Skip to main content

The Rent Term Premium for Cancellable Leases

Abstract

This study analyzes the rent term premium for leases that can be cancelled by the lessee. We model the lessor’s trade-off between leasing costs and the cost of cancellation options based on the recognition that many leases are cancellable by lessees, and lease markets involve significant transaction costs. We demonstrate that, regardless of the expected future rents, the rent term structure is upward-sloping when there is no leasing cost but U-shaped when the lessor faces moderate leasing costs. Residential leases in Japan, which are all cancellable by tenants, exhibit the term structure that is consistent with our calibrated model.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Notes

  1. 1.

    Source: The Real Estate Roundtable, 2011 Annual Report. Available at http://www.rer.org.

  2. 2.

    Source: The Equipment Leasing and Finance Foundation, Economic Impacts of the Proposed Changes to Lease Accounting Standards, December 12, 2011. Available at http://www.leasefoundation.org.

  3. 3.

    This type of lease contract was prevalent before 1941 but eliminated to prevent landlords from evicting incumbent tenants and circumventing rent control during World War II (Survey of New Form of Residence Associated with Fixed-Term Lease Contracts, Housing Research and Advancement Foundation of Japan, March 2015).

  4. 4.

    This requirement is specified by Article 28 of the Tenure Law, which is known as “Shakuchi-Shakka-Hou” in Japan.

  5. 5.

    See Iwata (2002) and Seko and Sumita (2007) for a discussion of the asymmetric nature of lease restrictions and the effects of the role of these asymmetries as a form of rent control.

  6. 6.

    Ministry of Land, Infrastructure, Transport, and Tourism, 2013FY Housing Market Survey (Jutaku Shijo Doko Chosa).

  7. 7.

    The stochastic discount factor is derived from the first-order condition for the lessor’s utility maximization problem given the lessor’s wealth portfolio and consumption stream.

  8. 8.

    Ambrose et al. (2002) study the opposite type of leases; in other words, leases with rents that adjust only in the upward direction.

  9. 9.

    The lessor’s use of alternative lease types does not change our proof because lease values for alternative leases are equalized at any time under the lessor’s consistent pricing condition.

  10. 10.

    The rent term premium is also affected by the expected net rent gap prior to the final period. We take into account the total rent gap in our numerical exercise.

  11. 11.

    We use lease contracts that are shorter than or equal to five years because the number of leases longer than five years is small and their tenant characteristics are significantly different from the average characteristics.

  12. 12.

    In Appendix D, we present the result of additional tests by probit regressions.

  13. 13.

    In Appendix D, we present the result of additional tests by probit regressions.

  14. 14.

    This empirical strategy is equivalent to pooling both types of leases and including interaction terms with a fixed-lease dummy by treating general leases as a reference group.

  15. 15.

    The average of the 2003 and 2008 national vacancy rates for rental housing is 19 %.

  16. 16.

    The estimated term structures exhibit the same shapes based on Models (b), (c), or (d).

  17. 17.

    The mean values are 16.4 and 15.1 years for building age, 9.5 and 9.8 min for the time to the nearest station in low- and high-vacancy areas, respectively.

  18. 18.

    To compute the market rent for the remaining term, we use a homogeneity property of the model. Because the rent risk, renewal costs, and risk-adjustments are all multiplicative, the ratio of the \( \left(T-t\right) \) year lease rate to the short-term rate at time t equals that ratio at time zero. Thus, \( {\hat{R}}_t^{T-t}={\hat{R}}_0^{T-t}\times {R}_t^1/{R}_0^1 \) \( . \)

  19. 19.

    We implicitly assume that the landlord inelastically supplies an existing rental unit and thus bears all costs associated with market frictions. This assumption simplifies computations because the lessee’s cancellation decisions are not affected by these costs.

  20. 20.

    The lessor’s risk aversion and the riskiness of short-term rents represented by a negative covariance with the discount factor alter the probability mass function under measure Q. Specifically, when short-term lease rates are negatively correlated with the discount factor, a larger probability mass is assigned to the state of a low rent as the risk aversion becomes larger. Then, the lower expected value under measure Q represents the certainty-equivalent value.

  21. 21.

    Source: Recruit Residential Price Index, January 14, 2013.

    Available at http://www.jresearch.net/house/jresearch/rrpi/index.html.

  22. 22.

    Rotten structures are excluded in this calculation.

