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The aim of this study is to explore the relationship between renewable energy consumption and economic growth within the framework of traditional production function for the period of 1990–2012 in 9 Black Sea and Balkan countries. For this purpose, we use Pedroni (1999, 2004) panel cointegration, Pedroni (2000, 2001) co-integration estimate methods and Dumitrescu and Hurlin (2012) heterogeneous panel causality estimation techniques. The study has concluded that there is a long term balance relationship between renewable energy consumption and economic growth and renewable energy consumption has a positive impact on economic growth. Heterogeneous panel causality analysis results support growth hypothesis in Bulgaria, Greece, Macedonia, Russia and Ukraine; feedback hypothesis in Albania, Georgia and Romania; neutrality hypothesis in Turkey and according to the panel data set including all nine countries the results support feedback hypothesis. With the findings, it was concluded that there is a significant impact of renewable energy consumption on economic growth in Balkan and Black Sea Countries.

Unlike previous energy consumption-economic growth studies, this study examines the relationship among energy consumption, economic growth, employment and gross fixed capital formation for 17 highly developed OECD countries by employing both the Toda–Yamamoto procedure which based on asymptotic critical values and the bootstrap-corrected causality test, since non-normality of the error term harms the validity of the Toda–Yamamoto procedure. This study finds that there is very small bias due to the assumption of normality. Furthermore using different information criterions, importance of lag length is tested. Findings indicate that selection of lag length is important for Denmark, Ireland, Norway and Spain. It is concluded that while there exists uni-directional causality running from energy consumption to real GDP for Japan, bi-directional causality is found for Italy, New Zealand, Norway and Spain. On the other hand, uni-directional causality from GDP to energy is found for Australia, Canada and Ireland whereas no causal nexus is found for all of other nine countries. Our analyses covering the sample periods imply that Japan, Italy, New Zealand, Norway and Spain should not follow energy conservation policy at the aggregated level, since the reduction of energy damages the economic growth.

Abstract The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil–agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda–Yamamoto and the nonparametric causality method of Diks–Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies.

Abstract In conventional causality testing based on asymptotic distribution theory, there is a high risk of wrongly rejecting the true null of no causality especially when the sample size is as small as typically seen in the literature. In this study, we offer a formal diagnosis of the existing contradictory results on the causal relationship between energy consumption and real GDP. We also employ a time series oriented advanced data generation process to perform simulation based inference for the People's Republic of China. Our study covers the 1971–2007 period and considers five different aggregated and disaggregated energy consumption measures as well as three different lag orders in both a bivariate as well as a multivariate frameworks. Our maximum entropy bootstrap based analysis, which avoids pretest biases and is also robust to Type I errors, supports the neutrality hypothesis in 53 out of the total of 60 model estimations. The strong results show that coarse aggregate data has a limited potential to observe the complex causal linkages between energy consumption and economic growth. Future policy oriented research on this nexus requires more focused analyses based on sectoral and provincial data.

Abstract With the world's lowest electrification rate, Africa is repositioning to offer its citizens a brighter future. Global renewable energy agencies and international financing to expedite rural electrification fueled by off-grid solar systems are attracting worldwide attention. Currently, 770 million people lack access to electricity on the continent, and more than 60% live in poor rural areas where the national power grid is non-existent. The challenge herein is how to supply electricity to rural population, living on $1.5 a day, at a reasonable power tariff. Although there are opportunities for off-grid solar energy to keep growing in sub-Saharan countries, it is impossible to ignore particular challenges in these countries. This paper focuses on three sub-Saharan counties: Kenya, Ethiopia, and Rwanda. Rwanda, Kenya, and Ethiopia foster off-grid solar systems as the primary solution through rural electrification programs. This paper provides a comparative analysis of the electrification experiences of these countries in terms of sources of funding, the challenges and opportunities they have been experiencing as well as an analysis of policy implications. The results show that off-grid solar systems improve health, ICT, and micro-enterprises in rural areas. However, governments should generate more robust developmental schemes that provide income to rural people that pushes them above the poverty line and enables them to afford off-grid solar products.

This paper aims to investigate the relationship between energy use-GDP, energy use-exports-trade and energy use-imports on aggregate level in the OECD countries. While the energy use-growth nexus is widely examined in the literature, studies on the energy use-trade nexus are very scarce. Thus, this study also serves to fill this gap by presenting a new research on the OECD countries. We employ the panel cointegration technique and use the Granger representation theorem to examine the presence of long-run relationship and the causality between pairs of variables. To investigate the presence of causality, several tests developed by Canning and Pedroni (2008) are used. We find that the pairs of energy use-GDP, energy use-exports and energy use-imports are cointegrated and there is two-way Granger causality between each pairs. We also estimate the long-run elasticities by employing panel dynamic ordinary least squares. The results suggest that the sign of long-run elasticity is positive for all pairs. Particularly, 1% increase in GDP, export and import causes almost 0.32%, 0.21% and 0.16% increase in energy use respectively.

Abstract Energy consumption in the industrial and commercial (service) sectors accounts for nearly 40% of global greenhouse gas emissions. Reducing this energy consumption will be critical for countries to achieve their national greenhouse gas reduction commitments. The ISO 50001-Energy management standard provides a continual improvement framework for organizations to reduce their consumption. Several national policies already support ISO 50001; however, there is no transparent, consistent process to estimate the potential impacts of its implementation. This paper presents the ISO 50001 Impacts Methodology, an internationally-developed methodology to calculate these impacts at a national, regional, or global scale suitable for use by policymakers. The recently-formed ISO 50001 Global Impacts Research Network provides a forum for policymakers to refine and encourage use of the methodology. Using this methodology, a scenario with 50% of projected global industrial and service sector energy consumption under ISO 50001 management by 2030 would generate cumulative primary energy savings of approximately 105 EJ, cost savings of nearly US $700 billion (discounted to 2016 net present value), and 6500 million metric tons (Mt) of avoided CO 2 emissions. The avoided annual CO 2 emissions in 2030 alone are equivalent to removing 210 million passenger vehicles from the road.

This study investigates the effect of renewable energy production on water and land footprint in 58 developed and developing countries for the period of 1980–2009. Utilizing the ecological footprint as an indicator, the fixed effects, difference and system generalized method of moment (GMM) approaches were employed and eight different models were constructed to achieve robustness in the empirical outcomes. Despite the use of different methods and models, the outcome was the same whereby GDP growth, urbanization, and trade openness increase the water and land footprint. Moreover, renewable energy production increases the water and land inefficiency because of its positive effect on ecological footprint. Additionally, based on the square of GDP it is concluded that the EKC hypothesis does not exist while the square of renewable energy production indicates that renewable energy production will continue to increase water and land footprint in the future. From the outcome of this study, a number of recommendations were provided to the investigated countries.

Abstract This study examines the long-run relationship between carbon emissions and energy consumption, income and foreign trade in the case of China by employing time series data of 1975–2005. In particular the study aims at testing whether environmental Kuznets curve (EKC) relationship between CO 2 emissions and per capita real GDP holds in the long run or not. Auto regressive distributed lag (ARDL) methodology is employed for empirical analysis. A quadratic relationship between income and CO 2 emission has been found for the sample period, supporting EKC relationship. The results of Granger causality tests indicate one way causality runs through economic growth to CO 2 emissions. The results of this study also indicate that the carbon emissions are mainly determined by income and energy consumption in the long run. Trade has a positive but statistically insignificant impact on CO 2 emissions.