energyconsumption and economicgrowth has begun to be tested empirically. Narayan and Smyth (2008) reported that energyconsumption and capital stock affected economicgrowth positively for the G7countries both in the short and long run. Tugcu et al. (2012) used the ARDL bounds testing and Hatemi-J causalitytest and found that the growth hypothesis was valid only in Japan in terms of nonrenewableenergyconsumption. They also confirmed the validity of the conservation hypothesis for Germany and the feedback hypothesis for the UK and Japan in terms of renewableenergyconsumption. Chang et al. (2015) examined the causalityrelationshipbetweenrenewableenergyconsumption and economicgrowth and confirmed the validity of the conservation hypothesis for France and the UK, and the growth hypothesis for Germany and Japan. Mutascu (2016) also examined the causalityrelationshipbetweenenergyconsumption and economicgrowth and found that the feedback hypothesis was valid in Canada, Japan, and the United States while the conservation hypothesis was valid in France and Germany. Destek and Okumus (2017) divided energyconsumption into the consumption of oil, coal and natural gas and examined their relationship with economicgrowth. Their findings revealed that the growth hypothesis was valid in Italy, Japan and the United States for oil consumption, the conservation hypothesis was valid in the UK, and the feedback hypothesis was valid in Germany. The growth hypothesis was valid in Italy, Japan, the UK and the United States, and the feedback hypothesis was valid in Germany in terms of natural gas consumption. Finally, the validity of the growth hypothesis was confirmed for Canada, and the conservation hypothesis was confirmed in the United States for the relationshipbetween coal consumption and economicgrowth.
Previous empirical studies have either assumed linearity in the context of cointegration long- run relationshipbetweenrenewableenergyconsumption and economicgrowth or provided evidence in favor of nonlinearity relying on asymmetric Granger causality testing (Destek, 2016). However, these studies do not explicitly account for the possibility of nonlinearity in the cointegration system. This could result from an asymmetric reaction to positive and negative shocks and could be accommodated by the application of various types of regime- switching models. One way to do so relies in solely allowing for nonlinearity in the error correction mechanism by the application of either a threshold ECM proposed by Balke and Fomby (1997), a Markov-Switching ECM of Psaradakis et al. (2004) or a smooth transition regression ECM developed by Kapetanios et al. (2006). However, a general caveat of this kind of models is the common assumption that the underlying cointegrating relationship is represented by a linear combination of the nonstationary variables. But this might be excessively too restrictive since for the same reasons claimed for the error correction mechanism, the long-run cointegration relationship itself could be subject to asymmetry or nonlinearity.
countries are also estimated by considering cross-sectional and time-dimensions of the panel. This panel analysis has significant power as compared to time-series approaches. The empirical analysis is very useful for policy decisions because, in the process of economicgrowth, it indicates long-term demand for renewable (non-renewable) energy sources. In doing so, we applied cross-sectional dependence, Pedroni cointegration, heterogeneous panelcausality, and both FMOLS and DOLS techniques. For example, traditional unit root tests are ineffective when applied to a series with cross-sectional dependence due to lower power. These first-generation unit root tests seem to over-reject the null hypothesis of cross-sectional dependency when defining the order of integration of variables is within the panel. In doing so, we have applied cross-sectional augmented IPS (CIPS) test. Pedroni cointegration test is based on the two-step long-run equilibrium cointegration method of Engle-Granger causality. This test developed seven test statistics: pooling (panel statistics test or within-dimension) which are allows homogeneity of the AR term and (group statistics test or between- dimension) are assumes heterogeneity of the AR term. These seven test statistics provide empirically efficient and reliable empirical results. Similarly, DOLS and FMOLS approaches provide very similar signs and significant results for each variable, but they slightly vary in magnitude. The reason is that both approaches indicate the endogeneity and serial correlation, model may have. Lastly, Dumitrescu and Hurlin  non-causalitytest is applied for examining causalitybetween the variables, which supports the presence of heterogeneity, and works under the fixed coefficients in a VAR framework. Therefore, Dumitrescu and Hurlin  methodological technique appears to be more reliable than that of conventional Granger causality tests.
