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Prof. Massimo Filippini, Dr. Silvia Banfi, Loa Buchli, NN
2 years (start in 2004 - 2006)
Open
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.
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