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Determinants of CO2 emissions in the European Union: The role of renewable and non-renewable energy
Eyup Dogan,Fahri Seker +1 more
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In this article, the authors investigated the impacts of renewable and non-renewable energy, real income and trade openness on CO2 emissions in the Environmental Kuznets Curve (EKC) model for the European Union over the period 1980-2012 by employing panel estimation techniques robust to cross-sectional dependence.About:
This article is published in Renewable Energy.The article was published on 2016-08-01. It has received 679 citations till now. The article focuses on the topics: European union & Greenhouse gas.read more
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Determinants of the ecological footprint: Role of renewable energy, natural resources, and urbanization
Recep Ulucak,Shahrukh A. Khan +1 more
TL;DR: In this article, the authors explored the relationship between real income, renewable energy, urbanization, natural resource rent, and ecological footprint in BRICS economies and developed important policy implications for BRICS countries to achieve sustainable development targets.
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Effect of natural resources, renewable energy and economic development on CO2 emissions in BRICS countries.
TL;DR: Abundance of natural resources mitigates CO2 emission in Russia, but contributes to pollution in South Africa, and natural resources help to form Environmental Kuznets Curve (EKC) hypothesis in Brazil, China, Russia, and South Africa.
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Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan
TL;DR: The main contribution of this study is to test the Environmental Kuznets Curve hypothesis at individual country analysis by the significance of renewable energy and non-renewable energy consumption in the context of Pakistan as mentioned in this paper.
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CO2 emissions, economic and population growth, and renewable energy: Empirical evidence across regions
TL;DR: In this paper, the authors investigated the nexus among carbon dioxide emissions, economic and population growth, and renewable energy across regions using an unbalanced panel dataset of 128 countries over the period 1990-2014.
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The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators
Roula Inglesi-Lotz,Eyup Dogan +1 more
TL;DR: In this article, the authors estimate the determinants of CO2 emissions for the ten biggest electricity generators in Sub-Saharan Africa for the period 1980 to 2011 by employing panel estimation techniques robust to cross dependence.
References
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Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI
Distribution of the Estimators for Autoregressive Time Series with a Unit Root
David A. Dickey,Wayne A. Fuller +1 more
TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
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Testing for a Unit Root in Time Series Regression
TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
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Bounds testing approaches to the analysis of level relationships
TL;DR: In this paper, the authors developed a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary.
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Testing for unit roots in heterogeneous panels
TL;DR: In this article, a unit root test for dynamic heterogeneous panels based on the mean of individual unit root statistics is proposed, which converges in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension)→∞.