Understanding the Economic Impact of the Federal Shutdown

As concerns about the economic ramifications of the unprecedented Federal shutdown grow, many Americans are feeling the pinch through lost wages and benefits. The effects extend beyond personal finance, with disruptions in air traffic causing some to rethink their Thanksgiving travel plans. This article explores another critical consequence: the potential for unreliable economic data that could leave investors paralyzed by uncertainty or lead them to make unwise decisions.

While the current AI bubble signifies a concerning misallocation of capital, the prevailing doubt surrounding economic data will amplify this issue, further undermining confidence.

By Lynn Parramore, Senior Research Analyst at the Institute for New Economic Thinking. Originally published at the Institute for New Economic Thinking website

The Fragility of Economic Stability

History has shown us that economic stability is not inherently guaranteed; rather, it is a delicate construction that can collapse swiftly when trust, transparency, and accountability falter.

As the government shutdown persists, a significant concern emerges: the flow of official economic data has nearly ceased. Key indicators regarding labor, inflation, and consumer spending are missing. Likewise, the Treasury Department is unable to effectively track cash flows or debt issuance. Crucial agencies like the Bureau of Economic Analysis (BEA) are skipping essential reports on spending, income, and investment. Such fundamental data is vital for maintaining market stability and grounding policymakers in reality.

This lack of reliable information affects not only bureaucratic processes but also reverberates through the daily lives of ordinary citizens, influencing mortgage rates, retirement accounts, and various economic factors.

With public data waning, both Wall Street and Main Street are increasingly turning to private-sector data for guidance. However, there is a crucial catch: many private entities operate with minimal oversight and often have compelling reasons to present data favorably.

Experts are sounding alarms that this combination of sparse public data and opaque private information creates significant blind spots—threatening to destabilize the entire economy. Let’s explore this further.

The Reliability of Economic Indicators

This raises essential questions: How trustworthy are private-sector economic indicators in comparison to official government statistics? What do the comparisons reveal?

Ben Schiffrin, a former SEC staffer with a focus on securities policy at Better Markets, asserts that government-collected statistics offer a standard of trust and transparency that private-sector data typically lack.

“The official data should come from a neutral perspective,” Schiffrin states. “For many, data from the Bureau of Labor Statistics (BLS) has long been regarded as credible. If it conveys good or bad news, it can generally be trusted.”

In contrast, private companies often manipulate information to suit their interests. A recent Wall Street Journal report noted that only ten percent of participants showed any interest in private-market investment options like private equity and real estate. Yet firms such as Apollo and Blackstone aggressively market these options, presenting data suggesting widespread enthusiasm. This creates a significant disconnect between actual investor demand and industry projections.

In financial realms, hype frequently overshadows reality. Consider the crypto market, where industry advocates routinely announce impressive adoption figures, promoting the idea of “mass adoption.” However, Schiffrin points out that various surveys—many from the Federal Reserve—indicate that only a small and decreasing percentage of Americans use cryptocurrency for transactions. “The disparity is stark,” he emphasizes. “It can’t be both fifty percent and two percent.”

Phillip Basil, a former Federal Reserve staffer studying banking policy at Better Markets, stresses the importance of understanding the limitations of datasets. “About 90% of the data available carries some form of limitation,” he notes. “Given the vast volume of data being collected today, some compromises are unavoidable.”

This is why recognizing these compromises is crucial. “Government data tends to be robust due to its transparency,” he explains. “In contrast, private organizations often conceal their sources and methodologies to protect proprietary processes.” Understanding these limitations is vital for forming accurate predictions and models.

The Consequences of Private Data Limitations

In a worst-case scenario, the shortcomings of private data could lead the entire economy toward disaster. Take, for example, credit rating agencies, which are profit-driven entities responsible for evaluating bonds and loans. Their assessments rely on a blend of public filings, issuer-supplied data, and proprietary models that incorporate a range of government data. Although classified as private firms, they hold substantial sway in public markets.

This influence was palpably felt leading up to the 2008 financial crisis when these agencies, embroiled in conflicts of interest, assigned top ratings to mortgage-backed securities that they had every incentive to rate favorably. Investors trusted these ratings blindly, leading to catastrophic fallout.

