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Publication Date:
February 2010
ISSN:
1935-1682
DOI:
10.2202/1935-1682.1685

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Simple Pricing Schemes for Pollution Control under Asymmetric Information

Peter W Kennedy1 / Benoit Laplante2 / Dale Whittington3

1University of Victoria, pkennedy@uvic.ca

2World Bank, benoit@laplante.org

3University of North Carolina at Chapel Hill, dale_whittington@unc.edu

Citation Information: The B.E. Journal of Economic Analysis & Policy. Volume 10, Issue 1, Pages –, ISSN (Online) 1935-1682, DOI: 10.2202/1935-1682.1685, February 2010

Publication History:
Published Online:
2010-02-23

Abstract

Most policies for pricing pollution under asymmetric information proposed in the literature to date are rarely – if ever – used in practice. This is likely due to their complexity. We investigate the scope for using somewhat simpler policies that are more closely related to pricing schemes already used by regulators in many jurisdictions. These schemes have a discrete block pricing (DBP) structure whereby a given unit price for pollution is applied up to a specified level of pollution for any given polluter, and a higher unit price is applied to any pollution from that polluter above the specified level. If the same price schedule is applied uniformly to all firms, we call it UDBP. We derive the optimal UDBP schedule for any given number of price blocks. We also derive the optimal limiting case of the UDBP schedule (with an infinite number of price blocks) as a uniform linear increasing marginal price schedule (ULIMP). The optimal ULIMP scheme strikes a balance between the information-related benefits of increasing marginal prices on one hand, and an increase in aggregate abatement cost, due to the non-equalization of marginal abatement costs across firms, on the other. In particular, the optimal schedule is steeper with larger aggregate uncertainty about marginal abatement costs, and flatter with more observable heterogeneity across firms. We then compare our price schemes with those proposed by Weitzman (1978) and Roberts and Spence (1976).

Keywords: pollution control; pollution pricing; asymmetric information

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