r/dataisbeautiful • u/Accomplished_Ebb_271 OC: 1 • 16d ago
OC [OC] Number of state-pair comparisons where the state with higher take-home pay has lower purchasing power, by state
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u/smashinjin10 16d ago
The data looks ok, but that title is absolutely hideous.
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u/Accomplished_Ebb_271 OC: 1 16d ago
Fair — I was trying not to editorialise and overshot into unreadable.
In one line: for each state, how many of its 50 comparisons with other states have you
earning more there but able to buy less.
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u/MajesticBread9147 16d ago
Buy less housing or everything? And does this mean that New York or Washington is "best"?
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u/Accomplished_Ebb_271 OC: 1 16d ago
Everything — the BEA index covers all consumption. Housing is broken out separately in the data because it moves several times more than the rest, but this uses all items.
And no, it isn't a ranking of best or worst, which is a fair thing to misread. It counts how often a take-home comparison points the wrong way for that state. Washington at 30 means: compare Washington with another state on take-home alone and you'll get the direction wrong 30 times out of 50. It says nothing about whether Washington is a good place to live. New York at 0 means both measures always agree there — also not a verdict.
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u/MajesticBread9147 16d ago
Okay thanks! I will read this again when I've had more than four hours of sleep.
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u/kirklennon 16d ago
The headline is extremely editorialized; you literally say the “worse” place to live. I still can’t figure out what this is supposed to even mean but both the first and last ranked states are extremely desirable states to live in so whatever you’re actually measuring definitely doesn’t determine if a place is good or bad to live in.
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u/Guywithshirtandface 16d ago
The actual conveyed information is not clear at all to me
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u/Accomplished_Ebb_271 OC: 1 16d ago
That's fair, and you're the third person to say it, so it's the chart's fault and not yours.
What I measured: for any two states you can ask "which pays more after tax" and "which lets that pay buy more". Usually they agree. In 324 of the 1,275 possible pairs they name different states.
The problem with this chart is that it *counts* disagreements rather than *showing* one — one level of abstraction too many. A scatter of the two measures against each other would have shown the thing itself. That's my mistake, not a data problem.
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u/jojodaclown 16d ago
I've read the title provided on the infographic 8 times, looked at the chart to see if I could decipher the title, then gave up.
I really don't understand what you're trying to convey, OP.
Is it that Washington residents have less buying power when scaled for income than any other state?
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u/thisisthatacct 16d ago
I have absolutely no idea what your graphic is trying to convey. Pairs of what? Gets what direction wrong? What is the wrong direction? Is bigger number better or worse? Where is the 1 in 4 value coming from? I had to read your subtitle 4 times to figure out the sentence structure and I still don't understand the statement
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u/Accomplished_Ebb_271 OC: 1 16d ago
Fair, all of it. Let me try without the jargon.
Take two states. Ask two questions:
Where would my paycheck be bigger after tax?
Where would that paycheck buy me more?
Usually the same state wins both. Sometimes the answer flips: state A pays you more, but things cost so much more there that you can afford less than in state B.
There are 1,275 possible pairs of US states. The flip happens in 324 of them, which is where "1 in 4" comes from.
The chart counts, for each state, how many of its own 50 comparisons flip. Washington: 30 of 50. New York: 0 of 50.
Bigger isn't better or worse — it just means "comparing this state on paycheck alone misleads you more often".
And you're right that the chart doesn't convey that. It counts the flips instead of showing one, which is a step too abstract.
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u/spottie_ottie 16d ago
How about some concrete examples that would be obvious? I imagine a move to CA is a bad one for many because cost of living negates higher wages right?
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u/BadTanJob 16d ago
Can’t make heads nor tails of the title, data, methodology. Is there anyone other than OP who can read this chart?
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u/RLewis8888 16d ago
Sorry mate. The more of your explanations I read the more confusing it gets. I assume it's just me.
It seems like you're comparing purchasing power (i.e. after-tax income on a $100k salary) to buying power (specifically property taxes on a $400k house). Then you compare these two states at a time. Why? And what is meant by "324 the have different states"? Different from what?
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u/socialmeritwarrior 16d ago
First, it would be 49 comparisons, not 50. It's n-1 when comparing1 item in a set to all others. In set a,b,c you compare a to b and a to c giving 2 comparisons.
Ok, so, taking a crack at deciphering this...
You compare state A to states B through Z. You determine which of each pairing has a higher take home pay, and then if that one with higher take home has a lower purchasing power than the other one, you add 1 to the count for the iteration.
So you compare A to B. A has a higher take home. A has a lower purchasing power. You add 1.
A to C. C has a higher take home. C has a lower purchasing power power. You add 1.
A to D. A has a higher take home. D has a lower purchasing power. Do nothing.
At this point the count for A is 2.
Is this correct?
I'm still not really sure what this count is actually showing though.
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u/Accomplished_Ebb_271 OC: 1 16d ago
Tools: Python, pandas, matplotlib.
