Subjectivity and bias is one of the biggest problems facing appraisers and users of appraisal reports. I have noted that my Fair Commission Model (FCM) will at certain points have to rely on calibrated estimates. It may be objected that the calibrated estimate approach is subjective and not objective. This criticism reflects a confusion about the nature of subjectivity and objectivity. I contend that calibrated estimates are no more inherently subjective than sector wide or local data sources.
Subjectivity and objectivity are a function of the accessibility of evidence.1 If the evidence upon which a calibrated estimate is based is openly and clearly observable to more than one expert, the estimate is objective. If the evidence upon which a calibrated estimate is based is not openly and clearly observable, it is subjective. In making or evaluating an estimate on of the key appraisal parameters any trained, experienced individual will have access to the nature, history and financial condition of the subject company (SC) and the competitive market in which it operates. Two or more experts may come up with different parameter estimates, but any differences will be due to different past experiences or due to bias.
Example: Suppose we have two experienced owner operators of barber shops who have each bought a shop in the past. One operator experienced a customer transfer rate of 70% while the other experienced a transfer rate of 45%. In trying to estimate the transfer rate of some third SC, it would be no surprise if the range of estimated transfer rates given by the two experts were different. The different results do not demonstrate a lack of objectivity or the presence of bias. Each expert had access to the same information but came to different conclusions because they had different past experiences.
What would constitute a subjective judgment? Subjective judgments involve observations accessible only to one individual. Let's say your arm hurts and I ask you how much it hurts and you tell me “a lot”. Your judgment on the intensity of your pain is subjective, precisely because you are the only one with access to the sensation of pain. You are the only one in a position to judge its intensity.
While I believe that calibrated estimates are no less objective than sector wide data, they are certainly more prone to the influence of bias. Business appraisers are almost always engaged by one party with some form of competing economic interest with another party. A seller of an equity interest will seek a higher appraisal than a buyer. One party in a marital or partnership dissolution will want a higher appraisal, the other a lower. The IRS in estate and gift taxation seeks higher valuations while taxpayers seek lower ones.
Appraisers can aspire to disinterested objectivity, but pressure, both subtle and not so subtle, is always present to slant or bias a valuation to the advantage of those paying the fee. Bias is always a possible influence on our conclusions. Those charged with mediating conflicting economic appraisals rightfully cast a wary eye to the appraisal process. These are the observations of Aswath Damodaran, a widely respected theorist on the valuation of publicly traded securities:
"You tell me who's paying the expert and I'll tell you what the bias is and where it is going in the analysis."2
A published survey of transfer rates or attrition rates not performed with any particular SC appraisal in mind can hardly be suspected of being biased with the thought of influencing a particular appraisal outcome. The same cannot be said of calibrated estimates. If the estimate is being made by an owner or employee of an SC, then there is likely to be a monetary incentive to bias answers.
One saving grace is that bias in making parameter estimates is usually easy to detect. A consistent pattern of estimates that pushes the appraised value of the equity either upward or downward is a fairly good indication of intentional bias. I should note also that even physical measuring devices are often biased in that they consistently yield measures that are either higher or lower than the true value. We do not reject physical measurements because of the possibility of bias and we should not reject calibrated estimates for that reason either.
1. For a fuller discussion see my “Qualitative Judgments and Consistency in Business Valuation.” The Journal of Business Valuation and Economic Loss Analysis, Volume 13, 2009.
2. Damodoarn, Answath, Strategic Risk Taking: A Framework for Risk Management, Wharton School Publishing, 2007, Page 127.
Copyright 2018 Michael Sack Elmaleh