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Initial Claims Not Great but Not as Bad as Claimed

by Lee Adler, Wall Street Examiner

The media exhibited much consternation today as economists’ consensus guess on first time unemployment claims turned out to be way too optimistic this week. That raised two questions in my mind. Was the number really that bad, and even if it was, does it matter?

The Labor Department reported that the seasonally adjusted (SA) representation of first time claims for unemployment rose by 32,000 to 360,000 from a revised 328,000 (was 323,000) in the advance report for the week ended May 11, 2013. The consensus estimate of economists of 330,000 for the SA headline number was too optimistic after 3 weeks of guesses that were too pessimistic. Call it “evening things up.” They were wrong one way 3 times in a row, so they overcompensated the other way this week. It’s a ridiculous game, but everybody plays anyway. Forecasters are virtually always wrong, not just because economic forecasting is quackery, but also because the seasonally adjusted number, being made-up, is impossible to consistently guess (see endnote).

The headline seasonally adjusted data is the only data the media reports but the Department of Labor (DOL) also reports the actual data, not seasonally adjusted (NSA). The DOL said in today’s press release,

“The advance number of actual initial claims under state programs, unadjusted, totaled 318,203 in the week ending May 11, a decrease of 15,436 from the previous week. There were 325,094 initial claims in the comparable week in 2012.”  [Added emphasis mine]

For purposes of this analysis, I adjusted this week’s reported number up by 4,000. The advance report is usually revised up by from 1,000 to 4,000 in the following week, when all interstate claims have been counted. Last week’s number was approximately 4,500 shy of the final number for that week released today, a slightly bigger miss than usual, but not material in the big picture. The adjusted number that I used in the data calculations and charts for this week is 322,000, rounded. It won’t matter that it’s a thousand or two either way in the final count next week. The differences are essentially rounding errors, invisible on the chart.

The actual filings represent a decrease of  0.9% versus the corresponding week last year. That’s a steep deceleration from the 11.6% drop last week and similar declines the two previous weeks. Such volatility in the year to year comps is entirely normal. The average year to year improvement of the past 2 years of -8.8%, but the range is from near zero to -20%. The year to year comparisons are now much tougher as the number of job losses declined sharply between 2009 and 2012. After 3 weeks of very strong comps, a little giveback isn’t anything to get excited about, especially since the rate of change is still within the parameters of the normal range.

The current week to week change in the NSA number is a jump of 19,000. That compares with an average change of a decrease of 5,000 for the same week over the prior 10 years. The comparable week has had extreme variations with both increases and decreases. In 2012 the comparable week had a decrease of 17,000, while in 2011 there was a decrease of 36,000. The current jump was the worst reading since a jump of 36,000 in the comparable week of 2009. If this repeats next week, then I’d say that’s evidence that the economy may have slowed, and even that might be jumping the gun. For now, there’s not enough data to jump to that conclusion.

The Labor Department, using the usual statistical hocus pocus, applied seasonal adjustment factors ranging from about 1.15 to about 1.07 to the week corresponding to this one over the last 10 years. This week they applied a factor of 1.13.

Click to enlarge

The correlation of the  broad trends of claims with the trend of stock prices over the longer term is strong. It is most visible when the claims trend is plotted on an inverse scale with stock prices on  a normal scale.

Click to enlarge

Stock prices were running with the initial claims trend until the Fed started QE3 and 4 late last year and early in 2013, causing the stock price rise to accelerate. Stocks are now at maximum extension within the trend channel of the past two years. The Fed’s QE3-4 money printing campaign has had far more success in creating a stock market bubble, which was one of Bernanke’s stated goals (in slightly different words) than in driving economic growth. The stock market appears to now be in parabolic blow-off mode as a result of the excess liquidity.

There’s plenty of room for a deep pullback in stock prices, but there’s always a chance that stock prices will decouple completely from economic indicators as long as the Fed ( joined by the BoJ) keeps cashing out the Primary Dealers every month via its asset purchase programs (QE3-4). The old refrain that “It’s the economy, stupid,” may in fact be meaningless in a world where the Fed is the market.

This report is excerpted from the Permanent Employment Charts page – More charts!

Note: There is no way to know whether the SA number is misleading or a reasonably accurate representation of the trend unless we are also looking at charts of the actual data. And if we look at the actual data using the tools of technical analysis to view the trend, then there’s no reason to be looking at a bunch of made up crap, which is what the seasonally adjusted data is. Seasonal adjustment just confuses the issue.

Seasonally adjusted numbers are fictional and are not finalized until 5 years after the fact. There are annual revisions that attempt to accurately reflect what actually happened this week. The weekly numbers are essentially worthless for comparative analytical purposes because they are so noisy. Seasonally adjusted noise is still noise. It’s just smoother. So economists are fishing in the dark for a fictitious number that is all but impossible to guess. But when they are persistently wrong in one direction, it shows that their models have a bias. Since the third quarter of 2012, with a few exceptions it has appeared that a pessimism bias was built in to their estimates.

To avoid the confusion inherent in the fictitious SA data, I work with only the actual, not seasonally adjusted (NSA) data. It is a simple matter to extract the trend from the actual data  and compare the latest week’s actual performance to the trend, to last year, and to the average performance for the week over the prior 10 years. It’s easy to see graphically whether the trend is accelerating, decelerating, or about the same.

The advance number for the most recent week is normally a little short of the final number the week after the advance report, because the advance number does not include all interstate claims. The revisions are minor and consistent however, so it is easy to adjust for them. Unlike the SA data, after the second week, they are never subsequently revised.

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