Nonetheless, as shown in table 5 and Fig.1, we find short run Granger causalityfrom RE to GDP for all economies except in Armenia, Egypt, and Morocco. This result reveals the growth hypothesis; according to which the renewableenergy contributes to GDP per capita for these economies in the short run. In this situation, renewableenergy is considered one of the main factors of production alongside labor and the capital, and an increase in the renewableenergyconsumption may lead to the increase in economicgrowth in these economies. This evidence is similar to that of Alper and Oguz (2016) in which they found causality running fromrenewableenergyconsumption to economicgrowth in Bulgaria. Similarly, there is evidence for Granger causality running from FDI to GDP for four economies (Algeria, Armenia, Israel, and Tunisia). This differs to the Seyoum et al., (2015)’ results who’s they found a unidirectional Granger-causality running from FDI to GDP in Egypt, Gabon and Mauritania. This implies that FDI contributes to GDP per capita for these economies which allows as accepting the FDI-led growth hypothesis in these economies in the short run. But the rejection of this assumption is verified for the other countries since they have no causality running from FDI to GDP. This result is consistent with Chowdhury and Mavrotas (2006) who found that FDI does not cause GDP in Chile. Likewise, the FDI-led growth hypothesis rejecting is supported by a few other studies (De Mello, 1999; Mutafoglu, 2012; Mohamed, Singh, and Liew, 2013; Goh et al., 2017).
In contrast to aggregate energyconsumption, there have been few studies specifically addressing the causal relationshipbetween 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 relationshipbetween 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.
This study examined data from the panel to explore the SSA nexus of pollutant emissions, renewableenergy, and economicgrowth. First, since wood biomass is perhaps the most common origin of renewableenergy in SSA, more great technologies are needed to optimize the use of wood biomass so that its benefits can be harnessed without adversely affecting the population's health. To accomplish this, a design of the renewable wood energy policy of the Member States of the European Union (EU) can be implemented into the renewableenergy approaches of the Economic Community of West African States. West African countries can employ similar or sophisticated modern technologies used by EU countries. Second, in the sub region‘s renewableenergy combination, the share of other renewableenergy factors such as solar, wind and geothermal needs to be expanded. Thirdly, SSA countries need a stronger response to reaching green renewableenergy. Though, the study recognizes both constant and constant trends as well as the long and short-run impact of known structural break (i.e., recent energy crisis) tests on co-integration. Thus, it would be quite useful to examine a structural break at the co-integrated point. In the presence of structural breaks, Gregory et al. (1996) investigate some of the issues associated with the co-integration test. They note that the existence of a structural break often creates false unit root in the system of co-integration, a small power to reject the null hypothesis of no co-integration emerges. That is, the existence of a structural break check makes it easy to assume this co-integration is not feasible. There are various types of tests at the co-integrated level for structural breaks. Although, the complex causality of Granger for the , , Pool Mean Group (PMG) and Panel Dumitrescu and Hurlin. The use of Lutkepohl tests, Hadri test, Breitung test, ADF- Fisher Chi-square, PP-Fisher Chi-square, Madalla and Wu testBootstrapCausality, Generalized Momentum Model (GMM), Pedroni (Engle-Granger base) test for cointegration, McCoskey and Kao test for cointegration, and Fisher (Combined Johansen) test is recommended for further research.
Several papers study the causal relationshipbetweenenergyconsumption (total energy use), international trade, and output. Lean and Smyth (2010a) study the dynamic relationshipbetweeneconomicgrowth, electricity production, exports and prices in Malaysia. Granger causality tests show the existence of a unidirectional causality running fromeconomicgrowth to electricity production. Lean and Smyth (2010b) study the causal relationship, in Malaysia, between output, electricity consumption, exports, labor, and capital in a multivariate model. They show the existence of bidirectional causalitybetween output and electricity consumption. They come to the conclusion that Malaysia should adopt the strategy of increasing investment in electricity infrastructure and encouraging electricity conservation policies to reduce unnecessary use of electricity. Narayan and Smyth (2009) come to the same conclusion for a sample of Middle East countries and find feedback effects between electricity consumption, exports and GDP. Sadorsky (2011) uses panel cointegration techniques for 8 Middle East countries to study how trade can affect energyconsumption. He finds Granger causality running from exports to energyconsumption and bidirectional causalitybetween imports and energyconsumption in the short-run. In the long-run, he finds that an increase in both exports and imports affect the demand of energy. Another study on a sample of 7 South American countries, Sadorsky (2012), confirms the long-run causalitybetween trade and energyconsumption. He concludes that environmental policies made to reduce energyconsumption will reduce trade.
