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To examine environmental pollution by economic growth and their impact in an environmental Kuznets curve (EKC) among developed and developing countries by Kong, YuSheng; Khan, Rabnawaz; Gherghina, Stefan Cristian is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is To examine environmental pollution by economic growth and their impact in an environmental Kuznets curve (EKC) among developed and developing countries about?
This study analyzes the core energy consumption among countries' specific variables by Environmental Kuznets Curve hypothesis (EKC), for a panel data of 29 (14 developed and 15 developing) countries during the period of 1977-2014. By assessing Generalized Method of Moments (GMM) regressions with first generation tests such as common root, individual Augmented Dickey-Fuller (ADF), and individual root-Fisher-PP which have been computed individually, the results confirm the EKC hypothesis in the case of emissions of solid, liquid, gases, manufacturing industries and also construction. Hence, we computed the cointegration test by Pedroni Kao from Engle-Granger based and Fisher. Since the variables are co-integrated, a panel vector error correction model is estimated in GDP per capita, emission from manufacturing industries, arms import, commercial service export, and coal rent, in order to perform Pairwise Granger Causality test and indicate Vector Error Correction (VEC), with co-integration restrictions. Moreover, the statistical finding from VEC short-run unidirectional causality from GDP per capita growth to manufacturing industries and coal rent, as well as the causal link with man
Who reads To examine environmental pollution by economic growth and their impact in an environmental Kuznets curve (EKC) among developed and developing countries?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Kong, YuSheng; Khan, Rabnawaz; Gherghina, Stefan Cristian
- Publisher
- Public Library of Science; San Francisco CA: Public Library of Science; Publons; ScienceOpen; Public Library of Science (PLoS) (ISSN 1932-6203)
- Published
- 2019
- Language
- EN
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)