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Tenant Concentration in REITs

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Abstract

To the extent that a property portfolio is dependent on a small number of tenants for a large proportion of rental revenue, the portfolio has a concentrated tenant base. This article investigates the impact of tenant concentration on property portfolio performance, risk, and the cost of debt. Utilizing the disclosure of major tenants by 152 Equity Real Estate Investment Trusts (REITs) from 2000 to 2017, I document a positive relation between tenant concentration and profitability. REITs with greater tenant concentration experience higher profit margins and lower expense ratios, suggesting the positive relation between tenant concentration and profitability is driven by increased operational efficiency. Although these REITs are more efficient, tenant concentration is often stated as a risk in public disclosures. Consistent with this view, I find that REITs with greater tenant concentration have greater idiosyncratic risk. Further, banks appear to price this risk into their rate setting process and penalize REITs with greater tenant concentration. Accounting for the quality of the tenant base, the positive effects of tenant concentration are prevalent in REITs with high quality tenants and the negative effects of tenant concentration are prevalent REITs with low quality tenants.

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Data Availability

Data comes from standard available databases.

Notes

  1. Larger property sectors that do not routinely disclose tenants include Multifamily, Self-Storage, and Hotel.

  2. Some REIT managers will refer to this as “credit concentration”. Others will use the phrase “tenant diversification” to refer to the opposite of tenant concentration. All of these refer to the same concept.

  3. View MREIC website here: http://investors.mreic.reit/

  4. Specifically, they find a U-Shaped curve with three groups: High diversification, moderate diversification, and single tenant properties. The highest spreads were in the high diversification group and the lowest spreads were in the moderate diversification group.

  5. In my sample, I am able to identify 57% of REIT-Tenant-Years as publicly traded firms with data available in Compustat. Following Liu et al. (2016) and Lu Andrews (Lu-Andrews, 2017), I limit my tenant quality tests to tenants with publicly available information. However, I address this further in the robustness section of the paper.

  6. https://www.bloomberg.com/news/articles/2018-10-16/sears-liquidation-would-cost-seritage-half-its-rent-income

  7. For reasons discussed in the data section, we will limit the tenant concentration measure to be only the top 5 and the top 10 tenants.

  8. Patatoukas (2011), Mihov and Naranjo (2017), and Dhaliwal et al. (2016) include all industries in Compustat but Campello and Gao (2017) include only manufacturing firms. Dhaliwal et al. (2016) sets firms with no major customers to zero, the rest of the papers limit their sample to firms that already have at least one major customer.

  9. In Table 10, I present results using the simple sum of the top 5 tenant’s tenant share rather than the Herfindahl-Hirschman style measure.

  10. Less than 10% of REIT-years have fewer than 5 tenants disclosed and an examination of these reveals this is typically because the REIT has less than 5 total tenants.

  11. The correlation between tenant concentration the expense ratio is negative. Lower values of the expense ratio represent greater efficiency.

  12. For example, Seritage Growth Properties has an average of 72% tenant share driven by its heavy reliance on Sears. Sears leases from Seritage all over the nation. Their geographic concentration is 0.17, well below the sample mean of 0.42.

  13. As noted in Dhaliwal et al. (2016), the use of industry averages as instrumental variables is a common approach in other papers. See, for example: Jin (2002), Hanlon et al. (2003), Shi (2003), Dass et al. (2014), and Mihov and Naranjo (2017).

  14. See Dhaliwal et al. (2016) for a similar argument in the context of the customer-supplier relationship.

  15. Examples include “Arlington County” and “City of New York”.

  16. This suggests that REITs that do not disclose are notably smaller REITs. Untabulated logistic regressions on the propensity to disclose confirms that REIT size is the largest determinant of disclosure likelihood.

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Acknowledgements

I would like to thank the participants at the 2019 Real Estate Finance and Investment Symposium at the University of Cambridge, Joseph Ooi (discussant), an anonymous reviewer, Dan W. French, my dissertation committee at the University of Missouri, McKay Price, and the participants at the following conferences and workshops: University of Colorado, Colorado Springs, University of Nevada, Reno, the College of Charleston, the University of Alabama, Birmingham, 2018 ARES annual meeting, 2019 PhD Project Finance and Economics annual meeting. I acknowledge funding from the Jeffrey E. Smith Institute of Real Estate.

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  1. University of Colorado, Colorado Springs, CO, USA

    Ryan G. Chacon

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Appendix

Appendix

Table 12 Variable definitions
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Table 13 Examples of REIT Disclosures
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Table 14 First stage regressions (2SLS)
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Table 15 PSM sample balance
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Chacon, R.G. Tenant Concentration in REITs. J Real Estate Finan Econ 66, 636–679 (2023). https://doi.org/10.1007/s11146-021-09829-1

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