Google Search Queries, Foreclosures, and House Prices
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Google Search Queries, Foreclosures, and House Prices Damian S. Damianov 1
& Xiangdong
Wang 1 & Cheng Yan 2
# The Author(s) 2020
Abstract We study whether Google search behavior for “mortgage assistance” and “foreclosure help” aggregated in the mortgage default risk indicator (MDRI) of Chauvet et al. (2016) helps predict future house prices and foreclosures in local residential markets. Using a long-run equilibrium model, we disaggregate house prices into their fundamental and bubble components, and we find that MDRI dampens both components of house prices. This negative relationship is robust to various model specifications and time horizons. A higher intensity of search online, however, is associated with lower future foreclosure rates. We also find that foreclosure rates increase after a decline in the fundamental component of home values, but are not sensitive to their transitory (bubble) component. Foreclosure rates are higher in metropolitan areas located in nonrecourse states. We interpret these findings as evidence for strategic household behavior. Our paper sheds new light on the predictive power of household sentiment derived from Google searches on prices and foreclosure rates in local housing markets. JEL Classification D12 . D14 . E51 . G21 . G33 . L85 . R31 Keywords Mortgage default risk . Foreclosures . House prices
* Xiangdong Wang [email protected] Damian S. Damianov [email protected] Cheng Yan [email protected]
1
Durham University Business School, Mill Hill Lane, Durham DH1 3LB, UK
2
Essex Business School, University of Essex, Colchester CO4 3SQ, UK
D. S. Damianov et al.
Introduction The subprime mortgage crisis serves as a powerful reminder of the seismic impact that the financial behavior of homeowners can exert on the U.S. financial system and economy. In the aftermath of the financial crisis, a voluminous literature has developed that aims to shed light on a key relationship in the run-up to the crisis: the interdependence between downward spiraling house prices and rising mortgage default rates. A better grasp of this issue was a matter of urgency during the housing market downturn as policymakers evaluated initiatives to curb the wave of foreclosures and help ‘underwater’ homeowners to stay in their homes (Calomiris et al. 2013; Foote et al. 2008). Yet, the topic remains high on the public policy agenda as it lays bare the tension between housing affordability and financial stability, and carries implications for mortgage market design and macro-prudential regulation. In the post-crisis period, there has also been substantial interest in the development of mortgage default risk indicators which can serve as a “warning signal” for ensuing future turmoil in housing and mortgage markets. The construction of such forwardlooking sentiment indices from household survey data (such as the consumer sentiment survey of the University of Michigan) however has proven elusive. Household surveys are constrained with respect to geographical coverage and number of par
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