Imperfect Information and Investor Inferences From Housing Price Dynamics
研究了房价动态中可能符合理性学习而非非理性反馈交易的特征，发现时间和空间扩散模式更支持理性成分，且人口密度加速了信息扩散。
We examine characteristics of housing price dynamics that may be consistent with rational learning and not simply irrational feedback trading. We find significant patterns of temporal and spatial diffusion that are more amenable to explanations that allow for rational components. First, we execute our tests not simply on housing price changes, but on town‐by‐town differentials from regional average price changes. Second, we find significant relationships with own and neighboring town differentials, but not with control groups of non‐neighboring towns. Third, we find that population density, a proxy for scale economies in information production, accelerates the diffusion process. Test were performed on quarterly data for large samples from Connecticut and the San Francisco area, employing method of moments estimators.