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Freddie Mac: Quality & Condition Ratings

Do you include the three modifers in the report, e.g., Q3/Above mid-point?
Since I don't do FNMA, I don't do any of that, but I am simply pointing out that every category is so broad, that you could divide it up when trying to do a comparison. For two decades plus everyone used EFFECTIVE AGE as a condition/age adjustment. It still works. Using a calculated age like the Epley method is best but observed effective age is just as valid as C numbers - which are likewise simply an observation and comparison with other structures. With effective age there are just as many categories as years in the total life. With C and Q ratings there are literally jumps of 15-20%.

But a lot of appraisers seems to have a problem with total life. I think @gregb posted a chart a few years ago showing that with each update, remodel and renovation, the remaining life slides further into the future. Maybe that was a Marshal & Swift chart. Saying something has a total life (remaining life + effective age) of X is not fixed in stone from the first date of construction. So, that 100-year-old house can have a 60-year total life. The concept of remaining life is how long will this structure be functional without major updates? And total life should reflect quality. A 45-50 year life is a lower quality house. A 60 year + life means a quality home.
 
Question: How can they NOT be used as the basis for adjustments if they are the industry standards to define differences, including differences between subject and comps in the SCA?
They are required as data for the GSEs. There are no requirements regarding how appraisers use them or don't. They are not industry standards, they are assignment specific requirements.

I never rely on them for anything. If comps are roughly similar in quality and condition to the subject, I discuss difference and impacts on value in reconciliation. If not, I rate them compared to the subject and run a simple regression comparing that rating to the adjusted sale prices of the comps (adjusted to the subject for all other differences impacting value).

For example, if differences are all over, I might rate comps as better or worse than the subject in increments of .25 each for kitchen, baths, overall interior condition, and overall exterior condition. So, the subject is "0" and the comps can be between -1 and +1. The regression yields a lump sum that then must be weighted by the rating for each sale to develop the adjustment to that sale.
 
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They are required as data for the GSEs. There are no requirements regarding how appraisers use them or don't. They are not industry standards, they are assignment specific requirements.

I never rely on them for anything. If comps are roughly similar in quality and condition to the subject, I discuss difference and impacts on value in reconciliation. If not, I rate them compared to the subject and run a simple regression comparing that rating to the adjusted sale prices of the comps (adjusted to the subject for all other differences impacting value).

For example, if differences are all over, I might rate comps as better or worse than the subject in increments of .25 each for kitchen, baths, overall interior condition, and overall exterior condition. So, the subject is "0" and the comps can be between -1 and +1. The regression yields a lump sum that then must be weighted by the rating for each sale to develop the adjustment to that sale.
Thanks for the comprehensive description of your methodology. Using a 1004, do you subsequently report regression results in the SCA form, or ignore the form by replacing it with results of ur analysis in an addedum (although arent SCA results required to be reported based upon the embedded grid?)
 
Thanks for the comprehensive description of your methodology. Using a 1004, do you subsequently report regression results in the SCA form, or ignore the form by replacing it with results of ur analysis in an addedum (although arent SCA results required to be reported based upon the embedded grid?)
I make the adjustment on the Q or C line and include a paragraph almost identical to that shown above, with the addition of the regression coefficient. All the math is included in a spreadsheet in my work file.
 
I support Spark but don't use Synapse yet--worried that it might provide a result that I'm not looking for! LOL
Question: Do you reference either Spark and/or Synapse in an appraisal report?

It does and will that's where you use your knowledge to adjust and/or delete. A perfect example is pools it wildly overstates those values it's just a tool I don't necessarily use it as gospel. My area is easy so my data going in is tight so the output, which is still a range allows you to fine tune the result. I should make a screen recording going through setting up a report and post it.

I reference Synapse not Spark
 
Pretty sure we aren't supposed to 'come up with' the ratings. The C and Q ratings are defined. Our task is to assign the appropriate ratings to the subject based on those definitions. Since it's still somewhat subjective... and the definitions aren't exhaustive... different appraisers may rate the same dwelling differently.
It is subjective. Agent called subject a fixer. I looked at it and it's average with some cosmetic repairs.
In one data source, it called subject C3 (how long ago was that? 40 years ago).
Appraiser gets final say.... after lender.
 
Question: How can they NOT be used as the basis for adjustments if they are the industry standards to define differences, including differences between subject and comps in the SCA?

How? Well, Market Value by its very nature is relative to the local market. It is based on all kinds of network relations in the local market. A market area may be all C2, all C3 or all C4 - or nearly so. If all the comps are C2, how in the f*** are you going to use that to support adjustments? GSE ratings very far from being sensitive enough to Quality or Condition, to do that.

So, that is why many appraisers consider these ratings simply required fodder for the GSEs. They make their adjustments in other ways.

