Spatial econometric models that attempt to understand people’s utility of their surroundings have the potential to serve as a new data-driven approach to spatial planning. The motivation of these models is that, if we understand people’s utility of their surroundings, we will be able to create a planned environment that is better aligned with people’s preferences. The main approach towards the end of this goal has been to conduct revealed preference studies for externalities in the urban environment, such as access to all types of nature, the exposure to noise and air pollution, access to infrastructure, service diversity and so forth.
The last few years there have been a push to expand the model framework. Several publications provide a theoretical setup that allows for a more accurate description of non-marginal changes in the planned environment. The next couple of years we will devote time and resources to models that are able to describe how companies and households sort across space by combining revealed and stated preference techniques. We use observed behaviour in the market for housing, and information on households and companies, which we combine with range of geospatial data in order to describe how they react to, changes in the provision of spatial public goods.