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Comparing the assets of the rich, poor, and middle class

Data on the asset distribution across U.S. households

The FRED Blog has covered income and wealth before: for example, distribution of wage income, net worth, and assets. This post covers household assets, but compares them across groups: the top 1%, the 90-99%, the 50-90%, and the bottom 50%. FRED has data from the Board of Governors of the Federal Reserve System’s Survey of Consumer Finances, and the graph above shows the total assets for households in these four wealth/asset groups.

It’s clear from the graph above that the bottom half of households collectively hold significantly fewer assets than any of the three other groups. Those groups hold about the same order of magnitude in assets, but with populations of very different sizes (40%, 9%, and 1% of the total number of households).

We also see that, for these three groups, total assets have grown almost continuously, except for a dip in the past recession. Of course, this could be due simply to inflation and population growth…

So, the second graph does this adjustment. It shows that total assets have increased over time for all three groups, even after this rescaling.

The third graph offers a further adjustment by dividing each line by the size of the group. This gives us an idea of the relative magnitude of the assets per capita in each group. The differences are so large that we removed the legends to make more space for the graph. The poorest group is so low, it’s not visible. So we might as well express the assets of the three top groups as a multiple of the assets of the poorest 50%, which we do in the last graph. Beyond the stark differences between the groups, it’s quite obvious that the assets of the top 1% have increased faster than those of the other two groups since the past recession. In fact, they have almost doubled relative to the poorest 50%, from 139 times to 258 times at the apex in 2017:Q1, to 235 times now.

How these graphs were created: Start with the release table for Levels of Wealth by Wealth Percentile Groups, select the four first series, click “Add to Graph.” That’s the first graph. For the second, use the first and go to the “Edit Graph” panel. For each line, in the “Edit Line…” tab, use the “customize data” tool to search for and add the CPI series and then the population series, and apply formula a/b/c. Repeat for the three other lines. For the third graph, modify the formula to divide each by 0.01, 0.09, 0.4, and 0.5, respectively. From the “Format” tab, deselect legends and axis labels to free up some space. For the last graph, for the first three lines, add series “WFRBLB50081” and add /(d/.5) to the formula. Remove the fourth line by deleting each of its constituting series.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: B230RC0Q173SBEA, CPIAUCSL, WFRBLB50081, WFRBLN09027, WFRBLN40054, WFRBLT01000

What’s worrying the markets?

More data on policy uncertainty

For some time now, FRED has offered various economic uncertainty indices from the work of professors Baker, Bloom, and Davis. We now have even more detailed data on uncertainty about specific economic policy categories; a handful are shown in the graph above.

Before we dive into any interpretations, we need to first understand the data. Basically, they track the number of mentions of specific economic policies in over 2,000 U.S. newspapers. Some policies are considered more important than others by journalists and the general public; some are perennial favorites and some are rarely discussed.

Overall, higher values likely show how worried the press, and probably the general public, are about that aspect of economic policy. High values are a combination of high uncertainty and the importance of the policy. A policy considered less important will be less likely to spike up even when there’s a lot of uncertainty about it.

Back to the graph: We selected five categories. The blue line clearly has the most action lately: It depicts uncertainty about trade policy, which is obviously tied to the ongoing trade war with China and other countries. The data also show significant trade policy uncertainty around 1994, the year NAFTA was introduced. A regular standout is the series in red—sovereign debt and currency crises—which has mostly to do with the recurring threats of government shutdowns when Congress struggles to pass a budget. The line in…teal, let’s call it, depicts uncertainty about financial regulation, which is clearly visible after the 2007 Financial Crisis, when Congress worked out the Dodd-Frank Act. Health care policy, in purple, has regularly been in the news since 2008 thanks to Obamacare. Finally, government spending, in light green, appears mostly in the years after the Financial Crisis as TARP was being implemented.

How this graph was created: Start from the Economic Policy Uncertainty index release table: Select “United States Indices,” then “Monthly Indices,” and then “Categorical…” Check the series you want and click “Add to Graph.”

Suggested by Christian Zimmermann.


Households’ lightening debt load

Data on the financial burden of U.S. households

There are many types of debt, including household debt, and many specific types of household debt as well. The Board of Governors of the Federal Reserve System collects a wide and well-organized array of data on debt. These data, especially in graph form, can help us better understand the financial burdens of U.S. households.

This FRED graph shows the percentage of disposable (i.e., after-tax) income that households dedicate to servicing specific types of debt. The graph has four lines. Let’s start at the bottom: The green line shows mortgage debt, and the red line shows consumer debt (credit card, auto, and personal loans). The blue line is the sum of the red and green lines. And the purple line adds to the blue line some other financial commitments, such as rent, auto leases, homeowners’ insurance, and property taxes.

What can we learn from this FRED graph?

The two top lines are almost always parallel to each other, which means that the contribution of those “other financial commitments” doesn’t really change much over time.

The financial burdens from mortgages and consumer debt vary quite a bit. Let’s consider two reasons for this: The larger the debt, the larger the burden, as households need to pay more interest on a larger principal. And changes in interest rates obviously influence how much is paid to service loans. The blue line (mortgage debt plus consumer debt) increased from the early 1990s until the past recession, when it decreased. This decrease is the result of the combination of the two effects noted above: the amount of debt and interest rates. With one exception (in the fourth quarter of 2012), total debt obligations are at the lowest they’ve been since these data were first collected. And this is especially true of mortgage debt.

How this graph was created: Start from the Household Debt Service and Financial Obligations Ratios release table, select the desired series, and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CDSP, FODSP, MDSP, TDSP

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