Question: do these lists use ALL principal cities of a metro area (e.g. Austin, Round Rock, San Marcos, etc.) or only the primary principal city (e.g. Austin)? If the former, that would tend to have the effect of raising the detached single family home percents for both lists 2 and 3.
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Mathematical Proof:
A priori: this is because “secondary” principal cities, S, tend to have more detached single family homes than “primary” principal cities, P, but less than the balance, B, of their metro: B > S > P.
Thus, using weighted averages of B grouped with S and S grouped with P (to account for differences in principal city size):
B > BS > S > SP > P
List 1 is the weighted average of all three, BSP, and non-metropolitan rural counties, R, are excluded altogether.
As it is, there are only two other groups presented here, lists 2 and 3 must be either one of these sets:
B and SP
BS and P
Note that my original point, including S with P rather than B tending to have the effect of increasing both numbers presented vis-a-vis the counterfactual (including S with B), follows from the above: SP > P and B > BS.
Very similar to how when the average person from California moves to Texas, they tend have the effect of making both states more blue.
That begs these questions: does this include Micropolitan Statistical Areas (mSAs) or have you restricted the dataset to only Metropolitan Statistical Areas (MSAs)? If you have restricted the dataset, did you go further and apply a minimum size threshold? If so, what is that threshold? Did you limit your data to only owner-occupied detached single family homes?
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To be honest, I would love to see the data very similar to what you calculated (which I love, by the way, thank you for this) for four data types:
• owner-occupied detached single family homes
• rented detached single family homes
• owner-occupied other residential units
• rented other residential units
For each of these data types, I would break them up thusly:
• Statewide Total
• Rural
• mSAs (collectively)
• MSAs{<1mil}—B (collectively)
• MSAs{<1mil}—S (collectively)
• MSAs{<1mil}—P (collectively)
• MSA-div{MSA>1mil}—B (individually)
• MSA-div{MSA>1mil}—S (individually)
• MSA-div{MSA>1mil}—P (individually)
The comparisons between these numbers would allow us to see which places are successfully providing housing supply to meet their demand AND developers are meeting that supply in a way that allows ALL individuals to build equity, which places are meeting demand but in a way that deprives individuals to accumulate wealth, and which places are not meeting demand at all (or exceeding it, destroying equity built by those previously).
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An interesting derivable nugget that might hint at what we’d see, although the way I interpret these numbers is as principal cities dropping the ball on providing housing the lower the number goes (if that state has a hot housing market).
(List 3 - List 2) the disparity in detached single family home rates between the primary principal city (or the collection of all principal cities?) and the balance of their metropolitan areas (or micropolitan areas?), collectively per state:
- New York — ~56%
- Pennsylvania — ~45%
- Delaware — ~42%
- New Jersey — ~39%
- Maryland — ~33%
- Vermont — ~33%
- Connecticut — ~32%
- Alaska — ~32%
- Massachusetts — ~31%
- North Dakota — ~30%
- Maine — ~29%
- New Hampshire — ~28%
- Hawaii — ~28%
- Utah — ~22%
- Illinois — ~22%
- South Dakota — ~21%
- Wisconsin — ~21%
- Virginia — ~20%
- Tennessee — ~20%
- Georgia — ~20%
- Washington —~20%
- Minnesota — ~20%
- Rhode Island — ~20%
- Missouri — ~19%
- Ohio — ~19%
- California — ~19%
- Texas — ~18%
- Colorado — ~18%
- North Carolina — ~17%
- Idaho — ~16%
- Iowa — ~16%
- Montana — ~16%
- South Carolina — ~16%
- Nebraska — ~15%
- Indiana — ~14%
- Oregon — ~14%
- Kansas — ~13%
- Arkansas — ~13%
- Arizona — ~13%
- Mississippi — ~12%
- Louisiana — ~11%
- Oklahoma — ~10%
- Kentucky — ~10%
- Alabama — ~9%
- Michigan — ~9%
- New Mexico — ~8%
- Florida — ~8%
- West Virginia — ~6%
- Nevada — ~5%
- Wyoming —~1%
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