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Erschienen in: The Journal of Real Estate Finance and Economics 3/2013

01.10.2013

Agent Change and Seller Bargaining Power: A Case of Principal Agent Problem in the Housing Market

verfasst von: Nasser Daneshvary, Terrence M. Clauretie

Erschienen in: The Journal of Real Estate Finance and Economics | Ausgabe 3/2013

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Abstract

When a seller hires an agent to sell his/her property, a successful outcome depends on the list price, marketing time, unobserved relative bargaining power of the buyers and sellers, and the effort levels of the seller and the seller’s agent. A divergence with respect to the list/transaction prices and the expected effort levels between seller and agent will create a principal-agent interest conflict. This conflict in some cases results in an agent change before the house is sold. The change will reduce the relative bargaining power of the seller, affecting the observed marketing time and transaction price. This study estimates the effects of an agent change on marketing time and transaction price after controlling for degree of overpricing, list-price revisions, marketing time, and endogenous selection bias. Our results show that: (1) on average, an agent change increases the marketing time by about 3 months and adversely affects the transaction price by about 2.7 %. Furthermore, we found that an agent change before the expiration of the listing contract, compared to that of after the expiration, has a smaller effect on the marketing time (2.3 vs. 3.8 months) and has a smaller transaction price discount (2.1 % vs. 4.2 %).

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Fußnoten
1
Theoretically, list price may also serve as a signal of a seller’s motivation (Yavas and Yang 1995) or a signal of a seller’s patience (Arnold 1999). Using various measures of seller motivation, including DOP, Springer (1996); Glower et al. (1998); Knight (2002); and Anglin et al. (2003) found an empirical effect of motivation on TOM.
 
2
The study by Sirmans et al. (2005) identified 18 hedonic models that included TOM as an independent variable in the price equation. In only one study, the coefficient was positive. In the remaining 17 studies, the coefficient of TOM was either negative (8) or not significant (9), mostly depending on whether TOM was entered as an endogenous variable or not.
 
3
There are other alternative possible reasons for a potential incentive-compatibility problem, such as information asymmetry or optimal risk-sharing between the seller and agent. For examples, see Arnold (1992) and Anglin and Arnott (1991).
 
4
In fact, one the authors of this paper, as a very interested buyer, experienced a situation where his agent discouraged him to see a house for sale. The agent stated that this owner (seller) is very picky when it comes to showing the house and will not negotiate the price or any other arrangements. The buyer ended up not seeing the house.
 
5
Springer’s (1996) empirical results reveal a price discount for houses that are sold by sellers that are eager, motivated, anxious, relocated, foreclosed on, and have vacant houses. Only foreclosed homes have a significantly reduced marketing time.
 
6
Our conversations with several real estate agents/brokers also revealed that often the withdrawal and agent change are due to sellers’ unrealistically high valuation of the property and/or sellers’ impatience.
 
7
For examples of TOM and price endogeniety studies see Sirmans et al. (1991); Yang and Yavas (1995); Yavas and Yang (1995); Knight (2002); Harding et al. (2003); Clauretie and Thistle (2007); and Clauretie and Daneshvary (2009).
 
8
For econometric reasons to include all the exogenous variables that are in Eq. (1) in Eq. (2), see Wooldridge (2009, pp. 518–522). For an intuitive explanation in the context of the price-TOM relationship, see Anglin et al. (2003, p. 98).
 
9
Again, note that the DOP estimation already includes the house characteristics and market condition variables, vector X n .
 
10
Given the labor intensity of creating a sample and the potential problems associated with neighborhoods’ heterogeneity, we restricted our empirical analyses to a sample of two relatively homogeneous neighborhoods.
 
11
House prices in the two neighborhoods gradually increased during 2005, were relatively flat during 2006, and gradually declined during 2007, resulting in a quadratic time trend.
 
12
All the estimated equations in this paper are heteroskedasticity corrected.
 
13
We also estimated a probit model that included house characteristics and market conditions variables, as well as DOP and TOM. As expected, due to inclusion of DOP in the equation, almost none of the house characteristic variables were statistically significant. The estimated coefficient of TOM and DOP did not change between the two models.
 
14
Given that all the explanatory variables in the price equation are included in the TOM estimated equation of TOM, via DOP, there is no need to correct the covariance matrix and adjust the standard errors of the price equation. When we do correct the standard errors, however, the significant levels of all the variables stay almost the same.
 
15
We also calculated an index of the property atypicality, estimated as defined by Haurin (1988), and included in the TOM and price equations. The coefficients of the index were not significant and had no impact on the size or significance of the other estimated coefficients in the models.
 
16
To check the robustness of our results, we tested our models by using a linear probability model for the agent change equation. The results are almost identical to those reported here that are based on a probit equation.
 
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Metadaten
Titel
Agent Change and Seller Bargaining Power: A Case of Principal Agent Problem in the Housing Market
verfasst von
Nasser Daneshvary
Terrence M. Clauretie
Publikationsdatum
01.10.2013
Verlag
Springer US
Erschienen in
The Journal of Real Estate Finance and Economics / Ausgabe 3/2013
Print ISSN: 0895-5638
Elektronische ISSN: 1573-045X
DOI
https://doi.org/10.1007/s11146-012-9369-9

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