A Real-Time Property Value Index Based on Web Data

Bárcena, María Jesús Gómez; Menéndez, Patricia; Palacios, María Blanca; Tusell, Fernando

doi:10.1016/b978-0-12-411511-8.00010-4

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…One application of hedonic models worth focusing on is the quality adjustments made on price indices to differentiate price increases associated with quality increases (Statistical Office of the European Communities et al, 2013). For this reason, accounting for spatial heterogeneity in price indices has been suggested in literature (Bárcena et al, 2014;Brunauer et al, 2012;Olszewski et al, 2017), Our findings similarly encourage consideration of spatial heterogeneity when using hedonic models in housing markets.…”

Section: Introductionsupporting

confidence: 73%

“…In the case of Turkey, Hülagü et al, (2016) employs a geographical stratification at a sub-city (above neighborhood) level in running hedonic regressions for quality adjustment purposes. In comparison, our results suggest spatial non-stationarity at a more local level with a different model, a possibility which has been explored in literature (Bárcena et al, 2014;Brunauer et al, 2012;Olszewski et al, 2017).…”

Section: Figure 3: Standard Hedonic Regression Residuals (Left) and Gwr Residuals (Right) On Mapsupporting

confidence: 59%

“…However, our findings support the idea that it could be beneficial to incorporate local spatial heterogeneity in price indices. (Bárcena et al, 2014;Brunauer et al, 2012;Olszewski et al, 2017) The results calls for caution in the use of hedonic pricing in policy making. The use of statistics based on hedonic pricing in policy decisions requires the spatial heterogeneity of the market to be kept in mind and further discussion on spatial nonstationarity is needed before applying them to decision making processes of far reaching decisions.…”

Section: Discussionmentioning

confidence: 99%

“…Hanink et al (2012) use a hedonic model at an aggregate county level and finds local variations in structural and contextual characteristics of housing across China. Lu et al(2014) explores using non Euclidean distance metrics Brunauer et al (2012),Bárcena et al (2014). andOlszewski et al (2017) tries to improve hedonic price indices using GWR and semi-parametric approaches in Austria, Spain and Poland housing markets, respectively.…”

mentioning

confidence: 99%

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Spatial heterogeneity in Istanbul housing market: a geographically weighed approach

Morali¹,

Yılmaz²

2020

Pressacademia

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Purpose -This study examines and documents spatial heterogeneity in Istanbul housing market using Geographically Weighted Model (GWR). Methodology -A GWR model with a Gaussian kernel and an adaptive bandwidth based on cross-validation is employed on a cross-sectional housing listing data set. Additional analysis is provided using geographically weighted Spearman's rank correlation measure between prices and variables. Findings-GWR model substantially boosts goodness of fit in our pricing model compared to a standard hedonic regression model. The variation within GWR coefficients is high and of micro nature. Median GWR coefficients often differ from standard hedonic regression coefficients. The variability of coefficients is plotted on map. Conclusion-Findings suggest the existence of spatial non-stationarity in standard hedonic regressions and favor the use of models appropriate for spatial heterogeneity. Findings encourage further research in hedonic models applications such as in quality adjustments to price indices.

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Section: Introductionsupporting

confidence: 73%

Section: Figure 3: Standard Hedonic Regression Residuals (Left) and Gwr Residuals (Right) On Mapsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Spatial heterogeneity in Istanbul housing market: a geographically weighed approach

Morali¹,

Yılmaz²

2020

Pressacademia

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“…The method is straightforward, conceptually simple to implement, understand and track. (Conceptual simplicity does not imply that the implementation is trivial; for an overview of some practical problems met see Bárcena et al (2013). ) However, ours is but a possible approach to a much researched problem: for a collection of papers from a spatio-temporal vantage point see Biggeri and Ferrari (2010).…”

Section: Discussionmentioning

confidence: 99%

Monitoring 15 Years of Residential House Price Development in Hungary With the Help of the FHB House Price Index

Nagy¹

2014

SSRN Journal

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This paper presents a simple disequilibrium model in the primary housing market, calibrated to the Warsaw market. Our aim is to point out that the primary housing market, due to the long construction process is always in disequilibrium, which has important policy implications. We discuss the last housing cycle and show how a combination of slight demand shocks with short-term rigid supply leads to strong fluctuations of house prices and new construction. The primary market can create a significant distress to the economy, because when house prices rise, this sector attracts capital and workers and is able to generate excessive supply, which finally can lead to the burst of the price bubble. The cyclical character is a permanent feature of the property market and can be explained by the inelasticity of supply. Market participants form price and demand expectations based on past observations. This causes frequent cycles that, under specific conditions, can lead to economic crises. We believe that the model describes the reality of the primary housing market better than equilibrium models do, so it can be useful for central banks and financial supervision institutions in the analysis of the impact of fiscal and monetary policy and regulations on the real estate market.

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Hedonic Models and House Price Index Numbers

Hill

Rambaldi

2022

Advances in Economic Measurement

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A Real-Time Property Value Index Based on Web Data

Cited by 4 publications

References 16 publications

Spatial heterogeneity in Istanbul housing market: a geographically weighed approach

Spatial heterogeneity in Istanbul housing market: a geographically weighed approach

Monitoring 15 Years of Residential House Price Development in Hungary With the Help of the FHB House Price Index

Hedonic Models and House Price Index Numbers

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