Learning about the neighborhood

Zhenyu Gao, Michael Sockin, Wei Xiong

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations


We develop a model to analyze information aggregation and learning in housing markets. Households enter a neighborhood by buying houses and consuming each other's final goods. In the presence of pervasive informational frictions, housing prices serve as important signals to households and capital producers about the neighborhood's economic strength. Our model provides a novel amplification mechanism in which noise from housing markets propagates throughout the local economy via learning because of the complementarity in households' decisions, distorting migration into the neighborhood and the supply of capital and labor. We provide consistent evidence based on the recent U.S. housing cycle.

Original languageEnglish (US)
Pages (from-to)4323-4372
Number of pages50
JournalReview of Financial Studies
Issue number9
StatePublished - Sep 1 2021

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics


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