Skip to main content

The FRED® Blog

Eat, drink, and be thankful Tracking prices of the Thanksgiving meal

Turkey, cornbread, sweets, and more. It’s no wonder 27% of Americans say their favorite holiday is Thanksgiving, according to a 2004 Gallup Poll. And the National Retail Foundation estimates that shoppers spend an average of about $300 per person during the long weekend. Some of that spending is on gifts and holiday sales. Here, we’ll focus on a costs specific to the Thanksgiving Day meal.

The International Monetary Fund tracks the global prices of a number of food items, and FRED has those data. The graph shows the change in price from one year ago for the four series most relevant to Thanksgiving: sugar, corn, poultry, and beverages. Sugar and corn are certainly the most volatile, with prices rising over 100% in a year on several occasions. However, prospects are good this year for a second helping of creamed corn: Prices in June were about 12% lower than they were a year ago (if you are sourcing on world markets), and the trend looks likely to continue.

Turkey, on the other hand, hasn’t fared so well this year. Before March 2017, prices hadn’t fluctuated by more than 20%; however, the change in poultry prices from June 2016 to June 2017 was over 32%. But don’t put away the baster and roasting pan just yet. The index measures the prices of poultry around the globe, not just turkey in the United States. Turkey is still comparatively cheaper than most other U.S. meats and alternatives. According to the USDA, turkey was $1.54 per pound in September, compared with $4.13 per pound for ham and $5.79 for beef roasts. So, although your turkey may be comparatively more expensive than last year’s, sticking to this meat dish may save you a substantial amount.

Those with a sweet tooth can also take a deep breath. June prices for sugar were almost 30% lower than a year prior. While damage done to sugar farms by recent hurricanes could limit future sugar production, recent USDA data show that the price continued to drop in September 2017. Sugar is consistently less volatile than other foods, so your traditional pies and cobblers will likely still find their way to the table.

How this graph was created: Search for “global price” and select “International Monetary Fund” as the source in the sidebar. This should give you all the relevant series on one page. (Otherwise, add them to the graph later.) Select the series you want and click on “Add to Graph.” From the “Edit Graph” tab, select units “Percent change from year ago” and click on “Apply to all.”

Suggested by Maria Hyrc and Christian Zimmermann.


Where is subprime? Mapping the distribution of subprime borrowers by county

The “subprime credit population”—those with credit scores below 650—received much attention during and after the Great Recession of 2007-2009. Are these borrowers concentrated in certain areas or evenly distributed across the country? FRED’s county-level data from Equifax maps out the percentage of each county’s population that’s classified as subprime. The geographic disparities are quite large. At the high end, in Kenedy County, Texas, almost 56% of the population has a subprime credit score. At the low end, in Hooker County, Nebraska, only 3% of the population has a subprime credit score. Overall, the subprime population is more common in Southern states, but there are exceptions. Big Horn County, Montana, is 35% subprime, resembling Hardin County, Texas, and Marshall County, Tennessee. But some of Big Horn’s neighboring counties in Montana—for example, Carbon County (16%) and Yellowstone County (23%)—have much smaller subprime populations.

How this map was created: From GeoFRED, select county-level data and choose “Equifax Subprime Credit Population” in the drop-down menu.

Suggested by Guillaume Vandenbroucke.

The full banana of the labor market An update on the Beveridge curve

Three and a half years ago, we published a blog post about the Beveridge curve featuring the graph above, which shows how job vacancies and unemployment relate to each other. Each dot represents their values at a particular date. Beveridge’s theory is that these two measures don’t form a kinked line along the axes in a scatter plot, but rather a banana shape. This shape occurs because of delays and frictions in the job market: Vacancies and job seekers take time to intersect, as there may be mismatches in terms of job location and qualifications, for example. The graph above doesn’t show the expected full banana because the available sample period just wasn’t long enough. So, we revisit this idea by updating the graph, shown below. The banana, although not very smooth, is now complete.

How this graph was created: Search for “job openings” and add the series to the graph. From the “Edit Graph” section, add the second series by searching for and adding “civilian unemployment.” From the “Format” tab, choose “Scatter” for graph type. To connect the dots, choose a non-zero line width in the settings of the first series, which is where you can also adjust the size of the dots.

Suggested by Charley Kyd and Christian Zimmermann.

View on FRED, series used in this post: JTSJOR, UNRATE

The “youngest” and “oldest” places to live Age differences across the U.S.

Much is said about the ethnic patchwork of the United States, but this map highlights another kind of diversity: age. FRED’s county-level data on the age distribution of the U.S. population show large variations across the country and also within states. The spread of the range is also surprising. The youngest median age, 21.4 years, is in Lexington City County, Virginia—a small county that hosts two universities. The oldest median age, 65.3 years, is in Sumter County, Florida, where over half the residents live in a giant retirement community. Florida is expected to have a high median age, but other states also have counties with high median ages, including the admittedly small counties of Mineral, Colorado (60.9 years); Highland, Virginia (59.0 years); and Hooker, Nebraska (57.9 years).

How this map was created: Go to GeoFRED, select county-level data, and find median age population data in the drop-down menu.

Suggested by Christian Zimmermann.

Where have all the workers gone? A smaller working-age population could mean less growth

How much an economy can produce depends to a large extent on the number of persons who are old enough to work but not too old to work. One can try to make sure there are employment opportunities, but obviously you need workers. The graph shows two measures of the “working age” population for the United States, based on different age spans. The 15- to 64-year-old range covers everyone who could work up to the hypothetical retirement age of 65. The 25- to 54-year-old range excludes the youngest (likely still in some form of schooling) and the oldest (who may have already entered some form of retirement). As the overall population of the U.S. increases, these two measures ought to increase as well. But the second measure lately has not. Why?

It all boils down to the age composition of the U.S. population.

    1. The large cohort of the Baby Boomers is now almost all older than 54, so would not be included in the 25- to 54-year-old age range.
    2. Fertility has decreased, so there are fewer younger people replacing those who are retiring from the workforce.
    3. Immigration can compensate for lower fertility, as immigrants are typically of working age, but immigration doesn’t appear to be strong enough to make up the difference.

With about a 10-year delay, the number of 15- to 64-year-olds should also flatten out, with far-reaching economic implications: The U.S. economy is unlikely to be able to sustain the growth of past decades without the usual growth in its working-age population.

How this graph was created: Search for “working age population age” and the two series should be visible. If not, use the side bar options to narrow down your choices. Check the two series and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: LFWA25TTUSA647N, LFWA64TTUSA647N

Subscribe to the FRED newsletter

Follow us

Twitter logo Google Plus logo Facebook logo YouTube logo LinkedIn logo
Back to Top