Environmental Objectives, Cost Efficiency, and Multivariate Stochastic Control

Document identifier: oai:dalea.du.se:2407
Access full text here:10.1007/s10666-007-9095-5
Keyword: Social Sciences, Economics and Business, Economics, Samhällsvetenskap, Ekonomi och näringsliv, Nationalekonomi, Environmental Objectives, Cost Efficiency, And Multivariate Stochastic Control
Publication year: 2008
Relevant Sustainable Development Goals (SDGs):
SDG 11 Sustainable cities and communitiesSDG 9 Industry, innovation and infrastructureSDG 6 Clean water and sanitation
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

This paper is concerned with the cost efficiency in achieving the Swedish national air quality objectives under uncertainty. To realize an ecologically sustainable society, the parliament has approved a set of interim and long-term pollution reduction targets. However, there are considerable quantification uncertainties on the effectiveness of the proposed pollution reduction measures. In this paper, we develop a multivariate stochastic control framework to deal with the cost efficiency problem with multiple pollutants. Based on the cost and technological data collected by several national authorities, we explore the implications of alternative probabilistic constraints. It is found that a composite probabilistic constraint induces considerably lower abatement cost than separable probabilistic restrictions. The trend is reinforced by the presence of positive correlations between reductions in the multiple pollutants.

Authors

Chuan-Zhong Li

Högskolan Dalarna; Nationalekonomi
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Erika Budh

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