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The Unemployment Insurance Weekly Claims Report was released this morning for last week. The 348,000 new claims is decrease of 5,000 from an upward adjustment of 2,000 for the previous week. The less volatile and closely watched four-week moving average came in at 355,000, the 19th week below 400K after 31 consecutive weeks above that benchmark. Here is the official statement from the Department of Labor:
In the week ending March 17, the advance figure for seasonally adjusted initial claims was 348,000, a decrease of 5,000 from the previous week’s revised figure of 353,000. The 4-week moving average was 355,000, a decrease of 1,250 from the previous week’s revised average of 356,250.
The advance seasonally adjusted insured unemployment rate was 2.6 percent for the week ending March 10, a decrease of 0.1 percentage point from the prior week’s revised rate of 2.7 percent.
The advance number for seasonally adjusted insured unemployment during the week ending March 10 was 3,352,000, a decrease of 9,000 from the preceding week’s revised level of 3,361,000. The 4-week moving average was 3,385,750, a decrease of 13,000 from the preceding week’s revised average of 3,398,750.
Today’s seasonally adjusted number came in slightly below the Briefing.com consensus estimate of 355K.
As we can see, there’s a good bit of volatility in this indicator, which is why the 4-week moving average (shown in the callouts) is a more useful number than the weekly data.
Occasionally I see articles critical of seasonal adjustment, especially when the non-adjusted number better suits the author’s bias. But a comparison of these two charts clearly shows extreme volatility of the non-adjusted data, and the 4-week MA gives an indication of the recurring pattern of seasonal change in the second chart (note, for example, those regular January spikes).
Because of the extreme volatility of the non-adjusted weekly data, a 52-week moving average gives a better sense of the long-term trends. This metric has now fallen below 400,000 for the first time since late November 2008. I’ve now added a linear regression through the data. We can see that this metric has started to slip below the long-term trend stretching back to 1968.
The Bureau of Labor Statistics provides an overview on seasonal adjustment here (scroll down about half way down). For more specific insight into the adjustment method, check out the BLS Seasonal Adjustment Files and Documentation.
Doug Short Ph.d is the author of dshort.com.
To contact the reporter on this story: Doug Short at email@example.com
To contact the editor responsible for this story: Damien Hoffman at firstname.lastname@example.org
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