Between 2011-2015, the demand for electricity usage increased averagely at 10.6 percent per annum, lower than the 13.4 percent average growth rate of the period 2006-2010 (Institute of Energy 2016.). Electricity remains the highest production capacity in the final energyconsumption mix, estimated to increase by 8 percent yearly on average until 2035, corresponding to a need for additional 93 giga watts of power generation capacity during the period. Nearly half of the new capacity is supposed to be powered by coal, while almost 25 percent will be supported by renewableenergy (EA Energy Anlyses 2017). Our study adds to the existing literature using data set fromVietnam to investigate the impacts of the adaptation and usage of clean energy on economicgrowth.
In a series of studies, Apergis and Payne (2010a, 2010b, 2011a, 2011b, 2011c, 2012) investigate the causal relationship between renewableenergyconsumption and economicgrowth for many groups of countries ranging from developed to developing countries. The authors use various cointegration techniques and causality approaches within a panel data framework. In the majority of cases, empirical results reveal that cointegration relationships and both short-run and long-run bi-directional causality exist among variables in question, proving the validity of the feedback hypothesis. Employing a panel error correction model within a multivariate model, Apergis et al. (2010) examine the causal relationship between CO2 emissions, nuclear energyconsumption, renewableenergyconsumption and economicgrowth for a panel of nineteen developed and developing countries aver the period 1984- 2007. Empirical evidence shows that there exists short-run bi-directional causality between renewable and nuclear energyconsumption and economicgrowth, supporting therefore the feedback hypothesis. The long-run analysis reveals the existence of a unidirectional causality running from the consumption of both nuclear and renewableenergy to economicgrowth, which suggests the validity of the growth hypothesis.
The importance of non-renewable, renewable and sustainable energy sources and energyconsumption in the economic development strategy of a country is undeniable. The purpose of the paper is to investigate the impacts of energyconsumption on the economicgrowth of Vietnam during the 1980-2014 period. By applying the Autoregressive Distributed Lag (ARDL) model of Pesaran et al. (2001), and the Granger causality test of Toda and Yamamoto (1995), the empirical results provide evidence that electricity consumption has positive impacts on Vietnam’s economicgrowth in both the short run and long run. For public policy prescriptions, the empirical evidence suggests that an exploration of new sources of renewable and sustainable energy is essential for long run economic development.
4 have adverse impact on economicgrowth if economicgrowth Granger causes energyconsumption/ neutral hypothesis is found between both the variables. If bidirectional causality is found both the variables / energyconsumption Granger causes economicgrowth then new sources of energy should be explored. Energy is an important stimulus of production process and energy must Granger cause economicgrowth. An expansion in production is linked with energy demand and economicgrowth might Granger cause energyconsumption. The main objective of present study is to investigate the relationship between renewableenergyconsumption capital, labour and economicgrowth in case of Pakistan of using Cobb-Douglas production function over the period of 1972Q1-2011Q4. In case of Pakistan, this study contributed to energy literature by five folds applying: (i) the ARDL bound testing approach to cointegration for long run relationship; (ii) the rolling window approach (RWA) to examine robustness of the ARDL results; (iii) OLS and ECM for long run and short run impacts of renewableenergyconsumption on economicgrowth; (d) the VECM Granger causality approach is to examine causal relationship between the variables and (v) innovative accounting approach to (IAA) test the robustness of the VECM Granger causality results. Our findings reveal that cointegration between renewableenergyconsumptioneconomicgrowth, capital and labor exists in case of Pakistan. Further, our empirical evidence reports that renewableenergyconsumption has positive impact on economicgrowth. Capital and labour also adds in economicgrowth. Furthermore, estimated results indicated bidirectional causality relationship between renewableenergyconsumption and economicgrowth.
In this paper, we use panel cointegration techniques to explore the relationship between renewable 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 relationship between 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 from panel error correction model expose that there is confirmation of bidirectional causality between renewableenergyconsumption and economicgrowth, between non-renewableenergyconsumption and economicgrowth as well as between renewable 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.
Previous empirical studies have either assumed linearity in the context of cointegration long- run relationship between renewableenergyconsumption 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.
