**[Stigma: The Psychology and Economics of Superfund]{.smallcaps}**[^1]

Kent Messer, William Schulze, Katherine Hackett,

Cornell University

Trudy Cameron,

University of Oregon

Gary McClelland

University of Colorado

*May 7, 2004*

**Introduction**

This paper summarizes a larger study that evaluates the benefits (as
captured in residential property values) of hazardous waste cleanup
conducted under the Comprehensive Environmental Response, Compensation,
and Liability Act (CERCLA), commonly known as Superfund. When this
legislation was passed in 1983, the public imagined that the
Environmental Protection Agency (EPA) would begin immediate clean up of
sites deemed hazardous to human and environmental health, using tax
money to be collected from the petroleum and chemical industries.
However, CERCLA's provision of joint and several liability requires that
all previous and current owners could be responsible for clean up cost,
regardless of the amount of hazardous waste deposited at the site. Thus
the legal complexity of CERCLA in establishing fair and just
responsibility substantially delayed clean up at many listed Superfund
sites.

This research documents the consequences of that delay on property
values in communities neighboring Superfund sites. To understand those
consequences, one must understand the psychology of risk perceptions and
stigma, the economics of property values that capture those perceptions,
as well as the long-term consequences of those perceptions. To explore
the possibility that stigma can help explain public reaction to
potentially hazardous sites, six Superfund sites in four areas are
examined: the Operating Industries, Inc. landfill site near the
communities of Monterey Park and Montebello, California; the radium
pollution in Montclair, Glen Ridge, and West Orange Townships in
northern New Jersey; the Industriplex and water Wells G & H Superfund
sites in Woburn, Massachusetts; and the Eagle Mine Superfund site
outside of Vail, Colorado. The research specifically examines the sale
prices of nearly 35,000 homes for up to a thirty-year period. Each case
study also includes a brief description of the site and the sample that
we obtained for the hedonic property value studies, which look at the
change in the sale price of homes over time. It should be noted that
many Superfund sites have shown no or small property value losses in
surrounding communities. The sites selected for this study all have
shown large losses at some point in time. Further, no previous property
value study has examined sites with large losses over the length of time
used here. The results we obtain are both surprising and inconsistent
with most prior work on property values (e.g., Hamilton and Viscusi,
1999). The case studies also document how trends in the
socio-demographic composition of the communities near the sites differed
from the trends in communities farther from the site.

In summary, the principal result is it that, when cleanup is delayed for
ten, fifteen, and even up to twenty years, the economic benefits of
cleanup are essentially lost because sites are stigmatized and the homes
in the surrounding communities are shunned. The paper is organized as
follows: the second section briefly describes the five Superfund sites
in three case studies, the third section discusses why residents of
communities neighboring Superfund sites may not completely believe
expert/scientific opinion regarding the health risks associated with the
sites, the fourth section outlines what is known about the psychology of
risk perceptions and stigma, while the fifth section integrates the
psychology of stigma with economic hedonic property value approach
which, as noted by Gregory and Cantor (1991), is a non trivial task. The
sixth section presents our conclusions.

**Case Studies**

[Operating Industries, Inc. Landfill]{.underline}: The OII Landfill
covers 190 acres and is located 10 miles (16 kilometers) east of Los
Angeles between the communities of Monterey Park and Montebello,
California. The Pomona Freeway (Route 60) divides the site into two
parcels, one 45-acre area lies north of the freeway and the other
145-acre parcel lies south of the freeway. The landfill is in the city
of Monterey and the city of Montebello borders the southern end and
portions of the northern section of the landfill. Throughout its
operating life, from 1948 to 1984, the landfill received 30 million
cubic yards of residential and commercial refuse, industrial wastes,
liquid wastes, and a variety of hazardous wastes. The Environmental
Protection Agency (EPA) determined that approximately 4,000 different
parties sent waste to the landfill at one point or another. In October
1984, the landfill was closed and proposed for listing on the National
Priority List (NPL). In June 1986, the landfill was officially listed as
a NPL Superfund site, and experts estimated that the cleanup could take
as much as 45 years and more than \$600 million to complete. As of 2002,
the EPA had reached settlement with more than 1,250 parties to pay for
the cleanup work, with the total settlements reaching almost \$1 billion
(Table 1).

In the early 1980's, Residents near the landfill formed Homeowners to
Eliminate Landfill Problems (HELP) to address increasing odor and
potential health problems at the site, as well as specific issues such
as leachate seepage, methane gas buildup, declining property values, and
land use after closure of the site. This organization, comprised of 460
dues-paying families, was an essential force in the eventual closing of
the landfill. Community council meetings became volatile as residents
protested the "assaulting stench" of the air. "We could never open the
\[house\] windows," said Montebello resident Phyllis Lee. As another
resident stated, "Some nights I wake up coughing at two, three, four
o'clock in the morning. The methane gas is so strong that I have a hard
time breathing."

According to Katherine Shrine, assistant regional counsel for the EPA
Region 9, "This site is basically a 300-foot-tall, 190-acre mountain of
every kind of disposable item in the world." Residents say the landfill
is so large that it interferes with television reception. Approximately
53,000 people live within three miles (4.8 kilometers) of the sites,
23,000 within one mile (1.6 kilometers) of the site, and 2,150 within
1000 feet (0.3 kilometers) of the landfill. Three schools are located
within 1 mile (1.6 kilometers) of the landfill. The area consists of
heavy residential development and mostly middle income and multi-racial
neighborhoods.

For the Operating Industries, Inc. (OII) Landfill case study, we were
able to obtain good data on selling prices, housing characteristics, and
Census information for nearly three decades (1970 to 1999). The length
of this sample enables and examination of how proximity to the landfill
affected housing prices well *before* the problems began to arise in the
late 1970's. A relatively large footprint was selected this study. The
broader neighborhood surrounding the OII Landfill site includes 9,279
dwellings between 60 meters and about 8.5 kilometers (5.3 miles) from
the boundary of the site.

[Montclair, West Orange, and Glen Ridge, New Jersey]{.underline}:
Montclair, Glen Ridge, and East and West Orange Townships are located
about eight miles (12.9 kilometers) from Newark Airport in northern New
Jersey. These towns are densely populated, and are located in one of the
most densely populated regions of the United States. The Montclair/West
Orange Radium Superfund site consists of 366 residential properties on
120 acres in Montclair and West Orange. The Glen Ridge Radium Superfund
site is comprised of 306 properties on 90 acres of residential land in
Glen Ridge and East Orange. The soil at both sites is contaminated with
radium, a naturally occurring element that can result in high levels of
radon gas and gamma radiation in nearby homes. Several plants occupied
the area, the largest of which was the U.S. Radium Corporation (formerly
the Radium Luminous Materials Corporation) which operated between 1915
and 1926. Because of its luminescent properties, radium was added to the
paint that was used for numbers on watch dials and instruments, which
became especially popular during World War I. The Center for Disease
Control (CDC) and the New Jersey Department of Health (NJDOH) declared
these sites to be a public health hazard due to concerns about lung
cancer. Montclair/West Orange and Glen Ridge were listed on the National
Priorities List (NPL) for Superfund sites in 1985 because of their
proximity to radium waste generated by radium processing. These plants
had operated in the area after the turn of the 20^th^ century and an
estimated 200,000 cubic yards of contaminated material were placed on
private and public areas in the communities.

