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Article Excerpt
This paper investigates the relation between the term structure of rents and future spot rents. A rich database of office rental agreements for various maturities is used to estimate the term structure of rents, and from this structure implicit forward rents are extracted. The data pertain to commercial properties in the three largest Swedish cities for the period 1998-2002. A positive relation between forward and spot rents is found in some regions, but forward rents underestimate future rent levels. Another contribution of the paper lies in the area of rental index construction. We provide evidence that rental indices should not only be quality constant (i.e., control for characteristics), but should also be maturity constant.
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Commercial leases are signed for a variety of maturities (terms). If rent levels for different terms are observable, then it should be possible to construct the term structure of rents in analogy with the term structure of interest rates. In most instances, one would expect very short leases to have high rent levels due to the transaction costs associated with such leases for the owner, while the longer end of the term structure curve can be either upward-or downward-sloping. Consideration of the term structure of existing rental contracts is obviously important when valuing individual properties. It should also matter for our picture of overall market movements. Rental indices that are constructed without controlling for the term structure may be biased if the composition of leases over different terms changes through time. Further, and this is the main focus of the paper, just like the term structure of interest rates is hypothesized to contain information that is useful in predicting future spot interest rates, the term structure of rents may offer important insights about market expectations of future rent levels.
In analogy with fixed-income securities, one may formulate an "expectations hypothesis" of the term structure of rents stating that forward rents are unbiased estimates of future spot rents. It is well known that such a hypothesis holds for interest rates under very restrictive conditions only. It can be shown that similar assumptions as in interest rate theory regarding risk aversion and the stochastic nature of interest rates (and of rents) are required in the case of rental contracts as well (see Clapham and Gunnelin 2003). The expectations hypothesis is conveniently formulated in terms of forward rates. There is no explicit forward market for leases, but it is possible to extract implicit forward rents from the spot rents at different maturities. For instance, the 1-year forward rent for a 1-year lease is implied by current spot rents on 1-year and 2-year contracts. These implicit forward rents may not be directly relevant for trading, since it is not possible to construct synthetic forward contracts, but it is still relevant to investigate if they are able to predict future spot rents. The mechanism that would bring about such a relation operates even in the absence of explicit or implicit forward contracts--in signing a lease, tenants could be expected to weigh the cost of a long contract against the expected costs (and uncertainty) of a sequence of shorter contracts. In other words, implicit forward rents should reflect market expectations of future spot rates. Under idealized conditions, they may even be unbiased predictors of future spot rates.
Despite the importance for actors on real estate markets of considering the term structure of rents, research in this area is limited. Grenadier (1995, 2002) puts forth equilibrium models of lease valuation that account for the term structure. Gunnelin and Soderberg (2003) report that differences in lease terms have a statistically significant impact on commercial rents in the Stockholm CBD for 7 out of 15 years between 1977 and 1991, with an upward-sloping structure in the bullish real estate markets of the 1980s shifting to a downward slope in 1990 at the start of the bearish years for real estate markets. Further evidence is provided by the lease-valuation model of Stanton and Wallace (2002) estimated on data for suburban malls in 14 U.S. metropolitan areas. They find significant differences in the slope of the term structure across markets.
There are a number of other empirical studies of commercial leases where lease length is one of the rent-explaining variables. The evidence on the impact of lease length varies. Early studies on U.S. data by Brennan, Cannaday and Colwell (1984) as well as Benjamin, Sa-Aadu and Shilling (1992) report statistically insignificant term effects, whereas Benjamin, Boyle and Sirmans (1990) find a negative and significant relationship between rents and term. Wheaton and Torto (1994) in a comprehensive study of over 50 U.S. metropolitan markets find a consistently positive term effect. Fisher and Webb (1997) find a significant positive term parameter for Chicago suburbs, but insignificant effects in a similar analysis for the Chicago CBD (Webb and Fisher 1996). (1) None of these hedonic studies, however, allows for possible variation in the term structure of lease rates over time.
Most studies have made use of U.S. data. Here, we study the term structure of rents using a rich database of office rental agreements for the three largest Swedish cities (Stockholm, Gothenburg and Malmo). The Swedish market differs from the U.S. market in at least two important ways. First, the duration of a typical Swedish lease (3 years) is shorter than that of a typical U.S. lease. Second, Swedish lease contracts are "purer," that is, have fewer option clauses than their U.S. counterparts. This feature makes them well suited for testing whether implicit forward rents are good predictors of future spot rents. A total of 4,387 leases for the period 1998-2002 are available for analysis. This period is characterized by sharp rent increases with rents growing by 50 to 90% in the Stockholm region and by 40 to 50% in Gothenburg and Malmo. The data include information about the maturity of leases, which ranges from a few months to over 10 years. Apart from age, the data set is limited on information about the property, but unique property identifiers make it possible to control for location and other property characteristics.
We use regression analysis to estimate the term structure of rents. Given the role of term structure effects, we investigate the sensitivity of rental indices to the method used for constructing such indices. Three types of indices are considered: indices computed from rent averages, indices that control for the structural and locational characteristics of properties and indices that control both for the characteristics of properties and the lease maturities. Controlling for the characteristics of properties appears to be very important, but controlling for the maturity of leases also has a sizeable impact on the estimated indices.
Based on these estimates of the term structure, we extract implicit forward rents and test for the ability of current forward rents to predict future spot rents. To the best of our knowledge, this is the first formal test of the expectations hypothesis for commercial leases. We find a positive (and significant) relationship in Stockholm, but implicit forward rents underestimate actual increases in rent levels, and we can reject the hypothesis that forward rates are unbiased predictors of future spot rents. This conclusion holds true even when transaction costs are taken into consideration.
The current paper differs in several ways from that of Gunnelin and Soderberg (2003), henceforth GS. First, we use a larger and more detailed data set covering several markets and a more recent time period. Second, GS estimate a parametric term structure, whereas the current study uses a nonparametric approach thereby putting less restriction on the term structure curve. Third, they discuss the relationship between term structure and rental expectations only informally. They note that the variation in term structure by and large seems to be consistent with the evolution of market rents during the examined period, but they do not formally test if the term structures predict future rents. The key contribution of this paper is to test such a relationship statistically. Finally, GS restrict the sample to leases signed during a 4-month period each year, thus discarding a significant number of observations. This paper employs an interpolation scheme in order to use leases signed throughout the year to infer the January term structure.
The structure of the paper is as follows. The next section provides a brief theoretical background on the term structure of rents. We then give an empirical overview of the main features of Swedish office markets in recent years, followed by a presentation of the data set used in this study. Our estimates of term structures are then presented, followed by an analysis of the importance of considering the term structure of rents when constructing rental indices....
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