Federal Reserve Economic Data

The FRED Blog has used ALFRED graphs to discuss the regular revisions to employment data and the periodic updates to real gross domestic product data. Here, once again, we tap into ALFRED to discuss revisions and updates to consumer price index (CPI) data.

The bars in the ALFRED graph above show the annual CPI inflation rates between 2018 and 2021 using two different vintages of CPI data: before (in red) and after (in blue) the January 2022 revision and update to the CPI data. The differences in annual inflation rates are minimal, so what is involved in those revisions and updates?

The revisions are conducted every year and involve adjusting many of the 80,000 individual prices recorded every month for changes in their seasonal patterns. For example, fresh fruit prices are lower during harvest on account of the bountiful supply available. The BLS considers these price swings and reports seasonally adjusted price indexes. However, the seasonal changes in prices can be as fickle as the seasonal weather and the corresponding adjustment factors used by the BLS require regular evaluation.

The updates are conducted every two years and involve adjusting the relative weights of goods and services purchased across eight different categories of consumer spending. For example, over the past two years of COVID-19-induced disruptions to regular life, consumers shifted their food purchases away from restaurants towards groceries. The BLS considers those changed patterns by introducing new spending weights in its market basket for goods and services.

Some research shows the impact large-scale and less-frequent revisions and updates to CPI data have on the accurate calculation of consumer price inflation. In that light, the small differences in annual inflation rates across data vintages reflected in the ALFRED graph are a testament to the value of more frequent and smaller-scale updates to CPI data. More accurate data facilitates better decision making, even if the reported inflation rates do not change much.

How this graph was created: Search ALFRED for “Consumer Price Index for All Urban Consumers: All Items in U.S. City Average.” By default, ALFRED shows a graph with two sets of bars: the most recent vintage and the prior vintage. Add additional vintages by using the “Add Line” tab and select the date of the desired vintage from the “or select a vintage” dropdown menu. Change the start date and the end date above the graph to customize the number of data points shown.

Suggested by Diego Mendez-Carbajo.

Homeownership is a significant part of the American economy—and, from many perspectives, the American Dream. Given the recent talk about rising house prices, one could ask whether prices are higher because ownership is higher or whether ownership is lower because houses have become less affordable. These topics are always complicated, but maybe a glance at the homeownership rate could help.

The FRED graph above shows the recent evolution of the homeownership rate, but the verdict is…unclear. The rate spiked through the early phase of the pandemic, which actually looks like an acceleration of a previous trend. But then the rate crashed back to pre-pandemic levels and seems to be staying put. These dynamics are much more complex than a simple story of housing demand and affordability can untangle, but maybe even-more-detailed data can shine a brighter light.

We have two ways to slice the national data: by Census region and by race.

• The graph above shows differences among Census regions. The Northeast and Midwest homeownership rates stay high after the pandemic spike, but we can’t see why only those regions are steady.
• The graph below shows differences among race categories. There’s no clear message here either, but these affordability issues do seem to plague Black homeowners, as their rates are definitively trending down.

Our only conclusion here is that these graphs aren’t enough to reveal the full story behind the homeownership rate.

How these graphs were created: All three graphs start from the Homeownership rates release table. Check the series you want displayed and click “Add to Graph.” To make the national line thicker, use the “Edit Graph” panel to open the “Format” tab and make the first line thickness “3.” For the last graph, start the graph on 1994-01-01, as racial disaggregation is not available prior to that date.

Suggested by Christian Zimmermann.

The Russian invasion of Ukraine has amplified concerns about the price of gasoline. And for good reason: In March, prices at the pump surged over $4 per gallon for the first time since July 2008. This increase is more than 50% above prices in March 2021, which were about $2.80 per gallon. Gas at $4 per gallon sounds scary, but are real gas prices really that high?

By real prices, we mean prices that take overall inflation into account. To investigate, we compare nominal gas prices (the price you pay at the pump) to real gas prices, which we compute by dividing the nominal price by the consumer price index (CPI) and multiplying by 127.5, the value of the CPI in January 1990. By doing this, we normalize the gas price to the value of the dollar in January 1990, allowing us to compare gas prices across time and account for overall inflation.

The FRED graph above shows the result: Real gas prices have indeed increased in the past few months; however, they have only recently reached their pre-pandemic level. While nominal gas prices have increased rapidly over the past few months, real gas prices were still lower than they were for most of the 2006-2014 period. In fact, today’s real prices are within one standard deviation of the mean over the past 15 years.

These normalized, real gas prices have remained relatively flat over the past 5 years, which tells us that the high nominal prices are substantially driven by high inflation. Now we understand that an essential driver of the long-run increase in the price at the pump is inflationary pressures.

How this graph was created: Search FRED for “gas price,” then from its graph click on “edit graph”, under “customize data,” and apply formula (127.5*a)/(b). Then open the “add line” tab and search for the gas price again.

Suggested by Julian Kozlowski and Sam Jordan-Wood.