Do US consumer survey data help beat the random walk in forecasting mortgage rates?

In line with term structure theory, empirical studies suggest that it is difficult to beat the random walk in forecasting long-term interest rates. We ask whether consumer survey data on both mortgage interest rates and expected inflation help beat the random walk in forecasting the 30-year fixed rate mortgage. Using the vector autoregressive (VAR) modeling framework with the mortgage rate and consumer survey data as variables, we generate the mortgage rate forecasts for 1988-2016. Our forecast evaluation test results indicate that the VAR forecasts generally embody useful predictive information above and beyond that contained in the random walk forecasts for 2008-2016. The evidence is weaker for 1988-2007 in the sense that the VAR forecasts fail to outperform the random walk (but still contain distinct useful predictive information). In line with the notion that consumers are 'economically' rational, our findings suggest that consumer survey data have become more informative due to the uncertainty created by the 2008 financial crisis.