This paper first outlines the impact of age-related properties on the efficiency of operations, portfolio risk, and the market value of REITs. Based on these findings, We examine three reasons REITs hold older properties. With a comprehensive data set on the property level collection from U.S. equity REITs from 1995 through 2020, we develop an estimate of the property’s age at the firm level based on the age of the individual properties owned by REITs. By controlling for key immutable characteristics, we conclude that REITs with older properties have lower efficiency in operations, less value, and higher risk than their peers. Furthermore, while shareholders do not receive higher stock returns, we have evidence that REIT managers with older assets in their portfolios are paid substantially more compensation. This is consistent with the agency cost associated with managers’ opportunism. In addition, REITs who own more properties in similar areas as their headquarters and that have a higher concentration of geographic properties are more likely to have older properties. This observation is consistent with the theory that is based on geographical locations of properties that are older. However, we did not find any evidence supporting growth related to core-plus or value-added investment strategies.

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Notes

1. In the U.S., since asset value in accrual income accounting is calculated on historical costs and depreciation is permitted under tax law to lower the tax-deductible income of the owner, it is crucial to calculate the annual depreciation rate of the property so that a depreciation plan is established to be tax-efficient.
2. For example, Malpezzi et al. (1987) found that the annual depreciation rate for residential properties varies between 0.38-2.40 percent. In another study using house data from the Netherlands, Franche and Van de Minne (2017) found an annual depreciation rate of 1.5% over in the initial 20 years and 1.1% over in the initial 50 years. In addition, Hulten and Wykoff (1981) estimate the annual depreciation rate for commercial buildings to be around 3 percent for structures built. Fisher et al. (2005) demonstrate they have found that properties with multifamily homes are subject to a rate of depreciation of 5.25 per year, based on the structure of the building.
3. Physical obsolescence refers specifically to wear and tear of the structure of the building and its elements over time (Francke & Van de Minne, 2017).
4. Functional obsolescence occurs when a structure becomes unsuitable for the intended use or less appealing to tenants or users because of technological advances or shifts in preferences, such as the demand for fiber-optic technology or the need for environmentally sustainable design for people who live in the space (Bokhari and Geltner in 2018).
5. Economic obsolescence is the idea of the most efficient and most effective usage of the property changing away from the present structure’s usage or intensity. A good example is when moving to residential or commercial use is more profitable than industrial uses of the present structure (see Bokhari & Geltner, 2018).
6. Levkovich et al. (2018). Also, the depreciation rates for commercial real property in the Netherlands differ significantly across property types. Most homes built between 1960 and 1990 experience adverse effects of depreciation; however, those built before World War II industrial and office properties may see an appreciation in value due to the vintage effect.
7. See the NAREIT website on “REITs by the Numbers” at https://www.reit.com/data-research/data/reits-numbers.
8. Research has shown that REITs in the US typically sell a small portion of their properties yearly. For instance, Eichholtz and Yonder (2015) report that the typical US REIT sells around five percent of its properties, based on the property value in dollars between 2003 and 2010. Feng et al. (2022) discovered that most REITs use a long-term investing strategy, holding most of their properties for an extended period. These results suggest that the average property age of REITs will mostly stay the same in the short time since it is an aggregate measure of properties of REIT portfolios. However, we recognize the possibility of a self-selection bias to occur as managers opt to keep older properties. This bias in selection is addressed with the Heckman sampling method. The results are essentially the same.
9. For, see a list of REIT headquarters by location: https://www.reitsacrossamerica.com/us-reits-headquartered-state.
10. In particular, older CEOs are more cautious by adopting a low-growth strategy (Child 1974), refusing to embrace technology (Kitchell, 1997), spending less money on R&D (Barker & Mueller, 2002), and making fewer acquisitions (Yim & Ooi, 2013) and assuming fewer risk (Serfling, 2014; Andreou et al. 2017, 2017; Belenzon et al. in 2019). In a recently published study, Zhang and Ooi (2022) examine the acquisitions of properties made by 150 REIT CEOs and conclude that younger CEOs tend to be more frequent and more aggressive with property acquisitions to show the market that they can strike deals.