NJDEP officials were planning to notify local government officials and
residents of their findings in early December 1983. However, despite a
request by NJDEP officials to hold the story until official notification
had been made, a November 30^th^ television news report broke the story
early. According to the *New York Times* (October 16, 1984) article
published one year later, "\[Many\] residents of the three communities
-- Montclair, West Orange and Glen Ridge -- were not told about the
problem until...technicians, wearing protective gear began taking soil
and air samples in and around their homes." A couple of news reports,
referred to the radium contamination in New Jersey as "another Love
Canal," since both residential areas were built on contaminated soil.

Initial attempts to remove the contaminated soil were hampered by the
lack of suitable waste depository, resulting in 4,902 drums and 33
containers of soil being stored for nearly two years on the yards of
partially excavated properties in Montclair. In 1999, nearly 20 years
after the initial identification of the problem and 12 years after being
put on the NPL, clean-up activities continued to occur as the streets
are replaced and as the EPA continued to investigate the possibility of
additional groundwater contamination. By 1998, a total of \$175 million
had been spent to remediate over 300 houses and remove 80,000 cubic
yards (or 5,000 large truck loads) of contaminated soil. In 2004,
estimates of total clean-up exceeded \$200 million (Table 1).

For this case study of the radium contamination in the communities of
Montclair, Glen Ridge, and East and West Orange in northern New Jersey,
we were able to obtain good data on selling prices, housing
characteristics, and Census information for one decade (1987 to 1997),
which started just two years after the cites were listed on the National
Priority List. This data enabled us to examine the change over time of
housing prices *during* the lengthy multi-phase clean-up process.

The data for this case study showed two different patterns of affects on
housing prices. For homes that neighbored the affected communities, but
did not experience the contamination themselves, there was a general
decrease in property values as described in the meta analysis of the
three metropolitan areas. For the homes that were within the affected
communities, the swings in property value changes were greater and the
initial remediation efforts appear to have caused a temporary recovery
in property value, however, this recovery does not appear permanent. One
possible explanation for this recovery in property values is that the
process of remediation often involved some remodeling of the homes
directly, such as a new garage and/or landscape. Therefore, the clean-up
not only removed potential hazards, but directly improved affected
homes.

[Industriplex and Water Wells G & H, Woburn, Massachusetts]{.underline}:
Woburn is a historic city (founded in 1640) of about 35,000 people
located 12 miles (19.3 kilometers) northwest of Boston. The community is
predominantly blue-collar because of its industrial heritage. In the
mid-1800s, Woburn became known for shoe manufacturing. Local
manufacturing activity later shifted from shoes to leather production,
and Woburn became a leader in the U.S. tanning industry by 1865. By
1884, Woburn was home to 26 large tanneries that employed approximately
1,500 employees and produced \$4.5 million worth of leather. At the peak
of Woburn's tanning industry, from 1900 to 1934, an estimated 2,000 to
4,000 tons of chromium was dumped directly into Woburn's water
resources, as well as 65 to 140 tons of copper, 85 to 175 tons of lead,
and 40 to 75 tons of zinc.

# Woburn is also the location of two large Superfund sites: Wells G & H and Industriplex. Together the sites cover almost 600 acres of land in the 14 square mile (22.5 kilometer) community. Both sites are located in the section of Woburn east of Main Street, a low, swampy area that includes many streams and the Aberjona River. This section of Woburn, referred to as East Woburn, is a mix of industrial and residential areas. For the Industriplex site, homes are located within 1,000 feet and 13,000 households are within a two mile (3.2 kilometer). Approximately 34,000 people live within three miles (4.8 kilometer) of both sites. While the two sites are distinct from each other, the pollution problems at both sites were discovered within a few months of each other. Both sites were evaluated by the Environmental Protection Agency (EPA) and added to the National Priorities List (NPL) in the early 1980s (Table 1). 

Throughout Woburn's history, more than 100 companies used the Aberjona
River, which flows through the city, for industrial waste disposal.
Companies dumped wastes on land, into lagoons and ponds adjacent to the
river, as well as directly into the river itself. From 1853 to 1931,
compounds and chemicals such as acetic acid, sulfuric acid, lead,
arsenic, and chromium, benzene and toluene were dumped behind buildings,
used as fill for low spots, and included in construction material for
dikes and levees. Woburn has a long history of public health problems,
including elevated rates of kidney and liver cancer, colon-rectal
cancer, child and adult leukemia, male breast cancer, melanoma, multiple
myeloma, and brain and lung cancer.

The 330-acre Wells G & H site is located near the Aberjona River, about
one and a quarter miles (2 kilometers) downstream (south) of the
Industriplex site. It once ranked as the tenth worst site on the EPA's
NPL list. The site is the location of two drinking water wells for the
city of Woburn, which were built in 1964 (Well G) and 1967 (Well H).
These wells were located near an automobile graveyard, an industrial
barrel cleaning and reclamation company, a waste oil refinery, a
tannery, a dry cleaner, and a machinery manufacturer. Despite public
complaints about the water from these wells, Woburn continued to use the
wells, especially during the summer. Both wells were finally closed in
1979 after testing showed that the water was contaminated. Soil and
groundwater at the site are contaminated with volatile organic compounds
(VOCs), such as trichlorethylene (TCE) and tetrachloroethylene (also
called perchlorethylne, PCE, or 'perc'). Land in this area is zoned for
industrial and commercial use, with some areas for residential and
recreational use.

The Industriplex site, the location of Woburn's most intensive
industrial activity since the 1850s, consists of 245 acres in an
industrial park and once ranked as the fifth worst site on the EPA's
national priorities list. This area is located one mile (1.6 kilometers)
northwest of the intersection of Interstate 93 and Route 128 and is
bordered by the communities of Wilmington and Reading. Two tributaries
of the Aberjona River flow through the Industriplex site. Of the 245
acres at the site, one-third was contaminated and 60 acres were used for
commercial purposes throughout the remediation of the site.
Contamination at the Industriplex site includes heavy metals and
hydrocarbons. In the soil, the contamination was primarily arsenic,
lead, and chromium and in the water the contamination was primarily
benzene, toluene, arsenic, and chromium. Additionally, hydrogen sulfide
gas emanating from buried animal hides from the tanneries and wastes
once permeated the air.

The discovery of two major hazardous waste problems in one town prompted
strong media interest as well as the active response and involvement of
Woburn's residents. Area newspapers and TV stations ran multi-part
stories about Woburn, alluding to it as a "toxic wasteland". Millions of
dollars and several years were devoted to the Woburn court case which
commanded front-page national media attention. The book describing the
lawsuit, *A Civil Action*, was published in 1996 and became a
bestseller. In 1999, the book was made into a movie staring John
Travolta.

