Federal Reserve Economic Data

The Americans with Disabilities Act (ADA) was signed into law 31 years ago. The FRED Blog has used data from the U.S. Bureau of Labor Statistics (BLS) to show that the fraction of people outside of the labor force because of disability is approximately constant. Today we revisit the general topic by looking at the percentage of people with a disability inside the labor force.

As a reminder, the civilian labor force is made up of workers who either (i) have a job or (ii) don’t have a job but are actively looking for one. And like it sounds, the civilian labor force doesn’t count those in the armed forces.

Our FRED graph above shows the percentage of workers with a disability who are in the labor force: Men are in green and women are in purple. The shares of these men and women are almost identical: 3.1%, or slightly more than 1 out of every 30 workers, on average. These shares declined slightly between 2009 (the first available data, at the end of the Great Recession) and 2014-2015. The shares increased modestly and unevenly up to 2019, the last year before the COVID-19-induced recession.

The available data cover only the period between two recessions, so we can’t separate the cyclical patterns from the long-term trend patterns in the data. But the BLS provides more detail about the distribution of employed persons with a disability across different types of jobs in this issue of The Economics Daily. And this 2018 working paper by current and former St. Louis Fed economists illuminates the roles of economic activity and the evolution of the labor force.

How this graph was created: Search for and select “Civilian Labor Force – With a Disability, 16 to 64 Years, Women.” From the “Edit Graph” panel, use the “Edit Line 1” tab to customize the data by searching for and selecting “Civilian Labor Force Level – Women.” Next, create a custom formula to combine the series by typing in a/b*100 and clicking “Apply.” Last, click on “Add Line” and repeat the same steps for men in the civilian labor force.

Suggested by Diego Mendez-Carbajo.

State and local governments receive two major sources of revenue: transfers from the federal government and their own tax receipts. Each of these series (since 1960) is plotted in the FRED graph above in billions of dollars at a seasonally adjusted annual rate. Both series trend upward over the past 70 years, as each has grown with the U.S. economy overall.

The graph shows the pandemic’s effect on the economy. First, the CARES Act, signed into law in March 2020, allocated hundreds of billions of dollars to state and local governments to fight the pandemic. The blue line spikes in the second quarter, with the surge in federal grants-in-aid to state and local governments, such as $150 billion through the Coronavirus Relief Fund. In the next two quarters, grants-in-aid remained above their long-run trend but fell from their very high level in April through June.

Second, there was concern that state and local tax revenues might be diminished by the pandemic. The graph shows an initial dip in tax revenue during the second quarter of 2020, but tax revenue largely recovered and ended 2020 at or slightly above its long-run trend.

Note that the most recent reported data end in December 2020. So, we don’t yet see the $350 billion in grants from the American Rescue Plan Act, which was passed in March of this year.

How this graph was created: Search FRED for “state and local government grants” and click on the relevant result. From the “Edit Graph” panel, use the “Add Line” tab to search for and select “state and local government current tax receipts.”

Suggested by Bill Dupor.

FRED just added a new family of data that can help us get a read on the U.S. economy.

The BBKI (Brave-Butters-Kelley Indexes) draw on about 500 indicators and search for some commonality among them, thanks to a technique called dynamic factor analysis. This analysis allows for an estimate of monthly GDP and decomposes it into different components. (GDP measures are typically quarterly, and this innovation is meant to be more timely.)

The graph above shows the monthly GDP estimate along with the coincident and leading indicators for a period spanning the past two recessions. Clearly, the leading indicator was able to accurately determine the direction of the changes in this current and strange recession. Anticipating the turning points, of course, is very difficult in forecasting.

The graph below shows a decomposition of the monthly GDP indicator into various components:

1. a trend, which varies very little through time
2. a leading component—that is, which current data will influence future GDP
3. a lagging component that was largely determined from the previous period
4. a cycle component—that is, a deviation from the trend that has some persistence
5. and an irregular component of random events and one-offs with no persistence.

As with many graphs lately, things are a little bit difficult to distinguish because of the scale of the data in our current environment. So let’s concentrate on the past year. The graph below shows that the large swings in 2020 were due to different components. The large downturn was due to the cyclical and irregular components, but the large upswing was mostly irregular, which then swings back down. This back and forth isn’t cyclical, at least not at the frequency that economists typically think a business cycle should last (2 to 8 years). And indeed, these wide swings didn’t have any economic fundamentals; they were tied to the evolution of health-related concerns.

How these graphs were created: Start from the BBKI release table, check the series you want displayed, and click “Add to Graph.” Adjust the time period to taste.

Suggested by Christian Zimmermann.