BLS Caught Fabricating Data

Friday, October 6, 2017
By Paul Martin

by Tyler Durden
ZeroHedge.com
Oct 6, 2017

While it’s not the first time we have observed the BLS manipulate data (the last time was in “This Is What Happens When The Bureau Of Labor Statistics Is Caught In A Lie”), never before had we actually caught the Bureau Of Labor Statistics openly fabricating data. Until now.

As reported earlier today, in one of the most closely watched statistics in today’s payrolls report, the BLS reported that the annual increase in Average Weekly Earnings was a whopping 2.9%, above the 2.5% expected, and above the 2.5% reported last month. On the surface this was a great number, as the 2.9% annual increase – whether distorted by hurricanes or not – was the highest since the financial crisis.

However, a problem emerges when one looks just one month prior, at the revised August data.

What one sees here, as Andrew Zatlin of South Bay Research first noted, is that while the Total Private Average Weekly Earnings line posted another solid increase of 0.2% month over month, an upward revision from the previous month’s 0.1%, when one looks at the components, it become clear that the BLS fabricated the numbers, and may simply hard-coded its spreadsheet with the intention of goalseeking a specific number.

Presenting Exhibit 1: Table B-3 in today’s jobs report. What it shows is that whereas there was a sequential decline in the Average Weekly Earnings for Goods Producing and Private Service-producing industries which are the only two sub-components of the Total Private Line (and are circled in red on the table below) of -0.8% and -0.1% respectively, the BLS also reported that somehow, the total of these two declines was a 0.2% increase!

What the above chart shows is, in a word, impossible: one can not have the two subcomponents of a sum-total decline, while the total increases. The math does not work.

This, as Zatlin notes, undermines not only the labor inflation narrative, but it puts into question the rest of the overall labor data, and whether there are other politically-motivated, goalseeked “spreadsheet” errors.

The Rest…HERE

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