For Woburn, Massachusetts, we were able to obtain data on selling
prices, housing characteristics, and Census information from 1978 to
1997 on 12,444 homes. Therefore, the sample begins one year before the
discovery of contamination at Industriplex and Wells G & H and extends
throughout the lengthy litigation and clean-up activities. The Woburn
case most clearly demonstrates the importance of accounting for
socio-demographic change when conducting economic studies on the value
of neighboring homes. When these factors are included, it becomes
evident that part of the decline in relative values for homes near the
two sites is related to a general deterioration of the neighborhoods and
that by not controlling for these effects that the property affects of
proximity to the sites may be overstated.

[Eagle Mine, Colorado]{.underline}: Eagle Mine is centrally located
between Vail and Beaver Creek ski areas, approximately 100 miles (160
kilometers) west of Denver, Colorado. Eagle Mine lies between the small
towns of Minturn and Red Cliff, just off U.S. Highway 24 and was once
one of the nation's top producers of zinc. The property consists of
approximately 6,000 acres, 340 of which are contaminated with toxic
waste. Most of the contamination originates from areas located along the
Eagle River, and includes: the abandoned mining town of Gilman located
on a cliff just above the mine, the old Eagle Mine processing plant in
Belden, two ponds containing wastes from the smelting of ore, Maloit
Park, Rex Flats, various waste rock and roaster piles, and an elevated
pipeline. The Eagle River (a major tributary of the Colorado River),
Cross Creek, and several other tributaries run through the site.

The Eagle Mine site is contaminated with eight to ten million tons of
hazardous substances including arsenic, nickel, chromium, zinc,
manganese, cadmium, copper, and lead. The main cause of Eagle River
contamination came from acid mine drainage, which occurs when sulfide
minerals, such as pyrite, are exposed to oxygen and water and then
oxidize. This process creates sulfuric acid, which contaminated soil,
groundwater, and surface water surrounding Eagle Mine, producing water
with low pH levels. Acid drainage at Eagle Mine resulted from
precipitation flowing through the waste piles that accumulated from
nearly 100 years of mining. As Eagle Mine acid drainage seeped into
ground and surface water, it killed aquatic life and vegetation growing
along the water\'s edge and contaminated the river with zinc, lead,
manganese, and cadmium. Not only did this contamination threaten brown
trout, the most populous fish in this segment of the river, but it also
permanently stained the rocks in and along the river bright orange,
providing Minturn and Red Cliff residents with a constant reminder of
the contamination at Eagle River.

State studies conducted in 1984 revealed dangerously high levels of
cadmium, copper, lead, and zinc in local water resources. Minturn, with
a population of 1500, is the closest town and draws drinking water from
Cross Creek and two wells located within 2000 feet of the mine tailings.
While Eagle Mine had a history of environmental problems dating back to
1957, the majority of the problems arose after the mine closed in 1984.
In March 1985, Ray Merry, the Eagle Mine Environmental Health Officer,
ordered the 14 families remaining in Gilman to leave the site because of
potential human health hazards. By July, all families had left the area
and Gilman became a ghost town. A gate prohibiting entrance to the town
read "Town for Sale." Eagle Mine was placed on the national Superfund
priorities list (NPL) in June 1986.

As the cleanup began, public concern about the possibility of adverse
human health effects intensified. Although the EPA chose not to endorse
the State of Colorado's cleanup plan because it was skeptical of the
plan's long-term effectiveness, the State forged ahead with the cleanup
of the Eagle River site fearing the worsening of public health and
environmental damages that might result from continued acid mine
drainage. However, the State's decision to pump tailings pond water back
into the mine, using the mine as a holding tank, proved to be disastrous
and caused even more pollution to infiltrate the Eagle River. A dry
winter caused mine seepage to make up most of river water, and the river
turned orange. As a result, fish populations declined dramatically.
Samples taken from the river that fall revealed zinc levels were 255
times higher than fish tolerance thresholds. No fish lived in the river,
and contamination was turning the Eagle River various colors.

For the Eagle Mine, near Vail, Colorado, we were able to obtain data
from 1,087 owner occupied properties downstream of the Eagle Mine over a
24-year period (1976 to 1999). Unfortunately, the data available from
the Eagle County Assessor's office does not span enough distinct Census
tracts for the differences in socio-demographic characteristics across
these tracts to be useful in explaining the variation in housing prices.
A challenge with this area is that, unlike the other three cases, a high
percent of the homes are recreational and not owner occupied. There is
substantial evidence that areas most effected by the pollution from
Eagle Mine, such as Minturn, did not experience rapid development growth
that occurred in other areas of the Vail area, even though they were in
closer proximity to Vail resort.

Due to the lack of socio-demographic data and the fact that this Eagle
Mine affected a mountain community where the main pollution was observed
in a river, not just the original point source, the data from Eagle Mine
was not included in the meta analysis of the three metropolitan areas.
Analyses that did not control for socio-demographic factors indicate
that clean-up did result in increases in property values after the
initial periods of decline after NPL listing and subsequent problems
with the clean-up.

+----------------+-------+-----+-------------------+--------+--------+
| **Table 1.     |       |     |                   |        |        |
| Three          |       |     |                   |        |        |
| Metropolitan   |       |     |                   |        |        |
| Superfund      |       |     |                   |        |        |
| Sites: Key     |       |     |                   |        |        |
| dates and      |       |     |                   |        |        |
| statistics**   |       |     |                   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
| **Site Name**  | **D   | **  | **Major Clean-up  | **Est  | *      |
|                | iscov | NPL | Phases**          | imated | *Total |
|                | ery** | Lis |                   | Cl     | Pr     |
|                |       | tin |                   | ean-up | operty |
|                |       | g** |                   | Cost** | Value  |
|                |       |     |                   |        | Loss** |
+----------------+-------+-----+-------------------+--------+--------+
| **Operating    | 1978  | 1   | 1988\. Drilling   | \$1    | 39.5%  |
| Industries,    |       | 985 | of wells and      | b      |        |
| Inc.           |       |     | groundwater       | illion |        |
| Landfill**     |       |     | treatment         |        |        |
|                |       |     |                   |        |        |
| Los Angeles,   |       |     | 1997\.            |        |        |
| California     |       |     | Construction of   |        |        |
|                |       |     | cap on landfill   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
|                |       |     |                   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
| **Montclair,   | 1983  | 1   | 1991\. Phase 1    | \$200  | 8.9%   |
| West Orange, & |       | 985 |                   | m      |        |
| Glen Ridge**   |       |     | 1993-1995. Phase  | illion |        |
|                |       |     | 2 & 3             |        |        |
| New Jersey     |       |     |                   |        |        |
|                |       |     | 1996\. Phase 4 &  |        |        |
|                |       |     | 5                 |        |        |
+----------------+-------+-----+-------------------+--------+--------+
|                |       |     |                   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
| # Industr      | 1979  | 1   | 1993. Main        | \$80   | 14%    |
| iplex and Wate |       | 983 |       cleanup on  | m      |        |
| r Wells G & H  |       |     |                   | illion |        |
|                |       |     | > both sites      |        |        |
| # Woburn,      |       |     |                   |        |        |
|  Massachusetts |       |     |                   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
| #              |       |     |                   |        |        |
+----------------+-------+-----+-------------------+--------+--------+
| **Eagle Mine** | 1984  | 1   | 1989-1991.        | \$70   | 15.3%  |
|                |       | 986 | Problematic       | mi     |        |
| Colorado       |       |     | State-            | llion, |        |
|                |       |     |                   |        |        |
|                |       |     | led cleanup       | \$0.7  |        |
|                |       |     |                   | m      |        |
|                |       |     | 1996\. Removal of | illion |        |
|                |       |     |                   | annual |        |
|                |       |     | contaminated      |        |        |
|                |       |     | soils             |        |        |
|                |       |     |                   |        |        |
|                |       |     | 1997\. Tailing    |        |        |
|                |       |     | piles             |        |        |
|                |       |     |                   |        |        |
|                |       |     | capped            |        |        |
+----------------+-------+-----+-------------------+--------+--------+

