uganda. The government should fast-track and consolidate interventions in electricity generation with the view of sustaining the long-run electricity demand and consumption in Uganda. In the short run, investments to improve energy efficiency and reduce losses should make more electricity available for consumption.
This paper attempts to re-examine the relationshipbetweeneconomicgrowth and electricity consumption in India for the period 1971-72 – 2016-17 for the country as a whole and for the agricultural and industrial sectors separately. Using gross value added (GVA) and per capita net national product (NNP) as indicators of economicgrowth techniques like cointegration, error correction model and Granger causality tests are applied for the study. The results indicate that there is a long run positive relationshipbetweeneconomicgrowth and electricity consumption when GVA is the indicator of growth. However, the short run coefficients are not statistically significant. Per capita NNP does not have any long run relationship with per capita electricity consumption but there is a unidirectional Granger-cause from log per capita NNP to log per capita electricity consumption when lag length is three. There is unidirectional Granger-causality from log GVA to log electricity consumption in the agricultural sector also. For the industrial sector, however, neither variable Granger causes the other. The cross section analysis for thirty two states and union territories of India reveals that per capita net state domestic product (NSDP) positively and significantly affects per capita electricity consumption of states in each of the years from 2012-13 to 2016-17. But the responsiveness of electricity consumption with respect to NSDP declines over the years.
The International Energy Agency (IEA 2012) says that transport consumes 27% of global fossil energy and accounts for 22% of total carbon dioxide emissions. The IEA (2012) also notes that road transport energyconsumption rose from 0.7 billion tons of oil equivalent in 1976 to 1.8 billion tons in 2010. During the same period, the global energyconsumption and economicgrowth grew by 1.7% and 3.2%, respectively. In 2012, the IEA argued that the road share of transport energyconsumption in China and India grew from 39.6% and 42% to 77.3% and 88%, respectively. Both countries doubled their share, while in South Africa, road transport energyconsumption increased from 66.7% to 90.8% of total transport energyconsumption. For rail transport, the same source indicates that the share of rail transport in total transport energy usage decreased in three countries during that period. In China, the share grew from 42.3% to 6.9%, in India from 55% to 6.7%, and in South Africa from 31.4% to 2.6%. In that vein, road transport accounts for the highest percentage of transport energy in G7 countries, with 94.7% of total transport energy in Germany, 93.8% in France, and 92.7% in Italy and the United Kingdom. BP (2017) notes that MENA countries are home to more than half the world’s crude oil reserves and more than a third of its natural gas. Their production reached more than 20 million barrels a day in 2014, and their per capita energyconsumption is forecast to overtake North America by 2035. MENA countries have an increasing consumption of natural gas (+3.5%), oil (+0.9%), nuclear energy (+75.3%) and renewable energy (+42%) and decreasing hydroelectric (-20.5%) and coal (-9.5%) consumption. The World Energy Council (2011) indicates that Middle East countries consume about 0.939 million barrels of gasoline per day and about 1.082 million barrels of diesel per day. This consumption is expected to triple by 2050. Similarly, fossil energyconsumption displays the same trend for the North African countries, where transport accounts for the highest consumption. For example, in Egypt, total transport energyconsumption increased 4.8% annually for the1981-2013 period. Gasoline and diesel fuel have the largest average annual growth rates, at 5% and 5.2% (ESCWA 2014) 1 . In Tunisia, transport accounted for about 26.9% of total energyconsumption and about 30% of total carbon emissions in 2010; in particular, road transport consumed around 70% of total transport energyconsumption (IEA 2012).
A second form of economic modelling is computable general equilibrium (CGE) modelling. Much CGE work was pioneered by the Monash Group. Mai, Adams and Dixon (2009) applied their model to China’s demand for energy. The Monash group have produced numerous studies using CGE analysis of China’s economy (for example Mai, Dixon and Rimmer 2010). Grossman and Krueger applied CGE models to environmental issues in their studies of the environmental impacts of NAFTA (Grossman & Krueger, 1991). The G-Cubed model built by McKibbin has been used to study the relationshipbetweeneconomicgrowth and energy use (and GHG emissions) (McKibbin, 2006). While analysis using CGE models has a number of strengths, their applicability, as with any tool, depends on the objectives of the practitioner. CGE models emphasise the role of prices in determining outcomes, which is not the focus of this thesis. In addition, the results tend to be presented in the form of, “the change in price of x has caused demand for coal to change by $10 billion dollars a year…” (Layman, 2004). To the extent that the approach lends itself to the present study, the benefits that can be gleaned from a CGE approach are not sufficiently greater than those that can be achieved at far less cost using the much simpler approach discussed below: decomposition analysis. Applying the principle of Occam’s Razor, the simpler approach is preferred.
