Adjustments: Now What?
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So, what are these methods and techniques?
We’re told to “support” our adjustments. We hear words like “prove” your adjustments… as if there were some magic formula which can give an exact, correct, and absolutely true number.
It used to be so easy… Our trainer gave us a sheet with the “right” adjustments. Simple.
USPAP Standards Rule 1-1 says we must be aware of, understand, and correctly employ recognized methods and techniques. What are they? Who recognizes them? How do I apply them?
So, what are these methods and techniques? Let’s look.
In The Appraisal of Real Estate (ARE) p.46, it says: “Qualitative analysis techniques may also be applied for elements of comparison for which quantitative adjustments cannot be developed.” So, it seems the very first reference in the ARE says some adjustments cannot be quantitatively developed!
The next reference (ARE) p.91 says, “…with supportable adjustments to recent comparable data providing the most credible evidence of market value.” So now we read that making adjustments which are “supportable” is enough (but there is no need to actually support or calculate or estimate or reckon or imagine such a number – should be enough to be “credible” (worthy of belief). “I could support it if I really wanted to!”
Then on page 275, “Statistical Analysis in Appraisal”, says:
“Statistical techniques like regression analysis have become accepted tools in the application of the approaches to value. In fact, the application of regression analysis to comparable sales data is a natural and obvious extension of the traditional analysis of differences in the sale prices of comparable properties in the adjustment process. A simple linear regression model can be used to estimate the influence of a particular characteristic with significant statistical reliability when an adequate supply of data is available.”
On page 377, The Sales Comparison Approach, it states clearly that an adjustment can be determined!
“Similarly, in applying the sales comparison approach appraisers often analyze conclusions derived in the other approaches to determine the adjustments to be made to the sale prices of comparable properties.”
On page 388, it says “Appraisers analyze market data using mathematical applications to derive quantitative adjustments.”
On pages 398-404, it tells us how to adjust. Here are the methods explained:
- Paired data: Compare two properties/transactions which are exactly the same except for the one feature.
- Grouped data: Compare comparable sales grouped by an “independent variable”. (It examples a time adjustment using date of sale – which exhibits the same “data discarding” issue as has been found in the GSEs residential form 1004mc, which give wrong results or in the wrong direction.)
- Secondary data: “This technique makes use of data that does not directly pertain to the subject or comparable properties.”
- Statistical: “An appraiser can develop a series of adjustment factors to control for different tract sizes by creating a simple linear regression model and then use the results of the regression analysis as a means of inferring the size adjustment for properties within the range of the data. If a reasonable pattern emerges, the model can be applied to a group of sales with differing land sizes to test its accuracy, although the process might also demonstrate that the indicated adjustments are incorrect.”
- Scenario: “Scenario analysis is a form of modeling in which the conditions created by future events are forecast to test the probability or correlation of alternative outcomes.” Got it.
- Graphic: “Use grouped data to illustrate variations in the elements of comparison.”
- Cost Related: “In cost analysis, adjustments are based on cost indicators such as depreciated building cost, cost to cure, or permit fees.”
- Capitalize income differences: “when the income loss incurred by a comparable property reflects a specific deficiency in the property”. (This presumes identical in all other respects.)
- Qualitative: “recognizes the inefficiencies of real estate markets and the difficulty of expressing adjustments with mathematical precision.” (Does this imply that quantitative methods are mathematically precise?)
- Trend: “In the context of statistical theory, trend analysis is often defined as analysis of a time series. In the context of sales comparison, the term simply refers to the use of statistical techniques to make comparisons of variables other than time.”
- Ranking: “The comparable sales are ranked according to overall comparability or by some other element of comparison so that the relative position of each comparable sale to the subject property is clear. Specific value trends can thereby be established for elements of comparison that are market-sensitive, and those that show no discernible or reasonable trends will be discarded.”
There you have it. Hopefully this clears it all up.
References are to The Appraisal of Real Estate, 14TH ed., Appraisal Institute, Chicago, 2013
Excellent. I never received a list of adjustments when I started well before licensure. Guess I missed that class. LOL
Statistical analysis is a joke, I have seen them for court cases, ran in an old 100 year old urban city area with so many variations in housing sizes, conditions, bedroom counts. Maybe, just maybe in a true cookie cutter development, and you would still need the builders specs and all those inflated charges they charge the buyers !
Most frequently after the builders sell out the The resales DO not reflect the builders premiums.
Market sales from the builder reflect velocity from the project, advertising, and promotion. Market sales from local and regular sources reflect the greater market.
Most appraisal work is for single family sales and refi’s requiring financing. Each of these has their influence on sales prices.
Appraisers HAVE to look at the larger market for the trends set and for the individuality created by the process.
All of these situations have need in the process, and all should be considered.
Computers became believable when Big Blue defeated the Russian chess master. Our health grew greater with the 1913 publications of the medical journals and statistics.
Personally I like cost related secondary data. It costs a certain amount of money to put that new deck, kitchen, bath, flooring, etc, into a house. That has a relative value in comparison to the whole. Usually a half to one fifth of actual cost brings about a good sensible adjustment. The proportional scaling away from true cost, of course related to how similar over all the available comparable selections were. The closer as a whole they were in terms of overall quality, despite different features, the smaller a proportion you need for the individuals. It’s always easier to adjust for something brand new. Then it’s easy to tie it up with a ppsf adjust and if that streamlines your adjusted sales values, you’re on the money. Thanks George, like these articles. Thank you also for the ce flyer. Could not attend, too slow right now. Offer that online and I’d pick it up.
The underlying premise is that “ARE” is to be the definitive source of appraisal information. What used to be the case, is not necessarily so any longer. Too many very recent revisions for convenience and AI objectives rather than well-defined principles and practices of the broader profession.
Everything George cites is reasonable…to other appraisers. That doesn’t mean state regulators agree or even have to agree. THEY are not taught that by TAF Investigator Courses or their agencies that USPAP is a requirement for them.
That means one state may require ‘proof’ for an adjustment while another better-informed state may only ask that adjustments be supported or supportable. I’ve seen very recent cases where an appraiser use qualitative analysis rather than quantitative because he had no proof or credible support for a specific quantitative adjustment and the state cited him for violating USPAP! Even though his explanation was thorough and credible and appropriately handled within the report.
George pointed out a wide variety of techniques beyond data analytics, for which I am appreciative. The sad truth is that regardless of the method used, the relatively new(er) prosecutorial approach to ‘enforcing USPAP’ by many state regulators, instead of the approach dictated by USPAP itself is rendering all techniques risky.
Not at all surprising, read today that Texas will change their school curriculum to show that the civil war was primarily based on slavery and not the two other idiotic reasons they’ve been telling their children for the last 100 years.
See Confederate Arizona
Before that war states were admitted as either Slave or non slave states. As today, politics are complex, no one issue dictates
The Sons of Liberty Appraisal Group…
Has a nice ring.
Things end where they begin. The choice is yours.
George cites nearly a dozen ways ! are they all hybrids? Chris doesn’t like statistics! Mark Twain said they came from Damned liars, the worst kind.
When appraisers started, R.E. Economic were in a disaster the worst kind the depression brought DEFLATION. They worked with any thing that would bring about a creditable solution. The methods that won out were based on substitution. Those were creditable, however banks and lenders continued to close, 3 years into the deprecation the economy started to level out, and then the government changed policy.
War brought us out the world depression, in better condition than the other nations.
The theory of Substitution measures the past. Bad things in the past! Statistics gives us a creditable view of the future. Sometimes good, sometimes bad.
Mandatory residential MLS allows a basis for creditable statistics, and licencee’s can use them. Some use Statistics accurately using the principles of Descart and others, or use substitutions and complain.
Mark Twain was a large publisher, who went bankrupt and lost the large publishing house.
Understand statistics and profit in this modernizing world.
Don, no disrespect intended, but statistics give NO credible future view at all. None. Statistics still rely upon assumptions of past events being indicative of future events. The only problem with that is no one knows how good the data really was, until it becomes ‘the past’ again.
Statistics are a limited benefit tool. Nothing more.
The past happens quickly, but with certainty