In the high-stakes world of economic policymaking, where decisions hinge on the precision of data, renowned economist Jeremy Siegel has ignited a fierce debate over the reliability of U.S. government statistics. During a recent appearance on CNBC’s “Squawk Box,” Siegel, a professor emeritus at the University of Pennsylvania’s Wharton School and chief economist at WisdomTree, lambasted the Bureau of Labor Statistics (BLS) for what he sees as systemic failures in collecting and reporting jobs data. His comments come amid controversy following President Trump’s abrupt firing of the BLS commissioner, triggered by a shockingly weak July jobs report that revealed only 73,000 new jobs added—far below expectations—and massive downward revisions to prior months’ figures.

Siegel didn’t mince words, highlighting how the BLS’s reliance on voluntary surveys with plummeting response rates—now as low as 60% for key employment metrics—has led to inaccurate readings of the economy. “The response rate is down to 60%. That’s unacceptable for the most important statistic we have,” he stated in the CNBC interview. This critique echoes longstanding concerns among economists, but Siegel’s prominence has amplified the issue, especially as the data discrepancies directly influenced Federal Reserve actions. He argued that had the Fed known the true extent of labor market weakness earlier, a rate cut in July would have been inevitable, potentially averting market volatility.

The Flaws in Data Collection Exposed

The core of Siegel’s criticism centers on the BLS’s methodology, which depends on surveys sent to about 400,000 firms. These are not mandatory, and without strict deadlines, responses trickle in late—sometimes weeks after initial reports. This delay, Siegel contends, creates a distorted picture, as seen in the July report’s revisions that erased nearly 260,000 jobs from May and June estimates, marking one of the largest such adjustments since 1979, excluding the COVID era. Posts on X (formerly Twitter) from financial analysts, such as those highlighting the “biggest shock” in revisions per Bloomberg Economics, underscore a growing sentiment that the labor market has been “downshifting” faster than acknowledged.

Moreover, Siegel pointed to the JOLTS (Job Openings and Labor Turnover Survey) report, where response rates have plunged to 20%—less than half pre-COVID levels. “COVID is over. We can’t keep using it as an excuse,” he said on CNBC. This isn’t isolated; a Marketplace report from May 2025 noted how proposed rules under the Trump administration could further erode data integrity by allowing deviations from established norms, raising alarms among former BLS officials.

Impact on Monetary Policy and Market Reactions

The ramifications extend to the Federal Reserve’s decision-making. Siegel emphasized that flawed data led to a missed opportunity for a July rate cut, with the fed funds rate remaining inverted relative to the 10-year Treasury yield—a signal he interprets as demanding lower rates than the current 4.33%. “It changed monetary policy,” he asserted. Indeed, following the report, market odds for a September rate cut surged to 83%, as noted in X posts analyzing the data, with some users like those from FinLite.ai labeling it a “jobs shock” that prompted Trump’s BLS firing.

Historical context adds depth: Siegel has long been vocal on economic indicators. In a 2023 ThinkAdvisor piece, he praised strong data for stock resilience, but recent events flip that narrative, suggesting overestimations masked underlying weakness. A Investopedia article from June 2025 highlighted BLS cutbacks in data collection, fueling expert concerns over inflation and unemployment metrics’ accuracy.

Calls for Reform and Broader Implications

Siegel advocates for mandatory surveys with time limits to boost response rates and transparency. “Why wasn’t there an explanation for the biggest mistake in 50 years?” he questioned on CNBC, demanding accountability. He rejects claims of political rigging—countering Trump’s assertions that numbers were manipulated against him—but insists the BLS must modernize in an era of instant data via the internet. This view aligns with a BizToc summary of Siegel’s recent statements, where he lamented the absence of a July cut due to delayed weak data revelations.

Yet, amid these critiques, Siegel remains cautiously optimistic about markets. He sees potential for AI-driven productivity to offset tariff drags—estimated at 1% to 1.5% of GDP by most economists—potentially sustaining a bull trend. In his latest WisdomTree commentary from July 2025, he projected solid 2025-2026 earnings growth, buoyed by technology adoption, even as GDP forecasts hover at 1.5% for the second half amid tariff uncertainties.

Balancing Optimism with Economic Realities

Critics argue that while Siegel’s points are valid, overhauling a government entity like the BLS isn’t straightforward. Private alternatives, such as ADP’s payroll data, offer supplements, but Siegel questions if they’re sufficient without systemic fixes. A 2022 Wharton Knowledge podcast captured his earlier optimism on inflation’s peak, contrasting with today’s warnings of weakening labor signals potentially heralding recession risks, as he noted in a 2022 Fortune interview.

The debate has spilled onto social media, with X users like Jeffrey P. Snider pointing to BLS revisions erasing job gains, a pattern “more typical of recession.” Others, echoing Heather Long’s post on the Sahm Rule triggering at 4.3% unemployment, signal broader economic unease. Siegel’s stance also resonates with past endorsements, such as Elon Musk’s 2022 support via The Economic Times, criticizing Fed reliance on lagging indicators.

Toward a More Reliable Economic Future

Ultimately, Siegel’s exposé underscores a critical juncture for U.S. economic data infrastructure. As tariffs loom and AI promises productivity boosts, accurate statistics are paramount. Without reforms, policymakers