Home Sale Prices Research Articles

Geospatial Analysis of the Socioeconomic and Demographic Effects of Historic Coal Mining in the Greater Pittsburgh Region, Pennsylvania, USA

A geospatial model was developed to statistically assess the socioeconomic effects of coal mining in the greater Pittsburgh, Pennsylvania area by integrating home sale data, abandoned mine lands (AML) inventory “problem area” sites, and census demographic information. Results indicated that homes located within problem areas sold for an average of 28% ($58,600) less than homes outside of these regions. Demographic data revealed a notable disparity in the population distribution within Allegheny County mining problem areas as having a statistically significant larger Black population. This same trend was even more pronounced in urban areas. The study also established that areas influenced by past mining activities had a higher proportion of individuals without formal postsecondary education. Logistic regression models were created to analytically evaluate the relationship between predictor variables, specifically home sale price and Community Needs Index, to the probability of being situated within mining problem areas. The home sale analysis indicated a negative correlation between sale prices and the likelihood of residing in a mining-affected zone, implying that properties with lower prices are more commonly situated in these impacted areas. The CNI logistic regression model revealed a correlation between the probability of living in a mining problem area and overall higher community needs.

Estimating proximity effects to wildfire fuels treatments on house prices in Cibola National Forest, New Mexico, USA

Forested landscapes in the Western United States are subject to growing size and severity of wildfires, in part due to historical management strategies focusing on wildfire suppression. Forest restoration treatments and fuels reductions, including thinning and prescribed burning, can reduce the frequency and intensity of wildfires. Extensive restoration and fuels treatment efforts are underway across many areas in the Southwestern United States, including New Mexico. The tradeoff between amenity values provided by forested landscapes and the wildfire risk associated with forested landscapes is becoming increasingly important to understand as development in the wildland-urban interface increases. Understanding how house proximity, relative to forest restoration or fuels treatments, is capitalized into home sale prices can provide useful information about how individuals value forested landscapes that have been altered to reduce wildfire risk or severity. We use a Hedonic Property Model to estimate the average treatment effect of proximity to forest restoration or fuel treatments in New Mexico, United States. We use matching methods to estimate the average treatment effect of proximity to forest restoration. We find that proximity to the forest has a positive amenity value; however, proximity to recent forest restoration or fuel treatments results in a decrease in house sale prices. We combine the results of our two models and calculate that homes not within one kilometer of a treated forest and within one kilometer of Cibola National Forest sell for an average $73,626 premium. The average premium drops to $22,996 for homes within one kilometer of a forest that has been recently treated and within one kilometer of Cibola National Forest.

Regional transport accessibility and residential property values: The case study of the Greater Toronto and Hamilton area

There has been a growing interest in land value capture as a means of funding investments in transport infrastructure (TI), as reported in a vast literature analyzing the relationship between property values and accessibility provided by TI in general and transit specifically. There has, however, been limited research on the role of network-level regional transport accessibility and the intra-regional spatial heterogeneity of the price effects. Furthermore, studies usually focus on one transport mode, disregarding the multi-modal competition, and are mostly (pooled) cross-sectional analyses which do not reflect the dynamic nature of developments in TI and housing markets. To address these gaps, this paper empirically investigates the roles of local and regional transport accessibility by car and transit on the evolution of sales prices of single-family homes from 2001 to 2016, across different geographical contexts while controlling for various determinants in the Greater Toronto and Hamilton Area (GTHA). The spatial panel models’ results confirm that regional transport accessibility does indeed play a significant role in property values over and above the local proximity to TI, with variations between transit and car and over the spectrum of low–high density areas, which needs to be accounted for in land value capture policies.