**[Scientific Mistakes and Errors]{.underline}**

The judgments of scientists and experts about the risks associated with
Superfund sites are only one component of the mix of news media stories
and perceptual cues received by the typical citizen. Even if statements
by scientists were accepted as credible, they would have to compete with
the mix of the other signals and perceptual cues. As simply one
component, such statements are unlikely to be the primary determinant of
individual risk beliefs. Risk beliefs determined largely by media
stories and other perceptual cues are unlikely to be easily changed by
the pronouncements of a few scientists (Fischhoff, 1989).

##  Furthermore, it is unlikely that statements by scientists will be accepted as completely credible. Even when different scientists are in essential agreement, the news media often focuses on those aspects where experts disagree (Wilkins and Patterson, 1990), thus lowering the perceived credibility of the experts. In a study examining news coverage of Three Mile Island and Chernobyl, Rubin (1987) found that news stories tended to dichotomize events rather than blend a continuum of information to recipients. The result is that the public discredits information it receives from experts because it appears that experts cannot agree among themselves and, therefore, do not really know the risk that a site presents. 

## News about human and environmental health is omnipresent. Despite the ideal that science discovers absolute truths, for every health or environment related article there appears to be a corresponding article that rejects the tenets of the previously publicized claim. The press is teeming with contradictory evidence. Nearly every day newspapers, magazines, and television shows report new information that further obscures issues rather than clarifies them. A cursory survey of two major national newspapers conducted between September 1, 1999, and November 1, 1999, yielded several articles that contested previously reported knowledge and claims or presented evidence of scientific or expert misjudgment or error. These articles reported the following: 

-   Contrary to the previous claims of the manufacturer, the diet drugs
    Redux and fen-phen can cause permanent heart damage ("Studies
    Bolster Link Between Diet Drugs, Heart-Valve Leaks", *Wall Street
    Journal*, September 10, 1999).

-   A drug manufacturer did not report to the Federal Drug
    Administration (FDA) all relevant test results prior to petitioning
    the FDA for approval of a drug ("Questions for Drug Maker on Honesty
    of Test Results: FBI Asks About Diet Product's Approval" *New York
    Times*, September 10, 1999).

-   For more than forty years, the tobacco industry suppressed evidence
    that tobacco use causes cancer ("Tobacco Industry Accused of Fraud
    Lawsuit by U.S.", *New York Times*, September 23, 1999).

-   Trained operators of a nuclear power plant in Japan poured more than
    six times the required amount of uranium into a tank, resulting in a
    nuclear chain reaction ("Japanese Fuel Plant Spews Radiation After
    Accident" *New York Times*, October 1, 1999).

-   The Mars Orbiter burned in space because the spacecraft's creator
    used imperial measurements when the spacecraft's navigational team
    used metric measurements ("Two Teams, Two Measures Equaled One Lost
    Spacecraft" *New York Times*, October 1, 1999).

-   Persian Gulf War soldiers who were given a drug to protect them from
    nerve gas attacks suffer from damage to areas of the brain that
    control reflexes, movement, memory, and emotion ("Drug May Be Cause
    of Veterans' Illness: Pentagon Survey Links Gulf War Syndrome to
    Nerve-Gas Antidote" *New York Times*, October 19, 1999).

-   Soldiers who participated in nuclear tests for the military in the
    1950s have higher than normal death rates and an increased
    likelihood of developing leukemia and prostrate and nasal cancer
    ("Testing in Nevada Desert is Tied to Cancers" *New York Times*,
    October 26, 1999).

Due to this barrage of events and news stories that present
contradictory, inaccurate, or incomplete scientific/expert evidence, it
is unlikely that the public will accept expert evidence as absolutely
accurate all the time. The result is that the public discredits
information it receives from experts because it appears that experts
cannot agree among themselves and, therefore, do not really know the
true risks associated with a situation Numerous other case studies
document errors and misestimation by scientists, government, and
industry as well as of scientific error exist. Other examples include:

*Errors by scientists*

-   The false discovery of Cold Fusion

-   The failures at Biosphere 2

-   Dioxin contamination in Times Beach, Missouri

> *Errors by government*

-   The near nuclear meltdown at Three Mile Island

-   Soil contamination at Love Canal, Niagara, New York

> *Errors by industry*

-   The defective Dalkon Shield for birth control

-   The Union Carbide Accident in Bhopal, India

-   Birth defects from Thalidomide

-   Environmental problems caused by DDT

The frequency of events as well as the ambiguity and uncertainty of
experts, government officials, and the media, as demonstrated by these
short case studies, leads to doubt and skepticism on behalf of the
public. The implication is that residents living near Superfund sites
are forced to construct their own risk beliefs based on perceptual cues
and media coverage. McClelland et al. (1990) surveyed residents near OII
about their risk beliefs and found a bimodal response with more than
half believing that living near the site was as dangerous as smoking
four packs of cigarettes per day, with an incremental annual risk of
death of approximately 1/100. Most of the remaining residents viewed the
risk as trivial. Assuming typical values for statistical life and
assuming three people per home, the discounted present value of the risk
for the residents that assessed the risk as similar to smoking exceeds
the price paid by these residents for their homes! Residents who
responded this way did report that they were desperate to sell and
sought immediate cleanup.

**Risk Perception, Perceptual Cues, and Stigma**

Some of the most important determinants of risk beliefs are perceptual
cues. Perceptual cues are physical aspects of a site that are perceived
by local residents, and are suggestive of risk. Examples of perceptual
cues include odors emanating from landfills, unusual odors or flavors in
well water, unusual soil or water coloration at the site, and a heavy
volume of truck traffic going in and out of the site. Ironically, some
of the actions taken by authorities to minimize public health and safety
risks tend to exacerbate risk beliefs by providing clear cues that some
risk is present. Erecting chain link fences, placing warning signs,
conducting on-site tests (especially by workers wearing protective
clothing) are all cues to residents that risk levels may be higher than
they thought. Such actions, which may be necessary, almost never lower
risk beliefs. Proximity to a site increases the frequency and duration
of contact with, or observation of, perceptual cues, which contributes
directly to the intensity of risk beliefs.

