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Reuters critic Felix Salmon thinks there's something fishy about the official BLS jobs numbers!
No, he's not alleging political interference. But he does make this point.
The jobs numbers have been ultra-steady, despite the fact that there's an expected 100K margin for error each month.
Every month, economists and traders look first at the headline jobs growth number: this month, it’s 155,000. Last month, it was 161,000. Which means the difference is just 6,000. That difference, from month to month, is what I’m charting here. Sometimes the difference is positive and sometimes it’s negative, but if you just look at the magnitude of the change, then over the past two years, the typical number has differed from the previous number by an average of 51,000, with a median of 30,000. And over the past five months, the changes have been much smaller still.
It’s entirely reasonable to look at these numbers and conclude that the labor-market recovery is “steady-as-she-goes”. Each month, we get another 160,000 new jobs, month in, month out, with some very modest month-to-month variation in the number.
But here’s the problem. Let’s say that the US economy was adding exactly 160,000 new jobs every month, with no variation at all in that number. In that case, what would we expect the monthly payrolls report to show? It would not show an exact 160,000 print every month, because there are errors in the data, as the BLS technical note does a very good job of explaining.
Here's the technical note to which he refers:
For example, the confidence interval for the monthly change in total nonfarm employment from the establishment survey is on the order of plus or minus 100,000. Suppose the estimate of nonfarm employment increases by 50,000 from one month to the next. The 90-percent confidence interval on the monthly change would range from -50,000 to +150,000 (50,000 +/- 100,000). These figures do not mean that the sample results are off by these magnitudes, but rather that there is about a 90-percent chance that the true over-the-month change lies within this interval. Since this range includes values of less than zero, we could not say with confidence that nonfarm employment had, in fact, increased that month. If, however, the reported nonfarm employment rise was 250,000, then all of the values within the 90- percent confidence interval would be greater than zero. In this case, it is likely (at least a 90-percent chance) that nonfarm employment had, in fact, risen that month. At an unemployment rate of around 6.0 percent, the 90-percent confidence interval for the monthly change in unemployment as measured by the household survey is about +/- 300,000, and for the monthly change in the unemployment rate it is about +/- 0.2 percentage point.
In general, estimates involving many individuals or establishments have lower standard errors (relative to the size of the estimate) than estimates which are based on a small number of observations. The precision of estimates also is improved when the data are cumulated over time, such as for quarterly and annual averages.
The stability is intriguing in light of this wide confidence interval.
Meanwhile, Cardiff Garcia at FT Alphaville has a more economics-oriented take on the stability and the resilience of the jobs data:
Consider all that has either influenced the US economy or at least made big headlines in the last two years — winter accelerations seemingly crashing into spring slowdowns; a debt ceiling debate coinciding with a debt downgrade; a supply chain disruption caused by the Japanese earthquake; commodity and gas price spikes; fiscal drag at both the federal and state levels; a dramatically evolving monetary policy framework; an election and fiscal cliff battle; a perpetual near-disaster in Europe and slowing emerging market growth.
In that light, the following line in today’s payrolls report is worth a quick remark:
In 2012, employment growth averaged 153,000 per month, the same as the average monthly gain for 2011.
In part owing to research about seasonal adjustment problems that we came across in late 2011 and early 2012, our line about the recovery throughout the past year has been that things were never quite as bad as we feared in the worst of times, and never quite as good as we’d hoped in the best of times.
Garcia concludes that ultimately the numbers give some reason for hope, given how much the economy has endured.
As for