The impact of current and former REOs across owner types: the case of Detroit

This article examines home price spillovers associated with the number of nearby current and former real estate owned (REO) properties. The effect of active REOs is decomposed into the contributions of properties owned by the government sponsored enterprises (GSEs), US Department of Housing and Urban Development (HUD), and private entities to assess impacts associated with differences in managing REO inventories. The impact of former REOs is decomposed into spillovers associated with investor and owner-occupied properties. This study draws on home sale price data in the Detroit tri-county area 2008–2013. Results indicate REOs owned by HUD and private entities are associated with substantial discounts, with the largest effects appearing after remaining in REO inventory for more than one year. Investor-owned properties are associated with sustained and growing negative price effects through more than three years of ownership. Policies ensuring adequate oversight of REOs and sales to owner-occupants and non-speculative investors are encouraged.

The Impact of Virtual Marketing Strategies on the Price-TOM Relation

Virtual tours such as pre-recorded videos or self-guided virtual reality (VR) tours represent marketing strategies that agents can use to promote homes for sale. Assuming agents aim at maximizing their net commissions, we expect virtual tours, which require more agent effort and are more costly, to be used for homes that are difficult to show due to being owner- or tenant-occupied. Using 34,359 single-family transactions from multiple US markets, we show that virtual tours impact the sales prices of occupied homes (1) directly (main effect) and (2) indirectly through an interaction with time on market (TOM). However, this impact differs in directionality and size across price segments and occupier type. The use of virtual tours has no effect on the sales prices of vacant homes. Our results suggest that virtual tours are effective strategies to overcome the difficulty of showing homes and moderate the price-TOM relation.

The impact of the Coronavirus pandemic on New York City real estate: First evidence.

We investigate whether pandemic‐induced contagion disamenities and income effects arising due to COVID‐related unemployment adversely affected real estate prices of one‐ or two‐family owner‐occupied properties across New York City (NYC). First, ordinary least squares hedonic results indicate that greater COVID case numbers are concentrated in neighborhoods with lower‐valued properties. Second, we use a repeat‐sales approach for the period 2003–2020, and we find that both the possibility of contagion and pandemic‐induced income effects adversely impacted home sale prices. Estimates suggest sale prices fell by roughly $60,000 or around 8% in response to both of the following: 1000 additional infections per 100,000 residents and a 10‐percentage point increase in unemployment in a given Modified Zip Code Tabulation Area (MODZCTA). These price effects were more pronounced during the second wave of infections. On the basis of cumulative MODZCTA infection rates through 2020, the estimated COVID‐19 price discount ranged from approximately 1% to 50% in the most affected neighborhoods, and averaged 14%. The contagion effect intensified in the more affluent, but less densely populated NYC neighborhoods, while the income effect was more pronounced in the most densely populated neighborhoods with more rental properties and greater population shares of foreign‐born residents. This disparity implies the pandemic may have been correlated with a wider gap in housing wealth in NYC between homeowners in lower‐priced and higher‐priced neighborhoods.

Leveraging Main Street as a Real Estate Amenity: Downtown Revitalization and Residential Property Values

As part of their efforts to reverse the effects of twentieth-century downtown disinvestment and automobile-oriented development, stakeholders in small towns across the United States look for viable means of restoring the vitality and character of their historic business districts. In this paper, I evaluate a widely adopted downtown revitalization strategy—the Main Street Program—by measuring its influence on the local housing market. I find that home sale prices are higher for residential properties sold in program-participating communities, and I observe an additional sale price premium for homes located in closer proximity to downtown districts with an active Main Street Program.