Amanda Fischer, a former SEC chief of staff and current policy director at Better Markets, has witnessed how private credit ratings can diverge significantly from independent assessments. She recalls an episode during the Biden administration where the National Association of Insurance Commissioners (NAIC)— tasked with representing state insurance regulators—permitted insurers to rely on private credit ratings to determine their capital requirements. This approach is convenient but often imprudent. In one instance, the NAIC conducted a study comparing its independent evaluations of private credit investments with ratings from smaller agencies, including Egan-Jones and Kroll.

“The findings revealed a considerable gap between our independent assessments and the ratings issued by these agencies,” she recalls. “One firm expressed its outrage publicly, prompting the NAIC to quietly remove the study from its website, leaving only a trace in a Financial Times article.”

Fischer points out that discussions within Biden’s Financial Stability Oversight Council (FSOC) have highlighted the need for state insurance regulators to rely less on such private credit ratings, particularly since smaller firms may exhibit biases favoring issuers.

However, the issue endures. Inflated or overly generous private credit ratings can obscure real risks, leaving insurers undercapitalized and exposing the financial system to vulnerabilities. UBS Chairman Colm Kelleher recently cautioned that U.S. insurers are engaging in “ratings arbitrage” reminiscent of the subprime practices that precipitated the 2008 crisis. The Bank for International Settlements also warns that credit ratings for private loans held by U.S. insurers may have been systematically inflated.

Legal Gaps and Oversight Challenges

The rise of private data and alternative markets exposes serious weaknesses in regulatory frameworks. These oversight gaps render both markets and average Americans vulnerable.

Schiffrin asserts that the U.S. securities regulation system hinges on precise information. Without accurate data, regulatory frameworks become inadequate.

Companies are not permitted to instruct investors on what to buy or sell; however, they must provide truthful and comprehensive information about their operations and financial status. This includes non-financial details—like company strategy and leadership changes—and strictly financial figures such as revenues and balance sheets that analysts scrutinize.

“Without trustworthy data, investors cannot make informed choices, leading to market dysfunction,” warns Schiffrin. He emphasizes the critical role of the SEC in enforcing laws that require companies to report earnings correctly. “If they fail to do this, it renders the information useless,” he states, underscoring the foundation of securities law.

Meanwhile, in newer alternative markets, such as prediction markets and specific crypto platforms, the SEC encounters substantial hurdles because these venues often fall outside traditional disclosure regulations, complicating oversight and enforcement.

Prediction markets resemble online betting platforms, permitting users to place bets on future events—ranging from election outcomes to economic performance indicators.

“The burgeoning prediction markets are generating debates around their regulation,” Fischer explains. “They introduce new avenues for data exploitation while primarily operating in a legal gray area concerning securities laws.”

Fischer notes that, surprisingly, state laws governing sports betting are often more stringent than those pertaining to prediction markets overseen by the Commodity Futures Trading Commission (CFTC). Currently, no regulatory body ensures these markets are transparent or that the information they utilize is accurately disclosed.

Many platforms are structuring their bets as “swaps” to avoid state gambling restrictions, claiming CFTC jurisdiction. However, Fischer highlights that the CFTC is not actively monitoring these markets, and there is little oversight for potential insider trading or manipulation—at least to the public’s knowledge.

She cites a recent case involving a significant wager on the Nobel Peace Prize winner just prior to the announcement: “The timing suggested that someone may have had access to insider information.” Such situations create opportunities for gaining profits from undisclosed information, blurring the line between legitimate speculation and insider trading.

Schiffrin identifies growing concerns around event contracts, particularly betting on elections. He points out that while platforms like FanDuel and DraftKings are regulated—with measures to address gambling addiction—the major players in prediction markets, such as Kalshi and Polymarket, are striving to operate with minimal oversight.

A recent article in Rolling Stone highlighted that FanDuel monitors critical metrics, such as the percentage of users struggling with gambling addiction. Conversely, platforms like Polymarket face virtually no accountability—allowing them to downplay serious issues like gambling addiction.

Moreover, accurate data can be weaponized by private entities, depending on who accesses it first. For instance, if a firm tracks real-time consumer spending and an investor gains access to this data early, they can execute trades before the public, reaping profits from information that others lack. This practice, known as frontrunning, poses a significant threat.

“This issue also applies to government data,” Schiffrin adds. “Questions arise about whether someone anticipated a policy announcement and acted on that knowledge. Government data should be subject to stricter controls to thwart misuse.”