11. See the article, “Older condos plagued by high maintenance costs,” at https://www.marketwatch.com/story/older-condos-plagued-by-high-maintenance-costs-2014-06-12.
12. See a TD Insurance article titled “How property insurance is calculated” at https://www.tdinsurance.com/products-services/home-insurance/tips-advice/premium-calculations.
13. Older structures are typically less efficient in energy efficiency when they are less efficient than newer ones because they typically follow outdated standards. See https://www.forbes.com/sites/pikeresearch/2016/04/13/energy-efficient-building/?sh=41a4e8d548f8.
14. Kenneth R. French’s Data Library: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.
15. See https://www.eia.gov/consumption/commercial/data/2018/pdf/CBECS_2018_Building_Characteristics_Flipbook.pdf.
16. We perform the time-series regression below on every REIT over the entire sampling period.
17. Ri,t=b0+b1Rm,t+b2SMBt+b3HMLt+b4RMWt+b5CMAt+et,=0+1,+2+3+4+5+e where Ri,t, is the excess stock return of REIT i, Rm,t, is the risk-free stock return of the market, SMBt (Small minus Big), HMLt (High minus Low), MOMt (Momentum), and RMWt (Robust minus Weak), and CMAt (Conservative minus Aggressive) are the return to zero investment factor-mimicking portfolios designed to capture size, book-to-market effects, momentum, profitability. And investment risk in the year and investment risk in the year. We then use the market return, the year-long average of SMB, HML, MOM RMW, and CMA risks, and factors estimated as model loadings to calculate the expected return estimated Ri,t.
18. Leskinen et al. (2020) offer an overview of the literature on green certification for commercial properties.
19. This regression has fewer observations, which is smaller than the other regressions because the information about repairs and maintenance costs is not available for certain REITs.
20. The literature suggests that the volatility of REIT return is very different from other asset types (e.g., Cotter & Stevenson, 2006; Fei et al., 2010). Furthermore, extreme risks for REITs are more severe than firms that do not have REITs (Zhou et al., 2012). The pricing of REITs is influenced by their unique risks (e.g., Ooi et al., 2009; Chiang et al., 2009; Cakici et al., 2014.) but not by distress risk (Shen, 2021).
21. The U.S. geographic regions determined by the National Council of Real Estate Investment Fiduciaries (NCREIF) are: (1) NE (Northeast) comprising ME, VT, NH, NY, CT, RI, MA, PA, NJ, DE; (2) ME (Mideast) which includes MD, WV, VA, KY, NC, SC, DC; (3) SE (Southeast): comprising TN, GA, FL, AL, MS; (4) EN (East et al.) which includes MI, IL, OH, IN, WI; (5) WN (West et al.) comprising MN, IA, MO, KS, NE, S D, ND; (6) SW (Southwest) comprising TX, OK, AR, LA, (7) MT (Mountain): MT, ID, WY, UT, CO, NM, AZ, NV; and (8) PC (Pacific) including WA, OR, CA, AK, HI.
22. Check out some of the most recent asset pricing studies that are available in the REIT literature (e.g., Ling et al. (2019), Beracha et al. (2019b), Chen et al. (2020), Milcheva et al. (2021), Shen (2021), Shen et al. (2021) as well as Zhu as well as Lizieri (2022)) in similar studies.
23. We analyze the equal-weighted excess monthly returns on portfolios’ stocks to ensure robustness. We get quantitatively similar results. However, we have removed these in the paper to make it easier for readers.
24. We employ the capital asset price (CAPM) model to ensure robustness. Fama, the French (1993) five-factor model, the five-factor model from Fama, and the French (2015) five-factor model. We observe quantitatively comparable results with the simple coefficients as well as the statistical significance of the alphas when using these models. The paper should include these results to make it easier for readers.