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The FRED® Blog

A closer look at labor in the U.S.

BLS state-level labor force participation rates

The U.S. Bureau of Labor Statistics collects all kinds of data on the labor force, employed persons, unemployed persons, and unemployment rates. FRED now offers the BLS’s labor force participation rates for the individual 50 states and the District of Columbia. With this new addition to FRED, we can easily track a state’s labor force participation rate over time and compare performance across states.

By the way, the labor force participation rate is the number of all employed and unemployed workers as a percentage of the total population. By “unemployed,” we mean those actively seeking employment; and by “total population,” we mean the civilian noninstitutional population 16 years and older.

The first graph shows labor force participation rates for each state of the Eighth District (the region served by the St. Louis Fed) plus the rate for the U.S. overall since January 1976. In February, the national rate was 63.2%, its highest level since September 2013. Three states in the District had higher participation rates in February than the national average: Indiana (65.2%), Illinois (64.6%), and Missouri (63.6%). Mississippi (55.4%), Arkansas (57.9%), Kentucky (59.0%), and Tennessee (61.0%) had rates below the national average. While peer comparisons are important, it’s also valuable to consider performance over time.

The second graph shows District state performance for the past year—that is, the year-over-year change in the labor force participation rate for each month. The year-over-year participation rate for the nation has improved for the past six consecutive months. Indiana shows the strongest and most consistent improvement in labor force participation, with a year-over-year increase in each month. In contrast, Missouri and Mississippi have declining participation rates, with negative changes each month. Arkansas also has had mostly negative changes each month, but in March had its first year-over-year increase since January 2018.

How these graphs were created: For the first graph, search for “Civilian Labor Force Participation Rate” and click “Add to Graph.” From the “Edit Graph” menu, use the “Add Line” tab to find seasonally adjusted state-level labor force participation rates (aka “LBSSA” in FRED). Add the corresponding series for each state: Arkansas (LBSSA05), Illinois (LBSSA17), Indiana (LBSSA18), Kentucky (LBSSA21), Mississippi (LBSSA28), Missouri (LBSSA29), and Tennessee (LBSSA47). For the second graph, take the first and use the “Format” tab to select “Bar” as the “Graph Type.” From the “Edit Line” tab, select “Change from Year Ago, Percent” for “Units.” Select “Copy to All.” Finally, select “1Y” in the options listed just above the graph to adjust the x-axis. The 102 state-level labor force participation rates (seasonally adjusted and non-adjusted series for the 50 states plus D.C.) can all be found in the corresponding release table.

Suggested by Kathryn Bokun and Kevin Kliesen.

View on FRED, series used in this post: CIVPART, LBSSA05, LBSSA17, LBSSA18, LBSSA21, LBSSA28, LBSSA29, LBSSA47

U.S. labor before FRED was born

A happy-birthday backward glance at 1991

Today, FRED celebrates its 28th birthday. On this happy occasion, the whole family (FRED, ALFRED, GeoFRED, and the little one, FREDcast) are gathering to read the 2018 Annual Report of the Federal Reserve Bank of St. Louis, much of which is dedicated to FRED.

Let’s look back at the U.S. economy before the birth of FRED (on April 18, 1991) and compare it with the economy of today. The graph above shows the unemployed according to the length of their unemployment spell: We can see there are many more long-term unemployed today. The second graph, which uses a dataset first released right after FRED was born, shows that the U.S. labor force has also become more educated.

We can’t offer our readers any cake, but we do have pie…charts. The two charts below compare men and women in the labor force and show that the share of women has increased a bit in the past 28 years. The change may not be obvious until you hover over the chart to verify it.

How these graphs were created: Start from the Current Population Survey, navigate to the release table you’re interested in, check the series you want displayed, and click “Add to Graph.” For the first two graphs, use the “Edit Graph” panel’s “Format” tab and select graph type “Area” with “Percent” stacked. Adjust the start date for the first graph. For the pie charts, chose graph type “Pie” and adjust the dates.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: LNS11000025, LNS11000026, LNS12027659, LNS12027660, LNS12027662, LNS12027689, UEMP15T26, UEMP27OV, UEMP5TO14, UEMPLT5

Is the rent too high?

Way more than 525,600 minutes of rent data

If you’re a renter and have been complaining that your rent keeps rising, the statistics seem to back you up. In the graph, the purple line shows the evolution of rents in the U.S. as a whole, while the light blue line shows the general price level (CPI). Clearly, rents are increasing faster than prices overall. Of course, location matters for anything related to housing, and there are large regional differences: Rents in the New York and San Francisco areas have clearly appreciated more than average. Rents in the Detroit area have increased but well below the average rate; still, they’re keeping up with general inflation.

Note, however, that the graph shows the evolution of rents, but not their level. It shouldn’t be too surprising that rents in 1984 (the beginning of this sample) were higher in New York and San Francisco than in Detroit. And that gap has increased even more over time.

How this graph was created: Search for “rent CPI CBSA” (which stands for core-based statistical area, a metropolitan area defined around a core) and select the area you want shown. We selected semi-annual data instead of monthly, as these data are not collected every month. Click on “Add to Graph.” Add the remaining two series the usual way: From the “Edit Graph” panel, open the “Add Line” tab, search for “rent CPI” and add it, then search for “CPI” and add it. The last step is to limit the sample period to start on 1984-01-01.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CPIAUCSL, CUUR0000SEHA, CUUSA101SEHA, CUUSA208SEHA, CUUSA422SEHA


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