Not In My Neighborhood: The Effects of Single-family Rentals on Home Values

2021 ◽  
pp. 101789
Author(s):  
Keith Ihlanfeldt ◽  
Cynthia Fan Yang
Keyword(s):  
Urban Studies ◽  
2020 ◽  
pp. 004209802092603
Author(s):  
Lindsey Conrow ◽  
Siân Mooney ◽  
Elizabeth A Wentz

City officials and planners have shown increased interest in pedestrian- and bicycle-friendly designs aimed at addressing urban problems such as traffic congestion, pollution, sprawl and housing availability. An important planning consideration is the economic impact associated with existing or planned infrastructure, especially in relation to home property values. In this study, we use measures of infrastructure and ridership to evaluate the relationship between bicycling infrastructure and activity and single-family home values in Tempe, Arizona. We apply a hedonic modelling approach and find that bicycle infrastructure density is positively associated with home sale price, while ridership density around home locations has no significant relationship with sale price. Our results inform discourse related to the potential economic values of residential bicycle infrastructure, especially in areas where property tax is a source of local public finance revenue. We show that the characteristics of bicycle-friendly design may be the same characteristics valued by homebuyers and the resulting increased home sale values may lead to increased property tax revenue in Tempe, Arizona.


2016 ◽  
Vol 9 (4) ◽  
pp. 483-501 ◽  
Author(s):  
Jin-Seong Lee

Purpose The primary purpose of this study is to identify whether there is a price premium and consumers’ preferences for higher housing density, and whether there is a relationship between housing densities and sales prices. The second purpose was to identify if there is a non-linear relationship between housing density and prices even though housing density is directly associated with housing prices. Design/methodology/approach This paper applies hedonic modeling techniques to measure the value of development density of apartments in the metropolitan area of Seoul, South Korea. The regression of the sale price is a function of different types of variables such as density, market, location and other control variables. Findings For the first question, this paper concludes that the higher densities cause housing prices to decrease in Seoul. The summary of the results presents that housing density, floor area ratio (FAR), building coverage ratio and floor level are all important components affecting housing prices. Generally, consumers tend to buy housing with central heating systems, more parking spaces, smaller portion of rental housing within an apartment and buildings that have more of a mixed-use function. Consumers are also found to pay higher premiums for housing in areas with high population growth and less housing supply. It is conclusive that people are inclined to live in populated areas but do not want more density. For the second question, the results show that generally FAR has quadratic effects, but most housing density variables tend to have a non-linear relationship depending on the different quantile groups. Originality/value There is a knowledge gap in the area of estimating development density of apartments. Generally, studies investigating property value impacts of multifamily housing focus on external effects of the multifamily housing on home values to examine whether high density development could result in a decrease in nearby property values. These studies found that there are some positive effects. A study found that high-density housing increases property values of existing single-family homes (Joint Center for Housing Studies, 2011). More specifically, developments that are of a high design quality and superior landscaping increase values of single-family homes as well. Also, those residents who live in these high-density apartments can be good potential buyers for the existing single-family homes. The greater the number of buyers, the greater the housing market becomes. Similarly, according to a report by the Joint Center for Housing Studies (2011) at Harvard University, the presence of multifamily residents correlates with higher home values in “working communities”. Indeed, density can be an important factor determining value of apartments because of its unique characteristics. However, no empirical evidence has been provided in the literature with regard to the value of the development density. This study contributes toward improving this knowledge gap.


Author(s):  
Hong Chen ◽  
Anthony Rufolo ◽  
Kenneth J. Dueker

In theory, proximity to light rail transit (LRT) may have two different effects on residential property values. On the one hand, accessibility (proximity to LRT stations) may increase property values. On the other hand, nuisance effects (proximity to the LRT line and stations) may decrease property values. Existing empirical studies are inconclusive, and failure to separate the effects of accessibility from the nuisance effects may explain some of the ambiguity. An examination is presented of the impact of the light rail system (MAX) in Portland, Oregon, on single-family home values using distance to rail stations as a proxy for accessibility and distance to the line itself as a proxy for nuisance effects. Geographic information system techniques are employed to create spatial-related variables and merge data from various sources. The study results confirm the hypothesis that the light rail has both a positive effect (accessibility effect) and a negative effect (nuisance effect) on single-family home values. The positive effect dominates the negative effect, which implies a declining price gradient as one moves away from LRT stations for several hundred meters. Without controlling for the nuisance effect of the distance to the rail line, the estimated coefficients on distance from stations appear to be biased and would underestimate the accessibility effect. The finding of an independent nuisance effect suggests that previous hedonic models may have reached contradictory results because the nuisance effect differs with different types of rail or other local characteristics.


2014 ◽  
Vol 13 (3) ◽  
pp. 254-274 ◽  
Author(s):  
John R. Hipp ◽  
Amrita Singh

Research has generally failed to explore whether the effect of neighborhood characteristics on home values has changed over time. We take a long–range view and study decadal changing home values in the southern California region over a 50–year period, from 1960 to 2009. We focus on the effects of racial composition and measures associated with the New Urbanism on changing home values. We find that whereas neighborhoods with more racial/ethnic minorities and racial mixing experienced relative decreases in home values in the earlier decades, this effect has effectively disappeared in the most recent decade and actually became positive for some measures. We also found that certain characteristics associated with the New Urbanism—population density, older homes, a lack of concentration of single family units—show stronger positive effects on home values in the most recent decades.


2008 ◽  
Vol 04 (02) ◽  
pp. 143-163 ◽  
Author(s):  
MAK KABOUDAN

This paper investigates use of genetic programming regression models to forecast home values. Neighborhood prices in a city are represented by a quarterly index. Index values are ratios of each local neighborhood to the global city average real price of homes sold. Relative average neighborhood home attributes, local socioeconomic characteristics, spatial measures, and real mortgage rates explain spatiotemporal variations in the index. To examine efficacy of model estimation, forecasts obtained using genetic programming are compared with those obtained using generalized least squares. Out-of-sample genetic programming predictions of home prices obtained using spatial index models deliver reasonable forecasts of home prices.


2018 ◽  
Vol 4 (4) ◽  
pp. 473-490 ◽  
Author(s):  
Junia Howell ◽  
Elizabeth Korver-Glenn

The history of the U.S. housing market is bound up in systemic, explicit racism. However, little research has investigated whether racial inequality also persists in the contemporary appraisal industry and, if present, how it happens. The present article addresses this gap by centering the appraisal industry as a key housing market player in the reproduction of racial inequality. Using a census of all single-family tax-appraised homes in Harris County (Houston), Texas, the authors examine the influence of neighborhood racial composition on home values independent of home characteristics and quality; neighborhood housing stock, socioeconomic status, and amenities; and consumer housing demand. Noting that substantial neighborhood racial inequality in home values persists even when these variables are accounted for, the authors then use ethnographic and interview data to investigate the appraisal processes that enable this inequality to continue. The findings suggest that variation in appraisal methods coupled with appraisers’ racialized perceptions of neighborhoods perpetuates neighborhood racial disparities in home value. The authors conclude with suggestions for future research and policy interventions aimed at standardizing the appraisal process.


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