EconPapers    
Economics at your fingertips  
 

Hedonic real estate price estimation with the spatiotemporal geostatistical model

Sachio Muto (), Shonosuke Sugasawa and Masatomo Suzuki
Additional contact information
Sachio Muto: The University of Tokyo
Shonosuke Sugasawa: Keio University
Masatomo Suzuki: Yokohama City University

Journal of Spatial Econometrics, 2023, vol. 4, issue 1, 1-37

Abstract: Abstract This study argues that the spatiotemporal geostatistical model for real estate prices, which accounts for and incorporates spatial autocorrelation, can be estimated successfully using the Bayesian Markov Chain Monte Carlo (MCMC) estimation. While this procedure often encounters difficulty in calculating probabilistic densities in the Metropolis–Hastings (MH) algorithm, this study introduces a feasible and practical estimation method, providing useful estimated parameters for the model. Using single-family house transaction data, we show that ordinary estimations of real estate prices, with respect to certain explanatory variables, may lead to the underestimation of standard errors of coefficients for explanatory variables with spatial effects unless spatial autocorrelation is controlled for. Our model also makes it possible to obtain accurate in-sample predictions and moderately improved out-of-sample predictions for real estate prices. This study further estimates a “decay rate:” a diminishing correlation between real estate prices and increasing distance, showing that geographical proximities are likely to have an important impact on real estate prices, especially at a range under 600 m.

Keywords: Real estate pricing; Bayesian econometrics; MCMC; Geostatistical model; Metropolis–Hastings algorithm (search for similar items in EconPapers)
JEL-codes: R39 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s43071-023-00039-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-023-00039-w

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43071

DOI: 10.1007/s43071-023-00039-w

Access Statistics for this article

Journal of Spatial Econometrics is currently edited by Giuseppe Arbia, Lung Fei Lee and James LeSage

More articles in Journal of Spatial Econometrics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2024-02-20
Handle: RePEc:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-023-00039-w