Federal Reserve Economic Data

How much more do managers earn than the workers they manage? Sometimes the data can answer a question like this directly. But in this case, we must do a little work.

First, our investigation today is motivated by the fact that earnings for non-managers are persistently lower than earnings for the total pool of employees, which includes managers. But we don’t have data for the earnings of managers alone. A few developments during the pandemic make this question even more interesting: Non-manager weekly earnings rose when the pandemic hit, but non-manager hourly earnings (rate of pay) did not rise when the pandemic hit. So, did non-managers work more hours for the same rate of pay? Let’s see.

We compare weekly earnings for (i) the entire pool of workers and (ii) just non-managers so we can try to suss out what managers make. Non-managers earn about $170 per week less than the pool of all workers (which includes managers), and the graph above shows no visible evolution in that difference.

Our second FRED graph compares the same datasets but in terms of percent change from a year ago. We see no systematic difference between the two until the pandemic hits. At that point, non-managers started making significantly greater gains than the average of all workers; and they continue to do so.

Now, “weekly earnings” are a product of hourly pay and weekly hours. So, we focus on hourly pay in the graph above—again, in terms of percent change from a year ago. We see that non-manager pay didn’t immediately increase more once the pandemic hit. The increase only in the latter part of the pandemic seems to imply weekly hours must have increased more in the early stages of the pandemic. Did they?

We cannot see any difference at all in the two lines showing weekly hours. How is that possible? We would have expected the blue line to be significantly higher than the red line early in the pandemic. The problem is that the hours measured in the first graph aren’t the same as those in the last graph. The first uses the concept of average hours, which essentially represent regular work hours for an employee. The last graph considers aggregate hours, which is a total of all hours worked in the economy, and thus multiplies the average hours by employment. And the latter changed quite a bit during the pandemic. So, as it turns out, the decomposition we wanted to perform here doesn’t work. Which is why it’s so important to understand the precise definitions of the data you’re working with.

How these graphs were created: Search FRED for “average weekly earnings” and sele ct the production and non-supervisory workers series. From the “Edit Graph” panel, search for the same seriesbut pick “all employees.” You have the first graph. For the second, set units to “percent change from previous year” and apply to all. For the third and fourth graphs, repeat the operations with “average hourly earning” and “aggregate weekly hours.”

Suggested by Christian Zimmermann.

This post offers something old and something new: It covers similar ground from a post last November, but it’s the first post to use FRED’s new mapping feature! We hope you like the look and functionality!

Our splendid new map above depicts growth in new business creations by state during 2021—specifically, the percent change between 2020 and 2021 in the number of business applications recorded by the U.S. Census for each state. Darker colors represent higher growth rates.

The data themselves also offer something old and something new: Growth in business applications was highest for the first state to enter the Union and lowest for the next-to-last state to enter the Union.

In Delaware, known as the “First State,” businesses grew by 47%, which is almost double the typical (or median) growth rate of 25%. Business laws there have long facilitated the formation, or incorporation, of new commercial enterprises, so perhaps this is no surprise.

However, in Alaska, on the opposite side of the continent, their 2% growth in business applications was the lowest in the country. Here at the FRED Blog, we shall not wander “into the wild” speculating about the reasons behind the slow growth in new business creations in the “Last Frontier” state.

How this graph was created: Search for and select “Business Applications for Alaska.” From the “Edit Graph” panel, use the “Edit Line 1” tab to modify the data frequency to “Annual” and the aggregation method to “Sum.” Last, close the edit panels and click on the “View Map” green button. Happy travels with FRED maps!

Suggested by Diego Mendez-Carbajo.

Corporate profits have been growing at unprecedented rates, and inflation in producer prices has risen sharply as well. Our FRED graph above helps us compare the two and briefly discuss their relationship.

Pre-tax corporate profits (shown by the blue line) increased by 51% between the fourth quarter of 2019 and the first quarter of 2022. During the same period, producer price index (PPI) inflation in manufacturing rose by 21.2% (shown by the red line).

Why would this matter? PPI inflation measures changes in prices producers receive for their products and prices other producers pay for those products as intermediate goods in their own production. During the COVID-19 pandemic, supply chain disruptions contributed to an increase in the price of these products. (See this Review article for a deeper discussion.) And yet, corporations seem to have passed through enough of these intermediate costs onto the consumers of their final products to see record profits and large profit margins.

How this graph was created: Search FRED for “corporate profits” and select “Corporate business: Profits before tax (without IVA and CCAdj).” From the red “Edit Graph” button in the top right, use the “Add Line” tab at the top to type in the search box “PPI manufacturing” and select “Producer Price Index by Commodity: Total Manufacturing Industries.” Change the units for PPI to “Percent change from a year ago.” In the “Edit Graph” panel, use the “Format” tab and under Line 2 change the y axis to “Right.” Change dates in the top right of the graph to the desired period.

Suggested by Ana Maria Santacreu and Jesse LaBelle.