This study examines the long-run relationship among foreign direct investment, renewableenergyconsumption, and economicgrowth for seven Middle East and North Africa countries over the period 1980 – 2017 using a newly developed cointegration test by McNown et al. (2018), the bootstrap autoregressive distributed lag (ARDL) test. The long run analysis reveals evidence of cointegraion among FDI inflows, renewableenergyconsumption, and economicgrowth in all countries except Iran and Turkey, where real GDP is used as the dependent variable. A similar result is observed in economies, with the exception of Mauritania when FDI inflow is treated as a dependent variable. Whereas, when RE is taken as a dependent variable, cointegration does occur in Algeria, Mauritania, Morocco, and Tunisia. In regards to the direction of causality, the short-term analysis provides varied results among diverse variable for various countries. In this context, this study recommends increasing public awareness and attention in the advantages of renewableenergy and clean technologies. In addition, MENA governments need to attract more FDI that includes green technologies and renewableenergy sources as a way to promote energy efficiency. Thus could contribute to economic development and boost environmental quality.
energy with little or no impact on climate change. Directive 2001/77/EC of the European Union defines renewableenergy sources (RES) as non-fossil renewableenergy sources that include wind, solar, geothermal, wave, tidal, hydropower, biomass, landfill gas, wastewater treatment plant gas and biogas . The RES can not only reduce GHG emissions but also contribute to job creation and national energy supply protection. Given these submissions, it is imperative to investigate how the emissions of pollutants and renewableenergy emitted from the use of fossil fuels can affect SSA economicgrowth. Different studies have been conducted to diagnose SSA countries ' growth and development problems, often using traditional growth models to identify the implications of certain fundamental variables, including capital formation, labor, human capital, and technology, for the region's growth and development. However, very few of these studies have identified energy use as a critical determinant of the region's economicgrowth ; ;  and . Moreover, only fewer studies investigate the impact of energy on sub- Saharan Africa's economicgrowth, as they mostly focused on assessing the impact of renewable or non-renewableenergy on the region's economicgrowth . This study is, therefore, particularly interested in how renewableenergyconsumption and pollutants fit into the sub-Saharan African region's complex system of economicgrowth. The study aims to examine the effects of renewableenergyconsumption and emissions of pollutants as a CO2 proxy on SSA's economicgrowth to provide the SSA policymakers with political implications. This research overcomes literature gaps by using alternative modeling frameworks, longer samples than previous studies, recent advances in econometric techniques, and being the first to investigate the impact of renewableenergyconsumption along with pollutants on the region's economicgrowth.
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 relationship between renewableenergyconsumption, GDP per capita and CO 2
37 unidirectional causality between renewableenergyconsumption and economicgrowth in the short-run and bidirectional causality in the long-run while bidirectional causality was remarked between non-renewableenergyconsumption and economicgrowth in both the short and long-run that suggests the importance of this energy sources in these exporting economies. These findings reveal that the renewableenergy sector is in its immaturity in the case of MENA exporting economies that have experienced remarkable growth, but as economicgrowth continues, more resources will become accessible for the renewableenergy sector development. Further, barriers and obstacles related to the high cost of renewableenergy in competition with subsidies to fossil fuels, the small size of the local market and the absence of a regional market, the lack of mastery of the technology and the weak capacity of local production of goods and services remain to hinder the renewableenergy development in these countries. Obviously, the transition towards a renewableenergy supply necessitates some form of government intervention in an attempt to conquer market distortions favoring fossil fuels. In fact, there are several initiatives and policies must be undertaken to promote and stimulate the introduction of renewableenergy such as the development of several important regional and regionally based institutions and cooperation, renewableenergy production tax credits, installation rebates for renewableenergy systems, renewableenergy portfolio standards, as well as the creation of markets for renewableenergy certificates.
