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Given the cumulative consequences of climate change, global concentration of greenhouse gases (GHGs) must be reduced; being inequality in per-capita emissions levels a problem to achieve a commitment by all countries. Thus, the evolution of carbon dioxide (CO2) emissions inequality has received special attention because CO2 is the most abundant GHG in the atmosphere. However, it is necessary to consider other gases to provide a real illustration of our starting point to achieve a multilateral agreement. In this paper, we study the evolution of global inequality in GHGs emissions during the period 1990-2011, considering the four main gases: CO2, methane (CH4), nitrous oxide (N2O) and fluorinated gases (F-gases). The data used in this analysis is taken from the World Resources Institute [1] and the groups of countries are constructed according to the quantity of emissions that each country released into the atmosphere in the first year of study. For this purpose we use the multidimensional generalized entropy measures proposed by Maasoumi [2] that can be decomposable into the between-and within-group inequality components. The biggest fall in inequality is observed when we attach more weight to the emissions transfers between the most polluting countries and assume a low substitution degree among pollutants. Finally, some economic policy implications are commented.

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In this paper, the class of Lamé Lorenz curves is studied. This family has the advantage of modeling inequality with a single parameter. The family has a double motivation: it can be obtain from an economic model and from simple transformations of classical Lorenz curves. The underlying cumulative distribution functions have a simple closed form, and correspond to the Singh-Maddala and Dagum distributions, which are well known in the economic literature. The Lorenz order is studied and several inequality and polarization measures are obtained, including Gini, Donaldson-Weymark-Kakwani, Pietra and Wolfson indices. Some extensions of the Lamé family are obtained. Fitting and estimation methods under two different data configuration are proposed. Empirical applications with real data are given. Finally, some relationships with other curves are included.