This finding suggests a decoupling betweenenergyconsumption and economic activity providing support to the argument that after 1970, the relationshipbetween the two variables could have changed. The hypothesis seems to be stronger for most countries while for the cases of Spain and Portugal a coupling between the two variables could still hold even after 1970s given that the two variables continue to rise simultaneously. In fact, in Figure 3 the energy intensities (the ratio of energyconsumption to GDP) of all countries after 1970 are presented and it can clearly be seen that while for the majority of them energy intensity declines, suggesting a decoupling between the two variables in the long run, for Spain and more clearly for Portugal the ratio remains relatively stable at the same levels, after 1970. This could be attributed to the relatively latter industrialization that the countries had compared to the more developed economies in northern Europe. In fact, the study by Henriques (2011) on the Portuguese economy has shown that two key outcomes of the later industrialization of the country could be the main reasons for the existing coupled relationship of energyconsumption and economicgrowth after 1970. The first is related with the “subsectoral structural change” that occurred in the country which was relatively different than that of more advanced economies in Europe favoring the immergence of energy intensive industries like chemicals and pulp. However the second and more “concerning” factor, has been the fact the country’s industry after the 1970s was focused more on a low value added production structure. In this sense, “in an time where knowledge was the important factor of production, producing low value- added products could … compromise the decoupling of energy from economicgrowth” (Henriques, 2011: 256).
Linh and Lin (2014) contribute to the most recent studies that assessed the dynamic relationshipbetweenenergyconsumption and economicgrowth using multivariate framework by adding the variables foreign direct investments and carbon dioxide emissions. This Vietnam study used data for the period between 1980 and 2010. The co-integration findings show that there is a long term relationshipbetweeneconomicgrowth, energyconsumption, foreign direct investments and carbon dioxide emissions. The Granger-causality results established bidirectional causality between foreign direct investment and income in Vietnam. This implies that an increase in Vietnam’s income has a potential of attracting more capital from overseas.
This test is carried out to check for the presence of cointegration which is a check for long run relationshipbetween exchange rate, real oil price and real interest rate differential variables. The paper utilise panel cointegration tests due to Pedroni (1998), Kao (1999) and Maddala and Wu (1999). The tests proposed in (Pedroni, 1998) are residual-based tests which allow for heterogeneity among individual members of the panel, including heterogeneity in both the long-run cointegrating vectors and in the dynamics. Two classes of statistics are considered in the context of the Pedroni (1998) test. The panel tests are based on the within dimension approach (i.e. panel cointegration statistics) which includes four statistics: panel v-statistic, panel ñ-statistic, panel PP-statistic, and panel ADF-statistic. These statistics essentially pool the autoregressive coefficients across different countries for the unit root tests on the estimated residuals. These statistics take into account common time factors and heterogeneity across countries. The group tests are based on the between dimension approach (i.e. group mean panel cointegration statistics) which includes three statistics: group ñ-statistic, group PP-statistic, and group ADF-statistic. These statistics are based on averages of the individual autoregressive coefficients associated with the unit root tests of the residuals for each country in the panel. All seven tests are distributed asymptotically as standard normal. Of the seven tests, the panel v-statistic is a one-sided test where large positive values reject the null hypothesis of no cointegration whereas large negative values for the remaining test statistics reject the null hypothesis of no cointegration.
has scrutinizes the linkage betweenenergyconsumption and output, suggesting that en- ergy consumption and output may be jointly determined and the direction of causality between these two variables needs to be tested. Following the seminal work of Kraft and Kraft (1978), several others including Masih and Masih (1997), Yang (2000), Wolde- Rufael (2009), Apergis and Payne (2009) and Ozturk et al. (2010) have tested the energyconsumption and economicgrowth nexus with a variety of techniques and for different panel of countries. Looking at the region of Gulf Cooporation Council (GCC), Al-Iriani (2006) investigates the causality relationshipbetween gross domestic product (GDP) and energyconsumption in the six countries of the Gulf Cooperation Council (GCC). Re- cently developed panel cointegration and causality techniques are used to uncover the direction of energyŰGDP causality in the GCC. Empirical results indicate a unidirec- tional causality running from GDP to energyconsumption. Evidence shows no support for the hypothesis that energyconsumption is the source of GDP growth in the GCC countries. Such results suggest that energy conservation policies may be adopted with- out much concern about their adverse effects on the growth of GCC economies. In the same context context, Hamdi et al. (2014) explores the relationshipbetween electricity consumption, foreign direct investment, capital and economicgrowth in the case of the Kingdom of Bahrain. The Cobb-Douglas production is used over the period of 1980 - 2010. Using autoregressive distributed lag (ARDL), a cointegration relationship has been detected among the series. It is found that electricity consumption, foreign direct invest- ment and capital add in economicgrowth. However, empirical works do not provide any precise answer, and there is still no consensus among economists whether there is a causalrelationship or not and if it exists, there is no clear-cut answer about the direction of this causation (Ozturk, 2010). The contradictory results may occur due to the differences in data sets, characteristics of the investigated countries, variables that are included in the studies, and the diversification in using econometric methodologies (Ozturk, 2010).
