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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 286
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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. 287
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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. 288