The effects of strong perceptual cues are well illustrated by the OII
Landfill. Initially, concern about high volumes of truck traffic and
odors (produced by decomposition in the landfill) prompted local
residents to organize and confront problems associated with the site.
McClelland et al. (1990) found a significant correlation between
recognition of these perceptual cues and the high risk beliefs of many
residents living near the site. Several of the perceptual cues were
removed or reduced by (a) installing wells to extract the methane gas
for commercial use and (b) closing the site, which eliminated most of
the truck traffic. Even though these actions did not address risks that
hazardous substances would migrate into local neighborhoods, the risk
estimates of many residents dropped dramatically after the principal
perceptual cues were removed. McClelland et al. also demonstrated that
there were significant property value losses associated with these risk
beliefs.

Attention given to a site in the media, apart from the actual content of
news stories, is itself a perceptual cue that risks may be high. Many
studies have shown that frequent exposure to media reports about a site
increases the likelihood that residents will believe the site is very
risky. The specific risk at a site and perhaps the site itself will
usually be unfamiliar to residents. That in itself increases risk
beliefs (Wilkins and Patterson, 1990). But more importantly, it means
that residents are almost totally dependent on the news media for
information about the risk. Reflecting the concerns of their consumers,
the news media often focus on aspects that accentuate dread, such as the
uncontrollability of the risk and the frightful worst outcome (e.g.,
dying of cancer) rather than on information about the low probabilities
of the risk and how those probabilities compare to other risks that
residents accept.

The signals that the media sends to the public regarding risks from
hazardous waste sites are important, but the way in which the public
interprets this information is equally important. A key feature of how
news coverage is interpreted by residents is whether there is an easily
identifiable \"villain\" responsible for the hazardous waste problems at
the site. For example, if the responsible party is a corporation whose
primary business activity is outside the community, then it is more
easily portrayed as a villain than a local business which has strong
affiliations to the community. Russell et al. (1991) found that the more
important a site\'s PRPs (potentially responsible party) were to the
local economy, the more skeptical residents living near the site were
that it needed to be cleaned up. Personal familiarity with a site also
influences how news reports are interpreted. The greater the prior
familiarity, the less risk beliefs are likely to be elevated by news
stories.

The largest PRP for the OII Landfill was an outside corporation that had
not provided significant employment or other economic benefits for the
residents who lived nearby. Most of the waste, especially that which was
hazardous, was generated and brought to OII from outside the community.
OII was primarily a commercial landfill serving many interests outside
of the community. In short, conditions were ripe for news stories to
elevate risk concerns significantly. How a risk affects the community,
society, and the economy will depend on individual and group perceptions
of the risk (Slovic et al., 1991). There can be a compounding or
\"rippling\" effect as more and more individuals respond to the risk
(Kasperson et al., 1988). Or, as Dr. Paul Slovic describes it,
interactions among individuals can produce a \"social amplification of
the original risk concern.\" The greater the population is living near a
site, the greater the potential for compounding or social amplification.

When residents or potential buyers are extraordinarily fearful of a site
they respond by shunning the site. This behavioral response has been
labeled stigmatization and has been explored in a number of experiments
that suggest that if risks are perceived as being excessive, people
replace calculations of risk versus benefit with a simple heuristic of
shunning, the avoidance of the stigmatized object.

Stigma has been shown to have a number of key properties. Laboratory
experiments testing these properties have involved dipping a sterilized
cockroach into glasses of juice and gauging subjects' willingness to
drink the juice after the cockroach has been removed (Rozin, 2001).
First, stigma shares many of the psychological characteristics of
contagion, where contagion is associated with touch or physical contact.
For example, while subjects refused to drink the juice if the sterilized
cockroach was dipped into the glass, they would drink the juice if the
cockroach was just placed near it. Second, stigma appears to be
permanent. Subjects refused to drink the juice even if the it been in
the freezer for one year. Third, stigma appeared to be insensitive to
dose, as reductions in the duration of contact between juice and
cockroach had little effect. Any contact was sufficient for subjects to
shun the juice. Fourth, the source of contagion is usually unknown.
Thus, while shunning may have evolved from an adaptive response to avoid
contaminated food, it can be triggered in inappropriate circumstances.
For example, subjects who saw sugar water placed in a clean empty jar
and then saw a cyanide label placed on the jar still tended to refuse to
drink the sugar water. Finally, subjects tend to medicalize the risk,
arguing that the stigmatization was the result of a fear of health
effects.

**Stigma and Property Values**

In contrast to the hedonic approach (Rosen, 1974, and for application to
hazardous sites see Bartik, 1998, Harrison and Stock, 1984, Ketkar,
1992, Kolhase, 1991, Mendelsohn, et al, 1992, Michaels and Smith, 1990,
etc.) where risk is treated as one of many attributes that contribute to
a determination of sale price, stigma is likely to effect property
values in a rather different and more direct manner. Upon learning of
the contamination potentially affecting their community, some current
home owners will simply be unwilling to continue to live in their home,
and likewise, potential buyers will be unwilling to consider buying a
home in that community. Thus, this shunning by both current owners and
potential home buyers reduces the total demand for housing for a
neighborhood near a site as shown in Figure 1. Imagine that the total
demand for homes in a particular fully built-out neighborhood with H
existing homes is Q(P) where Q is the number of desired homes, P is the
sale price, and quantity demanded falls with price, Q\'\< 0. If, for
example, homes were sold in a competitive uniform price auction, the
equilibrium price, P~e~, is obtained by solving H=Q(P), so
P~e~=Q^-1^(H). Now consider the case where a fraction f of home buyers
and owners shun a neighborhood because of a nearby Superfund site. The
usual hedonic model cannot handle this phenomenon because the hedonic
price adjustment for these individuals, either through very high
subjective risk beliefs (assuming conventional values of statistical
life) or shunning would give homes a risk deficit greater than or equal
to the value of the home. In other words, in either case the perceived
costs of staying in the home are greater than the entire value of the
home and the observed behavior would be identical. This implies that
fraction f of current owners will sell and that the number of potential
buyers will be reduced by fraction f as well. As shown in Figure 1,
since we have defined total demand for the neighborhood to include
current owners, the equilibrium price will now be determined by the
solving H=(1-f)Q(P), so P~e~\*=Q^-1^(H/(1-f)) and P~e~\* \< P~e~ for f
\> 0. If f falls with distance from the site, as is likely since
perceptual cues decline with distance, then property values will rise
with distance, *ceteris paribus.*

Figure 1: The effect of Stigma on Equilibrium Housing Prices

![](media/image1.pct)

The next question is, since a hedonic analysis is used for predicting
property prices, how can downward sloping demand be incorporated into
the analysis? The answer proposed here is that hedonic models predict an
average price based on home and community attributes, but do not take
into account individual buyer characteristics that will affect the
willingness to pay for homes in a particular area. So, for example,
relative to a predicted hedonic price, P~h~, one particular individual
will be willing to pay more because grandmother happens to live in the
neighborhood and another particular individual will be willing to pay
less because an ex-boyfriend lives in the neighborhood. Clearly no
hedonic market can exist for such attributes since they are buyer
specific and these sale price deviations will appear as part of the
error term in the estimated hedonic equation. Thus, for homes with a
particular set of hedonic attributes in a homogenous neighborhood with a
mean sale price of P~h~, there exists an array of values for homes among
potential buyers, V, with a cumulative distribution function of Q(V).
Presumably, the H buyers with the highest individual values will own
homes in the area.

