> But the fact still remains that most Americans are living paycheck to paycheck.
I am willing to believe that a large fraction are, but it is not 70% by any means and given all the bad numbers I have seen floating around I can't even tell what that number is. I would be shocked if it were below 10% and equally shocked if it were over 40%. If you have a good source of data, I would love to see it
> See the graph:
Just to be clear, that chart is the "other ways" chart. And people can select more than one item. The numbers being shown add up to way over 100%, if you look at the chart you linked, even though it excludes some options (options (a) and (c) from the actual question, which correspond to "I just pay it, what's the issue") that between them were selected by some fraction of people between 29.5% and 59%, depending on how many people selected both of those optons. Hard to tell what's really going on given this survey setup.
So as a simple example someone can check both "With the money currently in my checking/savings account or with cash" and "By borrowing from a friend or family member". Would you categorize them as being able to pay the $400 or not?
> only 19% said they could pay for it by "selling something"
Only 19% said they would sell something as an option to pay it.
I don't know about you, but if I had an unexpected cash flow issue I would probably be far more likely to borrow from friends/family as a tide-over than to "sell something". Depends on amounts, obviously....
> IRAs or 401ks are not liquid
I agree. My main point with those was that "savings" can mean many different things, and people are really bad about differentiating what they mean by it.
The only thing we can conclude from the bank survey is that somewhere around 30% of those surveyed _did_ have > $1k in a savings account. Which says nothing about how they'd pay an unexpected $400 expense, by the way...
> So I would say that half of Americans not having the savings to pay a $500 expense is accurate
I don't see how you can conclude that from the presented survey data. It was about a $400 expense (minor nit), and it's very hard to determine what people _can_ do vs what they _will_ do, and the latter is what the survey asked. And, again, allowed selecting all the things they might end up doing.
In the extreme, I know people who _could_ buy a house for cash but what they _do_ is take out a mortgage, for various reasons, including liquidity considerations, opportunity cost, etc.
> For example age 35-44, median net worth is $91,300
True.
> and the bottom quintile is net worth negative
Also true.
> I think it's easy to imagine how someone growing up in such a household would have a different experience than someone in the top quintile
Here we have an implication that may or may not hold. I know a number of people in their mid-to-late 30s and with negative net worth. All of them are doctors. Their kids are not obviously worse off than the kids of software engineers the same age (who generally have quite positive net worth).
That is to say, net worth numbers do not correlate straightforwardly with standards of living. Nor do income numbers necessarily.
There are things that seem like they should, like disposable income, but even there it's hard to tell apart someone who just has less income to work with and someone who prioritizes nicer house vs disposable income differently.
None of which takes away from the large number of people who really _are_ living paycheck to paycheck, or the children whose parents really _do_ struggle to make ends meet. And there really _are_ a lot of people who both have large student loans and have no idea how they will pay them off. And there are people with large incomes who still manage to live paycheck to paycheck, for various reasons, and obviously plenty of people with low incomes who live paycheck to paycheck. But as I keep repeating, all the data I've managed to find on this has been nearly useless because it equates things that are not equivalent (e.g. negative net worth with a low standard of living, or low income in your early 20s while lumping together students and non-students, etc, etc). This allows people to just read their preexisting biases into the data and come to widely divergent conclusions based on the same exact numbers.
Again, I would welcome any pointers to better data here.