Hedonic House Price Model Research Articles

Evaluating objective and perceived ecosystem service in urban context: An indirect method based on housing market

Ecosystem service (ES) evaluation is usually based on the stocks of natural resources and their functions. However, the value of ES in the urban area depends on human activities more than the existence of natural resources. This research implements an indirect market method by integrating hedonic housing price model to assess ES in urban context from both objective (remote sensing) and subjective perspectives (street view image). Machine learning tools are employed to investigate the impacts of objective and perceived ES on housing prices based on a case study in Wuxi, China. The analytical results suggest that the contribution of ES to house prices in Wuxi ranges from 0% to 10.85%. Further investigation found that visible trees are the most important ES factor of housing price, more important than the coverage of green space. We also find that the quality of blue-green spaces might modify the value of ES, while the poor landscape design and water pollution in the central urban area made the values of ES low in the housing market. This study proves that the indirect method based on the housing market is helpful in valuing ES in the urban context. The high importance of perceived blue-green spaces in ES encourages more efforts on landscape design rather than only increasing coverage.

Does better accessibility always mean higher house prices?

Numerous studies have explored the correlations between house prices and spatial accessibility, but few have delved into the nonlinearities between both. This study uses Cardiff (UK) as a case study and applies interpretable machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), to estimate the nonlinear effects of geometric locational accessibility and street network accessibility on house prices. The findings suggest (1) proximity to the CBD, typically the major determinant of land values in hedonic house price models, does not continuously yield higher prices; (2) street closeness centrality, a network-modelling approach to measuring accessibility, exhibits a more generalised pattern with house prices compared proximity to the CBD regardless of analytical spatial scales. The findings challenge the generalizability of Alonso’s bid-rent theory in accurately portraying the relationship between accessibility and house prices in specific urban contexts, highlighting the importance of re-evaluating classical urban theories in different city contexts using novel measures and modelling techniques.

Improving hedonic housing price models by integrating optimal accessibility indices into regression and random forest analyses

Improving hedonic housing price models by integrating optimal accessibility indices into regression and random forest analyses

Spatial-temporal patterns of summer urban islands and their economic implications in Beijing.

Urban heat island (UHI) has a great influence on human wellbeing in urban areas. Previous studies have investigated impact on environment, ecosystem, and human health of UHI. To investigateeconomic impact of UHI is a lack of research. In this study, spatial-econometric hedonic housing price models are developed for estimating the marginal value of summer UHI in Beijing, China. The results showed that UHI effects in Beijing became severe from 2015 to 2017. The heat islands showed a mix of high and sub-high land surface temperature (LST). The spatial Durbin model estimates that one-unit increase of UHI intensity (UHII) would lower the housing value by 3.91%. Regarding the different districts, households had different attitudes to the UHI effect. Specifically, households regarded UHI effect as amenity in the four suburban districts with hills and relatively low LSTs; however, in most urban districts and their surroundings, households were willing to pay to avoid UHI effects with 13.0 dollars to 826.3 dollars for one-degree UHII decrease. This study highlights the urgent need for planners and decision-makers to consider urban expansion, UHI effect, and their economic impact in future urban planning.

Investigating the Hedonic Housing Price Model for Lagos Residential Market

The conundrum on what exactly consumers are willing to pay for when demanding for housing remains a concern in the developing world. This study investigates the hedonic housing price for Lagos residential market with a view to determine the willingness to pay for housing quality traits. The hedonic pricing model is one way through which willingness to pay is being measured. The data employed was obtained from adult residents in the urban centers of the state (Lagos Metropolitan city). Specifically, Lagos State has 20 Local Government Areas (LGAs), out of which 16 constitute the Lagos Metropolitan City. Multistage sampling technique was used to select a sample of 677 housing consumers from the population. The Ridge Regression (RR) was used to estimate the multifactorial model that formed the hedonic housing price model. This method overcomes the problem of multicollinearity in the model and produce unbiased estimates. The findings show that house type has a higher impact on the willingness to pay for a house. Flooring condition of a house is more considered by the consumers than its roofing and walling. Besides, availability of clean water is the most important variable that consumers consider in the basic attribute as relates to life essentials. The next to it is the availability of fence in the apartment. In essence, security of life and property remains a concern to living in Lagos and Nigeria by extension. This underscores the need for Nigerian government to sincerely tackle insecurity in the nation. Essentially, government must strengthen its intelligent mechanisms so as to unravel and deal with internal and external sponsors of insecurity in the country. Closeness to bank and commercial centres stands to be the variable with the greatest impact on willingness to pay among the positive environmental externalities. Meanwhile, a unit increase in travel distance to hospital, market and water facility decrease willingness to pay by 6.1 percent, 3.4 percent and 0.6 percent, respectively. In all, house consumers in the city are willing to pay different prices for different housing quality traits.

