Showing papers in "Energy Economics in 2019"

TL;DR: In this paper, the authors investigated the direct and indirect effect of financial development on carbon emissions for 46 sub-Saharan Africa countries over the period 2000-2015, using the system-generalised method of moments.

TL;DR: The authors examined the effect of research and development (R&D) intensity on carbon dioxide (CO2) emissions in the Group of Seven (G7) countries since the nineteenth century using a non-parametric panel data model.

TL;DR: In this paper, the authors used the logarithmic mean divisia index (LMDI) to estimate seven socioeconomic drivers of the changes in CO2 emissions in China since 2000 and found that China's carbon emissions have plateaued since 2012 mainly because of energy efficiency gains and structural upgrading.

TL;DR: A review of the burgeoning literature dedicated to Energy Economics/Finance applications of ML suggests that Support Vector Machine, Artificial Neural Network, and Genetic Algorithms are among the most popular techniques used in energy economics papers.

TL;DR: In this article, the authors examined the effect of human capital on energy consumption for a panel of OECD economies over the period 1965-2014 and found that a one standard deviation increase in human capital reduces aggregate energy consumption by 15.36%.

TL;DR: In this paper, the role of research and development (R&D) investment on firms' environmental performance was investigated using a firm-level data for the period 2004-2016 from G-6 countries, and they found that R&D investment improves the firm's environmental performance consistent with the theoretical argument of natural resource-based view.

TL;DR: In this article, the authors extend the current literature by incorporating urbanization, energy consumption and international trade into a production function using a panel data set model over the period from 2001 to 2012.

TL;DR: This article examined the causal relationship between economic growth, energy consumption and carbon dioxide (CO2) emissions in high-income and upper-middle-income countries using the simultaneous equations framework, with data from 1985 to 2011.

TL;DR: In this article, the effects of foreign trade and foreign direct investment (FDI) on CO 2 emissions in Turkey were examined and an environmental Kuznets curve was found for both CO 2 measures.

TL;DR: In this paper, the authors examined the information interdependence among various commodities, such as energy, metals and agricultural commodities, and leading cryptocurrencies and found that cryptocurrencies are integrated within broadly defined commodity markets.

TL;DR: In this article, the authors investigated the dynamic directional information spillover of return and volatility between the fossil energy market, investor sentiment towards renewable energy and the renewable energy stock market using the connectedness network approach.

TL;DR: In this article, the authors used a new spillover directional measure and asymmetric spillover measures to investigate the dynamic asymmetric volatility spillover between oil and stock markets during the period of 2007 to 2016.

TL;DR: This article examined the relationship between oil prices and economic policy uncertainty in G7 countries using a nonparametric panel data technique that allows the trend and coefficient functions to evolve as unknown time-varying functional forms.

TL;DR: An overview of the current debate on the necessity of capacity remuneration mechanisms is provided in this paper, where the initial experiences of real-world implementations are discussed, and common findings in the literature, categorized by their economic implications, are derived.

TL;DR: In this article, the authors developed an embodied carbon analysis framework by integrating input-output approaches to explore the extent to which and how ICT drives carbon emissions at the sector level.

TL;DR: In this article, the nexus of GHG emission with tourism, financial development index, energy use, renewable energy, and trade in 34 high-income countries from three continents (Asia, Europe, and America) from 1995 to 2017 was explained.

TL;DR: In this article, the dynamic dependence between WTI crude oil and the exchange rates of the United States and China, taking structural changes of dependence into account by using six time-varying copula models, is analyzed.

TL;DR: In this article, the authors established five counter-measured scenarios based on the recently launched China's national carbon trading market and constructed a dynamic recursive Computable General Equilibrium model to study the impact of national ETS on the economy, energy and environment.

TL;DR: In this article, the role of serious geopolitical risk (GPRS) in forecasting oil volatility was investigated and the GARCH-MIDAS model was extended by incorporating GPR and GPRS from both statistical and economic significance.

TL;DR: The authors examined the frequency dynamics of volatility spillovers between crude oil and China's stock markets in a spectral representation framework of generalized forecast error variance decomposition using sectoral stock indices data and found evidence of total volatility spillover driven mainly by short-term spillovers.

TL;DR: In this paper, the predictive ability between forecast combination and shrinkage method in the prediction of oil price volatility was compared based on the heterogeneous autoregressive (HAR) framework, and it was shown that the elastic net and lasso have significantly better out-of-sample forecasting performance than not only the individual extended HAR models but also the combination approaches.

TL;DR: In this paper, the authors characterize the oil market as a nonlinear-switching phenomenon and examine its dynamics in response to changes in geopolitical risks over low and high risk scenarios, finding that the effects of threats appear to be moderate or non-significant.

TL;DR: In this paper, the authors proposed a new modeling framework allowing for the variable-specific decomposition of the environmental performance along time and quantity dimensions to identify the underlying patterns, and applied the Luenberger productivity indicator to decompose air pollutant emissions performance.

TL;DR: Wang et al. as mentioned in this paper extended the DEA model to consider two-sided nonhomogeneous problems, handling DMU sets that have non-homogeneity in both inputs and outputs, and the overall efficiency of 38 industrial sectors in China maintained a rising trend in five years.

TL;DR: Wang et al. as discussed by the authors employed a unique dataset of firm-level data on 13 cities in Jiangsu Province of China and investigated the relationship between FDI and energy intensity, taking into account the heterogeneity characteristics of firms, which implies that FDI firms have lower energy intensity than their local counterparts.

TL;DR: Zhang et al. as discussed by the authors employed the non-radial direction distance function to construct the green economic growth index by employing the System-GMM estimation, and further evaluated the effect of fiscal education spending and R&D spending on green economy growth.

TL;DR: In this article, a combined decomposition approach to emissions analysis by integrating the logarithmic mean Divisia index and production-theoretical decomposition analysis was developed to study CO2 emissions.

TL;DR: In this paper, the authors examined the extent of volatility between oil price and sectoral indices in the Gulf Cooperation Council (GCC) countries by using quantile regression analysis (QRA) for the return's series and denoised series over the period 2006-2017.

TL;DR: In this article, the impacts of changes in the implied volatility index of the oil market (OVX) on the changes in a Chinese stock market (VXFXI) were investigated.

TL;DR: In this article, the authors studied how different sources of oil price shocks are connected to exchange rates of major oil-dependent countries using daily data from March 1996 to February 2019. And they found that the connectedness of this relationship between price shocks and exchange rates has significantly increased after the global financial crisis.