High-Frequency Predictability of Housing Market Movements of the United States: The Role of Economic Sentiment
Mehmet Balcilar (),
Elie Bouri (),
Rangan Gupta () and
No 202066, Working Papers from University of Pretoria, Department of Economics
We analyse the ability of a newspaper-based economic sentiment index of the United States to predict housing market movements using daily data over the period 2nd August, 2007 to 19th June, 2020. For this purpose, we use a k-th order nonparametric causality-in-quantiles test, which allows us to test for predictability over the entire conditional distribution of not only housing returns, but also volatility, by controlling for misspecification due to nonlinearity and structural breaks â€“ both of which we show to exist between housing returns and the economic sentiment index. Our results show that economic sentiment does indeed predict housing returns (unlike the conditional mean-based, i.e., linear, Granger causality test and volatility), barring the extreme upper ends of the respective conditional distributions. Our results have important implications for academics, policymakers, and investors.
Keywords: Economic Sentiment; Housing Returns and Volatility; Higher-Order Nonparametric Causality in Quantiles Test (search for similar items in EconPapers)
JEL-codes: C22 C32 R30 (search for similar items in EconPapers)
Pages: 18 pages
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Journal Article: High-Frequency Predictability of Housing Market Movements of the United States: The Role of Economic Sentiment (2021)
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