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Long-Run Renewal of REIT Property Portfolio Through Strategic Divestment

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Abstract

Real Estate Investment Trusts (REITs) renew and recycle their property portfolios through divestment of inefficient assets and new acquisitions. Most previous literature focuses on the wealth effect of acquisition on REIT-level performance, while the property-level renewal process of REIT portfolios (especially divestments) remains unclear. Using a unique property-level dataset of Japanese REITs, we fill this gap by investigating the determinants of property divestment and the management strategy leading up to the divestments. We find that REITs strategically choose properties designated for divestment. The criteria include: (i) economic obsolescence that is captured through relatively large operating expense and/or a high rental yield within the REIT portfolio, (ii) mismatch in the geographical focus of the REIT, and (iii) a significant change in the capital value since acquisition. Especially during the periods of REIT growth, most of the above criteria apply, suggesting that the long-run renewal of a portfolio leads to its efficient asset allocation. We also provide evidence of property-level earnings management by REITs: the size of the capital expenditure is reduced just before the divestment to increase the net cash flows to appeal to potential buyers.

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Notes

  1. REITs typically present renewal strategies of their property portfolios. For example, see CapitaLand Commercial Trust “Portfolio Reconstitution Strategy”. http://www.cct.com.sg/about-cct/our-strategy/portfolio-reconstitution-strategy/. Accessed April 17, 2018.

  2. REITs can grow broadly in two ways: internal growth and external growth. The internal growth strategy requires cost cutting and revenue enhancement of existing properties. External growth is achieved through acquisition (or development) to boost the REIT portfolio. Acquisition is a popular tool to enable REITs to grow rapidly. Asset managers may emphasize acquisition because their earnings are directly related to acquisitions.

  3. Unlike the REITs in the United States and other countries, Japanese REITs disclose information on individual properties in their portfolio.

  4. Since Japanese REITs do not have to change appraisers, earnings management is likely to occur.

  5. Appraisals for properties in Japan are based on the net cash flow (NCF) rather than the net operating income (NOI) (Japan Credit Rating Agency, Ltd. (2014). Japanese Real Estate Investment Trust (J-REIT). https://www.jcr.co.jp/en/pdf/dm28/J-REIT20140602.pdf. Accessed March 7, 2018). The difference is that NCF reflects capital expenditure (and depreciation). In other words, capital expenditure and depreciation are deducted from the NOI to obtain the NCF.

  6. Within the REIT framework, real estate can be managed efficiently in terms of its risk, return, and operational cost because of a more competitive environment (Lewis et al., 2003). However, some inefficiency may remain in the REIT portfolio in the sense that the adjustment costs of real estate capital are large. If the REIT market is perfectly efficient, the so-called Tobin’s Q will be 1. In other words, the market should be evaluated in such a way that the totals of real estate capital and REIT corporate debt and equity are consistent. However, combining the property-level and firm-level datasets of Japanese REITs, Shimizu (2017) and Shimizu et al. (2015) report that Tobin’s Q exceeds 1 in a situation wherein the financial market overheats and show that the degree differs for each REIT corporation.

  7. Generally, a REIT manager’s compensation is linked to the REIT’s performance.

  8. Note that even if properties with high rental yields are divested, this does not preclude yield-accretive acquisition by growing REITs (that is, small REITs). The properties with high rental yields may be efficient for some REITs that seek high NOI.

  9. Most J-REITs have internal rules stating that the disposition prices need to exceed their appraised values.

  10. J-REITs distribute all the capital gains to shareholders, so there is no capital gains tax; this is similar to other REITs in the world.

  11. Since changing REIT managers is not common, the behavior is not likely to be attributable to a change in REIT managers.

  12. J-REITs disclose their property information with half-yearly frequency (fiscal term). If the final month of the fiscal term is between January and June, we define the period as the first half (H1); otherwise, we define the period as the second half (H2). Since properties may be in the portfolio for less than half a year, periods of divestment/acquisition (and other periods in operation) are normalized to the same full six months.

  13. As Miyakoshi et al. (2016) point out the J-REIT market also experienced a negative shock from the massive earthquakes in 2011.

  14. We neglect “partial divestment” (that is, selling only part of a property) and only consider “final divestment” (that is, selling an entire asset).

  15. In the finance literature, the total yield of a property is the sum of (i) the ratio of the NOI during a lease to the appraised value and (ii) the ratio of the capital gain to the appraised value. In real estate markets, the former is much larger than the latter; thus, we employ the definition of rental yield in Eq. (2).