This paper aims to analyze the relationshipbetweenrenewable and non-renewableenergyconsumption and GDP growth in 29 OECD countries over the period of 1990-2012. It also seeks to contribute to the literature on the dynamic nexus betweenrenewable and non- renewableenergyconsumption and industrial output of these matured economies. We use the Common Correlated Effects Mean Group (CCEMG) estimator, proposed by Pesaran (2006) to examine long run relationshipbetween dependent and independent variables. Following Liao et al. (2010) and Arbex and Perobelli (2010) we utilize a production function framework accounting for renewable and non-renewableenergyconsumption in addition to usual inputs: capital and labour. We also test for structural breaks in the data and examine the possibility of cross-sectional dependence (CSD) by following Carrion-i-Silvestre et al. (2005) and Pesaran (2004) respectively. The empirical results show that both renewable and non-renewableenergy positively impacts GDP and industrial output. We also find the possibility of substitution of renewableenergy for non-renewableenergy. Using the Pooled Mean Group (PMG) model of Pesaran et al (1999) after time demeaning of variables to control for CSD, we find evidence of a bidirectional short-run relationshipbetween GDP growth and non- renewableenergyconsumption while unidirectional causalitybetween GDP growth and renewableenergyconsumption. The later finding is contradictory with those of Apergis and Payne (2011a) who find unidirectional causalityfrom GDP to renewableenergy use. We also find bidirectional causalitybetween industrial output and renewable and non-renewableenergyconsumption.
The (Kao, 1999) test follows the same basic approach as the Pedroni (1998) tests, but specifies cross-section specific intercepts and homogeneous coefficients on the first-stage regressors. In the null hypothesis, the residuals are nonstationary (i.e., there is no cointegration). In the alternative hypothesis, the residuals are stationary (i.e., there is a cointegrating relationship among the variables). The third test is the Johansen-type panel cointegration test developed by Maddala and Wu (1999). The test uses Fisher's result to propose an alternative approach to testing for cointegration in panel data by combining tests from individual cross-sections to obtain at test statistic for the full panel. The Maddala and Wu (1999) test results are based on p-values for Johansen's cointegration trace test and maximum eigenvalue test. Evidence of cointegration between real exchange rate and real oil price using the Maddala and Wu (1999) test is obtained if the null hypothesis of none (r = 0) cointegration variables is rejected and the null of at most 1 (r ≤ 1) cointegrating variables is accepted, suggesting the direction of causality is running from real oil price to real exchange rate. In other word, the paper would confirm the existence of a unique cointegration vector for the estimated model.
Our main aim in this paper is to investigate nonlinear causal relationshipbetweenenergyconsumption and output growth rate in the case of G7 (group of seven) countries. The G7countries are the most industrialized countries that play a crucial role in global economy, and have comparable level of economic development. In addition, these countries’ share in total carbon dioxide emission accounted for around 32.2% in 2007 according to calculations of Carbon Dioxide Information Analysis Center (CDIAC) of the US Department of Energy (Boden et al., 2010). In recent years, the G7countries have followed policies aimed at reducing total greenhouse gas emissions. Therefore, it is important to discover all aspects of the causal relationshipbetweenenergyconsumption and output for these countries.
Regarding the link between FDI and economicgrowth, previous research has failed to establish if there is a positive or negative relationship amongst these variables. On one hand, proponents of the positive association between FDI inflows and economicgrowth, in the literature, are attributed to Van Loo (1977), Findally (1978), Romer (1993), Gruben and McLeod (1998), Borensztein et al. (1998) and De Mello (1999). Based on the basic neoclassical growth model of Solow (1956), they underline that FDI enhance growth by exercising a positive impact on the level of capital accumulation through increased investment and by increasing total factor productivity of host countriesfrom technology transfers and spillovers effect. On the other hand, dependency theorists (Caves, 1971 and Hymer, 1976) were highly critical of the role of FDI in the economicgrowth of host countries. They reject the notion that incoming FDI flows to developing countries promote growth, arguing that FDI is a strategy used by MultiNational Corporations (MNCs) in developed economies to advance monopoly power over local industries (Prebisch, 1968). The MNCs reinforce their competitive advantage over local firm, characterized by low power in terms of marketing and advertisement, by controlling the supply of inputs and earning the benefits of tax incentives in the host country.
