# Average American Debt – Debt by Generation, Income, Type, and Aggregates

March 15th, 2021 by
PK

In 2019, the average American household carried $107,596.90 in debt. The median American household had$25,427.95 in debt, and the top 10% of households had $298,884.10 in debt. Not including real estate debt, the average and median American household carried$22,065.03 and \$5,210.70 in debt, respectively.

In this post, I'll break down American household debt averages and other statistics. We'll look at debt by age and generation, as well as categories of debt and more.

Ready to learn about the debt burden of Americans? Let's dive in.

Table of Contents

## Debt Statistics in America

It's hard to find quality debt statistics for the United States.

Luckily for you and me, the Federal Reserve SCF is an extremely high-quality triennial survey providing a view of American assets and liabilities. I use this data for our net worth statistics – and it's also convenient here. However, there are some caveats – more on those in the methodology section.

Following are SCF sourced debt statistics broken down into a variety of categories.

## Debt Statistics by Percentile

First up, we'll look at debt deciles. While the average and median are interesting, looking at debt distribution is a better visualization of America's debt relationship.

Below are debt statistics for all debt, then special categories excluding a primary residence and all real estate debt.

I also ran the math on the percentage of American households who have debt classified into the three groups.

• Have debt including real estate: 76.6%
• Have debt not including loans on primary home: 68.8%
• Have debt not including any real estate loans: 67.6%

## Debt by Type

The SCF has an incredibly detailed look at all types of assets and debts.

This section looks at some of those debt types at the aggregate level – you can find the definitions in the Federal Reserve's flowchart. The final row shows the percentage of American households who hold that type of debt.

I've also done a deeper dive on a few types of debt. Learn more about:

## Debt by Generation

Age – just as it does with income – affects Americans' debt. Here's how debt breaks down when you tally up the average and quartile breakpoints for American households by generation.

In this section, here's how I broke down the generations:

• Millennial (18-37 years old)
• Gen X (38-54)
• Baby Boomer (55-74)
• Silent (75-94)
• Greatest (95+)

Don't get hung up on the ages – I'll do a finer breakdown in a further post.

## Debt by Income Bracket

Debt is also tied to income – because debt can both fuel income... and allow a household to take on more debt.

The Fed broke down the income brackets in this manner, and I'm matching their tradition. This breakdown better groups "lookalike" brackets than something like deciles or quartiles.

Said another way – the 26th and 21st percentile incomes have more in common than the 99th and 94th.

## American Debt Overview Methodology

All the stats in this post come from the Federal Reserve SCF's 2019 survey. I list statistics as 'households', but technically we're looking at PEUs or Primary Economic Units:

"...the PEU consists of an economically dominant single individual or couple (married or living as partners) in a household and all other individuals in the household who are financially interdependent with that individual or couple.

For example, in the case of a household composed of a married couple who own their home, a minor child, a dependent adult child, and a financially independent parent of one of the members of the couple, the PEU would be the couple and the two children."

Federal Reserve SCF Data Codebook, 2019

Survey design (including PEUs) limits what we can find, too, especially for student loan debt – how do you define the PEU of a shared dorm?

Compared to the FRB's student loan data, the SCF might be around half a trillion dollars short or so... at least from what creditors believe they're owed.

Still, the numbers are more-than-directionally accurate; the broader trends and distributions are probably good enough to project to the 'actual' distribution, if not exact numbers.

Just beware; there's nuance to the numbers. Enjoy!

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