  16. Almost all the properties held by J-REITs are located in Japan. Specifically, the “Tokyo central wards” consist of the five central wards (Minato, Chuo, Chiyoda, Shibuya, and Shinjuku wards) of Tokyo; “other Tokyo wards” cover the remaining wards of Tokyo; “other Tokyo metropolitan areas” include the Tokyo prefectures (excluding the ward areas of Kanagawa, Chiba, Saitama, Gunma, Tochigi, and Ibaraki); “other metropolitan areas” include the Sapporo, Sendai, Nagoya, Kyoto, Osaka, Kobe, Hiroshima, and Fukuoka areas; and “other areas” include the remaining rural areas in Japan and outside of Japan (i.e., two properties located in Malaysia).

  17. Note that the actual capital gain/loss based on the sales price is observed only for the sales events.

  18. The change in capital value may be related to the period since acquisition, so we control the latter in the regression analysis (see Eq. (4)).

  19. We restrict the sample so that the operating expense ratio is between [0, 1), the rental yield (%) is between (0, 5), the yield accretion (%) is between (− 0.1, 0.1), and the capital gain (%) is between (− 100, 100), depending on the variables used in each analysis. For example, for the operating expense ratio of properties in operation, 3,596 (= 46,420 – 42,824) samples out of 46,420 are truncated. The performance variables are restricted to be positive, since (i) our dataset does not distinguish whether the variables are actually zero or not reported, and (ii) negative values for the NCF and NOI are exceptions (fewer than 2% of the subsamples in operation).

  20. In Appendix B, we conduct some robustness checks.

  21. We do not take lagged variables for geographical focus since the REIT-level policy regarding whether to focus on Tokyo central wards in period t is observed in period t (in other words, the property divestment may be due to a policy change).

  22. In Fig. 3, we exclude the divestment/acquisition “0H” periods as special periods. Especially at the time of divestment, we observe some jumps at 0H for its negative sign (see Table 3), which may be due to the ceasing of property operation in the final period.

  23. In J-REITs, there are no tax incentives for divesting properties with a capital loss.

  24. For each of the four variables of interest, although the size of the coefficients differs to some extent, their dynamics around divestment do not change significantly for the estimation methods.

  25. In Fig. 4, we exclude the divestment “0H” period as a special period. We observe some jumps at 0H for its negative sign (see Tables 5 and 6), which may be due to the ceasing of property operation in the final period.

  26. In Table 5, we employ only a small subsample of periods/properties with a positive CapEx. As robustness checks, we conduct linear specifications for “per floor area of performance measures,” including periods/properties with negative/zero performance measures in the analysis; the results also confirm the property-level earnings manipulation.

  27. Anecdotal evidence shows that REITs often decide on property dispositions one or two years before the divestments.

  28. As Shimizu et al. (2015) point out the NOI represents some stickiness due to the rollover contract. In some properties, there may be some improvements in the NOI just before divestment. This is another possibility that may make the rental yield high in the case in which appraisal values do not reflect the future cash flow properly. REITs may improve the NOI by replacing tenants or placing tenants in previously vacant sections, for example. This enables REITs to sell their assets at a higher price than their appraised value.

  29. In Japan, the appraised value reflects the NCF, and most REITs have internal rules that the disposition price needs to exceed the appraised value. REIT managers may intentionally reduce their final appraised value to meet this requirement, while the property seems attractive to potential buyers according to the latest property performance indicator (i.e., NCF).

References

  • Alcock, J., Glascock, J., & Steiner, E. (2013). Manipulation in US REIT investment performance evaluation: Empirical evidence. Journal of Real Estate Finance and Economics, 47(3), 434–465.

    Article  Google Scholar 

  • Ambrose, B. W. (1990). Corporate real estate’s impact on the takeover market. Journal of Real Estate Finance and Economics, 3(4), 307–322.

    Article  Google Scholar 

  • Ambrose, B., & Bian, X. (2010). Stock market information and REIT earnings management. Journal of Real Estate Research, 32(1), 101–137.

    Article  Google Scholar 

  • Baber, W. R., Fairfield, P. M., & Haggard, J. A. (1991). The effect of concern about reported income on discretionary spending decisions: The case of research and development. Accounting Review, 66(4), 818–829.

