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

Rangan Gupta, Marco Lau Chi Keung, Wendy Nyakabawo

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)30-46
Number of pages17
JournalJournal of Reviews on Global Economics
Publication statusPublished - 29 Jan 2020


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