Does Home Sale Price Increase with Days on Market? Examining the Heterogeneous Impacts of Marketing Time on Selling Price

Does Home Sale Price Increase with Days on Market? Examining the Heterogeneous Impacts of Marketing Time on Selling Price

Environmental Justice and Urban Parks. A Case Study Applied to Tarragona (Spain)

There is consensus regarding the fact that urban green areas contribute to the quality of life of their inhabitants. Therefore, efficient city management must assess whether the population has access to green areas and the areas’ quality in relation to, for example, vegetation, facilities or furnishings. Therefore, the objective is to establish environmental justice of urban parks in Tarragona (Spain) by developing a Park Quality Index (PQI) and the sociodemographic characteristics (level of studies, Human Development Index –HDI–, home sale and rental prices) of the population living within 300 m of a park. To prepare this, a GIS-integrated Multi-Criteria Evaluation (MCE) was produced. The results show that the green areas have low accessibility and availability and that most parks obtain an average-low PQI, with the best-valued aspect being the vegetation and the worst being the facilities. Regarding the degree of environmental justice, a causal relationship between the PQI and the indicators used emerges. The average value of the home sale prices is the one that shows the greatest correlation. These results can be used together with participatory procedures as a basis for identifying places with greater inequality, and for selecting the more effective actions that enable increasing environmental justice with respect to green areas.

Golf courses and home values in California’s Central valley

PurposeThe purpose of this study is to examine the net effect of golf courses’ proximity on home sale prices in Kern County, California.Design/methodology/approachA spatial Durbin error model is used with sales price data for 1,693 homes sold in Kern County in the third quarter of 2018. This paper compares 90 different spatial econometric models using Bayesian techniques to produce posterior model probabilities which guided model selection and the number of neighbors to use.FindingsThe results show that significant spatial dependence exists in home values in Kern County. Point estimates indicate that homes abutting golf courses are valued at less than those which are not. This study also finds that the farther away from golf courses the average home is, the higher its value.Originality/valueThis study contributes to the existing literature in three dimensions. First, this paper analyzes whether proximity to golf courses impacts home values in Kern County where a study of this nature has not been conducted. Second, the analysis uses transaction data for 2018 which was a period when the sport’s popularity was fading and golf courses closing. Third, Bayesian model comparison techniques are used to select the appropriate model.

노량진뉴타운 재개발사업 주택매매가격 결정요인 분석

This study aims to identify the factors that determine the housing price for each stage of the time phased redevelopment project difference for apartment houses in the same area, targeting the redevelopment project area, Noryangjin New Town District 1, in Seoul. From January 2006 to December 2020, the actual transaction price of transactional housing was extracted and statistically significant variables were set, and an empirical analysis was performed using the hedonic pricing model. As a result of the analysis, it was found that the road interface had a positive (+) effect on the home sales price, and a lot area, years passed and period of contract had a negative (-) effect. The fact that the land area has a negative (-) effect on the housing price is related to the provisions of the provision of housing pre-sale to members. In the case, period of contract and years passed, it is judged to have a negative (-) effect due to a decrease in real estate prices and a recent increase in home sales prices as the project progress is delayed. In addition, the magnitude of the relative influence on the home sale price was in the order, period of contract (-0.684), a lot area (-0.463), road junction (0.192), and years passed(-0.094).

Neighborhood Institutions and Residential Home Sales: Evaluating the Impact of Property Tax Exemptions

We focus on the urban amenities of “neighborhood institutions,” which are the myriad localized governments and nonprofits, such as religious and educational institutions, that provide public or quasi-public services to their neighborhoods. We examine whether neighborhood institutions positively impact their surrounding neighborhoods by utilizing property tax exemption records from the City of Milwaukee, Wisconsin, during 2002–2016. We combine these records with parcel-level data on residential home sales to identify each institution’s exact location and type. Using a traditional hedonic model and a repeat sales model, we examine the influence of nearby tax-exempt properties on residential home sales. We find from the repeat sales model that close proximity (0 m–250 m) to educational properties, labor halls, and utilities are associated with lower home sale prices, all else equal. We find a sporadic and limited positive correlation with nearby colleges and cemeteries and home sale prices.

