To examine environmental pollution by economic growth and their impact in an environmental Kuznets curve (EKC) among developed and developing countries

• Published in: PloS one Vol. 14; no. 3; p. e0209532
• Main Authors: Kong, YuSheng, Khan, Rabnawaz
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 26.03.2019; Public Library of Science (PLoS)
• Subjects: Analysis; Carbon dioxide; Carbon Dioxide - analysis; China; Coal; Computation; Construction industry; Developed Countries - economics; Developing countries; Developing Countries - economics; Earth Sciences; Ecology and Environmental Sciences; Economic Development; Economic growth; Emissions; Energy consumption; Engineering and Technology; Environmental impact; Environmental Kuznets curve; Environmental pollution; Environmental Pollution - economics; Error correction; Error correction & detection; European Union; Exports; Gases; Hypotheses; Hypothesis testing; Impact analysis; Imports; Internationality; LDCs; Manufacturing; Manufacturing industries; Method of moments; Physical Sciences; Pollution; Population; Production management; Regression analysis; Renewable resources; Research and Analysis Methods; Social Sciences; United States; United States; China; United States > US; Japan; Germany; Russia; India
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0209532

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 manufacturing industries and commercial service export. Additionally, there occurred no causal link among economic growth, arm import and coal rent.