We propose a new measure for housing sentiment and show that it accurately tracks expectations about future house price growth rates. We construct the housing sentiment index using partial least squares on questions related to consumers' opinions of buying conditions for houses from University of Michigan's consumer survey. We find that housing sentiment strongly outperforms several macroeconomic variables typically used to forecast house prices. An in-sample forecast regression using quarterly data over the period 1975-2014 shows that housing sentiment is able to explain 48 percent of next quarter's national house price growth. Out-of-sample forecast regressions yield similar results. The strong predictive power of the sentiment index is robust across forecast horizons and holds at the state-level.
|Publisher||Department of Business and Management|
|Number of pages||31|
|Publication status||Published - 2016|
- Housing sentiment
- house price forecastability
- partial least squares
- dynamic model averaging