US Initial Jobless Claims 4-Week Average
US Initial Jobless Claims 4-Week Average stood at 198,500 persons on Oct 10, 2026, according to FRED (Federal Reserve Bank of St. Louis). It is one of the indicators in the Jobless claims table (Value · Daily), with a complete series running from Jan 1, 2000 to Oct 10, 2026. The complete series with an interactive chart, free to download.
This indicator in the Jobless claims table
| Indicator | 10-10-2026 | 03-10-2026 | 26-09-2026 | 19-09-2026 | 12-09-2026 | 05-09-2026 | 29-08-2026 | 22-08-2026 | 15-08-2026 | 08-08-2026 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Initial Claims - 4-Week Average | 198,500 | 198,250 | 200,500 | 202,500 | 204,000 | 206,250 | 207,500 | 205,750 | 204,250 | 199,750 | |
| Continued Claims - 4-Week Average | 1,708,750 | 1,710,500 | 1,723,250 | 1,742,250 | 1,757,000 | 1,776,750 | 1,780,750 | 1,786,750 | 1,788,250 | ||
| Insured Unemployment Rate | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 | 1.2 | 1.2 | 1.2 |
Understanding US Initial Jobless Claims 4-Week Average
The moving average of initial jobless claims takes observations from adjacent periods and calculates an average, thereby smoothing out short-term jumps caused by holidays, weather, or uneven processing. The underlying economic content remains the new flow of claims following employment disruptions, but each data point does not exclusively represent the specific period labeled on the chart. Unlike the unadjusted initial claims series, this metric is less sensitive to new news but provides a clearer picture of the underlying layoff trend.
One should read the direction and slope of the average line rather than searching for the cause of every individual point. Because the calculation windows overlap, consecutive observations share a large portion of the underlying data; a small change between two periods is therefore not independent evidence regarding the labor market. Year-over-year comparisons are appropriate when seeking to remove residual seasonality, while period-over-period comparisons should be used solely to identify whether a trend is accelerating or slowing. When the original data is revised, the averages for affected periods may also change accordingly.
Frequently asked questions
- Why does the moving average react more slowly than raw claims?
- Each point blends new observations with prior ones, meaning shocks only gradually feed into the full average.
- Is a single decline enough to confirm that layoffs have cooled?
- Not by itself. It is necessary to see whether the downward momentum persists as older observations roll out of the calculation window.
- Does the moving average fully eliminate seasonal factors?
- No. This calculation smooths short-term fluctuations but can still be influenced by hiring seasons and holiday schedules.