Neighborhood Price Research Articles

Economic benefits of urban streetscapes: Analyzing the interrelationships between visual street environments and single-family property values in Seoul, Korea

Policymakers and planners often face questions about whether the creation of walkable environments can positively affect nearby housing prices. In response to this situation, numerous previous studies have examined the relationships between neighborhood-scale walkable environments and neighboring property values. However, it remains unknown if micro-scale visual streetscapes significantly affect nearby housing prices. This study builds upon prior literature by examining the economic effects of both neighborhood and streetscape walkability on single-family housing prices in Seoul, Korea. We use 14,686 housing sales transaction data between 2017 and 2019. In addition, this study utilizes a Deeplab V3+ deep learning model using 233,106 Google Street View (GSV) panoramic images to empirically identify micro-scale streetscapes. Based on such data, we employ a hedonic price model to examine the interrelationships between both macro- and micro-scale walkable environments and single-family housing prices. Our findings show that paved sidewalks on streets are associated with higher housing prices in disadvantaged neighborhoods, while street greenery and a sense of enclosure are positively correlated in advantaged areas. In particular, the sense of enclosure presents diminishing marginal effects. Our findings can help policymakers and planners establish detailed design strategies and guidelines for creating walkable environments that can maximize these economic benefits.

Foreign buyer taxes and housing affordability

AbstractTo improve housing affordability jurisdictions in different countries has introduced taxes on nonresident home buyers. We use the foreign buyer tax introduced in British Columbia, Canada, in August 2016 to investigate the extent to which such taxes improve housing affordability through their effect on local house prices. Our work uses direct transaction‐level identification of foreign buyers that resulted from policies prior to the announcement and subsequent introduction of the tax. Using a difference in differences methodology, we compare house price changes pre‐ and posttax between high and low foreign buyer concentration neighborhoods. We find that house prices decline by 6% in neighborhoods with above median concentrations of foreign buyers after the tax relative to prices in neighborhoods with below median concentrations of foreign buyers. The quantitative effects are also striking with overall foreign buyer share falling from 13.2% of single‐family transactions in the 6 weeks prior to the announcement of the tax to 1.7% for the 3 months following the tax. The unique contribution of this article is our use of transaction‐level data to explicitly identify the properties purchased by foreign buyers to create more accurate control and treatment groups than found in other analyses.

Understanding Accra’s housing market: an exploratory study using user-generated data

ABSTRACT Access to housing data in Ghana has been a challenge for researchers due to the lack of comprehensive data sources. However, the recent availability of big data sources has presented opportunities to bridge this data access gap. Using Greater Accra as a case, this study uses web scraping techniques to acquire publicly available housing data from two major E-commerce websites in Ghana and explores the Greater Accra Metropolitan Area’s (GAMA) prevailing housing market. Spatial autocorrelation statistics show clustering of high median prices in known high-class neighborhoods. Median prices in high-class neighborhoods were three to five times higher than median prices in the entire metropolis, highlighting high housing costs in high-class neighborhoods. This research highlights the high housing cost in GAMA, making it impossible for the average resident to afford to buy a house. Hence, a more inclusive housing strategy is needed to provide affordable housing options for all.

Analysis of the Effect of Infrastructure Development on Land Prices in Cinere and Beji Districts, Depok City

The surge in housing prices in cities has triggered the emergence of many problems related to urban settlements, starting from the construction of housing that is far from the city center, congestion problems, pollution, to encouraging the occurrence of many informal slum settlements. This causes a shift in settlements to supporting areas, especially Jabodetabek. Residential prices are dominantly influenced by high land prices. Infrastructure development has a major influence on economic growth and the development of an urban area. However, this is not easy to apply in the Depok City area, especially in the Cinere and Beji District areas. Housing development is very rapid but must be followed by the development of facilities and infrastructure. The purpose of this study was to analyze the influence of infrastructure development factors such as road network (accessibility), availability of facilities (transportation network, electricity network, telephone network, clean water network, educational facilities, health facilities) and residential neighborhoods based on the opinions of housing residents on land prices in residential neighborhoods in Depok City, especially in Cinere Dan Beji Districts. The research method used is research using a mixture of quantitative and qualitative methods in stages considering the complexity of the problem. Quantitative methods will be used to look at housing-related data as a basis, then to NJOP analysis as a basis for land prices. The results of this study indicate that in general, the data analysis shows compatibility with the literature that has been done, that land prices are very significantly influenced by the accessibility of the main highway network and the presence of commercial equipment to fulfill needs.

