Search and Predictability of Prices in the Housing Market

63 Pages Posted: 15 Mar 2021

See all articles by Stig Møller

Stig Møller

Aarhus University - CREATES

Thomas Pedersen

Aarhus University - Department of Economics and Business Economics

Erik Christian Montes Schütte

Aarhus University - CREATES; DFI

Allan Timmermann

University of California, San Diego (UCSD) - Rady School of Management

Date Written: March 2021

Abstract

We develop a new housing seach index (HSI) extracted from online search activity on a limited set of keywords related to the house buying process. We show that HSI has strong predictive power for subsequent changes in house prices, both in-sample and out-of-sample, and after controlling for the effect of commonly used predictors. Compared to the stock market, online search has much stronger predictive power over house prices and its effect also lasts longer. Variation in housing search is a particularly strong predictor of subsequent price changes in markets with inelastic housing supply and high speculation.

JEL Classification: C10, E17, G10, R3

Suggested Citation

Møller, Stig and Pedersen, Thomas and Schütte, Erik Christian Montes and Timmermann, Allan, Search and Predictability of Prices in the Housing Market (March 2021). CEPR Discussion Paper No. DP15875, Available at SSRN: https://ssrn.com/abstract=3805290

Stig Møller (Contact Author)

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Thomas Pedersen

Aarhus University - Department of Economics and Business Economics ( email )

Fuglesangs Allé 4
Aarhus V, 8210
Denmark

Erik Christian Montes Schütte

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Allan Timmermann

University of California, San Diego (UCSD) - Rady School of Management ( email )

9500 Gilman Drive
Rady School of Management
La Jolla, CA 92093
United States

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