The number of jobs openings is one of the main economic indicators that economists consider when trying to evaluate the health of the economy. The FRED graph above shows job openings data since 2000: There’s been an upward trend from 2010 all the way to February 2020. Job openings dropped during the pandemic but picked up and increased significantly from late 2020 through 2022.

The way these data are collected reflects how the world has evolved over time: From 1951 to 2008, the Conference Board produced a Help-Wanted Advertising Index of print advertisements that measured the change in help-wanted classified ads from 51 major US newspapers. This index was arguably one of the most important at the time, as it helped economists measure the efficiency of the job-matching process. However, as the world moves from print to digital media and the loss in newspaper readership continues, data-collection methods also must change.

Nowadays, the job openings data come from “JOLTS,” which is the Job Openings and Labor Turnover Survey conducted by the Bureau of Labor Statistics. The data are from a sample of around 21,000 US business establishments, and job openings include all positions that are open on the last business day of the reference month.

For a job to be considered “open,” it has to meet three conditions. One of them is that the employer must be actively recruiting workers from outside the establishment to fill the position. According to the BLS website, this may involve “advertising in newspapers, on television, or on radio; posting Internet notices; posting “help wanted” signs; networking with colleagues or making “word of mouth” announcements.”

How this graph was created: Search for “job openings” on FRED and the series should be among the top choices.

Suggested by Praew Grittayaphong and Paulina Restrepo-Echavarria.

The FRED Blog has discussed why measuring inflation trends is important for policy analysis. In a nutshell: The month-to-month inflation rate changes too often and by too much to reliably inform financial decisions. To address this challenge, researchers use different methods to study the difference between temporary and persistent changes in consumer prices.

The FRED graph above shows consumer price inflation (the black dashed line). It also shows two versions of the underlying inflation gauge (UIG), a recently added data series measuring the trend component—that is, the persistent component—of inflation. The series is produced by economists at the Federal Reserve Bank of New York. They use consumer price index data from the US Bureau of Labor Statistics (BLS) and a dynamic factor model, a technique that helps identify the shared features of large sets of economic data, to construct the two trend estimates:

• The full data set measure (the blue line) combines many of the BLS price data series with several macroeconomic and financial variables.
• The prices-only measure (the red line) solely employs BLS price data.

The graph shows the trend estimates are less volatile than the month-to-month inflation rates. Also, the data suggest the June 2022 peak in inflation had a large transitory component and the upward persistent trend reversed course soon afterward.

For more information about various inflation measures, check this short video of Mark Wright or read on about other series in FRED:

• The Bureau of Labor Statistics reports a consumer price index commonly known as “core CPI” that excludes the prices of two historically volatile prices: food and energy. Learn more about core CPI here.
• The Federal Reserve Bank of Cleveland reports the trimmed mean of the CPI by excluding the price components that show the most extreme monthly changes. Learn more about trimmed means here.
• The Federal Reserve Bank of Atlanta reports a sticky price CPI after sorting the components of the CPI into “flexible” or “sticky” (slow to change) categories. Learn more about the sticky CPI here.
• The Federal Reserve Bank of Dallas reports a trimmed mean personal consumption expenditures (PCE) by excluding the price components that show the most extreme monthly changes from the inflation measure targeted by the Federal Open Market Committee of the Federal Reserve. Learn more about trimmed means here.

How this graph was created: Search FRED for “Underlying Inflation Gauge: Full Data Set Measure.” Next, click the “Edit Graph” button, select the “Add Line,” and search for “Underlying Inflation Gauge: Prices-Only Measure.” Do that again to add the “Consumer Price Index for All Urban Consumers: All Items in U.S. City Average.” Last, select the “Line 3” tab, and use the “Units” dropdown menu to select “Percent Change from Year Ago” to transform the index series into the inflation rate.

Suggested by Diego Mendez-Carbajo.

The labor market has experienced both large and small shocks over the past three years. But in many ways, the employment situation has returned to pre-2020 conditions. Today we discuss one way it has not.

The FRED graph above shows the proportion in the overall labor force of men with a disability (in green) and women with a disability (in purple). At the time of this writing, these BLS data are available between the third quarter of 2008 and the first quarter of 2023. We see a clear, marked increase in the proportion of both men and women with a disability in the labor force after the first quarter of 2021.

Our post connects to a recent post from the US Department of Labor: Authors Joelle Gamble and Megan Dunn-Paul highlight increases in (i) flexibility in work schedules and (ii) opportunities to work remotely as potential explanations for the remarkable change in labor market trends for workers with a disability. You can find the data they used here.

Will this trend persist, increase, reverse? We don’t know that, but we do know FRED will keep updating the data. Check back in July to mark the 33rd anniversary of the signing of the Americans with Disabilities Act (ADA) into law.

How this graph was created: Search FRED 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