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ADDITIONAL INFORMATION
The following four tables provide information useful in performing the methods presented in this
chapter. Table 12-2 provides a summary of findings from recent studies on house prices and
local amenities and disamenities. In general, these studies found that good access to major
highways has a positive effect on house prices, but when the house is very near to the facility,
noise, dust, and other disamenities may counter the value of accessibility to some extent.
Table 12-2.
Selected recent studies of house prices
and local amenities or disamenties
Study Findings
Studies of highways or other transportation infrastructure
Boarnet and Chalermpong (2001) Impact of new toll roads on house prices in Orange
County, CA; techniques used include hedonic
estimation and repeat sales
Langley (1981) Impact of the Washington, DC Beltway on house
prices; found that house prices increase with the
distance from the highway out to a distance of 1,125
feet, and then decrease beyond that distance
Gatzlaff and Smith (1993) Effect of Miami rail transit on house prices; used
repeat sales technique to construct house price index
Huang (1994) Surveyed the literature on the impacts of
transportation infrastructure, specifically transit
stations and highways, on property value
Kockelman and ten Siethoff (2002) Property values and highway expansion: an
investigation of timing, size, location, and use
effects
Studies of other (nontransportation) environmental amenities or disamenities
Gayer (2000) Effect of Superfund hazardous waste sites on house
prices in the greater Grand Rapids, MI, area
Gayer et al. (2000) Effect of Superfund hazardous waste sites on house
prices in the greater Grand Rapids, MI, area
Kiel (1995) Effect of Superfund hazardous waste sites on house
prices in Woburn, MA
Leggett and Bockstael (2000) Effect of fecal coliform bacteria in Chesapeake Bay
on the price of waterfront property
Palmquist and Danielson (1989) Soil quality and farmland value in North Carolina
Smith and Huang (1993) Air quality (metaanalysis of 26 studies)
Smith and Huang (1995) Air quality (metaanalysis of 37 studies)
Zabel and Kiel (2000) Air quality and house prices in Chicago, Denver,
Philadelphia, and Washington, DC, metropolitan
areas
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Table 12-3.
Residential gradients from recent studies
1
Author(s) Year Data Metro area Rent gradient
Highway studies
Boarnet and Chalermpong 1988- House sale price and Orange County, -$0.88 to -
(2001) 2000 distance to nearest CA $4.49/ft. (1982
highway ramp dollars)
Voith (1993) 1970- House sale price and auto Montgomery -$955 to -$1,168
1988 commute time County, PA (1990 dollars)
per minute
Langley (1981) 1962- House sale price index Washington, DC, -$3,000 to
1978 from sale-resale pairs, Metro Area -$3,500 per
comparing houses within house for
and outside of 1,125 foot properties within
buffer from highway 1,125 feet of
highway
Li and Brown (1980) 1971 House sale price and Boston, MA -$1,642 to
distance to expressway -$1,815 per
interchange house for each
doubling of
distance
Transit studies
Haider and Miller (2000) 2000 Prices of houses in and out Greater Toronto C$4,000/house2
of 1.5 km distance from area, Canada
subway line
Sedway Group (1999) 1999 House price and distance San Francisco -$3,200 to
from transit station Bay Area, CA -$3,700/mile
(Alameda and
Contra Costa
Counties)
Cambridge Systematics 1997 House price and distance San Francisco -$2.88 to
(1998) from transit station Bay Area, CA -$69.12/ft 3
(Urban/CBD
properties)
Voith (1993) 1970- House sale price and Montgomery $7,279 to
1988 accessibility to train station County, PA $9,605/house
1
Unless otherwise indicated, this is the drop in value for each unit distance from a transportation facility.
2
In this study, the authors separate housing stock into two groups: one includes houses within a 1.5km distance of a
subway line and the other includes the rest of the housing stock. All else equal, the authors found that a house within
the 1.5 km distance of a subway line sells for C$4,000 (4,000 Canadian dollars) more, on average.
3
The gradients are for single-family housing units in urban areas. The gradient is steep closer to the BART station
(within 1,000 ft.) and flat farther from the station (more than 2,000 ft.). In other words, house values drop quickly
near station but slowly far away from station. Note, also, that the data used in this study were gathered from
properties that are located in urban areas (not suburban locations) and within 2,500 feet of stations only. The
magnitude of gradient is much higher than in the Sedway study, where the data are from suburban counties.
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House price gradients that were obtained from various studies on transportation and residential
property values are listed in Table 12-3. We note that some of these studies are quite dated. The
various price gradients estimated in these studies corroborate the less specific findings presented
in Table 12-2 in that the Orange County and Boston studies indicate a considerable negative
price effect of distance from a major highway. The trade-off between the positive influence of
shorter commute times versus the negative effect of direct proximity to such a facility is evident
in the two studies of the Washington, DC, area.
Similar information for commercial property is presented in Table 12-4. In the case of
commercial properties, access to major highways and thus customers has a strong positive
impact on property values. In some cases, these studies found a greater than linear decline in
values with greater distance from an access point.
Table 12-5 lists a series of gradients obtained from a recent TCRP report. That study found that
direct proximity to a rail transit station within the city has a major positive effect on both single-
and multiple-family residential property values. Within the city, impact on per-square-foot rental
prices for offices space is nearly twice that on retail space. In suburban areas, retail space
benefits much more due to direct proximity to a station.
Table 12-4.
Gradients for commercial property
Author(s) Year Data Metro area Rent gradient
Highway studies
Kockelman and ten 1982- Property and land value Austin, TX -$510,000/
Siethoff (2002) 1999 (10 types of use) and acre/sq.mi.1
distance to frontage road
network
Transit
Cambridge Systematics 1998 Rent per sq ft per month of San Francisco -$.05/1000
(1998) retail and office properties Bay Area, CA sq ft/mo/mi
Sedway Group (1999) 1999 Land price per sq ft for San Francisco -$117/sq ft/
office properties Bay Area, CA mi
1
The gradient in this case is quadratic (dollar value per distance squared), rather than linear (dollar value per
distance). In the case of a quadratic gradient, the negative effect of being away from a frontage road increases more
rapidly with distance than in the case of a linear gradient. For example, for the gradient of $510,000/acre/sq mi,
being 0.1 mile away from the road network will reduce property value by $5,100 per acre. If we double the distance
to 0.2 mile, the effect on land value will be quadrupled, to -$20,400 per acre. In the linear case, however, doubling
the distance will only double the negative effect on land value.
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