The Unemployment Insurance Weekly Claims Report was released this morning for last week. The 346,000 new claims number was a 42,000 decline from the previous weeks upwardly revised 388,000. The less volatile and closely watched four-week moving average, which is usually a better indicator of the recent trend, rose by 3,000 to 358,000.
Here is the official statement from the U.S. Department of Labor:
“In the week ending April 13, the advance figure for seasonally adjusted initial claims was 352,000, an increase of 4,000 from the previous week’s revised figure of 348,000. The 4-week moving average was 361,250, an increase of 2,750 from the previous week’s revised average of 358,500.
“The advance seasonally adjusted insured unemployment rate was 2.4 percent for the week ending April 6, unchanged from the prior week’s unrevised rate. The advance number for seasonally adjusted insured unemployment during the week ending April 6 was 3,068,000, a decrease of 35,000 from the preceding week’s revised level of 3,103,000. The 4-week moving average was 3,083,000, a decrease of 2,250 from the preceding week’s revised average of 3,085,250.”
Today’s seasonally adjusted number was slightly below the Briefing.com consensus estimate of 355K.
Here is a close look at the data over the past few years (with a callout for the several months), which gives a clearer sense of the overall trend in relation to the last recession and the trend in recent weeks:
As we can see, there’s a good bit of volatility in this indicator, which is why the four-week moving average (the highlighted number) is a more useful number than the weekly data. Here is the complete data series:
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 four-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. I’ve now added a linear regression through the data. We can see that this metric continues to fall below the long-term trend stretching back to 1968.
A Four-Year Comparison
Here is an overlay of the past three calendar years and the beginning of 2013 using the four-week moving average. The purpose is to show the relative slope of improvement since the peak in the spring of 2009. The latest year was off to an excellent start, but the last few weeks have shown a reversal.