Spatial Hedonic Approach Research Articles

Willingness to pay for multiple dimensions of green open space: Applying a spatial hedonic approach

AbstractTo optimize land conservation strategies with limited resources, it is necessary to understand people's preferences and willingness to pay (WTP) for green open space. The hedonic pricing method (HPM) is widely used. However, the conventional HPM assumes no value spillovers between neighbouring properties. Here we adopt a spatial regression approach that allows us to relax the no‐spillover assumption. Through an analysis of access to different types, intensity and developability of open green space on house prices in the City of Edmonton, Canada, we illustrate how spatial HPM can be used to quantify direct and spillover values of different dimensions of open green space. We find that WTP for open space has significant spillover effects, ignoring such spillovers would under‐estimate the total value of open space protection and thus the socially optimal amount of land conservation. All else equal, people are willing to pay most for houses that are close to non‐developable green open space and woodlands. The highest price premiums are for woodlands and non‐developable green open space, followed by living near the University of Alberta farm. On the contrary, people need small compensation to live near large commercial farms. The results suggest a NIMBY attitude toward preservation of commercial agriculture.

A spatial hedonic approach for modeling the relationship between quality of urban life and housing prices, case study: Alexandria city, Egypt

A spatial hedonic approach for modeling the relationship between quality of urban life and housing prices, case study: Alexandria city, Egypt

Do superfund sites affect local property values? Evidence from a spatial hedonic approach

Seven different Superfund sites located within or just outside the county border of Jefferson County, Kentucky are investigated. Our finding shows that the use of a traditional hedonic pricing model will result in inefficient estimates compared to a spatial error hedonic model. Considering two different phases of the cleanup process, we find that the median housing value is lower for houses near deleted Superfund sites but is not significantly affected by sites classified as final. Another consideration is the implications of multiple Superfund sites, and findings indicate that multiple Superfund sites do not significantly impact housing values.

Evaluating the value of an entrepreneurial city with a spatial hedonic approach: A case study of London

This study assesses the value of a city by using the housing price function with a geographically weighted regression model, including various social, economic, and environmental factors. To assess these values, various specific data scores—such as those related to ethnic groups, green areas, crime rates, education, unemployment rates, number of entrepreneurs, and environmental quality—were considered in a case study of London. The results indicate that some variables such as time to city center and entrepreneurship have a positive impact on the local areas’ value in London, as shown by housing prices, while those related to unemployment have a negative impact. Moreover, although the London city center has benefitted more in terms of value than its outskirts have, a few specific policies related to startups and entrepreneurship have succeeded in connecting these areas to existing companies and entrepreneurs. In general, large cities may be better equipped to promote such startup and entrepreneurship policies under local industry plans for future development.

Decoupling values of agricultural externalities according to scale: a spatial hedonic approach in Brittany

Agricultural activities jointly generate various externalities. Hedonic pricing method allows for their valuation. Previous hedonic studies have estimated the value of the externalities generated by a given agricultural activity in a single parameter. Based on simple theoretical model, we illustrate that this parameter captures the sum of the different externalities generated by the activity. Using insights from papers highlighting a distance-decay in the willingness-to-pay, explain that this parameter can differ at different spatial scales. Using specific spatial econometric model with spatial lags on the explanatory variables, we distinguish between the value of infra-municipal agricultural externalities (called direct effects) and the value of extra-municipal agricultural externalities with larger spatial range (called spillover effects) arising from the same agricultural source. Among the estimated models, the spatial lag of the exogenous variable and the general nested spatial models are selected as the best models. We find that swine activities present negative effects at all scales whereas dairy cattle activities, including grassland management, present negative direct effects but positive local spillovers.

Transforming Abandoned Rail Corridors into Multi-purpose Trails: Applying a Spatial Hedonic Approach to Estimating the Economic Benefits of the Little Miami Scenic Trail in Cincinnati, Ohio, USA

This research assesses the appreciation in residential property values in connection with proximity to the Little Miami Scenic Trail, a multi-purpose biking, hiking, and jogging trail built along an abandoned railroad corridor near Cincinnati, Ohio, USA. Applying two spatial hedonic frameworks, the spatial lag of X (SLX) model and the spatial Durbin error model, we conclude that proximity to trail entrances had significant impacts on property values for both, Euclidean and network distance measures. Specifically, the SLX results indicate that decreasing the distance to the closest trail entrance by one foot (meter) increases a house’s property value by US$0.92 (US$3.02) when using network distances.

