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Response rates for the vacancy series that feeds Fed expectations have fallen from the high 60s to roughly 30% in a decade. The BLS has started publishing the evidence.
The Investor · Invest desk
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On March 13, 2026, the Bureau of Labor Statistics began publishing a detailed series of response rates for the Job Openings and Labor Turnover Survey alongside the January 2026 data release, with total nonfarm history running back to January 2015 [1]. That decade-long view shows the response rate falling from the high 60s in percentage terms to around 30% in recent periods [2][3], which means roughly two-thirds of the businesses the agency contacts are not answering [4].
The mechanics matter here because JOLTS is not a census. It is built from a sample of approximately 21,000 establishments and reports job openings, hires, quits, layoffs and total separations [5]. At a response rate near 30%, the published series is being estimated from on the order of 6,300 responding establishments [6]. Collection runs about 45 days across computer-assisted telephone interviews, web submissions, email and fax, and the breadth of channels has not arrested the decline [7]. The BLS describes the fall as structural rather than a drift, and consistent with what is happening across its other establishment surveys [8].
Two consequences for anyone who prices off this data. The first is precision. Sampling error scales with the inverse square root of the number of respondents, so a move from roughly 67% response to roughly 30% implies standard errors about 50% wider, holding sample design and everything else constant [9]. That is an arithmetic illustration rather than a restatement of the BLS published variances, which incorporate weighting and imputation, but the direction is not in dispute: a month-to-month wobble in openings that would have been marginally meaningful in 2015 is closer to noise now.
The second is bias, which is the harder problem. The concern flagged in the reporting is that non-respondents may differ systematically from respondents, and that if smaller firms or particular industries are disproportionately dropping out, statistical adjustments may not fully compensate [10]. Non-response bias does not average out over three-month windows the way sampling noise does. It shifts the level, and it is difficult to detect from outside the agency.
To its credit, the BLS is making the problem legible. Starting with the January 2026 data it also began breaking response rates down by industry, region and establishment size [11], which is exactly the cut needed to test the small-firm hypothesis. The response-rates page was last updated on May 20, 2026 with additional methodological context [12]. Less helpfully for anyone building regional models, some state-level JOLTS data moved from monthly to annual publication beginning in January 2026 [13].
The practical adjustment for operators is unglamorous. Treat single-month JOLTS prints, and especially the openings-to-unemployed ratio built on top of them, as a low-resolution signal; lean on the quits rate over quarters rather than months; and stop treating a revision as a surprise when a third of the intended sample is doing the talking.
What to watch: the industry, region and size breakdowns as they accumulate over 2026, and specifically whether small-establishment response sits materially below the 30% headline [11][2]. If it does, the level of reported openings, not just its variance, is in question. Watch too whether other establishment surveys get the same disclosure treatment, given that the BLS says the decline is not confined to JOLTS [8].
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Ranked by verification strength, evidence, and original report placement.
On March 13, 2026, the BLS began publishing a detailed series of JOLTS response rates alongside the January 2026 data release, including historical total nonfarm response rates going back to January 2015.
JOLTS response rates have fallen to around 30% (low-to-mid 30s) in recent periods.
A decade ago JOLTS response rates were in the high 60s percentage range; the rate has roughly been cut in half since.
Roughly two-thirds of the businesses the BLS contacts for JOLTS are not participating.
JOLTS tracks job openings, hires, quits, layoffs and separations across approximately 21,000 establishments nationwide, and is a primary tool economists and policymakers use to gauge US labour market health.
The BLS collects JOLTS data over roughly 45 days using computer-assisted telephone interviews, web submissions, email and fax, and businesses have increasingly opted out despite the variety of channels.
Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Single secondary retelling of specific but uncited official figures
Every claim in the cluster rests on one item, a crypto-and-finance aggregator republishing Investopedia material, with no link to or excerpt from the BLS response-rate page it describes. The dates and rate levels are specific and internally consistent, which raises confidence that a real BLS disclosure underlies them, but nothing here is independently corroborated and the two sharpest quantitative statements in the ledger are derivations rather than reported measurements.
Underlying indicator in wide use; new transparency artefact live but downstream uptake unmeasured
Adoption is measurable in two directions. The series itself is described as a primary tool for economists and policymakers, and the BLS transparency changes are concrete shipped events with dates: the response-rate series from March 13, 2026, breakdowns from the January 2026 data, a page update on May 20, 2026, and a state-level cadence change. What is absent is any evidence that researchers, the Fed or market participants have actually incorporated the response-rate data into how they read JOLTS, so uptake of the disclosure is unquantified.
Real, dated disclosure wrapped in a trustworthiness verdict the data does not yet support
The factual core, a response rate roughly halved to about 30% and a BLS series that now documents it, is solid and modestly stated. The overshoot is in the interpretation: the source asserts the indicator is 'quietly becoming less trustworthy' and the cluster's derived claim puts a ~50% number on the precision loss, yet no published standard errors, revision history or evidence of skewed non-response appears anywhere in the material. Overstatement is moderate rather than severe because the underlying disclosure is genuinely new and the risk mechanism is legitimate.
Attention-driven syndication; no commercial product interest visible
The observable incentive is editorial rather than commercial: a crypto-and-finance aggregator republishing Investopedia macro content, a category of story that draws traffic from readers positioning around US data releases, and framing it with a trust verdict sharper than the reported facts. No vendor, tool or investment position stands to benefit within the supplied material, and the BLS action described is disclosure of unflattering data about its own survey, which cuts against a promotional reading. Score reflects a mild attention incentive and thin evidence about the originating publisher's motives.
Directionally credible, quantitatively unverified
Confidence is limited by single-source dependence and the absence of any primary citation, but the specificity of the dates and the plausibility of the trend, plus the fact that the disclosure is the kind of thing that would be easy to falsify, support moderate belief in the factual spine. Confidence in the interpretive layer, the size of the precision loss and the existence of real distortion, is materially lower.
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1 article · August 15, 2026