David Geltner () (George Macomber Professor of Real Estate Finance, Department of Urban Studies & Planning, Massachusetts Institute of Technology, Cambridge, MA 02139) David C. Ling () (William D. Hussey Professor of Real Estate, Department of Finance & Real Estate, Warrington College of Business Administration, University of Florida, Gainesville, FL 32611-7160)
Abstract
Since the founding of NCREIF almost three decades ago statistical methodologies useful for investment performance index construction have advanced dramatically, notably including developments such as the repeated-measures regression (RMR) and related noise-filtering techniques. In recent years, electronic databases of commercial property prices have been developed that far exceed the quality and coverage of those databases available only a few years ago. Together, these two developments offer capabilities for transactions-based indices, mass appraisal, and other tools that could be very useful for improving real estate research indices. This paper focuses on the technical considerations associated with the design and construction of commercial real estate return indices for asset class research. In particular, we discuss in detail property sampling issues, differences between transaction price and appraisal based indices, the trade-off between random measurement error and temporal lag bias, optimal reporting and property revaluation frequencies, and the uses and limitations of some econometric methods of index construction developed over the past decade in the real estate academic literature.
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