student loans | Search Results

Are household debt and student debt exploding?

On the importance of properly deflating

Posted on May 15, 2017

The graph above shows two series related to household debt that have received a great deal of attention lately: consumer credit (mostly lines of credit and credit cards) and student loans. These series show stark increases especially in recent years. But one has to be careful before jumping to conclusions, as the eye may be deceived here. First, the student loans shown here are only those that come directly from the federal government, and that specific program was introduced in 1994. So part of the increase is simply this program ramping up. But more importantly, one has to consider the important factors for the time period shown here: overall prices increased, population grew, and real incomes increased as well. Thus, it could be that these graphs simply show the increases in these three factors and nothing else.

To make things clearer, we need to divide by a measure that also increases along with these three factors and thus represents the size of the economy over the years. One popular candidate for this is nominal (that is, not real) GDP. It accounts for price, population, and productivity growth. The graph below is the same as the above, except that both series are divided by nominal GDP. The new graph still shows an increase for both series, but it’s not as dramatic. It also has the advantage of providing a frame of reference for the numbers: Total outstanding consumer credit currently amounts to about 20% of national income, and student debt is 6%. Whether this is excessive is open to debate. But one should focus on the data in percentages, not in billions of dollars.

How these graphs were created: Search for “consumer credit” and click on the desired series. Once you have the graph, go to the “Edit Graph” section and open the “Add Line” panel. Search for “student loans” and take the series with a longer time range. Apply formula a/1000 so that the units match. You have now the first graph. For the second, add a series to each line by searching for “GDP” (do not take real GDP) and apply formulas a/b and a/b/1000, respectively.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: FGCCSAQ027S, GDP, HCCSDODNS

Household debt meets corporate debt

Posted on April 30, 2020

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

The rich borrow, too

Liability distribution across rich and poor households

Posted on November 4, 2019

Over the past few weeks, we’ve used data from a dataset compiled by the Federal Reserve Board specifically to analyze the distribution of data across households. While our target so far has been assets, today we look at liabilities. How do rich and poor households borrow?

The graph above shows the total liabilities of four wealth classes: the top 1%, the next 9%, the next 40%, and the bottom 50%. At first glance, it appears that richer households hold less in liabilities. But if you hover over the graph, you see the actual percentages: the top 1% hold 4.6% of all liabilities, the bottom half 36%. One might assume the rich borrow less and the poor borrow more. But to better understand this, let’s take a look at the major categories on the liability side of things.

The first category is mortgages, shown in the second graph. Poorer households are less likely to own a home, and when they do it is a smaller home. As they have less funds, they need proportionally larger mortgages to own those smaller homes. Richer households need smaller mortgages, but they have a fiscal incentive for larger mortgages, as mortgage interest is deductible from their taxes and their tax rates are likely higher. In the end, we see that the top 1% hold 4.2% of all mortgages, while the bottom half has 39%.

The second category is consumer credit, on shown in the bottom graph. This includes credit cards, student loans, car loans, and other similar liabilities. Here the bottom half amasses 54% of the total debt; quite obviously they borrow to make many purchases. But the top 1% also punch above their weight with 2.1% of total consumer credit. How come? One reason is that expensive but highly rewarding courses of study (medicine, law) contribute quite a bit to student debt. Also, the consumer credit numbers include credit card balances paid in full (about 30% of credit card debt, or 7% of all consumer credit).

How these graphs were created: The procedure is the same for each graph. You can find these series in the Distributional Financial Accounts or the Levels of Wealth by Wealth Percentile Groups release table; check the series you want, and click “Add to Graph.” From the “Edit Graph” menu, open the “Format” tab to choose graph type “Area” with stacking “Percent.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: WFRBLB50101, WFRBLB50102, WFRBLB50103, WFRBLN09047, WFRBLN09048, WFRBLN09049, WFRBLN40074, WFRBLN40075, WFRBLN40076, WFRBLT01020, WFRBLT01021, WFRBLT01022

Are household debt and student debt exploding?

On the importance of properly deflating

Household debt meets corporate debt

The rich borrow, too

Liability distribution across rich and poor households

Need Help?

Subscribe to the FRED newsletter

Follow us