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Testing for exuberance in house prices using data sampled at different frequencies

Author

Listed:
  • Otero Jesús

    (Facultad de Economía, Universidad del Rosario, Bogotá, Colombia)

  • Panagiotidis Theodore
  • Papapanagiotou Georgios

    (Department of Economics, University of Macedonia, Thessaloniki, Greece)

Abstract

We undertake Monte Carlo simulation experiments to examine the effect of changing the frequency of observations and the data span on the Phillips, P. C. B., S. Shi, and J. Yu. 2015. “Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500.” International Economic Review 56 (4): 1043–78 generalised supremum ADF (GSADF) test for explosive behaviour via Monte Carlo simulations. We find that when a series is characterised by multiple bubbles (periodically collapsing), decreasing the frequency of observations is associated with profound power losses for the test. We illustrate the effects of temporal aggregation by examining two real house price data bases, namely the S&P Case–Shiller real house prices and the international real house price indices available at the Federal Reserve Bank of Dallas.

Suggested Citation

  • Otero Jesús & Panagiotidis Theodore & Papapanagiotou Georgios, 2022. "Testing for exuberance in house prices using data sampled at different frequencies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(5), pages 675-691, December.
    • Handle: RePEc:bpj:sndecm:v:26:y:2022:i:5:p:675-691:n:3
    DOI: 10.1515/snde-2021-0030
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