Controlling for the Impact of Variable Liquidity in Commercial Real Estate Price Indices

Liquidity in private asset markets is notoriously variable over time. Therefore, indices of changes in market value that are based on asset transaction prices will systematically reflect intertemporal differences in the ease of selling a property. We define and develop a concept of "constant-liquidity value" in the context of a model that is characterized by pro-cyclical volume of trading. We then present an econometric model that allows for estimation of both a standard transaction-based price index and a constant-liquidity index. Our application to the NCREIF database reveals that, in the case of institutional commercial real estate investment, constant-liquidity values tend to lead transaction-based and appraisal-based indices in time, and also to display greater volatility and cycle amplitude. The differences can be significant for strategic investment policy viewed from a mean-variance portfolio optimization perspective.     

The 2015 Maastricht-NUS-MIT International Real Estate Finance &; Economics Symposium: Editors’ Introduction to the Special Issue

We use an empirical model of commercial mortgage spreads to examine how tenant diversification impacts credit spreads for mortgages on retail properties. We find that mortgages on properties with a highly diversified tenant base have spreads that are up to 7.1 basis points higher than spreads on mortgages for single-tenant properties, but that mortgages on properties with moderate levels of tenant diversification have spreads that are up to 5.2 basis points lower than mortgages on single-tenant properties. The spread discount for mortgages on properties with moderate levels of tenant diversification disappears when the lease of the property’s largest tenant expires before the loan matures. Despite the spread discount that is given to properties with moderate levels of tenant diversification, we find that the likelihood with which a mortgage goes into default increases as tenant diversification increases.     

Call for papers and participation

Call for papers and participation     

Riskiness of Real Estate Development: A Perspective from Urban Economics and Option Value Theory

In this article, we define a new construct for urban economic and investment analysis, which revisits the conventional wisdom that investment in real estate development is riskier than investment in stabilized property assets. This new construct, referred as a “development asset value index” (DAVI), is a value index for newly developed properties (only) in a given geographical property market. It tracks longitudinal changes in the highest and best use (HBU) value of locations, and it reveals developer and landowner behavior taking advantage of the optionality inherent in land ownership. In particular, the DAVI reflects developers' use of flexibility in the exercise of the call option to (re)develop the property to any legal use and density. We empirically estimate a DAVI for commercial property (i.e., central locations) and compare it with a corresponding traditional transaction‐price‐based property asset price index (PAPI) corrected for depreciation. We believe that the difference primarily reflects the realized value of flexibility in land development. We find that the DAVIs display greater value growth and are smoother over time and less cyclical than their corresponding PAPIs for the same locations. This suggests that developers successfully use flexibility, and that development may be riskier than stabilized property investment due primarily only to leverage effects (construction costs). Practical implications are also discussed.     

Estimating Real Estate Price Movements for High Frequency Tradable Indexes in a Scarce Data Environment

Indexes of commercial property prices face much scarcer transactions data than housing indexes, yet the advent of tradable derivatives on commercial property places a premium on both high frequency and accuracy of such indexes. The dilemma is that with scarce data a low-frequency return index (such as annual) is necessary to accumulate enough sales data in each period. This paper presents an approach to address this problem using a two-stage frequency conversion procedure, by first estimating lower-frequency indexes staggered in time, and then applying a generalized inverse estimator to convert from lower to higher frequency return series. The two-stage procedure can improve the accuracy of high-frequency indexes in scarce data environments. In this paper the method is demonstrated and analyzed by application to empirical commercial property repeat-sales data.     

Loss Aversion and Anchoring in Commercial Real Estate Pricing: Empirical Evidence and Price Index Implications

Loss aversion behavior plays a major role in the pricing of commercial properties, and it varies both across the type of market participants and across the cycle. We find that sophisticated and more experienced investors are at least as loss averse as their counterparts and that loss aversion operated most strongly during the cycle peak in 2007. We also document a possible anchoring effect of the asking price in influencing buyer valuation and subsequent transaction price. We demonstrate the importance of behavioral phenomena in constructing hedonic price indices, and we find that the impact of loss aversion is attenuated at the aggregate market level. This suggests that the pricing and volume cycle during 2001–2009 was little affected by loss aversion.