The Value of “Green” in Resale Residential Real Estate: Premium by Neighborhood Value Quintile, Homestead Status and Year

This paper evaluates about 146,000 home sales from the Multiple Listing Service (MLS) of Bexar County (San Antonio), Texas, from January 2009 to April 2019 to measure the extent that a home’s selling price reflects a Green premium which is identified in the MLS. We exclude new houses from this analysis. For the span of our data, we find a 4.2% increase in the sale price of Green homes, holding other features constant. When evaluated by Area (approximate selling price quintile), we find premiums of 6.9%, 5.7%, 1.2%, 3.5%, and 5.3% by order of increasing neighborhood value quintile. When assessing Homestead versus Non-Aomestead homes, we find a premium of 2.8% for Homesteads and 6.4% for Non-Homesteads. Considering the time trend, we found the premium starting under 3% in 2009 and increasing to a little over 5% where it remained for three years and decreased to about 4% in 2014 where it remained through the end of the data in 2019.

The Impact of the Coronavirus Pandemic on New York City Real Estate: First Evidence

Concerns about the lingering novel Coronavirus may have led to long-term structural change in desired dwelling locations in some large U.S. cities, such as New York City. Densely concentrated neighborhoods may be at higher risk of virus contagion, giving more individuals incentives to move out. We investigate whether this pandemic-induced disamenity adversely affected real estate prices of one- or two-family owner-occupied properties across New York City. First, OLS hedonic results indicate that greater COVID case numbers are concentrated in neighborhoods with lower-valued properties. Second, we use a repeat-sales approach for the period 2003 to 2020, and we find that both the fear of contagion and pandemic-induced income effects adversely impacted home sale prices. Estimates suggest sale prices fell by roughly $60,000 or around 8% in response to both of the following: 1,000 additional infections per 100,000 residents; and a 10-percentage point increase in unemployment in a given MODZCTA. These price effects were more pronounced during the second wave of infections. Based on cumulative MODZCTA infection rates through 2020, the estimated COVID-19 price discount ranged from approximately 1% to 50% in the most affected neighborhoods, and averaged 14%. Interestingly, the fear of contagion effect intensified in the more affluent, but less densely populated NYC neighborhoods, while the income effect was more pronounced in the most densely populated neighborhoods with more rental properties and greater population shares of foreign-born residents. This disparity implies the pandemic led to inequality between homeowners in lower-priced and higher-priced neighborhoods.

The politics of urban trees: Tree planting is associated with gentrification in Portland, Oregon

This study evaluated the hypothesis that urban-tree planting increases neighborhood gentrification in Portland, Oregon. We defined gentrification as an increase in the median sales price of single-family homes in a Census tract compared to other tracts in the city after accounting for differences in the housing stock such as house size and number of bathrooms. We used tree-planting data from the non-profit Friends of Trees, who have planted 57,985 yard and street trees in Portland (1990–2019). We estimated a mixed model of gentrification (30 years and 141 tracts) including random intercepts at the tract level and a first-order auto-regressive residual structure. Tract-level house prices and tree planting may be codetermined. Therefore, to address potential endogeneity of tree planting in statistical modeling, we lagged the number of trees planted by at least one year. We found that the number of trees planted in a tract was significantly associated with a higher tract-level median sales price, although it took at least six years for this relationship to emerge. Specifically, each tree was associated with a $131 (95% CI: $53–$210; p-value = 0.001) increase in tract-level median sales price six years after planting. The magnitude of the association between the number of trees planted and median sales price generally increased as the time lag lengthened. After twelve years, each tree was associated with a $265 (95% CI: $151–$379; p-value<0.001) increase in tract-level median sales price. Tree planting was not merely a proxy for existing tree cover, as the percent of a tract covered in tree canopy was independently associated with an increase in median sales price. Specifically, each 1-percentage point increase in tree-canopy cover was associated with a $882 (95% CI: $226–$1538; p-value = 0.008) increase in median sales price. In conclusion, tree planting is associated with neighborhood-level gentrification, although the magnitude of the association is modest.

The association between residential housing prices, bicycle infrastructure and ridership volumes

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.

