An economic weather report: income, migration, and who stays to raise kids.

Note: This is a public method demo with Bruce Boston and Tim Ellis. The shipping product is turbolapper - AFM (Apple Intelligence on-device; data stays on your Mac). See requirements and Technology.

Read the country like weather

High income is not the same thing as a good place to stay. In this session Bruce and Tim treat US public data as an economic weather report: where people earn, where they move, whether they can own a home, and whether they raise children there.

The map is the same public-data corpus as the US markets & segments episode - 193 distinct economic communities, bubbles sized by population, percentiles across the set - now used as an operator dashboard instead of a geography lesson. They built it in turbolapper on a Mac. You can watch them click the cuts live.

Summary

• Data: Public US geography and demographics - 193 economic communities with income, domestic and international migration, home ownership, home values, births, and kids under 18.
• Method: One prepared map, many questions. Color by the metric you care about; hover a market; compare the next cut without leaving the machine.
• Result: San Francisco pays (99th percentile income) and still loses domestic population. Seattle is a high-income market people are not fleeing. Births in SF sit mid-pack; kids under 18 go stark red - families have children there, then leave.
• You get: A way to read where activity is going, not just where salaries are high - on open data you can inspect.
• Next: Watch the session · Join the waitlist

The map they click

The session starts from the lights-at-night view (the original inspiration), then the community bubble map with no state lines. Miami is still obviously Miami. Each bubble carries a percentile against the other 192 communities.

That is the point of prep: one honest geography, then free follow-ups. Per capita income. Then domestic migration. Then home values. Then births. The second question is where the weather report gets useful.

Cut 1 · Per capita income

Color the map by income and the story is the one everyone already knows: large blue bubbles on the coasts and a few inland giants. San Francisco sits at the 99th percentile, New York at the 98th. Seattle, Chicago, Los Angeles show as places you would move if salary were the only dial.

It is a fine starter view. It is a weak final answer for “where are people actually going?”

Cut 2 · Domestic vs international migration

Flip to domestic migration and the high-income giants invert. Americans are moving out of California’s big bubbles, Manhattan, Los Angeles. Seattle is the outlier in the session cut: 87th percentile income, domestic migration near flat (35th) - people are not emptying out the way they are from San Francisco.

Miami is the sharper split:

• Domestic: second-percentile of negative migration - a large exodus of Americans.
• International: 100th percentile inbound - one of the fastest foreign inflows in the set.

Tim’s naive Florida story (“that is where Americans are going”) does not survive the Miami bubble. The session points the domestic flow to the Panhandle, Jacksonville, Orlando, Sarasota, Winter Haven - and solo sunsetters (65+, single, with money) as the Miami exception.

San Francisco, which both hosts have lived in, shows the same two arrows at once: Americans leaving, internationals arriving, still very high per capita income, with first-generation grinders and rent-splitters overindexing.

Cut 3 · Home ownership and home values

Large markets skew low ownership. New York in the session cut is at the 0th percentile - about half rented, half owned. Detroit is the large-market exception: high ownership, economical prices, mixed reasons.

They color high home values as red (unaffordable). The correlation is blunt: where homes are unaffordable, ownership is low. That is a clean mechanical reason high-income San Francisco and New York still lose people who want to buy.

A low-income Texas market in the cut still shows roughly two-in-three homes owned because median value sits around $136k. St. Louis shows up as calm weather: income around the 73rd percentile, home value in the 36th, ownership in the 70th, people not leaving. The session’s operator takeaway: salary-only maps would have sent a young household to the coasts; the stacked cuts would not.

Cut 4 · Births vs kids under 18

Bruce’s line in the room: outside Salt Lake, you can see a baby belt. Births are another “do people feel they can stay?” indicator - with the honest caveat that a senior-heavy market (Florida) will look red without an age-normalized rate.

The finding that earns the write-up:

• San Francisco births: about the 39th percentile - middle of the pack, not the floor.
• Kids under 18: stark red.

People have children there. They do not raise school-age kids there. Manhattan does not even have the births. Miami is weaker on births than SF and still shows the “have a kid, then leave” motion.

California is not one cell. Agricultural interiors (Fresno, Stockton, Bakersfield, the Yuma/El Centro edge) stay blue for families. Anyone who has spent time in the state already knows it behaves like several states; the map just makes the grain visible.

What Local Analytics means here

This is not a warehouse ticket for one migration dashboard. It is stacked questions on a prepared public corpus:

1. Start with a decision - where are households actually going, not just where pay is high.
2. Keep one geography (193 communities) and change the metric until the story holds or breaks.
3. Stay on the Mac - the engine in the session is the turbolapper stack; the shipping product is turbolapper - AFM (Apple Intelligence; data stays on your Mac).
4. Ask the next cut for free on the app side - income without migration is a lie; births without kids-under-18 is another.

The prior episode taught the map grammar (tiles → lights → DMAs → segments). This one uses that grammar as a weather report.

How to run a version of this yourself

1. Start from the US markets views so the geography is honest.
2. Pick 4–6 public metrics that answer “stay vs leave”: income, domestic migration, international migration, ownership, home value, births, kids under 18.
3. Percentile each metric across markets so color is comparable.
4. Hover the famous cities, then hunt the calm ones (the St. Louis-shaped markets).
5. When two metrics disagree (births vs kids under 18), treat that disagreement as the finding.
6. Keep proprietary CRM or payroll joins on-device when you leave open data.

FAQ

What does this demo show?

How Team Data Crunch reads US public data as an economic weather report: 193 communities, then income, migration, housing, and family cuts on a Mac. Watch: YouTube · Community. Map grammar: US markets & segments.

Is the point that everyone should move to Seattle?

No. Seattle is one high-income market that is not emptying in this cut. The method is the proof: stack income with migration, housing, and kids - then decide. St. Louis is in the session as a calm counterexample, not a ranking.

What is an “economic community” here?

A public-data market bubble - population-sized, no state lines, 193 in this cut - so a metric can be percentiled against the rest of the country. It is DIY geography for exploration, not a licensed Nielsen or Claritas product. See US markets for DMA and segment context.

Can I do this in turbolapper - AFM?

Yes - that is the product direction. Confirm macOS 26 + Apple Intelligence requirements, then join the waitlist. Related method demos: US markets · federal data · retail prep · NYC taxi.

Watch and go further

• Watch: US economic weather session
• Related: US markets & segments · Federal data · Community
• Product: Waitlist · Technology · Pricing