Valuation of Externalities in Urban Areas with Special Focus on Electromagnetic Pollution, Air Pollution and Noise

Investigators
Prof. Massimo Filippini, Dr. Silvia Banfi, Loa Buchli, NN

Time Frame
2 years (start in 2004 - 2006)

Funding
Open

Abstract
Electromagnetic pollution (i.e. non-ionizing radiation), noise and air pollution are typical local negative externalities in urban areas: they are produced as side-effects of human and economic activity (road transport, telecommunication) and affect individual’s well-being negatively without compensation. The main goal of the proposed research project consists of the estimation of households’ willingness to pay for the improvement of urban environmental quality with a particular focus on these three forms of pollution.
The motivation for this project can be found largely in the growing concern of population about electromagnetic pollution caused mostly by mobile telecom antennas, TV and radio transmitters and high voltage power lines.
However, very recent studies on the costs caused by these pollution forms in Switzerland are missing. Therefore, we believe that it is important to control for the up-to-dateness of the costs estimations of noise and air pollution on human beings currently used in Switzerland.
These externalities have to be tackled by the State, either directly, by taking for example pollution abatement measures, or indirectly, by introducing market mechanisms or setting a legal framework aimed at providing consumers and producers incentives to reduce emissions. Either option is associated with costs to Society. Policy maker’s decisions should therefore rely on Cost-Benefit Analyses in order to ascertain that the benefits of a certain policy option outweigh its costs.
For this reason, the project aims at the important task of providing policy makers with new or up-dated information on benefits associated with environmental quality improvements in the fields of electromagnetic pollution, noise and air pollution.
This research project suggests estimating the value of a quality improvement applying two valuation methods: the Hedonic Price Method and a Discrete Choice Model using revealed and stated data jointly in the estimation process. It will be interesting to compare the results obtained through the two methods in order to check their validity.