• Energy Research

Abstract This paper investigates the short-run and long-run causality issues between electricity consumption and economic growth in the selected 11 Middle East and North Africa (MENA) countries by using Autoregressive Distributed Lag (ARDL) bounds testing approach of cointegration and vector error-correction models. It employs annual data covering the period from 1971 to 2006. The unit root tests results indicate that some of the variables for Algeria, Jordan, Tunisia and United Arab Emirates do not satisfy the underlying assumptions of the ARDL bounds testing approach of cointegration methodology before proceeding to the estimation stage. Thus, we drop these countries from the ARDL bounds testing approach of cointegration and causality analysis. The cointegration test results show that there is no cointegration between the electricity consumption and the economic growth in three of the seven countries (Iran, Morocco and Syria). Thus, causal relationship cannot be estimated for these countries. However, the cointegration and causal relationship is found in four countries (Egypt, Israel, Oman and Saudi Arabia). The overall results indicate that there is no relationship between the electricity consumption and the economic growth in most of the MENA countries. Further evidence indicates that policies for energy conservation can have a little or no impact on economic growth in most of the MENA countries.

Abstract This study investigates the relationship between natural gas energy consumption and economic growth by including trade openness, total labor force and gross fixed capital formation as a major determinants of GDP growth within the multivariate framework model in Gulf Cooperation Council (GCC) countries. A panel GDP model is constructed taking the period of 1980–2012. The result revealed that natural gas energy consumption is cointegrated with GDP growth in the investigated countries. In addition, based on the panel dynamic ordinary least square (DOLS) and the fully modified ordinary least square (FMOLS), this study concluded that the natural gas energy consumption affects the GCC’s countries GDP growth positively in the long run. Furthermore, the results from the Granger causality test revealed bidirectional causality between natural gas energy consumption and GDP growth which confirms the feedback hypothesis. From the outcome of this research, a number of policy implications were provided for the GCC countries.

Abstract This paper provides a survey of the recent progress in the literature of energy consumption–economic growth and electricity consumption–economic growth causality nexus. The survey highlights that most empirical studies focus on either testing the role of energy (electricity) in stimulating economic growth or examining the direction of causality between these two variables. Although the positive role of energy on growth has become a stylized fact, there are some methodological reservations about the results from these empirical studies. A general observation from these studies is that the literature produced conflicting results and there is no consensus neither on the existence nor on the direction of causality between energy consumption (electricity consumption) and economic growth. As a policy implication, to avoid from conflicting and unreliable results, the authors may use the autoregressive distributed lags bounds test, two-regime threshold co-integration models, panel data approach and multivariate models including new variables (such as: real gross fixed capital formation, labor force, carbon dioxide emissions, population, exchange rates, interest rates, etc.). Thus, the authors should focus more on the new approaches and perspectives rather than by employing usual methods based on a set of common variables for different countries and different intervals of time.

Abstract The aim of this research is to examine the link between CO 2 emissions, hydroelectricity consumption, urbanisation and real GDP in China and India during the period of 1965–2013. The long-run cointegration is investigated by the autoregressive distributed lag (ARDL) bounds testing approach, which is augmented with structural breaks. We employ the ARDL cointegration test to establish long run relationship in the variables. Furthermore, we use the ARDL to show that real GDP and urbanisation have long-run positive impact on emission, while hydroelectricity consumption exerts long-run negative impact on emission in both countries. The results support the existence of environmental Kuznets curve (EKC) hypothesis in China and India. Besides, the paper assesses the causal link between the variables by using Granger causality procedures and the results show that there is long-run bidirectional relationship between the variables in both countries.

The dispute between economic growth and greenhouse gas emissions is one of the major challenges of the twenty-first century. The central issue of the emerging economies revolves around the decoupling of economic growth and the rising carbon dioxide (CO2) emissions. This study examines the decoupling the CO2 emissions from the economic growth through the employment of the Tapio decoupling index and decomposition of CO2 emissions into its pre-determined factors through the Log Mean Divisia Index (LMDI) decomposition technique for Pakistan, India, and China (PIC) for a time span of 1990–2014. The findings of the Tapio elasticity analysis depict that in a few years, environmental impact has been seen to be decoupled from the economic growth in the respective PIC countries. However, relatively Pakistan experienced expensive negative decoupling; India mostly experienced weak decoupling and expensive coupling, while China exhibited weak decoupling in multiple years. In addition, the analysis of Tapio decoupling elasticity showed that energy intensity is the key factor supporting the decoupling in PIC countries, while population, affluence (GDP per capita) and energy structure have weakened the progress of decoupling. Furthermore, the analysis of the LMDI decomposition suggested that population, energy structure and affluence in PIC countries increase the CO2 emissions, while energy intensity reduces CO2 emissions, while mixed effects are reflected by carbon intensity.