Spatial analysis of housing prices in Tehran city

PurposeThe purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).Design/methodology/approachIn terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.FindingsThe result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.Originality/valueThere is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

The Size and Spatial Extent of Neighborhood Price Impacts of Infill Development: Scale Matters?

Infill investments are argued to mitigate environmental footprints, regenerate places and accommodating population growth, but frequently generate local opposition. However, there is a dearth of knowledge around how different types of infill affect different segments of local property markets, how persistent effects are and how far they reach. Using detailed geocoded infill development activity and sales data, we test the price level and trajectory impacts of five infill types, distinguished by the net scale of additional dwellings, on property prices within five concentric 100-meter rings. Using an adjusted interrupted time-series estimation strategy with locality, property and neighborhood characteristic controls we find that developments that generate a net increase in dwellings of four or less, typically result in an appreciation in the average sales prices of proximate dwellings. Moderate and large-scale developments generate negative price effects, but these effects predominantly affect apartments and townhouses, not the dominant detached house submarket. Over time, amenity effects and local market potential may even have a further positive expectation effect on detached house prices. Infill type differentiation shows that urban densification may result in positive affordability outcome in the apartment submarket, but has the opposite effects in the detached house submarket. Divergent price trajectories also contribute to widening wealth disparities.

Strong, weak, or reversed: The spatial heterogeneities in the effects of squatter settlements on house prices

The proliferation of squatter settlements in many cities is an example of increasing social inequality and associated residential segregation. Squatter settlements are known to reduce house prices nearby, but we find that their effects are far from homogeneous in the city. To identify such varying effects, we used geographically weighted regression (GWR), which allows for the regression coefficients to vary over space. In the City of Buenos Aires, we found that the negative effect of the proximity to the squatter settlements is stronger in higher income neighborhoods while that in the lower income neighborhoods were weak or insignificant. We also found that a squatter settlement in a strategic area can be an opportunity to redevelop into a highly productive area, thereby raising the house prices nearby through speculation. These findings suggest that policies to improve a squatter settlement are not only in the interest of its residents, also but of the high-income households in the city. This improvement would not lead to a substantial rise in house prices in low-income neighborhoods that would otherwise worsen the housing affordability.

Disaster-Induced Displacement: Effects on Destination Housing Prices

Hurricane Katrina displaced more United States residents than any disaster since the Dust Bowl. Approximately 1 in 5 New Orleans residents relocated to Texas, moving from a majority Black city to places in which no group predominates. The arrival of Katrina survivors led to documented changes in local schools and labor markets; the Katrina diaspora’s effect on housing markets, however, remains understudied. What effect should we expect? In-migration constitutes an increase in demand, pushing prices up—but existing residents may have a preference for segregation, leading them to decrease their own demand for affected neighborhoods. In this paper, we assess the effect of large flows of Katrina survivors from New Orleans on housing prices in Texas neighborhoods. Recognizing that associations could reflect selection on the part of survivors, who might be attracted to neighborhoods with declining prices, we construct an instrument for survivor in-flows using the destinations of pre-Katrina movers. We find that neighborhoods with larger inflows of survivors see slower house price growth, even after controlling for neighborhood characteristics and differences between cities. The house price effect is persistent: five years after Hurricane Katrina, we estimate that the neighborhoods receiving the largest in-flows of displaced people saw approximately 7.5% lower housing price growth in comparison with similar neighborhoods where no survivors relocated. Finally, we show that effects are concentrated in places that received economically disadvantaged movers or movers from predominantly Black neighborhoods of New Orleans. Altogether, these findings are consistent with the hypothesis that existing residents have a demand for segregation vis-a-vis Katrina survivors. As climate change makes large disaster-induced population flows increasingly common, there is a critical need for further research on how to ameliorate the costs of these large relocations, both for the individuals who must relocate and for the places in which they resettle.

