Federal Reserve Economic Data

The consumer price index (CPI) is calculated by looking at the cost of a market basket of consumer goods and services purchased by an average urban consumer. During the past two years, overall CPI inflation has increased and decreased, in part because of supply and demand shocks to the prices of individual goods and services, such as eggs and shelter. These specific shocks make it difficult to identify trends in broad inflation. But alternative price indexes can help measure the “core” of inflation.

The FRED graph above shows the all-items CPI inflation rate (dashed red line), reported by the U.S. Bureau of Labor Statistics, plus two special aggregations of consumer prices:

• The “all items less food and energy” CPI inflation (green line) is also reported by the BLS; it excludes the prices of food and energy, two components of the all-items CPI that are frequently the most volatile.
• The “sticky price” CPI inflation (blue line) is reported by the Federal Reserve Bank of Atlanta, which sorts the components of the all-items CPI and categorizes them as either “flexible” or “sticky” (slow to change).

Between January 2013 and January 2023, both of these special aggregations of consumer prices have signaled very similar core inflation rates; but their lockstep movement broke down during the COVID-19-induced recession in 2020. Since then, “all items less food and energy” CPI inflation has been noticeably more volatile than “sticky price” CPI inflation. This dynamic suggests a broader range of price categories has experienced notable and unexpected changes.

Stick to the FRED Blog and learn more about core inflation. A post on the topic was recently referenced in the Federal Register, the daily journal of the United States government, as part of a proposed rule.

How this graph was created: Search FRED for “Sticky Price Consumer Price Index.” Next, click the “Edit Graph” button, select the “Add Line,” and search for “Consumer Price Index for All Urban Consumers: All Items in U.S. City Average.” Next, select the “Line 2” tab and use the “Units” dropdown menu to select “Percent Change from Year Ago.” Repeat the “Add Line” step to add the “Consumer Price Index for All Urban Consumers: All Items Less Food and Energy in U.S. City Average” series to the graph and calculate their year-over-year percent growth rate.

Suggested by Diego Mendez-Carbajo.

Layoffs in the technology sector dominated the news cycle in the second half of 2022, and the trend seems to be continuing into 2023: In January, Google and Microsoft announced another 12,000 and 10,000 layoffs, respectively. So, are these layoffs in or out of proportion with the labor market in general?

FRED has employment data specific to the Information industry. While this industry doesn’t exclusively represent the tech sector, it does include sectors where computer programmers, computer support specialists, computer systems analysts, and software developers are likely to work. These sub-industries are publishing, internet broadcasting, telecommunications, and—most relevant for this post—data processing, hosting, and related services.

The FRED graph above shows layoff levels for workers in the Information industry (in red) and for all nonfarm workers (in blue), indexed to 100 in April 2022. In that month, layoffs were at “normal” levels for both industries. This transformation enables us to see whether layoffs in Information have been increasing and, if so, whether they’ve increased more sharply relative to layoffs overall.

The graph shows that Information layoffs and layoffs overall had increased by similar percentages in May. But Information layoffs have gone up by more since then and remain more elevated. This pattern became more pronounced at the end of 2022: The last available month of data is December 2022, when Information layoffs were up by 65.5% compared with an increase of 26% for layoffs overall. Recent layoff announcements have continued into 2023, so we’ll look at the January 2023 data to compare with 2022 data.

How this graph was created: Search FRED for “Layoffs and Discharges: Total Nonfarm” and select “Monthly, Level in Thousands, Not Seasonally Adjusted” from the options. Next, click the “Edit Graph” button and use the “Add Line” tab to add “Layoffs and Discharges: Information.” Select “Edit Line 1” and change “Units” to “Index (Scale value to 100 for chosen date).” Next, select “2022-04-01” as the date to equal 100 for your custom index and “Copy to all.” Finally, enter “2022-04-01” to “2022-12-01” above the figure on the right to adjust the time period.

Suggested by Victoria Gregory and Elizabeth Harding.

US employment has largely returned to pre-pandemic levels since the COVID-related disruptions. But this recovery hasn’t been even across the labor market. So we use FRED* to illustrate the recovery in employment according to establishment size: 1-19, 20-49, 50-249, 250-499, and 500+ employees.

Before the pandemic, employment across all establishment sizes had been slowly increasing. Predictably, employment dropped in March 2020 for all size categories.

• For the smallest establishments (1-19 employees), employment dropped the least and recovered the fastest; however, employment in these establishments has fallen slightly since the end of 2021.
• For establishments with 20-49 employees, 250 to 499 employees, and 500+ employees, employment has followed a similar pattern, increasing above employment levels from 2020.
• For mid-range establishments with 50 to 249 employees, employment dropped the most and recovered the slowest.

Employment across all establishment sizes is now above the levels in January 2020. And while the initial drop in employment came from COVID-19 for all establishments, it is unclear why the various drops and recoveries have been so uneven across establishment sizes. One possible explanation is the agility of smaller firms and the deeper resources of large firms. The smallest establishments could remain at work or go back to work faster due to lower risk of exposure to COVID given a smaller number of employees. The largest establishments also have the resources to establish COVID procedures and testing to help employees get back to work.

The mid-range establishments may have struggled more than other size groups because their number of employees was too large to return without rigorous prevention measures and too small to have the resources to fight for and secure scarce COVID-19 tests. Business applications for new firms have increased, and new firms tend to be small. This could also explain why small firms saw the smallest decline and fastest recovery.

*Notes about the data: The data set is from Automatic Data Processing Inc. (ADP), which defines an establishment as a single physical location engaged predominantly in one activity and covers US nonfarm private employment. To focus on the employment patterns before and after the pandemic, we index the employment level to January 2020 (right before the pandemic) and graph the data from 2018 to the latest observation available.

How this graph was created: Search FRED for “Small Establishments” and select “Nonfarm Private Employment in Small Establishments with 1 to 19 Employees.” Select the orange “Edit Graph” button to get to the “Add Line” section, where you’ll search for “Small Establishment” in the search bar and select the series “Nonfarm Private Employment in Small Establishments with 20-49 Employees.” Repeat for “Medium Establishments” and “Large Establishments.” Use “Edit Line 1” to change the units to “Index (Scale value to 100 for chosen date),” which is “2020-01-01,” and select “Copy to all.” Finally, change the start date of the graph to 2018-01-01.

Suggested by Maggie Isaacson and Hannah Rubinton.