Very interesting new report about how America's economic geography has changed since the great recession: https://t.co/l3YE4WzgKx

Short version: Places with lots of skilled workers are doing great, other places aren't. But more people are moving to the former, which is good.

And here are cool interactive maps to go along with the report:
https://t.co/vG5pjEa7B9
Report is via @LettieriDC, who is doing great work on struggling places.
A bit of good news: People are moving from economically bad places to economically good places, though probably too slowly.
Rural America continues to languish.
Business is really concentrating in the good areas.
What separates the good places from the bad places?

Educated workers, of course.
Educated workers, educated workers, educated workers...
And, here's the racial breakdown. Nothing too surprising here. Note that the distressed places are pretty racially mixed, while the prosperous places are about 75% white.
And here is the full report: https://t.co/qdRmXPqlmk

(end)

More from Noah Smith

This thread demonstrates that a lot of academic writing that *looks* like utter nonsense is merely scholars dressing up a useful but mundane point with a ton of unnecessary jargon.


My theory is that the jargon creates an artificial barrier to entry. https://t.co/MqLyyppdHl

If one must spend years marinating one's brain in jargon to be perceived as an expert on a topic, it protects the status and earning power of people who study relatively easy topics.

In econ, a similar thing is accomplished by what recent Nobel prize winner Paul Romer calls "mathiness": https://t.co/DBCRRc8Mir

But mathiness and jargon are not quite the same...

Jargon usually doesn't force you to change the substance of your central point.

Mathiness often does. By forcing you to write your model in a way that's mathematically tractable (easy to work with), mathiness often impoverishes your understanding of how the world really works.

has written about this problem:
1/Lots of tech companies and workers are making noises about leaving San Francisco, LA, NYC, and other "superstar" cities.

Some are predicting a shift to remote work and distributed companies.

Let's take a hard look at what that would actually

2/We're all familiar with the trend of tech companies and other knowledge industries (finance, biotech, etc.) piling into a few tech hubs, raising rents and house prices.

Now some think the advent of Zoom, Slack, etc. might reverse this trend.

https://t.co/nQVCJrKvrB


3/But escaping the superstar cities is going to be tough.

The forces keeping tech companies in places like SF are so strong that these regions have essentially become prisons for these companies.


4/In order to escape the prison of the superstar cities, tech companies and other knowledge industries will have to overcome the Four Jailers of Industrial Clustering:

1. In-person office productivity

2. Thick market effects

3. Knowledge spillovers

4. City life amenities

5/I'm actually pretty optimistic that companies can find ways to make remote work productive.

Studies show that working from home *some* of the time actually tends to raise
Today's @bopinion post is about how poor countries started catching up to rich ones.

It looks like decolonization just took a few decades to start

Basic econ theory says poor countries should grow faster than rich ones.

But for much of the Industrial Revolution, the opposite happened.
https://t.co/JjjVtWzz5c

Why? Probably because the first countries to discover industrial technologies used them to conquer the others!

But then colonial empires went away. And yet still, for the next 30 years or so, poor countries fell further behind rich ones.
https://t.co/hilDvv0IQV

Why??

Possible reasons:
1. Bad institutions (dictators, communism, autarkic trade regimes)
2. Civil wars
3. Lack of education

But then, starting in the 80s (for China) and the 90s (for India and Indonesia), some of the biggest poor countries got their acts together and started to catch up!


Global inequality began to fall.

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