In this study, we have explored the causalrelationshipbetweenenergyconsumption and economicgrowth in Ethiopia, during the period from 1971 to 2013. We have employed a multivariate Granger-causality framework that incorporates financial development, investment and trade openness as intermittent variables – in an effort to address the omission-of-variable bias. Based on the newly developed ARDL bounds testing approach to co-integration and the Error-Correction Model-based causality model, our results show that in Ethiopia, there is a distinct unidirectional Granger-causality from economicgrowth to energyconsumption. These results apply, irrespective of whether the estimation is done in the short run or in the long run. We recommend that policy makers in Ethiopia should consider expanding their energy-mix options, in order to cope with the future demand arising from an increase in the real sector growth.
The impact of transport and communication infrastructure on economicgrowth is a topic that has attracted considerable attention from researchers, academicians and practitioners in the existing economic literature (Zhou et al. 2002, Esfahani and Ramirez 2003, Pradhan and Bagchi 2013, Kim et al. 2017, Jin and Rafferty 2017). For example, Fernald (1999) affirmed that there is a strong link between investment in transport infrastructure and economic productivity. With data for 29 US industries, the empirical evidence shows that the decline in productivity registered in the United States after 1973 was more important in high-intensity vehicle industries. The results also confirm that these industries benefited disproportionately from investments in road networks. In OECD countries, Roller and Waverman (2001) tested the impact of telecommunications infrastructure on economicgrowth by applying a micromodel for telecommunication investment with a macro-production function. Their empirical analysis confirmed the presence of a positive causalrelationshipbetween telecommunication infrastructure and economic development, i.e., a feedback effect. For countries in Latin America (Guatemala, Honduras, Nicaragua), Escribano and Guasch (2005) indicated that access to the internet increases the productivity of workers from 11% to 15%. Yeaple and Golub (2007) examined the impact of three types of infrastructure (roads, telecommunications, and electricity) on total factor productivity for 18 countries and 10 manufacturing industries over the period of 1979-1997 period. They apply the three-stage least squares (3SLS) estimation strategy and show that roads have the most important impact on productivity in different industries. These results help explain patterns of comparative advantage and international specialization. In addition, Mu and Van de Wall (2007) showed that the extension of rural road networks in Vietnam increases job opportunities by 11% for unskilled workers.
Energy can be divided into two categories: renewable energy and non-renewable energy. The need to reduce greenhouse gas in the environment can lead to an increase in renewable energy, in order to let the use of fossil energy decline. Another issue is that to maintain sustainable growth, the need for so-called ‘green’ energy is higher than for lower growthcountries (Maji & Sulaiman, 2019). Decoupling energyconsumption from economicgrowth is necessary to increase energy efficiency (Moreau & Vuille, 2018). By doing so, the relationship of energy use on growth needs to attenuate. Decreasing energyconsumption is one part of the necessary plan to reduce emissions and reducing our impact on climate change (Friedlander, 2009). However, Shahbaz et al. (2017) conclude from previous research that one causalrelationshipbetweeneconomicgrowth and energyconsumption has not been defined.
Unfortunately, most of these studies relied upon limited time series data, usually 30 to 35 observations, which reduces the power and size properties of conventional unit root and cointegration tests. Furthermore, they did not take into account the endogeneity of regressors in panel methods. 3 Recent studies emerged to confront these problems using a dynamic panel data approach, Dynamic Ordinary Least Square (DOLS) and Fully Modified OLS (FMOLS) estimators. For example, Lee (2005) employed panel cointegration and panel error correction models to investigate the causalrelationshipbetweenenergyconsumption and GDP in 18 developing countries during the period 1975 to 2001. He found a unidirectional causality in both the short and long-run betweenenergyconsumption and GDP. Applying the same approach for 6 countries of the Gulf Cooperation Council (GCC), Al-Iriani (2006), found a unidirectional causality running from GDP to energyconsumption. Mahadevan and Asafu- Adjaye (2007) re-examined energyconsumption and GDP growthrelationship in a panel error correction model, using data on 20 net energy importers and exporters and taking into account prices. As mentioned above, this is because prices responses have been argued to have a crucial role in affecting income and energyconsumption directly. They show that among the energy exporters, there is bidirectional causality betweeneconomicgrowth and energyconsumption in the developed countries in both the short and long-run, while in the developing countries, energyconsumption stimulates growth only in the short-run.