Due to the availability of renewableenergyconsumption data, numerous researchers have examined the dynamic relationshipbetweenenergyconsumption (fromrenewableenergy sources) and economicgrowth for different countries by using different regional panel data sets with different econometric approaches but have arrived at mixed empirical results. In doing so, this paper contributes to the existing literature in several aspects: (i) This study examines the impact of energyconsumptionfrom non-renewable and renewable sources on economicgrowth in APEC countries; (ii) Research & development expenditures are included in the augmented production function as an additional determinant of energyconsumption and economicgrowth; (iii) The unit root and cointegration tests are applied by considering cross-sectional dependence in the panel; (iv) FMOLS and DOLS are applied for long-term estimates; (v) The Granger panelcausality is applied in order to examine the causal relationshipbetweeneconomicgrowth and its determinants. Our results indicate the presence of cointegration between the variables. Moreover, renewable and nonrenewableenergyconsumption contributes to economicgrowth. Research and development expenditures have a positive effect on economicgrowth. Trade openness is positively linked with economicgrowth. The Granger causality analysis shows that renewableenergyconsumption causes economicgrowth, but economicgrowth causes non-renewableenergy. The feedback effect exists between research and development expenditures and economicgrowth.
The topic of the interrelationship betweenenergyconsumption and economicgrowth is widely discussed in scientific literature. Scientists agree that the reason for the interest in such investigations arises because of increased worldwide concern about the impact of energy and environmental policies on the country’s economy. Recently, the investigations of causality interrelationships betweenenergyconsumption and economicgrowth have been performed for many countries, including Indonesia Thailand, Japan, China, other Asian countries, G7 economies, Spain, Albania, Bulgaria, Romania, Central America, OECD and non OECD, Sub-Sahara African countries, for the panel of countries (China, Hong Kong, Indonesia, Korea, India, Malaysia, Philippines, Singapore, Taiwan, and Thailand), and many other countries. The results of these investigations are different, country- specific and depend on the structure of the economy, energy type selected, period analyzed, methodology applied and a variety of other factors.
In the literature, there are several studies, theoretical and empirical, which put the accent on the relationshipbetweenenergyconsumption, economicgrowth, and the emission of CO2 that may ex- ist. Empirically it has been tried to find the direction of causalitybetweenenergyconsumption and economic activities for some countries employing the Granger Test, ECM and other techniques. In recent papers, Zhang and Lin (2012) chowed that urbanization increases energyconsumption and CO2 emissions in China using panel estimation. They proves that the effects of urbanization on en- ergy consumption vary across regions and decline continuously from the western region to the central and eastern regions. Shyamal and Rabindra (2004) examined the different direction of causal rela- tion betweenenergyconsumption and economicgrowth in India through a co-integration technique combined with the Granger causalitytest. They find the existence of a bi-directional causality be- tween energyconsumption and economicgrowth. Wang et al. (2016) used a co-integration approach in China data to examine the relation betweeneconomicgrowth, energyconsumption and CO2 emis- sion. Granger causalitytest identified a bi-directional causal relationshipbetweeneconomicgrowth and energyconsumption, and a uni-directional causal relationship was found to exist fromenergyconsumption to CO2 emissions. Saidi and Hammami (2015) studied the impact of energy consump- tion and CO2 emission on economicgrowth for 58 countries. They have used simultaneous equations models estimated by the GMM-estimator and they find evidence that energyconsumption has a pos- itive impact on economicgrowth and that the CO2 emissions have a negative impact on economicgrowth.
In this paper, we use panel cointegration techniques to explore the relationshipbetweenrenewable and non-renewableenergyconsumption and economicgrowth in a sample of 11 MENA Net Oil Importing Countries covering the period 1980 – 2012. The Pedroni (1999, 2004), Kao(1999) as well as Westerlund(2007) panel cointegration tests indicate that there is a long-run equilibrium relationshipbetween real GDP, renewableenergyconsumption, non- renewableenergyconsumption, real gross fixed capital formation, and the labor force with elasticities estimated positive and statistically significant in the long-run. Results frompanel error correction model expose that there is confirmation of bidirectional causalitybetweenrenewableenergyconsumption and economicgrowth, between non-renewableenergyconsumption and economicgrowth as well as betweenrenewable and non-renewableenergyconsumption that is evidence of their substitutability and interdependence in both the short and long-run supporting the feedback hypothesis. We suggest that Governments should implement policies that promote the development of renewableenergy sector in order to realize economies of scale such as tax credits for renewableenergy production, installation rebate for renewableenergy systems as well as the establishment of markets for renewableenergy certificates.
