Carbon emissions in Central and Eastern Europe: environmental Kuznets curve and implications for sustainable development

Abstract

This study examines the impact of various factors such as gross domestic product (GDP) per capita, energy use per capita and trade openness on carbon dioxide (CO 2) emission per capita in the Central and Eastern European Countries. The extended environmental Kuznets curve (EKC) was employed, utilizing the available panel data from 1980 to 2002 for Bulgaria, Hungary, Romania and Turkey. The results confirm the existence of an EKC for the region such that CO 2 emission per capita decreases over time as the per capita GDP increases. Energy use per capita is a significant factor that causes pollution in the region, indicating that the region produces environmentally unclean energy. The trade openness variable implies that globalization has not facilitated the emission level in the region. The results imply that the region needs environmentally cleaner technologies in energy production to achieve sustainable development. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.

Economic Transformation in the Beijing-Tianjin-Hebei Region: Is It Undergoing the Environmental Kuznets Curve?

“…Pollution indicators therefore include discharge volume of industrial wastewater, SO 2 emission volume, and generated volume of industrial solid waste. Based on the indicators issued by the Ministry of Environmental Protection and the experience in the literature [19,28,[40][41][42][43], this study also adopts the related control variables such as the added value of the secondary industry, population size, total import/export trade amount, urbanization rate, patent authorization, coal consumption volume, electricity consumption volume and crude oil consumption volume. With these variables, we can increase the reliability and stability of the outcomes of the regression.…”

A projected turning point in China's CO<SUB align="right">2 emissions: an Environmental Kuznets Curve analysis

“…β 1 is a constant, and β 2 , β 3 , β 4 and β 5 are the elasticity coefficients for GDP/capita, squared GDP/capita, EC/capita and openness ratio, respectively. In a common sense, β 2 should be positive since a higher GDP corresponds to more CO 2 emissions in this case; β 3 would be negative if China's past CO 2 emissions were consistent with the EKC hypothesis; β 4 is expected to be positive because higher energy consumption comes from more economic activities when there have not been significant changes in technology (Ang, 2007;Atici, 2009); and β 5 is expected to be negative in developing countries because they have net exports of energy-intensive products to developed countries (Halicioglu, 2009). …”

“…To determine the CO 2 EKC, a linear ln-quadratic equation is often adopted in terms of CO 2 /capita regarding GDP/capita, EC/capita and trade openness ratio (Ang, 2007;Auffhammer and Carson, 2008;Halicioglu, 2009;Jalil and Mahmud, 2009;Atici, 2009;Sun et al, 2010). This study used the same method with the following logarithm form of the equation:…”

Climate change mitigation in China

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“…The validity of the EKC hypothesis is often tested by a linear natural logarithmic-quadratic model, which describes the long-term relationship between CO 2 emissions and their impact factors (Ang, 2007;Atici, 2009;Auffhammer and Carson, 2008;Halicioglu, 2009;Jalil and Mahmud, 2009). This thesis adopted the same method to test the EKC hypothesis in China, using empirical data for the period 1980-2008.…”