Looking at the strength of the economy and resources, ASEAN is on the right path to be back seen as the future engine of growth in Asia as well as the world. Therefore, identifying and managing the relationship between economicgrowth and energy consumption is very crucial in understanding the economicgrowth path in the future and living standard of its population. Based on the analysis of trends data on GDP and electricityconsumption for ASEAN for the past three decades, it is apparent that the continuous increase in electricityconsumption is quite consistent with GDP. The significant rise in demand and virtual dependence on energy, especially electricity is due to technology driven lifestyles of the twenty- first century, further makes an inquiry into mechanisms linking these key variables a timely one. Further studies on ASEAN as a whole are needed because the characteristics of ASEAN are different from other regions, even varies among ASEANcountries. According to IEA (2015), the inherent differences among ASEANcountries have important implications for the different power systems in terms of markets (pricing, impact of subsidies), governance frameworks (institutions, policies), electricity security (national resources, electrification, emergency), as well as region-wide initiatives, at both individual country and regional levels.
6 developed by Granger (1969) to examine the relationship between electricityconsumption and economicgrowth using data from 15 countries from 1970 to 1990. They found neutral effects between both variables in the cases of India, the Philippines, and Zambia. Furthermore, their analysis indicates that the conservation hypothesis is valid for Colombia, ElSalvador, Indonesia, and Kenya, whereas the growth effect is found in Mexico, Canada, Hong Kong, Pakistan, Singapore, Turkey, Malaysia, and South Korea. Wolde-Rufael (2006) applied the bounds testing approach developed by Pesaran et al. (2001) as well as the causality developed by Toda and Yamamoto (1995) to examine cointegration and causality between electricityconsumption and economicgrowth in 17 African countries. The results reveal that economicgrowth causes electricityconsumption in 6 countries (Cameroon, Ghana, Nigeria, Senegal, Zambia, Zimbabwe), whereas electricityconsumption causes economicgrowth in 3 countries (Benin, Republic of Congo, Tunisia), and the feedback effect exists between both variables in 3 countries (Egypt, Gabon, Morocco) 3 . Yoo (2006) investigated the direction ofthe causal association between electricityconsumption and economicgrowth for ASEANcountries and reported a feedback effect for Malaysia and Singapore and that economicgrowth causes electricityconsumption in Indonesia and Thailand. In the case of the OPEC region, Squalli (2007) employed the bounds testing and causality approaches developed by Pesaran et al. (2001) and Toda and Yamamoto (1995), respectively, to examine cointegration and causality between electricityconsumption and economicgrowth. The causality results indicate the dependence of economicgrowth
Electricity demand is driven by the increasing modernisation of economies and industrialisation opportunities. It is regarded as a necessary factor for infrastructural development and the increasing standard of living (Masuduzzaman 2013). Due to the importance of electricityconsumption on economicgrowth and development, the causal relationship between energy consumption and economicgrowth has been investigated by many researchers over past decades. In Bangladesh, Ahamad and Islam (2011) and Mozumder and Marathe (2007) established that electricityconsumption and economicgrowth are co-integrated. Ahmad and Islam (2011) and Mozumder and Marathe (2007) found bidirectional causality flowing between electricity c onsumption per capita to GDP per capita and economicgrowth. Masuduzzaman’s (2013) research focused on Bangladesh and validated a unidirectional causality flowing from economicgrowth and electricityconsumption to investment was found in the long term. The results imply that economicgrowth is driven by electricityconsumption and investment in the long term. Adebola and Shahbaz (2013) undertook a study for Angola for the period 1971 to 2009 and their findings suggested the existence of long term co-integration between electricityconsumption, economicgrowth and urbanisation. The results further illustrated bidirectional causality between electricityconsumption and economicgrowth. This implies that electricity is important for economicgrowth in Angola. Therefore, policies geared towards improvement of the electricity industry should be taken into consideration. Adebola, Shahbaz and Shahzad (2016) found that electricityconsumption boots economicgrowth in Angola and established bidirectional causality flowing between economicgrowth and electricityconsumption.
Aims of the study were to critically examine the extent to which electricityconsumption influences economicgrowth in Ghana and also determine, if it is electricityconsumption that causes economicgrowth in Ghana or otherwise. The study employed Augmented Dickey-Fuller test, Cointegration test, Vector Error Correction Model and Granger Causality test. The study revealed that, in the long term, a hundred percent increase in electricity power consumption will cause real gross domestic product per capita to increase by approximately fifty-two percent. However, in the short run, electricityconsumption negatively affects real gross domestic product per capita. The study again revealed that unidirectional causality run from electricityconsumption to economicgrowth meaning that any policy actions taken to affect the smooth consumption of electricity in Ghana will definitely affect her gross domestic product per capita. Therefore, the current load shedding policy due to low supply of electricity will definitely affect the Ghanaian economy negatively, that is lower production levels, high inflation, and high rates of unemployment and lower standard of living. Therefore, the government of Ghana should invest massively into electricity infrastructure and conservation measures to meet the needs of the various sectors of the Ghanaian economy.