References

  1. Agarwal, S., Ambrose, B. W., Huang, H., & Yildirim, Y. (2011). The term structure of lease rates with endogenous default triggers and tenant capital structure: theory and evidence. Journal of Financial and Quantitative Analysis, 46, 553–584.

    Article  Google Scholar 

  2. Ambrose, B. W., & Yildirim, Y. (2008). Credit risk and the term structure of lease rates: a reduced form approach. Journal of Real Estate Finance and Economics, 37, 281–298.

    Article  Google Scholar 

  3. Ambrose, B. W., Hendershott, P. H., & Klosek, M. (2002). Pricing upward-only adjusting leases. Journal of Real Estate Finance and Economics, 25, 33–49.

    Article  Google Scholar 

  4. Beck, T., & Demirguc-Kunt, A. (2006). Small and medium-size enterprises: access to finance as a growth constraint. Journal of Banking and Finance, 30, 2931–2943.

    Article  Google Scholar 

  5. Blume, M. E., & Keim, D. B., (1988). The valuation of callable bonds. Working paper 14–89, Rodney White Center for Financial Research, The Wharton School.

  6. Bond, S., Loizou, P., & McAllister, P. (2008). Lease maturity and initial rent: is there a term structure for UK commercial property leases? Journal of Real Estate Finance and Economics, 36, 451–469.

    Article  Google Scholar 

  7. Chang, C. C., Ho, H. W., Huang, H., Yildrim, Y. (2012). Simultaneous implication of credit risk and embedded options in lease contracts. Working paper.

  8. Clapham, E., & Gunnelin, A. (2003). Rental expectations and the term structure of lease rates. Real Estate Economics, 31, 647–670.

    Article  Google Scholar 

  9. Copeland, T. E., & Weston, J. F. (1982). A note on the evaluation of cancellable operating leases. Financial Management, 11, 60–67.

    Article  Google Scholar 

  10. Devos, E., Dhillon, U., Jagannathan, M., & Krishnamurthy, S. (2012). Why are firms unlevered? Journal of Corporate Finance, 18, 664–682.

    Article  Google Scholar 

  11. Eisfeldt, A. L., & Rampini, A. A. (2009). Leasing, ability to repossess, and debt capacity. Review of Financial Studies, 22(4), 1621–1657.

    Article  Google Scholar 

  12. Follain, J. R., Scott, L. O., & Yang, T. L. (1992). Microfoundations of a mortgage prepayment function. Journal of Real Estate Finance and Economics, 5, 197–217.

    Article  Google Scholar 

  13. Geltner, D. M., Miller, N. G., Clayton, J., & Eichholtz, P. (2014). Commercial real estate analysis and investments (3rd ed.). Mason: OnCourse Learning.

    Google Scholar 

  14. Giaccotto, C., Goldberg, G. M., & Hegde, S. P. (2007). The value of embedded real options: evidence from consumer automobile lease contracts. Journal of Finance, 62, 411–445.

    Article  Google Scholar 

  15. Goodman, A. C., & Kawai, M. (1985). Length-of-residence discounts and rental housing demand: theory and evidence. Land Economics, 62, 93–105.

    Article  Google Scholar 

  16. Graham, J. R., Lemmon, M. L., & Schallheim, J. S. (1998). Debt, leases, taxes, and the endogeneity of corporate tax status. Journal of Finance, 53(1), 131–162.

    Article  Google Scholar 

  17. Grenadier, S. R. (1995). Valuing lease contracts: a real-options approach. Journal of Financial Economics, 38, 297–331.

    Article  Google Scholar 

  18. Grenadier, S. R. (2005). An equilibrium analysis of real estate leases. Journal of Business, 78, 1173–1214.

    Article  Google Scholar 

  19. Gunnelin, A., & Soderberg, B. (2003). Term structures in the office rental market in Stockholm. Journal of Real Estate Finance and Economics, 26, 241–265.

    Article  Google Scholar 

  20. Gurkaynak, R. S., & Wright, J. H. (2012). Macroeconomics and the term structure. Journal of Economic Literature, 50, 331–367.

    Article  Google Scholar 

  21. Ho, S. S. M., Lam, K. C. K., & Sami, H. (2004). The investment opportunity set, director ownership, and corporate policies: evidence from an emerging market. Journal of Corporate Finance, 10, 383–408.

    Article  Google Scholar 

  22. Hubert, F. (1995). Contracting with costly tenants. Regional Science and Urban Economics, 25, 631–654.

    Article  Google Scholar 

  23. Iwata, S. (2002). The Japanese tenant protection law and asymmetric information on tenure length. Journal of Housing Economics, 11, 125–151.

