Developing a methodology for assessing the economic impacts of large scale environmental regulations

Peter Berck and Peter Hess

Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley

Abstract: This paper explains the development and implementation of a methodology for assessing the economic impacts of large-scale environmental regulations. The development process began with a literature review surveying channels through which environmental regulations might influence economic performance. Avenues deemed suitable were incorporated into a computable general equilibrium (CGE) model of the California economy. This model is based on the California Department of Finance's Dynamic Revenue Analysis Model (DRAM). Modifications to DRAM for the current project include a revised sectoring scheme that features industries of particular regulatory interest, revamped data matrices that accommodate this new sectoring scheme, a new air pollution module, programming options designed to facilitate the simulation of environmental regulations, and enhanced output reporting that highlights income, production, employment, and price responses to proposed regulatory changes. The new model, E-DRAM, is implemented, policy experiments are run, and their results are interpreted. A brief time-series exploration of state-product, pollution prevention costs, and pollution follows. In it, vector auto regression (VAR) techniques are used to investigate the relationship between Gross State Product (GSP), pollution prevention expenditures, and levels of pollution. Findings suggests that the cost of holding pollution levels constant increases with GSP and that the cost of pollution control given asp rise as ambient pollution levels fall. This line inquiry will be more fruitful as more data becomes available.

Keywords: cge models; environmental aspects; environmental policy; methodology; regulations (search for similar items in EconPapers)
Date: 2000-02-01
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