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Let’s talk turkey prices well as prices in Turkey

If you know this blog, you may have been expecting a holiday-themed post this week. We did our best, but—spoiler alert—it’s a bait and switch. We don’t have any recent price data on turkey meat. What we do have are recent price data on meat in Turkey. And, as you can see from the FRED graph above, that nation suffers from chronically high price inflation. (FYI: FRED has over 2,000 series of Turkish data.)

This year, Thanksgiving is more challenging in the U.S. not just for travelers but also for statistical agencies. The data-collection process for many of the series available in FRED has been disrupted by the pandemic, as agencies scramble to change their procedures to accommodate health guidelines and changing economic practices.

One example is the price of turkeys, which is usually available in the consumer price index. The Bureau of Labor Statistics hasn’t been able to provide an update since March 2020. Until the data become available again, we’ll have to serve up something less traditional. But we remain thankful for all the work these statistical agencies do to collect the data to make sense of our economy and make progress in the face of national challenges.

How this graph was created: Search for “turkey CPI” and click on the relevant series. From the “Edit Graph” menu, use the “Add Line” tab to search for the other series. Then be sure the indexes for both series are set to 100 on the same date.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CP0112TRM086NEST, CUSR0000SAF112

The state of decline in retail sales

Using new Census data to compare U.S. states

FRED recently added more new data from the Census Bureau: 11 categories of retail sales for U.S. states. A previous post looked at national declines in retail sales, and national data continue to show the pandemic’s damaging effects on this sector.

As with most economic measures, though, the effects aren’t equally distributed across the nation. So let’s use GeoFRED maps to examine individual state experiences—specifically, July 2020 sales compared with July 2019 sales for (1) electronics and appliance stores, (2) gas stations, and (3) clothing and clothing accessories stores.

The first map covers electronics and appliance stores. National data show a decline of 4.7% year over year, which would be even more concerning in normal times but is not the worst downturn we’ve observed during the pandemic. The map shows a lack of uniformity, with some strong decreases (California’s –14.2% at worst) and some strong increases (Montana’s +21.3% at best). For consumer durables like electronics and appliances, timing is important: In hard times, households postpone these purchases. When things improve, they catch up. The lack of uniformity here likely stems from the different phases of the pandemic across U.S. states.

The second map covers gas stations: National data show a decline of 16.2% year over year. Here, the effects are much more uniform across states, with a narrow range of –19.7% to –12.9%, except for Washington’s –6.7%. It’s hard to find substitutes for gasoline purchases, and all states experienced a similar drop in demand for travel and commuting.

The third map covers clothing and clothing accessories, where the story is similar to the one for gas stations. National data show a decline of 21.9%, and state numbers range from –26% to –12% (except for New Jersey’s –2.9% and Connecticut’s –5%).

For national accounting purposes, clothing isn’t considered a durable good, as electronics and appliances are. And that may be for the good reason that, as these map shows, clothing sales behave differently from those durable goods sales.

How these maps were created: A good starting point is the release table for monthly state retail sales. Click on a state series and then navigate below the graph to the related material, which includes a link to the GeoFRED map. (Or you could click on “View Map” on the graph and then “Edit Map”). Zoom-in or -out as you wish.

Suggested by Christian Zimmermann

Replicating economic research…on gasoline affordability

Here at the FRED Blog, we believe it’s important to be able to replicate economic analysis, which begins by identifying the data used in that analysis. That’s why FRED Blog posts include a list of the data series used to build the graphs. Moreover, all FRED data series themselves include a suggested citation.

The FRED graph above can help us reproduce some research published in our Economic Synopses series: “Gasoline Affordability.” The essay, published in 2004, compares wages with gasoline prices. To replicate the analysis, we searched for the two series mentioned in the essay: the CPI index for the price of gasoline and the average hourly wage rate of production workers.

The second FRED graph helps us test the robustness of the analysis by extending its conclusion about gasoline affordability and demand for SUVs past the original publication date. (Again, it was published in 2004.)

Between 2004 and 2009, when gasoline became gradually less affordable, the sales of lightweight trucks decreased. Nevertheless, despite the fact that gasoline was unevenly affordable between 2010 and 2020, the sales of lightweight trucks grew at a steady rate. Something other than gas prices must be driving demand for SUVs.

To learn more about auto sales, read Bill Dupor’s Economic Synopses essay “Auto Sales and the 2007-09 Recession.”

How this graph was created: Search for and select “Consumer Price Index for All Urban Consumers: Gasoline (All Types) in U.S. City Average.” From the “Edit Graph” panel, use the “Edit Line 1” tab to customize the data by searching for and selecting “Average Hourly Earnings of Production and Nonsupervisory Employees, Total Private.” Next, create a custom formula to combine the series by typing “a/b” and clicking on “Apply.” Next, use the “Add Line” tab to create a user-defined line. Create a line with start and end values of 10. Last, use the “Add Line” tab to search for “Motor Vehicle Retail Sales: Light Weight Trucks” and click on “Add data series.” To change the line colors, use the choices in the “Format” tab.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: AHETPI, CUSR0000SETB01, LTRUCKSA

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