INFORMATION FRICTIONS AND HOUSING MARKET DYNAMICS |
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| Authors: | Elliot Anenberg |
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| Institution: | Federal Reserve Board, U.S.A.This is a revised version of my job market paper. I am very grateful to my advisor, Pat Bayer, and committee members Jimmy Roberts, Andrew Sweeting, and Chris Timmins for comments. I also thank Peter Arcidiacono, Ed Kung, Jon James, Steve Laufer, Robert McMillan, Guido Menzio, Karen Pence, and Jessica Stahl. An earlier version of this article was circulated under the title “Uncertainty, Learning, and the Value of Information in the Residential Real Estate Market.” The analysis and conclusions set forth are those of the author and do not indicate concurrence by other members of the research staff or the Board of Governors. |
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| Abstract: | I examine the effects of seller uncertainty over their home value on the housing market. Using evidence from home listings and transactions data, 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 microsearch model of the home selling problem with Bayesian learning. The estimated model highlights how information frictions help to explain the microdecisions of sellers and how these microdecisions affect aggregate market dynamics. The model generates a significant microfounded momentum effect in short‐run aggregate price appreciation rates. |
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