Understanding Rationality and Disagreement in House Price Expectations
Professional house price forecast data are consistent with a rational model where agents must learn about the parameters of the house price growth process and the underlying state of the housing market. Slow learning about the long-run mean can generate forecast bias, a response of forecasts to lagged realizations, sluggish response of forecasts to contemporaneous realizations, and over-reaction to forecast revisions. Introducing behavioral biases, either over-confidence or diagnostic expectations, helps the model further improve its predictions for short-horizon over-reaction and dispersion. Using panel data for a cross-section of forecasters and a term structure of forecasts are important for generating these results.
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Copy CitationZigang Li, Stijn Van Nieuwerburgh, and Wang Renxuan, "Understanding Rationality and Disagreement in House Price Expectations," NBER Working Paper 31516 (2023), https://doi.org/10.3386/w31516.Download Citation
Published Versions
Zigang Li & Stijn Van Nieuwerburgh & Wang Renxuan & Tarun Ramadorai, 2026. "Understanding Rationality and Disagreement in House Price Expectations," The Review of Financial Studies, vol 39(2), pages 297-342.