Federal Reserve Economic Data

How many government employees are there in the United States? At the time of this writing, there are a little less than 23 million public employees, distributed across the three levels of government: 14.9 million in local government (in green), 5.5 million in state government (in red), and 2.4 million in the federal government (in blue). The FRED graph above shows how these numbers have evolved.

What’s striking is that the federal government workforce has remained relatively flat over seven decades, while the lower levels show steady increases. Federal employment also has regular spikes, corresponding to temporary hires to conduct the decennial census.

Of course, over such a long period, the population of the United States would have increased considerably. So it probably makes more sense to look at the public workforce as a percentage of the population. This is what the second graph below does. Now we can see that federal public employment has been slowly declining since 1959, state employment stopped growing in the 1990s, and local employment stopped as well in the 2000s.

How these graphs were created: First graph: Look for the Current Employment Statistics (Establishment Data) releases and select Table B-1. Select the three series shown and add them to the graph. Second graph: Take the first, click on “Edit Graph,” add the population series, and apply formula a/b*100. Repeat for the two other lines.

Suggested by Christian Zimmermann.

Buckle up and come along on a joyful ride with FRED. Like a three-point turn, this post covers the average maturity of new and used car loans by making three maneuvers.

First, we define the terms. The maturity of a car loan is the target date for full repayment of the borrowed amount. It can be reported in years or months. A value-weighted maturity refers to assigning more importance to loans that are for a larger percentage of the vehicle’s value.

Second, we describe the data. The FRED graph above shows data from the Board of Governors of the Federal Reserve System on the value-weighted average maturity of car loans. Both the blue line tracking new cars and the green line tracking used cars reveal a rising trend since 2009. Also, the value-weighted average maturity of loans for used cars had been consistently lower than that for new cars. But since 2022, both weighted-maturity averages are effectively the same. What gives?

Third, we analyze the data. The rising average value-weighted maturity of loans for used cars can be the result of two different factors:

(a) Used car owners may be taking on loans with longer maturities and repayment schedules.

(b) They may be financing a rising proportion of the vehicle’s value, as high as that financed by new car owners.

Research by Robert Adams, Vitaly Bord, and Haja Sannoh suggests it’s b that’s driving the recent trend in these data.

How this graph was created: Search FRED for and select “Average Maturity of New Car Loans at Finance Companies, Amount of Finance Weighted.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Average Maturity of Used Car Loans at Finance Companies, Amount of Finance Weighted.”

Suggested by Diego Mendez-Carbajo.

Credit spreads are the difference between the performance of corporate-issued debt and the spot Treasury curve. Analysts look at these spreads to gain insight into the return investors get for owning riskier securities, as opposed to risk-free Treasury bonds. However, different segments of the corporate credit sector have different means and variance, which makes it difficult to compare the evolution of credit spreads over time and understand if financial conditions are tight or loose.

The FRED graph above allows us to compare spreads across different investment grade categories: The blue, red, green, purple, and teal lines are credit spreads from the whole US corporate, BBB, single-A, AA, and AAA indices, respectively.

The graph displays the z-scores of credit spreads from the end of 1996 to the present. These z-scores are the position of a raw variable in terms of its distance from the mean, measured in standard deviation units. Values below zero indicate a negative distance from a mean credit spread, indicating relatively small spreads. On the other hand, values above zero indicate relatively large spreads. Not surprisingly, there are spikes across all investment categories during recession periods (shaded in gray). These spikes indicate the relatively high risk of purchasing corporate debt at these points in time compared with the entire period.

Since the pandemic, credit spreads have narrowed, with indices below zero indicating levels beneath the historical average. Further, credit spreads are currently about half a standard deviation below the historical mean across all investment-grade categories. This suggests that financial conditions are loose.

How this graph was created: Search FRED for and select the following series IDs. For each new credit spread, click the “Edit Graph” then the “Add Line” option.

• BAMLC0A4CBBB
• BAMLC0A0CM
• BAMLC0A3CA
• BAMLC0A2CAA
• BAMLC0A1CAAA

Download the data and calculate the mean and standard deviation of each credit spread using your favorite tool. Go back to the graph in FRED and edit the formula for each line. Change each formula from a to (a-u/s) where u and s are the mean and standard deviations for a given credit spread, respectively.

Suggested by Anna Cole and Julian Kozlowski.