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Do Spatial Characteristics Affect Housing Prices in Korea? : Evidence from Bayesian Spatial Models

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  • KWON, Heeeun
  • HWANG, Beom Seuk

Abstract

This paper employs a Bayesian conditional autoregressive model to geographically analyze housing prices in Seoul, Korea from a demographic perspective. Spatial dependence patterns are detected between 424 administrative districts in Seoul, and the parameter estimation will be implemented via a Bayesian approach. We confirm that the proposed model with spatial heterogeneity presents superior performance than the other common spatial regression models. We also demonstrate that the proposed model offers the flexibility to resent various global spatial autocorrelation, and that the model adequately captures the model variablesʼ effect on housing prices.

Suggested Citation

  • KWON, Heeeun & HWANG, Beom Seuk, 2023. "Do Spatial Characteristics Affect Housing Prices in Korea? : Evidence from Bayesian Spatial Models," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 64(2), pages 109-124, December.
    • Handle: RePEc:hit:hitjec:v:64:y:2023:i:2:p:109-124
    DOI: 10.15057/hje.2023006
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    More about this item

    Keywords

    Bayesian inference; conditional autoregressive model; Markov chain Monte Carlo (MCMC); spatial dependence;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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