Weekly Unemployment Claims: Up 9K, Better Than Forecast

Here is the opening statement from the Department of Labor:

SEASONALLY ADJUSTED DATA

In the week ending February 27, the advance figure for seasonally adjusted initial claims was 745,000, an increase of 9,000 from the previous week's revised level. The previous week's level was revised up by 6,000 from 730,000 to 736,000. The 4-week moving average was 790,750, a decrease of 16,750 from the previous week's revised average. The previous week's average was revised down by 250 from 807,750 to 807,500.

The advance seasonally adjusted insured unemployment rate was 3.0 percent for the week ending February 20, a decrease of 0.1 percentage point from the previous week's unrevised rate. The advance number for seasonally adjusted insured unemployment during the week ending February 20 was 4,295,000, a decrease of 124,000 from the previous week's unrevised level of 4,419,000. The 4-week moving average was 4,448,000, a decrease of 99,000 from the previous week's unrevised average of 4,547,000. [See full report]

This morning's seasonally adjusted 745K new claims, up 9K from the previous week's upwardly revised figure, was better than the Investing.com forecast of 750K.

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.

Unemployment Claims since 2007

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.

Unemployment Claims

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).

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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