Post #685: Statistical comparison of states re-opening and not.

Posted on May 8, 2020

In brief:  This is a contrast of the states that have and have not chosen to re-open their economies.  On average, the states choosing to re-open now are much more rural, and have about a third as many COVID-19 cases per capita, compared to the states that are still waiting.

The question of the hour is whether or not this early re-opening will increase the spread of COVID-19.

Normally, evaluating the impact of a “natural experiment” like this would be difficult.  That’s because health care decisions normally depend on … well, health.  And that correlation messes up any simple-minded comparison of those who did and did not take some health-related course of action.

But in this case, luckily (?), it looks like the early-versus-late opening decision appears almost purely driven by politics, not public health.  And since this is an equal-opportunity virus, that’s about as close as you can get to random assignment.  It doesn’t care if you are R or D.  It doesn’t care if you’re pro-Trump, anti-Trump, or have no opinion.  The upshot is that trends in the growth of cases — for April, and for the last half of April, and for May so far — are virtually identical in the early-reopening versus later-reopening states. 

And so, I’m putting my marker down for an acid test on this issue.  (I.e, a quick and dirty test that likely reveals the correct result in a short amount of time.)  I’ll revise the above table in a couple of weeks or so.  If the numbers in that right-hand green column diverge, then we’ll know that early reopening cost us something in terms of health.  If they don’t, then not.

This is (was) my line of business — Direct Research

Sometimes the only way to get the analysis done is to do it.  From the raw data to the writeup.  It’s what I used to do, before I retired.*

* So that I can now look in horror at the paper assets that my continued livelihood depends on, pondering which of them will survive this Black Swan event, and which shall go off to Money Heaven, never again to be seen on Earth.  My financial advisor urges caution and stability.  I respond that individuals who bought into stocks in 1929 were made whole again circa 1956.  Despite the fact that I am an economist (Ph.D. — no joke, I actually have one!), I am a lousy investor, so let me just squelch this fear-fest and get back to statistics.)

What you see above is the Johns Hopkins case count data, matched to Census population and land area data, split by the New York Times classification of which states are re-opening their economies now, and which area not.

The use of the NY Times classification was a key simplifying step, because this is complex enough, and nebulous enough, that somebody has to study each state and make some sort of subjective judgment.  I’m more than happy to accept what the Times has done in that regard.

For all you statistics fan(s) out there, I put this together using SAS, so there’s plenty of opportunity for (e.g.) incorporating additional explanatory data.  But, honestly, I’m not quite seeing the need for that, at the moment.

To a health economist — and maybe to an old-school political economist — the results are kind of hilarious.

The states that are choosing to re-open now are far more rural, and have a far lower COVID-19 case load per capita, than those who are not choosing to re-open at this time.  That kind-of makes sense, but I suspect that’s mostly just an artifact of which states have Republican governors, and the spread of COVID-19 having been concentrated in urbanized areas.

But the hilarious and interesting part is the trend data.  As in, no-difference-in-trend.  To a very close approximation, the two sets of states have had the same average COVID-19 growth rate for the month leading up to May 1, for the two weeks leading up to May 1, and for the week following May 1.  So the idea that the early re-opening states have seen falling new case counts, and that makes them different from the other states — that’s just wrong.

But look at the interesting part.  Look at how the growth rates are the same across the two groups, even though the cases/capita (yellow) averages three times higher in the non-reopening states.

Because, to me, that says we’re not all on the same path.  More or less, on average, those early-reopening states look like they are going to avoid the worst of this.  Most US states (with a few exceptions) imposed restrictions around the same time.   And at that point, whatever density of cases you had, that carried forward.  And the upshot is that both groups of states have followed the same growth curve.  It’s just that, in absolute numbers, the rapid-reopening states never got hit as hard (on average), and, assuming they don’t screw it up, never will get hit as hard (on average), as the ones that are currently delaying economic re-opening.

Finally, all other details aside, the almost-complete-equivalence of those trend numbers provides a good quick-and-dirty test for whether or not re-opening costs lives.  We need to come back and revisit that last column of numbers in a few weeks.  If the early re-openers don’t diverge from the later-reopeners, given how well matched these two groups were historically (in terms of trends), I think that will be a fairly strong argument that re-opening early was harmless.