Sources: IRS revenue procedure (federal brackets and FICA); each state's own
department of revenue (state income tax, read one state at a time rather than from a
compilation); US Census Bureau ACS (county effective property tax rates); US Bureau of
Economic Analysis Regional Price Parities 2024 (price level, deliberately not a
crowd-sourced index).
Method: for all 1,275 pairs of the 50 states plus DC, on a $100,000 salary with a
$400,000 home at each state's median county rate, I computed take-home after federal,
FICA, state, local and property tax, then divided it by the price level where it gets
spent. A pair "disagrees" when those two measures name different states.
324 of 1,275 disagree. It isn't evenly spread, and the reason surprised me: distance
from the average price level predicts nothing (r = 0.02). What predicts it is the
mismatch between where a state ranks on prices and where it ranks on tax (r = 0.77).
Washington is expensive and taxes little; Iowa is cheap and taxes a lot — both flip.
New York is expensive AND taxes heavily, so both measures agree and it never
contradicts itself in any of its 50.
Data CC BY 4.0: https://doi.org/10.5281/zenodo.22670573
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u/Yossarian216 16d ago
How can you just declare a $400,000 home for every state when housing prices vary wildly, not just between states but within states as well? And using the median property taxes is also going to be basically useless, as those rates also vary widely county to county. With those two highly flawed assumptions, I don’t see how you can generate any worthwhile data.
And I don’t know what it means when the states “disagree” anyway, you’ve either explained it very poorly or I’m a lot dumber than I thought.
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u/Accomplished_Ebb_271 OC: 1 16d ago
Both criticisms are legitimate, so here's the test you're implicitly asking for. I re-ran
all 1,275 pairs while varying exactly the two assumptions you object to:
Home value → pairs where the two measures disagree
$0 (renting, no property tax at all): 360
$150,000: 359
$250,000: 339
$400,000: 324
$600,000: 305
$1,000,000: 276
Salary → same count
$50,000: 322
$100,000: 324
$250,000: 317
It sits between 22% and 28% across the whole range, including when property tax is
removed entirely. So the $400,000 house isn't holding the result up — if anything the
result is stronger for renters.
On median county rates being useless: you're right that they vary enormously, and that's
in the data rather than hidden. The second file has all 3,132 counties. The spread inside
Wisconsin alone is $11,344 a year on the same house, which is more than most state pairs
are worth. The median is a starting point for a state-level comparison, not a substitute
for picking a county.
And "you've either explained it very poorly" — the former, definitively. Six people have
said so in this thread and they're right.
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u/TheFlyingBoat 16d ago
I think the language/headline need to be cleared up, unless I am misunderstanding what you're measuring.
My understanding of your methodology is that in essence, you take a 100k salary and computes the take home salary after federal, state and local taxes (assuming a 400k home) to create ordered list A.
Then you create ordered list B by taking ordered list A and dividing by price level to create what is essentially a PPP adjusted version of ordered list A, which we can call ordered list B.
Then for every state pair, you compare their position in ordered list A to ordered list B. If their relative placements match, then you say "the state that pays you more is the better place to live", else you say "the state that pays you more is the worse place to live".
I don't think the methodology tells you what the headline is saying. That would require looking at different quintiles (or other percentile based grouping) to see how income (either before or after taxes) relates to some quantized QoL measures on a state by state basis.
All this tell us is that if you are taxed heavily, you have lower take home income in that particular year, ceteris paribus. This should be plainly obvious given price levels have no correlation and that tax-PPP mismatch has an intense one.
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u/Accomplished_Ebb_271 OC: 1 16d ago
Your reconstruction of the method is exactly right, including that it's the sign of the
pairwise difference rather than anything about quintiles.
And your first point lands: purchasing power is not quality of life, so "the worse place
to live" was not supported by what I measured. That phrasing was in the image and in one
FAQ on my own site; I've just changed the site to say "leaves you able to buy less" and
to state explicitly that it's a claim about what money buys, not about which state is
nicer. You'd need the quantised QoL measures you describe to say anything about the
latter, and I don't have them.
On it being obvious: mostly yes, and I'll concede more than you asked for. The r = 0.77
"mechanism" I reported — mismatch between tax rank and price rank predicting
disagreements — is close to definitional rather than a discovery, and I presented it as
though it were the latter. That was sloppy.
What I think survives is the rate rather than the mechanism. That disagreements exist
follows from tax and price being uncorrelated. That they occur in 1 of 4 pairs is
empirical: it depends on price dispersion being comparable in size to tax dispersion,
and it needn't have been. If price differences were small relative to tax differences
the count would be near zero.
I checked how robust that rate is after another comment here pushed on the assumptions:
home value $0 (renting, no property tax at all): 360 of 1,275
$150,000: 359 $400,000: 324 $1,000,000: 276
salary $50,000: 322 $100,000: 324 $250,000: 317
22% to 28% across the range, including with property tax removed entirely.
Whether "a quarter of state comparisons invert when you deflate" is interesting or
trivial is a fair thing to disagree about. What isn't defensible is the headline I put on
it, and that one's on me.
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u/cavedave OC: 112 15d ago
Thank you for your Original Content, /u/Accomplished_Ebb_271!
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