Federal Reserve Economic Data

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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.

View on FRED, series used in this post: EPUFINREG, EPUGOVTSPEND, EPUHEALTHCARE, EPUSOVDEBT, EPUTRADE

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

The price of a BLT

Slicing the layers of the CPI

Over the summer, FRED added 1,479 new series on average prices for a wide range of consumer items. Almost half of the new data are prices of foodstuffs, more than enough for a seven-course dinner.

But to keep it simple, let’s make a traditional BLT sandwich: bacon, lettuce, and tomato on white bread. (Today, we’ll hold the mayo.) Like most things, the price of a BLT has risen over time, which you may have noticed at the local diner or in the supermarket. Let’s “go figure with FRED” what’s been driving up the price of this lunch staple.

The FRED graph immediately below plots the prices of all four ingredients over time. The prices of three of the ingredients rise at a fairly constant rate, which is a sign of low and stable consumer price inflation. But the fourth price (in red) is not only noticeably higher than the rest but rises at a much steeper rate. So, this ingredient has been experiencing a higher rate of price inflation.

Have you looked at the graph’s labels to figure out the culprit? It’s the bacon!

Now, if you’d like to follow our recipe and portion sizes for each ingredient, you can track the price of an actual BLT in the graph below: As of August 2019, it’s $1.53!

How these graphs were created: On the FRED homepage, under the search bar, click on “Release” (in the “Browse by…” line). Then scroll down and select “Average Price Data” then “Food.” From the table, select “Tomatoes, Field Grown, Per Lb. (453.6 Gm) in U.S. City Average,” “Bacon, Sliced, Per Lb. (453.6 Gm) in U.S. City Average,” “Lettuce, Iceberg, Per Lb. (453.6 Gm) in U.S. City Average,” and “Bread, White, Pan, Per Lb. (453.6 Gm) in U.S. City Average.” Click on “Add to Graph.” For the second graph, start with the first and use the “Edit Graph” menu to apply a formula to adjust for the weight of the items in your sandwich. (The prices are all given in pounds, so we divide by 16 to get ounces and then multiply by the number of ounces we prefer: 2 oz. of tomatoes, 3 oz. of bacon, 1.3 oz. of lettuce, and 2 oz. of bread.) To stack all the individual prices, use the “Format” tab to select graph type “Area and Stacking: Normal.”

Suggested by Diego Mendez-Carbajo and Maria Arias.

View on FRED, series used in this post: APU0000702111, APU0000704111, APU0000712211, APU0000712311


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