However, private sector data is no different from other corporate information. “Public companies have insider trading policies because early access to market-moving information is problematic. Although the government isn’t a public entity, the same risks apply if it becomes a source of critical market data,” he states. Just as earnings reports can influence markets, early access to significant government information can also have repercussions.

Fischer warns that the risks are amplified in emerging sectors like prediction markets. “Having worked at the SEC, I strongly advise against insider trading, as typically, offenders get caught. But in prediction markets, enforcement is scant. The usual norms of fairness and transparency don’t seem to be applicable.”

The Ripple Effect of Data Inaccuracies

Inaccurate or absent economic data significantly influences policymakers’ decisions, a crucial factor, particularly when the Federal Reserve determines interest rates. These rates affect everything from mortgages to credit cards and savings. Insufficient or misleading information can send ripples throughout the economy, impacting everyone’s financial situation.

Basil clarifies, “If monetary policy isn’t accurately formulated, it poses a major risk to everyone, especially everyday workers.”

He articulates how rate adjustments directly affect daily life. “Whether using a credit card, taking out a loan, or contributing to a pension, all of these financial instruments are influenced by the rate cycle. For individuals and small businesses alike, this is critically important.”

Basil underscores the challenges faced by Fed officials: “If actual data is unavailable for a Federal Open Market Committee (FOMC) meeting, there are workarounds like projecting certain figures and incorporating those into models. However, when projections are based on uncertain inputs, the potential for cascading errors increases.”

He references concerning comments made by Fed Chair Jerome Powell during a recent press briefing following a policy meeting, where Powell acknowledged the daunting task of collecting reliable data: “We’ll gather every scrap of data we can find, analyze it diligently. This is our responsibility.” He also highlighted reliance on private data and informal interviews to compensate for discrepancies, acknowledging that an unpredictable data landscape complicates their task.

“Powell is right, but it’s still problematic,” Basil explains. “If the Fed exercises caution and slows down, while potentially prudent, what if caution isn’t warranted? Accurate data could indicate necessary rate adjustments that benefit consumers, but instead, they may hold back. The true danger lies in the Fed becoming hesitant when action is essential. Meanwhile, markets and the economy continue to evolve without clear guidance from the Fed.”

Basil expresses particular anxiety about data gaps outside the banking sector. “The Fed receives ample data on banks, but most of it is weekly or quarterly,” he explains. “Even that is not frequent enough. In key non-bank markets, however, there’s almost no reliable data available.”

Two critical areas directly affecting everyday lives include the repo market—where banks lend to one another overnight—and the Treasury market, where the U.S. government raises money by selling bonds. Treasury rates dictate borrowing costs for mortgages, car loans, and credit cards.

Basil observes that reliable data regarding these markets is surprisingly lacking. “The Office of Financial Research recently discovered that the repo market is nearly twice as large as previously thought due to untracked over-the-counter transactions. These short-term rates are crucial, as they impact how financial institutions extend loans to one another.”

He points to September 2019 and March 2020 as cautionary examples, when the Fed lacked visibility into these markets and responded by injecting trillions of dollars until stability returned. “They overcorrected due to their limited understanding of the scale of the problem,” he notes.

Such repercussions affect everyone. Disruptions in Treasury markets can lead to increased borrowing rates, unsettling businesses and consumers alike. “When chaos erupted last April, the Fed cited hedge funds as the culprit while the Treasury pointed fingers at foreign investors—yet nobody had a clear picture due to insufficient data.”

“These gaps often go unnoticed, but when market disruptions occur, they become glaring issues,” Basil adds.

Conclusion

The current shutdown is not merely slowing the availability of critical information; it is jeopardizing the economy by placing it in the hands of unreliable data. Policymakers relying on incomplete, outdated, or privately generated figures heighten the risks associated with every decision made.

The stakes are high, as inadequacies in official data, ambiguous private statistics, and unregulated alternative markets establish blind spots that could precipitate real economic challenges. Addressing these issues is straightforward: restore timely public data flow, enhance oversight of private information critical to the markets, and close the existing legal loopholes surrounding emerging financial platforms. Until these steps are taken, our economic journey resembles “driving into the fog”—and we are all passengers on this uncertain ride.