Getting back to the analysis of the subject's prior sale, I'm a big advocate of comparing a prior sale to its respective comps to see how the market previously reacted to those attributes. If we're using sales of SFRs on smaller lots in our current SCA, then how did the subject previously compare to such SFRs on smaller lots that sold in the same time frame?
You may recall I posted some sales involving two datasets - homes with larger lot sizes and homes with smaller lot sizes. The purpose of that (unqualified/un-analyzed) data dump was to see what the effects were, generally, of the additional lot area in that market segment at that time:
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Now you are critical of my use of sales with a narrow size and age range in that market, and maybe you're right. I normally start by looking for "most similar" and stop when I find enough comparables to make my case, the idea being that the fewer variables I have to account for the less room there is to screw the value conclusion up.
The top group is obviously smaller in number and consists of the "A" sales we were discussing earlier. I didn't go into each sale to see if there were multiple parcels involved, so just looking at them will require assuming they're all single lot sales. I don't have access to the local MLS so I have no way of finding any house+extra assemblages selling to the same buyer other than the one I stumbled across on Maple (I only found that one because I was looking at lot sales).
Anyhow, the smaller "A" group above includes homes built in that narrow age and size range on the larger lots. One having a larger lot, one having a somewhat smaller lot and the middle two with 15,000sf lots. I assume that expanding the geographic radius would turn up more of these sales, and same for expanding the size or age ranges. Sales with disparate ages are generally a no-go for me unless I am coming up short WRT "more similar". It's something I do when I'm desperate, not as a default.
The larger and more proximate group in the 2nd dataset involves similar size/age homes as the subject but on smaller lots (relative to the subject's 15,000sf 2-parcel assemblage). We can call them the "C" group because they're neither an assemblage nor do they have the comparable lot sizes. The other wrinkly with the C group is that homes built on the smaller lots will often be of inferior design/quality so that's a variable we'd have to suss out when using them in an appraisal.
These are small datasets, so when it comes to comparing them that's a problem. Needs more cowbells
But the two things that jump out in looking at both these datasets is that the median price for the smaller group of "A" homes above is actually smaller than the median for the similar sized homes on smaller lots. Probably because the one $235k sale screws up the range. Tossing that 1 outlier sale and just using the remaining 3 cuts down on the pricing spread.
Median for A (@3sales) = $325,000
Average for A (@ 3 sales) = $323,333
Median for C = $326,000
Average for C = $322,863
The A group is tough to take seriously because the dataset is too small. Regardless, a comparo of these two datasets - which differ primarily in lot size - doesn't support ANY adjustment for lot area. I wouldn't have expected to find that, but my expectation didn't stop that from happening.
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The other thing that's interesting from looking at both datasets is that all of these sales were 2016 sales, and not one of them - even among the A group - comes close to supporting the subject's 2016 transaction price. OTOH both the medians and averages of both groups DO line up pretty closely with the list price for the SFR itself on its 7500sf lot - which we can plainly see it ended up selling for - when it was listed in 2016.
These are the kinds of things I look for when I analyze a prior sale for the market's reaction to a variable.