When we set out to establish price recommendation for one of our listings, we look at a wide variety of data and metrics which we then synthesize into a specific recommendation. For example, we’ll typically consider:
- Similar homes that sold recently
- Current market dynamics of supply and demand
- Active listings that potential buyers will be comparing us to
- The typical neighborhood price range, comparison to new homes (if builders are still in the neighborhood)
- Among many other factors
However, one metric that is conspicuously absent from our analysis is price per square foot. Many of our clients ask us about this, so I thought I’d offer a full rational for why we don’t typically use price per square foot ($/SF).
Why we don’t typically use price per square foot
First, why would someone choose to use $/SF in the first place? There are two reasons that this metric gets frequent discussion.
First, it’s super simple to compute and it provides an appearance of statistical rigor. We all like to feel our conclusions are based in fact, so there is a natural tendency to gravitate towards a metric that’s easily applied to any home.
However, if we dig a little deeper, the real purpose of $/SF is to compare disparate homes. After all, if the homes were already of similar size, we would just compare their absolute price rather than resorting to an alternate calculation.
This is a problem because the best way to evaluate the potential sale price of a home is to compare it with similar homes – not disparate homes. In other words, the whole premise of $/SF is that it allows for comparison between apples and oranges, when we’d rather compare apples to apples.
Specifically, the follow problems tend to arise when using $/SF:
$/SF is inversely correlated to the size of the home.
In other words, the bigger the home gets, the lower the $/SF tends to be. Of course, there are luxury homes which still demand a very healthy $/SF, but even among that subset, the $/SF goes down as the house gets bigger.
This is a problem because it means $/SF isn’t a good way to compare homes of differing sizes… but the whole point of $/SF is to compare homes of differing sizes. In theory, $/SF would be fairly reliable when comparing homes of very similar size. Of course, at that point, you might as well just compare the absolute price of the home instead.
$/SF can’t be used to compare different home styles (rancher, 2-story, tri-level, etc.)
This is because it is almost always cheaper to build up than out. So a 2,400 SF rancher with no basement will cost WAY more than a 2,400 SF 2-story home with a basement (800SF/level).
If averaging $/SF (which is what most people will do), the source data tends to be widely varied. The problem arises if we try to apply an average to a specific home because there really is no “average” home – there are just homes above average and homes below average.
To illustrate, we might have 5 homes with average $/SF of $95, $112, $143, $157, and $158. Those homes average to $133/SF, but there probably isn’t a $133/SF home in the neighborhood. More likely, the home in question is ~$150/SF or it’s ~$110/SF. This applies to other metrics too. While averages can be helpful in looking at trends, they aren’t particularly helpful in pricing a specific home.
$/SF comparison will almost always be more favorable towards an architecturally simple home, whereas a buyer may look more favorably on a home with more “wow factor”.
Perhaps the most common example for our purposes is a house that could be built with either A) A 2-story ceiling in the living room, or B) An extra bedroom upstairs resulting in a 1-story living room ceiling.
The shell of the house is the same for either option, but the extra bedroom adds square feet. However, the home with the 2-story ceiling has more “wow” when you walk in, and it will likely sell for about the same price as the other option – that means a higher $/SF. This is an important point because it applies to homes that appears to have the similar upgrades and finish quality. If you compare them based on an MLS listing or a spec sheet, the house with the extra bedroom wins every time, but that likely won’t be the case in real life when people walk through the homes.
It’s instructive that even appraisers don’t typically use $/SF when appraising homes – at least not in the sense in which we’re discussing it.
Instead, appraisers find homes that are relatively close in size to begin with, then make a small $/SF adjustment for the difference in size only.
To illustrate, when doing an appraisal of a 4,000 SF home listed for $600,000 ($150/SF), an appraiser might find a “comp” of a nearby 3,500 SF home which sold for $550,000 ($157/SF). Using only $/SF, the larger home would be $628,000 at $157/SF. However, the appraiser won’t adjust using $157/SF or even $150/SF. He will make an adjustment using something around $50/SF. So the adjusted value of the smaller homes goes up by only $25,000 to $575,000 for purposes of valuing the larger home.
Is price per square foot ever useful?
So is $/SF ever useful? Perhaps, but I think those cases are quite rare. Typically, by the time you adjust for all the factors, you’d be better off just using a different framework to begin with.
I can only think of two situations where we tend to use $/SF. First, it’s often used when talking to custom builders in order to provide some sort of price before a home is designed. This is less than ideal too, but sometimes it’s the only option if you want to have a conversation. Second, we will sometimes use it to describe a relative difference, such as saying, “The per SF value of a rancher will tend to be higher than a 2-story.”
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