However, the majority of empirical studies have come up with mixed and ambiguous results. For example, Masih & Masih (1996), Erol & Yu (1987) and Cheng & Lai (1997) find that there is positive and unidirectional causality running from income to electricityconsumption where the country does not rely on electricityconsumption for economic development. The country thus can adopt energy preservation policies without any harmful effect on economicgrowth. On the other hand, several studies such as by Asafu-Adjaye (2000), Yang (2000), and Glasure & Lee B (1997) observed that there is a unidirectional causality between electricityconsumption to income. Thus, it is confirmed that the country is highly dependent on energy consumption for economicgrowth. As a result, energy preservation policies may cause harm and conflict with economicgrowth (Narayan & Singh, 2007). Many works of literature have studied the causal relationship between these two variables, particularly in developed economies. However, there are only a few studies that have been conducted for emerging markets, particularly in the context of Malaysia. Therefore, to contribute to the existing literature, this paper attempts to examine the long-run relationship between electricityconsumption and economicgrowth in Malaysia.
Another reason would be that Vietnam has been in its early period of development, and most people have relatively low income. Annual per capita GDP in 2010 (at constant price) was USD 712; percentage of the poor was 9.5%, and many people just got out of the national poverty line; nearly 68.1% of population located in rural areas (General Statistics Office, 2011). So when income increases, individuals or households try to get their basic needs rather than electricity-intensive goods at least in the short-run. Moreover, rural economy is based on agricultural production, so expansions of this production due to an increase in income would not have significant effects on electricityconsumption, at least in the short-run. These characteristics would explain that economicgrowth does not statistically affect electricityconsumption in the short-run in Vietnam.
During the past few years, numerous studies have been conducted to examine the relationship between electricityconsumption and economicgrowth of an economy. So far, it has been found that there is a strong relationship between electricityconsumption and economicgrowth. Ferguson et al. (2002) 1 has studied the issue in over 100 countries and found that there is a strong correlation between electricityconsumption and economicgrowth. However, the existence of strong relationships does not necessarily imply a causal relationship 2 . The electricityconsumption in Pakistan has been by and large on a rise throughout the economic history of the country. Aqeel and Butt (2001) 3 have examined a unidirectional causal relationship running from electricityconsumption to economicgrowth elucidating that rise in electricityconsumption leads towards higher economicgrowth. However during the last decade, the economy of Pakistan has faced immense fluctuations. It has recorded a growth rate of 9 percent during the fiscal year 2004-05, as well as a growth rate of 2.4 percent in the fiscal year 2008-09 4 . On the other hand, the electricityconsumption has increased at a more or less persistent rate of 6 percent during 1998-2007 5 . The terrorism and political turmoil stricken country has been facing lowered economicgrowth rates amid to the global meltdown. Likewise, the government’s inability to add to the installed capacity of the power generation sector has given rise to a severe energy crisis. The power sector recorded an increase of 53 percent in electricity generation between 1994 and 1999 (from 11,320MW to 17,400MW) but this increase was reduced to a mere 12 percent between 1999 and 2007 (from 17,400MW to 19,420MW). There has been no significant increase in the installed capacity since then and it is reported to stand at 19,575MW in March 2009 6 . The actual electricity generation from an installed capacity of 19,420MW is 15,903MW. Whereas, the demand for electricity varies between 17,000-19,000MW depending on the seasonal variations, giving rise to a shortage of 3000-4000MW. 7 According to a statement issued by the Government of Pakistan, the load shedding is causing a loss of Rs.219 billion per annum along with a loss of 400,000 jobs and exports worth Rs.75 billion. 8
Given the fact that bivariate models are employed in these studies, the studies may lose important variable(s) and obtain biased results. Therefore, some of the studies investigate electricityconsumption-growth nexus by adopting multivariate causality analysis to prevent the omitted variable bias. For instance, Ozturk (2010) provided a survey of the literature to show the relationship between energy consumption and economicgrowth; electricityconsumption and economicgrowth causality nexus. There are some other researchers who have highlighted this relation (see (Iwata, 2010; Wang, 2011)). Shahbaz (2014) studied the interrelationship among FDI, electricityconsumption, and CO2 in Bangladesh. Hamdi (2014) employed the ARDL and VECM models to investigate the relationship between economicgrowth, foreign direct investment (FDI), and electricityconsumption in Bahrain. Their result suggested unidirectional causal relationships run from FDI and electricityconsumption to economicgrowth. Their result found that FDI and trade openness have a positive impact on energy pollutants. However, different researches have utilized time series models and Granger causality analysis to test the relationship between electricityconsumption (ELC) and economicgrowth in different countries. Some studies have been based on the VAR model (e.g., (Yang, 2000; Aqueel, 2001; Ghosh, 2002; Yoo, 2006; Huang, 2008)). In addition, several studies have been used the VEC model (see, (Bekhet and Othman, 2001; Jumbe, 2004; Shiu and Lam, 2004; Chen, 2007; Yuan, 2008; Narayan and Smyth, 2009; Yoo and Kwak, 2010; Odhiambo, 2011; Lee and Chang, 2008)). The following group of studies has employed the ARDL model, for instance, Fatai (2004); Squalli (2007); Ouédraogo (2010); Narayan and Smyth (2009); Narayan and Smyth (2007); Tang (2009).
