In models of optimal household behavior, the value of housing affects consumption, savings and other variables. But homeowners do not know the value of their house for certain until they sell, so while they live in their home they must rely on local house price data to estimate its value. This article uses data from the recent housing boom and bust to demonstrate that changes in households' self-assessed home values are strongly consistent with the predictions of a model in which households optimally filter available house price data. Specifically, we show that self-assessed house prices did not increase as rapidly as house price indexes during the boom and did not decline as severely during the bust. A Kalman filter model nearly perfectly replicates these data. These findings have direct implications for economists studying asking prices during booms and busts, optimal default decisions and other key housing-related phenomena.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics