According to the 14th Edition of the Appraisal of Real Estate, there are several techniques available to quantify adjustments to the sale prices of comparable properties.•Data analysis techniques, such as paired data analysis, grouped data analysis, and secondary data analysis.
Paired data analysis is the process of measuring a single difference in value between two properties, by analyzing properties that are similar in all other respects.
Grouped data analysis is related to paired data analysis, but studies pairs or sets of data to identify the effect on a dependent variable. It extends the logic of paired data analysis to larger data sets. An example would be to compare a group of properties situated on interior lots, as well as a group of properties on corner lots, for purposes of developing a range and reconciling the value indications.
In contrast, secondary data analysis makes use of data that does not directly pertain to the subject or comparable properties. It is data often obtained from data vendors, county assessors, or other means, and is used to support adjustments.
Statistical analysis in appraisal most commonly involves the application of regression analysis. Simple linear regression allows comparison of a single independent variable, while multiple regression allows for comparison of many independent variables.
Graphic Analysis is a variant of statistical analysis in which the appraiser arrives at a conclusion by visually interpreting a graphic display of data. A simple display of grouped data on a graph may illustrate how the market reacts to variations in the elements of comparison or may reveal submarket trends.
In cost analysis, adjustments are based on cost indicators, such as depreciated building cost, cost to cure, or permit fees. Capitalization of income differences can be used to derive an adjustment when income loss reflects a specific deficiency in the comparable, such as lack of an elevator in a low-rise office building, or inadequate parking facilities for a convenience store or medical office building.
Historically, Paired Data Analysis, or "matched pairs" has often been largely regarded as one of the most reliable techniques, with cost related adjustments and capitalized income differences available as alternate techniques for certain circumstances where they were appropriate.
In contrast, statistical and graphic analysis were largely the domain of academics, with relatively few local fee appraisers utilizing these techniques. However, graphic analysis has been recognized in recent years for its simple, yet powerful ability to summarize and reflect trends within the market, as well as relevant data sets, for purposes of deriving adjustments and inferring conclusions regarding the subject property based on its characteristics related to the elements of comparison.
Evidence of this can be seen in not only the appraisal literature, where numerous articles have been published over the past three decades. One of the early articles on the subject noted in 1986: "Visual display of quantitative appraisal information can significantly affect the successful presentation of data and the conclusions of real estate studies. Graphs and charts can facilitate clients understanding of increasingly complex real estate appraisal techniques" . However, while there was relatively early recognition of the benefits of graphics within the appraisal field by some appraisers, its use in modern day appraisal has been relatively limited.
In order to understand why such a powerful technique is not more widely used by more appraisers, it is helpful to understand recent history:
According to Wikipedia, "the mass-market consumer electronic devices effectively began in 1977 with the introduction of microcomputers. However, early personal computers were of interest mostly to hobbyists and technicians." In fact, it was not until 1984 until Apple launched the Macintosh, with advertising during the super bowl, that the first successful mass-market mouse-driven computer with a graphical interface was available. In 1985, Microsoft developed the Windows operating system in cooperation with IBM, and in 1992, released Windows 3.1. Microsoft recognized the importance of the internet in 1995 and ultimately released Internet Explorer in 1997, along with Microsoft Office 97.
With the cost of personal computers becoming more affordable and the functionality and usability of software improved, coupled with understanding of the power of the internet, personal computers started to become much more common. In 2001 personal computer sales truly began to reach critical mass, with 125 million personal computers shipped in that year, versus the 48,000 sold in 1977.
The point of this brief history discussion on personal computers, is simply that it has been less than 15 years since personal computers have become virtually ubiquitous. However, a recent study completed by the Appraisal Institute concluded that approximately 50% of all existing appraisers have 20+ years experience. This suggests that more than half the existing appraisers in the field today were trained and learned the valuation process well before computers became in wide use. And even for many younger appraisers, their mentors often continue to teach them the same techniques and methods that were taught to them as new appraisers. As a result, an extraordinarily high percentage of existing appraisers tend to approach the valuation process in a manner that was largely developed before personal computers and software packages like Excel were widely available.
While personal computers have become increasingly important to all appraisers over the past decade, particularly as a word processing tool that effectively eliminated the use of typewriters, the appraisal profession as a whole, at least in terms of the fee appraiser community, has been slow to embrace the techniques of graphic analysis within the appraisal process.