    Article  Google Scholar 

  24. McConnell, J. J., & Schallheim, J. S. (1983). Valuation of asset leasing contracts. Journal of Financial Economics, 12, 237–261.

    Article  Google Scholar 

  25. Miceli, T. J., & Sirmans, C. F. (1999). Tenant turnover, rental contracts, and self-selection. Journal of Housing Economics, 8, 301–311.

    Article  Google Scholar 

  26. Mooradian, R. M., & Yang, S. X. (2000). Cancellation strategies in commercial real estate leasing. Real Estate Economics, 28, 65–88.

    Article  Google Scholar 

  27. Raess, P., & von Ungern-Sternberg, T. (2002). A model of regulation in the rental housing market. Regional Science and Urban Economics, 32, 475–500.

    Article  Google Scholar 

  28. Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation in pure competition. Journal of Political Economy, 82, 34–55.

    Article  Google Scholar 

  29. Rubinstein, M. (1974). An aggregation theorem for securities markets. Journal of Financial Economics, 1(3), 225–244.

    Article  Google Scholar 

  30. Schallheim, J. S., & McConnell, J. J. (1985). A model for the determination of “Fair” premiums on lease cancellation insurance policies. Journal of Finance, 40, 1439–1457.

    Google Scholar 

  31. Seko, M., & Sumita, K. (2007). Japanese housing tenure choice and welfare implications after the revision of the tenant protection law. Journal of Real Estate Finance and Economics, 35, 357–383.

    Article  Google Scholar 

  32. Sharpe, S. A., & Nguyen, H. H. (1995). Capital-market imperfections and the incentive to lease. Journal of Financial Economics, 39, 271–294.

    Article  Google Scholar 

  33. Stanton, R., & Wallace, N. (2009). An empirical test of a contingent claims lease valuation model. Journal of Real Estate Research, 31, 1–26.

    Google Scholar 

Download references

Acknowledgments

We thank Brent Ambrose; Yildiray Yildirim; Ed Coulson; Nai Jia Lee; James Conklin; Masahiro Okuno-Fujiwara; Hiroyuki Ozaki; Hiroyuki Seshimo; Toshiki Honda; David Geltner, Lynn Fisher; and the participants of the AREUEA International Conference in Korea, the ASSA meeting in Chicago, the Keio University Public Economics Seminar, the 26th ARSC annual conference, the 2013 Japanese Economic Association Autumn Meeting, and Maastricht-NUS-MIT symposium for providing valuable comments and suggestions. This research is supported in part by the Keio/Kyoto University Global COE Program of Japan and the Institute for Real Estate Studies at the Pennsylvania State University.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jiro Yoshida.

Appendices

Appendix A: Proofs

Proof of Lemma: To prove the lemma, we define two conditions:

  1. Condition (a)

    At least one of the initial leases has not been cancelled until period \( T-1 \); i.e., the market rent has not been low enough to induce cancellations of both leases: \( \forall t\le T-2:\ {\hat{R}}_t^{T-t}> \min \left\{{\hat{R}}_0^T,{\hat{R}}_0^{T-1}\right\} \).

  2. Condition (b)

    The market rent for the final period is higher than the preceding rental income under the \( T \) strategy: \( {R}_{T-1}^1>{\hat{Y}}_{T-2}^T \) .

There are three cases with respect to the rent for the final period. We demonstrate that the rent for the \( T-1 \) strategy is strictly higher than the rent for the \( T \) strategy in the first case and is equal to the rent for the \( T \) strategy in the second and third cases.

