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Much of the existing research analyses on emissions and climate policy are dominantly based on emissions data provided by production-based accounting (PBA) system. However, PBA provides an incomplete picture of driving forces behind these emission changes and impact of global trade on emissions, simply by neglecting the environmental impacts of consumption. To remedy this problem, it is proposed to calculate national emissions based on consumption-based accounting (CBA) system. In this article we question the relevance of PBA"s dominance. To this end, we, firstly, try to assess and compare PBA with CBA adopted in greenhouse gas emissions accounting systems in climate change debates on several issues and to discuss the policy implications of the choice of approach. Secondly, we investigate the convergence patterns in production-based and consumption-based emissions in 35 Annex-B countries for the period between 1990 and 2015. This study, for the first time, puts all these arguments together and discusses possible outcomes of convergence analysis by employing both the production and consumption based per capita emissions data. The empirical results found some important conclusions which challenge most of the existing convergence studies.

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PurposeThe purpose of this study is to examine whether the elasticity of substitution (ES) varies between developed and developing countries.Design/methodology/approachThe author derives the growth regressions from the Solow model under the constant elasticity of substitution production function by using the first-order Taylor series expansion and estimate them for each country group classified based on time-varying behavior of income per worker using the data-driven algorithm.FindingsThe ES is not unitary and varies among country groups. Developed countries generally have a higher ES than developing countries.Originality/valueFor the first time, the author uses the first-order Taylor series expansion to linearize the steady-state value of income per worker, as the author considers this approach to be relatively more straight-forward and tractable. Furthermore, the author estimates the equations using both cross-section and panel data techniques and employs the data-driven algorithm proposed by Phillips and Sul (2007) to classify countries.