Comment by rory | Hacker News Reader

Comment by rory | Hacker News Reader

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Is there any actual evidence that what you're saying is the reason for the difference though? It's incorrect that credit scores are highly correlated with income [0].

Most accidents are caused by things that are pretty ordinary forms of irresponsibility [1]. A credit score is a (flawed) measure of financial responsibility. That seems like a much more reasonable, although less narratively satisfying, connection.

[0] https://www.federalreserve.gov/econres/notes/feds-notes/are-...

  We find a low correlation between credit score levels and income, with the correlation coefficient around 0.27 for income levels and 0.29 for log income.

[1] https://www.iii.org/table-archive/21313

  Driving too fast for conditions or in excess of posted limit or racing  8,746  17.2%

  Under the influence of alcohol, drugs, or medication  5,164  10.1

  Failure to yield right of way  3,728  7.3

  Failure to keep in proper lane  3,381  6.6

  Operating vehicle in a careless manner  3,302  6.5

  Distracted (phone, talking, eating, object, etc.)  3,008  5.9

> Most accidents are caused by things that are pretty ordinary forms of irresponsibility

This is a big diversion form the actual point, but it's important. The vast majority of these crashes (the word "accident" is rarely used by news/DOTs/etc anymore) could be prevented by designing streets to control speed and improve visibility. So I'd argue that they're caused by poor design which comes as a result of misplaced societal values.

Re the second item in that list of causes, an interesting article came out a couple days ago: https://www.bloomberg.com/news/articles/2022-03-21/make-the-...

> could be prevented by designing streets to control speed and improve visibility

And if you make school tests easier, everyone will get a passing a grade, but that’s not the point.

The point here is that responsibility is not an area specific skill, people who are financially responsible, tend to drive responsibly, people who are reckless drivers, tend to be reckless spenders too.

> but that’s not the point.

Yes I literally started my comment by explaining that I was ignoring the point to make a different one.

It's funny how people read what they want to read.

There are road designs that prevent driving while drunk or texting?

Maybe not drunk driving, but road design can reduce distracted driving crashes:

https://news.cision.com/property-casualty-insurers-associati...

There are road designs that significantly reduce the consequences of those actions. Narrow lanes with chicanes prevent driving at high speeds. Concrete barriers prevent cars from swerving into cyclists and pedestrians. Roundabouts eliminate left turn conflicts.

Yes, society can and should do more to encourage people to drive safely, but that doesn't mean it's impossible to do so.

The same logic applies to all sorts of things like obesity, smoking, etc.. These things obviously have multiple causes-- some societal, some individual. It's not a binary.

We find a low correlation between credit score levels and income,

Interestingly, these two articles claim a correlation:

https://bluewatercredit.com/is-there-a-link-between-your-inc...

  Low income (50% or less of MFI) = 664 median credit score
  Moderate Income (50% to 79% of MFI) = 716 median credit score
  Middle Income (80% to 119% of MFI) = 753 median credit score
  Upper Income (120% of MFI or more) = 775 median credit score

This one shows similar numbers: https://www.valuepenguin.com/average-credit-score#income

Neither of your links contain an actual correlation measure, or links to actual source data. To even call them "articles" is a stretch, they appear to essentially be ads / link magnets (which as a category have an obvious bias).

You have to like, control for things and stuff..

I'm not familar with Fed notes, is there an actual published study behind that Fed note?

The amount of data and studies out there to correlate income level and credit rating is surprisingly low. The data set used by the Fed seems surprisingly weak, a self-reported survey sent out with credit card offers:

We use the Mintel/Comperemedia data (the Mintel data henceforth) that provide a unique combination of credit scores and survey-based income data for the same consumers. The Mintel data set is a monthly proprietary survey of credit card offers, with about 2,500 consumers selected to participate in the survey each month. Participants of the Mintel survey have very similar educational attainments and income to other nationwide representative household surveys, such as the Survey of Consumer Finances. The Mintel sample, however, has a somewhat higher average age and greater share of white consumers.

The link literally is a published study. Not sure if that's supposed to be some kind of gotcha. Fed research generally isn't published in third party journals.

And the method you describe isn't weak at all, compared to social sciences research in general. If anything, it's stronger than most could possibly be, since lying on the survey is a crime in this case.

I just expected a little more information around their data source other than "It's hard to find good data, this proprietary source (so you can't look at it) is the best we could find, it has some known biases, but we eyeballed it and it looks good enough". In particular I was looking for a full study that explained what "very similar" meant since the fairness of that input data seems it's key to their results.

if true, that doesn't look like a very strong correlation to me, at least at first blush. the difference between high and low income is 111 points on a scale that goes from 300 to 850?

In terms of getting a loan, anything below 580 is considered "very poor" (though I don't now how FICO relates to car insurance pricing). So the usable range if you're looking for good rates is more like 580-850, or 270 points.

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