First Case: Conditions \( \left(\mathrm{a}\right) \) and \( \left(\mathrm{b}\right) \) both hold. If the initial rent for the \( T \) -period lease is greater than or equal to the initial rent for the \( T-1 \) -period lease \( \left(\mathrm{i}.\mathrm{e}.,\ {\hat{R}}_0^T\ge {\hat{R}}_0^{T-1}\right) \) , then condition \( \left(\mathrm{a}\right) \) implies that the initial \( T-1 \) period lease will never be canceled until maturity. The rent at time \( T-2 \) will be \( {\hat{Y}}_{T-2}^{T-1}={\hat{R}}_0^{T-1} \) for the \( T-1 \) strategy and \( {\hat{Y}}_{T-2}^T= \min \left\{{\hat{R}}_0^T,{\hat{R}}_t^{T-t};t\le T-2\right\} \) for the \( T \) strategy. By condition \( \left(\mathrm{b}\right) \), the rent under the \( T \) strategy will be unchanged for the final period \( \left({\hat{Y}}_{T-1}^T={\hat{Y}}_{T-2}^T\right) \), whereas under the \( T-1 \) strategy, the initial lease will expire at time \( T-1 \), and the rent during the final period will be adjusted upward to \( {\hat{Y}}_{T-1}^{T-1}={R}_{T-1}^1 \) . Condition \( \left(\mathrm{b}\right) \) also implies that during this period, the rent for the \( T \) strategy will be strictly lower than the rent for the \( T-1 \) strategy \( \left({\hat{Y}}_{T-1}^T<{\hat{Y}}_{T-1}^{T-1}\right) \) .

Conversely, if the initial rent is lower for the T-period lease than for the \( T-1 \) -period lease \( \left(\mathrm{i}.\mathrm{e}.,\ {\hat{R}}_0^T<{\hat{R}}_0^{T-1}\right) \), then conditions (a) and (b) imply that the initial \( T \) period lease will never be canceled until maturity. Thus, the rent during the final period is the initial rent \( \left({\hat{Y}}_{T-1}^T={\hat{R}}_0^T\right) \). In contrast, the \( T-1 \) -period lease may or may not be cancelled. If the initial lease has expired without a cancellation, the rent during the final period will be \( {\hat{Y}}_{T-1}^{T-1}={R}_{T-1}^1 \). Alternatively, if the initial lease has been cancelled, the rent during the final period will be the historical minimum of market rents: \( {\hat{Y}}_{T-1}^{T-1}= \min \left\{{\hat{R}}_t^{T-t};t\le T-1\right\} \). In either case, conditions (a) and (b) imply that during this period, the rent for the T strategy will be strictly lower than the rent for the \( T-1 \) strategy \( \left({\hat{Y}}_{T-1}^T<{\hat{Y}}_{T-1}^{T-1}\right) \).

Second Case: Condition (a) holds but condition (b) does not hold \( \left({R}_{T-1}^1\le {\hat{Y}}_{T-2}^T\right) \) . The final rent is the same for both strategies \( \left({\hat{Y}}_{T-1}^T={\hat{Y}}_{T-1}^{T-1}={R}_{T-1}^1\right) \) because the rent is adjusted to the low level of market rent that exists during the final period regardless of whether the initial T period rent is higher than the \( T-1 \) period rent.

Third Case: Condition (a) does not hold. Because both leases will have been cancelled at the same time before time \( T-1 \), both strategies will use the same lease during the final period. Thus, the final rent is the same for both strategies: \( {\hat{Y}}_{T-1}^T={\hat{Y}}_{T-1}^{T-1} \).

In summary, the \( \mathrm{T} \) strategy produces a strictly lower rent than the \( T-1 \) period strategy \( \left({\hat{Y}}_{T-1}^T<{\hat{Y}}_{T-1}^{T-1}\right) \) if conditions \( (a) \) and \( (b) \) both hold. Otherwise, both strategies give the same rent \( \left({\hat{Y}}_{T-1}^T={\hat{Y}}_{T-1}^{T-1}\right) \) .

Proof of Proposition: Suppose the initial rent for the \( T \) -period lease is not higher than the initial rent for the \( T-1 \) -period lease \( \left({\hat{R}}_0^T\le {\hat{R}}_0^{T-1}\right) \). The \( T-1 \) strategy will produce a weakly positive rent premium relative to the \( T \) strategy until both leases are cancelled. In addition, the \( T-1 \) strategy will generate a strictly higher expected rent than the \( T \) strategy for the final time period that is examined, as demonstrated by the lemma. Thus, the \( T-1 \) strategy would provide a strictly larger value to the lessor than the \( T \) strategy; this result would violate the specified consistent pricing condition. Therefore, the initial rent for the \( T \) -period lease must be higher than the initial rent for the \( T-1 \) -period lease \( \left({\hat{R}}_0^T>{\hat{R}}_0^{T-1}\right) \). In other words, the term structure of cancellable leases must be upward sloping between \( T-1 \) and \( T \). Because we can apply the same argument to any lease term \( u\;\left(u=2,\dots, T\right) \), the term structure for all cancellable leases must be upward sloping.

