Auctions, Microstructure Noise, and Weekly Patterns in Housing Markets

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 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 sales and listings in the Los Angeles metro area stems from the intra-week patterns in the data and endogenous dynamics in the models with the microstructure noise. The remaining volatility can be generated from 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