Scenic landscapes, visual accessibility and premium values in a single family housing market: A spatial hedonic approach

This article uses a hedonic modelling approach to assess the implicit willingness to pay for the visual accessibility of voluntarily protected, privately owned, scenic lands based on single family houses. These lands are perpetually protected to preserve natural, historic, and scenic characteristics. The capitalized house premium was captured using a visual accessibility variable, which was a combined weighted measure of ‘view’ and ‘proximity,’ referred to here as the Gravity Inspired Visibility Index. Both global ( adjusted R2 = 0.52, AICc = 29,828) and geographically weighted regression models ( adjusted R2 = 0.59, AICc = 29,729) estimated the price effect but the geographically weighted regression model outperformed the global model. The results from the geographically weighted regression model indicated an average 3.4% price premium on the mean value of homes in the study area. The paper offers a useful framework for evaluating the effect of land protection for planning and real estate purposes. It also offers useful insights for conservation agencies, local governments, professional planners, and real estate professionals for prioritizing land sites with scenic views.

Do Superfund Sites Affect Local Property Values? Evidence from a Spatial Hedonic Approach

The presence of Superfund sites can have substantial impacts on surrounding property values. A shortcoming of studies utilizing the traditional hedonic price model is that they fail to account for the presence of spatial dependence or autocorrelation in residential housing. Jefferson County, Kentucky is home to Louisville, the largest city in the state. Seven different Superfund sites are located within or just outside the county border. Community planners, appraisal professionals, or policy makers considering the use of a traditional hedonic pricing model will find inefficient estimates compared to a spatial error hedonic model. This study also considers two different phases of the cleanup process, suggesting that median housing value is lower for houses in close proximity to deleted Superfund sites, but is not significantly affected by sites classified as final. Another consideration is the implications of multiple Superfund sites located within five miles of the block group centroid. Findings indicate that multiple Superfund sites do not significantly impact housing values.

“Living on the edge”: Estimating the economic cost of sea level rise on coastal real estate in the Tampa Bay region, Florida

Climate change and especially sea level rise are posing unprecedented pressure on coastal communities through enhanced coastal flooding and saltwater intrusion. Thus, adapting to its impacts has drawn global attention. Since the cost-efficiency of adaptation alternatives is crucial in decision making, accurately estimating the economic cost of sea level rise is an imperative task for coastal planners and managers. This study employed a spatial hedonic approach to estimate the economic cost due to inundation by future sea level rise. The applied methodology provides better estimates of the economic losses due to sea level rise by accounting for lost coastal amenities, and the results generated can also be utilized for cost-benefit analysis. In 2050, it is estimated that the inundation of 3-foot sea level rise could cost Hillsborough and Pinellas County over 300 and 900 million dollars respectively for the real estate market alone. Local coastal planners and managers may find this methodology useful in estimating the potential economic cost due to sea level rise and support making adaptation decisions. We also stressed the importance of such studies to support local decision making and enhance adaptation planning for the climate change and sea level rise in the coastal communities.

Assessing Regional Quality of Life: A Call for Action in Regional Science

Intellectual appeal and simplicity of use has led to the widespread application of the spatial hedonic model in assessing regional quality of life. Yet, the traditional spatial hedonic approach contains numerous assumptions, which typically are untested. Violation of the assumptions in practice can lead to significantly biased estimates of regional quality of life. More sophisticated econometric approaches have been developed to reduce the biases. However, each approach typically only addresses one or two of the concerns. More promising is the use of structural models, which by design have the potential to overcome all the limitations of the spatial hedonic approach.

Lots of value? A spatial hedonic approach to water quality valuation

Very few studies have addressed the effects of water quality on recreational values in a hedonic property price setting. This study elicits the value of improved water quality capitalised in Finnish recreational property prices adjacent to the Baltic Sea, lakes and rivers. In addition, spatial econometric methods are employed to address the spatial autocorrelation found in data. An expert-determined, water body specific water quality index that describes the usability status of the water is used instead of more specific, but also more problematic, water quality indicators. The study finds that water usability has a positive effect on property prices, with weak suggestions on non-linearity.

Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach

The recent progress of spatial econometrics has developed a new technique called the “spatial hedonic approach,” which considers the elements of spatial autocorrelation among property values and geographically distributed attributes. The practical difficulties in applying spatial econometric models include the specification of the spatial weight matrix (SWM), which affects the final analysis results. Some simulation studies suggest that information criteria such as AIC are useful for the SWM's selection, but if many model candidates exist (e.g., when the selections of explanatory variables are performed simultaneously), then the computational burden of calculating such criteria for each model is large. The present study develops an automatic model selection algorithm using the technique of reversible jump MCMC combined with simulated annealing; termed trans-dimensional simulated annealing (TDSA). The performance of the TDSA algorithm is verified using the well-known Boston housing dataset, and it is applied empirically to a Japanese real estate dataset. The obtained results suggest a two-step strategy for model selection, with SWM (W) first, followed by the explanatory variables (X and WX), will result in local optima, and therefore these variables should be selected simultaneously. The TDSA algorithm can find the significant variables that are “hidden” because of multicollinearity in the unrestricted model, and can attain the minimum AIC automatically.

Valuing Access to Water—A Spatial Hedonic Approach, with an Application to Bangalore, India

An important infrastructure policy issue for rapidly growing cities in developing countries is how to raise fiscal revenues to finance basic services in a fair and efficient manner. This requires estimates of the potential benefits or positive welfare effects that may follow from improved infrastructure. In this paper, we take advantage of a unique geo-referenced household survey to carry out a hedonic analysis of housing values that explicitly accounts for spatial spillovers. We use this to derive an estimate of the value of improved access to water in the Indian city of Bangalore. The findings suggest that by limiting the focus to individual or private benefits only, we may underestimate the overall social welfare from investing in service supply. We further demonstrate how spatially explicit policy simulations based on these estimates provide insight into the total effects of targeted interventions. Appréciation de l'accès à l'eau—Une méthode hédonique spatiale appliquée à la ville de Bangalore, en Inde Rèsumè Un important problème de politique en matière d'infrastructure qui se pose pour les villes à expansion rapide de pays en voie de développement est comment lever des recettes fiscales, de façon à la fois équitable et efficace, pour financer des services essentiels. Ces villes doivent, pour ceci, procéder à des évaluations des bénéfices potentiels ou des effets sociaux positifs que pourrait engendrer une meilleure infrastructure. Dans la présente communication, nous faisons usage des résultats d'une étude géoréférencée unique sur les ménages pour effectuer une analyse hédonique des valeurs des habitations, qui tienne compte de façon explicite des débordements spatiaux. Nous utilisons ensuite ces résultats pour dériver une estimation de la valeur d'un meilleur accès à l'eau dans la ville de Bangalore, en Inde. Les conclusions indiquent qu'en limitant notre recherche aux bénéfices individuels ou privés seulement, nous risquons de sous-estimer les avantages sociaux généraux des investissements dans la fourniture de services. Nous démontrons également comment des simulations de la politique, aux implications spatiales implicites sur la base de ces évaluations, permettent d'obtenir des connaissances sur les effets totaux des interventions ciblées. Valorando el acceso a agua—Un planteamiento hedónico espacial con una aplicación a Bangalore, India Extracto Una cuestión importante en cuanto a política de infraestructura para las ciudades de rápido crecimiento en países en vías de desarrollo es cómo incrementar los ingresos fiscales para financiar servicios básicos de forma justa y eficiente. Esto requiere estimaciones de los beneficios potenciales o de los efectos positivos para el bienestar social que podrían derivar de una mejor infraestructura. En este trabajo aprovechamos un exclusivo estudio georreferenciado sobre la vivienda para aplicar un análisis hedónico que tiene en cuenta explícitamente excedentes espaciales. Lo utilizamos para derivar una estimación del valor de un mejor acceso a agua en la ciudad india de Bangalore. Los descubrimientos sugieren que limitando el enfoque a los beneficios individuales o privados podríamos subestimar el bienestar social general procedente de invertir en el suministro de servicios. También demostramos cómo las simulaciones de políticas espacialmente explícitas basadas en estas estimaciones proporcionan una visión interna de los efectos totales de intervenciones dirigidas.