The Cointegration tests supported the evidence of cointegration among the real output; measured by GDP and energy use in all the member countries. The VECM results confirmed that in the long-run, the “growth hypothesis” is true for the sample period in Nigeria while “conservation hypothesis” is true for Egypt. The “feedback hypothesis” was established by the results of estimation of long-run causality for Bangladesh, Indonesia, Iran, Malaysia, Pakistan and Turkey. The results based on the long-run analysis by VECM suggest that energyconsumption plays an important role in enhancing productivity in all the countries except Egypt in long-run and energy use has important implications for these developing countries in the long-run. The results support the evidence of causality running in either one or both directions betweenenergyconsumption and GDP in all the countries in the long as well as in the short-run except Indonesia in the short-run. On the whole, results suggest that the economies of most countries are energy dependent and shortage of energy may negatively affect the economicgrowth which eventually results in a fall in income, employment and broadly, social welfare.
Recently, contributions have exposed that the world is facing severe problems with energy depletion in consequence of the unbalanced availability between finite energy resources and population growth as well as industrial development. The available quantity of finite-based energy resources was expected to last between 30-150 years 2 . Additionally, According to the International Energy Agency (IEA, 2012), production from gas and oil reserves will drop to about 40-60% by 2030. Besides, Huntington (2009) exposed that this type of energy use was also vulnerable to disruptions caused by major events in the world, such as war, monopolistic behaviors (e.g. by OPEC 3 ) and commonly more depending on the political stability of the net oil producing countries . These circumstances indeed slowed down the economic development in most countries in the world. Not only finite energy resources availability became the immediate concern, but also the environmental degradation whereas oil and coal exploitation ultimately led to forest destruction, biodiversity extinction as well as natural disasters.
Like other developing countries Pakistan is also an energy intensive growing economy, and as in most other non- oil producing countries its energy needs are met by large quantities of imports. The ACGR (annual consumptiongrowth rate) of net consumption of total energy is 6.4 percent. The share of oil, gas and electricity is 48 percent, 30 percent (of which more than half is used for electricity) and 15 percent respectively by Aqeel (2001). The share of imported oil was 92 percent of net consumption of oil in 2004-2005, which is about 44 percent of total net consumption of energy in the country. Thus to meet its growing needs of energy, Pakistan faces both energy constraints from the supply side and demand management policies. (Riaz, 1984, and Chisti and Mahmood, 1980). However, for any such policy making it is essential to determine the causal relationshipbetweenenergyconsumption and general economic activities. The purpose of this study is to determine such a relationship for Pakistan. This is accomplished by examining Granger Causalitybetweengrowth in energyconsumption and GDP growth and unit root test. The paper is organized in the following manner. First is the methodology with interpretation of primary literature, then empirical findings are presented and finally the results will be concluded.
tests based on the within approach which includes four statistics (panel tests) and on the between approach which includes three statistics (group tests). In total, there are seven statistics for the tests of the null hypothesis of no cointegration in heterogeneous panels (for more details see: Farhani and Ben Rejeb, 2012b). However, all these tests are based on the residual and variants of Phillips and Perron (PP, 1988) and Dickey and Fuller (ADF, 1979). Table-5 shows Pedroni’s (2004) results indicate that we reject null hypothesis of cointegration at the 5% significance level except group rho-statistic. Kao (1999)’s residual cointegration tests are presented in Table-6, which reject null hypothesis of cointegration relationshipbetweenrenewableenergyconsumption, GDP per capita and CO 2
Although nature has endowed sub-Saharan Africa with an array of natural energy resources such as wind, coal, water, oil, wood and solar, a large number of these resources have remained unexploited for decades. Consequently, many African countries face serious energy deficits due to poor investment in energy infrastructure. The inadequate provision of energy services in Sub-Saharan Africa has been cited by the United Nations Economic Commission for Africa (UNECA, 2004) as a limiting factor to economicgrowth and poverty alleviation efforts. Predominantly, the rural population and the urban poor are the ones who do not have access to modern energy services; a situation which has resulted in majority of the population to live on less than $1 a day (GNESD, 2007). In order to meet daily energy needs, majority of the population relies on traditional biomass sources such as wood, agricultural residues, and other primitive energy sources and thus exacerbating the problems of environmental and land degradation.