New Jobless Claims Plunge To 300K, Much Better Than Forecast

The Unemployment Insurance Weekly Claims Reportwas released this morning for last week. The 300,000 new claims number was a dramatic decline of 32,000 from the previous week’s 332,000 (revised from 326,000). The less volatile and closely watched four-week moving average, which is usually a better indicator of the trend, fell by 4,750, now at 316,250.

Here is the opening of the official statement from the Department of Labor:

In the week ending April 5, the advance figure for seasonally adjusted initial claims was 300,000, a decrease of 32,000 from the previous week’s revised level. The last time initial claims were this low was May 12, 2007 when they were 297,000. The previous week’s level was revised up by 6,000 from 326,000 to 332,000. The 4-week moving average was 316,250, a decrease of 4,750 from the previous week’s revised average. The previous week’s average was revised up by 1,500 from 319,500 to 321,000.

Today’s seasonally adjusted number at 300K came in well below the Investing.com forecast of 320K.

Here is a close look at the data over the past few years (with a callout for the past year), which gives a clearer sense of the overall trend in relation to the last recession and the volatility in recent months.

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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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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).

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Because of the extreme volatility of the non-adjusted weekly data, a 52-week moving average gives a better sense of the secular trends. I’ve added a linear regression through the data. We can see that this metric continued to fall below the long-term trend stretching back to 1968.

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