Housing Markets: Auctions, Microstructure Noise, and Weekly Patterns

Abstract

This paper studies volatility in the housing markets by developing dynamic
search and matching models with bidding wars, or auctions. The models’ moments
are aggregated to the statistics on the offer acceptance dates and the closing dates
to emphasize the differences between these statistics in the data. I find that up to
70% of the volatility of monthly home sales and listings in the Los Angeles metro
area stems from the intra-week patterns in the data and the microstructure noise
in the models. The remaining volatility can be generated by adding exogenous
shocks to the models.

Keywords: housing, real estate, volatility, microstructure, search and matching, pricing, liquidity, Nash bargaining, auctions, bidding wars

JEL Classification: E30, C78, D44, R21, E44, R31, D83