Federal Reserve Economic Data

The COVID-19 pandemic prompted workers to reconsider their professional lives and consider different types of employment. Self-employment, which is a vital source of jobs in the US, followed a different pattern of recovery than total employment during and after the COVID-19 pandemic.

The self-employed make up between 10% and 11% of the 157 million employed workers in the United States. The Bureau of Labor Statistics (BLS) defines the self-employed as those working for profit or fees in their own business and distinguishes between incorporated and unincorporated self-employment. The incorporated self-employed, as you might expect, legally incorporated their businesses, gaining tax incentives and personal asset protection. The BLS typically excludes them from analysis of self-employment because they’re considered employees of their own corporations.

The FRED graph above shows self-employment levels for both the incorporated (blue) and unincorporated (red), as well as total employment (green). The series are indexed to 100 in February 2020, right before the COVID-19 pandemic.

The incorporated and unincorporated self-employed have taken different paths over the past three years. The level of unincorporated self-employment has closely followed that of total employment and declined drastically in March and April 2020. But the level of incorporated self-employment changed little throughout this period. Unincorporated self-employment steadily recovered to pre-pandemic levels from April 2020 to July 2021, but incorporated self-employment declined more gradually to its trough in February 2021 before it began to recover.

There could be a few reasons why these groups look so different. The incorporated may have accepted PPP loans at a higher rate than the unincorporated if they were more attuned and accustomed to navigating government rules and regulations. Their businesses also tend to be more developed, potentially with more capital to keep themselves afloat. Their dip may have come later in the pandemic, after the relief dried up and the end-of-2020 COVID wave arrived.

Now, as both forms of self-employment rise above pre-pandemic levels, it’s unclear whether the trends in incorporated and unincorporated self-employment will once again diverge.

How this graph was created: Search FRED for “Employment Level Total Wage and Salary, Incorporated Self Employed.” Next, click the “Edit Graph” button and use the “Add Line” tab to add “Employment Level All Industries Self-Employed, Unincorporated.” Then, select “Add Line” once more and search for “Employment Level.” Click “Edit Line 1” and change “Units” to “Index: Scale value to 100 for chosen date.” Next, select “2020-02-01 Start” to the right of “U.S. Recession” as the date to equal 100 for your custom index and “Copy to all.” Finally, adjust the date range to begin at “2020-01-01.”

Suggested by Victoria Gregory and Elisabeth Harding.

The labor force is defined as the people who currently hold a job or are actively seeking a job. A person who is not employed and also is not looking to become employed isn’t considered part of the labor force.

When the pandemic hit in early 2020, businesses closed. A larger-than-usual portion of the labor force was suddenly without work. Some got other jobs, some kept looking, but millions left the labor force. This departure had a multitude of causes, such as early retirement, self-isolation due to the pandemic, taking care of loved ones, or frustration with an unsuccessful job search and continued access to increased federal unemployment benefits.

The FRED graph above shows that the number of people outside the labor force spiked in the spring of 2020. That number declined, as more workers re-entered the labor force over the next year, but the number is still well above what it was before the pandemic.

The red line in the graph is the 5-year trend line from January 2015 to January 2020, which we extended to the current time: More people are still outside the labor force than we would have expected, based on the trend leading up to the pandemic. In fact, there are 2.2 million more people outside the labor force than was expected, which can help explain the current tightness in the labor force.

How this graph was created: On FRED search for “not in labor force” and select the series. Set the start/end dates to January 2015 and 2020. Export the data by clicking “Download.” From your spreadsheet software, calculate a trend line from January 2015 to January 2020. Then go back to the FRED graph and click “Edit Graph.” From the “Add Line” tab, use the “Create user-defined line” to create the red line. Start the line in January 2015 with the value 93510 and end on the present day with a value of 97689. Finally, set the graph to display from 2014.

Suggested by Jack Fuller and Charles Gascon.

The FRED Blog uses graphs to help tell the story behind the data. But sometimes the FRED graphs themselves tell us there’s even more to the data than meets the eye. Today, we look at wealth data based on households interviewed in the Survey of Consumer Finances (SCF) and reported in the Distributional Financial Accounts (DFAs) from the Board of Governors of the Federal Reserve System.

The solid blue line in the FRED graph above shows the number of U.S. households in the wealthiest 0.1% of the population, with units on the left axis. The dashed red line shows the sum total of all the other U.S. households, with units on the right axis. Although the household count of the wealthiest households has increased between 1989 and 2022, it hasn’t done so steadily or continuously. And that caught our eye.

The number of households in the wealthiest 0.1% of the population is a proportion of the total number of households interviewed in the SCF and reported in the DFAs. So, when the total number of households increases, so does the number of households with the most wealth. That certainly seems to be the case between 1993 and 2020.

Of course, the same applies in reverse. Consider the first three quarters of 2020—the early stages of the COVID-19 recession. During that time, due to socioeconomic reasons, the overall number of households decreased. And so did the count of households in each of the five wealth groupings reported in the DFAs. That included the number of the wealthiest, the top 0.1%.

However, there was no such decrease in the overall number of households between 1989 and 1993, when the count of wealthiest households fell by 8.6%. So how can this be explained? The short answer is that it’s an artifact of using a survey (the SCF) to estimate the characteristics of a small group (the top 0.1% in the DFAs).

Not satisfied by the short answer and want to learn more? Read on!
The longer answer is that the overall sample size of the SCF was smaller in earlier years (the 1990s) than in later years (the 2000s). More importantly, the number of the wealthiest, the top 0.1%, interviewed in the survey was relatively smaller than it is in more recent surveys. This means that the DFAs report larger proportions of the wealthiest households in those earlier surveys.

When determining where the threshold lies for the top 0.1% of wealthiest households, the DFAs create the group by assigning a finite number of households from the SCF to the top 0.1%. The threshold will get as close to the top 0.1% as the data allow, but it will not necessarily match an individual household in the population. In that way, in 1989, the SCF threshold lies at 0.11% (too many households); and, in 1992, it lies at 0.09995% (too few households). That is why the DFAs show a declining number of households in the top 0.1% during the first several years of the survey.

Another way to put it is that small differences in proportions, when applied to populations of almost 100 million households, make for eye-catching patterns in reported numbers.

How this graph was created: Search FRED for “Household Count in the Top 0.1% (99.9th to 100th Wealth Percentiles).” On the resulting graph, click on “Edit Graph,” open the “Add Line” tab, and search for the same series again. For this line, then search for and add the other series, then apply formula a+b+c+d. Finally, in the “Format” tab, place the legend for the second line on the right side.

Suggested by Diego Mendez-Carbajo.