Endogenous Spatial Externalities: Empirical Evidence and Implications for the Evolution of Exurban Residential Land Use Patterns

  • Elena Irwin
  • Nancy Bockstael
Part of the Advances in Spatial Science book series (ADVSPATIAL)


The notion that “neighbors” may generate spatial externalities is well established in economics. In addition to textbook examples of externalities among firms, a significant body of empirical work in urban and environmental economics has provided evidence of the effects of neighboring, undesirable land uses on residential location decisions and housing values. The goal of this chapter is not to challenge or augment this literature, but rather to use it as a starting point in asking whether spatial externalities may influence actual land use conversion decisions by landowning agents. The basic thesis proposed here is that agents’ consideration of these spatial externalities may influence their land use decisions if the resulting change in a parcel’s relative values in alternative land uses is sufficiently strong. If so, then the presence of such spatial externalities creates an interdependence among neighboring agents’ land use decisions, which implies that land use conversion may be partially driven by a process of endogenous change.


Land Rent Duration Dependence Land Parcel Neighboring Agent Spatial Externality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 7.
    See Irwin and Bockstael (1999) for a fuller discussion of these identification strategies and why they are not applicable in this case.Google Scholar
  2. 11.
    For discussion of these methods see, for example, Lee (1992).Google Scholar
  3. 12.
    Diggle (1984) and Cressie (1993) outline a way to use the quantile-quantile plot to statistically test the null hypothesis that the point pattern is generated by a completely spatially random point process (CSR). To do so, the empirical distribution function generated from the observed point pattern is plotted along with upper and lower envelopes from multiple simulations generated under the CSR assumption. This is akin to establishing a confidenceGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Elena Irwin
    • 1
  • Nancy Bockstael
    • 2
  1. 1.The Ohio State UniversityUSA
  2. 2.University of MarylandUSA

Personalised recommendations