Dani Broitman (p), Danny Czamanski

Proximity to nature is highly valued by urbanites. They demonstrate higher willingness to pay for housing at locations near open and green spaces. But, nature in cities can generate negative externalities as well. In this paper we illustrate the complex relationship between of cities and nature and suggest that their balance is time and location specific. The paper presents estimates of positive and negative externalities based on data about urban open spaces, observed and perceived presence of wild animals and residential property values in the city of Haifa, Israel. These data were analyzed to uncover spatial regularities and basic statistical relationships.The results reveal the presence of dominant positive externalities related to proximity to open and green areas. However, in certain areas and under certain circumstances, the nuisances generated by the presence of wild animals in close proximity to housing is correlated with lower property prices.

Toke Emil Panduro (p), Cathrine Ulla Jensen, Bo Jellesmark Thorsen, Thomas Lundhede

We present the results of a large scale analysis on how trading prices of single family detached houses and summer cottages in Denmark are affected by proximity to on-shore windmills. We furthermore present an analysis of how off-shore windmills affect the same types of prices using a suitable case of off-shore windmills visible from the shore of a Danish island. For on-shore mills, we find that they affect property prices in their surroundings negatively, and we find that the more mills and the closer, the larger the negative impact. The mean estimates indicate that a price of a family house will be reduced with 3-6 % if two wind turbines are placed 1,000 m from the house, the range depending on the region. If eight windmills are placed around 1,000 m from the house, the price is reduced some 6-10 %, again depending on the region. For the off-shore mills, which are x km out of the coast, using a difference in difference matching design, we are unable to identify a significant effect of view of the windmills from either house or nearby beach, when placed at this distance from the coast. Our results and modeling approaches are useful for policy and planning for windmill placements, and we illustrate this by providing maps showing how the marginal cost of another windmill various across the landscape according to the number of existing house and the value of property in the proximity.