HR automatons keep saying no. But when someone writes that all eyes will be on the US payrolls numbers on Friday, that’s a sackable offense. Few beyond finance actually care although the farmers down at the local pub apparently speak of nothing else.
Donald Trump cared enough to fire the head of the Bureau of Labor Statistics, which produces the monthly report. And indeed, this employment data is one of the most watched indicators by markets — perhaps the most watched.
The Monthly Obsession
The frenzy begins over two weeks before each release. Will it be higher or lower than last time? What’s the consensus and why? As the release approaches, everything else fades from view.
Back in the London portfolio days, the data came out at two in the afternoon — long after the second bottle at lunch. Returning to the office wasn’t happening. Long term investing, after all, was the excuse.
Meanwhile, on Wall Street, chaos reigned. A surprise in the number of jobs could spark fear about interest rates moving up or down, sending bonds and equities into spasms.
But the market couldn’t even agree on the meaning. A high number? Maybe good because the economy is strong. Or maybe bad because the Fed might hike rates. A disappointing figure? The same loop, in reverse.
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The Real Problem: Phoney Data
The core problem isn’t conflicting interpretations. It’s that the numbers are phoney in the first place — something Trump pointed out, and not wrongly.
Unless the president read the fine print on the BLS website, he might not even grasp how flawed it really is. The estimate — because that’s what it is — comes from a monthly survey of about 121,000 businesses and government agencies, which equates to nearly two thirds of a million worksites. Yet around 20% of the workforce is left out: farmers, the self employed, household workers, sole proprietors, military personnel.
It’s a jobs report, not a people report. Two jobs — one in journalism, another in telemarketing — both get counted. Double counting and extrapolation are easy enough to solve. The real problem is the obsession over the first release.
How the Report Works
Here’s the drill: three weeks after month end, preliminary payroll estimates are released. Everyone stares at the figures despite the word “preliminary” plastered across the report.
Maybe the weather was hot. Maybe a long weekend hit. Thousands of grads tasked with filling out the survey might’ve been triggered, skipped work, and forgot to send out layoff notices.
The next month brings a revised number — including the late data and seasonal adjustments. A month later, another revision. A year later, the BLS revises again.
All Hype, No Follow Up
But it’s the initial data that grabs headlines. Revisions, no matter how big, rarely get the same attention. Trump’s outrage over revisions in May and June was an exception.
These deltas can be huge often wider than the entire range of economist estimates.
Had the final numbers come first, many market reactions and narratives would have been completely different. And prices rarely correct themselves when the true figures show up.
The BLS doesn’t hide these changes. The data is all there, in detail, going back decades. It’s the public and the markets that ignore them. Recency bias, the behavioral scientists call it.
The 133,000 Job Error
Take June’s second revision: the original estimate was 147,000 new jobs. The Financial Times declared the US economy had surpassed expectations.
But the revised number was just 14,000.
If that had been known, the subheadline wouldn’t have said investors scaled back interest rate cut bets and helped push Wall Street to new highs.
Dye and Data
Sure, it all averages out over time. But so does the dye in a cheap pair of blue jeans. And someone’s white shirt ends up ruined. Transparency doesn’t matter when the market has already moved on — or worse, lost money.
Time for Reform
So when Trump says he did the right thing by firing the BLS chief, there’s agreement — though maybe for different reasons. A new regime that improves the data would benefit everyone.
Start by scrapping the first two estimates. Markets and economists can wait. They already wait a whole quarter for GDP data, which, at least, isn’t phoney.
Source: Financial Times — Original Article
Note: This article reflects opinions and content originally published by the Financial Times.