Multiple Reference Points and Length of Ownership in the Housing Market

Reference-dependent utility has been shown to have a significant influence on housing market activity. Sellers facing a nominal loss on their home due to market conditions, tend to inflate the asking price and thus the transaction price of their home, indicative of loss aversion. However, the original purchase price of a home may lose influence as a reference-point as the period of ownership increases, while homeowners rely increasingly on other benchmarks such as neighboring homes’ sales prices as reference points. In other words, a homeowner may have multiple reference points in their underlying utility function, whose relative influences shift in importance over time. We use comprehensive administrative data on residential real estate transactions in Singapore’s private housing market to test the influences of original purchase price and recent neighborhood price as reference points over the length of homeownership. Purchase price and neighborhood price are each valid reference points based on established empirical methods in the behavioral and housing economics literature. By testing for their relative influences as a function of length of ownership, we find that prior purchase price is more influential for the first years of ownership, while neighborhood price becomes more influential during the subsequent holding years. Finally, we provide a theoretical framework for understanding the relative influences of multiple reference points over time, which supports the empirical findings.

Asset price dynamics in a “bull and bear market”

We generalize an existing asset market model with heterogenous agents. In particular, we consider the case in which no-trade and low-trade intervals of chartists and fundamentalists respectively are not congruent. Thus we model chartist and fundamentalists who respond to asset prices in agent-specific neighborhoods around the fundamental value with different trade intensities. The resulting asset price dynamics is generated by a one-dimensional 5-piece linear map with discontinuities. Our analysis of this map focusses on coexisting price equilibria. Conditions for their existence and stability are determined analytically. By visualizing the results we allow for a basic bifurcation analysis in a 4-dimensional parameter space. According to our findings the extent of the disparity between the no-trade and low-intervals effects the existence of equilibria but not their stability.

Determinants of a foreclosure discount

This study adds to previous research analyzing the impact of foreclosure status on real estate sales price by using a Swedish dataset were an appraiser has estimated the market value of apartments before they were sold at foreclosure auction. Appraisal data can address the issue of selection bias and a potential overestimation of foreclosure related discount. A mean discount of 7.9% with a corresponding median value of 9.5% is shown when comparing appraisal estimates with prices achieved at foreclosure auction. A hedonic model is also applied, and the resulting discount is estimated at 23.9%. Measures of local market conditions are related to the foreclosure discount, with hedonic price models and models using appraisal data producing consistent results. It is found that the discount is higher in lower priced neighborhoods, in neighborhoods that are heterogeneous in terms of price and in less liquid neighborhoods (significant in the hedonic model). It is also found that apartments with a higher value relative to the neighborhood price level sell at larger discounts. The results are consistent with studies on search and matching theory and contrast from earlier studies that attribute a foreclosure discount to seller motivational factors.

Retail Marijuana Deregulation and Housing Prices

Despite federal law, twelve American states and Washington D.C. have legalized recreational marijuana since 2012. Using a national housing data set from the online real estate listing database Zillow.com, we identify the cross and inter-state effects of marijuana legalization on house prices in different points of the price distribution function. We find positive effects upwards of ten percent in the top half of the price distribution following successful legalization ballot initiatives, and between five and fifteen percent across the distribution after the state enacts the ballot initiative and the first legal sales take place. A spatial difference-in-differences model reveals that within Colorado and Washington, prices in neighborhoods with new dispensary openings nearby experience a seven percent price appreciation. To summarize, our results suggest that there are second order benefits to marijuana legalization.

