Valuing Noise Level Reductions in a Residential Location Context

The noise levels measured in metropolitan streets are on many occasions over the norms but the consequences of this as a health hazard are only starting to be questioned; this is obviously worse in the large cities of the second and third worlds. A stated preference (SP) experiment was designed to estimate the willingness-to-pay (WTP) for reducing the noise level in a group based residential location context. Important issues were the proper definition of the context and the variable metric for the environmental attribute. The experiment considered variations of the attributes travel time to work, monthly house rent, position of the dwelling with respect to the sun and subjective noise level inside it; objective levels were also measured after the experiment. With this data we estimated Multinomial Logit and Mixed Logit (ML) models based on a consistent microeconomic framework, with linear and non-linear utility functions and allowing for various stratifications of the data. The more flexible ML models also allow to treat the repeated observations problem common to SP data and, as expected, gave a better fit to the data. Based on these models we estimated subjective values of time, that were consistent with previous values obtained in the country, and also sensible values for the WTP for reductions in the subjective noise level at a given location.