Housing Submarkets and the Lattice of Substitution

Pryce, Gwilym

doi:10.1177/0042098013482502

Cited by 31 publications

(41 citation statements)

References 26 publications

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“…A further extension of our method would allow for nonspatial dependence between aerial units. Pryce (2013), for example, argued that Euclidean distance or contiguity might not be the only way that dependence occurs between aerial units-perceived substitutability; social networks or communication and transport links might lead to some units being "close" even if they are spatially distant. In such circumstances, the conditional autoregressive component of the model could be constructed in substitutability or network space rather than Cartesian space (ºaszkiewicz, Dong, and Harris 2014).…”

Section: Resultsmentioning

confidence: 99%

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

Dong

Harris

et al. 2015

Annals of the American Association of Geographers

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This article explores how to incorporate a spatial dependence effect into the standard multilevel modeling (MLM). The proposed method is particularly well suited to the analysis of geographically clustered survey data where individuals are nested in geographical areas. Drawing on multivariate conditional autoregressive models, we develop a spatial random slope MLM approach to account for the within-group dependence among individuals in the same area and the spatial dependence between areas simultaneously. Our approach improves on recent methodological advances in the integrated spatial and MLM literature, offering greater flexibility in terms of model specification by allowing regression coefficients to be spatially varied. Bayesian Markov chain Monte Carlo (MCMC) algorithms are derived to implement the proposed model. Using two-level travel satisfaction data in Beijing, we apply the proposed approach as well as the standard nonspatial random slope MLM to investigate subjective travel satisfaction of residents and its determinants. Model comparison results show strong evidence that the proposed method produces a significant improvement against a nonspatial random slope MLM. A fairly large spatial correlation parameter suggests strong spatial dependence in district-level random effects. Moreover, spatial patterns of district-level random effects of locational variables have been identified, with high and low values clustering together

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Section: Resultsmentioning

confidence: 99%

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

Dong

Harris

et al. 2015

Annals of the American Association of Geographers

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“…Peng & Thibodeau, 2013;Rae, 2015). Different methods may be used to distinguish submarkets, such as statistical analyses (Bourassa, Hamelink, Hoesli, & MacGregor, 1999), methods using cross-price elasticity (Pryce, 2013), hedonic price theory (Rosen, 1974) or spatial analyses (Wu & Sharma, 2012). Previous sub-market research has focused on grouping properties to create better models with the price as dependent variable (e.g.…”

Section: Problem Specificationmentioning

confidence: 99%

Measurement of entropy in the assessment of homogeneity of areas valued with the Szczecin Algorithm of Real Estate Mass Appraisal

Gnat¹

2019

JEM

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Aim/purpose -General real estate taxation is a process regulated, inter alia, by the Real Estate Management Act. It is intended to establish a tax base for real estate in the event of a change in real estate tax base. General taxation is one of several applications of mass valuation of real estate, which enables valuation of many properties at the same time and with a uniform approach. One of the methods of mass valuation of real estate already applied in practice is the Szczecin Algorithm of Real Estate of Mass Appraisal (SAREMA). One of the immanent features of general taxation and the algorithm itself is the division of a selected area into possibly homogeneous areas called taxing zones within the general taxation terminology and, more broadly, elementary areas, according to the nomenclature used in the SAREMA. The paper presents the results of the studies on the measurement of elementary areas homogeneity on the example of land plots located in Szczecin. It is important to assess whether the designated sub-areas of valuation cover properties similar to each other in terms of their specific characteristics. If so, it will help to obtain more accurate mass valuation results. Design/methodology/approach -The paper proposes to use a modified entropy measure to establish whether the designated areas are homogeneous in terms of the specified properties of real estate. The database of real estate includes more than 1.5 thousand urbanised land plots located in Szczecin. The measurement of entropy will be preceded by the specification of elementary areas. The available methods include the application of an expert approach, under which land boundaries will be indicated by property valuers.Findings -The main conclusion of the study is that a modified measure of entropy ensures a better indication of the degree of indefiniteness of valued sub-areas and thus it offers a better way of supporting the delimitation of these sub-areas in comparison to the classical measure of entropy.Research implications/limitations -The delimitation of valuation sub-areas constitutes an important element of mass valuation. Proper execution of this process enables obtaining much more precise valuations. An objective measure of homogeneity gives a chance to compare different approaches to the creation of the above-mentioned subareas and to choose the best of them. Originality/value/contribution -The main achievement of the study is a proposal to modify the classical entropy measure, thanks to which it better reflects the specificity of the assessment of homogeneity of the areas valued in terms of property market analysis.

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“…There is also a large literature on regressionbased estimation of house prices drawing on the 'hedonic' framework (see Adair et al, 2000;Harris, 1999; and critiques by Malpezzi, 2003 andPryce, 2013), but there are important shortcomings to this approach from a network perspective. An important difference between true statistical network analysis and techniques such as hedonic regression is the capacity to deal with dependence and connectivity (Goldenberg et al, 2010).…”

Section: Existing Literaturementioning

confidence: 99%

“…To illustrate how the conceptual framework described above could be applied empirically, we use the CPEP estimates generated by Pryce (2013) to construct a network based on perceived substitutability in the Glasgow housing market. Estimates of CPEP are based on 33,680 geocoded GSPC (Glasgow Solicitors Property Centre) residential property transactions for the period 1999 to 2007.…”

Section: Empirical Illustrationmentioning

confidence: 99%

Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration

Dean

Pryce

2017

Urban Studies

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Housing markets are unlikely to be impervious to the preferences and prejudices associated with urban segregation. For example, two neighbourhoods with very different religious attributes are unlikely to be perceived as close substitutes by homebuyers that have a strong preference for neighbours of a particular religion. This paper offers a new framework for the conception and measurement of social integration, defined in terms of perceived homophily. Homophily is the tendency for links to form between similar nodes in a network and we can think of perceived homophily as the tendency for any pair of neighbourhoods to be considered by the housing market to be close substitutes. Textbook economic theory suggests that we should expect the degree of perceived substitutability to affect cross-price elasticities. These can be measured empirically to reveal discontinuities in the network of perceived substitutability of different housing locations. Applying homophily coefficients to substitutability measures allows us to estimate perceived religious homophily between neighbourhoods. The approach can be applied to any city or region that has geocoded house transactions and socio-demographic data. We illustrate the method using data on Glasgow and find strong evidence of religious homophily. This suggests an underlying lack of social integration/cohesion and implies that the Glaswegian housing market is by no means blind to religion.

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Housing Submarkets and the Lattice of Substitution

Cited by 31 publications

References 26 publications

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

Measurement of entropy in the assessment of homogeneity of areas valued with the Szczecin Algorithm of Real Estate Mass Appraisal

Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration

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