Land Use Regulations and Homelessness
Credit to Gary Winslett for noticing this pattern:
I saw this tweet from him earlier today, and decided to do a quick analysis to put some numbers on this observation and visualize the relationship. If you want to read more, here’s a longer article from Gary related to this topic.
The Land Use Freedom rank here comes from the Cato Institute, and is based on scores across several categories including local rent control laws (which count negatively), Wharton Residential Land Use Regulatory Index (a measure of housing market regulation), and more. Details here.
Below is a plot of state homelessness rate per 10,000 people (data here) against land use freedom score (from this Cato Institute report, data available here, calculated with relative weights listed here). This is using only the 2019 data from the Cato report.
And yes I watermarked this plot in case anyone tries to use it as definitive evidence for causation lol. But the correlation is pretty interesting. R-squared of 0.3822 means that 38.22% of the variance in the homeless rate can be explained by the land use freedom score.
I also colored the dots red and blue based on whether they voted Republican or Democrat in the 2020 presidential election. It looks like the blue states tend to have more homelessness than the red states, so this is potentially a confounding variable — I probably could have plotted the homelessness rate against a lot of other variables that differ between red and blue states (gun ownership, church attendance, BBQ restaurant quality, etc), and shown a non-causal correlation between them.
Edit 2-7-23: When I first wrote this, I mentioned that the difference between red states and blue states could be a confounding factor, but I didn’t expand on why. u/GymmNTonic on the SSC subreddit listed some specific reasons why blue states might have more homelessness than red states. Here is their comment:
These are big, densely populated cities that are liberal. I’m not saying the author is 100% wrong, there’s obviously regulation issues driving housing inflation that can result in homelessness, but I think bigger factors are that it’s easier to be homeless in big liberal cities that:
a) don’t bus you out to other cities and are generally more tolerant of the population existing
b) where you have more opportunities to panhandle from a very dense population
c) have more social services for the homeless
d) for those who are not mentally ill and have the capacity to work, more job opportunities
e) in many cases, more opportunities for shelter against winter in big city infrastructure, particularly Los Angeles
So, it’s more that it’s much much more difficult to be mentally ill in rural areas with low cost of housing, because to someone in full on psychosis, any housing cost other than a free awning on a doorstep is still too much cost.
Anyway, it could be that blue states tend to have more homelessness and blue states tend to have more restrictive housing markets and expensive housing — but that the market regulations and expensive housing are not causing the homelessness.
Still, the relationship holds even when we analyze the red and blue states separately, although it’s a bit weaker.
Anyway, these simple linear regressions aren’t solid, definitive proof of anything, but I think they’re enough to put a hypothesis on the table for further investigation. Correlation doesn’t always mean causation, but in this case there’s a clear potential mechanism of causation: NIMBY regulations → lower housing supply→ more expensive housing → more homelessness.
Here are plots of the relationship between the land use freedom score and median home value (data here).
Then, lastly, Alyssa Vance showed in her LessWrong post that housing costs are correlated with the homelessness rate (R-squared ≈ 0.69).
Again, none of this is solid proof that overregulation of housing markets is causing homelessness. But I think it’s enough to warrant further investigation of this hypothesis, and maybe look for causation in natural experiments. For example, Oregon recently passed a statewide YIMBY policy to reform some zoning regulations and allow more housing to be built — it will be interesting to see if this is followed by a drop in the homelessness rate in Oregon in the coming years.
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An alternative hypothesis that I think should be explored is that, regardless of whether it's a red state or a blue state, the places with the highest homelessness AND the highest land use restrictions are places that people want to move to, perhaps due to favorable climate and natural beauty: California and Oregon on the blue state side, Montana on the red. The places with low land use regs and low homelessness are places nobody wants to move to if they can help it: Georgia (too hot) and Michigan (too cold) on the blue side, Alabama and Oklahoma on the red side. (That would make New York quite the outlier, though, since I grew up there and I can confirm the weather and scenery are uniformly terrible outside of fall upstate.) Anyway, it would be interesting to see what the graphs would look like if you tried to find correlations between either homelessness or land use freedom scores and net population gain/loss in those states. My general thought is that you can only get away with restrictive land use regs when lots of people want to move there.