Losses of Residential Utility from Budget Constraints on Preferences for Homes

Budget-constrained residential preferences differ from unconstrained residential preferences if residents mentally devalue unaffordable attributes’ levels of available homes in comparison with affordable ones. Budget-constrained and unconstrained utilities of 70 recent-mover respondents in Saskatoon SK in 1987 and 74 inner-city respondents in Windsor ON in 2020 are quantified for 12 generic attributes of homes in conjoint choice experiments. Budget constraints on their utilities for homes’ attributes’ levels are operationalized by superimposing marginal implicit prices from a hedonic housing price model in each city. Residential utilities are then statistically compared both through time and for subsamples within full samples, and losses of utility are predicted. Respondents will experience an approximate one-quarter and one-tenth loss of possible utility for a home in Saskatoon and Windsor, respectively, if they cannot afford their unconstrained most preferred attributes’ levels. Losses of utility are predicted even though budget-constrained utilities of subsamples of respondents are higher as hypothesized for affordable levels of four attributes, and lower for unaffordable levels of those attributes. In conclusion, theoretical and practical implications of these predictions of losses of residential utility are discussed for residents, housing providers and policymakers.

The rising and heterogeneous demand for urban green space by Chinese urban residents: Evidence from Beijing

Studies using Hedonic housing price model to discuss residents' demand for urban green space (UGS) demonstrate the importance that residents place on UGS. While much of the empirical findings have focused on residents' willingness to pay, more attention needs to be paid on its temporal change and spatial heterogeneity. Taking advantage of the diverse composition of urban parks, housing, and residents in Beijing, this paper explores the dynamic and heterogeneous demand for UGS. Using more than 240 thousand micro housing resale transaction data from 2011 to 2019, this paper constructs a Hedonic model to empirically estimate and confirm the basic, dynamic and heterogenous willingness to pay of residents for urban parks. Our empirical findings confirm the rising and heterogeneous demand for UGS by Chinese urban residents. First, the willingness to pay for parks of urban residents has continued to grow during our study period. Second, in view of different socioeconomic characteristics, there exists heterogeneous demand related to the housing of residents and different types of parks. Residents who live in homes with a larger size have a stronger demand for urban parks. Meanwhile, urban residents prefer parks with free entry over fee-based parks, and they have strong preference for some specific types of parks. Moreover, we conduct a survey and collect 907 valid samples to directly obtain residents' willingness to pay for urban parks, and the survey results further confirm the abovementioned findings. This study deepens the understanding of urban residents’ demand for UGS, and will contribute to more scientific decision making on the planning, financing and management of UGS.

Konut Fiyatının Belirleyicilerinin Hedonik Fiyat Modeliyle Analizi: TR71 Bölgesi Örneği

The aim of this research is to analyze the determinants of house prices in the TR71 region by hedonic model. Least squares estimator is used in the analysis of hedonic house price model, which is built on a semi-logarithmic form. According to analysis findings, house size, room number, floor number of the house, floor number of the building and bathroom number affect the house prices positively, while the age of building affects house prices negatively. In addition, the analysis findings point out that the house of the house from the real estate agent instead of the owner has a negative effect on the house prices. Moreover analysis findings, show the fact that the house is located in Aksaray, Kırşehir and Nevşehir instead of Niğde have a positive effect on house prices. Also analysis findings reveal that spatial factors have more pronounced effects on the house prices than the physical properties of the house. A significant effect of the combi boiler, heater, stove and floor heating system on house prices is not detected in the analysis findings. Finally, the analysis findings indicate that the fact that the house is located within site does not have a significant effect on house prices.

