I agree with you that measuring the shares of out-of-county commuters is not a very good way to do things (with the Triangle being one of the most egregious examples) -and like you said, the political and back-of-the-napkin math implications are obvious if you know where to look.
But I guess I didn’t consider, until now, that you were implying that that problem that ran far deeper: that the entire idea of looking at commuting metrics at all is fundamentally not useful. That seems like a more radical (but also interesting!) critique than to just call for definition changes, but I’m not sure what a better alternative would be…??
Because of the threshold to become an MSA may be too low, and Rocky Mount qualifies to have its own MSA. This is because they house enough residents (146k, versus a 50k minimum), and more people who live in places like Wilson Co. commute there than into the Raleigh-Cary MSA. CSAs form when there a MSA exists to be at its core, and Rocky Mount just so happens to do that.
I think that’s true for two groups of people: casual observers who just like to see the Triangle’s popularity as if it’s economic ESPN, and developers who run more detailed market analyses and do their own due diligence with precision as a non-negotiable.
But there are other people who can also benefit from demographics analyses by geography, but I'm struggling to believe they're as invested in doing things "right" as developers. (click to see who!)
-
politicians who have other competing interests, and want simple evidence that can help them craft stories and support agendas
-
companies that run thought experiments on big relocations, and want simple fiduciary values to help them identify specific vibes to quickly reach conclusions with minimum due diligence
-
journalists and other internet entities who want to quickly jump to conclusions about our local economies, and want a few, simple numbers to help build that message with minimum nuance
I think that’s what John is saying: people tend to lump Raleigh and Durham together, anyways, but the current ways we collect and report data as a nation forces people to make unintuitive distinctions. The process that exists now is based on a poor method with unintended consequences, and it seems like the increased investment in our region is worth the red tape headaches needed to make that happen.
Also, I dove into the three comments about the Triangle’s CSA, and I felt like it made sense why the OMB didn’t find them compelling.
And... I'll be honest... I wouldn't have seriously paid attention to us, either, if I was them. (click to see why!)
-
@Yimbyforlife’s comment. Not much else to say here; congrats on becoming a part of the permanent record of the National Archives, I guess?
-
A geographer and blogger called out the OMB’s methods, but it was more of a philosophical criticism against implicit urban bias. His comment included attachments that presented Virginia’s planning districts system as a starting point. Unfortunately, it only mentioned Raleigh in passing, the comment started off sounding standoffish and accusatory, and the attached presentation also looked like it came from the 1990s and still would’ve made people want to claw their eyes out.
-
The Research Triangle Regional Partnership’s Executive Director made solid points in favor of using alternative metrics to commuting patterns for measuring regional growth. However, that point was hidden in a letter that could just be summarized as “please make an exception just for the Triangle
”. He also didn’t really address any of the actual questions the OMB wanted comments on, nor did he otherwise hit them where it hurts, in my view.
In comparison, changes for a different rule were put on hold because of a much more successful torrent of comments. The OMB wanted to raise the minimum population size of a “metropolitan area” from 50k residents to 100k, but they received 712 comments from across the country in opposition to that out of a total of 734. If we want to make actually have a shot at making a difference, I think we need to learn from how they made statistical and sociological arguments, plus how they got so many people together to write comments.