Clearly touched a nerve with some, only one thing I’ll comment to that: the point of the article is narrow: Under what circumstances can we trust regression? This is a math question, not an opinion-based discussion – we can trust regression IF it passes the 4 tests above. IF your data set is not tampered with and fulfills the four tests above, then, Yes you can trust the output.

However, IF 1) the data doesn’t pass those four tests, 2) the results fail basic mathematical rigor, then the answer is No. If you chose to use data/results that are not mathematically supported, and claim that you’ve done due diligence, you’ve actually been negligent in your duties. Given that statistical analysis is not a required course for appraisers, and that many new companies are putting out “products” that offer to do the math for you, its important that we educate ourselves on the way these tools work and how/when to use them and when to set them aside.

The question is vital to appraisers: Can/Is regression producing CREDIBLE results. Perhaps in a future series of blogs, we can cover the various tools that our friend the PhD recommended given that the most normalized of data sets in our region could not be used to produce credible regression analysis.

Do not confuse statistical regression on a large disparate data set (what the article essentially addresses) with regression on appraiser “curated” data sets. Conventional statistical reliability metrics rarely work even if we ignore the argument that the data IS the population and is not a sample set of the population.

The R value on the two paired sales is 100%. The R value of three, four or five matched pairs may also be high, but those three, four or five matched pairs may not be statistically reliable even though matched pairing is the “gold standard” in deriving adjustments.

So yes, some of the parametric statistical software packages are likely resulting in misleading conclusions even with high Rs and low Ps. However, using regression software for appraiser curated data is as reliable as the conventional methods discussed above. We are instead relying on non-parametric statistics, and of course judgement.

I might also add that regular regression analysis is not what FNMA is doing. They are taking our XML data and “chaining” appraisals together. Essentially the subject of one appraisal is the comp in another appraisal and so on up and down the line. By analyzing this chain they are deriving ranges of adjustments. It is the ultimate in appraiser curated data.

In every market there may be winners and there may be losers. Credibility of agency has no limits in this regard, being the likely root cause of some data discrepancy. The sold examples may present as illogically varied valuation indicators within data sets. They do not necessarily imply the need for alteration of reasonable market derived estimates of worth, simply because the data is not matching up. They skew data for other examples.

Credible market value appraisal for an individual unit requires individual unit comparisons, and a human to make quality judgments about the material worth condition and volume. Credible estimates of worth differences expressed in the form of an applied grid adjustment number usually tie an analysis up nicely. Such analysis approaches do not require subscriptions to anything other than MLS data. Appraisers paying for typing services or whipping out boilerplate language are likely missing the mark for logical individual analysis and competent unique language expression describing why. If appraisers are actually interpreting data it should be just another single step on the field to then type that unique interpretation effort into the report.

The tech industry has developed pretty interesting price analysis programs lately. We’re still waiting for something which accurately expresses value.

I’m looking at somewhat subjective prices of best matched individual sold comparables, then extracting value from that through a myriad of logical line item adjustments on the fly. Using these advanced softwares seems like more trouble than they’re worth. Sounds like I’d be applying routine data clean up methods to an entire data set rather than just an individual spread of comps. The act of selecting good matching comps is how appraisers can bypass a constant need for market derived adjustments in many scenarios. If they’re reasonably aligned, all it takes to adjust pricing to a streamlined value indicator is simple logic through individual line item comparisons, and not all that much extra effort.

It’s important to define the need. Regression may be better for those dealing in mass data, but may not be best for individual comparisons. Manually orientated appraisal development is highly defensible, relatively simple and routine once an appraiser can make short work of data cleanup.

Logical adjustment is easy if you understand the product being appraised for value. A home. A collection of physical components of various price, quality, and volume. Components with real world price tags. Mass data may miss the mark because it can not sort individual details quite like a human can. Then apply logical thoughtful individual adjustments, or not apply them, whatever may lead to credible assignment results.

When a shopper sees a ruined deck, the first question they ask is not what’s the impact of market value of this item. The question they ask is how much is that going to cost me to correct? Smart home shoppers keep a mental checklist of expected costs, then they’re on to the next showing to do that all over again. Some are in it for speculation, others want them turn key. Regression allows too much room for quality of condition error and instead must rely on price indicators for just about everything. These price analysis programs are branded as value results, so just run with that I suppose.

Interesting. Have you seen this advertised in standard company materials yet?

https://www.fanniemae.com/content/fact_sheet/property-inspection-waiver-fact-sheet.pdf

With the appraisal waiver program, appraisers will only get difficult and higher risk assignments. So the new deal is nothing under 400k for well qualified borrowers, no more everyday condos, no more full service refinance requests for the better half of well qualified borrowers with decent ltv’s.

https://www.fanniemae.com/singlefamily/property-inspection-waiver

Generally speaking, most appraisers will no longer be asked to provide regular appraisal services in neighborhoods we could actually afford to live in.

Its a CLOWN SHOW.

It is not magic; it is hard work using the tools of our trade, understood and practiced with objectivity and attention to the behavior of the market participants. This can’t be understood without inspecting the property as in the latest iteration of a valuation, or an algorithm written by a nerdy guy with a new gadget. Get real people, stop buying the crap people are selling appraisers while selling us out to the lowest bidding AMC who is basically a corrupt middleman.

My point is, homeowners often don’t know what they own, agents often don’t know what they are selling, lenders often don’t know what their lending on, public officials often don’t know how to correctly categorize a property, and software engineers often don’t know how to engineer.

Seek the truth.

So true, I guess that is why we say that “appraising is both an art and a science”.