A New Index of Environmental Quality
An optimal weighting scheme is proposed to construct a new index of environmental quality for different countries using an approach that relies on consistent tests for stochastic dominance efficiency. The test statistics and the estimators are computed using mixed integer programming methods. The variables that are considered include countries' greenhouse emissions, water pollution and forest benefits, as from the dataset of the World Bank. First, the stochastic efficient weighting for each set of variables is calculated to build three sub-indices (for greenhouse emissions, water pollution and land without forests) and then an overall risk index of environmental quality is constructed. One main result is that land without forest contributes the most (with around 70%), greenhouse emissions contribute with around 20% and water pollution contributes less (with around 10%). Finally, countries are ranked according to their index of environmental quality and their rankings are compared with those of the Kyoto Protocol.
|Date of creation:||Jul 2011|
|Date of revision:|
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- Kenneth Arrow & Partha Dasgupta & Karl-Göran Mäler, 2003.
"Evaluating Projects and Assessing Sustainable Development in Imperfect Economies,"
2003.109, Fondazione Eni Enrico Mattei.
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- Charles M. Beach & Russell Davidson, 1983. "Distribution-Free Statistical Inference with Lorenz Curves and Income Shares," Review of Economic Studies, Oxford University Press, vol. 50(4), pages 723-735.
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