Federal Reserve Economic Data

It can be useful to compare economic statistics across countries, including unemployment rates. It’s not always easy to do so, and our post today explains why.

The unemployment rate is a ratio of two measures:

1. the number of unemployed
2. the total labor force

Both measures are subject to their own definitions and interpretations, with some tricky details. For example, what counts as “looking for work”? This question defines who’s unemployed vs. who’s outside the labor force. Does perusing a job-posting website suffice, or does it require actively sending resumes to businesses? Do teenagers count? Students? What about temporary layoffs?

The Organisation for Economic Co-operation and Development (OECD) standardizes economic measures across its member countries and publishes harmonized statistics, including unemployment rates.

Our FRED graph above shows the OECD’s harmonized unemployment measure (in blue) along with the Bureau of Labor Statistics’ measure (in red) for the US. Both these rates use the age range of 25 to 54 years and track each other remarkably well, hinting that their definitions are very similar.

The US unemployment rate that’s widely disseminated, though, covers those who are 16 years or older. This rate (in green) is higher and should not be used to compare the US unemployment rate with the rates in other countries.

How this graph was created: Search FRED for and select “OECD unemployment rate US 25-54.” Click on “Edit Graph,” open the “Add Line” tab and search for “unemployment rate,” take the UNRATE series, and change the frequency to quarterly (average over months). Repeat for “unemployment rate 25-54.”

Suggested by Christian Zimmermann.

The FRED graph above shows the prices of a dozen eggs and a pound of chicken breast. (A previous post graphed price changes for those items.)

Egg prices have been in the news for their stark increases recently. But chicken breast prices not so much, as those prices have been relatively stable. Why the difference in price patterns for products from the same animal?

Economic theory would tell you this: If two goods are substitutes, their prices track each other well, as one can be replaced by the other if one becomes relatively more expensive. But eggs and chicken meat are not substitutes in either production or consumption.

Are they complements? That would mean that, if you eat one, you necessarily eat the other. Only few recipes call for both eggs and chicken meat, so they aren’t complements in consumption. But they could be complements in production: An egg-laying hen can also provide chicken meat. In a case such as this, excess demand for one over the other can lead to a divergence of prices.

But that is not the explanation either. Nowadays, chickens are very specialized. “Broilers” grow in a few weeks before slaughter, while laying hens live for years. The latter have more opportunity to catch diseases, and the current avian flu epidemic is affecting them much more than broilers, which can be replaced quickly. Thus, chicken breast prices are much less affected, if at all, by current circumstances.

How this graph was created: Search FRED for “chicken breast” and click on the first choice. Click on “Edit Graph,” then open the “Add Line” tab, and search for/select the series for eggs. Finally, start the graph in 2006.

Suggested by Christian Zimmermann.

Home mortgages are households’ largest source of debt. And since 2010, student loans have been their second-largest source of debt.

The FRED Blog has discussed student loan and household debt before, in relation to overall economic activity. Today, we compare student loan debt with three other categories of consumer credit:

• Revolving consumer credit, mostly credit card debt (blue area)
• Automobile loans (green area)
• Student loans (orange area)
• Other, non-revolving consumer credit (purple area)

The FRED graph above shows quarterly data on each category from the Board of Governors of the Federal Reserve System. The units are in millions of dollars, but are presented in stacked areas to easily show each category as a percentage of the entire pool of consumer credit.

Data on student loans, as a standalone category of consumer credit, has been reported only since 2006, so we can’t observe the rollout of the Federal Direct Student Loan Program in 1994. But the growing share of student loans, as a fraction of overall consumer credit, is easy to see: It’s risen from 20.6% in 2006 to 35.6% in 2024. Learn even more here.

How this graph was created: Search the alphabetical list of FRED releases for “Z.1 Financial Accounts of the United States” and select “Quarterly: L.222 Consumer Credit.” Select the four series listed under the heading “Memo” naming the types of consumer loans and click “Add to Graph.” Use the “Format” tab to change the graph type to “Area” and the stacking option to “Percent.”

Suggested by Diego Mendez-Carbajo.