U6RATE: US U-6 Unemployment Rate Monthly Data from FRED (1994–2026)

The US U-6 Unemployment Rate is the broadest official measure of labor underutilization, monthly since 1994: the standard unemployed, plus people marginally attached to the labor force, plus those working part-time because they cannot find full-time work. It is the answer to “the real unemployment rate is higher”, quantified by the BLS itself. The range runs from 6.6% (December 2022, the series low) to 22.9% (April 2020); at 7.9% in mid-2026 against a headline U-3 of 4.2%, the gap between the two measures sits near its historical norm.

Dataset: US U-6 Unemployment Rate (1994–2026) · Updated 2026-09-01

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

Source: US Bureau of Labor Statistics, Current Population Survey · FRED series U6RATE

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns.

A value of 7.9 means 7.9% of the extended labor force was unemployed or underemployed by the broadest official definition.

Download the Complete Dataset

The full dataset is available in CSV and Excel formats.

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

FRED Direct CSV Access

The underlying data is available from FRED under series code U6RATE:

https://fred.stlouisfed.org/graph/fredgraph.csv?id=U6RATE

Direct CSV Access: Eco3min Structured Dataset

https://eco3min.fr/dataset/u6-unemployment-rate.csv

This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/u6-unemployment-rate.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(f"Latest U-6: {df['u6_rate'].iloc[-1]:.1f}%")
print(df.tail())

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/u6-unemployment-rate.csv"
df <- read_csv(url)

tail(df)
summary(df$u6_rate)

Both examples load the dataset directly from the URL, no download or API key required.

Methodology

U-6 is the widest of six official BLS underutilization measures (U-1 to U-6) from the Current Population Survey. Documentation: the BLS consumer price index databases. Numerator: unemployed persons + marginally attached (want work, available, searched within 12 months but not the last 4 weeks; includes discouraged workers) + employed part-time for economic reasons. Computed on the FRED U6RATE series. Denominator: civilian labor force plus the marginally attached.

Published monthly with the Employment Situation report, seasonally adjusted.

This dataset is updated daily (Mon–Sat, 08:00 UTC) via automated pull from the FRED API; new observations appear with each source release.

Data Quality & Provider Notes

• Release latency. First Friday after the reference month, with the jobs report.
• Revisions policy. Seasonal factors revise annually; January population-control updates create small level steps that are not economic signal.
• Survey basis. CPS household survey (~60,000 households), sampling error of roughly ±0.2pp on monthly changes.
• Definition scope. ‘Marginally attached’ requires recent search; people out of the labor force without recent search (caregiving, disability, retirement) are outside even U-6.
• Known gaps. None since inception, but the series begins in 1994, no official U-6 for earlier recessions.

Common Pitfalls When Using the U-6 Rate

1. Calling U-6 the ‘real’ unemployment rate. U-3 and U-6 measure different, equally official concepts; neither is truer. The informative statistic is usually their spread, not either level.
2. Comparing today’s U-6 to pre-1994 episodes. The measure did not exist before the 1994 CPS redesign; any 1982 or 1975 ‘equivalent’ is a reconstruction with different definitions.
3. Ignoring the part-time component’s size. Involuntary part-timers typically make up nearly half the U-6/U-3 gap; shifts in part-time work (scheduling practices, gig classification) move U-6 without changing joblessness.
4. Over-reading monthly moves. The components are small CPS subsamples; 0.1–0.2pp monthly changes are within sampling noise.

Historical Regimes

1994–2000: The long tightening. U-6 fell from ~11.8% to under 7% as the 1990s expansion converted part-timers and re-attached the marginal: the first demonstration of how much slack the broad measure holds late-cycle.

2001–2007: The jobless-recovery decade. U-6 rose past 10% after the dot-com bust and never fully retraced, ending the expansion near 8.4%: broad underemployment stayed sticky even as U-3 normalized.

2008–2010: The GFC blowout. U-6 peaked at 17.2% (late 2009) against a 10% headline: the seven-point spread that made ‘underemployment’ a household word.

2011–2019: The seven-year repair. The slowest slack absorption in the modern record: U-6 needed until 2017 to regain its pre-crisis level, finishing 2019 near 6.9%.

2020: The spike. 22.9% in April 2020: one in four extended-labor-force participants unemployed or underemployed at the trough.

2021–2026: Record low, then drift. U-6 hit its all-time low of 6.6% (December 2022) at peak tightness, then drifted to 7.9% by mid-2026: a normal spread over a 4.2% headline, slack rebuilding gradually rather than discontinuously.

Related Macroeconomic Datasets

U-6 extends the headline rate; the series below decompose the extension and its drivers.

Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Sources

• US Bureau of Labor Statistics: Alternative Measures of Labor Underutilization (CPS)
• Federal Reserve Bank of St. Louis: FRED series U6RATE

Dataset Reference