Federal Reserve Economic Data

The World Bank has many data series that allow comparisons among countries over time, and today’s FRED graph reveals some trends in life expectancy and national income.

Lower life expectancy in low-income countries has been catching up. In 1982, life expectancy at birth in low-income countries was about 66% of what it was in high-income countries. Then life expectancy increased at a faster pace in low-income countries, and the value rose to 78% by 2018. This rising longevity, especially in relation to longevity in high-income countries, is remarkable because it doesn’t coincide with an improvement in relative economic performance.

In 1982, real GDP per capita in poor countries was 2.8% of what it was in rich countries. In 2018, it was 1.8%. Despite poor countries losing ground to rich countries on the economic front (GDP per capita), they gained ground on the health front (life expectancy at birth).

For more information, read on… Countries in this analysis are classified as low income or high income depending on their 2019 gross national product per capita. And countries aren’t always in the same group from one year to the next, of course.

1. This variability doesn’t affect the conclusion here that there’s a disconnect between economic performances and life expectancy.
2. This general conclusion from the FRED graph also holds for individual countries. For example, life expectancy in Benin grew from 63% of life expectancy in the U.S. in 1980 to 70% in 2018. But Benin’s GDP per capita remained below 1% of U.S. GDP per capita for that period.
3. Finally, the statistical correlation of life expectancy and GDP per capita across individual countries has been steadily declining since the 1960s, shown in the graph below. The FRED graph above is a manifestation of this decline.

How this graph was made: Search for and select “Life Expectancy at Birth, Total for Low income Countries.” From the “Edit Graph” panel, use the “Customize data” search field to search for and add the series “Life Expectancy at Birth, Total for High Income Countries” to the same line. In the formula bar, type a/b*100. Next, under the “Add Line” tab, search for and add “Constant GDP per capita for Low Income Countries” and “Constant GDP per capita for High Income Countries.” In the formula bar, type a/b*100.

Suggested by Guillaume Vandenbroucke.

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.