The Role of Distance‐Dependent Versus Localized Amenities in Polarizing Urban Spatial Structure: A Spatio‐Temporal Analysis of Residential Location Value in Columbus, Ohio, 2000–2015

This study examines the relative effects of distance‐dependent versus localized amenities in changing urban spatial structure of residential location values within urban areas. We also investigate the spatio‐temporal patterns of neighborhood value, which is the sum of distance‐dependent and localized amenity effects, at a local community scale. We use a hedonic housing price model that controls for residential property characteristics to distinguish the effects of distance‐dependent and localized amenities that manifest in housing prices. We also utilize kriging and spatial statistics to examine the relative contributions of these effects to increasing spatial polarization between high‐valued versus low‐valued neighborhood locations. We conduct this analysis using a georeferenced housing transactions database containing almost 480,000 parcel‐level home sales during the period 2000–2015 within the urbanized area of Columbus, Ohio, USA, a highly segregated city. Results demonstrate the dominant and major role of localized amenity effects in shaping the polarized urban spatial structure of housing prices and neighborhood value. Quantitatively, we find a tripling of the Moran's I values of the neighborhood value, meaning deepening, and worsening divide between high‐valued versus low‐valued residential locations.

Measures of labour market accessibility. What can we learn from observed commuting patterns?

It is well known that measures of labour market accessibility explains spatial variation in housing prices even in markets with polycentric labour market structures. This paper examines whether data on observed commuting patterns can replace or supplement gravity-based measures representing the commuting potential at specific locations. We use data from a region in Western Norway,and we find that measures based on observed commuting flows and commuting time cannot replace a gravity-based measure of labour market accessibility. Based on, inter alia, the spatial Durbin estimator we find that measures of observed commuting flows increase the explanatory power of a hedonic house price model.

A comparative study on the value of scenic views between an inland and a coastal city in Korea

ABSTRACTThis study estimates hedonic house price models for an inland city of Seoul and a coastal city of Pusan using spatial regression with successful bidding price data of court auction during the period from January 2006 to December 2014. Among hedonic attributes such as floor area, building age, total floor level, living floor level, direction of the window of the living room, proximity to natural environment, scenic views and others employed in this study, our main focus is on scenic views. As a result of our empirical analysis, the most preferred view turns out to be a water-related view such as a broad river view in Seoul or an ocean view in Pusan. A mountain view, affecting negatively in a coastal city like Pusan which is adjacent to the beautiful ocean, has positive influence in Seoul, since it is an inland city with no ocean in sight with only a river running across the heart of the city which is surrounded by mountains serving as its boundary. While a building view in Seoul has negative effect on the price, it affects positively in Pusan.

Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations

ABSTRACTGeographically Weighted Regression (GWR) is a widely used tool for exploring spatial heterogeneity of processes over geographic space. GWR computes location-specific parameter estimates, which makes its calibration process computationally intensive. The maximum number of data points that can be handled by current open-source GWR software is approximately 15,000 observations on a standard desktop. In the era of big data, this places a severe limitation on the use of GWR. To overcome this limitation, we propose a highly scalable, open-source FastGWR implementation based on Python and the Message Passing Interface (MPI) that scales to the order of millions of observations. FastGWR optimizes memory usage along with parallelization to boost performance significantly. To illustrate the performance of FastGWR, a hedonic house price model is calibrated on approximately 1.3 million single-family residential properties from a Zillow dataset for the city of Los Angeles, which is the first effort to apply GWR to a dataset of this size. The results show that FastGWR scales linearly as the number of cores within the High-Performance Computing (HPC) environment increases. It also outperforms currently available open-sourced GWR software packages with drastic speed reductions – up to thousands of times faster – on a standard desktop.

