Academic journal article Real Estate Economics

Smoothing in Commercial Property Valuations: Evidence from Individual Appraisals

Academic journal article Real Estate Economics

Smoothing in Commercial Property Valuations: Evidence from Individual Appraisals

Article excerpt

Jim Clayton [*]

David Geltner [**]

Stanley W. Hamilton [***]

We explore the causes and extent of appraisal smoothing, defined as a temporal lag bias in appraisals, by analyzing how appraisers use the transaction price data available to them. We test the empirical validity of the partial adjustment model that underlies the traditional "unsmoothing" of benchmark return indexes. We reject the no-lag null hypothesis and find that the extent of bias-inducing behavior appears to vary over time in the manner suggested by rational appraisal behavior as the quantity and quality of contemporaneous transaction information changes. We find evidence that appraisers valuing the same property in consecutive periods anchor onto their previous appraised values, resulting in more lagging than first-time appraisals. An implied policy prescription is for investment managers to rotate appraisers so as not to allow the same appraisal firm to consecutively value the same property.

One of the major concerns with existing commercial property return indexes is that they are typically based on appraised values rather than contemporaneous transaction prices. Previous literature suggests that this results in "smoothing" of the return index. Smoothing, in this sense, is characterized by reduced volatility and/or lagging in the appraisal-based index as compared to a contemporaneous transaction-based index. In fact, formal research into the index smoothing phenomenon has generally assumed that such smoothing exists. Starting from this assumption, it has typically postulated a "partial adjustment" model of the relation between the appraisal-based and a corresponding "true" index, and then proceeded to focus on methods to "unsmooth" (or "de-lag") the appraisal-based index to infer something closer to a "true" real estate return index.[1] Consistent with perceived notions of index smoothing, these techniques produce revised return indexes that have greater volatility and value turning points that occur earlier in time.

Recently this unsmoothing literature has come under attack from a couple of directions. Lai and Wang (1998) argue that appraisal-based returns can be more volatile than "true" property returns. Geltner (1998) responds that Lai and Wang have not carefully defined what they mean by "true" returns, and that they have confused smoothing (which may encompass either volatility reduction or return lagging) at the aggregate (index) level with volatility reduction alone at the disaggregate (individual property) level. Ling, Naranjo and Nimalendran (1999) note that previous unsmoothing models either depend on the assumption that true returns lack serial correlation (which may not be so in private real estate markets) or that they are ad hoc in their theoretical underpinnings. For example, some unsmoothing procedures have used subjective assumptions to adjust the appraisal-based return data.[2] Corgel and deRoos (1999) present a comparative analysis of the statistical properties of estimated true returns implied by seve ral different unsmoothing models, and they note that the optimal real estate allocation in a mixed-asset portfolio including securities is somewhat sensitive to the unsmoothing model used.

Both Lai and Wang (1998) and Cho and Megbolugbe (1996) suggest that an important deficiency in the unsmoothing literature is that there is little direct empirical support for the quantitative partial adjustment model that underlies the unsmoothing methodology. That is, while the underlying partial adjustment framework generally fits with market participants' intuition about the appraisal process, there has been no empirical testing and calibration of this model.[3]

This lack of empirical testing is attributable to two major problems. First, depending on the definition of the "true" real estate returns, it may be conceptually impossible to empirically observe the true returns that would be necessary for an empirical test or calibration of the smoothing model. …

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