The data for the variables such as economicgrowth, capital and employment have been sourced from World Development Indicator while renewableenergyconsumption and carbon dioxide emissions were sourced from International Energy Agency (IEA). The data set comprises of observations for economicgrowth proxies by gross domestic product measured in millions of 2010 constant US dollars and renewableenergyconsumption, which is measured in million kilowatt- hours. Additional variables include, carbon dioxide emissions measured in metric tones, capital proxies by gross fixed capital formation and employment proxies by commercial, agricultural and manufacturing employments. The data used in this study covers a period between 1990 and 2014 and its extrapolated into quarterly data.
insights like the problem of and the best way to increase renewable investment . This study does not consider these issues, which may have direct as well as indirect effects on economicgrowth in the process of renewable deployment. Developing an investment climate, improving human resources, and removing all financial and political obstacles are significant steps toward the deployment of renewable sources. For example, this process has also included in the majority of OECD nations, as well as other nations. Financial considerations, investment subsidies, solar cells sales tax exemptions, feed-in tariffs, tax or credit incentives, green certificate trading, and establishing quota are significant tools for continuous deployment. Power planners, international cooperation organizations, government utilities on energy policy, and related organizations need to work together to enforce renewableenergy deployment policies.
Table 7 reported that the sign of ECT (-0.07) coefficient is significant and negative, in line with the a priori expectation. This validates that there is a long run causality flowing fromrenewableenergyconsumption, carbon dioxide emissions, trade openness and capital formation to economicgrowth. The long run results further suggested a long run causality flowing fromeconomicgrowth, renewableenergyconsumption, trade openness and capital formation to carbon dioxide emissions. This is because the coefficient of the lagged error term (-0.118) was found to be negative and significant. The existence of a long run causality flowing fromrenewableenergyconsumption to economicgrowth suggest that the energy policies such as energy conservation cannot be applied in the long run as this will have adverse effect economicgrowth. It agrees with the studies conducted by Omri, Mabrouk and Sassi-Tmar (2015) for Hungary, India, Japan, Netherlands, and Sweden
energyconsumption and economicgrowth has begun to be tested empirically. Narayan and Smyth (2008) reported that energyconsumption and capital stock affected economicgrowth positively for the G7 countries both in the short and long run. Tugcu et al. (2012) used the ARDL bounds testing and Hatemi-J causality test and found that the growth hypothesis was valid only in Japan in terms of nonrenewable energyconsumption. 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 causality relationship between renewableenergyconsumption 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 causality relationship between energyconsumption 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 relationship between coal consumption and economicgrowth.
4 al.  also found bidirectional causality between renewableenergy use and economicgrowth. Enriching the analysis using different methods, i.e. autoregressive distributed lag (ARDL) model, VECM Granger causality and innovation accounting approaches, Shahbaz et al.  support feedback hypothesis regarding renewableenergyconsumption and economicgrowth for Pakistan. Using rolling window approach (RWA), they revealed that renewableenergyconsumption, capital, and labor have a positive effect on economicgrowth except few quarters. Using a dynamic panel data model, Saidi and Mbarek  found that bidirectional causality exists between renewableenergyconsumption and real GDP per capita for nine developed countries over the 1990-2013 period. Moreover, Ocal and Aslan  maintained that renewableenergyconsumption has positive effects on economicgrowth for the new EU member countries by utilizing the asymmetric causality test and the ARDL approach. Chang et al  investigated the causal link between renewableenergyconsumption and economicgrowth in G-7 countries employing the heterogeneous panel Granger causality method and found bidirectional evidence with regard to this relation. Destek and Aslan  found evidence that renewableenergyconsumption plays a vital role in economicgrowth in Peru, Greece and South Korea among 17 emerging countries. Furthermore, more recent studies such as Amri , Bhattacharya et al. , Destek , Lu , Saad and Taleb , Troster et al.  investigated the bi-directional causality between renewableenergyconsumption and economicgrowth and reached different results for various countries and country groups.
