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Dynamic Relations Between Housing Markets, Stock Markets, and Uncertainty in Global Cities: A Time-Frequency Approach

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This paper considers dynamic features of house prices in metropolises that are characterized by high degree of internationalization. Using the wavelet coherency procedure the degree of co-movement and causality between housing, stock markets and macroeconomic uncertainty are investigated. In addition, the existence of volatility spillover across housing markets is assessed in the time-frequency domain using a novel procedure that involves combining the wavelet decomposition with time varying parameter vector autoregression model. The results highlight that the clustering of global business in a limited number of metropolises that act as “global hubs” leaves local housing markets exposed to international shocks and volatility spillover. The empirical analysis suggests that the correlations between real estate and stock markets from one side, and real estates and uncertainty on the other side, intensify during the turmoil periods, but causality and co-movement relationships appear, predominately, in the medium-, long run period.

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  • Huthaifa Alqaralleh & Canepa, Alessandra & Gazi Salah Uddin, 2022. "Dynamic Relations Between Housing Markets, Stock Markets, and Uncertainty in Global Cities: A Time-Frequency Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202213, University of Turin.
    • Handle: RePEc:uto:dipeco:202213
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    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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