Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment

Authors

  • Rangan Gupta Department of Economics, University of Pretoria, Pretoria, 0002
  • Chi Keung Marco Lau Huddersfield Business School, University of Huddersfield, Huddersfield, HD1 3DH
  • Wendy Nyakabawo Department of Economics, University of Pretoria, Pretoria, 0002

DOI:

https://doi.org/10.6000/1929-7092.2020.09.05

Keywords:

Housing sentiment, housing market returns and volatility, higher-order nonparametric causality-in-quantiles test, overall and regional US economy.

Abstract

This paper examines the predictive ability of housing-related sentiment on housing market volatility for 50 states, District of Columbia, and the aggregate US economy, based on quarterly data covering 1975:3 and 2017:3. Given that existing studies have already shown housing sentiment to predict movements in aggregate and state-level housing returns, we use a k-th order causality-in-quantiles test for our purpose, since this methodology allows us to test for predictability for both housing returns and volatility simultaneously. In addition, this test being a data-driven approach accommodates the existing nonlinearity (as detected by formal tests) between volatility and sentiment, besides providing causality over the entire conditional distribution of (returns and) volatility. Our results show that barring 5 states (Connecticut, Georgia, Indiana, Iowa, and Nebraska), housing sentiment is observed to predict volatility barring the extreme ends of the conditional distribution. As far as returns are concerned, except for California, predictability is observed for all of the remaining 51 cases.

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Published

2020-01-29

Issue

Section

Articles