Earth

[Elliott]

"The (R-squared) , (also called the coefficient of determination), which is the proportion of variance (%) in the dependent variable that can be explained by the independent variable. Hence, as a rule of thumb for interpreting the strength of a relationship based on its R-squared value (use the absolute value of the R-squared value to make all values positive):

- if R-squared value < 0.3 this value is generally considered a None or Very weak effect size,
- if R-squared value 0.3 < r < 0.5 this value is generally considered a weak or low effect size,
- if R-squared value 0.5 < r < 0.7 this value is generally considered a Moderate effect size,
- if R-squared value r > 0.7 this value is generally considered strong effect size,

Ref: Source: Moore, D. S., Notz, W. I, & Flinger, M. A. (2013). The basic practice of statistics (6th ed.). New York, NY: W. H. Freeman and Company. Page (138)."

Since there are so many variables in the buying and selling of residential real estate, I've always thought it was speculative to rely on statistical analysis for adjustments. I only have one very homogenous neighborhood in my market, when I run a correlation on living area differences, I get a R2 of 0.77 and consider it significant, and then I round it up and adjust close to where I think the market is actually seeing it with very simple analysis.

 

[TerryRohrer]

"The (R-squared) , (also called the coefficient of determination), which is the proportion of variance (%) in the dependent variable that can be explained by the independent variable. Hence, as a rule of thumb for interpreting the strength of a relationship based on its R-squared value (use the absolute value of the R-squared value to make all values positive):

- if R-squared value < 0.3 this value is generally considered a None or Very weak effect size,
- if R-squared value 0.3 < r < 0.5 this value is generally considered a weak or low effect size,
- if R-squared value 0.5 < r < 0.7 this value is generally considered a Moderate effect size,
- if R-squared value r > 0.7 this value is generally considered strong effect size,

Ref: Source: Moore, D. S., Notz, W. I, & Flinger, M. A. (2013). The basic practice of statistics (6th ed.). New York, NY: W. H. Freeman and Company. Page (138)."

Since there are so many variables in the buying and selling of residential real estate, I've always thought it was speculative to rely on statistical analysis for adjustments. I only have one very homogenous neighborhood in my market, when I run a correlation on living area differences, I get a R2 of 0.77 and consider it significant, and then I round it up and adjust close to where I think the market is actually seeing it with very simple analysis.

I know nothing of your source, but I know a few folks who do very little but rely on statistical analysis (not in real estate) and have no issues concluding that models with an R² in the .30s range are significant. R² is not a measure of the strength or weakness of the model, it is a measure of how well the variables included in the model explain the variation in the dependent variable. There are other measures intended to gauge the significance of a given variable. I guess it might be a case of those who can't write texts books while those who can, do.

As to statistical analysis being speculative? How so? What methods do you rely on that aren't?

 

[J Grant]

A point value, whether from an appraisal, an AVM , or other method can never be 100% accurate ( whatever that means ), because value is a concept, a way to measure prices - and prices are not consistent in RE even for same or similar properties. Statistics and regression can show trends and or averages, and patterns. But their results can suffer from rote input and the quantity of data used, the more chances the properties of the data is less similar to the subject /smaller group of comps a buyer would consider as alternatives.

I believe it is allowed now but seldom used ) -if the agencies wanted to make it more attractive option for lenders to choose to loan an LTV % up or down $ within a 3 or 5 percent of the point value , such as point value 195,000, lender can choose to lend within 3 % higher or lower, based on a formula/ combination of buyer credit and type of property/market cycle interest rate

Applied adjustments as others noted are there to model after the way buyers " adjust" with their wallets by paying more for positive features they want and less /discounted for adverse features . An adjustment can never be fool proof accurate no matter how much "support" is shown ( still mystified what support would ever satisfy an impossible standard ). The reason for that is because buyers do not pay or discount in exact same amounts for a same feature in a same property type/price range. In a 300k range house, for example, some buyers might pay only 10k more to get a pool, others 15k more, others 20k more ( assuming same quality pool ). So what amount should appraiser adjust ? Perhaps 15k is a credible adjustment if it narrows the range down reasonably as extracted from paired sales and that makes sense given typical cost of a pool for that price range .

 

[Meandering]

If that happens, you can be sure that adjustments are being made that are not warranted, and/or adjustments that should be made are not being made.

But isn't that the same as the pot calling the kettle black?

You can search for sales by price and find lots of physically dissimilar properties that sold for the same price.



Therefore the error of the magic math lies within your very own posting:

Not sure where you are reading at, but in my view, adjustments are to account for the measureable impact physical differences have on price, as best we can measure. Every day, I see houses that appear to be similar in most respects, but sell for significantly different prices. Some of those differences in price cannot be reliably explained...there are at least four different parties to each pair of sales, each with their own agenda and circumstances and motivations and bank accounts and available credit and a host of other personal perspectives. None of those differences are contemplated in our definition of market value,

Rights
FINANCING
CONDITIONS OF SALE
MARKET
Location

long before you get to the contribution or not, of an extra half bath.

Well, consider the "adjustments" appraisers are supposed to take in sequence, prior to deciding if that extra half bath, pushed the GLA above the median and the "value" is then distorted by the math.

