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Information frictions and housing market dynamics

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  • Elliot Anenberg
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    Abstract

    This paper examines the effects of seller uncertainty over their home value on the housing market. Using evidence from a new dataset on home listings and transactions, I first show that sellers do not have full information about current period demand conditions for their homes. I incorporate this type of uncertainty into a dynamic search model of the home selling problem with Bayesian learning. Simulations of the estimated model show that information frictions help explain short-run persistence in price appreciation rates and a positive (negative) correlation between price changes and sales volume (time on market).

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    Bibliographic Info

    Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2012-48.

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    Date of creation: 2012
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    Handle: RePEc:fip:fedgfe:2012-48

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    1. James A. Berkovec & John L. Goodman, 1996. "Turnover as a Measure of Demand for Existing Homes," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 24(4), pages 421-440.
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    Cited by:
    1. Paul E. Carrillo & Erik Robert De Wit & William D. Larson, 2012. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the U.S. and the Netherlands," Working Papers 2012-11, The George Washington University, Institute for International Economic Policy.

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