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Multi-scale causality and extreme tail inter-dependence among housing prices

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  • Kang, Sang Hoon
  • Uddin, Gazi Salah
  • Ahmed, Ali
  • Yoon, Seong-Min

Abstract

This study explores multi-scale causality and extreme tail dependence structures among housing prices in four cities: Seoul, Hong Kong, Tokyo, and New York. We apply two different and unique approaches in our analysis of monthly housing price data: (i) the frequency domain Granger casualty test and (ii) the non-parametric copula test. Employing the frequency domain casualty test, we find both bi-directional and uni-directional causalities at different frequency bands. Additionally, the nonlinear copula estimates indicate asymmetric tail dependence for housing price pairs in all four cities. Finally, the Hong Kong housing market has a greater effect on the Seoul and Tokyo housing markets than does the New York housing market.

Suggested Citation

  • Kang, Sang Hoon & Uddin, Gazi Salah & Ahmed, Ali & Yoon, Seong-Min, 2018. "Multi-scale causality and extreme tail inter-dependence among housing prices," Economic Modelling, Elsevier, vol. 70(C), pages 301-309.
  • Handle: RePEc:eee:ecmode:v:70:y:2018:i:c:p:301-309
    DOI: 10.1016/j.econmod.2017.11.014
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    References listed on IDEAS

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    More about this item

    Keywords

    Housing prices; Inter-dependence; Multi-scale causality; Non-parametric copula test; Tail distribution;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • 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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