Accounting for Spatial Variation of Land Prices in Hedonic Imputation House Price Indices: a Semi-Parametric Approach

Abstract Location is capitalized into the price of the land the structure of a property is built on, and land prices can be expected to vary significantly across space. We account for spatial variation of land prices in hedonic house price models using geospatial data and a semi-parametric method known as mixed geographically weighted regression. To measure the impact on aggregate price change, quality-adjusted (hedonic imputation) house price indices are constructed for a small city in the Netherlands and compared to price indices based on more restrictive models, using postcode dummy variables, or no location information at all. We find that, while taking spatial variation of land prices into account improves the model performance, the Fisher house price indices based on the different hedonic models are almost identical. The land and structures price indices, on the other hand, are sensitive to the treatment of location.

주택 거래 간 시공간 의존성을 고려한 헤도닉 가격 추정

주택 거래 간 시공간 의존성을 고려한 헤도닉 가격 추정

Accounting for spatial variation of land prices in hedonic imputation house price indexes

Location is capitalized into the price of the land the structure of a property is built on, and land prices can be expected to vary significantly across space. We account for spatial variation of land prices in hedonic house price models using geospatial data and a semi-parametric method known as mixed geographically weighted regression. To measure the impact on aggregate price change, quality-adjusted (hedonic imputation) house price indexes are constructed for a small city in the Netherlands and compared to price indexes based on more restrictive models, using postcode dummy variables or no location information at all. We find that, although taking spatial variation of land prices into account improves the model performance, the Fisher house price indexes based on the different hedonic models are almost identical. The land and structures price indexes, on the other hand, are sensitive to the treatment of location.

Searching for Isard’s Regional Essence

At the inception of the Southern Regional Science Association in the early 1960s, Walter Isard maintained that areal regions are fundamental units of observation and analysis. To this day, understanding the special significance of regions motivates much of our empirical research. In my address, I argue that regional fixed effects estimates from regression analysis can help us comprehend the distinctive character of areal units. This paper offers two examples from my research. First, I present the results of a regression model that explains regional knowledge spillovers in U.S. counties. Santa Clara County (Silicon Valley) has by far the largest fixed effect estimate of any U.S. county. Overall, the county level fixed effects for knowledge spillovers follow a pattern of rapid exponential decay. Next, I inspect neighborhood fixed effects taken from a hedonic housing price model of the Charleston, South Carolina region. The results suggest a clear preference for coastal proximity as reflected in house prices. For neighborhoods away from the coast, the fixed effects estimates exhibit a steep decline toward zero. Like Silicon Valley’s regional advantage in knowledge, beachfront neighborhoods benefit from an exclusive, time invariant advantage that is hard, if not impossible, to replicate in space.

A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method

Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

Functional regression over irregular domains: variation in the shadow price of living space

ABSTRACTFunctional regression over irregular domains: variation in the shadow price of living space. Spatial Economic Analysis. Hedonic house price models need to account for spatial heterogeneity – the variation in the functional surface of shadow prices. In this context, the complexity of spatial domains raises issues for traditional spatial econometric methods. Specifically, discontinuities in the spatial surface need to be accounted for, including irregular boundaries, peninsulas and interior holes. Motivated by an application to housing markets, we develop a method for estimating the functional surface of a regression coefficient that varies over such an irregular spatial domain. Spatially varying coefficients for a specific regressor are estimated by a combination of three smoothing problems using splines based on finite element analysis. The effect of additional regressors is also allowed. We verify finite sample performance using a simulation study, and develop an application to the Aveiro–Ílhavo urban housing market in Portugal.

Valuing the Redevelopment Option Component of Urban Land Values

AbstractThis study draws from the redevelopment, real option, and urban spatial growth literatures to explore the spatial dynamics of the components of house prices. More specifically, the paper proposes that the capitalized value of the option to redevelop housing at the property level can be estimated by incorporating the likelihood of exercising the redevelopment option (the probability of redevelopment) into spatial and nonspatial hedonic house price models. Accordingly, option values are estimated for properties across the spectrum of the housing life cycle. Results from the study reveal a substantial level of spatial variation and clustering in the predicted option values, indicating that location is a major determinant of redevelopment and real option values. Furthermore, the results provide new evidence in support of the theoretical construct that properties purchased for immediate redevelopment are only valued for the underlying land.

The Spatial Dimension of House Prices

The Spatial Dimension of House Prices