Water Quality Trading When Nonpoint Pollution Loads are Stochastic

FCN Working Paper No. 10/2009

43 Pages Posted: 4 Jun 2010

See all articles by Gaurav S. Ghosh

Gaurav S. Ghosh

Pennsylvania State University - College of Agricultural Sciences - Department of Agricultural Economics and Rural Sociology

James S. Shortle

Pennsylvania State University - College of Agricultural Sciences - Department of Agricultural Economics and Rural Sociology

Date Written: November 1, 2009

Abstract

We compare two tradable permit markets in their ability to meet a stated environmental target at least cost when some polluters have stochastic and non-measurable emissions. The environmental target is of the safety-first type, which requires probabilistic emissions control. One market is built around the trading ratio, which defines the substitution rate between stochastic and deterministic pollution, and is modeled on existing markets for water quality trading. The other market is built around a new definition of the pollution credit as a multi-attribute good, where the attributes supply information to the market on the environmental risks associated with stochastic pollution loads. The market with multi-attribute credits is found to out-perform the trading ratio market in its ability to satisfy the safety-first environmental target at least cost. This result comes about because polluters are able to directly price risk in this market. In the trading ratio market risk is not a factor in polluters' trading decisions and is only controlled, through the trading ratio, under highly restrictive conditions.

Keywords: Water Quality Trading, Stochastic Pollution, Market

Suggested Citation

Ghosh, Gaurav S. and Shortle, James S., Water Quality Trading When Nonpoint Pollution Loads are Stochastic (November 1, 2009). FCN Working Paper No. 10/2009, Available at SSRN: https://ssrn.com/abstract=1620502 or http://dx.doi.org/10.2139/ssrn.1620502

Gaurav S. Ghosh (Contact Author)

Pennsylvania State University - College of Agricultural Sciences - Department of Agricultural Economics and Rural Sociology ( email )

University Park, PA 16802-3306
United States

James S. Shortle

Pennsylvania State University - College of Agricultural Sciences - Department of Agricultural Economics and Rural Sociology ( email )

University Park, PA 16802-3306
United States

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