# Federal Reserve Economic Data

The FRED® Blog

### Posts tagged with: "HCCSDODNS"

View this series on FRED

## On the importance of properly deflating

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

## 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