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The more, the better? Forecasting gains from high-frequency housing prices in a Markov-switching dynamic factor model

Published online by Cambridge University Press:  20 August 2021

MeiChi Huang
MeiChi Huang*
Affiliation:
Department of Business Administration, National Taipei University, 151, University Rd., San Shia District, New Taipei City, 23741 Taiwan, Republic of China
*
Email: meichihuang@mail.ntpu.edu.tw.
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Abstract

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This paper extracts housing boom-bust cycle signals from metropolitan statistical area (MSA)-level housing prices using a Markov-switching dynamic factor model. To mitigate the estimation bias, it utilizes high-frequency housing prices that follow the methodology of the monthly Case–Shiller house price indices. The housing bust phases specified from weekly and daily housing prices precede those based on monthly prices by approximately 2 years. MSAs with top signal-to-noise ratios offer greater marginal contributions to improvements in forecasting housing cycles than MSAs with bottom ratios for all frequencies. The results highlight the importance of indicator quality and provide evidence against “The more, the better” since incorporating more MSA-level housing prices into housing factors does not guarantee more satisfactory housing cycle forecasts.

Keywords

MSA (Metropolitan Statistical Area)-level housing priceMarkov-switching dynamic factor modelhousing cyclesignal-to-noise ratio91B84

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 27 , Issue 1 , January 2023, pp. 93 - 110
Copyright
© Cambridge University Press 2021

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