Abstract

We analyze the ability of an index of mortgage default risks (MDRI) for 43 states and 20 metropolitan statistical areas (MSA) of the US derived from Google search queries, in predicting (in- and out-of-sample) housing returns of the corresponding states and MSAs, based on various panel data and time-series approaches. In general, our results tend to prefer the panel data model based on common correlated effects estimation. We highlight that growth in MDRI negatively impacts housing returns within-sample, with predictive gains primarily concentrated beyond a year. These results are robust to alternative out-of-sample periods and econometric frameworks. Given the role of house prices as a leading indicators, our results are of value to policymakers, especially at the longer-run.

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