New Jobless Claims At 297K, Matching Forecasts [Dow Jones Industrial Average, SPDR S&P 500 ETF Trust]

jobsDoug Short: Here is the opening statement from the Department of Labor:

In the week ending November 29, the advance figure for seasonally adjusted initial claims was 297,000, a decrease of 17,000 from the previous week’s revised level. The previous week’s level was revised up by 1,000 from 313,000 to 314,000. The 4-week moving average was 299,000, an increase of 4,750 from the previous week’s revised average. The previous week’s average was revised up by 250 from 294,000 to 294,250.

There were no special factors impacting this week’s initial claims. [See full report]

Today’s seasonally adjusted number was spot on the Investing.com forecast of 297K. The four-week moving average at 294K is now 20K above its 14-year interim low set four weeks ago.

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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A Four-Year Comparison

Here is a calendar-year overlay since 2009 using the 4-week moving average.

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