The implicit value of tree cover in the U.S.: A meta-analysis of hedonic property value studies

Published Date
August 2016, Vol.128:68–76, doi:10.1016/j.ecolecon.2016.04.016
Analysis

Author 

• Shyamani D. Siriwardena ^a,,1,
• Kevin J. Boyle ^b,1,
• Thomas P. Holmes ^c,1,
• P. Eric Wiseman ^d,1,

• aDepartment of Forest Resources and Environmental Conservation, 313 Cheatham Hall (0324), Virginia Tech, Blacksburg, VA 24061, USA
• bVirginia Tech Program in Real Estate, 420 Bishop-Favrao Hall (0715), Virginia Tech, Blacksburg, USA
• cUSDA Forest Service, Southern Research Station, Research Triangle Park, NC, USA
• dDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, USA

Received 18 March 2015. Revised 1 March 2016. Accepted 3 April 2016. Available online 4 May 2016. 

Abstract

Trees in residential neighborhoods and communities provide benefits for homeowners that are capitalized into residential property values. In this paper, we collected data from hedonic property value studies and merged these data with ancillary spatial data describing forest and socio-economic characteristics surrounding each study area to conduct a meta-analysis of the impact of tree canopy cover on the value of residential properties. The meta-analysis suggests that property-level tree cover of about 30% and county-level tree cover of about 38% maximize the implicit price of tree cover in property values. Currently, tree cover in the original study areas was about 14%, on average, around or near study properties. The empirical results, therefore suggest under investment of tree cover on private property from the perspective of individual property owners and from a societal perspective. The findings also have implications for community forest programs regarding planting trees and protection of mature trees to address potential changes in tree abundance, species diversity and stand age due to development and climate change.

Keywords

Hedonic valuation

Tree canopy cover

Community forestry

Forest matrix

Climate change

---

Fig. 1.

 Table 1

Table 1.

 Table 2

Table 2.

 Table 3

Table 3.

 Table 4

Table 4.

 Table 5

Table 5.

 Table 6

Table 6.

 Table A1

Table A1.

• ☆
  This research was supported by the Southern Research Station of the U.S. Forest Service(12-JV-11330143-106) and Virginia Agricultural Experimental Station.

• ⁎ 
  Corresponding author.

For  further details log on website :
http://www.sciencedirect.com/science/article/pii/S0921800916304293