A Theoretical Basis for Hedonic Regression: A Research Primer

Edmonds, Radcliffe G.

doi:10.1111/1540-6229.00311

Cited by 37 publications

(10 citation statements)

References 24 publications

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“…Their aim is to organize masses of data around relevant sets of concepts. With respect to hedonic housing price models in particular, the relevant set of concepts may be stated as follows (Lancaster 1966;Rosen 1974;Lucas 1975;Freeman 1979;Edmonds 1984). The utility of a housing unit is a function of its attributes.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications

2001

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Recent advances in spatial data analysis are making their way into a variety of applied research settings. Once purely the domain of specialists, increased availability of both spatial data and the software with which to handle them, spatial analysis techniques are diffusing into other areas of research. This article first details the rationale and need for spatial considerations in hedonic price models and focuses on the link between the context of the housing market and the statistical considerations necessary when dealing with spatial data. These issues are then explored via an application to the housing market of Cuyahoga County, Ohio. It was found, first, that explicit modeling of space is not always warranted. One of our two models shows no substantial signs of spatial misspecification. However, in the second model, where diagnostic tests call for the explicit modeling of space, some drastic differences were found between the space-neglected model and the more correctly specified spatial hedonic model. This highlights the need to include spatial diagnostics as part of the standard model-fitting procedure for hedonic house price applications. Copyright 2001 Gatton College of Business and Economics, University of Kentucky.

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Section: Introductionmentioning

confidence: 99%

Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications

2001

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“…In the Lancastrian model, goods possess characteristics giving rise to utility. A characteristic is "an objectivelymeasurable, utility-affecting attribute of a model" while "a model is a distinct, homogeneous, marketable tied bundle of characteristics" (Edmonds, 1984).…”

Section: Experienced Utility For Hedonic Pricing Models Of Smart Real Estatementioning

confidence: 99%

iSpace: principles for a phenomenology of space user in smart real estate

Lecomte¹

2019

JPIF

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Purpose As smart technologies become an integral part of real estate in smart cities, the purpose of this paper is to explore the impact of ubiquitous computing on space users in smart real estate. Design/methodology/approach The analysis builds on two fields of knowledge rarely referenced in real estate studies: computer sciences and social sciences. The paper starts by analysing the idiosyncrasies of a new type of space user in smart real estate, known as the Cyber-dasein in reference to Heidegger’s phenomenology. The Cyber-dasein serves as an archetypical space user in smart environments. Findings The paper introduces digital-time as a new realm of real estate, and discusses the use of “experienced utility” in hedonic pricing models of smart real estate. It concludes by advocating a multidisciplinary collaborative approach for future research on real estate in smart environments. Practical implications There is a need for the real estate sector to decide on a metric for the new digital dimension of real estate owing to the implementation of smart technologies in the built environment. Originality/value This is the first research paper on this important topic. It is totally original and new.

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“…The availability of on-site garage parking is one such factor in a household's housing purchase or rental decision, and it is the primary explanatory variable of interest in this study. Economic theory does not specify the housing characteristics which should be incorporated in a hedonic regression model (Edmonds, 1984;Sirmans et al, 2005). As such, there is considerable variation in the explanatory variables other scholars have included in their models.…”

Section: Modeling Approachmentioning

confidence: 99%

Hidden Costs and Deadweight Losses: Bundled Parking and Residential Rents in the Metropolitan United States

Gabbe¹,

Pierce

2016

Housing Policy Debate

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There is a major housing affordability crisis in many American metropolitan areas, particularly for renters. Minimum parking requirements in municipal zoning codes drive up the price of housing, and thus represent an important potential for reform for local policymakers. The relationship between parking and housing prices, however, remains poorly understood. We use national American Housing Survey data and hedonic regression techniques to investigate this relationship. We find that the cost of garage parking to renter households is approximately $1,700 per year, or an additional 17% of a housing unit's rent. In addition to the magnitude of this transport cost burden being effectively hidden in housing prices, the lack of rental housing without bundled parking imposes a steep cost on carless renters-commonly the lowest income households-who may be paying for parking that they do not need or want. We estimate the direct deadweight loss for carless renters to be $440 million annually. We conclude by suggesting cities reduce or eliminate minimum parking requirements, and allow and encourage landlords to unbundle parking costs from housing costs.

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A Theoretical Basis for Hedonic Regression: A Research Primer

Cited by 37 publications

References 24 publications

Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications

Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications

iSpace: principles for a phenomenology of space user in smart real estate

Hidden Costs and Deadweight Losses: Bundled Parking and Residential Rents in the Metropolitan United States

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