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
•Journal Article
CO2 emissions, economic growth and energy consumption in Iran: A cointegration approach
TL;DR: In this article, the authors examined the dynamic relationship among carbon dioxide (CO2) emissions, economic growth and energy consumption based on the environmental Kuznets curve (EKC) hypothesis for Iran during the period 1971-2007.
43
Income inequality, ecological footprint, and carbon dioxide emissions in Asian developing economies: what effects what and how?
Salim Khan,Wang Yahong +1 more
TL;DR: In this paper, the authors analyzed the impact of income inequality on both carbon emissions and ecological footprint, and confirmed the positive relationship between carbon emissions, ecological footprint and income inequality under the methodology of Driscoll and Kraay (D&K) standard error approach.
The changing of the relationships between carbon footprints and final demand: Panel data evidence for 40 major countries
TL;DR: In this article, the authors analyzed the relationship between the emissions caused by countries from a demand point of view, the carbon footprints and the demand for goods and services in these countries, and especially in the European countries.
42
Carbon Emissions and Economic Growth: Production-based versus Consumption-based Evidence on Decoupling
Servaas Storm,G.U.R. Mir +1 more
TL;DR: In this paper, the authors assess the Carbon-Kuznets-Curve hypothesis using internationally consistent and comparable production-based versus consumption-based CO2 emissions data for 40 countries(and 35 industries) during 1995-2007 from the World Input Output Database (WIOD).
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.