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The largest changes in payroll employment

Comparing April 2020's social distancing and August 1983's AT&T strike

The April 2020 changes in payroll employment are unprecedented in scale, but their nature is familiar.

The FRED graph above shows the monthly percentage change in payroll employment across all service-providing industries since 1939. Although the most recent reduction in leisure and hospitality employment (the red bar on the far right edge of the graph) has been the largest, both in magnitude and in proportion to the size of the industry’s labor force, we can compare it to a somewhat similar event: the American Telephone & Telegraph Co. union workers’ strike of August 1983 (the blue bars at the center of the graph).

Both reductions in employment were orchestrated: In 1983, the labor stoppage was to achieve better working conditions; in 2020, the labor stoppage has been to slow the spread of the COVID-19 pandemic.

The flip side of an organized labor stoppage is the organized nature of its recovery. In the case of the striking telephone workers, employment rebounded the following month. Alas, it’s too early to know if or when scaling back social distancing will produce a similar recovery in employment. Check FRED on June 5, 2020, at 8:30 AM (CST) to see the next changes in payroll employment.

How this graph was created: From FRED’s main page, browse data by “Release.” Search for “Employment Situation” and from “Release Tables” click on “Current Employment Statistics (Establishment Data).” From the table, select each of the nine industries in the private service-providing sector and click “Add to Graph.” From the “Edit Graph” panel, use the “Edit Line” tab to change the units to “Percent Change” and click “Copy to All.”

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CES4300000001, USEHS, USFIRE, USINFO, USLAH, USPBS, USSERV, USTRADE, USWTRADE

Data on families

Maps and charts for Mother’s Day

Did you remember to call your mother yesterday? Did you send flowers? Why not also send her a (belated) FRED dataset? Above is one example—a colorful GeoFRED map showing county-level data on single-parent households with children. Below is another—a pie chart showing the percentages of family types with their own children: married couples, single mothers, and single fathers.

Once you’ve selected some FRED data, explore more graph formats by clicking on “Edit Graph” from the series page. You can get to the series page for the FRED data shown here by clicking on “View on GeoFRED” and “Customize” at the bottom of the image. From the “Format” tab, navigate through the options, including colors and patterns.

And don’t forget to say “Thank you” to Mom!

How the map was created: In GeoFRED, click on “Tools” and select the county maps. Look for “Single-Parent Households” in the dropdown menu. From the “Choose Colors” tab pick colors to taste.
How the pie graph was created: In FRED, search for “Total Families with Children under 18 Years Old with Married Couple.” From the “Edit Graph” panel, use the “Add Line” feature to search for and select the “Total One Parent Families with Children under 18 Years Old with Mother.” Do the same to add the series “Total One Parent Families with Children under 18 Years Old with Father.” From the “Format” tab select “Graph type: Pie” and pick segment colors to taste.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: FMLWCUMC, OPFWCUFO, OPFWCUMO

Reckoning with premature deaths

CDC data on premature deaths for the St. Louis area

The COVID-19 pandemic has affected everyone in some way. The mildest cases involve inconveniences such as being confined at home to avoid spreading the virus. Other cases involve unemployment, lost businesses, and accumulating debt. The worst cases involve coping with the premature deaths of loved ones.

Each death—and its associated life—has unique and powerful elements. Yet, some deaths can be considered more “normal” than others, especially if they’re associated with very old age. The FRED graph above explores CDC data on premature deaths for FRED’s hometown, St. Louis city, as well as neighboring St. Louis County (separate from the city). Solid lines show the crude rates while dashed lines show the age-adjusted rates from 1999 to 2017.

According to the CDC, the premature death rate includes all deaths of those younger than 80 years of age. The crude death rate is simply the number of deaths reported each calendar year per 100,000 people. The age-adjusted death rate is a weighted average of the age-specific death rates, where the weights are associated with a fixed population by age. This is an important adjustment because differences in the composition of the population over time or across counties make comparisons difficult.

First, there’s a dramatic difference between St. Louis’s city and county. This can be expected from the economic asymmetries between the two locations: On average, St. Louis County residents are economically much better off than city residents. In 2017, the rate for the city was 675, which is more than 50% higher than the rate for the county, 446. The age-corrected rates have an even wider (70%) gap, with 594 for the city and 348 for the county.

Compounding factors make a difference: demographic (e.g., age, education), economic (e.g., occupation, nutrition, access to care), social (e.g., exposure to crime, access to care), and environmental (e.g., pollution, access to parks). (A previous FRED Blog post discusses the large variation observed in U.S. premature death rates.) Since these factors move with the economy, a natural hypothesis is that, as the economy grows, its rate of premature deaths should decline.

But premature death rates are on the rise in many locations. During the almost 20 years covered in the graph, both locations have made very little progress. Before the Great Recession of 2007-2009, both locations were either in a stagnant state (a stable rate for the county) or on a favorable trend (a declining rate for the city). After that, both locations entered an adverse trend, almost reversing the gains of the previous years. This result is eliminated once we look at the age-corrected series. Yet, the age-corrected rates still show a troublesome upward trend for premature deaths.

How to create this graph: Search FRED for “premature death” and choose the series for St Louis city. From the “Edit Graph” panel, use the “Add a Line” feature and add the same series for St. Louis County. Likewise, add the series for age-corrected rates. Select the colors and line thicknesses to make the graph easy to read.

Suggested by Alexander Monge-Naranjo.

View on FRED, series used in this post: CDC20N2U029189, CDC20N2U029510, CDC20N2UAA029189, CDC20N2UAA029510

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