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Pandemic-related initial claims for unemployment assistance

FRED now offers data on pandemic-related initial claims for unemployment assistance. An initial claim is filed by an employee with the state employment agency after losing her/his job. A pandemic-related initial claim is filed by an employee covered under the expanded eligibility criteria specific to the pandemic.

The Pandemic Unemployment Assistance (PUA) program is funded through the Coronavirus Aid, Relief, and Economic Security (CARES) Act, which temporarily expanded unemployment insurance eligibility to workers not usually eligible for regular unemployment compensation or extended benefits: e.g., self-employed workers, freelancers, independent contractors, and part-time workers impacted by the pandemic.

The number of these claims varies dramatically from week to week and from state to state. Here, the data show percent changes from November 14, 2020, to November 21, 2020. The dark red indicates a state where the number of these initial claims increased in that week, and the light red indicates a state where the number remained constant or decreased.

For these dates, the PAU-related initial claims grew by 646% in Maine, remained unchanged in Mississippi, and fell to zero in Minnesota.

How this map was created: From GeoFRED, click on “Build new map” (green button, northeast corner of the screen) and then click on “Tools” (orange cogwheel button, northwest corner). Under “Region” select “State,” under “Data” select “Pandemic Unemployment Assistance Initial Claims,” under “Units” select “Percent Change,” and under “Date” select 2020-11-21. Next, click on “Edit Legend” and under “Number of color cases” select 2. Last, enter “0” on the topmost box and choose colors to taste.

Suggested by Diego Mendez-Carbajo and Maria Arias.

In mid-2020, the least wealthy gained the most net worth

The FRED Blog has discussed how the onset of the COVID-19 pandemic reduced the net worth of households. To recap: Your net worth is the difference between the value of your assets and the value of your liabilities. When the value of your assets decreases while the value of your liabilities stays constant, your net worth becomes smaller.

The ALFRED graph above shows that the largest reduction in household net worth during the first quarter of 2020 occurred for the wealthiest 1% of households. The high volatility of financial markets during that period and the differences in the distribution of total assets across different classes of households can help explain that.*

The same ALFRED graph also shows that, during the second quarter of 2020, household net worth increased all around, this time with the largest gains among the bottom 50% of households.

Given the large reduction in economic activity recorded during that time, this rebound is remarkable. Faster growth in home prices and the large accumulation of real estate assets among the least wealthy can help explain this gain in net worth. Also, much of the gains in asset values comes from expectations of higher future incomes, which may not correlate with current income nowadays.

*This post shows an ALFRED graph to display the data available at the time of writing. For the latest data, see this graph.

How this graph was created: From FRED’s main page, browse data by “Release.” Search for “Distributional Financial Accounts” and click on “Levels of Wealth by Wealth Percentile Groups.” From the table, select the “Total Net Worth” series held by each of the four wealth quantiles and click “Add to Graph.” Use “Edit Line 1” to change the graph units by selecting “Units: Percent change” and clicking “Copy to All.” Last, edit the graph “Format” by selecting “Graph type: Bars” and choosing colors to taste.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: WFRBLB50107, WFRBLN09053, WFRBLN40080, WFRBLT01026

How staying at home in 2020 affected the transportation industry: Part 3

Debt as a life raft

We covered transportation equipment in Part 1 of this series and petroleum and coal products in Part 2 [[ ]]. Census Bureau data show that, as their incomes dropped, companies in these industries took out new, long-term debt. And that’s what we discuss here, in Part 3.

The FRED graph above shows “Long-Term Debt Due in More Than 1 Year: Other Long-Term Loans” data for both the transportation equipment manufacturing and petroleum and coal products manufacturing industries. And the graph lets us compare these industries’ debt levels now with their levels during the Great Recession of 2008-2009.

In the second quarter of 2020, transportation equipment manufacturers increased long-term debt by $30.8 billion, up from $250.2 billion in the first quarter of 2020. Petroleum and coal products also increased their debt, by $35.5 billion.

During the Great Recession, petroleum and coal products increased their debt for consecutive quarters, so their tactic of increasing debt now isn’t historic in itself—although, the amount of their debt is at an all-time high.

Transportation equipment manufacturers were able to decrease their debt load for consecutive quarters. So their significant increase in debt now helps illustrate the difference between the disruptions from the Great Recession and those from COVID-19. For example, during the Great Recession, many Americans still drove to work, sent their kids to school, and took vacations. In 2020, those activities came to a standstill.

The Quarterly Financial Report also shows that the current debt carried by transportation equipment manufacturers peaked in the second quarter but decreased in the third quarter by $10.1 billion…

Read on for more detail and calculations from the Census Bureau’s QFR

These long-term debt increases during the first and second quarters of 2020 also caused an interesting shift in each industry’s debt leverage. Petroleum and coal products reported a long-term debt to total assets ratio ((Long-term Debt, Due in More than 1 Year, From Bank Loans + Long-term Debt, Due in More than 1 Year, Other Long-term Loans)/Total Assets) of 21.54%, an increase of 6.89% from the one reported in the second quarter of 2019. The transportation equipment manufacturing industry reported a long-term debt to total assets ratio of 24.20%, an increase of 5.65 % from the same period in 2019. Along with an increase in long-term debt, several companies shifted assets toward higher amounts of cash. In the second quarter alone, transportation equipment manufacturing reported a total cash, U.S. government and other securities to total assets ratio of 10.93%. This is an increase of 5.19% from the same period in 2019. Transportation equipment manufacturing companies slowed down their borrowing in third quarter of 2020 and decreased their long-term debt to total assets ratio to 22.32%. In the third quarter of 2020, petroleum and coal products companies continued to float operations with debt, increasing long-term debt due in more than 1 year, thereby increasing their long-term debt to total assets ratio by 0.35%, increasing their long-term debt to total assets ratios.

About the U.S. Census Bureau: The U.S. Census Bureau collects data from thousands of companies to create monthly, quarterly, and annual reports for U.S. policymakers. These reports are free to the public and provide critical insight into the U.S. economy. To view all the Census Bureau economic indicator reports, visit the Briefing Room.

How this graph was created: Search for and select “Quarterly Financial Report: U.S. Corporations: Transportation Equipment: Long-Term Debt, Due in More Than 1 Year: Other Long-Term Loans, Millions of Dollars, Not Seasonally Adjusted.” From the “Edit Graph” panel, use the “Edit Line 1” tab to confirm these data fields if necessary: “Units: Millions of Dollars” and “Modify frequency: Quarterly.” Next, use the “Add Line” tab to search for the FRED series ID “QFRD319324USNO” and click on “Add data series.” To change the line colors, use the choices in the “Format” tab.

Suggested by Brooks Hurry and John Darr from the U.S. Census Bureau.

View on FRED, series used in this post: QFRD319324USNO, QFRD319TRAUSNO


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