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Erschienen in: The Journal of Real Estate Finance and Economics 2/2017

29.02.2016

List Prices in the US Housing Market

verfasst von: Darren K. Hayunga, R. Kelley Pace

Erschienen in: The Journal of Real Estate Finance and Economics | Ausgabe 2/2017

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Abstract

A seller sets the list price based upon their ex-ante perception of the trade-off between marketing duration versus transaction price, which depends on the liquidity of the property and the depth of the market. As such, list prices reflect property, market, and seller characteristics. In addition, Genesove and Mayer (2001) and Bokhari and Geltner (2011) use prospect theory to motivate how expected nominal losses and gains from sale can also influence list prices. We consider these multiple factors affecting list prices through a rich dataset from the National Association of Realtors, which contains variables on seller motivations, structure liquidity, and other difficult to observe variables such as seller age, race, and income.

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Fußnoten
1
When setting list prices, TOM and LPR are future expected outcomes. Nevertheless, we formally test for possible simultaneity and find expected TOM and LPR are in fact endogenous. We use instrument variables and two stage least squares to treat the endogeneity.
 
2
Seminal papers include Stigler (1961); McCall (1970), and Mortensen (1970).
 
3
Theoretical studies include Wu and Colwell (1986); Haurin (1988); Quan and Quigley (1991); Salant (1991); Horowitz (1992); Yavaş and Yang (1995); Arnold (1999); Krainer and LeRoy (2002); Haurin et al. (2010); Deng et al. (2012); Stacey (2013), and Albrecht, Gautier, and Vroman (2016).
 
4
See Springer (1996); Harding et al. (2003b); Clauretie and Daneshvary (2011); Goodwin and Johnson (2013), and Aroul and Hansz (2014).
 
6
It is more intuitive to code expected gains as positive and losses as negative. However, subsequent interpretation of the gain and loss variables may prove challenging. The data exhibit a positive relation between expected nominal losses and list prices i.e., the greater the expected loss the higher the list price. If expected losses are coded as negative, the positive relation will yield a negative slope coefficient on loss. To avoid confusion caused by the negative parameter estimate being an increase in list prices, we follow the literature in coding the loss and gain variables.
 
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Metadaten
Titel
List Prices in the US Housing Market
verfasst von
Darren K. Hayunga
R. Kelley Pace
Publikationsdatum
29.02.2016
Verlag
Springer US
Erschienen in
The Journal of Real Estate Finance and Economics / Ausgabe 2/2017
Print ISSN: 0895-5638
Elektronische ISSN: 1573-045X
DOI
https://doi.org/10.1007/s11146-016-9555-2

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