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Women’s employment and child care services during the pandemic

During the COVID-19 pandemic in the United States, it was mainly women who took on the significant demands of childcare and housework, causing a sharp drop in their labor force participation rate: From February 2020 to April 2020, an estimated 7,000,000 women between 25 and 54 years of age decided to forgo employment. There’s evidence to suggest this mass exodus of women from the labor force was due to school closures and lack of child care.

In this FRED Blog post, we examine the employment levels for women 25-54 years of age and for men 25-54 years of age as well as the number of childcare job postings compiled on Indeed.com in early 2021, after the US economy had moved out of the COVID-19-related recession.

The FRED graph above shows that growth in women’s employment was stronger than (and surpassed) growth in men’s employment as of April 2021. There’s also a correlation between the growth of childcare job postings and the growth of these employment levels: As women returned to work after the COVID recession, the number of childcare requests rose.

One possible explanation for the higher employment growth rate for women is that the US government made childcare more affordable. In early 2021, we can see a disproportionate increase in the percent change of childcare postings. The American Rescue Plan Act was enacted in March 2021 and contained a childcare tax credit that would help pay for the care of eligible children and other dependents. After the Act was enacted, we see a huge spike in the following months of April and May, indicating an increased demand for childcare, possibly to take advantage of this tax credit.

How this graph was created: From FRED, search for and select “Employment Level – 25-54 Yrs., Women.” From the “Edit Graph” panel, modify the frequency to monthly and change the units to display the percent change from a year ago. From the “Add Line” tab, search for and select “Employment Level – 25-54 Yrs., Men,” modify the frequency to monthly, and change the units to display the percent change from a year ago. Add the third line: “Childcare Job Postings on Indeed in the United States,” modify the frequency to monthly, and change the units to display the percent change from a year ago. From the “Format” tab, switch the axis of the childcare job postings to the right. Finally, edit the time window so it shows from January 1, 2021, to June 1, 2021.

Suggested by Alexander Bick and Kevin Bloodworth.

Three measures of US credit card debt

Is it troublesome that credit card debt has topped $1 trillion?

In 2023, outstanding credit card balances in the United States surpassed $1 trillion for the first time. This milestone has raised concerns about the health of household finances and the implications for consumer spending going forward.

The FRED graph above shows three measures of credit card debt, with all balances normalized to 100 in the first quarter of 2011 to better illustrate longer-run trends: The blue line shows the balances, the green line shows the balances adjusted for inflation, and the red line shows the balances as a percentage of disposable income.

The blue line shows the growth in balances on credit cards and other forms of revolving credit issued by US commercial banks since 2011. In 2023 Q3, balances were 18.2% higher than at the start of the recession in 2020 Q1 and 34.8% higher than the post-recession low in 2021 Q1.

This growth in credit card balances since 2021 has occurred alongside substantial inflation. Measured by the consumer price index (CPI), inflation reached a peak annual rate of 8.9% in June 2022. In total, the CPI rose 20% between May 2020 and October 2023, which is close to the growth in total credit card balances over this period. What do we see if we look at “real” balances—that is, nominal balances divided by the CPI? As the green line shows, in 2023 Q3, “real” credit card balances were essentially equal to their level in 2020 Q1.

Are these higher balances putting increased pressure on household finances? That depends on several factors, including the growth in other types of household debt, interest rates, and disposable income. Between 2020 Q1 and 2023 Q3, nominal personal disposable income rose by more than nominal credit card balances. As the red line shows, relative to disposable income, credit card balances were actually slightly smaller in 2023 Q3 than they had been in 2020 Q1. Of course, interest rates have risen substantially over this period, so the cost of carrying a balance has increased.

This isn’t a full analysis of the state of household balance sheets, but the growth in outstanding credit card balances does seem less alarming when compared with the growth in household income over the same period. For more insights on this topic, check on US credit scores and credit use rates.

About the data: These data don’t include balances on credit cards issued by non-bank entities, but credit card debt is mainly held by banks, so this measure is pretty solid. Also, by convention, FRED graphs show quarterly data as occurring in the first month of a quarter. So the peak in credit card balances shows as occurring in January 2020, or one month before the beginning of the recession. However, based on weekly data, the peak in credit card balances occurred during the first week of March.

How these graphs were created: Search FRED for and select “Consumer Loans: Credit Cards and Other Revolving Plans, All Commercial Banks.” From the graph, click on “Edit Graph” and open the “Add Line” tab, then search for and select “Disposable Personal Income” and “Consumer Price Index for All Urban Consumers, All Items in U.S. City Average.” For the latter two lines, add the Consumer Loans series under the “Customize data” section and set the formula to 100*(b/a) by clicking “Apply.” For all three lines, set the units to “Index (Scale value to 100 for chosen date),” enter the date “2011-01-01,” and set the frequency to “Quarterly.” Set the earliest date in the window to “2011-01-01.”

Suggested by David Wheelock.

The pandemic made calculating national income even more difficult

Archival FRED tracks the data revision process

There are three ways to measure GDP:

  • The expenditure approach adds private and public consumption, investment, and the trade balance. It’s the famous Y=C+I+G+X-M.
  • The income approach principally counts labor income and profits.
  • The product approach adds up each step of production.

All three measurements should add up to the same number. But, for various reasons detailed in this blog post, there’s always a small difference, called a “statistical discrepancy.” The ALFRED graph above shows this discrepancy as the proportional difference between GDP and national income. For the period just before and during the recent pandemic, that discrepancy went as high as 3%, for the first quarter of 2022.

Compare that graph with our second graph, which covers a more “normal” period. Here, the largest discrepancy is only 1.3%.

ALFRED’s job is to track “vintages” of data: In these graphs, the vintages are the values assigned to quarterly GDP. Those values for each given quarter were revised over time as more (and/or more-precise) information was collected.

During the “normal” period shown in the second graph, these revisions are minor compared with the revisions during the pandemic, shown in the first graph. This comparison highlights how difficult it was to compute the initial estimates of GDP and national income during the pandemic. Later vintages of the quarterly data had more typical discrepancies. This observation tells us that the BEA was able to adapt to the challenges of the pandemic quite rapidly and maintain the high level of accuracy in their data collection process.

How these graphs were created: Go to ALFRED, search for (nominal) GDP, click “Edit Graph,” search for (nominal) “national income,” and apply formula a/b-1. Finally, play with vintage dates and sample periods to obtain the two graphs.

Suggested by Christian Zimmermann.



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