In addition to renewable and non-renewable energy, the study included variables such as TFP, Human capital and prices in a multivariate function. The neutral hypothesis is confirmed in South Africa since there is no causal relation between non-renewable energyconsumption and economicgrowth which may be as a result of the relative size of the budget allocated to energy. This supports the findings of Payne (2009).Payne (2009) uses the Toda-Yamamoto procedures to test for Granger causality with a production function framework for the US from 1949 to 2006 and finds no relation between renewable energy and growth. Apergis and Payne (2011) test the causality between renewable energy and growth for 20 OECD countries and find a feedback relation in the long-run which confirms the findings between renewable energy and growth in Nigeria. This finding is also supported by Sadorsky (2009) who finds evidence of bidirectional relation between renewable energy and growth for 18 emerging economies from 1994 to 2003.Similarly to the findings on renewable energy for Ghana, Bowden and Payne (2010) find a unidirectional causality from renewable energy to growth. The findings suggest that Nigeria, Ghana and Algeria should invest more in renewable energy since renewable energyconsumption leads to growth in the long run.
This study investigated the relationshipbetweeneconomicgrowth, and energyconsumption in Malaysia using annual time series data for the period of 1976 – 2014. ARDL cointegration method developed by Shin et al. (2014) was applied and we tested the causal relationshipbetween the variables using VECM, VDCs and IRF tests. The empirical results provide evidence that the variables are asymmetrically cointegrated. The finding of this study is crucial as it suggests that a change in the energyconsumption will affect the economicgrowth in Malaysia and the impact of a reduction in energyconsumption will have a larger effect compared to an increase in energyconsumption. Policymakers in Malaysia can influence the economicgrowth in Malaysia by controlling the energyconsumption of the nation. Government incentives in encouraging energy saving behavior and development of alternate source of energy can lead to sustained economicgrowth without impacting the production level of the nation.
With the processing of urbanization in China, energyconsumption will change quickly. At the same time, power industry is a pillar industry, and electricity plays a very important role on the sustainable healthy coordinative and rapid development of its economy and society. Thus, more and more attention has been paid to analyze the dynamic relationshipbetween electricity consumption and economicgrowth has caused widespread interests and dispute in both academia and industry recently. At present, the key point at issue is that whether electricity consumption Granger causes economicgrowth, or in the opposite way. The conclusions vary on different countries or regions at different periods. This is because different countries have different economic development policies, even if the same country would have different economic policies at different periods.
Many studies have recently focused on investigating the causal relationshipbetween electricity consumption and economicgrowth in developing countries to confirm national electricity policies as shown in Table 1. However, we find that such studies lead to mixed results that in turn give rise to some heated discussions regarding the effect of electricity conservation policies on economicgrowth in developing countries. For example, Yoo (2005), Jumbe (2004), Morimoto and Hope (2004) and Yang (2000) found that bi-directional causality existed between electricity consumption and economicgrowth in Korea, Malawi, Bangladesh and Taiwan. On the other hand, Shiu and Lam (2004) showed that there was uni-directional causality running from electricity consumption to economicgrowth in China without any feedback effect, as did Altinay and Karagol (2005), Wolde-Rufael (2004), Aqeel and Butt(2001) and Narayan and Singh (in press) and in the case of Turkey, Shanghai, Pakistan and Fiji. Moreover, Ghosh (2002) found evidence of unidirectional causality running from economicgrowth to electricity consumption in India. In addition to these, Murry and Nan (1996) and Wolde-Rufael (2006) found that there are diverse causality betweeneconomicgrowth and electricity consumption in different countries.
This study examines the Effect of EnergyConsumption on EconomicGrowth in Cameroon using Generalised Method of Moments technique. The findings of this study reveal the existence of a positive and significant relationshipbetweenenergyconsumption and economicgrowth. This study therefore recommends that companies in charge of oil refining and transportation should increase petroleum supply around the country by connecting the major towns with petroleum pipelines. But cleaner sources of energy should be used so as to curb the effects of climate change which results from the consumption of fossil fuels. Energy infrastructures should be Sustain and enhance. This does not only involve good maintenance practices of existing energy infrastructure but it also deals with ensuring that there is increase in such infrastructure through the issuance of licenses to the private sector for operation of such facilities and by reducing regulatory barriers even to long term capacity contracting. Also, natural gas infrastructures should be constructed and installed throughout the country. Availability of such facilities will increase the gas production and consumption and possibly growth.
By using the data for the period 1955 to 1996 for Pakistan, Aqeel and Butt (2001) concluded that economicgrowth causes total energyconsumption. The study further investigated that economicgrowth leads to growth in petroleum consumption. On the other hand, in the case of gas sector, neither economicgrowth nor gas consumption affects each other. In power sector, electricity consumption leads to economicgrowth. Lee (2005) tested the cross sectional and time series data of 18 developing countries to find the relationshipbetweenenergyconsumption and GDP. He concluded that energyconsumption Granger causes GDP. Asafu (2000) found a unidirectional Granger causality from energy to income in India and Indonesia while bi directional causality betweenenergy an income in the case Thailand and Philippines. By using a data for three SAARC countries, Imran and Masood (2010) found a long run relationshipbetweeneconomicgrowth and energyconsumption and a unidirectional causality from energyconsumption to economicgrowth but no causality found in short run. Jumble (2004) found that the causality running from electricity consumption to the income in the case of Turkey.