The literature on Granger causality has grown considerably, following his seminal work in 1969, slowly during the first years and more rapidly in recent years. Granger causality test suggests which variables in the models have significant impacts on the future values of each of the variables in the system. Among recent applied studies, a significant amount of work has been devoted to addressing the above mentioned question of causality betweenenergyconsumption and economicgrowth. This paper studies the time series properties of energyconsumption and GDP and reexamines the causality relationshipbetween the two series in the top 10 emerging markets excluding China due to lack of data and G-7 countries 1 . Soytas and Sarı (2003) show that there is a bi-directional causality in Argentina, causality running from GDP to energyconsumption in Italy and Korea, and from energyconsumption to GDP in Turkey, France, Germany and Japan.
Considering first the country-specific studies, Ocal and Aslan (2013) examine the causalrelationshipbetween renewable energy use and economicgrowth in Turkey over the period 1990-2010. Using the ARDL approach and Toda-Yamamoto causality tests, the authors found that there exists a unidirectional causality running from economicgrowth to renewable energyconsumption, supporting therefore the conservation hypothesis. Using the same causality tests, Menyah and Wolde-Rufael (2010) test the hypothesis that nuclear energyconsumption and renewable energyconsumption reduce CO2 emissions in the US during 1960-2007. Among others, they find that economicgrowth and CO2 emissions Granger cause renewable energyconsumption with no feedback. Yildirim et al. (2012) apply the Toda-Yamamoto procedure and bootstrap-corrected causality test on the US data. Biomass energyconsumption, hydropower energyconsumption and biomass-wood-derived energyconsumption are used along with the total renewable energyconsumption, while employment and gross capital formation are used as control variables. Empirical evidence reports a unidirectional causality running from biomass energyconsumption to economicgrowth while the neutrality hypothesis is supported betweeneconomicgrowth and all of the other renewable energy kinds as well as the total renewable energyconsumption.
1, if we focus on papers studying the relationship in the case of Azerbaijan, namely Apergis and Payne (2009), Bildirici and Kayıkçı (2012), Tang and Abosedra (2014), Senturk and Sataf (2015) and Hasanov et al. (2017) employed the panel estimation methods, which might not take into account the country specific features of the relationship. Only Kalyoncu et al. (2013) used time series data for individual countries, but they used relatively old data set, namely the study employed 1995-2009 interval. Hasanov et al. (2017) devoted to the energy-growth nexus in the oil exporting countries, including Azerbaijan, is a valuable study with the wide literature review and estimating the relationship for the mentioned countries. However, the study makes use of conventional Granger causality not Toda- Yamamoto approach. Taking into account the fact that there is not individual study investigating the energy use-income relationship in the case of Azerbaijan, the objective of the current paper is analyzing the relationship employing Azerbaijani data. We chose Azerbaijan as a representative for the similar countries. It can be seen representative for different country cases from different aspects. First, it is an oil- reach developing country, second, Azerbaijan is one of the former Soviet Union countries. From this perspective, the results of the study might be useful for the above mentioned economies.
Shahbaz et al (2016), analyzed emissions of carbon dioxide, economic development and energy use for the next eleven nations. The researcher collected the data of 11 countries annually from 1972 to 2013 for the study. For the current analysis the author used VAR model and Granger causality test. Which indicate that economicgrowth available at the minimal cost of environment, and suggest for policy maker to attain sustainable economicgrowth while maintaining long run environment quality. Brini, Amara, and Jemmali (2017), worked on the links of international trade, renewable energyconsumption and economic development of Tunisia. The investigator used the data from the year of 1980 to 2011 and applied granger causality test and ARDL bounds approach which disclosed that in short run there is two-way association in international trade and renewable consumption of energy. In long run result indicated the negative effect amid economicgrowth and energy use from renewable sources. Bakirtas and Akpolat (2018), explored the bond amongst urbanization, energy use and economic development in the markets of new emergent nations which includes India, Malaysia, Indonesia, Mexico, Colombia, and, Kenya, on time series data over the years 1971 to 2014 for the study by applying Dumitrescu-Hurlin panel granger causality test to discover joint interconnection impact from the two series. The study concluded that due to bivariate analysis, relationship from economic development to energy usage, relation of urbanization to consumption of energy and the economic development lies panel granger causality and according to trivariate analysis from energy use and relation from urbanization to economic development and from the relation of economic growing and urbanization to energy usage and the relation of energy use to economic development to urbanization lies the panel granger causality.
