NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Learning about the Neighborhood

Zhenyu Gao, Michael Sockin, Wei Xiong

NBER Working Paper No. 26907
Issued in March 2020
NBER Program(s):Asset Pricing, Corporate Finance, Economic Fluctuations and Growth, Monetary Economics

We develop a model to analyze information aggregation and learning in housing markets. In the presence of pervasive informational frictions, housing prices serve as important signals to households and capital producers about the economic strength of a neighborhood. Our model provides a novel mechanism for amplification through learning in which noise from the housing market can propagate to the local economy, distorting not only migration into the neighborhood, but also the supply of capital and labor. We provide consistent evidence of our model implications for housing price volatility and new construction using data from the recent U.S. housing cycle.

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Document Object Identifier (DOI): 10.3386/w26907

 
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