Nigeria has struggled to provide electricity to its large population ever since independence. According to Nigerian Electric Power Authority (NEPA), the Niger Dam has the maximum capacity to generate 5,900 megawatts of electricity per day which falls far below the average national consumption rate of 10,000 megawatts per day. This has compelled NEPA to ration electric power supply over the years. The inability to satisfy the domestic and, to a large extent, industrial needs for electricity is reported to have had debilitating impact on the growth potentials of the Nigerian economy (World Bank, 1991). Even so, the demand for electricity, according to NEPA, is projected to increase from 5,746 megawatts in 2005 to nearly 297,900 megawatts by the end of 2030. This implies that NEPA needs to add approximately 11,686 megawatts of electricity to its stock each year in order to match this projection.
Specialization. David Ricardo’s concept of comparative advantage suggests that through opening trade countries would achieve gains (Alhajhoj, 2007). His model suggests an export-led growth type of framework, where each country can optimize its profits through specializing in the production of a single product. The specialization in activities in which a country has comparative advantage can lead to greater allocative efficiency. Through exchange, each of the countries would benefit from the better quality of the traded goods and also realize profits due to the weak competition in the chosen product or service of specialization. This way both nations would be better off (Borisova, 2013). The trade theory argues that the more a country becomes involved in international markets, the more specialized it becomes (Ali et al., 1991). Studies, such as Alhajhoj (2007) confirmed the export provoked growth in Saudi Arabia from 1970 to 2005. Thornton (1996) has also found empirical evidence for the causality of exports towards growth for Mexico in the years between 1895 and 1992.
Fiscal policy impacts may vary by time horizon, so that investigation of fiscal policy requires recognising that short-run and medium-run examination inspect the consequences of policy under the presumption of unaltered potential output. The medium-run analysis assesses the impact of changes in money related assets which makes the issue of how the spending shortfall is finance. Ultimately, the long-run analysis examines the effects of fiscal policy on an economy’s rate of growth over time consequently permits technology, capital, and labour force to change .  findings indicate that government expenditure has a negative effect on the economicgrowth of Malaysia during the period 1970–2014 with Ordinary Least Squares (OLS) technique.  expounds that there is a long- term relationships exist between national products and government development expenditure. Overall, the estimation analysis of ARDL's model for Wagner’s law shows that the national product factor is still relevant in influencing government development expenditure in Malaysia.
The energy industry contributes to economic development in two ways. First, energy is an important sector in its own right, which creates jobs and value, by extracting, transforming and distributing energy goods and services throughout the economy. Secondly, energy underpins the rest of the economy. Energy is an input for nearly all goods and services. In many countries, the flow of energy is usually taken for granted. However, price shocks and supply interruptions affect the whole economic set-up. For countries such as Uganda, which face chronic power (electricity) shortages, continuous disruptions take a heavy toll on economic activity. Electricity, for example, is critical in the delivery of basic social services like education and health. Electricity also helps to power machines that support income-generating activities (for instance pumping water for agriculture, food processing, and light manufacturing). Lack of modern energy services in rural areas limits the willingness of professionals (teachers, doctors, nurses,) to live and work in these areas, further limiting services and opportunities to local populations. There is strong evidence linking availability of energy and social economic development.
Results of the weighted symmetric ADF test (ADF-WS) and the generalized least squares version of the Dickey-Fuller test (ADF-GLS) are presented in table no. 4. The null hypothesis is unit root and the alternative hypothesis is level stationarity for both tests. The Dickey-Fuller regressions include an intercept and a linear trend in the levels, and include an intercept in the first differences. The numbers of optimal lags are based on SBC. 95% simulated critical values for 36 observations computed by stochastic simulations. The results indicate that electricityconsumption per capita and real GDP per capita are I(1) while employment ratio is I(0). Thus we can confidently apply the ARDL methodology to our model.
