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Published in: The Journal of Real Estate Finance and Economics 1/2020

01-05-2019

Paying for a Name? Comparing the Performance of Franchised Real Estate Brokerage Firms

Author: Stephen L. Locke

Published in: The Journal of Real Estate Finance and Economics | Issue 1/2020

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Abstract

This paper compares the relative performance of franchised and independent real estate brokerage firms. One problem that arises when comparing the performance of two different brokerage types is that agents may self-select into a particular type. The empirical methods used control for potential self-selection by using within-agent variation in franchise affiliation for agents who have worked for both types of brokerage firms. The results suggest that agents self-select into particular real estate brokerage types and firms. Thus, failing to account for self-selection can lead to substantial bias.

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Footnotes
1
Zumpano et al. (1996) showed that buyers with high opportunity costs and little information about the local market are more likely to use a broker to search for a house.
 
2
All firms that are part of a traditional franchise are considered in this study. A separate variable is used for firms operated locally but affiliated with a nationwide company such as HomeServices of America. A single dummy variable was created for each franchise even if multiple branches were observed.
 
3
For example, Carson and Dastrup (2013) reported considerable spatial variation in housing prices during the Great Recession. Across metropolitan areas, housing prices declined none at all to more than 60%.
 
4
A summary of the fees associated with each real estate franchise can be found on the National Association of Realtor’s website at https://​magazine.​realtor/​sites/​default/​files/​asset/​document/​2017_​Franchise_​Report.​pdf.
 
5
This may occur if a broker attempts to maximize their revenue though increasing the number of properties sold (at a lower price) instead of maximizing the sales price for each individual transaction.
 
6
This selection process and more favorable commission structure is discussed in Munneke and Yavas (2001).
 
7
All sales prices were converted to December 2017 dollars using the CPI. Transactions with missing housing characteristics, office or agent information, or price data were dropped from the sample.
 
8
An alternative approach would compare properties that were sold, not listed, by franchised and independent real estate brokers. The current focus is on the listing broker as they are chosen by the home seller.
 
9
It is important to note that overpriced does not imply expensive. A house priced at $150,000 could take much longer to sell than a house priced at $300,000 if the $150,000 house is priced 30% higher than a comparable house and the $300,000 house is priced 30% less than a comparable house. The degree of the overpricing variable holds constant the price of the house compared with other properties that could be considered substitutes.
 
10
The days on market regressions could have been estimated using a survival model as in Rutherford and Yavas (2012). For ease of interpretation, the empirical approach more closely follows Levitt and Syverson (2008), in which dependent variables are the logged sales price and days on market.
 
11
For simplicity, the estimated coefficients for all structural housing characteristics are not shown.
 
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Metadata
Title
Paying for a Name? Comparing the Performance of Franchised Real Estate Brokerage Firms
Author
Stephen L. Locke
Publication date
01-05-2019
Publisher
Springer US
Published in
The Journal of Real Estate Finance and Economics / Issue 1/2020
Print ISSN: 0895-5638
Electronic ISSN: 1573-045X
DOI
https://doi.org/10.1007/s11146-019-09702-2

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