Convergence in per capita CO2 emissions: a robust distributional approach
Carlos Ordás Criado () and
Jean-Marie Grether
No 10-70, CEPE Working paper series from CEPE Center for Energy Policy and Economics, ETH Zurich
Abstract:
This paper investigates the convergence hypothesis for per capita CO2 emissions with a panel of 166 world areas covering the period 1960-2002. The analysis is based on the evolution of the spatial distributions over time. Robust measures of dispersion, asymmetry, peakedness and two nonparametric distributional tests - shape equality and multimodality - are used to assess spatial time differences. A robust normal reference bandwidth is also applied to estimate Markov’s transition laws and its subsequent ergodic (long-run) distributions. Our results point toward non-stationary, flattening and rightskewed spatial distributions before the oil price shocks of the 1970s and more stable shapes between 1980 and 2000 at the world level and for many country groupings (similar income, geographic neighbors, institutional partners). In the latter period, group-specific convergence patterns emerge with the clearest single-peaked and compact density shapes being reached in the wealthy, well-integrated and European countries during the last years of the panel. No significant multimodality is formally detected in the world distribution over the whole period. The Markov analysis suggests more divergence and larger per capita emissions for the world before stabilization occurs. A variety of steady state distributions are identified in the country subsets.
Keywords: carbon dioxide emissions; air pollution; convergence; distribution dynamics; stochastic kernels; robustness (search for similar items in EconPapers)
JEL-codes: C14 D30 Q53 Q56 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2010-02
New Economics Papers: this item is included in nep-ene and nep-env
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Citations: View citations in EconPapers (24)
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Journal Article: Convergence in per capita CO2 emissions: A robust distributional approach (2011) 
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