Forest Disturbance Impacts on Residential Property Values

  • Robert J. HuggettJr.
  • Elizabeth A. Murphy
  • Thomas P. Holmes
Part of the Forestry Sciences book series (FOSC, volume 79)

Natural environments and the amenities they offer have fueled much of the population growth in the rural United States (Deller et al. 2001, English et al. 2000). In fact, the fastest growing counties in the United States during the early 1990s were non-metropolitan counties that were destinations for retirees or that offered outdoor recreation opportunities (Johnson and Beale 1994). Migration to these rural and exurban areas from urban and suburban locations, along with growth in the United States population, has resulted in an increased mixing of humans, their artifacts, and natural environments. These expanding interface and intermix areas expose more lives and property not only to desirable natural amenities, but also to natural disturbances and disamenities.

This chapter seeks to provide a basic framework for modeling the effects of forest and other natural disturbances on property markets. The modeling section will begin by introducing the hedonic property model in a simple, accessible format. Several important modeling issues and aspects of forest disturbances that make them special in regard to describing their impact on property markets will be discussed next. These include the tension between risks and amenities embodied in a forest resource, the temporal dynamics of disturbance manifestation, and spatial dependence among observed outcomes present challenges to capturing the effects of disturbance shocks. Two case studies will follow, examining the price responses of residential housing to wildfire and an invasive species, the hemlock woolly adelgid. The chapter will conclude with a discussion of management and policy implications of disturbance shocks to property markets.


Housing Price Housing Market Residential Property Hedonic Price Property Market 
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.


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Copyright information

© Springer Science + Business Media B.V. 2008

Authors and Affiliations

  • Robert J. HuggettJr.
    • 1
  • Elizabeth A. Murphy
    • 2
  • Thomas P. Holmes
    • 1
  1. 1.Southern Research StationUnited States Forest ServiceResearch Triangle Park
  2. 2.Department of Economics and Legal Studies in BusinessOklahoma State UniversityStillwater

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