Housing Markets: Auctions, Microstructure Noise, and Weekly Patterns

88 Pages Posted: 8 Jun 2017 Last revised: 31 Jan 2025

See all articles by Alina Arefeva

Alina Arefeva

UW Madison - Wisconsin School Business

Multiple version iconThere are 2 versions of this paper

Date Written: January 15, 2020

Abstract

This paper examines the drivers of housing market volatility through dynamic search-and-matching models that incorporate auctions, a prevalent yet understudied mechanism in housing transactions. Two versions of the model are developed: one where buyers visit homes randomly and another where search is directed by seller reserve prices. The analysis demonstrates that microstructure noise—arising from individual decisions and the interaction of search frictions and auctions—generates persistent volatility, even in large markets. The paper also identifies systematic weekly patterns in housing activity, which account for up to 60% of monthly variation in sales and listings. Together, microstructure noise and weekly patterns explain 70-80% of market volatility, with the remainder driven by exogenous shocks. These findings underscore the importance of auctions, microstructure noise, and weekly patterns in understanding housing market dynamics.

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

Suggested Citation

Arefeva, Alina, Housing Markets: Auctions, Microstructure Noise, and Weekly Patterns (January 15, 2020). Available at SSRN: https://ssrn.com/abstract=2980095 or http://dx.doi.org/10.2139/ssrn.2980095

Alina Arefeva (Contact Author)

UW Madison - Wisconsin School Business ( email )

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Madison, WI 53706
United States

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