Spatial Market Inefficiency in Housing Market: A Spatial Quantile Regression Approach

Jiyoung Chae; Anil K. Bera

doi:10.1007/s11146-022-09923-y

Spatial Market Inefficiency in Housing Market: A Spatial Quantile Regression Approach

Research output: Contribution to journal › Article › peer-review

Abstract

This paper empirically tests housing market efficiency in the spatial dimension by using the spatial autoregressive conditional heteroskedastic (ARCH) and spatial quantile regression models. The tests were conducted in terms of both housing returns and squared returns (volatility). The sale price data used is from Cook County residential MLS for the years 2010–2016. The main findings are that housing returns are not spatially correlated but squared returns are spatially correlated, and the spatial dependence of squared returns seems to be stronger for higher squared return quantiles.

Original language	English (US)
Pages (from-to)	70-99
Number of pages	30
Journal	Journal of Real Estate Finance and Economics
Volume	69
Issue number	1
DOIs	https://doi.org/10.1007/s11146-022-09923-y
State	Published - Jul 2024

Keywords

Housing market
Market efficiency
Spatial dependence
Spatial quantile regression
Spatial volatility clustering

ASJC Scopus subject areas

Accounting
Finance
Economics and Econometrics
Urban Studies

Online availability

10.1007/s11146-022-09923-y

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Cite this

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abstract = "This paper empirically tests housing market efficiency in the spatial dimension by using the spatial autoregressive conditional heteroskedastic (ARCH) and spatial quantile regression models. The tests were conducted in terms of both housing returns and squared returns (volatility). The sale price data used is from Cook County residential MLS for the years 2010–2016. The main findings are that housing returns are not spatially correlated but squared returns are spatially correlated, and the spatial dependence of squared returns seems to be stronger for higher squared return quantiles.",

keywords = "Housing market, Market efficiency, Spatial dependence, Spatial quantile regression, Spatial volatility clustering",

author = "Jiyoung Chae and Bera, {Anil K.}",

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AU - Bera, Anil K.

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N2 - This paper empirically tests housing market efficiency in the spatial dimension by using the spatial autoregressive conditional heteroskedastic (ARCH) and spatial quantile regression models. The tests were conducted in terms of both housing returns and squared returns (volatility). The sale price data used is from Cook County residential MLS for the years 2010–2016. The main findings are that housing returns are not spatially correlated but squared returns are spatially correlated, and the spatial dependence of squared returns seems to be stronger for higher squared return quantiles.

AB - This paper empirically tests housing market efficiency in the spatial dimension by using the spatial autoregressive conditional heteroskedastic (ARCH) and spatial quantile regression models. The tests were conducted in terms of both housing returns and squared returns (volatility). The sale price data used is from Cook County residential MLS for the years 2010–2016. The main findings are that housing returns are not spatially correlated but squared returns are spatially correlated, and the spatial dependence of squared returns seems to be stronger for higher squared return quantiles.

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KW - Spatial volatility clustering

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Spatial Market Inefficiency in Housing Market: A Spatial Quantile Regression Approach

Abstract

Keywords

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