Journal Article10.1016/J.ENPOL.2009.09.005
Carbon dioxide emissions and economic growth: Panel data evidence from developing countries
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TL;DR: In this article, the authors test the Environment Kuznet's Curve (EKC) hypothesis for 43 developing countries and find that carbon dioxide emissions have decreased with a rise in income.
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About: This article is published in Energy Policy. The article was published on 01 Jan 2010. The article focuses on the topics: Income elasticity of demand & Panel data.
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Citations
The relationship between energy consumption and fiscal decentralization and the importance of urbanization: Evidence from Chinese provinces
TL;DR: Fiscal decentralization has a non-linear relationship with energy consumption, which confirms the concave behaviour of fiscal decentralization in the Chinese provinces and underscores the validity of the environmental Kuznets curve hypothesis in those provinces, given the control variables.
Testing the nuclear energy induced environmental Kuznets curve for Bulgaria: An ARDL bounds test with sharp and smooth breaks
Veli Yilanci,Qasim Raza Syed,Ilham Haouas +2 more
- 09 Jan 2024
TL;DR: Nuclear energy reduces emissions in Bulgaria, supporting the Environmental Kuznets Curve hypothesis.
Is the Environmental Kuznets Curve Hypothesis Valid for Kenya? an Autoregressive Distributed Lag (ARDL) Approach
Yabesh Ombwori Kongo,Ernest Saina,Vincent Ngeno +2 more
TL;DR: This study examines the Environmental Kuznets Curve (EKC) hypothesis in Kenya using ARDL model, finding no evidence of EKC, indicating economic activities do not positively affect emissions, and recommends investing in environmental policies alongside economic development for sustainable growth.
Clarifying the Relationship Among Green Investment, Clean Energy Consumption, Carbon Emissions, and Economic Growth: A Provincial Panel Analysis of China
Yuanyuan Wan,Ning Sheng +1 more
TL;DR: This study examines the relationships between green investment, clean energy consumption, carbon emissions, and economic growth in China's 30 provinces and cities from 2003 to 2017, revealing significant positive impacts on clean energy and economic growth, but no effect on carbon emissions.
References
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)→∞.
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Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors
TL;DR: In this paper, a method for testing the null of no cointegration in dynamic panels with multiple regressors and computing approximate critical values for these tests is presented. But the method is limited to simple bivariate examples, in large part due to the lack of critical values available for more complex multivariate regressions.
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•Posted Content
Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors
TL;DR: In this paper, a method for testing the null of no cointegration in dynamic panels with multiple regressors and computing approximate critical values for these tests is described, which allows for considerable heterogeneity among individual members of the panel, including heterogeneity in both the long-run cointegrating vectors as well as heterogeneity in the dynamics associated with short-run deviations from these coefficients.
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The Rise and Fall of the Environmental Kuznets Curve
TL;DR: A critical history of the environmental Kuznets curve (EKC) can be found in this article, where a new generation of decomposition and efficient frontier models can help disentangle the true relations between development and the environment and may lead to the demise of the classic EKC.
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The local power of some unit root tests for panel data
TL;DR: In this article, the local power of panel unit root statistics against a sequence of local alternatives is studied and the results of a Monte Carlo experiment suggest that avoiding the bias can improve the power of the test substantially.