A Quarterly Transactions-based Index of Institutional Real Estate Investment Performance and Movements in Supply and Demand

Abstract

This article presents a methodology for producing a quarterly transactions-based index (TBI) of property-level investment performance for U.S. institutional real estate. Indices are presented for investment periodic total returns and capital appreciation (or price-changes) for the major property types included in the NCREIF Property Index. These indices are based on transaction prices to avoid appraisal-based sources of index “smoothing” and lagging bias. In addition to producing variable-liquidity indices, this approach employs the Fisher-Gatzlaff-Geltner-Haurin (Real Estate Econ., 31: 269–303, 2003) methodology to produce separate indices tracking movements on the demand and supply sides of the investment market, including a “constant-liquidity” (demand side) index. Extensions of Bayesian noise filtering techniques developed by Gatzlaff and Geltner (Real Estate Finance, 15: 7–22, 1998) and Geltner and Goetzmann (J. Real Estate Finance Econ., 21: 5–21, 2000) are employed to allow development of quarterly frequency, market segment specific indices. The hedonic price model used in the indices is based on an extension of the Clapp and Giacotto (J. Am. Stat. Assoc., 87: 300–306, 1992) “assessed value method,” using a NCREIF-reported recent appraised value of each transacting property as the composite “hedonic” variable, thus allowing time-dummy coefficients to represent the difference each period between the (lagged) appraisals and the transaction prices. The index could also be used to produce a mass appraisal of the NCREIF property database each quarter, a byproduct of which would be the ability to provide transactions price based “automated valuation model” estimates of property value for each NCREIF property each quarter. Detailed results are available at http://web.mit.edu/cre/research/credl/tbi.html . Copyright Springer Science+Business Media, LLC 2007Transaction-based index, Commercial real estate investment performance, NCREIF database, Commercial property type returns, Constant liquidity index, Ridge regression techniques,

Revisiting supply and demand indexes in real estate

“…The indexes for demand and supply reservation prices that follow from equations (23) Fisher et al (2007), the indexes are presented such that the mean of the supply and demand indexes are equal. The indexes can also be used as a liquidity indicator; if the difference between demand and supply becomes smaller (larger) there is less (more) liquidity in the market.…”

“…To do so, we further develop and extend the Fisher et al (2003Fisher et al ( , 2007 methodology to a repeat sales indexing framework. This has the advantage that it takes care of all unobserved heterogeneity, which is an important consideration in commercial real estate.…”

“…The first and most widely employed technique for constructing separate demand and supply reservation price indexes in real estate was pioneered by Fisher et al (2003Fisher et al ( , 2007.…”

“…In order to apply the Fisher et al (2003Fisher et al ( , 2007 method in a repeat sales framework, we adapt the sample selection methodology for repeat sales models developed by Gatzlaff and Haurin (1997). Perhaps even more importantly, our methodology allows us to esti-mate supply and demand indexes at a much more granular level, in part because it allows us to use the much larger RCA database.…”

“…Perhaps even more importantly, our methodology allows us to esti-mate supply and demand indexes at a much more granular level, in part because it allows us to use the much larger RCA database. The Fisher et al (2003Fisher et al ( , 2007 methodology was limited by the NCREIF database coverage to just estimating national indexes, even though property markets are inherently local in nature. A key innovation in our methodology, which also enables granular index production, is our use of a Bayesian, structural time series model for index estimation, building on the work of Francke (2010); .…”