    Google Scholar 

  • Ball, J., Rutherford, R., & Shaw, R. (1993). The wealth effects of real estate spin-offs. Journal of Real Estate Research, 8(4), 597–606.

    Article  Google Scholar 

  • Bartov, E. (1993). The timing of asset sales and earnings manipulation. Accounting Review, 68, 840–855.

    Google Scholar 

  • Bens, D. A., Nagar, V., & Wong, M. H. (2002). Real investment implications of employee stock option exercises. Journal of Accounting Research, 40(2), 359–393.

    Article  Google Scholar 

  • Bokhari, S., & Geltner, D. (2011). Loss aversion and anchoring in commercial real estate pricing: Empirical evidence and price index implications. Real Estate Economics, 39(4), 635–670.

    Article  Google Scholar 

  • Bokhari, S., & Geltner, D. (2018). Characteristics of depreciation in commercial and multifamily property: An investment perspective. Real Estate Economics, 46(4), 745–782.

    Article  Google Scholar 

  • Booth, G. G., Glascock, J. L., & Sarkar, S. K. (1996). A reexamination of corporate sell-offs of real estate assets. Journal of Real Estate Finance and Economics, 12(2), 195–202.

    Article  Google Scholar 

  • Bushee, B. J. (1998). The influence of institutional investors on myopic R&D investment behavior. Accounting Review, 73(3), 305–333.

    Google Scholar 

  • Campbell, R. D., Petrova, M., & Sirmans, C. F. (2003). Wealth effects of diversification and financial deal structuring: Evidence from REIT property portfolio acquisitions. Real Estate Economics, 31(3), 347–366.

    Article  Google Scholar 

  • Campbell, R. D., Ghosh, C., & Sirmans, C. F. (2005). Value creation and governance structure in REIT mergers. Journal of Real Estate Finance and Economics, 31(2), 225–239.

    Article  Google Scholar 

  • Campbell, R. D., Petrova, M., & Sirmans, C. F. (2006). Value creation in REIT property sell-offs. Real Estate Economics, 34(2), 329–342.

    Article  Google Scholar 

  • Capozza, D., & Korean, S. (1995). Property type, size and REIT value. Journal of Real Estate Research, 10(4), 363–379.

    Article  Google Scholar 

  • Clayton, J., & MacKinnon, G. (2003). The relative importance of stock, bond and real estate factors in explaining REIT returns. Journal of Real Estate Finance and Economics, 27(1), 39–60.

    Article  Google Scholar 

  • Crane, A., & Hartzell, J. (2010). Is there a disposition effect in corporate investment decisions? Evidence from real estate investment trusts. Mimeo.

    Book  Google Scholar 

  • Dechow, P. M., & Sloan, R. G. (1991). Executive incentives and the horizon problem: An empirical investigation. Journal of Accounting and Economics, 14(1), 51–89.

    Article  Google Scholar 

  • Deng, X., & Ong, S. E. (2018). Real earnings management, liquidity risk and REITs SEO dynamics. Journal of Real Estate Finance and Economics, 56(3), 410–442.

    Article  Google Scholar 

  • Diewert, W. E., & Shimizu, C. (2016). Alternative approaches to commercial property price indexes for Tokyo. Review of Income and Wealth, 63(3), 492–519.

    Article  Google Scholar 

  • Diewert, W. E., Fox, K., & Shimizu, C. (2016). Commercial property price indexes and the system of national accounts. Journal of Economic Surveys, 30(5), 913–943.

    Article  Google Scholar 

  • Genesove, D., & Mayer, C. (2001). Loss aversion and seller behavior: Evidence from the housing market. Quarterly Journal of Economics, 116(4), 1233–1260.

    Article  Google Scholar 

  • Glascock, J. L., Davidson, W. N., & Sirmans, C. F. (1991). The gains from corporate selloffs: The case of real estate assets. Real Estate Economics, 19(4), 567–582.

    Article  Google Scholar 

  • Graham, J. R., Harvey, C. R., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economics, 40(1), 3–73.

    Article  Google Scholar 

  • Gyourko, J., & Nelling, E. (1996). Systematic risk and diversification in the equity REIT market. Real Estate Economics, 24(4), 493–515.

    Article  Google Scholar 

  • Healy, P. M., & Wahlen, J. M. (1999). A review of the earnings management literature and its implications for standard setting. Accounting Horizons, 13(4), 365–383.