As a sidenote, I and others criticize the GSE's and many Appraisal Leaders for being stupid. It is genuinely true, although as "The Basic Laws of Human Stupidity" Second Basic Law states:

"Although convinced that fraction σ of human beings are stupid and that they are so because of genetic traits, I am not a reactionary trying to reintroduce surreptitiously class or race discrimination. I firmly believe that stupidity is the indiscriminate privilege of all human groups and is uniformly distributed according to a constant proportion. This fact is scientifically expressed by the Second Basic Law, which states that:

The probability that a certain person be stupid is independent of any other characteristic of that person.

"In this regard, Nature seems indeed to have outdone herself. It is well known that Nature manages genetic traits, I am not a reactionary trying to reintroduce surreptitiously class or race discrimination. I firmly believe that stupidity is an indiscriminate privilege of all human groups and is uniformly distributed according to a constant proportion. This fact is scientifically expressed by the Second Basic Law, which states that The probability that a certain person be stupid is independent of any other characteristic of that person. In this regard, Nature seems indeed to have outdone herself. It is well known that Nature manages, rather mysteriously, to keep constant the relative frequency of certain natural phenomena. For instance, whether men proliferate at the North Pole or at the equator, whether the matching couples are developed or developing, whether they are black or white, the female to male ratio among the newly born is a constant, with a very slight prevalence of males. We do not know how Nature achieves this remarkable result but we know that in order to achieve it Nature must operate with large numbers. The most remarkable fact about the frequency of stupidity is that Nature succeeds in making this frequency equal to the probability σ quite independently from the size of the group. Thus one finds the same percentage of stupid people whether one is considering very large groups or dealing with very small ones. No other set of observable phenomena offers such striking proof of the powers of Nature. The evidence that education has nothing to do with the probability σ was provided by experiments carried out in a large number of universities all over the world. One may distinguish the composite population that constitutes a university in five major groups, namely the blue-collar workers, the white-collar employees, the students, the administrators, and the professors. Whenever I analyzed the blue-collar workers I found that the fraction σ of them were stupid. As σ’s value was higher than I expected (First Law), paying my tribute to fashion I thought at first that segregation, poverty, lack of education were to be blamed. But moving up the social ladder I found that the same ratio was prevalent among the white-collar employees and among the students. More impressive still were the results among the professors. Whether I considered a large university or a small college, a famous institution or an obscure one, I found that the same fraction σ of the professors were stupid. So bewildered was I by the results that I made a special point to extend my research to a specially selected group, to a real elite, the Nobel laureates. The result confirmed Nature’s supreme powers: σ fraction of the Nobel laureates were stupid. This idea was hard to accept and digest, but too many experimental results proved its fundamental veracity. The Second Basic Law is an iron law, and it does not admit exceptions. The Women’s Liberation Movement will support the Second Basic Law; as it shows that stupid individuals are proportionally as numerous among men as among women. The “developing” of the “Third World” will probably take solace in the Second Basic Law as they can find in it the proof that after all the developed are not so developed. Whether the Second Basic Law is liked or not, however, its implications are frightening: the law implies that whether you move in distinguished circles or you take refuge among the headhunters of Polynesia, whether you lock yourself in a monastery or decide to spend the rest of your life in the company of beautiful and lascivious women, you always have to face the same percentage of stupid people—which percentage (in accordance with the First Law) will always surpass your expectations." [Cipolla, Carlo M.. The Basic Laws of Human Stupidity (pp. 16-18). Knopf Doubleday Publishing Group. Kindle Edition. ]

Most large organizations, instill mediocrity and stupidity in their employees and managers. Once employees feel absolutely safe in their jobs, they turn into morons.

Of course the best organizations keep EVERYONE running a race, destroying families in the process, leading to a childless world that dies away. No solution - except that.
 
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Bingo. In the early stages I received a ding when my C rating changed on the same comp I previously used. My ratings fixed that I explain what I do it works for me
Hard to believe but I make mistakes.
When I realized my C rating was incorrect for a comp the first time and for another report if I had to use that comp, I'm "forced" to use same C rating.
Knowing Big Brother is watching me, I didn't want to bring red flag if I changed my rating.
 
Hard to believe but I make mistakes.
When I realized my C rating was incorrect for a comp the first time and for another report if I had to use that comp, I'm "forced" to use same C rating.
Knowing Big Brother is watching me, I didn't want to bring red flag if I changed my rating.
So, when you see you made a mistake you do not correct it? You are supposed to correct that very thing. You are NOT "forced" to use the same rating. You choose or chose if in fact you are not just spewing BS, to do so.

You choose to be GSE form filler or an Appraiser, period.
 
I'm the practical appraiser.
Given the rules, you don't want to bring further issues upon yourself.
 
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