Empirical evidence of sustainable development: Causality relationship between economic growth and environmental degradation in Ecuador and Latin America and The Caribbean

This article is an inductive argumentation and an empirical-analytical paradigm that evaluates the actual relationship between Gross Domestic Product (GDP) per capita and the Carbon Dioxide (CO2) in the case of Ecuador and to compare it with Latin America and the Caribbean within a period of analysis from 1960 to 2011. It was developed an Augmented Dickey-Fuller unit root (ADF), a Granger Causality Test and a Johansen Cointegration test. It was obtained a VAR model with two variables with a number of 14 lags – VAR2(14) which were tested for which were tested for causality by demonstrating a bidirectionality for Latin America and the Caribbean and a unidirectionality of GDP per capita to CO2 for the Ecuador. Keywords: economic growth, sustainable development, environmental economics. References [1]E. Urteaga, «Las teorías económicas del desarrollo sostenible,» Cuadernos de Economía, vol. 32, nº 89, pp.113-162, 2009. [2]G. 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Any Signs of Green Growth? A Spatial Panel Analysis of Regional Air Pollution in South Korea

Focusing on air emissions in South Korean provinces, we investigate whether economic growth has become greener since the implementation of the national green growth strategy in 2009. Given the relevance of regional elements in the economic and environmental policies, the focus lies on spatial aspects. That is, spillovers from nearby provinces are controlled for in a SLX model by means of the Han–Phillips estimator for dynamic panel data. Our results suggest mainly the existence of inverted N-shaped Environmental Kuznets curves for sulfur oxides (SOX) and total suspended particles (TSP). As the curves initially decrease strongly with increasing income, the main cleanup is achieved with the mean income level. However, abatement of the remaining TSP emissions only takes place at higher income levels. While the fixed effects estimations indicate that per capita SOX and TSP emissions have been significantly lower since 2009, the effects vanish once spatial interactions are taken into account and no evidence is found that regional economic growth has become greener. Apart from economic growth, population density and energy consumption are the main drivers of emission changes, with the latter having robust spatial spillovers. The respective spatial interactions decrease with increasing distance and become insignificant after 150 km.

CO2 Emissions are First Aggravated and then Alleviated with Economic Growth in China: A New Multidimensional EKC Analysis

CO2 emissions have become a topical issue worldwide, but few studies have explored the relationship between CO2 emissions and income by establishing direct, indirect and total environmental Kuznets curves (EKCs). Using an annual panel dataset collected over the 1997-2017 period in China, this study first analyzed the spatiotemporal evolutionary process of CO2 emissions and subsequently developed direct, indirect and total EKCs based spatial Durbin model (SDM) and partial derivative approach. These results indicate that, first, CO2 emissions have characteristic positive spatial autocorrelation, with gravity centers that have shifted westward. Second, the direct EKC forms a line, while the total EKC resembles a lying-S shape as well as the total EKC, which indicates that compared to local economic growth, neighboring growth plays a very different role in impacting local CO2 emissions. Furthermore, neighboring economic growth seems to have stronger impacts on local emissions, and the turning point of the total EKC comes much earlier than that of the conventional EKC due to the spillover effects of economic growth. Finally, the growth of the population, as well as the rise of energy intensity, can stimulate CO2 emissions in both local and neighboring regions. Industrialization seems to have a nonsignificant impact on emissions changes due to the offsetting effects of the positive direct and negative indirect impacts of the share of secondary industry. Improvements in local urbanization may lead to an increase in emissions, while neighboring improvements may have stronger restricting effects; thus, urbanization improvement is beneficial to emissions reduction. This study provides more scientific information from both local and neighboring perspectives, which may differ from conventional results but still be beneficial for emissions reduction policy makers to introduce corresponding measures.

Estimating different order polynomial logarithmic environmental Kuznets curves

This paper contributes to the environmental literature by (i) demonstrating that the estimated coefficients and the statistical significance of the non-leading terms in quadratic, cubic, and quartic logarithmic environmental Kuznets curve (EKC) specifications are arbitrary and should therefore not be used to choose the preferred specification and (ii) detailing a proposed general-to-specific type methodology for choosing the appropriate specifications when attempting to estimate higher-order polynomials such as cubic and quartic logarithmic EKC relationships. Testing for the existence and shape of the well-known EKC phenomenon is a hot topic in the environmental economics literature. The conventional approach widely employs quadratic and cubic specifications and more recently also the quartic specification, where the variables are in logarithmic form. However, it is important that researchers understand whether the estimated EKC coefficients, turning points, and elasticities are statistically acceptable, economically interpretable, and comparable. In addition, it is vital that researchers have a clear structured non-arbitrary methodology for determining the preferred specification and hence shape of the estimated EKC. We therefore show mathematically and empirically the arbitrary nature of estimated non-leading coefficients in quadratic, cubic, and quartic logarithmic EKC specifications, being dependent upon the units of measurement chosen for the independent variables (e.g. dependent upon a rescaling of the variables such as moving from $m to $bn). Consequently, the practice followed in many previously papers, whereby the estimates of the non-leading terms are used in the decision to choose the preferred specification of an estimated EKC relationship, is incorrect and should not be followed since it potentially could lead to misleading conclusions. Instead, it should be based upon the sign and statistical significance of the estimated coefficients of the leading terms, the location of turning point(s), and the sign and statistical significance of the estimated elasticities. Furthermore, we suggest that researchers should follow a proposed general-to-specific type methodology for choosing the appropriate order of polynomials when attempting to estimate higher-order polynomial logarithmic EKCs.

Monitoring Cointegrating Polynomial Regressions: Theory and Application to the Environmental Kuznets Curves for Carbon and Sulfur Dioxide Emissions

This paper develops residual-based monitoring procedures for cointegrating polynomial regressions (CPRs), i.e., regression models including deterministic variables and integrated processes, as well as integer powers, of integrated processes as regressors. The regressors are allowed to be endogenous, and the stationary errors are allowed to be serially correlated. We consider five variants of monitoring statistics and develop the results for three modified least squares estimators for the parameters of the CPRs. The simulations show that using the combination of self-normalization and a moving window leads to the best performance. We use the developed monitoring statistics to assess the structural stability of environmental Kuznets curves (EKCs) for both CO2 and SO2 emissions for twelve industrialized countries since the first oil price shock.