Valuing the benefits of the urban forest: a spatial hedonic approach

This paper measures the benefits of the urban forest by examining its effect on housing prices. A Geographic Information System is used to develop a measure of the urban forest, the Normalised Difference Vegetation Index, from satellite imagery and to construct other variables from a variety of sources. Spatial hedonic housing price models for the Indianapolis/Marion County area are estimated. The models indicate that greener vegetation around a property has a positive, significant effect on housing price, holding everything else constant. This effect is dominated by measures at the neighborhood level. These findings indicate that property owners value the urban forest, at least in part, by the premium they pay to live in neighborhoods with greener, denser vegetation. These findings also indicate that public action to maintain and enhance the urban forest may be warranted. Planners and urban foresters can use these findings to inform public and policy debates over urban forestry programs and proposals.

A Spatial Hedonic Approach to Assess the Impact of Swine Production on Residential Property Values

A spatial hedonic model is developed to assess monetary harm of confined animal feeding operations (CAFOs) on property values, taking explicitly into account spatial dependence in property values. Spatial autocorrelation was found in the form of spatial lag dependence, not spatial error dependence. When spatial lag dependence is explicitly taken into account, on average the impact coefficient estimate of a CAFO is reduced by 18%. For example, the impact on the value of the median house ($63,520) 1 mile from a swine facility with 10,000 head fell from − $6,800 to − $5,200, or 23.5%. The magnitude of the spatial autoregressive parameter was about 0.2 for the 1-mile distance band, meaning one-fifth of the house value could be explained by the values of the neighboring houses.

Measuring the benefits of air quality improvement: a spatial hedonic approach

The primary objective of this paper is to improve the methodology for estimating hedonic price functions when the data are inherently spatial. A spatial-econometric hedonic housing price model is developed and estimated for the Seoul metropolitan area to measure the marginal value of improvements in sulfur dioxide (SO 2) and nitrogen dioxide (NO x ) concentrations. Diagnostic testing favored the spatial-lag model over the spatial error model. Results showed that SO 2 pollution levels had a significant impact on housing prices while NO x pollution did not. The authors attribute this differential impact to the relatively higher levels of SO 2 pollution when compared with pollution standards and the relative recency of the NO x pollution. Marginal WTP for a 4% improvement in mean SO 2 concentrations is about $2333 or 1.4% of mean housing price.

The cardiovascular changes associated with intravenous and long-term oral labetalol: F.D. Thompson, Institute of Urology, London, England; M.M. Hussein; A.M. Joekes

Climate change and especially sea level rise are posing unprecedented pressure on coastal communities through enhanced coastal flooding and saltwater intrusion. Thus, adapting to its impacts has drawn global attention. Since the cost-efficiency of adaptation alternatives is crucial in decision making, accurately estimating the economic cost of sea level rise is an imperative task for coastal planners and managers. This study employed a spatial hedonic approach to estimate the economic cost due to inundation by future sea level rise. The applied methodology provides better estimates of the economic losses due to sea level rise by accounting for lost coastal amenities, and the results generated can also be utilized for cost-benefit analysis. In 2050, it is estimated that the inundation of 3-foot sea level rise could cost Hillsborough and Pinellas County over 300 and 900 million dollars respectively for the real estate market alone. Local coastal planners and managers may find this methodology useful in estimating the potential economic cost due to sea level rise and support making adaptation decisions. We also stressed the importance of such studies to support local decision making and enhance adaptation planning for the climate change and sea level rise in the coastal communities.

Screening: Detection, referral, and follow-up of upper pinellas county hypertensive candidates: Bonnie Stemler, Upper Pinellas Chapter, American Red Cross, Clearwater, Florida; Melinda Brett

Climate change and especially sea level rise are posing unprecedented pressure on coastal communities through enhanced coastal flooding and saltwater intrusion. Thus, adapting to its impacts has drawn global attention. Since the cost-efficiency of adaptation alternatives is crucial in decision making, accurately estimating the economic cost of sea level rise is an imperative task for coastal planners and managers. This study employed a spatial hedonic approach to estimate the economic cost due to inundation by future sea level rise. The applied methodology provides better estimates of the economic losses due to sea level rise by accounting for lost coastal amenities, and the results generated can also be utilized for cost-benefit analysis. In 2050, it is estimated that the inundation of 3-foot sea level rise could cost Hillsborough and Pinellas County over 300 and 900 million dollars respectively for the real estate market alone. Local coastal planners and managers may find this methodology useful in estimating the potential economic cost due to sea level rise and support making adaptation decisions. We also stressed the importance of such studies to support local decision making and enhance adaptation planning for the climate change and sea level rise in the coastal communities.