House price dynamics: Fundamentals and expectations

Abstract

We investigate whether expectations that are not fully rational have the potential to explain the evolution of house prices and the price-to-rent ratio in the United States. First, a Lucas type asset-pricing model solved under rational expectations is used to derive a fundamental value for house prices and the price-rent ratio. Although the model can explain the sample average of the price-rent ratio, it does not generate the volatility and persistence observed in the data. Then, we consider an intrinsic bubble model and two models of extrapolative expectations developed by Lansing (2006Lansing ( , 2010 in applications to stock prices: one that features a constant extrapolation parameter and one in which the extrapolation coefficient depends on the dividend growth process. We show that these last two models are equally good at matching sample moments of the data. However, a counterfactual experiment shows that only the extrapolative expectation model with timevarying extrapolation coefficient is consistent with the run up in house prices observed over the 2000-2006 period and the subsequent sharp downturn. JEL classification: E3, E65, R21 Bank classification: Asset pricing; Domestic demand and components; Economic models RésuméLes auteures tentent de déterminer si l'évolution des prix des maisons et du ratio de ces prix aux loyers aux États-Unis peut s'expliquer par le fait que les anticipations ne soient pas entièrement rationnelles. Elles résolvent d'abord un modèle d'évaluation des actifs à la Lucas sous l'hypothèse de rationalité des anticipations afin d'obtenir une estimation du niveau fondamental des prix des maisons et du ratio prix/loyers. Même si le modèle parvient à restituer la moyenne empirique du ratio, il ne génère pas la volatilité et la persistance observées dans les données. Les auteures considèrent ensuite un modèle de bulle intrinsèque ainsi que deux modèles dotés d'anticipations extrapolatives mis au point par Lansing (2006Lansing ( et 2010

Explaining House Price Dynamics: Isolating the Role of Nonfundamentals

“…The model however can approximately match the volatility of the price–rent ratio observed in the data if the agents employ a simple moving‐average forecast rule for the price–rent ratio that places a large weight on the most recent observation, that is, “backward‐looking, extrapolative‐type expectations.” The authors assert that the moving‐average model, which predicts a positive correlation between expected future returns on housing and the price–rent ratio, is consistent with the survey evidence from real estate and stock markets discussed above. Simulations performed by Granziera and Kozicki () also show that a rational expectations model is unable to explain the recent boom and bust in house prices, whereas asset pricing models with backward‐looking expectations are able to capture observed house price changes and volatility during the 2000s.…”

House Prices, Credit Growth, and Excess Volatility: Implications for Monetary and Macroprudential Policy

“…Adam, et al (2012) show that the introduction of constant-gain learning in a small open economy can help account for recent cross-country patterns in house prices and current account dynamics. Granziera and Kozicki (2012) show that a simple Lucas-type asset pricing …”

House Prices, Expectations, and Time-Varying Fundamentals

“…Gelain, et al (2013) show that the introduction of simple moving-average forecast rules for a subset of agents can significantly magnify the volatility and persistence of house prices and household debt in a standard DSGE model with housing. Granziera and Kozicki (2012) show that a simple Lucastype asset pricing model with backward-looking, extrapolative-type expectations can roughly match the run-up in U.S. house prices from 2000 to 2006 as well as the subsequent sharp downturn.…”