To further understand the property value market, we model the market
itself as a discriminative auction to account for the fact that
identical homes in the same neighborhood can, in fact, sell for
different prices depending on individual buyer attributes (see Cox et
al, 1984, for a discussion of the relevant theory and an experimental
test of this auction). Approximating the property value market with an
appropriate auction where multiple buyers compete for available homes
solves the potential problem associated with modeling real estate sales
as bilateral negotiations where sellers have no value. Rather, in a
discriminative auction other potential buyers provide competition that
maintains the price at a higher level than that which would be predicted
by bilateral negotiation. The properties of a discriminative auction are
well understood and this auction provides a reasonable approximation of
the real estate market under the special circumstances where homes near
a site are stigmatized.

As previously discussed, sellers in our model have essentially no value
for the homes they are selling since they shun the site. Thus, any price
they can get for the home is acceptable. This corresponds to an auction
situation where buyers bid on H homes put up for sale, and the H bidders
with highest bids obtain the homes for the prices bid. Figure 2 shows
this market in the context of total demand where all homes in a
neighborhood are potentially up for sale. Note that the bids in a
discriminative auction (shown as the lower step function) fall below the
true values (upper step function). Note also, that compared to the price
that would be obtained in a uniform price auction giving a price, P~e~,
in a discriminative auction there is a distribution of bids and sale
prices around the equilibrium price, since buyers pay accepted bid
prices. It is well known that in a discriminative auction that if buyers
are risk neutral, the average of the accepted bids will equal the
uniform price, so revenue neutrality exists in theory between uniform
price and discriminative auctions. Note also that risk aversion will
increase bids in a discriminative auction and bring them closer to true
values because buyers trade off the gain in consumer surplus of a lower
accepted bid against the reduced probability of having their lower bid
accepted. The lower bid curve shown in Figure 2 assumes risk neutrality
and plausibly provides a lower bound for bids in a real estate market.

> Figure 2: Discriminative Auction Market

![](media/image2.pct)

With these concepts in mind, we can then turn to the hedonic model
estimated to explain property values at each of our study sites. The
hedonic model estimated to explain property values uses a logarithmic
specification and takes the form:

$\text{SPRICE}_{\text{it}} = P_{t}\text{DIST}_{\text{it}}^{b_{1t}}e^{b_{2}A_{\text{iT}}}e^{b_{e}S_{\text{it}}}e^{b_{4}D_{\text{iT}}}e^{\varepsilon_{\text{it}}}$
(1)

Here, *P~t~* is an area-wide price index for owner-occupied housing in
year t, *DIST­~it~* is the distance of each dwelling from the Superfund
site in question. The coefficient associated with this variable will be
allowed to differ across years by interacting the constant distance
measure with yearly dummy variables. The vector *A~iT~* is property
attributes and *S­~it~* is a vector of (interpolated) time-varying
characteristics of the census tract in which the dwelling is located,
and *D~iT~* is a vector of the logarithms of the distances from the
dwelling to a potentially relevant set of other spatially differentiated
local amenities or disamenities, calculated at time T, the end of the
sample period, rather than contemporaneously.

Taking the logarithms of both sides of the equation yields a version of
this model that is appropriate for estimation:

$\text{LSPRICE}_{\text{it}} = \text{ln}P_{t} + b_{1t}\text{LDIST}_{\text{it}} + b_{2t}A_{\text{iT}} + b_{3t}S_{\text{it}} + b_{4t}D_{\text{iT}} + \varepsilon_{\text{it}}$
(2)

where *LSRICE~it~* denotes the logarithm of the observed selling price,
ln*P~t~* will be captured as an intercept for the first year in the
sample and a set of intercept shifters activated by year dummy
variables. The variables of key interest are the *LDIST­~it~*, which
consist of a vector of logged distances from the dwelling to the
Superfund site interacted with yearly dummies in order to permit
year-varying elasticities of housing prices with respect to distance to
the site.

Since this equation is estimated separately each year over the 20-30
years of observations that have been obtained for each of the sites, the
variation in b~1t~ (the effect of distance from the Superfund site on
property values) can be observed over time. To dampen noise, we average
b~1t~ the coefficients over three-year intervals.

To get time trends in property values as affected by the site, we
normalize both by the initial three-year period property value effect,
t=0, and by distance. Thus, we ask the question, at a minimum distance
from the site, *DIST*~min~, how do property values compare to price at
distance *DIST*~max~ (the boundary of the available data), which was
chosen to be sufficiently far away that no effects of the site should be
present, and to the magnitude of this effect in the initial period. The
relative property value effect, normalized by base period and by
property values at a large distance is defined as

[]{.mark}$R_{t} = \left( \frac{\text{DIST}_{\text{min}}}{\text{DIST}_{\text{max}}} \right)^{b_{1t} - b_{\text{10}}}$

\(3\)

Thus, the index for each site starts at 1.0 (or 100% in the figures
below) and either decreases or increases in successive three-year
periods from this value.

As can be seen in the Figure 3 presented below, relative property values
of the three metropolitan case studies (OII in Los Angeles, Industriplex
and Wells G&H in Woburn, and Montclair, New Jersey) tend to follow an
overall declining trend consistent with the notion of progressive
stigmatization of the site as suggested by arguments from psychology.
This result is in contrast to a number of earlier studies that examined
property values over shorter time periods (Carroll et al, 1996, Dale et
al 1999, Kiel et al, 1995, 2001).

What explains the long term downward trends observed in relative
property values shown in Figure 3? If the trend is driven by f, the
fraction of home owners and potential buyers who shun homes near the
site, a model of the determination of f over time is needed. From the
discussion of the psychology of risk perception and stigma, the
determination of the fraction of shunners will be driven by media
attention and perceptual cues resulting from activity at the site, which
are in turn driven by events such as discovery, NPL-listing, and
cleanup. Thus, it is plausible that the percentage change between
periods in the fraction of the population who shun the site is a linear
function of events of type j occurring during the prior interval,
characterized by the discrete dummy variable, E~j,\ t-1~, so

> $f_{t} - f_{t - 1} = \alpha + \sum_{j}^{}{\beta_{j}E_{j,t - 1}}$
>
> \(4\)

So, in a period with no events, E~j,\ t-1~= 0 ∀j, we hypothesize that α
is negative and f will decline, thereby raising home values, because
some people who know about the site will leave the area (perhaps because
of job opportunities elsewhere) and some new potential buyers will move
into the area who will have no awareness of the site. Other events, such
as cleanup activities, might, (a) raise awareness and thereby increase
the fraction of the population who shun the site, or alternatively, (b)
reduce the fraction of shunners by convincing people who know about the
site that it is now safe. This latter possibility is unlikely in that
the notion that, \"once contaminated, always contaminated\" is part of
the psychology of stigmatization.

**Figure 3: Relative Property Value over Time for Three Metropolitan
Superfund Sites**

![](media/image3.pct){width="3.49375in" height="4.5in"}(Property values
at site boundary relative to values at study area boundary and initial
year value)

![](media/image4.pct){width="3.591666666666667in" height="4.625in"}

![](media/image5.pct){width="3.502083333333333in"
height="4.503472222222222in"}

There is no available data on f, so the model specified above cannot be
estimated directly. However, if, one assumes a constant elasticity of
demand, η\<0, and risk neutrality, a simple transformation exists
between f~t~ and R~t~ as defined above:$f_{t} = 1 - R_{t}^{- \eta}$.
Thus, the equation describing movement in f~t~ can be rewritten as:

$R_{t}^{- \eta} - R_{t - 1}^{- \eta} = - (\alpha + \sum_{j}^{}{\beta_{i}E_{j,t - 1}})$

\(5\)

To employ this transformation we need to know the relevant elasticity of
demand. Based on the arguments above, the variance of the error term in
the estimated hedonic price equation provides the information to
calculate an approximate price elasticity. It can be shown that, at the
log mean, the point price elasticity is defined as

$h\text{=-}\left( \frac{2}{s\sqrt{2p}} \right)$

\(6\)

where $s$ is the standard deviation from the site-specific regressions.
For the three metropolitan sites, the estimated elasticity of demand is
-1.77 for OII, -1.85 for Montclair and -1.96 for Woburn. Note that the
assumptions of risk neutrality for home buyers and that the residual in
the property value equation is entirely due to unobserved heterogeneity
in individual values are extreme. But they allow a simple approximate
transformation between f and R.

Table 1 presents a meta analysis using the data shown in Figure 3 of
relative property values over time for the three metropolitan sites in
our sample. A total of 21 observations on relative property values were
available from the three metropolitan Superfund sites that provided18
observations on changes in property values for use in the meta-analysis.
For Discovery, NPL Listing, and the Beginning of Major Phases of
Clean-up, dummy variables were used. Events" includes all major
happenings on the site including major news events (both positive and
negative), filing or resolving lawsuits, and major EPA announcements and
Records of Decisions. Note: this does not measure the number of news
articles, but instead more major events that were described in the case
studies). A total of 118 events were listed for the 17 valid
observations.

The meta analysis across the three metropolitan sites shows that
discovery, cleanup itself, and newsworthy events all negatively effect
property values by drawing attention to the site and increasing the
number of owners and potential buyers who shun the site thereafter.
Thus, the effect of any publicity or site information, good or bad,
appears to increase the fraction of the current home owners and
potential buyers that stigmatize and consequently shun the communities
neighboring the sites. In other words, at least within the observed
period of the studies, all news is bad news and causes relatively
permanent property value losses as an increasing fraction of original
owners leave and more potential buyers shun the site. The only good news
in the study is that property values did significantly recover for a
short period after sites were listed on the NPL. But, it is likely that
as soon as it was realized that EPA could not immediately clean up the
sites, the process of stigmatization began with consequent reduction in
property values. All of these coefficients are significant at the 1%
level.

*Table 3: Mini-Meta Analysis for Three Metropolitican Sites, Dependent
Variable*$R_{t}^{- \eta} - R_{t - 1}^{- \eta}$

(Regression explaining relative property value changes over 3-year
intervals as a function of Discovery, NPL listing, Cleanup and
Newsworthy Activities)

  -------------------------------- ----------------- --------------------
  **Model**                        **B**             **t**

  (Constant)                       .118              2.875

  Discovery                        -.258             -3.971

  NPL - Listing                    .211              4.474

  Clean-up Begins                  -.136             -3.752

  Number of Events                 -.026             -5.056
  -------------------------------- ----------------- --------------------

N=18

R^2^ = 0.813

Rather than property losses reversing immediately once the cleanup is
complete, we see no permanent recovery in property values within the
time period of our data and speculate that recovery will only occur as
the local population gradually moves away and the site disappears from
media attention, so more buyers are uninformed. Note that McClelland et
al. (1990) found that most buyers were uninformed in spite of reporting
requirements. The positive intercept in the meta analysis (significant
at the 5% level) indicates that property values will increase at a
linear rate of about 12% every three-years if no actions are taken and
no news is generated by the site. Thus, at OII one could expect a
complete recovery in about a decade if no news is generated from the
site and recovery might occur in about half that time for the other
sites.

The sites excluded from the meta analysis are also of some independent
interest. Although the Eagle Mine (see Figure 4) has very different
characteristics from the three metropolitan sites discussed above, it
shows a similar pattern in that relative property values decline for
most of the period analyzed. Given the small amount of data available
along the Eagle River, we are forced to use six-year rather than
three-year periods for the analysis but do confirm the general pattern
shown above. The inside Montclair property value estimates do not use
distance as an explanatory variable since the homes themselves are
within the Superfund site. Yearly dummy variables averaged over the same
three-year intervals used in the outside-Montclair analysis show that,
unsurprisingly, cleanup itself does have a positive impact on property
values (see Figure 5).

![](media/image6.pct){width="3.7916666666666665in" height="4.875in"}
Figure 4 Figure 5

Another interesting result in the property value studies is the effect
of including socio-demographic variables. As shown in Figure 6, these
make a large difference in the magnitude of property losses at the
Woburn site. Negative socio-demographic trends, that may be the result
of the progressive stigmatization of the site, also take a substantial
toll on property values (that are not included in the meta analysis),
but possibly should be included in any damage assessment.

> Figure 6

![](media/image8.pct){width="3.734027777777778in"
height="4.817361111111111in"}

**Conclusions**

Since economic benefits are based on discounted present value, the
benefits of delayed cleanup for homes surrounding sites are likely to be
negligible where cleanup itself takes 20 years and another 5-10 years
may be needed after cleanup is complete for property values to recover.
The principal policy conclusion becomes evident. A site must be cleaned
up immediately after it is determined to be hazardous. Quasi-permanent
economic damages seem to result from the stigma generated by delayed
cleanup. It is interesting to note that Carol Browner did in fact change
USEPA policy to at least partly attempt to avoid the pattern shown in
this study. EPA began to work with PRPs in an attempt to negotiate
sufficient cleanup at potential Superfund sites to avoid having sites
listed on the NPL. This policy which was developed under the guise of
\"regulatory reasonableness\" may, in fact, have represented an optimal
response given the difficulty stigma presents for neighborhoods
surrounding Superfund sites. It should also be noted that the enormously
costly process of litigation and delayed cleanup that has occurred under
the Superfund program has provided strong incentives for industry to
avoid creating new hazardous waste sites. However, for residents living
near Superfund sites, as they have often stated, the program has failed
in spite of EPA\'s best efforts. In this regard, it should be noted that
when CERCLA was passed, little or none of the work in psychology
necessary to understand the phenomena described here had been completed.
In fact, much of the relevant work was motivated by Superfund sites and
other hazardous facilities.

