Residential Property Values Research Articles

The Impact of Transportation and Walkability on Residential Property Value

In order to determine the impact of transportation and walkability as one of the important smart growth principles in creating economic value, this study examines the impact of transportation and walkability on Residential Property Value in Shah Alam, Selangor, Malaysia neighborhoods. Based on secondary data collected on Brickz.com, a hedonic regression model was constructed to estimate median Residential Property Value in Shah Alam, Selangor for the Residential Property Value assessment. The model's findings demonstrate that transportation and walkability factors have less impact on estimated Residential Property Value than other residential structure characteristics such as number of floors, number of bedrooms, and land area. Only three variables from the Structure Characteristic were statistically significant in this study: Structure Characteristic no of the floor, Structure Characteristic No of the Bedroom and Structure Characteristic Land Area. Consequently, all transportation and walkability are insignificant towards residential house prices. This shows that there are still ways to increase house prices through attractive house structure planning. With this, the formation of an attractive house structure in development planning is an important aspect in increasing the demand for house prices while rising house prices efficiently. The adoption of the appropriate use of public transport uses the principle of good growth to achieve added value and improve the overall quality of life in the neighborhood.

Individual property tax to fund public transport

Efficient and reliable public transport is of prime concern to city dwellers. To function efficiently, public transport generally needs subsidies from the state or local government. Our goal was to design and develop an alternative model of property tax that would provide financing for public transport. It was hypothesised that if the market value of real estate depends on the proximity of public transport, property tax can be a reliable source of financing for public transport. Based on the hedonic pricing theory, we used multiple regression to measure the impact of public transport proximity on the value of residential property. The data on the market value of property and property tax was taken from statistical tax reporting forms of the Federal Tax Service. The data on various public transport infrastructure facilities was used from the specialized open registers. We tested our alternative model of property tax, using the case of the Ekaterinburg Metro and the Tram and Trolleybus Company, through regression analysis of 7,685 objects of residential property in the City of Ekaterinburg. It was found that the efficiency of the underground service is higher than that of the city’s tram network. On the average, the proximity of underground stations increases the value of housing by over 6%. As predictive estimation of the amount of tax determined by the proximity of public transport showed, the alternative model of property tax is sufficient to cover capital expenditures of the city’s public transport operators and could, therefore, contribute to further expansion and modernization of the transport network.

On the Impact of Infrastructure Improvement on Real Estate Property Values: Evidence from a Quasi-natural Experiment in an Emerging Market

Prior studies show infrastructural improvements impact property values positively. The effect is often reflected soon after the announcement and continues until the project is complete. These studies, however, are primarily set in developed countries. Emerging markets pose unique risks where uncertainty around implementation and funding could dampen these positive effects significantly. We utilize a quasi-natural experiment around an inner-city road redesign and improvement project in Bangalore, the fastest growing city in India. We exploit the difference-in-difference regression approach to examine the project’s impact on residential and commercial property values around two sets of geographically proximate roads, one of which was chosen for the redesign. Unlike in developed countries, we find that property values are unaffected by the announcement when uncertainty is the highest but start reflecting the positive value of the infrastructure once construction starts and show significant gains upon completion. Our findings carry important policy implications for structuring value capture strategies in emerging markets.

Air Pollution and Negative Housing Premium in Korea: Incorporating Transboundary Pollution Spillovers from China

In this study, we estimate the degree and scope of PM2.5-induced negative price shock in Korea’s local housing markets, taking a 2SLS hedonic approach. For the analysis, we constructed a 5-year panel data set of Korea’s 110 city and county level municipalities between 2012 and 2016, and instrumented inverse distance-weighted, wind direction-aligned PM2.5 levels in 260 Chinese prefecture-level cities to consider the long-range transport of air pollutants. We find a PM2.5 elasticity of housing price of -0.36 for the period analyzed, suggesting that, on average, a 1% PM2.5 level increase in a Korean city or county is associated with a 0.36% decline in local residential property value. Transboundary pollution has significant effects on Korea’s local PM2.5 levels, showing an elasticity of 0.05—a unit % increase in PM2.5 levels in China’s major cities exacerbates Korea’s PM pollution by 0.05%, accounting for a comparable share of the PM-caused negative housing premium. Compared to the national average, PM2.5 elasticity with respect to housing price is 22–25% higher in Seoul and its vicinity, which is more vulnerable to transboundary pollution than the rest of Korea.

