Understanding Rationality and Disagreement in House Price Expectations

Zigang Li, Stijn Van Nieuwerburgh and Wang Renxuan

The Review of Financial Studies, 2026, vol. 39, issue 2, 297-342

Abstract: 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 generates overreaction to forecast revisions and a modest response of forecasts to lagged realizations. Heterogeneity in signals and priors about the long-run mean helps the model account for cross-sectional dispersion in forecasts. Introducing behavioral frictions helps improve the model’s predictions for short-horizon overreaction and dispersion. Using a cross-section of forecasters and a term structure of forecasts are crucial for inference.

Keywords: C32; D84; G41; R32 (search for similar items in EconPapers)
Date: 2026
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Working Paper: Understanding Rationality and Disagreement in House Price Expectations (2023)
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