Housing appreciation patterns in low-income neighborhoods: Exploring gentrification in Chicago

Using data from Chicago, this paper analyzes different housing appreciation patterns from 1983 to 2005 depending on the initial level of income of the neighborhoods where these properties are located. Findings suggest that appreciation patterns of low-income neighborhoods are different than those of high-income neighborhoods. Moreover, appreciation of housing prices in low-income neighborhoods that have experienced gentrification is different than in other low-income neighborhoods not gentrified. To analyze this issue further, we compare the behavior of housing prices in neighborhoods experiencing different stages of gentrification with housing prices in low-income neighborhoods that have not been gentrified. Housing price appreciation is only observed in neighborhoods gentrified that had low levels of income when gentrification was measured. One interpretation of these findings is that housing prices appreciate in neighborhoods experiencing early stages of gentrification, but not in neighborhoods that have been gentrified for longer periods of time. These results could suggest that gentrification may cause displacement pressures in the early stages, but prices are stabilized in neighborhoods being gentrified for some time, reducing the probability of displacement of the low-income population.

Local Banks, Credit Supply, and House Prices

I study the e?ects of an increase in the supply of local mortgage credit on local house prices and employment by exploiting a natural experiment from Switzerland. Losses in U.S. security holdings triggered a migration of dissatis?ed retail customers from a large, universal bank (UBS) to homogenous local mortgage lenders in mid-2008. Mortgage lenders close to UBS branches experience larger in?ows of deposits, unrelated to their investment opportunities. Using variation in the geographic distance between UBS branches and local mortgage lenders as an instrument for deposit growth, I ?nd that banks with an exogenous positive funding shock invest in strict accordance with their specialization (i.e. local mortgage lending). Consequently, house prices in neighborhoods around a?ected banks rise over 50% more than around una?ected banks. I also ?nd an increase in the number of employees at small ?rms, reliant on real estate collateral, in these neighborhoods. My results show that local mortgage oriented banks a?ect house prices through the supply of credit and that bank specialization thereby plays an important role in the allocation of capital across sectors.

Neighborhood Variation in the Price of Cheap Tobacco Products in California: Results From Healthy Stores for a Healthy Community.

Retail marketing surveillance research highlights concerns about lower priced cigarettes in neighborhoods with a higher proportion of racial/ethnic minorities but focuses almost exclusively on premium brands. To remedy this gap in the literature, the current study examines neighborhood variation in prices for the cheapest cigarettes and a popular brand of cigarillos in a large statewide sample of licensed tobacco retailers in a low-tax state. All 61 local health departments in California trained data collectors to conduct observations in a census of eligible licensed tobacco retailers in randomly selected zip codes (n = 7393 stores, completion rate=91%). Data were collected in 2013, when California had a low and stagnant tobacco tax. Two prices were requested: the cheapest cigarette pack regardless of brand and a single, flavored Swisher Sweets cigarillo. Multilevel models (stores clustered in tracts) examined prices (before sales tax) as a function of neighborhood race/ethnicity and proportion of school-age youth (aged 5-17). Models adjusted for store type and median household income. Approximately 84% of stores sold cigarettes for less than $5 and a Swisher Sweets cigarillo was available for less than $1 in 74% of stores that sold the brand. The cheapest cigarettes cost even less in neighborhoods with a higher proportion of school-age residents and Asian/Pacific Islanders. Neighborhood disparities in the price of the cheapest combustible tobacco products are a public health threat. Policy changes that make all tobacco products, especially combustible products, less available and more costly may reduce disparities in their use and protect public health. Much of what is known about neighborhood variation in the price of combustible tobacco products focuses on premium brand cigarettes. The current study extends this literature in two ways, by studying prices for the cheapest cigarette pack regardless of brand and a popular brand of flavored cigarillos and by reporting data from the largest statewide sample of licensed tobacco retailers. Significantly lower prices in neighborhoods with a higher proportion of youth and of racial/ethnic groups with higher smoking prevalence are a cause of concern. The study results underscore the need for policies that reduce availability and increase price of combustible tobacco products, particularly in states with low, stagnant tobacco taxes.

