Estimating Commercial Property Fundamentals from REIT data

45 Pages Posted: 7 Jul 2021 Last revised: 1 Nov 2021

See all articles by David Geltner

David Geltner

Massachusetts Institute of Technology (MIT); MIT Center for Real Estate

Anil Kumar

Aarhus University, Department of Economics & Business Economics; Danish Finance Institute

Alex Van de Minne

University of Connecticut - School of Business

Date Written: October 31, 2021

Abstract

In this paper we propose a new methodology for the estimation of fundamental property-level investment real estate time series performance and operating data using real estate investment trust (REIT) data. The methodology is particularly useful to develop publicly accessible operating statistics, such as income or expenses per square foot. Commercial property operating statistics are relatively under-studied from an investment perspective. To demonstrate the methodology and its usefulness, we estimate the time series of property values, net operating income, cap rates, operating expenses and capital expenditures, per square foot of building area, by property type (sector) at a quarterly frequency for multiple specific geographic markets from 2004 through 2018. We show illustrative results for Los Angeles offices and Atlanta apartments. The methodology is essentially an extension and enhancement of the so-called "Pure Play" method introduced by Geltner and Kluger (1998). It enables easy derivation of important basic data that should be useful for academic and industry practitioner analysts, derived from high quality stock market based information. The extensions and enhancements introduced here to the prior methodology allow estimation of actual quantity levels rather than just longitudinal relative values (index numbers). They also avoid the need for any data source other than published REIT data. Our methodology allows for an "additive" model structure that is more parsimonious to address the need for granular market segmentation. We also introduce a Bayesian framework that allows the estimation of reliable time series even in small markets.

Keywords: Real Estate Price Indices, Commercial Real Estate, REITs, Structural Time Series Modelling, Bayesian Inference, Real Estate Operating Statistics, Capital Expenditures, Operating Income and Expense

JEL Classification: R30, C01, C11

Suggested Citation

Geltner, David and Kumar, Anil and Van de Minne, Alex, Estimating Commercial Property Fundamentals from REIT data (October 31, 2021). MIT Center for Real Estate Research Paper No. 21/11, Available at SSRN: https://ssrn.com/abstract=3881407 or http://dx.doi.org/10.2139/ssrn.3881407

David Geltner (Contact Author)

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
Cambridge, MA 02139
United States

MIT Center for Real Estate ( email )

77 Massachusetts Avenue
Cambridge, MA 02139
United States

Anil Kumar

Aarhus University, Department of Economics & Business Economics ( email )

Fuglesangs Alle 4
Aarhus V, 8210
Denmark

Danish Finance Institute ( email )

Alex Van de Minne

University of Connecticut - School of Business ( email )

368 Fairfield Road
Storrs, CT 06269-2041
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
299
Abstract Views
946
Rank
154,029
PlumX Metrics