Within such an environment before describing and implementing the multivariate models’ investigation, the study also finds it necessary to give some introduction information regarding the foreign trade accounts of Turkey as well as the composition of the trade flows. While Turkey is observed to be a final good exporter, its composition of imports is different. Within this framework, decomposition of exports and imports should be investigated differently. When we observe the historical path of exports, results remark that industrial products has an average share of 84% for the post 1980 period, which represents the start of the liberalized era for Turkey. Moreover most recent statistics underline that EU has the highest share in the export targets of the country. Figures underline that in 2008 60% of total exports are to the Euro area. More interesting is the path of the composition of import volumes. While final remark regarding the causalrelationshipbetween imports and growth seems to be an empirical matter of fact, import led growth models remark the significance of intermediate and investment goods in the import composition whereas, growth led import understanding underlines the consumption goods share in the overall environment. Table 1 illustrates the historical developments in the composition of import volumes of Turkey for the post 1980 period. Findings indicate that for the post 1980 liberalization era, while composition of exports change slightly, import decomposition seems to realize a relatively stable path.
To investigate the causality between biomass energyconsumption (BMC), real GDP (Y) and oil prices (OP) for 10 countries, the paper employed the ARDL approach of cointegration developed by Pesaran (1997) and Pesaran and Shin (1999) 7 . Recently, ARDL has become popular due to the low power and other problems associated with Johansen(1988), Engle-Granger (1987) and Johansen and Juselius (1990). The ARDL cointegration approach has numerous advantages over other cointegration methods. First, the ARDL procedure can be applied if the regressors are I(1) and/or I(0), while the Johansen cointegration techniques require that all variables in the system be of equal order of integration. The ARDL can be applied irrespective of whether underlying regressors are purely I(0), purely I(1) or mutually cointegrated and therefore do not need unit root pre-testing. Second, while the Johansen cointegration techniques require large data samples for validity, the ARDL procedure is a statistically more effective in determining the cointegration relationship in small samples. Third, the ARDL procedure allows the variables to have different optimal lags. Finally, the ARDL procedure employs only a single reduced form equation, while the other cointegration procedures estimate the long-run relationship within a context of system equations.
The results of the granger causality tests of this research are in line with findings by Erol and Yu (1987), Yu and Jin (1992), and Masih and Masih (1996), who obtained similar results on other countries as well as Malaysia case. The granger causality tests conducted above indicate only the existence of causality. They do not, however, provide any indication on how important is the causal impact that energy has on output formation. For example, when there is a shock to energy supply, it would also be interesting to gauge by how much this shock will affect the output formation. In addition, it is very important to know how long the effect of such a shock will last. In order to provide such explanation, we decompose the variance of the forecast-error of output into proportions attributable to innovations in variable energy in the system including its own. Impulse response analysis is taken into account to further capture temporal responses of a variable to its own innovation and innovations in other variables in the system. The function can observe whether the response of observable variables is temporal or persistent in nature.
The economicgrowth and energyconsumption nexus was previously investigated by numerous research studies. From these previous research studies, four hypotheses regarding this nexus can be found in the empirical literature that dealt with this topic. These include the conservation hypothesis, the growth hypothesis, the neutrality hypothesis and the feedback hypothesis. In the first place, the conservation hypothesis claims that the changes in energyconsumption originate from the changes in the level of economic activity. Secondly, the growth hypothesis is based on unidirectional causality running from energyconsumption to economicgrowth. Further, the growth hypothesis assumes that there are countries where the increase of energyconsumption is a significant component of economic development. Next, the feedback hypothesis assumes that there are countries with bi-directional causal relationships betweeneconomicgrowth and energyconsumption. Finally, the neutrality hypothesis states that there are countries in which energyconsumption does not depend on economicgrowth and vice versa. In this article, the author investigates the nexus betweenenergyconsumption and economicgrowth in 10 Southern Africa Development community (SADC) countries. The author applied the Granger’s causality analysis, which allows for the investigation of the existence and direction of influence betweenenergyconsumption and economicgrowth. The article makes a significant contribution to existing literature because the investigation focuses on SADC countries, which as far as the author knows, have rarely been studied collectively by the previous studies. In addition, these countries have not been studied collectively using the methodology that is used in this study.