Race matters (even more than you already think): Racism, housing, and the limits of The Color of Law

ABSTRACT As any good American urbanist knows: race matters. But precisely how does it matter? How have the pervasive and enduring modalities of racism (especially anti-Blackness) shaped the American metropolis over the last decades? Several influential attempts to answer these questions have focused heavily on racism’s momentous impacts on housing and related spatial practices. Such accounts have garnered intensified attention with the appearance of Richard Rothstein’s widely heralded The Color of Law. My central contention is that most conventional treatments of how racism impacted mid-century housing and spatial practices (including Rothstein’s) are deeply flawed. While almost obsessively centering racism as determinative, they nevertheless underestimate how fundamental it is to America’s institutions. I focus particularly on market institutions as they shape residential property values. Doing so reveals both a significant historical rereading of mid-century urban America’s highly racialized housing and spatial practices, as well as a more powerful account of ongoing racial dispossessions.

Characterising percentage energy from ultra-processed foods by participant demographics, diet quality and diet cost: findings from the Seattle Obesity Study (SOS) III.

Higher consumption of 'ultra-processed' (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016-2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.

Does concentration of social housing influence house prices? Evidence from New Zealand

PurposeHousing affordability in New Zealand is placing significant pressure on the country’s social housing sector with increased demand for public sector accommodation. A common belief suggests that social housing has a negative effect on nearby residential property values. This study aims to develop proximity and concentration measures of social housing to determine if their spatial distribution affects property values.Design/methodology/approachUsing over 32,000 residential sales transactions from Auckland (New Zealand) during a three-year period (2014–2016), this study applies standard hedonic OLS framework with the addition of spatial autoregressive model and spatiotemporal autoregressive model to test if proximity and concentration of social housing influence residential property values.FindingsThe research found that private houses that share boundaries with public housing are discounted by 1.7%–3.3% depending on the socio-economic status of the submarket. The authors find that wealthier submarkets are better equipped to absorbing negative externalities attached to social housing. Proximity measures tend to peak at 250 m, with houses discounted up to 5% within that distance. Concentration levels of social housing had a greater influence on the private residential market. At low levels of concentration, houses in areas of high and low socio-economic levels were discounted by approximately 6.5%. The discount does not remain uniform and the gap between the two areas is apparent at medium and high concentration levels. The negative effect was the highest − 23% – in the neighbourhoods that were socially and economically deprived.Originality/valueThe study’s findings can assist policymakers in informing strategies on the future social housing initiatives. The findings suggest that a dispersed development strategy that incorporates a balanced mix of tenure and socio-economic groups should be preferred over a high-density social housing concentrated in already deprived neighbourhoods.

Identification and analysis of urban Shrinkage risk based on residential property values

With the adjustment of the economic structures and the slowdown of development, urban shrinkage has become a common phenomenon, especially in developed countries. In contrast, for developing cities, there is a special phenomenon of urban shrinkage, that is, border expansion and space shrinkage coexist. In view of this situation, it is difficult to effectively identify the signs and trends of urban degradation and space shrinkage by only studying the macro scale of urban space. The purpose of this paper is to build an evaluation model of urban space shrinkage risk, which can be run for the whole process of urban space development. It can also be applied to diverse scales of urban space and identify the mechanism of the transformation and diffusion of the space shrinkage risk on the time scale and the space scale. This study took Jinan City in China, a typical second-tier city, as a sample of urban shrinkage and took the urban residential property values as the key index to evaluate the shrinkage risk. The results show the risk of urban space shrinkage on the micro-scale. This paper analyzes the transfer and spillover effects of the urban space shrinkage risk by using Moran's spatial correlation tools and transfers this micro space shrinkage risk to the macro level to analyze the characteristics and trends of the typical urban shrinkage in China from the macro level. According to the Moran’s Index, the urban space was divided into four types: collapsed areas, emerging areas, blocking areas, and revitalized areas. Based on this classification, the back-propagation neural network and decision making trial and evaluation laboratory (BP-DEMATEL) model was used to analyze the influencing factors for each spatial type. It measured the degree of cause and centrality of each influencing factor and identified the contribution and function of the influencing factors of the spatial risk for the whole urban spatial system. It identified the basic, characteristic factors of the shrinkage risk for each type of urban space and analyzed the core reasons for the shrinkage risk of various types of urban space. The main conclusion of this paper is that the sparse distributions of the economic and population densities will lead to the fracturing and isolation of the urban space and increase the risk of urban space shrinkage. The shrinkage risk of the urban interior space presents different modes and driving mechanisms.