ECM represents the one period lagged error-term derived from the cointegration vector and 's are serially independent with mean zero and finite covariance matrix. From the equations (10) and (11) given the use of a VEC and VAR structure, variables are treated as endogenous variables. The F test is applied here to examine the direction of any causal relationship between the variables. The electricityconsumption does not Granger cause economicgrowth in the short run, if and only if all the coefficients 21k ‟s k are not significantly different from zero in equations (10) and (11). Similarly the economicgrowth does not Granger cause electricityconsumption in the short run if and only if all the coefficients 12k ‟s k are not significantly different from zero in equations (10) and (11). There are referred to as the short-run Granger causality test. The coefficients on the ECM represent how fast deviations from the long-run equilibrium are eliminated. Another channel of causality can be studied by testing the
After establishing that economicgrowth is linked in the long-run with energy consumption, price index, labor and capital, we need to examine the causality between the five variables. Panels A, B and C of Table 9 report the results of the short-run and long-run Granger- causality tests for each panel data set. The optimal lag structure of two years is chosen using the Schwarz Bayesian Criterion. In panel A which includes all countries of our sample, Eq. (14a) shows that energy consumption, labor force and capital have a positive and statistically significant impact in the short-run on economicgrowth whereas price index has negative impact on economicgrowth. The sum of the lagged coefficients indicates that energy consumption (0.337) has greater impact on real GDP than labor force (0.279) and less than real gross fixed capital formation (0.413). 17 This highlights the importance of energy in the economicgrowth process in African countries. Moreover, the error correction term is statistically significant at 5% and denotes the speed of adjustment to long-run equilibrium. In term of Eq. (14b), it appears that economicgrowth and capital have positive impact on energy consumption, whereas, labor has no impact on energy consumption. On the other hand, the impact of price index is negative in the short-run. Then, there is complementarity between energy usage and capital, and substitutability between price index and energy consumption. The statistically significance at 1% of the error correction term suggests that energy consumption responds to deviations from long-run equilibrium. In regards to Eq. (14c), it is not surprising that energy consumption has positive impact on price index, and the other variables are not significant. There is also no evidence for long-run adjustment in price index, because the error correction term is statistically insignificant. With respect to Eq. (14d), both real GDP and capital have a positive and statistically significant impact on labor in the short- run, while the impact of energy is statistically insignificant. Finally, in Eq. (14e), real GDP and energy consumption have a positive and significant impact on capital, whereas price index have negative impact and labor is statistically insignificant. In terms of the long-run dynamics, based on the statistical significance of the error correction terms from Eqs. (14d)- (14e), capital and the labor force each responds to deviations from long-run equilibrium. Overall, the relationship between energy consumption and economicgrowth is characterized by bidirectional causality, in both the short and long-run.
This study examines whether energy consumption in BRICS countries is a determinant of economicgrowth. BRIC that is (Brazil, Russia, India, China), the initials of Brazil, Russia, India and China, was first used in conjunction with the research report, Building Better Global Economic BRICs, prepared by Goldman Sachs chairman (O’neil, 2011). In addition to being the fastest-growing "emerging markets" in the world, the four countries in question have many common characteristics such as having large surface area, overcrowding and rapid and steady growth in recent years. These countries, which encompass 25% of the world's surface area and 40% of the world's population, are rapidly developing as global market economies, and with this rising momentum they will be able to leave behind G7 countries (Canada, France, Germany, Italy, Japan, USA) (Narin and Kutluay, 2013). However, in recent years it was argued that new countries, defined as emerging markets should be included in the BRIC and BRIC after the inclusion of South Africa (South Africa) in April 2011, Expanded to BRICS (Kaya and Yalçinkaya, 2016).
8 Where u it are residual terms and assumed to be identically, independently and normally distributed. The statistical significance of lagged error term i.e. ECT t 1 further validates the established long run relationship between the variables. The estimates of ECT t 1 also show the speed of convergence from short run towards long run equilibrium path in all models. The VECM is superior to test the causal relation once series are cointegrated and causality must be found at least from one direction. Further, VECM helps to distinguish between short-and-long run causal relationships. The VECM is also used to detect causality in long run, short run and joint i.e. short-and-long runs respectively in the following three possible ways: The statistical significance of estimate of lagged error term i.e. ECT t 1 with negative sign confirms the existence of long run causal relation using the t-statistic. Short run causality is indicated by the joint 2 statistical significance of the estimates of first difference lagged independent variables. For example, the significance of 22 , i 0 i implies that electricityconsumption Granger-causes economicgrowth and causality runs from economicgrowth to electricityconsumption can be inferred by the significance of 22 , i 0 i . The same inference can be drawn for rest of causality hypotheses. Finally, we use Wald or F-test to test the joint significance of estimates of lagged terms of independent variables and error correction term. This further confirms the existence of short-and-long run causality relations (Shahbaz et al. 2011) and known as measure of strong Granger-causality (Oh and Lee, 2004).