When Trump economic adviser Judy Shelton recently declared US jobs data "very unreliable," I couldn't help but roll my eyes. Not because she's wrong, necessarily—there are legitimate critiques of our employment metrics—but because of the tired predictability of it all.
Here's the playbook: When the numbers make your team look good, they're gospel. When they don't? Well, suddenly there are "serious methodological concerns" that need addressing.
I've covered economic policy debates for years, and this dance is as choreographed as a Broadway show. Both parties do it. Both parties know they do it. And yet, here we are again.
Look, employment data is messy. It just is. The Bureau of Labor Statistics is essentially trying to track the economic activities of 330 million Americans in real-time. That's like counting ants at a picnic during a windstorm.
The BLS runs two separate surveys—one of businesses (the establishment survey) and one of households—which frequently tell different stories. Then they apply seasonal adjustments and various statistical models that can dramatically reshape the narrative.
These aren't secret flaws. They're known limitations of economic measurement.
What's interesting about Shelton's timing is that the labor market has shown remarkable resilience despite aggressive Fed tightening. The unemployment rate has remained near historic lows—a fact that complicates certain political narratives.
(I should note that beneath those headline numbers lurk genuine concerns: labor force participation hasn't fully bounced back to pre-pandemic levels, and many workers juggle multiple jobs to stay afloat.)
The history of politicians questioning jobs data is rich with hypocrisy. During Obama's presidency, remember Jack Welch? The former GE boss who suggested the administration was cooking the books when unemployment numbers improved? Then during Trump's term, Democrats suddenly discovered all sorts of problems with the same metrics.
And now... well, the pendulum swings back. Again.
There's actually a term economists use—though not in polite company—for this phenomenon: "politically convenient skepticism." The math is simple: Your doubt about economic data is directly proportional to how badly it contradicts your preferred narrative.
I spoke with three former BLS economists last year about this very issue. All three—spanning appointments under both Republican and Democratic administrations—expressed frustration with how their work becomes weaponized in political battles.
"We're just counting things," one told me, clearly exasperated. "We're not in the business of making anyone look good or bad."
The truth? The BLS data isn't perfect, but it's far from "very unreliable." It remains among the best economic indicators we have. The real issue isn't the data itself but how we interpret it.
Economic statistics work best as trend indicators rather than precise snapshots of reality. Smart market watchers know this. They examine not just headline numbers but revisions to previous months, sector breakdowns, wage trends, and hours worked.
What Shelton is really doing—and I've seen this movie before—is setting the stage for potential policy shifts. If you're planning to change economic direction, it helps to first establish that the metrics by which those policies might be judged are fundamentally flawed.
It's a neat trick. Too bad it's so transparent.
So the next time you hear someone passionately arguing about jobs numbers, do what I do: check if their position on data quality remained consistent when the numbers pointed in different directions.
That's the true test of intellectual honesty in economic debates. And honestly? Most folks fail it miserably.
