Abstract
This study investigates the robustness and validity of the environmental Kuznets curve hypothesis for Brazil, Chile, China, Colombia, Egypt, Greece, India, Indonesia, South Korea, Malaysia, Mexico, Peru, the Philippines, Thailand, and Turkey. The hypothesis postulates the connection between pollution and income follows an inverted U-shaped path, which means that environmental degeneration rises with income during the beginning phases of economic growth; however, it declines after reaching a specified peak. For the empirical part of our study, we employed summability procedures designed to analyze the nonlinear long-term relationship for persistent processes. The yearly data consist of carbon dioxide emission and gross domestic product, both of which are expressed in per capita terms and cover the period from 1960 to 2014. The results illustrate the Environmental Kuznets Curve hypothesis holds for China, Colombia, India, South Korea, and the Philippines, which means that environmental problems wither away with economic growth and are resolved automatically without any need for policy action in these countries.
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Notes
The Kuznets Curve comes from the original work of Kuznets (1955) who estimated the dynamic relationship between income inequality and GNP per capita. According to Kuznets (1955), income distribution inequality increases with the rise in per capita income until a particular point, and after that point, if per capita income continues to rise, then income inequality decreases significantly.
The sample countries come from the MSCI Emerging Markets Index generated by Morgan Stanley Capital International to measure equity market performance of emerging markets. For details, see https://www.msci.com/emerging-markets.
Assuming for illustration \(g(x_{t} ) = \theta_{1} x_{t} + \theta_{2} x_{t}^{2}\), let \(x_{t} = x_{t - 1} + x_{0} + \varepsilon_{t}\) and \(\varepsilon_{t} \sim i.i.d.(0,\sigma_{\varepsilon }^{2} )\), then it is obtained \(\text{var} (x_{t} - x_{t - 1} ) = \sigma_{\varepsilon }^{2} \Rightarrow x_{t} \sim I(1)\). In other words, Engle and Granger (1987) characterization of a stationary process holds for \(\Delta x_{t}\) (finite variance). The same property can be investigated for \(\Delta x_{t}^{2}\): \(\text{var} (x_{t}^{2} - x_{t - 1}^{2} ) = {\rm E}(\varepsilon_{t}^{4} ) + 4(t - 1)\sigma_{\varepsilon }^{4} - \sigma_{\varepsilon }^{4} \Rightarrow x_{t}^{2} \sim I(?)\). It can be seen that the finite variance characteristic is clearly violated given that the variance is a function of time. Because this problem cannot be solved by further differencing, it is not possible to determine the order of integration of \(x_{t}^{2}\). The difficulty arises from the requirement of the Engle and Granger (1987) characterization to investigate the differences of a process, with the intrinsic linearity of the difference operator creating obvious problems for nonlinear processes. For technical details, refer to Eberhardt and Presbitero (2015).
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We wish to thank the anonymous referee for many helpful comments. Special thanks go to the Editor for allowing us the opportunity to revise our work. Any remaining errors are solely ours.
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Bozoklu, S., Demir, A.O. & Ataer, S. Reassessing the environmental Kuznets curve: a summability approach for emerging market economies. Eurasian Econ Rev 10, 513–531 (2020). https://doi.org/10.1007/s40822-019-00127-z
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DOI: https://doi.org/10.1007/s40822-019-00127-z
Keywords
- Balancedness
- CO2 emissions
- Co-summability
- Emerging markets
- Environmental Kuznets curve
- Nonlinear co-integration