Here is the opening statement from the Department of Labor:

In the week ending October 1, the advance figure for seasonally adjusted initial claims was 219,000, an increase of 29,000 from the previous week's revised level. The previous week's level was revised down by 3,000 from 193,000 to 190,000. The 4-week moving average was 206,500, an increase of 250 from the previous week's revised average. The previous week's average was revised down by 750 from 207,000 to 206,250.

The advance seasonally adjusted insured unemployment rate was 1.0 percent for the week ending September 24, an increase of 0.1 percentage point from the previous week's revised rate. The previous week's rate was revised down by 0.1 from 1.0 to 0.9 percent. The advance number for seasonally adjusted insured unemployment during the week ending September 24 was 1,361,000, an increase of 15,000 from the previous week's revised level. The previous week's level was revised down by 1,000 from 1,347,000 to 1,346,000. The 4-week moving average was 1,370,750, a decrease of 10,250 from the previous week's revised average. The previous week's average was revised down by 250 from 1,381,250 to 1,381,000.

This morning's seasonally adjusted 219K new claims, up 29k from the previous week's revised figure, was worse than the Investing.com forecast of 203K.

Here is a close look at the data over the decade (with a callout for the past year), which gives a clearer sense of the overall trend.

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As we can see, there's a good bit of volatility in this indicator, which is why the 4-week moving average (the highlighted number) is a more useful number than the weekly data. Here is the complete data series.

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Here's a copy of the above chart, but zoomed in, so the COVID spike isn't as prominent.

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The headline Unemployment Insurance data is seasonally adjusted. What does the non-seasonally adjusted data look like? See the chart below, which clearly shows the extreme volatility of the non-adjusted data (the red dots). The 4-week MA gives an indication of the recurring pattern of seasonal change (note, for example, those regular January spikes).

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Because of the extreme volatility of the non-adjusted weekly data, we can add a 52-week moving average to give a better sense of the secular trends. The chart below also has a linear regression through the data.

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Here's a look at a sample of year's claims going back to 2009.

For an analysis of unemployment claims as a percent of the labor force, see this regularly updated piece The Civilian Labor Force, Unemployment Claims and the Business Cycle. Here is a snapshot from that analysis.

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