Despite the relatively slow adaptation by the fee appraiser community of graphic analysis, this trend is likely to change in the coming years as a result of the prominent role this technique exhibited in the most recently released 14th Edition of The Appraisal of Real Estate text book, published in 2013 by the Appraisal Institute. This reference book is considered to represent the authoritative text on real estate appraisal, having been cited by over 700 U.S. court decisions.
It is difficult to overstate the significance that this new prominence within this publication, given the fact that all preceding editions have merely mentioned graphic and statistic analysis as acceptable techniques in quantifying adjustments, but provided little discussion. In contrast, the 14th Edition provides numerous examples of graphic analysis applications and use, particularly in the sales analysis chapter, in addition to devoting an 18-page discussion on the matter within the addendum pages.
Given the lack of thorough discussion and coverage within previous additions of the Appraisal of Real Estate text, the reluctance of the fee appraiser community to embrace this tool can be considered understandable, however, it seems more likely now that appraisers will begin to recognize the ability of simple linear regression, which does not require an advanced educational background in statistics, but can be used to illustrate and reflect the thought processes and conclusions of market participants and provide a persuasive representation of that data.
A very important, yet often overlooked concept in appraisal, includes the principle of diminishing marginal productivity, which is governed by the principle of balance. Simply stated, this law of economics holds that increases in the agents of production added to a parcel of property produce greater net income up to a certain point, however, further increments in the agents of production will cause productivity to decline proportionately.
By way of example; all appraisers have struggled with size adjustments for say a 5,000 square foot office building, when the available sale comparables range from 2,500 SF to 7,500 SF. What is the appropriate level of adjustment? In many cases, regression analysis provides the most accurate and reliable method of making this determination.
This technique often allows the patterns of the market to become evident, making it possible to draw inferences about the attitudes and behavior of the market and then to objectively draw conclusions.
In fact, effectively controlling for size differences makes it easier to discern appropriate adjustments for the remaining elements of comparison. It is fundamentally the same principal upon which the matched pairs technique depends: the ability to control for the other elements of comparison, allowing the appraiser to measure differences in value attributable to other elements of comparison.
If market value is an objective value created by the collective patterns of the market, market analysis should then clearly and correctly demonstrate the behavior of the market. Further, a market value appraisal should demonstrate the relationship of an individual property to the collective market pattern.
Stated another way, a pattern of valid and relevant market data is like the scale of a meter from which values can be objectively extracted and verified by any reader of an appraisal. The fundamental role of graphic analysis in an appraisal is to facilitate an accurate and verifiable "reading" of the market. Most appraisal users have sufficient education and background to visually evaluate goodness of fit when relevant data are correctly plotted and labeled. The simplicity and intuitive nature of graphic analysis allows a broad range of appraisal users to rapidly evaluate the reasonableness of the conclusions. In contrast, more sophisticated statistical methods may demand greater experience and education of the user without necessarily improving the reliability or credibility of the analysis. Excessively elaborate statistical analysis could be misapplied or be abused if it conveys a greater degree of scientific certainty than is warranted.
Appraisers do not necessarily seek to maximize the number of sale comparables in order to achieve statistic significance. On the contrary, once a thorough search for market data has been completed, appraisers filter the data, eliminate irrelevant or unreliable data, and select only the most relevant and appropriate sales. The process of filtering and eliminating irrelevant or less relevant data is part of defining the subjects market. It consists of market segmentation, which focuses on users, and disaggregation, which focuses on the property.
By carefully selecting only the most relevant data, appraisers mirror market attitudes and behavior. This filtering and eliminating process is essential to the appraisal process. Expanding the size of comparable data sets simply to accommodate rigorous application of statistical methods would likely introduce undesirable "noise" and result in misleading conclusions that do not adequately reflect market attitudes, motivations, and behavior. In appraisals, therefore, adding more comparables to perform statistically valid manipulations does not necessarily improve the reliability or credibility of the market value indications.
As long as the reliability of the value indication improves, increasing the number of comparables is desirable. For example, secondary comparable data may be needed to support a specific adjustment to the price of the "most applicable" comparable. However, for these smaller data sets, graphic analysis tends to provide more a more meaningful and relevant summary of the data used in most appraisals.