This study investigates the environmental Kuznets curve (EKC) hypothesis in Kenya using the time period of 1980–2012. To achieve the objective of this study, the ARDL approach was utilized. To prevent any estimation errors and unreliability in the model, the Narayan and Narayan (Energy Policy 38:661–666, 2010) approach was used to control the multicollinearity problems in the regression. The outcome of this research revealed that fossil fuel energy consumption, GDP, urbanization, and trade openness increase air pollution mutually in the long run and short run. However, renewable energy consumption mitigates air pollution in the long run and the short run. Moreover, financial development also reduces air pollution, but only in the long run. Based on the results, the EKC hypothesis does exist in Kenya. From the findings of this research, few policy recommendations were provided to help Kenya for reducing its air pollution levels.

Abstract In the quest towards a cleaner environment via the mitigation of climate change and its impact, this study examined the validity of the environmental Kuznets curve (EKC) hypothesis, energy efficiency and energy consumption indicators in Kenya. The study employed an autoregressive distributed lag technique, statistically inspired modification of partial least squares regression and Utest method to analyze four models with data spanning 1971 to 2013. Both the autoregressive distributed lag model and the Utest estimation confirmed an inverted u-shaped curve, thus, validating the environmental Kuznets curve hypothesis in Kenya. The study revealed that an increase in energy consumption exacerbates carbon dioxide emissions in the long-run. The statistically inspired modification of partial least squares regression revealed that electricity from renewable energy sources plays a critical role in carbon dioxide emission reduction. An increase in GDP per capita and household consumption expenditure increases energy consumption. Energy imports had no long-run effect due to the recent oil discovery, coal, prospects of nuclear energy and the potential for more renewable energy sources in Kenya. The study highlights that using sustainable technologies like, inter alia, carbon capture and storage in the exploitation of oil and coal are essential to reducing pollution. Rural-urban migration increases the burden on electric power consumption, thus, reducing energy efficiency if conservation options are not enforced. As a policy implication, engaging the public on energy conservation and management options will help curb energy challenges like load shedding — which appears troubling in Africa.

AbstractThis study investigates the influence of biofuel energy consumption on Brazil's economic growth during the period 1980–2012 by employing the Autoregressive Distributed Lag (ARDL) approach and the vector error correction model (VECM) Granger causality. The results revealed two structural breaks during the early 1980s due to the Latin American debt crisis as well as the early 2000s due to the worries related to the increasing global spreads. Moreover, it was found that economic growth, biofuel energy consumption, capital, urbanization, and globalization are co‐integrated. Additionally, it was found that biofuel energy consumption, capital, urbanization, and globalization increase Brazil's economic growth in the short run and in the long run. However, the two structural breaks have a significant negative influence on economic growth. The vector error correction model Granger causality revealed a feedback causal relationship between all the variables (with the exception of capital). However, a unidirectional causality was concluded from capital to economic growth, biofuel energy consumption, urbanization, and globalization. From the results of this study, a number of policy implications were provided. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

This study explores the effect of economic growth (GDP), renewable energy consumption (RE) and financial development (FD) on CO2 emission (CO2) in Latin America and Caribbean countries. To achieve this goal, a panel CO2 model was built over the period 1980–2010. The Kao cointegration test results revealed that the variables are cointegrated. The Fully Modified OLS (FMOLS) results indicated an inverted U-shape relationship between CO2 and GDP, thus confirming the Environmental Kuznets Curve hypothesis. Furthermore, FMOLS results also revealed that FD can improve environmental quality by its negative long-run effect on CO2. However, RE has no long-run effect on CO2 indicating that the RE does not contribute to CO2 reduction. The VECM Granger causality results revealed feedback causality between GDP, RE, FD and CO2 in both short- and long-run. Additionally, Granger causality results also revealed that RE, GDP, and FD can be a good solution to reduce environmental damage since they have a causal effect on CO2. This study shows the investigated countries should increase their banking loans on green energy, energy efficiency and energy saving projects to reduce environmental damage. In addition, the above recommendation can increase the contribution of renewable energy in reducing environmental damage.