Appendix B: Detail of Numerical Analysis

We numerically analyze the term structure by parameterizing the risk-free rate, rent volatility, the risk premium on the short-term rent, the expected rent growth, and most importantly, leasing costs. We construct an annual binomial-tree model for an 8 year period and generate 1000 paths of short-term lease rates. At each node of the tree, the short-term rate changes by a factor of either \( \exp \left(\sigma \right) \) or \( \exp \left(-\sigma \right) \), where σ ∈ [0, ∞) is a rent volatility measure. In the continuous-time limit, an instantaneous rate of rent growth during time period \( \tau \) is normally distributed with the volatility \( \sigma \sqrt{\tau } \). At the beginning of each year, a lessee chooses the rent that is represented by Equation (3).Footnote 18 We introduce a proportional leasing cost \( c{\widehat{Y}}_t^T \), which is equivalent to a \( 12c \) -month vacancy cost at the time of cancellation. The lost income during vacant period is typically the most significant cost for the lessor.Footnote 19 We compute the landlord’s rental income for each rent path because the cancellation option is a path-dependent option. The present value of the T-year lease is computed as:

$$ {\hat{V}}^T={\displaystyle {\sum}_{t=0}^{T-1}{\mu}_t{\mathrm{E}}_0^Q\left[{\hat{Y}}_t^T\left(1-c{\mathbb{I}}_{\left\{{\hat{Y}}_t^T\ne {\hat{Y}}_{t-1}^T\right\}}\right)\right]}, $$
(B1)

where \( {\mu}_t \) is the risk-free discount factor for t -time periods, \( {\mathrm{E}}_0^Q\left[{\hat{Y}}_t^T\right] \) is the expected lease rate under the equivalent martingale measure Q, and \( {\mathbb{I}}_{\left\{{\hat{Y}}_t^T\ne {\hat{Y}}_{t-1}^T\right\}} \) is an indicator function that takes the value of one if the lease is cancelled and zero otherwise.Footnote 20 After computing the present value \( {V}^1 \) for a roll-over short-term strategy, we determine the initial lease rate for a T-period lease \( {\hat{R}}_0^T \) such that the consistent pricing condition holds: \( {V}^1 = {\hat{V}}^T \) for T = 2, …, 8.

Appendix C: Parameter Values for Calibration

We determine parameter values as follows. We use 1 % for the risk-free rate because the average end-of-month yields of Japanese Government Bonds are 1.32 % for 10-year bonds and 0.65 % for 5-year bonds between 2001 and 2012. Regarding rent growth rates and volatility, we use the Recruit quality-adjusted rent index for the Kanto region between 2005 and 2012.Footnote 21 In our lease sample, 39 % of general leases and 56 % of fixed-term leases are observed in this region. The average annual growth rate is 0.82 % and standard deviation is 1.97 %. Considering that there are smoothing issues in this aggregate index and that the volatility for an individual property is much larger, we use 1 % for the rent growth and 8 % for the rent volatility. Given that the rent volatility is relatively small, we assume that the risk premium on the short-term rent is 1 %. Regarding the lessor’s costs, we use the 2008 National Housing and Land Survey and compute the average vacancy rate for rental dwellings to be 19 %.Footnote 22 Additional contracting costs are at most a few hundred dollars and ignorable. We use 19 % as the high vacancy rate and 5 % as the low vacancy rate.

Appendix D: The Difference in Property and Tenant Characteristics Between Fixed-Term Lease, General Lease, and Owner-Occupied Samples

In this appendix, we present the result of probit regressions regarding the difference between owner-occupied properties and leased properties (Model (a)) and between fixed-term lease properties and general lease properties (Model (b)). Tables 6 and 7 present results for property characteristics and tenant characteristics, respectively. In Model (a), most property and tenant characteristics exhibit statistically significant differences between owner-occupied properties and leased properties. In contrast, in Model (b), differences are not statistically significant for most characteristics. These results are consistent with the descriptive statistics presented in Tables 1 and 2.

Table 6 Difference in property characteristics
Table 7 Difference in tenant and owner characteristics

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yoshida, J., Seko, M. & Sumita, K. The Rent Term Premium for Cancellable Leases. J Real Estate Finan Econ 52, 480–511 (2016). https://doi.org/10.1007/s11146-015-9528-x

Download citation

Keywords

  • Leasing
  • Housing
  • Asset pricing
  • Cancellation options
  • Term structure
  • Expectations hypothesis
  • Transaction costs
  • Hedonic regression
  • Japan

JEL Classification

  • G12
  • G13
  • R31