Determining a justifiable bath or bedroom adjustment is really tough to pin down, especially when you are dealing with properties in the $500,000+ range. I always use comp sales with the same bedroom/bath counts when possible, but is there a good method for justifying the value of an additional bath or bedroom? Paired sales is the first method I would attempt to try, but it rarely seems to define an appropriate well-defined adjustment (especially if other factors had to be adjusted for first like square footage, quality, garages, etc.). In a recent "adjustments" class I took, the instructor used mass data comparing multiple 3 bedroom homes to 4 bedroom homes. Makes sense, but I wonder what other factors contributed to any value difference found (factors that weren't considered because every sale in the data set was not analyzed individually).
I think there is a belief in our industry by some that analysis necessary to conclude an adjustment amount needs to be conclusive to a relatively precise number. In the adjustment CE class I teach, that is not my opinion and I do my best to dispel that belief.
Many times, it is relatively easy to do an analysis that indicates that there is
additional value for a particular element or amenity. Looking at a large enough data sample, appropriately filtered, can provide that indication. And one can use mathematical techniques to refine that indication to a point if one chooses to do so.
But more often than not, when one does a set of matched pairs to identify the contributory value of an element, one is going to find that the matched pairs return different results. There is going to be a range. I see this all the time with pool amenities.
I can trend the data and demonstrate that, on average, homes with pools sell for more than homes without pools in certain markets. A formula can be extracted from the trends and a mathematical calculation can be constructed that will provide a point-value for that element.
But when I test that using matched pairs, I've yet to see the result equal the mathematical calculation (and, the expectation is that it wouldn't match the calculation unless all data points fell exactly on their respective trend lines and the trends were 100% correlated over time).
I might see a trend analysis support a pool adjustment at $15,000.
I might include a couple of matched pairs, and see that the value difference ranges between $3,000 and $12,000.
What is my conclusion?
I might conclude that a pool in that neighborhood contributes value (the historical trend). I have data that shows in two examples, a pool can be shown to contribute $3k or $12k. The rest is just picking the point. Maybe $5k fits best within the rest of my assignment's analysis. Maybe $10k, maybe $12k, or maybe even $15k. Once I've concluded that an element warrants an adjustment, and once I have data that gives me a range of where that adjustment falls, I've solved that problem. I just need to pick the adjustment amount and move along.
So that is my point in my post: When we are discussing things like bed or bath count differences, the first order of business is to determine if there is evidence on a large scale to indicate that such an element can impact value. The next step is to refine that large-scale analysis to a specific analysis so that it can be evaluated in the context of the larger data:
"Gee, when I look at a lot of data over time, I can see that there is a price difference if I'm comparing 3- to 4-bedroom homes in this size range. Although I'm not accounting for every difference in this larger-scale analysis, it is reasonable to presume that the quantity of data is compensating for much of those individual differences. Based on the big picture, it looks like 4-bedrooms have contributory value."
Next, I look at some specific data from the specific assignment:
"Ok, when I do a couple of matched pairs, I don't get the clear-cut difference that I did in the trend. One shows a $7k difference, another shows a $5k difference, and the third actually comes up with a negative value?"
Finally, I reconcile my findings and come to a conclusion:
I've analyzed the potential contributory value of a 4- vs. a 3-bedroom home from within this competitive market. I first looked at the historical pricing trends and there appears to be a value difference; 4-bedroom homes trend higher than 3-bedroom homes in general and within the same size range.
Next, I analyzed 3 sets of matched pairs. The data indicated that two sets indicated a contributory value of $5k to $7k, but one set showed a negative value.
I considered all the analyses and have concluded that a 4th bedroom in this neighborhood does have contributory value over a 3rd bedroom, all other things being equal.
I've reconciled my adjustment to $5k and have applied that in the grid.
[or]
While the analysis indicates a contributory value for the extra bedroom, that contributory value is less than 1% of the indicated value ranges and not sufficiently significant to make a line-item adjustment.
However, I did consider it in my reconciliation analysis by giving most weight to the 4 bedroom homes; this adequately considers the contributory value that may exist.
[or]
In this price range, that value difference is not significant and not demonstrably conclusive; it is well within normal market imperfections in pricing. Therefore, I've concluded that no adjustments are warranted for this amenity difference.
And, in anticipation of the question, "Do you always do that in your assignments?"
The answer is, "When I think it is necessary, yes."
And, it isn't about the size of the adjustment ($5k) in my example that is important (assume we are talking about a $50k adjustment); it is about the process, about not getting hung up on a too discrete point-adjustment, and about doing the analysis when the appraiser determines it is warranted.
My 2-cents.