Unintended Consequences of Risk Based Pricing: Racial Differences in Mortgage Costs

The following analysis focuses on the role that risk pricing has had in the allocation and access to mortgage funds, specifically how it results in cost differences by race. Using a sample of fixed-rate first lien mortgages, we control for the risk characteristics of borrowers and assets. We find that borrowers with comparable credit quality experience significantly higher costs for mortgages in neighborhoods with a high density of minority households. Further, when the pricing differential is controlled for in a model of mortgage default, there is no support for neighborhood price differences. This finding illustrates a potential inequity that results from efficient/risk pricing in mortgage underwriting.

Foreclosed and Sold: An Examination of Community and Property Characteristics Related to the Sale of REO Properties

Foreclosure affects not only the foreclosing homeowner but also the surrounding residential neighborhood. Prior work has found that the negative neighborhood impacts of foreclosed properties that remain as real-estate-owned (REO) properties persist until the property is resold. Furthermore, negative neighborhood price externalities are more substantial the longer a home spends in REO stock. This article used foreclosure data from Dallas County, Texas, to examine how both housing and neighborhood characteristics are related to the possibility of the sale of a foreclosed property out of REO stock. The findings from the Cox proportional hazard model indicate that homes in low-income minority neighborhoods and homes with property characteristics associated with a need for more preventative maintenance were slower to sell. Results have the potential to provide insight into how housing and neighborhood characteristics might help to explain part of the uneven geographic distribution of foreclosure impacts following the 2007–2009 financial recession.

Neighborhood price externalities of foreclosure rehabilitation: an examination of the Neighborhood Stabilization Program

The federally funded, HUD-administered Neighborhood Stabilization Program (NSP) was enacted in the wake of the financial recession to mitigate the underlying adverse neighborhood effects associated with foreclosed properties. We examined the neighborhood price impacts of NSP-funded foreclosure rehabilitation undertaken by Habitat for Humanity in Dallas County, Texas, using a difference-in-difference framework. Foreclosure rehabilitation projects in Dallas County produced an average 15% increase in neighborhood home prices that sold up to 30 months after the rehabilitated property sale and within 0.1 miles of the rehabilitated property. Foreclosure rehabilitation that involved significant exterior repairs was associated with the largest estimated effect sizes. Results suggest that NSP funding in Dallas County effectively targeted homes that had the potential to have the most severe neighborhood impacts and that rehabilitation was an effective means of reversing neighborhood price externalities associated with blighted foreclosed properties.

Why Are Foreclosures Contagious?

AbstractThis article investigates the mechanism by which foreclosed properties depress neighboring property prices. Using a novel dataset on housing capital expenditure, I verify as accurate the claim of disinvestment theory made in earlier studies. When capital expenditure investment, neighborhood price trends, number of Multiple Listing Service listings and neighborhood fixed effects are controlled for, the negative effect on property prices is significant from nearby foreclosures, real estate owned (REO) listings and REO sales, but not from default and delinquent properties. The effect is larger in a depressed market than in an appreciating market. I argue that the most plausible explanation for these results is that a foreclosure discount drives down the reference prices for nearby properties and depresses neighborhood values. This discount information is revealed to the public through foreclosures, REO listings and REO sales.

The impact of urban renewal on neighborhood housing prices in Taipei: an application of the difference-in-difference method

This study examined the impact of urban renewal delineation time on housing prices in neighborhoods undergoing urban renewal. More specifically, the study used the difference-in-difference method to assess successful housing transactions in Taipei City from 2008 to 2011. According to the empirical results, before the implementation of urban renewal, the average housing price in the areas that later underwent urban renewal (the treatment group) was lower than that in neighborhoods that did not undergo urban renewal (the control group) by 11,180 NTD. After the urban renewal projects were publicly announced, the price per ping of the control group was increased by 148,800 NTD, while the price per ping of the treatment group was increased by 163,680 NTD. This means that the housing prices per ping in the urban renewal areas were increased by 14,880 NTD more than the housing prices per ping in the areas not affected by urban renewal after the urban renewal projects were publicly announced. This increase, then, indicates the value added after implementation of urban renewal delineation time on houses in the neighborhood. Therefore, research into the impact of urban renewal on housing prices should be concerned not only with the neighborhood factors or time factors of urban renewal delineation. Rather, the two types of factors should be considered at the same time.