    Article  Google Scholar 

  • Lewis, D., Springer, T. M., & Anderson, R. I. (2003). The cost efficiency of real estate investment trusts: An analysis with a Bayesian stochastic frontier model. Journal of Real Estate Finance and Economics, 26(1), 65–80.

    Article  Google Scholar 

  • Li, Q., Ong, S. E., & Mori, M. (2013). Property dispositions and REIT credit ratings. Mimeo.

    Google Scholar 

  • McIntosh, W., Ott, S. H., & Liang, Y. (1995). The wealth effects of real estate transactions: The case of REITs. Journal of Real Estate Finance and Economics, 10(3), 299–307.

    Article  Google Scholar 

  • Miyakoshi, T., Shimada, J., & Li, K. W. (2016). The impacts of the 2008 and 2011 crises on the Japan REIT market. Journal of the Japanese and International Economies, 41, 30–40.

    Article  Google Scholar 

  • Mueller, G. (1998). REIT size and earnings growth: Is bigger better, or a new challenge? Journal of Real Estate Portfolio Management, 4(2), 149–157.

    Article  Google Scholar 

  • Ong, S. E., Ooi, J. T., & Kawaguchi, Y. (2011). Seasoned equity issuance by Japan and Singapore REITs. Journal of Real Estate Finance and Economics, 43(1–2), 205–220.

    Article  Google Scholar 

  • Ooi, J. T., Newell, G., & Sing, T. F. (2006). The growth of REIT markets in Asia. Journal of Real Estate Literature, 14(2), 203–222.

    Article  Google Scholar 

  • Ooi, J. T., Ong, S. E., & Li, L. (2010). An analysis of the financing decisions of REITs: The role of market timing and target leverage. Journal of Real Estate Finance and Economics, 40(2), 130–160.

    Article  Google Scholar 

  • Ooi, J. T., Ong, S. E., & Neo, P. H. (2011). The wealth effects of property acquisitions: Evidence from Japanese and Singaporean REITs. Real Estate Economics, 39(3), 487–505.

    Article  Google Scholar 

  • Ro, S., & Ziobrowski, A. J. (2011). Does focus really matter? Specialized vs. diversified REITs. Journal of Real Estate Finance and Economics, 42(1), 68–83.

    Article  Google Scholar 

  • Roychowdhury, S. (2006). Earnings management through real activities manipulation. Journal of Accounting and Economics, 42(3), 335–370.

    Article  Google Scholar 

  • Shimizu, C. (2017). Microstructure of asset prices, property income, and discount rates in Tokyo residential market. International Journal of Housing Market and Analysis, 10(4), 552–571.

    Article  Google Scholar 

  • Shimizu, C., Diewert, W. E., Nishimura, K. G., & Watanabe, T. (2015). Estimating quality adjusted commercial property price indexes using Japanese REIT data. Journal of Property Research, 32(3), 217–239.

    Article  Google Scholar 

  • Tang, C. K., Mori, M., Ong, S. E., & Ooi, J. T. (2016). Debt raising and refinancing by Japanese REITs: Information content in a credit crunch. Journal of Real Estate Finance and Economics, 53(2), 141–161.

    Article  Google Scholar 

  • Wiley, J. A. (2013). REIT asset sales: Opportunistic versus liquidation. Real Estate Economics, 41(3), 632–662.

    Article  Google Scholar 

  • Womack, K. S. (2012). Real estate mergers: Corporate control & shareholder wealth. Journal of Real Estate Finance and Economics, 44(4), 446–471.

    Article  Google Scholar 

  • Yoshida, J., Kawai, K., Geltner, D., & Shimizu, C. (2017). How rents and expenditures depreciate: A case of Tokyo office properties. Mimeo.

    Google Scholar 

  • Zhu, Y. W., Ong, S. E., & Yeo, W. Y. (2010). Do REITs manipulate their financial results around seasoned equity offerings? Evidence from US equity REITs. Journal of Real Estate Finance and Economics, 40(4), 412–445.

    Article  Google Scholar 

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Acknowledgements

We would like to thank an anonymous referee, Kwong Wing Chau, Helen Bao, David Geltner, Christian Hilber, Kaoru Hosono, Daisuke Miyakawa, Graeme Newell, Toshiro Nishioka, Xu Peng, Kazuto Sumita, Iichiro Uesugi, Jiro Yoshida, and the participants in the 2018 Asia Pacific Real Estate Research Symposium, the 25th Conference of the European Real Estate Society, the 32st Annual Meeting of the Applied Regional Science Conference, and the workshops at the Hitotsubashi University and Research Institute of Economy, Trade, and Industry for their helpful comments. We would like to thank Tokyu Land Corporation for providing the data. The stock market indices from Bloomberg were available from Hitotsubashi University, where Chihiro Shimizu joins as a Visiting Research Fellow. This work gratefully acknowledges the support received from JSPS KAKENHI Grant Numbers 16J03877, 17K18919, and 25220502, and the Nomura Foundation.