Zoning – Neighborhood Character and Historic Overlays in Lexington, KY

Zoning has a significant impact on our built environment. Overlay zoning, an additional form of restrictive zoning, is a tool that municipalities utilize to control development. This study analyzes the impact that historic district (H-1) and neighborhood character (ND-1) overlays have on single family home sale price in Lexington, KY. Results suggest that overlays have a significant positive impact on home prices. Homes within overlays can expect to have a premium of between 18-27% over comparable homes not in overlay zones. Results also suggest that overlays exhibit spatial impacts that extend further than the homes included in the overlay.

Calibration and evaluation of Quigley's hybrid housing price model in Microsoft Excel.

Quigley derived his hybrid price model to improve the precision of predicted prices of sold homes by statistically merging data of resold homes in a repeat sales model with that of once-sold homes in a single sales hedonic price model. The literature has few applications of the hybrid model aside from those by Quigley and his collaborators. Two reasons for this underuse may be its computational intensiveness and its marginal empirical improvement in comparison with two other models. This paper first demystifies this computational intensiveness by calibrating models in Microsoft Excel with transferable procedures into other software. It second evaluates the hybrid price model’s empirical improvement as a reason for its underuse by predicting prices of 2,559 sold and resold homes observed in two inner-city neighbourhoods in Windsor, Ontario, during a 30-year period. The results as hypothesized are its lower standard errors of regression coefficients and higher simple R-squared than those of a single sales hedonic price model. Moreover, the hybrid model’s predictions have higher correlations than those of the single sales model with not only in-sample observed prices or changes in prices but also out-of-sample ones. The conclusion speculates in plans for future research about reasons for two models’ similar or dissimilar regression coefficients and standard errors predicting correspondingly similar or dissimilar sale prices of homes through time.

Zoning, density, and rising housing prices: A case study in Portland, Oregon

This study uses path analysis models to evaluate the associations between zoning, development density and the sales prices of new and existing single-family homes at the dwelling-unit level in Portland, Oregon. Development density is associated with the sales prices of single-family homes directly by determining land costs and indirectly by correlating with the size and construction costs of structures. A prominent trend in Portland’s and the nation’s real estate markets is that new single-family homes are getting bigger. Another trend is that single-family homes have been built on smaller lots despite their growing floor areas. Because developers tend to build smaller homes on smaller lots, the decline of lot sizes helps to contain the effect of growing home size on housing prices. However, the counter effect of smaller lot sizes is somewhat weak because home sizes have a stronger association with housing prices than lot sizes. Homebuyers in Portland are willing to pay a premium to live in neighbourhoods with higher densities, which further limits the potential of higher density development as a tool to reduce single-family home costs. In addition to its indirect associations with home prices via the determination of lot and home sizes, zoning exhibits a significant and direct association with the prices of existing single-family homes, but not with the sales prices of new single-family homes. Existing single-family homes in higher density zones tend to sell at lower prices, ceteris paribus, suggesting that the concern of future neighbourhood change prevails over the opportunity for redevelopment.

Urban trees, house price, and redevelopment pressure in Tampa, Florida

We examined the relationship between urban trees and the sales price of single-family homes in Tampa, Florida. We chose Tampa, because the city is facing major redevelopment pressure that may impact the association between trees and house price. In particular, a frequently voiced view in Tampa’s development community is that trees adversely affect the value of houses that are being sold for redevelopment. We estimated hedonic models of sales price controlling for house and neighborhood characteristics and correcting for spatial autocorrelation (n = 1,924). We found that trees within 152m (500 feet) of a house’s lot were significantly associated with higher sales prices. Specifically, a 1-percentage point increase in tree-canopy cover was associated with a total increase in sales price of $9,271 to $9,836 (results were largely insensitive to correction for spatial autocorrelation). Our results demonstrate that, even in a city facing major redevelopment pressure, trees are associated with higher sales prices.