To investigate whether renewableenergyconsumption influence growth, I make use of data on 22 countries that are members of the Organization of Economic Development (OECD). The countries included are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, and the United States. Analyzing the way that certain factors influence growth over time requires a specific type of data called time series data. Time series data refers to measurements taken over time, as opposed to cross sectional data which refers to observations at a single point in time. Analyzing time series data comes with its own challenges. This is because data from one year almost certainly influences the data from following years. Lagged independent variables can be used when it is expected that X affect Y after a period of time. More complicated cases exist when the impact of an
This article examines the dynamic relationship between renewable and non-renewableenergyconsumption and industrial output and GDP growth in OECD countries using data over the period of 1980-2011. The panel cointegration technique allowing structural breaks is used for empirical investigation. The results show that there is a long-term equilibrium relationship among non-renewable and renewableenergy sources, industrial output and economicgrowth. The panel causality analyses show bidirectional causality between industrial output and both renewable and non-renewableenergyconsumption in the short and long run. However, there is evidence of bidirectional short-run relationship between GDP growth and non-renewableenergyconsumption while unidirectional causality between GDP growth and renewableenergyconsumption. These results indicate that OECD economies still remain energy-dependent for their industrial output as well as overall economicgrowth. However, expansion of renewableenergy sources is a viable solution for addressing energy security and climate change issues, and gradually substituting renewable to non-renewableenergy sources could enhance a sustainable energy economy.
Mexico, Peru, and Vietnam, but a positive effect for Malaysia and New Zealand. The evidence for Canada and Chile is inconclusive. An interesting implication is that, based on the specific country characteristics, trade expansion could be more harmful than beneficial for the environment. As such, different countries should encourage the implementation of an appropriate strategy and policy in favour of trading environmentally-friendly products in order to gain the benefits from the establishment of the CPTPP, as well as to minimize the negative impacts on the environment of conducting international trade.
The causal relationship between energyconsumption and economicgrowth has been examined extensively in a number of countries in recent years, with conflicting results. Three views exist regarding the relationship between energyconsumption and economicgrowth. The first view, which posits that energyconsumption Granger-causes economicgrowth, has been supported by studies like those of Chang et al. (2001) for the case of Taiwan; Wolde-Rufael (2004) for Shanghai; Lee (2005) for the case of developing countries; Altinay and Karagol (2005) for Turkey; Chiou-Wei et al. (2008) for Taiwan, Hong Kong, Malaysia and Indonesia; Akinlo (2009) for Nigeria; Odhiambo (2009a) for Tanzania; Odhiambo (2010) for the case of South Africa and Kenya; Chu (2012) for the case of 13 countries; Dergiades et al. (2013) for Greece; Muhammad et al. (2013) for Pakistan; Odhiambo (2014) for the case of Uruguay and Brazil; Abosedra et al. (2015) for Lebanon; Iyke (2015) for Nigeria; Tang et al. (2016) for Vietnam; Rahman (2017) for the case of Asian populous countries; Saidi et al. (2017) for the case of the European countries; Cai et al. (2018) for the case of Canada, Germany and the US; Le and Quah (2018) for the case of 14 selected countries in the Asia and the Pacific region; Bekun et al. (2019) for South Africa; and more recently Rahman et al. (2020) for the case of China when coal and oil consumption are used as proxies for energyconsumption.
The empirical evidence suggests that renewable and non-renewableenergyconsumption stimulate economicgrowth in OECD countries. However, comparing the magnitudes of their coefficients confirms that non-renewables are still the dominant type of energy utilised in the process of economicgrowth. Similar results are obtained for industrial output, indicating that although the share of the use of non- renewableenergy is declining compared with the share of renewable sources, non- renewables still play a considerable role in industrial production in developed countries today. The results also indicate that while oil and natural gas consumption positively and significantly influence economicgrowth, no significant relationship is observed between coal consumption and economicgrowth. It seems to be due to emerging policies that try to curb pollutant emissions by imposing a cost on higher- carbon fuels that in turn results in declined demand for coal in developed countries. In contrast, even though policies seek to slow consumptiongrowth of oil, it is still the dominant fuel particularly in the transport sector. According to the EIA, since developed countries tend to have higher vehicle ownership per capita, oil consumption within the OECD transportation sector usually accounts for a larger share of total oil consumption than in non-OECD countries. In addition, oil is used in many ways, from the manufacture of goods, to transport of goods and people, to food production, to operating construction equipment, to mining. Therefore, it seems not to be achievable to substitute oil for clean energy in the near future. However, natural gas, which has the second position after oil, has an important feature in that it generates less carbon emissions compared with the other fossil fuels. Thus, fuel transformation at least from coal and/or oil to natural gas should be taken into account by policymakers.