# References

Adams, G. and Cantor, R. 2001. Risk, Stigma, and Property Value-What are
People Afraid of? In J. Flynn, P. Slovic and H. Kunreuther (Eds.),
*Risk, Media and Stigma -- Understanding Public Challenges to Modern
Science and Technology*, (pp. 175-185), London, UK & Sterling, VA:
Earthscan Publications Ltd.

Bartik, T.J. 1988. \"Measuring the Benefits of Amenity Improvements in
Hedonic Price Models,\" *Land Econ.*, 64(2):172-183.

Carroll, T. M., et al. 1996."The economic impact of a transient hazard
on property values: The 1988 PEPCON explosion in Henderson, Nevada."
*Journal of Real Estate Finance and Economics* 13: 143-167.

Cox, J. C., Smith, V. L., and Walker, J. M. 1984. "The Theory and
Behavior of Multiple Unit Discriminative Auction", *Journal of Finance*,
39 (September), 983-1010.

Dale, L., et al. 1999. "Do property values rebound from environmental
stigmas? Evidence from Dallas." *Land Economics* 75: 311-326.

Fischhoff, B. 2001. Defining Stigma. In J. Flynn, P. Slovic and H.
Kunreuther (Eds.), *Risk, Media and Stigma -- Understanding Public
Challenges to Modern Science and Technology*, (pp. 361-368), London, UK
& Sterling, VA: Earthscan Publications Ltd.

Fischhoff, B. 1989. \"Appendix C \-- Risk: A Guide to Controversy\"
*Improving Risk*

*Communication*, National Research Council, National Academy Press,
Washington, D.C.

Gayer, T. 2000. "Neighborhood demographics and the distribution of
hazardous waste risks: An instrumental variables estimation." *Journal
of Regulatory Economics* 17: 131-155.

Gayer, T., and W. K. Viscusi. 2002. "Housing price responses to
newspaper publicity of hazardous waste sites." *Resource and Energy
Economics* 24: 33-51.

Hamilton, James T. and W. Kip Viscusi, *Calculating Risks: The Spatial
and Political*

> *Dimensions of Hazardous Waste Policy*. Cambridge, Mass.: MIT Press,
> 1999, 326 pp.

Harrison, D. and J. Stock. 1984. \"Hedonic Housing Values, Local Public
Goods, and the Benefits of Hazardous Waste Cleanup,\" discussion paper,
Energy and Environmental Policy Center, Harvard Univ.

Kasperson, R., O. Renn, P. Slovic, H. Brown, J. Emel, R. Goble, J.
Kasperson, and S. Ratick. 1988, \"The Social Amplification of Risk: A
Conceptual Framework,\" *Risk Analysis*, 8(2): 177-187.

Ketkar, K. 1992. \"Hazardous waste sites and property values in the
state of New Jersey,\" *Applied Economics*, 24:647-659.

Kiel, K., and J. Zabel. 2001. "Estimating the economic benefits of
cleaning up Superfund sites: The case of Woburn, Massachusetts."
*Journal of Real Estate Finance and Economics* 22: 163-184.

Kiel, K. A. 1995. "Measuring the Impact of the Discovery and Cleaning of
Identified Hazardous-Waste Sites On House Values." *Land Economics* 71:
428-435.

Kiel, K. A., and K. T. McClain. 1995. "House Prices During Siting
Decision Stages - the Case of an Incinerator From Rumor Through
Operation." *Journal of Environmental Economics and Management* 28:
241-255.

Kohlhase, J. 1991 "The Impact of Toxic-Waste Sites On Housing Values."
*Journal of Urban Economics* 30:1-26.

Kohlhase, J. 1991. \"The Impact of Toxic Waste Sites on Housing
Values,\" *Journal of Urban Economics*, 30:1-26.

Kunreuther, H. and Slovic, P. 2001. Coping with Stigma: Challenges and
Opportunities. In J. Flynn, P. Slovic and H. Kunreuther (Eds.), *Risk,
Media and Stigma -- Understanding Public Challenges to Modern Science
and Technology*, (pp. 331-352), London, UK & Sterling, VA: Earthscan
Publications Ltd.

McClelland, G., W. Schulze, and B. Hurd. 1990. \"The Effect of Risk
Beliefs on Property Values: A Case Study of a Hazardous Waste Site,\"
*Risk Analysis*, 10:485-497.

McCluskey, J. J., and G. C. Rausser. 2001."Estimation of perceived risk
and its effect on property values." *Land Economics* 77: 42-55.

Mendelsohn, R., D. Hellerstein, M. Huguenin, R. Unsworth, and R. Brazee,
1992. \"Measuring Hazardous Waste Damages with Panel Models,\" *J. Env.
Econ. Manag.*, 22:259-271.

Michaels, G. and V. Kerry Smith. 1990. \"Market Segmentation and Valuing
Amenities with Hedonic Models: The Case of Hazardous Waste Sites,\"
*Journal of Urban Economics*, 28:223-242.

Page, G.W. and H. Rabinowitz. 1993. \"Groundwater Contamination: Its
Effects on Property Values and Cities,\" *Journal of the Amer. Planning
Association*, 59:473-481.

Rosen, S. 1974. \"Hedonic Prices and Implicit Markets: Product
Differentiation in Pure Competition,\" *Journal of Political Economy*,
82:34-55.

Rozin, P. 2001. Technological Stigma: Some Perspectives from the Study
of Contagion. In J. Flynn, P. Slovic and H. Kunreuther (Eds.), *Risk,
Media and Stigma -- Understanding Public Challenges to Modern Science
and Technology*, (pp. 31-40), London, UK & Sterling, VA: Earthscan
Publications Ltd.

Rubin, D. 1987. \"How the Media Reported on Three Mile Island and
Chernobyl,\" *Journal of Communication*, 37(3):42-57.

Russell, M., E. Colglazier, and M. English. 1991. *Hazardous Waste
Remediation: The Task Ahead*, Waste Management Research and Education
Institute. Hazardous Waste Remediation Project. The University of
Tennessee, Knoxville.

Slovic, P., M. Layman, N. Kraus, J. Flynn, J. Chalmers, and G. Gesell.
1991. \"Perceived Risk, Stigma, and Potential Economic Impacts of a
High-Level Nuclear Waste Repository in Nevada,\" *Risk Analysis*,
11(4):683-696.

Viscusi, K.W. and J.T. Hamilton. 1994. \"Superfund and Real Risks,\"
*American Enterprise*, Vol. 5, no. 2, March-April, 36-45.

Wilkins, L. and P. Patterson. 1987. \"Risk Analysis and the Construction
of News,\" *Journal of Communication*, 37(3):80-92.

Wilkins, L. and P. Patterson. 1990. \"Risky Business: Covering
Slow-Onset Hazards as Rapidly Developing News,\" *Political
Communication*

[^1]: ^\*^ This research was supported by the USEPA under cooperative
    agreement CR 824393-01-0. This study has not been reviewed by USEPA
    and all results and conclusions are the sole responsibility of the
    authors. We do wish to thank Alan Carlin for his patience and
    support.