Property rights conveyed. Nope not listed as being consider. Why bother anyway? All property rights are the same, people don't pay more or less for a property based on differences in those rights, so long as they can live in the house, that's all that really matters. Right, got it. Wasted money on AI classes.

Financing;

So,
with historically low interest rates, and a URAR mandate:

DEFINITION OF MARKET VALUE3) a reasonable time is allowed for exposure in the open market; (4) payment is made in terms of cash in U. S. dollars or in terms of financial arrangements comparable thereto; and (5) the price represents the normal consideration for the property sold unaffected by special or creative financing

I guess that favorable financing thing, comparable to cash, just isn't a value consideration, no matter what the GSEs pre-print on their forms. And that, financing just isn't the second adjustment consideration in the sequence of adjustments listed in the AI books.



Conditions of sale;
Ghee, anyone confirm that none of the sellers of those database properties were in a hurry to sell, beyond what is "typical"? Any of those sellers have problems paying their current mortgages and want to leave quick, before moratoriums end, so they can go live with their parents and repair their credit from late or missed mortgage payments? Naw, nothing atypical about that. Just because there are eviction moratoriums

Market;

Ghee, in a global pandemic, it's still all good, there are sufficient listings and sales all the time to always support "typical" Not like a lack of listings would impact the sale prices, and conversely, not like anyone is running up bids to live in the inner city neighborhoods where covid is more deeply impacting the local competition. Naw, it's all just "typical".



But you guys might be on to something.

The value really turns on amount of finished square footage, above or below ground (ANSI Standard) isn't really important anymore. That math says, this is it and everything else, just isn't considered to impact value, but was presented to waste your time in appraisal classes you got to pay a premium price for.

Yeah, yeah that's the ticket.

Oh one of the really funny thing about housing and value differences, revolves around expenses, which appraisers consider with energy efficient things like solar or Geo-thermal heat, yet they totally ignore differences in real estate taxes.

Gonna be something racial in that pretty darn soon.


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[Mejappz]

Gonna be something racial in that pretty darn soon.

It’s just a matter of time.

 

[J Grant]

Dragging in the word "racial " into threads which have nothing to do with the topic makes this board cringe worthy and an embarrassment, being that the public can log on and read it.

 

[Elliott]

 

[TerryRohrer]

Not sure why that was necessary. I saw the citation in your first post. I still don't know anything about your source, and still think the verbiage you posted, if verbatim from that source, is irresponsible at best, and plain wrong. There are, at last count, 432 million statistics texts books around (I have too many of those, and have yet to find one that makes the subject crystal clear to me), each by authors claiming to be the only experts really worth reading.

I'm no expert. Google "is r squared a measure of the strength of a model" and start reading. The first result I got was from Minitab, a major statistics software provider:

"While R-squared provides an estimate of the strength of the relationship between your model and the response variable, it does not provide a formal hypothesis test for this relationship. The F-test of overall significance determines whether this relationship is statistically significant."

A blurb from Duke University includes:

"The question is often asked: "what's a good value for R-squared?" or “how big does R-squared need to be for the regression model to be valid?” Sometimes the claim is even made: "a model is not useful unless its R-squared is at least x", where x may be some fraction greater than 50%. The correct response to this question is polite laughter followed by: "That depends!" A former student of mine landed a job at a top consulting firm by being the only candidate who gave that answer during his interview.

R-squared is the “percent of variance explained” by the model. That is, R-squared is the fraction by which the variance of the errors is less than the variance of the dependent variable. (The latter number would be the error variance for a constant-only model, which merely predicts that every observation will equal the sample mean.) It is called R-squared because in a simple regression model it is just the square of the correlation between the dependent and independent variables, which is commonly denoted by “r”. In a multiple regression model R-squared is determined by pairwise correlations among all the variables, including correlations of the independent variables with each other as well as with the dependent variable. In the latter setting, the square root of R-squared is known as “multiple R”, and it is equal to the correlation between the dependent variable and the regression model’s predictions for it. (Note: if the model does not include a constant, which is a so-called “regression through the origin”, then R-squared has a different definition. See this page for more details. You cannot compare R-squared between a model that includes a constant and one that does not.)"

 

[Meandering]

You should get back on your meds, maybe have 'em up the dosage. This kind of incoherent rambling idiocy precludes intelligent discussions. How do you expect anyone else to follow what you mean when you can't do that yourself? What is "the math?" What "distorts the math?" What does "the math" say?

You criticize what "appraisers" do. Are you one, or just here to detract from what hereto for was a rational and reasoned conversation?

Typical.

Can't intelligently respond, so attack the poster.
Come on professional, what's the order of adjustment considerations?
As a CG, you should know that.


The "math" is incomplete, because it does not weight in the factors that impact value - as taught - AND - is part of your certification testing, that appraiser are to consider firstly, as impacting value, before the differences in physical characteristics. Just because the adjustments are made in dollar amounts, does not negate the order of adjustments, oh and hey look, they're almost the same on the pre-printed URAR.

But, couple the happy dog math with the Disparate Impact thread, and this is swinging wide open a bunch of doors for greater scrutiny of the profession and those "professionals".



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[Meandering]

View attachment 51507


View attachment 51508

Search your MLS by sold price.

List all those that sold for the same price,

and list all their physical differences that did not impact that price.