Qualitative Adjustments

[George Hatch]

By the time we're done we invariably quantify our qualitative analyses and we qualify our quantitative analyses.

 

[Terrel L. Shields]

don't adjust for small features like a fireplace

I don't either but they can indicate a quality issue. I did a lot of regression analysis when I first tried it just to see what the drivers of value were, excluding land. Regression fails with items like fireplaces were common presenting either absurd adjustment or low Rsquare values. Eventually I concluded that size, age-condition (effective age), garages, and quality (oft reflected in brick, part brick, or all brick exterior as a proxy) were driving the bulk of general adjustments. The rest of adjustments should come from cost related adjustment or pairing if possible.

 

[George Hatch]

Austin spent a lot of time advocating RA on this forum and he always said (and I agree, in principle) that the data involving typical SFRs usually stops responding significantly once you increase the variables beyond about 4 factors.

 

[Terrel L. Shields]

Austin spent a lot of time advocating RA on this forum and he always said (and I agree, in principle) that the data involving typical SFRs usually stops responding significantly once you increase the variables beyond about 4 factors.

I had Realstat and using the example (which was commercial property), it really needed a couple dozen sales or even 40 or so, which is problematic with rural and small towns- impossible with commercial or farm properties basically...and town properties typically are somewhat more predictable than rural. So I went to a cheap add on and whittled it down to 4 or 5 factors. The first thing I did was take the land out of the equation and value based on land prices...which we had far more of those than large fully developed areas would. This allowed me to work with as few as 8 or 9 sales, with 10 or more being desirable. By doing both paired sales and sensitivity along with the RA, it often were very close results which, in my mind, meant the adjustments were credible.

To @ucbruin 's point about the "Book" - really I think in a given area, you could develop such adjustments periodically and apply them favorably within price groups. OTOH, with the spreadsheet sensitivity analysis, it's so quick to simply punch in the comps and see what they say, and an added benefit is if one of your sales is "far out", then perhaps you need a better comp.

 

[ucbruin]

"...if one of your sales is "far out", then perhaps you need a better comp."....

In a really conforming area....
Is a "program" really needed to figure this out???

 

[George Hatch]

I had Realstat and using the example (which was commercial property), it really needed a couple dozen sales or even 40 or so, which is problematic with rural and small towns- impossible with commercial or farm properties basically...and town properties typically are somewhat more predictable than rural. So I went to a cheap add on and whittled it down to 4 or 5 factors. The first thing I did was take the land out of the equation and value based on land prices...which we had far more of those than large fully developed areas would. This allowed me to work with as few as 8 or 9 sales, with 10 or more being desirable. By doing both paired sales and sensitivity along with the RA, it often were very close results which, in my mind, meant the adjustments were credible.

To @ucbruin 's point about the "Book" - really I think in a given area, you could develop such adjustments periodically and apply them favorably within price groups. OTOH, with the spreadsheet sensitivity analysis, it's so quick to simply punch in the comps and see what they say, and an added benefit is if one of your sales is "far out", then perhaps you need a better comp.

I like sensitivity analysis and use it all the time because it has the benefit of being internally consistent with the dataset I'm adjusting, it's simple to perform, and its easy to demonstrate and explain.

 

[J Grant]

Attempting to recognize a data set as anything other than imperfect would be in a case of a cookie cutter location with dozens of recent comparable sales, if that. The vast majority of the data sets that appraisers work with are imperfect to the degree that they would be stricken from nearly all scientific studies, yet we attempt to sell findings from these conclusions as concrete. It is one that appreciates or understands how imperfect said data could be and their respective variance to question our "support" for quantitative in many cases.

Even cookie cutter subdivisions have their issues -" Desperate Housewives of Cookie Cutterville" -
If RE markets yielded "perfect data" ... or even logical and consistent data, we would not be needed as appraisers
There instead would be a Kelly Blue Book with different versions for houses, condo units and buildings.

 

[J Grant]

yet we attempt to sell findings from these conclusions as concrete.

I don't' think appraisers actually try to "sell" our findings as concrete. (Look at all the caveats around a market value opinion). We'd rather offer a range of value, but most clients need a specific number , and the fact that we provide it as a MVO does not mean we claim it to be a universal one and only number..
.

 

[J Grant]

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Just got this from my (Trek ) bike dealer - if only, right, for RE? (lol)

 

[Michigan CG]

It's curious to me that so many folks get disjointed about the idea of the Book of Adjustments....
Yet have no issue with the idea that one can apply common sense to a reach a conclusion....

In residential appraising one develops over time their own "lists" and should update those adjustments. The problem with a lot of the "book of adjustment" people is that the "book" they are using was never credible in the first place. I have read a couple reports lately where the appraiser puts in the report his/her list of adjustments...... $2,500 for a bedroom, $500/year, $500 for a deck or patio, $3,000 for a bathroom; $1,500 for a half bath, basements at $10/SF..............

Let us look at the deck. I am appraising a SFR with a sales price of $200,000. The home is 15 years in age and cost new of the property would be about $200,000 with a land value of $50,000. The subject home has depreciated 25% and the comparable properties show similar depreciation.

Cost new for a typical bathroom will be about $8,000 and about $5,000 for a half bath. The $3,000 bathroom adjustment indicates ~40% depreciation and the $1,500 half bath indicates about 70% depreciation. That deck that had a cost new of $5,000 has depreciated 90% and the patio 75%.

The $500/year adjustment would indicate a $7,500 age adjustment vs new while it is really $50,000.

The lists never make sense.