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Do countries influence neighbouring pollution? A spatial analysis of the EKC for CO2 emissions

Abstract By considering spatial relationships, this study aims to analyse to what extent per capita CO2 emissions are determined by renewable energy consumption, the share of the services sector in GDP, energy intensity and real per capita income. A panel data set composed of 173 countries over the 1990–2014 period is used to estimate an environmental Kuznets curve (EKC) augmented by neighbouring per capita income and energy intensity. Both standard and spatial forms are estimated for seven different sets of countries to assess the robustness of the results. Finally, several forecasts are performed to verify global sustainability and to provide some policy suggestions for the period 2015–2100. The empirical results indicate that (i) most areas support the standard EKC, (ii) there seems to be an inverted U-shaped relationship between neighbouring per capita income and national per capita emissions in Europe, Asia and the World as a whole, (iii) neighbouring energy intensity increases national per capita emissions, and (iv) forecasts show that economic growth will accelerate climate change. However, a steady annual growth in renewable energy consumption and a steady decrease in energy intensity, both close to 2.5%, may guarantee environmental sustainability prior to 2100.
- University of Oviedo Spain
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).136 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