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Appendices

Appendix A: Calculation of Yield Accretion

The yield accretion or contribution for property i of REIT r in period t, \({YA}_{i,r,t}\), is measured as:

$${YA}_{i,r,t}\equiv \frac{\sum_{j\in {I}_{r,t}}{NOI}_{j,t}}{\sum_{j\in {I}_{r,t}}{AV}_{j,t}}-\frac{\sum_{\begin{array}{c}j\ne i,j\in {I}_{r,t}\end{array}}{NOI}_{j,t}}{\sum_{j\ne i,j\in {I}_{r,t}}{AV}_{j,t}}$$
(A.1)

The first term on the right-hand side of Equation (A.1) is the portfolio yield of REIT r in period t after the acquisition of property i. The second term is the portfolio yield of REIT r in period t before the acquisition of property i. Specifically, \({NOI}_{i,t}\) is the net operating income of target property i in period t. \({AV}_{i,t}\) is the appraised value of target property i in period t, and Ir,t is the set of properties owned by REIT r in period t. The rental yield of the target property (REIT portfolio) is computed by dividing the NOI by the appraised value of the property (REIT portfolio). Our measure of yield accretion hypothetically assumes that property i (in the current portfolio) was newly added to the portfolio without property i. Therefore, the yield accretion is calculated for (i) properties newly acquired in the period, (ii) properties continuing to stay in the portfolio in the period, and (iii) properties divested in the period.

For an acquisition to be yield-accretive, the target property yield must be higher than the yield of the REIT portfolio. The overall accretion effect on the yield is dependent on both the size of the target property and the REIT property portfolio. Even if the rental yield of the property is significantly higher than the REIT portfolio yield, the marginal accretion effect on the REIT portfolio yield may be negligible if the acquired property is small relative to the REIT portfolio.

Appendix B: Robustness Checks

Independent Tests of Hypotheses 1–3

Table 7 provides the individual tests of each Hypothesis 1 to 3. The probit model for divestment is based on Eq. (4), employing the same control variables as in Table 2. We take lagged variables (a half year before the analysis periods) for operating expense ratio, rental yield, and capital gain/loss.

Table 7 Probit model for divestment (independent tests of Hypotheses 1 to 3)

Column (1) shows the effect of economic obsolescence; the results confirm that Hypothesis 1a/1b holds. Column (2) shows the effect of geographical focus. The results confirm that properties that do not match the geographical focus of specialized REITs are likely to be divested (Hypothesis 2). Since we exclude the rental yield of properties in the regression, some of them are captured by location variables. Properties located outside of central Tokyo typically exhibit a high rental yield, and those properties are likely to be divested. Column (3) shows the effect of a capital gain/loss; the results confirm that Hypotheses 3a/3b hold.

REIT-Type Subsample Tests of Hypothesis 2

Table 8 shows the result of the REIT-type subsample analysis focusing on the location variables (the Central Tokyo REIT dummy and its interaction terms between locations are not included in the regression). The probit model for divestment is based on Eq. (4), employing the same control variables as in Table 2. We take lagged variables (half a year before the analysis periods) for operating expense ratio, rental yield, and capital gain/loss.

Table 8 Probit model for divestment (REIT-type subsample tests of Hypothesis 2)

The Central Tokyo REITs in column (2) are more likely to divest properties in other metropolitan areas and other areas than the Tokyo central wards; this is contrary to all the REITs in column (1) and other REITs (excluding Central Tokyo REITs) in column (3). The results again confirm that properties that do not match the geographical focus of specialized REITs are likely to be divested (Hypothesis 2). Note that, for Central Tokyo REITs, the economic obsolescence of properties is not the statistically significant criterion for divestment.

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Suzuki, M., Ong, S.E., Asami, Y. et al. Long-Run Renewal of REIT Property Portfolio Through Strategic Divestment. J Real Estate Finan Econ 66, 1–40 (2023). https://doi.org/10.1007/s11146-022-09895-z

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