In early October, the world learned that America’s best and brightest economic minds had wildly overestimated post-pandemic job growth. The September jobs report revealed that the economy had added just 194,000 new positions, but experts from Down Jones and other industry leaders had predicted 500,000 — a swing and a miss so totally off base that it missed the mark by more than 300,000 jobs.
Two months later when the Bureau of Labor Statistics (BLS) published the November jobs numbers, Barron’s reported that the forecasters had again whiffed by more than 300,000 — this time the economy added 210,000 jobs instead of the 535,000 that had been expected.
Two months later in January, the next report showed that the economy had added an impressive 467,000 jobs, and the Bureau of Labor Statistics (BLS) took the unusual step of retroactively adding more than 700,000 jobs to the previous two months’ numbers.
It was great news — unless you work in the economic prognostication business. This time around, the forecasts were as inaccurate as they had been before, but now they stumbled in the other direction. Economists had predicted that the economy would add just 150,000 new jobs, less than a third of what reality delivered.
What’s going on — are economists just guessing? Why are the most reliable predictors so unpredictable — and is anyone capable of charting the labor market’s trajectory in post-pandemic America?
GOBankingRates asked the experts.
It’s a Hard Time To Be an Economic Fortune Teller
In its analysis of November’s botched numbers, Barron’s explained just how much more complex the pandemic recovery has proven to be compared to a standard economic recovery. From rising inflation and the Great Resignation to the emergence of new COVID-19 strains and the rise of the gig economy and remote work, 2021 put an impossible number of powerful new variables in play.
“The economy is behaving oddly,” said Jonathan Tian, co-founder of Mobitrix. “That’s the reason why estimates keep missing the mark so badly. As economists expected the surge in cases to lead to anemic gains, it couldn’t knock the U.S. job market recovery off course, and employment has boomed with the addition of over 400,000 jobs.”
The BLS uses a formula to even out predictable fluctuations in the jobs data it gathers. That formula was not built to survive the rigors of 2021.
“Ultimately, the wild month-over-month fluctuations and underestimates in recent jobs reports are an artifact of how the Bureau of Labor Statistics seasonally adjusts its employment data,” said Dr. Krieg Tidemann, assistant professor of economics at Niagara University. “Employer demand for labor follows a seasonal cycle, such as retail and service industries hiring temporary workers during the holiday season. We can think of these seasonal patterns as a smokescreen that complicates economists’ ability to interpret each month’s employment data, making it challenging to identify employment trends and assess the strength of the labor market. To correct for this problem, the BLS seasonally adjusts each month to account for the fact that we expect employment to surge in some months and decline in others.”
The BLS Adjusted for an Omicron Setback That Never Came
In a normal year, seasonal adjustments provide more reliable data by evening out the peaks and valleys that aren’t representative of the norm. The problem with 2021 was that there was no norm for economists to use to calibrate their projections.
“The seasonal adjustment methods are designed for normal periods that do not experience the once-in-our-lifetime employment swings seen during the pandemic period,” Tidemann said. “This led the monthly initial jobs reports to wildly overstate job growth in summer 2021 and understate new employment in fall 2021.”
The BLS adjusted, but not before the confusion had already been sown.
“Just as the pandemic has forced families and employers to creatively respond to the challenges of the pandemic, the BLS also needed to revise its seasonal adjustment procedures for the pandemic period,” Tidemann said. “As they noted in their most recent jobs report, changes to their seasonal adjustment procedure led to substantial upward revisions in the initial late 2021 jobs report estimates. As many economists connected fall’s underwhelming preliminary jobs estimates with the surging Delta wave of the coronavirus, it was reasonable to predict a similar subpar jobs report during winter’s Omicron wave. However, after correcting their seasonal adjustment process, this no longer appears to have been the case.”
Even in the Best of Years, Economic Forecasting Is Imprecise Work
It’s not just the BLS jobs reports. Economic projections, in general, are built on approximations, incomplete data, an enormous set of variables and intangibles like a population’s emotions or expectations.
“There are a number of reasons why economic predictions are generally bad,” said Peter C. Earle, research fellow at the economic research and advocacy think tank the American Institute for Economic Research (AIER). “The first is that, quite simply, it’s an inexact science, a social science, and thus not amenable to mathematical modeling or quantification. Yes, in grad school we spend a lot of time using high-powered mathematics — econometrics — but that use has more to do with expressing relationships symbolically than anything that happens in the real world.”
Economist Culture Is Quick To Forgive Even the Biggest of Blunders
Finally, it must be pointed out that there simply isn’t a lot at stake for economists who get it wrong and the industry appears to be lousy at self-policing.
“To be honest, for most economists, there’s just no skin in the game,” Earle said. “There’s no cost for inaccuracy, so whether they forecast correctly or not they continue on their merry way. Oh sure, for some there’s a reputational cost to being very wrong, but the economy moves slowly enough via month-to-month data points that bad predictions can be steered gradually back toward what’s actually occurring.”
Also, the more inexact a science is, the more room there is for researchers to insert their own preconceived notions and biases into the result.
“I think that often the economists and experts who collect and report the data go into it having already created an expected outcome in their mind,” said Carter Seuthe, CEO of Credit Summit. “These assumptions are expressed to the public, and then when the actual numbers are reported, the discrepancy seems confusing. The truth is that we are still in such an unpredictable time because of the pandemic, so experts simply can’t be making these assumptions ahead of time because there is really no way to create accurate predictions.”
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