Considerations in the Design and Construction of Investment Real Estate Research Indices

Journal of Real Estate Research, The, Oct-Dec 2006 by Geltner, David, Ling, David C

Abstract

This paper surveys some of the major technical issues in the design and construction of real estate research indices, both appraisal-based and transactions-based. The paper considers property sampling issues, differences between transaction prices, market values, and appraised values, the trade-off between random measurement error and temporal lag bias, optimal reporting and property revaluation frequencies, and the uses and limitations of modern statistical techniques. Although one of the conclusions of the analysis is that most research questions are best addressed with transactions-based, rather than appraisal-based, indices in the United States, the paper suggests how appraisal-based indices can still be useful for some research purposes.

The past decade has seen the development of technological and information advances that hold great potential for moving investment real estate performance measurement to a new level of accuracy and usefulness for the industry. In particular, the development of large-scale electronic databases of commercial property transaction prices, and the advance of econometric techniques honed by the academic real estate community offers a tremendous new opportunity to advance the level of information and knowledge about the commercial real estate asset class.

Geltner and Ling (2001, 2006) conclude that the real estate investment industry's needs for performance measurement, research, and decision support are too diverse to be optimally met by a single index product or a single type of index. They present arguments for creating two separate families of index products: one focused on the asset class research support role, the other focused on the evaluation benchmarking and performance attribution support role.

Although Geltner and Ling (2001, 2006) discuss the general characteristics of benchmark and research indices, the present paper focuses more narrowly, but more deeply, on some basic technical considerations associated with the design and construction of commercial real estate return indices for asset class research support purposes. In particular, this paper discusses 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.

The paper proceeds as follows. First, the important statistical qualities of a real estate return index are identified. second, there is a discussion of the essential differences among transaction prices, appraised values, and market value. Third, a simple stylized model of the property valuation estimation process for asset class research is presented, followed by a discussion of the practical implications of the model for the construction of research-oriented return indices. Fourth, there is a discussion of the optimal reporting and property revaluation frequencies for appraisal-based indices, as well as property sampling issues in a transaction-based research index. The paper closes with a summary of the findings and concluding remarks.

It is worth noting that this paper is not a classical "scientific" research article in that a hypothesis is not presented and tested. Rather, this article is meant to be expository and demonstrative and to communicate some essential key points on investment real estate index construction to a broader audience of both academics and technical practitioners.

Statistical Qualities of a Real Estate Return Index

The dynamic statistical quality of a return index refers to the type of periodic time-series statistics that can be computed from the index, as well as the quality of those statistics. For example, how frequently can return statistics be calculated? Does the index tend to be "noisy"? To what degree do its periodic returns exhibit temporal lag bias? The four major attributes (or dimensions) of the index that interact to determine its dynamic statistical quality include:

1. Index return reporting frequency;

2. Frequency of revaluation observations per property;

3. Number of properties in the underlying population tracked by the index; and

4. Index construction "technology," or methodology used to construct the index from the underlying valuation observations.

"Reporting frequency" refers to the periodicity of reported returns or pricechanges in the index (e.g., annually, quarterly, or monthly). Labeling this frequency m per year, m = 1 for an annual index, m = 4 for a quarterly index, and m = 12 for a monthly index. Higher frequency reporting implies shorter individual return periods, as the period length is the inverse of the frequency.

"Revaluation frequency" refers to the average number (or fraction) of transaction price observations or ("serious") reappraisals per year per property in the index population.1 Labeling this f per year, f = 1 if each property is reappraised on average once per year, f = 0.2 if properties in the subject population transact (are bought and sold) on average once every five years.