House Prices, Expectations, and Time-Varying Fundamentals

Abstract

We investigate the behavior of the equilibrium price-rent ratio for housing in a standard asset pricing model and compare the model predictions to survey evidence on the return expectations of real-world housing investors. We allow for time-varying risk aversion (via external habit formation) and time-varying persistence and volatility in the stochastic process for rent growth, consistent with U.S. data for the period 1960 to 2013. Under fully-rational expectations, the model significantly underpredicts the volatility of the U.S. price-rent ratio for reasonable levels of risk aversion. We demonstrate that the model can approximately match the volatility of the price-rent ratio in the data if near-rational agents continually update their estimates for the mean, persistence and volatility of fundamental rent growth using only recent data (i.e., the past 4 years), or if agents employ a simple moving-average forecast rule for the price-rent ratio that places a large weight on the most recent observation. These two versions of the model can be distinguished by their predictions for the correlation between expected future returns on housing and the pricerent ratio. Only the moving-average model predicts a positive correlation such that agents tend to expect high future returns when prices are high relative to fundamentals-a feature that is consistent with a wide variety of survey evidence from real estate and stock markets.

Explaining House Price Dynamics: Isolating the Role of Nonfundamentals

“…Gelain and Lansing () investigate the behavior of the equilibrium price–rent ratio for housing in a standard asset pricing model and compare the model predictions to survey evidence on the return expectations of real‐world housing investors. They find that the fully rational expectations model significantly underpredicts the volatility of the U.S. price–rent ratio for reasonable levels of risk aversion.…”

“…However, measuring exogenous shifts in the mortgage credit supply function is challenging (Adelino et al , Aron et al ). In fact, other researchers have argued that credit availability and loan‐to‐value (LTV) ratios increased during the recent housing boom, at least in part, because lenders were responding to increased home buyer optimism and speculative demand for housing (Dell'Ariccia, Igan, and Laeven , Goetzmann, Peng, and Yen , Gelain and Lansing ).…”

Discussion of Ling, Ooi, and Le

“…As an alternative to rational expectations, models in which agents employ simple moving‐average forecast rules with exponentially declining weights on past data can generate large swings in asset prices without the need for implausible fundamental shocks (e.g., Gelain, Lansing, and Mendicino , Gelain and Lansing ). A moving‐average forecast rule has the following virtues: (i) it requires only a minimal amount of computational and informational resources; (ii) it is consistent with the empirical findings of Ling, Ooi, and Le who show that past price changes help to predict future price changes; (iii) it implies that investors will tend to expect high future returns after a sustained price run‐up; and (iv) it provides a very good fit of the survey expectations data, which are characterized by a delayed response to macroeconomic news (Coibion and Gorodnichencko ).…”

Explosive bubbles in house prices? Evidence from the OECD countries

“…In the literature, rents are usually considered an important part of fundamentals for house prices, see e.g. Hamilton and Schwab (1985), Meese and Wallace (1994), Himmelberg et al (2005), Gallin (2008), Brunnermeier and Julliard (2008), Campbell et al (2009), Plazzi et al (2010), Cochrane (2011), Ghysels et al (2013), Engsted andPedersen (2014a, 2015), and Gelain and Lansing (2014). For the owner of a house who also lives in the house, rents can be seen as a proxy for the unobservable housing service flow and thus are the equivalent to the dividends that an owner of a stock obtains in the equity market.…”