Valuation Modeling within Thin Housing Markets Case Study: Arab Housing Market in Israel

The primary aim of this paper is to introduce valuation modeling applicable to thin housing markets, with a focus on the Arab housing sector in Israel. The estimation procedure utilizes two input values: transaction data and subjective valuations provided by property owners, the data for which are derived from the Israel Tax Authority (ITA) and the Household Expenditure Survey (HES). Average property values are also weighted and ranked according to location, size, and average income factors. The main contribution of these modeling techniques is that they can be employed to estimate the residential property values in markets that experience a low frequency of housing transactions and where information is limited, with the added benefit of understanding housing value movement and market dynamics. Housing policies could be influenced by this deeper understanding of house price behavior within localities and submarkets, potentially with the ability to monitor changes in dwelling values and segmentation and segregation effects.

Problems of modeling the valuation of residential properties

The solution of the housing problem for many decades has been and remains one of the most important tasks facing the nation.. The problem of modeling the value of residential properties is becoming more and more urgent, since a high-quality forecast makes it possible to reduce risks, both for government bodies and for realtors specializing in the purchase and sale of residential properties, as well as for ordinary citizens who buy or sell apartments. Predictive models allow us to get an adequate assessment of both the current and future situation on the residential property market, to identify trends in the cost of housing and the factors influencing these changes. This involves both the qualitative characteristics of the particular property, and the general condition and the dynamics of the real estate market. Russia is characterized by significant differences in the level of development of regions, therefore, by differences in trends of supply and demand prices for real estate. Valuation of residential properties at the regional level is particularly important, since all of the above determines the social and economic importance of this problem. This article presents a comprehensive model for estimating the value of residential properties in the secondary housing market of Moscow using decision tree methods and ordinal logistic regression. A predictive model of the level of housing comfort was built using the CRT decision tree method. The results of this forecast are used as input information for an ordinal logistic regression model for estimating the value of residential properties in the secondary market of Moscow. Testing the model on real data showed the high predictive ability of the model we generated.

Correlation between Environmental Variables and Rental Values of Residential Properties in Greater Port Harcourt City, Rivers State, Nigeria

Property value is a function of many factors. It is a common knowledge that environmental variables and the influence of location externalities are vital to the formation of residential property value. The study assesses the relationship between environmental variables and rental value of residential properties in Greater Port Harcourt City, Rivers State. Data was collected from both primary and secondary sources. In a wider perspective, data was collected through questionnaires, interviews, document reviews and field observations. A total of 450 out of 500 copies of questionnaires administered to the residents was retrieved while 78 was retrieved out of 116 copies of questionnaires administered to the Professional Estate Valuers managing residential properties within the study area. Questionnaire was distributed on the basis of household population in the study area and stratified systematic sampling approach was adopted in the selection of 500 (residents) respondents. Data analysis techniques used include mean, standard deviation and spearman rank correlation. Three research questions were formulated and one hypothesis tested at 0.01 and 0.05 level of significance. Findings revealed that there is a relationship between environmental variables and rental value of residential properties. Secondly, the study showed environmental variables that negatively influence residential property value include floodwater, air pollution, waste dumpsite, traffic congestion, noise pollution and wetland in the study area. Based on the findings, recommendations were made among which is the need for the creation of awareness and public sensitization on environmental issues with potential adverse effect on property values and living standard was also recommended. Essentially, the study will be beneficial to students, property developers, local planning authorities of Rivers State in regulating development and housing for the infrastructural development in the State.

The effect of farmers’ market access on residential property values

Improving farmers' market accessibility is increasingly being used as a mechanism to promote healthy food consumption. Previous studies about farmers’ markets largely focused on describing either the demographics of market patrons or the impact of market participation on fruit and vegetable intake. Thus, little empirical research has examined how market accessibility impacts nearby communities.The goal of this study is to assess whether consumers value farmers' market accessibility by exploiting preferences revealed through housing purchases. Using residential sales data from 2007 to 2012 in five Central Maryland counties, we tested whether farmers' market accessibility is associated with housing prices by estimating hedonic models with temporal and neighborhood fixed effects. The results suggest an inverse association between housing prices and distance to the closest farmers’ market, a relationship that remains statistically significant when using matching and instrumental variables estimators. The results also suggest that the association between market accessibility and housing prices is stronger in areas with poor-quality food environments.The findings are important to policy makers and planners because they suggest that farmers' market accessibility is valued by consumers in nearby communities and that consumers with limited access to food stores are willing to pay a premium for houses with access to farmers’ markets. Assessing the mechanisms driving this association is an important area for future research.

