A meta‐analysis of the effect of environmental contamination on non‐residential real estate values

Published date12 July 2011
DOIhttps://doi.org/10.1108/14635781111150349
Pages460-478
Date12 July 2011
AuthorJesse Saginor,Robert Simons,Ron Throupe
Subject MatterProperty management & built environment
A meta-analysis of the effect of
environmental contamination on
non-residential real estate values
Jesse Saginor
College of Architecture, Texas A&M University, College Station, Texas, USA
Robert Simons
Cleveland State University, Cleveland, Ohio, USA, and
Ron Throupe
Burns School of Real Estate & Construction Management, Daniels
College of Business, University of Denver, Denver, Colorado, USA
Abstract
Purpose – This paper seeks to reduce the lack of quantitative research by addressing diminution in
value to non-residential property resulting from environmental contamination.
Design/methodology/approach – This meta-analysis extracts data from approximately a dozen
peer-reviewed articles and 100 case studies from real estate appraisers in the USA. A dataset
containing 106 contaminated non-residential observations is examined using Regression (OLS).
Forward (stepwise) and backward selection was performed. The dependent variable included
percentage loss and dollar amount. The independent variables were contamination type, US region,
land use type, distance from the source (mostly contaminated subjects), passage of time, year, urban or
rural, market conditions, litigation, and indemnification.
Findings – The model adjusted Rsquares range from 37 percent to 66 percent. Approximately a
third of cases had no loss. This research used petroleum case studies as the reference category for
comparison with other types of contamination. The following variables were statistically significant in
all four models: Creosote/PCB and Other contamination. The following were significant in two models:
Other land use, 30-year mortgage rate, Rural location, TPH, Multiple contamination, TCE,
Under-remediation, and Mineral extraction region. Finally, the following variables were significant in
one model at least at a 90 percent level of confidence: Heavy metals, Industrial Midwest region, and
pre-1995 sale.
Practical implications Properties in the remediation phase show less of a loss in value. Selective
case studies within the same period of the clean-up cycle make the best comparables. The US regional
location was less important.
Originality/value – This is the first empirical research using a meta-analysis to study damage
effects for non-residential property affected by contamination.
Keywords Meta-analysis,Commercialproperty, Detrimentalconditions, Environmentalcontamination,
Damages, Assetvaluation
Paper type Research paper
I. Introduction
This research addresses the overall effects of the influence of environmental
contamination on commercial and industrial property values. Environmental sources
that influence property values include superfund sites, leaking underground storage
tanks, landfills, air and water pollution, pipeline ruptures, nuclear power plants,
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1463-578X.htm
JPIF
29,4/5
460
Received December 2010
Accepted March 2011
Journal of Property Investment &
Finance
Vol. 29 No. 4/5, 2011
pp. 460-478
qEmerald Group Publishing Limited
1463-578X
DOI 10.1108/14635781111150349
overhead transmission lines, roads, and several other urban nuisance uses. The study
begins with summarization of a literature review of approximately a dozen
peer-reviewed journal articles, which produced a total of 20 observations (see
Appendix). An additional 108 cases were provided by an extensive appraisal
transaction database from practicing appraisers. Research findings are combined and
distilled into a data set of 106 observations that contains information about each
study’s dollar property value loss (the dependent variable), with the independent
variables being type of contamination, information, urban or rural environment, local
and national market conditions, information about the contaminative event,
remediation, and several other variables. Regression analysis is used to determine
the effect of contamination and other independent variables on sales price, expressed in
dollars or percent.
Contamination affects property values through its impact on the real estate bundle
of rights. These rights include the rights to possess, enjoy, control, and dispose of real
property. A loss can occur in ways other than the discounted sale, such as inability to
access capital, finance or refinance, delay of sale, etc. See Simons et al. (1999), or
Jackson (2001) for a review of how a loss can occur. The sales prices studied in this
research are the net proceeds in the disposal part of the real estate bundle of rights
(realized capital loss) not considering the timing of sale.
Meta-analysis has traditionally been used for clinical studies and has not been
widely applied to real estate. Unlike published work on residential property that relies
upon regression analysis, most commercial and industrial studies employ case study
methodologies and the site being studied is typically also the source of contamination.
Other results are limited to the specific models and discussed in depth in their
respective section. These results include varying levels of significance depending on
the type of contamination and geographic region. This paper aims to extrapolate
similarities across the available data.
II. Existing literature
There has been one meta-analysis of similar scope on the effect of contamination on
residential property values, one meta-analysis strictly for air pollution, and two
comprehensive literature reviews on the effect of contamination on commercial and
industrial real estate values. These analyses and reviews are described below. In
addition, Simons (2005) conducted a literature review of over 100 peer-reviewed articles
on proximity influence (both positive and negative) for residential and commercial
property, which is a partial source of the data set for this study. Despite several
excellent international studies, the data set consists of the literature pertaining to the
USA due to issues with finding comparable economic indicators for non-US studies.
Simons and Saginor (2006) conducted a meta-analysis of the effects of
environmental contamination and positive amenities on proximate residential real
estate property values in the USA. Contamination sources include leaking
underground storage tanks, superfund sites, landfills, water and air pollution, power
lines, pipeline ruptures, nuclear power plants, animal feedlots, and other urban
nuisances. The study summarized a literature review of 75 peer-reviewed journal
articles and selected case studies. A data set of 290 observations that contain
information about each study’s loss (the dependent variable), with the independent
variables being distance from the source, type of contamination, urban or rural
Effect of
environmental
contamination
461

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