Measuring Air and Water Pollution Over Time Using Stochastic Dominance

Abstract

We employ a stochastic dominance (SD) approach to analyze the components that contribute to environmental degradation over time. The variables that are considered include countries' greenhouse gas (GHG) emissions and water pollution as from the data set of the World Bank. Our approach is based on pair-wise SD tests. First, we study the dynamic progress of each separate variable over time, from 1990 to 2005, within 5-year horizons. Then, pairwise SD tests are used to study the major industry contributors to the overall GHG emissions and water pollution at any given time, to uncover the industry which contributes the most to total emissions and water pollution. We find that CO₂ emissions not only contribute the most to the GHG emissions over time, but also increased within 15 year in the first-order SD sense. On the other hand, water pollution increased in a second-order SD sense. Pair-wise industry comparisons suggest that the major industry contributors to the CO₂ emissions have always been the electricity and heat production sectors, while the transport sector has been the second contributor between 1990 and 2005. Finally, the food industry gradually became the major contributing industry for water pollution over time.