Zoning as a control of pollution in a spatial environment
AbstractSpace matters not only because of the transportation costs it imposes on the economy but also because it can serve as an effective instrument to control pollution damages. Previous models of pollution either disregard space altogether or presume a predetermined separation between polluters and pollutees, usually into a CBD where the polluting industry is located and a residential ring where the city's laborers reside. All possible location combinations of housing and industry are considered in this study. The results demonstrate that the management of pollution must recognize the trade-off between two cost components: pollution costs and transportation costs. This trade-off along with the non-convexity inherent in spatial models results in multiple local optima. Negligible commuting costs combined with pollution emissions bearing ill effects at a rate declining with distance leads to an allocation with one industrial zone and one residential zone. As commuting costs increase, the optimal allocation passes through an endogenously determined series of increasing thresholds. Each time a threshold is crossed the number of zones of each type increases until the internal solution is reached after the final threshold has been crossed. In the internal solution, there is no commuting, and housing and industry assume adjacent locations. In such an economy, Pigouvian taxes are generally inefficient. Instead, the efficient tax is a per unit land tax equal to the additional damages contributed by that land unit's pollution.
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Bibliographic InfoPaper provided by University of California at Berkeley, Department of Agricultural and Resource Economics and Policy in its series CUDARE Working Paper Series with number 875.
Length: 56 pages
Date of creation: 1999
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Other versions of this item:
- Hochman, Oded & Rausser, Gordon C., 1999. "Zoning as a control of pollution in a spatial environment," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt0qq9849t, Department of Agricultural & Resource Economics, UC Berkeley.
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