Federal Reserve Economic Data

March 14, also written as 3/14, is widely celebrated as π day. This is taken seriously in St. Louis, which is home to the 314 telephone area code.

The FRED Blog team is always eager to celebrate the occasion, so today we offer some pie charts. Now, using pie charts is rarely a good idea. They’re not as informative as other chart types. But today we make an exception and use three of them to track different groups’ relationships with bakery products—including pie, of course!

The chart above shows how much individuals from six age categories spend on bakery products. Imagine the United States as a large family with one member from each age group. If each were spending the same amount on bakery products, we would see a pie with six equal slices. But we do not see that. It seems that, as age increases, so does pie consumption. An advantage to becoming older, perhaps?

The second pie chart shows a different family in which each member belongs to a different income category. Not surprisingly, the poorer cousin spends less on bakery products than the wealthier grandparent. Qu’ils mangent de la brioche!

And our last pie shows the four different Census regions. Here, the differences are more subtle. It looks like bakery products are more appreciated in the Northeast and the West. Or they’re simply more expensive and require greater expenditures. Older data on the price of bread by region seem inconclusive. And, although there shall be enthusiastic pie eating in St. Louis today, we don’t expect that will move the annual Midwest statistic.

How these charts were created: For each, the principle is the same: Search FRED for the first series with, say, “expenditures bakery by age” and take one result. From the “Edit Graph” panel, use the “Add Line” tab to search for and select the next series. Repeat until you have a complete set. Use the “Format” tab to choose graph type “pie.” Bon appétit.

Suggested by Christian Zimmermann.

The FRED Blog has discussed how, over the past 30 years, the composition of US trade among its partners has changed dramatically. China became the largest supplier of US imports in 2009 and kept that role until 2018. That was the golden age of offshoring. However, as the poet Emily Dickinson would remind us, “thus passes the worldly glory.”

The FRED graph above shows four data series produced collaboratively by the Census Bureau and the Bureau of Economic Analysis. Each line represents, as of December 2023, the monthly dollar value of goods imported from the largest US trade partners.* They are, in descending order, the European Union (blue line), Mexico (green line), China (red line), and Canada (purple line).

This short essay from Luis Torres at the San Antonio Branch of the Federal Reserve Bank of Dallas describes why Mexico overtook China as the second-largest supplier of imported goods into the US. A combination of new tariffs (that is, taxes on imported goods) and supply-chain disruptions reduced goods inflows from China. At the same time, Mexico and Canada boosted their manufacturing industries. In the lingo of international trade, this is the age of nearshoring—notwithstanding the European Union.

*These values exclude import duties, freight, insurance, and other charges related to bringing the merchandise into the US.

How this graph was created: Search FRED for “U.S. Imports of Goods by Customs Basis from European Union.” Next, click the “Edit Graph” button and use the “Add Line” tab to add the other three series. Save some time by typing their series ID in the search box: IMPCH, IMPMX, and IMPCA.

Suggested by Diego Mendez-Carbajo.

In January 2024, overall CPI rose 0.3% on a seasonally adjusted basis—a slight uptick from its 0.2% rate in December. It’s still a slowdown year-over-year, but this increase came as an unwanted surprise to observers expecting to see inflation continue to moderate. What’s stopping the headline inflation rate from continuing its decline?

The answer, at least in January, was shelter inflation. For January 2024, the shelter index rose by 0.6% and contributed more than two-thirds of the total CPI increase. The above graph shows the year-over-year change in shelter prices over the past decade. It’s evident that the trajectory of shelter inflation has been different from the non-shelter components of CPI: “All items less shelter” inflation peaked in mid-2022 and has been declining since, but shelter inflation peaked about one year later in March 2023 and has been declining at a slower rate.

Why is this? Shelter costs have unique characteristics that distinguish them from other goods and services. The shelter component of CPI comprises rent, lodging away from home, and owners’ equivalent rent (OER).

Rents are sticky. They change only when leases renew or a tenant moves, so it may take some time for those prices to reflect market conditions. OER comes from the same housing survey and is an attempt to estimate what owner-occupied houses would rent for, based on surveying local renters. In addition, these measures are sampled less frequently than for other goods, precisely because they change so sluggishly. This results in CPI shelter data lagging current housing market conditions.

Researchers at the San Francisco Fed, among other places, have tried to incorporate real-time data to predict what will happen to CPI shelter measures. They find that pressure from shelter inflation could ease over the coming year.

How this graph was created: Search FRED for and select “Consumer Price Index for All Urban Consumers: All Items Less Shelter in U.S. City Average.” From the “Edit Graph” section, click “Add Line” and select “Consumer Price Index for All Urban Consumers: Shelter in U.S. City Average.” In the “Edit Line” section, set units to “Percent Change from Year Ago” for both graphs.

Suggested by Nathan Jefferson.