Valuing interacting externalities

Is it optimal, in terms of social welfare, to locate a new high voltage power line near a busy highway? Should a new wind farm best be built near a noisy railroad? Put more generally, is the total joint impact of environmental externalities lower than the sum of the individual externalities when the externalities are concentrated in a single area? Or is there some embedding effect such that adding an extra externality barely influences people’s valuation? The answer to this question is of prime importance to policy makers who have to decide on the optimal location of public utility and transport infrastructure and/or on the necessity of often vast investments to reduce the externalities. Although some authors already attempted to disentangle the welfare effects of multiple externalities, the type and size of interactions between different externalities is still poorly understood. In particular we identify 3 main challenges. First, most analyses of the valuation of multiple externalities lack a solid theoretical framework to guide the empirical effort. Second, although anecdotic evidence seems to suggests multiple externalities are not independent, a well-structured empirical approach in which the welfare impact of interacting externalities is estimated, is still missing. In particular an approach which aims to validate the predictions of a more formal model, would add significantly to the existing literature. Third and finally, it is currently not clear how the results from the above empirical exercise can be transferred to other locations. Adding more complex interaction effects poses additional challenges for benefit transfer exercises, as the relative magnitude of each of the overlapping externalities might steer the level of the interaction effect. The ultimate goal of this project is therefore to disentangle complex interaction effects of environmental externalities both theoretically as empirically, thus extending the existing literature towards integrating in a consistent way multiple externalities in environmental economics’ hedonic pricing valuation methodology. As a first step we aim to build to a consistent theoretical framework. The objective of this theoretical exercise is to derive a consistent inverse demand function for housing. This inverse demand function, which relates the value of private property to its characteristics, serves as the theoretical basis for consistent welfare evaluation of changes in the level of exposure to the externalities. In a second step we will build on an extensive dataset containing house sales transactions, environmental characteristics and socio-economic neighborhood characteristics for Flanders (Belgium) to estimate the welfare impact of overlapping and interacting environmental externalities with hedonic regression techniques. In the third and final step we will set up an ‘experiment’ to calculate the difference between the value of an externality using standard benefit transfer methodology with the value of an externality derived from hedonic regressions taking into account interacting externalities. The difference between both estimates can be interpreted as an estimate of the bias from using conventional benefit transfer which does not take into account multiple externalities, compared to methodologies that do account for the interaction effects.

Keywords:externalities, interacting, Valuing

Disciplines:Applied economics, Economic history, Macroeconomics and monetary economics, Microeconomics, Tourism