The illusion of a hedonic price function: Nonparametric interpretable segmentation for hedonic inference

Nishi, Hayato; Asami, Yasushi; Shimizu, Chihiro

doi:10.1016/j.jhe.2021.101764

Cited by 8 publications

(8 citation statements)

References 36 publications

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“…In apartment buildings, the impact of housing vacancies is shared within the building, but does not spill over to neighboring buildings. Despite the correlation between apartment rent and vacancy duration in the overall housing market, as shown in Tables 2 and 3, the market may be segmented based on rent levels (Nishi et al, 2021). Table 4 presents the results of using a series of quantile regressions.…”

Section: Resultsmentioning

confidence: 99%

“…Quantile regression provides researchers with the conditional distribution of responses with respect to a specific quantile (Koenker and Bassett, 1978; Koenker and Hallock, 2001); thus, facilitating the estimation of responses across different levels of rental prices. Assuming that the real estate market is segmented according to housing prices, as well as housing and local environment attributes (Nishi et al , 2021), the demand curve for housing characteristics will differ depending on the income level of the tenants (Zietz et al , 2008). The top 10% and bottom 10% quantile regression models were used to reflect the different characteristics of apartments based on rent.…”

Section: Methodsmentioning

confidence: 99%

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The impact of apartment vacancies on nearby housing rents over multiple time periods: application of smart meter data

Baba

Shimizu

2022

IJHMA

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Purpose This study aims to explore the spatial externalities of apartment vacancy rates on housing rent by considering multiple vacancy durations. Design/methodology/approach This research uses smart meter data to measure unobservable vacant houses. This study made a significant contribution by applying building-level smart meter data to housing market analysis. It examined whether vacancy duration significantly affected apartment rent and whether the relationship between apartment rent and vacancy rate differed depending on the level of housing rent. Findings The primary finding indicates that there is a significant negative correlation between apartment rent and vacancy duration. Considering the spatial externalities of apartment vacancy rates, the apartment vacancy rates of surrounding buildings did not show any statistical significance. Moreover, quantile regression results indicate that although the bottom 10% of apartment rent levels showed a negative correlation with all vacancy durations, the top 10% showed no statistical significance related to vacancies. Practical implications This study measures the extent of spatial externalities that can differentiate taxation based on housing vacancies. Originality/value The findings indicate that landlords have asymmetric information about their buildings compared with the surrounding buildings, and the extent to which price adjusts for long-term vacancies differs depending on the level of apartment rent.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The impact of apartment vacancies on nearby housing rents over multiple time periods: application of smart meter data

Baba

Shimizu

2022

IJHMA

Self Cite

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“…Previous literature had provided several methods for constructing price indices, such as the hedonic model (Lancaster, 1966;Kain and Quigley, 1970;Rosen, 1974;Wilhelmsson, 2009;Wu et al, 2012;Li et al, 2020;Nishi et al, 2021), the repeat-sales method (Bailey et al, 1963;Gatzlaff and Haurin, 1997;Deng et al, 2012;Minne et al, 2020) and the hybrid method (Case and Quigley, 1991;Quigley, 1995;Leishman and Watkins, 2017). Each of these shows both advantages and disadvantages (Meese and Wallace, 1997).…”

Section: Price Analysis and Index Constructionmentioning

confidence: 99%

Constructing segmented rental housing indices: evidence from Beijing, China

Song

Wilhelmsson

Yang

2022

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PurposeThis paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.Design/methodology/approachThe hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.FindingsRental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.Research limitations/implicationsResidential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.Practical implicationsResidential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.Originality/valueThis paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.

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“…It is argued that to obtain unbiased estimates of the implicit prices identifying segmentation of the property market is essential. Some studies, namely, Adair et al (1996), Watkins (2001), Berry et al (2003), Lipscomb and Farmer (2005), Tu et al (2007), Liu et al (2020), andNishi et al (2021) utilized hedonic price techniques to test for market segmentation. They recognised the importance of both spatial and structural characteristics when defining submarkets and observed greater levels of homogeneity in the sample at a submarket level.…”

Section: Related Literaturementioning

confidence: 99%

House Price Determinants and Market Segmentation in Boulder, Colorado: A Hedonic Price Approach

Yazdani

2021

Preprint

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In this research we perform hedonic regression model to examine the residential property price determinants in the city of Boulder in the state of Colorado, USA. The urban housing markets are too compounded to be considered as homogeneous markets. The heterogeneity of an urban property market requires creation of market segmentation. To test whether residential properties in the real estate market in the city of Boulder are analyzed and predicted in the disaggregate level or at an aggregate level we stratify the housing market based on both property types and location and estimate separate hedonic price models for each submarket. The results indicate that the implicit values of the property characteristics are not identical across property types and locations in the city of Boulder and market segmentation exists.

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The illusion of a hedonic price function: Nonparametric interpretable segmentation for hedonic inference

Cited by 8 publications

References 36 publications

The impact of apartment vacancies on nearby housing rents over multiple time periods: application of smart meter data

The impact of apartment vacancies on nearby housing rents over multiple time periods: application of smart meter data

Constructing segmented rental housing indices: evidence from Beijing, China

House Price Determinants and Market Segmentation in Boulder, Colorado: A Hedonic Price Approach

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