Chris Cunningham, Kristopher Gerardi, and Lily Shen
Working Paper 2022-11a
September 2022 (Revised April 2023)

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Despite the prevalence and high cost of real estate agents, there is limited empirical evidence as to the nature or efficacy of their services. In this paper we estimate real estate agents’ value-added when both selling and buying homes using micro data from three large Multiple Listing Services (MLS). We find that homeowners who forgo a conventional real estate agent, but who list their homes on the MLS via a flat-fee broker, sell for between 1 and 4 percent more on average before commission while taking only a few days longer to sell. However, there is an important trade-off as these sellers are significantly less likely to complete a sale. We further show that these average effects mask a significant amount of real estate agent heterogeneity. Using a novel aspect of our data, which allows us to identify and track agents over time, we estimate the distributions of real estate agent fixed effects in both hedonic and time on the market models. We document a large amount of heterogeneity across agents in both outcomes. Finally, we identify and characterize top-performing agents and show that their performance is persistent, they are rewarded by the market in terms of future business, and they appear to perform their best in cold markets when properties are more difficult to sell.

JEL classification: D01, D8, G5, L8, R31

Key words: market intermediaries, agency theory, real estate, brokerage labor market, prices, time on the market

The authors thank Brent Ambrose, Salome Baslandze, Danny Ben-Shahar, Jim Conklin, Arash Dayani, Simon Fuchs, Daniel Greene, Sven Damen, Qu Feng, Georg Kirchsteiger, He Tai-Sen, Veronika Penciakova, Mark Jensen, Vincent Yao, Blerina Zykaj, and seminar participants at the University of Florida, the University of Georgia, the University of Antwerp, ULB, the 2022 SMU-Jinan Conference on Urban and Regional Economics, UEA, AsRES-AREUEA Joint Conference, and the ASSA-AREUEA conference for helpful comments and suggestions. They also thank Stephanie Sezen for excellent research assistance. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.

Please address questions regarding content to Chris Cunningham, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309; Kristopher Gerardi, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309; or Lily Shen, Clemson University, 145 Business Building, Clemson, SC 29634.

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