Eco-gentrification and who benefits from urban green amenities: NYC’s high Line

This study estimates the impact of the introduction of New York’s High Line, an elevated walkway in Manhattan by relating the increase in housing values to the issue of eco-gentrification in urban areas. Studies have shown that increasing the amount of green space can lead to gentrification: rising property values, displacement of existing residents, and a large in-migration of wealthy populations. We utilize Geographic Information Systems (GIS) to spatially model the effects of the High Line on residential property values. We exploit spatial and temporal differences of the High Line’s opening to estimate its impact on residential home values. We find that homes closest to the High Line experienced a 35.3% increase in housing values. We estimate the driving force behind this premium by using a triple difference approach by analyzing elevation levels and find that homes with relatively the same height as the High Line receive the largest premium. This study serves to inform policy makers regarding potential inequality of green space provisions. We provide policy recommendations for minimizing the housing price impact of green space creation.

Impacts of mining on property values in Kalgoorlie-Boulder, Western Australia

Mining activities have a positive impact on local communities through providing formal employment opportunities in the local area. However, the air and noise pollution associated with surface mining represent a negative externality for residents in communities near mining activity. To support urban planning processes, accurate information on both the positive and negative impacts of surface mining is required. In this study, we estimate the dis-amenity of proximity to a large open-pit gold mine in Kalgoorlie, Western Australia, that has been capitalised into residential property values. To estimate the impact of proximity to the mine on property values, we use sales data for 21,850 residential properties sold in Kalgoorlie-Boulder between 1990 and 2018. We use distance to the mine as a measure of the impact. We control for spatial heterogeneity using spatial fixed effects. We found that residential properties located within two kilometres of the mine trade at a 20% to 30% discount to similar residential properties located at least six to seven kilometres from the mine. Our results can be used for planning appropriate buffer zones around mining activities.

Retail and Place Attractiveness: The Effects of Big‐Box Entry on Property Values

The opponents of big‐box entry argue that large retail establishments generate a variety of negative externalities. The advocates, on the contrary, argue that access to a large retail market not only delivers direct economic benefits, but also a variety of positive spill‐over effects, and therefore, can be considered a consumer amenity that increases the attractiveness of the entry location. To test the validity of these competing arguments, we use the entry of IKEA in Sweden as a quasi‐experiment and investigate if increased access to retail is associated with place attractiveness, where attractiveness is proxied by residential property values. We find that entry by IKEA increases prices of the properties sold in the entry cities by, on average, 4.2% or 62,980 SEK (approximately 6,600 USD), but such an effect is statistically insignificant for the properties in the immediate vicinity of the new IKEA retail trade area. We also observe an attenuation of the effect with distance from the new IKEA store, where the properties located 10 km away experience a 2% price increase. Our results indicate that large retailers have the potential to increase place attractiveness, but perhaps not in the immediate vicinity of the new establishment.

The Influence of Canopy Cover on Property Values in a Small Southern US City

Urban forests have been shown to impact residential property values in the United States and other countries. This study demonstrates a hedonic pricing analysis estimating the impact of urban forest canopy cover on single-family residential property values using Lakeland, Tennessee, during the period of 2001 to 2005 as a typical study area for the southern United States. Canopy cover on the lot was not a significant contributor to property values. However, a 1.0% increase in canopy within buffers of 100 m, 500 m, and 1 km surrounding the lot was associated with a 0.12%, 0.17%, and 0.21% increase in home sales prices, respectively. Although the percentage increases were small, given the price of a home in areas like these, the dollar values were high. These results can be used to assist urban planners and policy makers in prioritizing forested lands for conservation and to evaluate economic effects of urban forestry policies and programs.

Bottom-Up or Top-Down Local Service Delivery? Assessing the Impacts of Special Districts as Community Governance Model

This article assesses the impacts of bottom-up local governing institutions relative to top-down bureaucracies in local service delivery. Community services districts (CSDs) in California, a class of special districts that provides various neighborhood-level services, are examined to answer this question. An innovative characteristic of this institutional form is that it is residents who create them through a grass-root collective action to achieve a bottom-up governance structure, after opting out from a county service system. With changes in residential property values as performance metrics, the quantitative analysis utilizes district formation events and features a hedonic difference-in-difference regression. The results show that the creation of CSDs produces more significant impacts on property values than county authorities do. Yet, the effects are heterogeneous across the communities when the analysis is further drilled down to each district. The exploratory qualitative case study then uses interview data with district managers and document analysis to unveil what administrative factors explain the success and failure trajectory of bottom-up institution management. The case study identifies such factors as critical codeterminants, including managerial and board leadership, clarity of a problem statement, public support, and intergovernmental coordination with county and state agencies.

Exploring Spatial Pattern of Residential Property Value around Cultural Heritage Sites in Ile-Ife, Nigeria

Cities in both developed and developing economies are characterised by various cultural heritage sites. Such sites can impact the value of residential properties around them either positively or negatively. In view of this, this study explores the spatial pattern of residential property values around cultural heritage sites in Ile-Ife, Nigeria. One (1) cultural heritage site each was purposively selected in the core and sub-urban areas of Ile-Ife. Furthermore, systematic sampling technique was used to select one of every twenty (20) buildings within different radii (1-300, 301-600 and 601-900 meters) of the selected cultural heritage sites. A total of two hundred and twenty-three (223) buildings were selected. Hence, 223 questionnaires were administered on the residents of the buildings. Interview was also conducted on ten (10) real estate practitioners in the study area to optimally provide answers rental values of residential properties around the cultural heritage sites. The extracted data were analysed using multiple regression and rent differential technique. Findings showed that as distance increases from the cultural heritage sites, the average rental value of residential properties was also on the increase in the core and sub-urban areas of Ile-Ife. It was therefore established that there exists a positive relationship between the distance from cultural heritage sites and rental values of residential properties. The study further revealed that cultural heritage sites had a negative impact on the rental values of proximate residential properties in the study area. The study however concluded that the rental values of residential properties reflect distance to cultural heritage sites. It is recommended that property investors should give adequate attention to location to make accurate and dependable decisions on the supply of residential properties, especially in cities where there are cultural heritage sites.

Factors Influencing Rental and Capital Values of Residential Investment Property in Abuja, Nigeria

There are various purposes the rental or capital values of residential investment property could be sought. However, most previous studies on factors influencing value of residential investment property are expressed in a general term; not specifically indicating whether rental or capital value. This may mislead investors in making the wrong investment decision. Using aggregation and disaggregation approach, this study examined the general and specific factors determining the rental and capital values of residential investment property in Abuja, Nigeria with a view to providing information that could guide the investment decisions. With the use of a structured questionnaire, cross sectional survey was adopted to obtain the perceptual opinion from 136 estate surveying and valuation firms in the study area. Data was analyzed with descriptive statistics of Relative Important Index (RII). The findings reveal a variation in the outcome of general factors and specific factors and that in specific term, factors influencing the capital value are significantly more in quantity and rating than the ones influencing the rental value. Out of the 23 (13 for rental and 10 for capital value) general determining factors, 11 (3 for rental and 8 for capital value) are actually significant. Average number of rooms; change in maintenance cost/taxes and the neighbourhood characteristics mainly influence the rental value of residential property while cost of construction; type of structure/quality of facilities; potential of rental growth; title and size of the land; neighbourhood attributes; inflation impact; size and structural characteristics and state of supply in property market are the main factors influencing the capital value. This noted variation is an indication for property investment stakeholders to be cautious and specific in the selection of the most appropriate determining factors for their investment objective to avoid investment decision errors.

The housing market impacts of human activities in public spaces: The case of the square dancing

Square dancing is a popular public activity performed in squares and parks in Chinese cities. Although dancers benefit from such activity physically and mentally, nearby residents may suffer from noise pollution and other negative externalities. However, only a few existing studies have explored the effects of square dancing on the value of residential properties and open spaces. To fill this knowledge gap, this study utilizes the hedonic price model and spatial econometric model to investigate the external effects of square dancing in the housing market of Hangzhou, China. Results show that nearby housing price drops by 5.8 % and 13.0 % when people dance in the nearest park and square. In addition, square dancing decreases the value of parks and squares, and this mediating effect shows spatial heterogeneity (e.g., the premium of living in the segments of 0–200 m and 200 m – 1 km from parks decreases from 0.231 to 0.047 and from 0.126 to 0.045, respectively; the premium of living in the segments of 0–800 m, 800 m – 1.5 km, and 1.5–3 km from squares decreases from 0.157 to 0.060, from 0.165 to 0.022, and from 0.166 to 0.033, respectively). The results of this study indicate that square dancing has a significant negative external effect on housing price and the value of open space. This study offers implications for policy makers to achieve a harmonious society and humanized urban planning. The findings and implications of this study ensure the benefits of residents and improve the value of residential properties and open spaces. In addition, the findings can be generalized across cities or countries where square dancing and other human activities (e.g., night market) are popular.