The Effect of Declining Listings on Concentration and Market Structure in Residential Real Estate Brokerage

Abstract

Real estate brokers compete in localized markets generally characterized by low barriers to entry and many participants; however, widespread and consistent price coordination has persisted over multiple decades. Previous research has found that while anecdotal instances of high concentration exist, the industry is relatively unconcentrated. In the past decade and a half, a major recession and a pandemic have significantly reduced housing supply in many markets. We analyzed the competitiveness of the market structure of residential real estate brokerage in 200 individual U.S. markets, varying by size and geographic location, to see whether real estate brokerage markets have become more concentrated. Contrary to expectations, we found that larger firms were more adversely affected by the nationwide reduction in listings and that competitiveness of market structure in this industry was not negatively impacted. Additionally, we were able to engage in a longitudinal comparison in 90 of these markets, 14 years apart, allowing us to observe the impact of a sizable contraction in the overall volume of listings that occurred in 2021.

Keywords:

• Real estate
• market structure
• competition

Acknowledgments

The authors thank Bright Data for assistance in collecting data used for this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 U.S. v. National Association of Realtors (2020).

2 U.S. v. National Association of Realtors (2020). See Scarcella (2023), REALTOR Magazine (2023), and Wall Street Journal (2023) for discussions of how the legal case has evolved.

3 The Herfindahl-Hirschman Index (HHI) is a commonly used measure of market concentration. It is calculated by summing the squared market shares (expressed as percentages) of the participating firms in an industry. Because market shares are squared before adding them, higher market shares are weighed more heavily. HHI ranges from 0 (many atomistic firms) to 10,000 (monopoly). The 2010 USDOJ/FTC Horizontal Merger Guidelines (https://www.justice.gov/atr/horizontal-merger-guidelines-08192010#5c) classify markets with HHI < 1,500 as competitive, markets with 1,500 < HHI < 2,500 as moderately concentrated, and markets with HHI > 2,500 as highly concentrated (U.S. Department of Justice and the Federal Trade Commission, 2010).

4 See Beck et al. (2012) for more details.

5 Rejected markets included Saint Paul, MN (Minneapolis), Burnsville, MN (Minneapolis), Evanston, IL (Chicago), Lakewood, CO (Denver), Lewisville, TX (Dallas), Lynnwood, WA (Seattle), Bellflower, CA (Los Angeles), Hermosa Beach, CA (Los Angeles), and Decatur, GA (Atlanta).

6 In Beck et al. (2012), market population was used only for city selection. The number of listings was used to define markets as “small,” “medium,” or “large.” Given the large contraction in the number of listings in 2021 and that the contraction was heterogeneous across different markets, real estate market sizes (large/medium/small) are defined here by market population, not by volume of listings as they were in the 2012 paper.

7 This web-scraping tool was developed in cooperation with Bright Data (www.brightdata.com). A description of the process by which the raw data were cleaned can be found in Appendix A.

8 To allow for a more direct comparison with 2007 data, markets with a population of over 1million were grouped together to generate the average 2007 HHI of 447. Note that in the 2012 paper, since groups were defined by number of listings, some of the markets with 1 million + residents were considered “medium” in that study.

9 We have data for population and listings in each market for 2007, but not median price. Interestingly, when we regress HHI and CR4 on population and the number of listings for 2007, population becomes insignificant and the number of listings is negative and significant. When we run this same specification for 2021, population is significantly negative and number of listings is insignificant. We interpret this to mean that in a stable long-run equilibrium, which better describes 2007 than 2021, it is the total number of listings that determines the number and size distribution of firms that a market can support. When that long-run equilibrium is disrupted by exogenous events and the market shrinks significantly as in 2021, population becomes more important than listings, probably because it is more reflective of the long-run equilibrium that market will return to when the exogenous disruption passes.

10 See Appendix B for a detailed discussion of our comparisons.

11 The size of a brokerage firm can be measured by the number of listings, the number of agents, the number of closed transactions, or by dollar volume of listings or closed transactions. All are likely to be strongly positively correlated. We were only able to observe the number and dollar value of listings on Realtor.com, and so those are the measures that we used.

12 As an example, Nashville, TN, was considered a medium market in 2007 as it had 4,159 listings. By 2021, Nashville’s population had increased from 1.31 million to 1.99 million people and might better be characterized as a large real estate market. For the sake of consistency, the original 2012 classifications of market sizes were retained in this section.

13 Note that one market, Carlsbad, CA, was a significant outlier. It saw an increase in firms from 10 to 137 (1,270% increase) during this period. If this outlier is included, the average growth in the number of firms is 51%.

14 Multiple unsuccessful direct requests for clarification from Realtor.com were attempted.