Yang (2000), using updated data from 1954-1997 for Taiwan Province of China, investigated the causalrelationshipbetween GDP and the aggregate categories of energyconsumption, including coal, natural gas and electricity. He found bidirectional causality between total energyconsumption and GDP. Pachauri (1977) found that there was a strong correlation betweeneconomic development and energyconsumption in India. Stern (2000), in a study of the United States economy, found in a multivariate dynamic analysis that energy not only Granger causes GDP, it is also significant in explaining GDP. He also found co-integration in a relationshipbetween the factors (GDP, capital, labour and energy). Ghali and El-Sakka (2004) conducted a study on the causality betweenenergyconsumption and economicgrowth in Canada. They found that the short-run dynamics of variables indicate that Granger’s causality between output growth and energy use was bidirectional.
Regarding the qualitative data analysis, interviewee P2 states that: “Employees have the space to give ideas which can be incorporated in advancing the working environment, their ideas are welcomed to us as managers.” However, when the final decision is taken about implementing or not an innovative idea, interviewees with consensus indicate that it is the management, which has the last word, and staff has no direct authority in decision-making. Concerning the evaluation and experimenting of innovative ideas, interviewee P4 states as follows: “We lack on financial resources to experiment new ideas, although when funds exist, we foremost participate actively in testing new ideas.” Concerning citizen participation in designing or planning new or improved services, interviewee P3 states: “Citizens have the tools to proclaim their concerns and give recommendations, however, these recommendations are rarely incorporated in the decision making process.” Thus, when analyzing the information given from the eight interviewees in total, findings indicate that it is the management which takes the final decision and the staff is not motivated or incorporated in the decision making process. Another consensus among the interviewees was about the incorporation of recommendations coming from citizens, which recommendations are rarely taken in consideration.
A valid contribution to the topic of the relationshipbetween renewable energyconsumption and real GDP was done by Apergis & Payne (2010a; 2010b; 2011) too. Scientists had analyzed the statistical data of various groups of countries those level of economic development was very different. They used heterogeneous panel co- integration and Granger causality tests to reveal the relationshipbetween renewable energyconsumption and real GDP in short- and long-run. The results of the tests for different groups of countries were very similar. The results of the heterogeneous panel co-integration test showed that a long-run equilibrium relationshipbetween renewable energyconsumption and real GDP existed in 20 OECD countries during 1985-2005 (Apergis & Payne, 2010a), 15 Eurasia (including Lithuania) countries during 1992-2007 (Apergis & Payne, 2010b), 6 Central America countries during 1980-2006 (Apergis & Payne, 2011). However, the elasticity coefficients for renewable energyconsumption with respect to real GDP were different. It was calculated that a 1% increase in renewable energyconsumption increased real GDP in OECD countries by 0.76%, in Central America countries by 0.244%, in Eurasia countries by 0.195% when Russia is included in the analysis and only by 0.074% when Russia is excluded. The results of Granger causality test supplemented the results of performed heterogeneous panel co-integration test in two ways. Firstly, Granger-causality test affirmed that bi- directional causality between two variables existed both in short- and long-run. Secondly, the results indicated that renewable energyconsumption might affect real GDP through its positive impact on real gross ﬁxed capital formation. Later Apergis et al. (2010c) expanded the scope of research in a way they investigated the causality relationships between four variables, i.e. between CO 2
Economicgrowth is one of the most important determinants of economic welfare. The global economic crisis that broke out in 2008 has reawakened interest in fiscal policy as an instrument for longer-term growth and development. The term fiscal policy has conventionally been associated with the use of government revenue, especially taxation and public expenditure to influence the level of economic activities. The implementation of fiscal policy is essentially routed through government’s budget. Fiscal policy deals with government deliberate actions in spending money and levying taxes with a view to influencing macro-economic variables in a desired direction. This includes sustainable economicgrowth, high employment creation and low inflation. Thus, fiscal policy aims at stabilizing the economy, Increases in government spending or a reduction in taxes tend to pull the economy out of a recession; while reduced spending or increased taxes slow down a boom ( Ruba, 2014).