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Posts tagged with: "HHMSDODNS"

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Household debt meets corporate debt

Households take on debt for a variety of reasons, such as financing education and purchasing a house. Household debt in the U.S. increased from 59% of GDP in 1990 to 98% of GDP in 2009, and many economists argue that the Great Recession was “Great” because household leverage was so high at the time. It has since declined steadily. In fact, in 2019, household debt and corporate debt were the closest they have been in nearly 30 years.

The FRED graph above shows both series as a percentage of GDP: household debt and corporate debt. Household debt has exceeded corporate debt since the early 1990s, and this difference was particularly large in the years leading up to the Financial Crisis of 2008. For instance, in the third quarter of 2006, household debt was greater than corporate debt by as much as 31% of GDP. In the years since the Great Recession, however, U.S. household debt has steadily decreased. This decline, accompanied by an increase in corporate debt since 2012, has reduced the gap between household and business debt. In fact, in the last quarter of 2019, household debt and corporate debt were both around 74% of GDP.

What has driven this decrease in household debt? There are many types of household debt: mortgages, student loans, auto loans, credit card loans, etc. The second FRED graph decomposes household debt into some of these categories and shows that the decrease in household debt is driven primarily by the decline in mortgages over the recent decade. Auto loans have remained stable as a percentage of GDP; student debt has increased slightly, but not nearly enough to offset the large decrease in mortgage debt.

How these graphs were created: First graph: Search for and select “Nonfinancial Business; Debt Securities and Loans; Liability; Level.” From the “Edit Graph” menu, add the series “Households and Nonprofit Organizations, Debt Securities; Liability, Level.” For both lines, add the second series “Gross Domestic Product, Billions of Dollars, Seasonally Adjusted Annual Rate.” To rescale the series as a percentage of GDP, change the formula to (a*100/b) in the formula bar. Second graph: Search for and select “Households and Nonprofit Organizations, Debt Securities; Liability, Level.” From the “Edit Graph” tab, search for and add each of the following FRED series IDs: HHMSDODNS, MVLOAS, SLOAS. For each line, also add the series for GDP and then change the formula to (a*100/b).

Suggested by Asha Bharadwaj and Miguel Faria-e-Castro.

View on FRED, series used in this post: CMDEBT, GDP, HHMSDODNS, MVLOAS, SLOAS, TBSDODNS

On household debt

Some people are worried about high levels of U.S. household debt. When looking at aggregate numbers, there are two ways to consider this question. The first is how much it costs to service this debt as a fraction of disposable (after tax) income. This is shown with the blue line. The second is how much debt there is with respect to the same disposable income measure. This is shown with the red line. Whether these numbers are high is difficult to say; household-level data are more appropriate for that question. But in the aggregate, both measures have clearly decreased during the past crisis. Note the scale, though: While service payments decreased by almost one-third, the debt ratio decreased by only one-fifth. And whenever interest rates go back up, service payments will increase.

How this graph was created: Creating the blue line is easy: Search for “household debt” and select the series for debt service as percent of disposable personal income. The red line is more complex because it has to be constructed: We need the two components of household debt (consumer credit and mortgages) as well as nominal disposable income—nominal, not the real or per capita versions, because the debt measures are in nominal terms. So, from within the graph, search for “household consumer debt” and add this series (a) to the graph. We must combine more data here, so add “household mortgage debt” (b) and “disposable income” (c), being sure to select “modify series 2.” Then create your own data transformation by applying the formula (a+b)/c. Finally, switch the y-axis position to the right.

Suggested by Christian Zimmermann

View on FRED, series used in this post: DPI, HCCSDODNS, HHMSDODNS, TDSP

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