Federal Reserve Economic Data

FRED aggregates data from various sources. Those sources routinely revise and update the data they produce. After all, more-accurate data allow for better decisionmaking. These sources also update the names of their data series to accurately describe the activity they record. FRED incorporates these updates with an automated process.

One source, the Bureau of Labor Statistics, provides the consumer price index (CPI) dataset, which measures the average change over time in the prices paid by urban consumers. The FRED graph above displays one CPI data series that had its name changed as of February 14, 2023: from “Cable and satellite television service” to “Cable, satellite, and live streaming television service.”

This update to the series name reflects the addition of customizable internet-based live streaming of television services, which had been commonly provided via land cable and satellite wireless signals.

So what does this FRED graph show? The time period is January 1992 to December 2022, the units are percent change from a year ago, and the values are the year-over-year inflation rate of television service prices. These prices had some cyclical ups and downs but were trending downward until 2011, when that declining trend reversed. In fact, price growth for television services has markedly outpaced total price growth for its parent category, recreation services.

Stay tuned to the FRED Blog for more news of updates to additional data series names.

How this graph was created: Search FRED for “Cable, satellite, and live streaming television service.” Next, click the “Edit Graph” button, select the “Line 1” tab, and use the “Units” dropdown menu to select “Percent Change from Year Ago.” Last, select the “Format” tab to change the graph type to “Bar.”

Suggested by Diego Mendez-Carbajo.

In the US, we commonly measure inflation with the yearly change in the consumer price index (CPI), which stands at 6.3% for January 2023. As we’ve said before in the FRED Blog, a single number like this can hide a lot of variation across all the goods consumed by Americans. So let’s look at a recent, interesting twist in prices in this country.

The FRED graph above divides the CPI into two parts: prices related to shelter and all other prices. It starts at an index value of 100 in January 2022 and ends in January 2023 to show how prices evolved over the past year. Shelter-only CPI has a value of 107.9, meaning it has increased by 7.9% since January 2022. All-items-except-shelter CPI has a value of 105.7.

The price of shelter has been continuously increasing, while the price for everything else stopped increasing in June 2022 and has even decreased a bit since. Does this mean our latest inflation episode is over except for shelter? Possibly, especially because there are data-collection lags when calculating the cost of shelter. Still, is six months enough time to claim victory and is the CPI even the right measure? We leave these difficult questions for policymakers to answer.

How this graph was created: Search FRED for CPI shelter. Click on “Edit Graph,” open the “Add Line” tab, search again for CPI shelter, but this time select the CPI less shelter. Choose unit “100 for a given date,” type in 2022-01-01, and click on “Apply to all.” Finally, reduce the sample period to one year.

Suggested by Christian Zimmermann.

The FRED Blog frequently provides context to help tell the story behind the data. Today we need a bit of history as well to help clarify the names of the data series themselves.

In 1876, the city of St. Louis, Missouri, became its own county, separating its local government affairs from the rest of St. Louis County, Missouri. Since then, the U.S. Census has tallied population statistics across subdivisions, or tracts, of these two separate counties with very similar names.

The FRED graph above shows the racial dissimilarity index for St. Louis City (in blue) and St. Louis County (in red). The Census reports the index as a percent of the non-Hispanic White population that would have to move from one census tract in a county to another census tract in the same county to achieve an even distribution of racial groups across that county.

Consider 2009, when the first data in the series are available: At that time, about two out of every three non-Hispanic White residents in the city of St. Louis would have had to change where they lived for this specific type of racial dissimilarity to disappear within St. Louis City. Slightly more than half of the residents in St. Louis County would have had to do the same to eliminate this racial dissimilarity in that county.

Twelve years later, the population landscape has changed. Since 2020, in terms of their racial makeup, the tracts in St. Louis City are noticeably more like one another than the tracts in St. Louis County.

However, the overall racial makeup of these two similarly named neighboring counties is very different and should be taken into consideration when interpreting the data. To begin with, almost two out of every three County residents are non-Hispanic White. In the City, the ratio is almost one-to-one. The population trends are also different: Between 2010 and 2020, the city lost almost 6% of its residents, while the county added 5%.

So, at least two different population trends could be at play here. Perhaps, on average, neighborhoods in the City are becoming more racially integrated while neighborhoods in the County remain steadfastly less integrated. Or it could be that population loss of racial minorities in some City neighborhoods is making the overall racial distribution there more even. Of course, both trends can be at play here. An in-depth analysis of tract-level Census data is needed to come to a definite conclusion.

How this graph was created: In FRED, search for “White to Non-White Racial Dissimilarity (5-year estimate) Index for St. Louis city, MO.” Next, click “Edit Graph” at the top right corner and navigate to the “Add Line” tab. Search for “White to Non-White Racial Dissimilarity (5-year estimate) Index for St. Louis County, MO” and click on “Add data series.”

Suggested by Diego Mendez-Carbajo.