U.S. government shutdown CPI distortion

U.S. Government Shutdown Fallout: Why CPI and Jobs Data Aren’t “Working Normally” in December — and Why Markets Are More Volatile

After the U.S. shutdown, CPI and jobs data aren’t functioning normally. Here’s why distorted data is driving volatility—and how investors should read December numbers.

Key Takeaways

✔ The 2025 U.S. government shutdown led to the cancellation of October CPI, creating a major inflation data gap.
October’s unemployment rate was not released for the first time since 1948, weakening labor market assessment.
✔ November CPI may reflect missing data, delayed pricing, and timing distortions, making it abnormal.
✔ In this environment, policy signals and multi-month trends matter more than single data points.

The 2025 U.S. government shutdown, which lasted roughly 43 days, was not just a political disruption.
It temporarily halted the production of the most important economic indicators investors rely on: CPI and employment data.
While data releases have resumed, a bigger question remains.
Are these numbers actually reliable?
For a Federal Reserve that emphasizes data-dependent monetary policy, distorted or incomplete data can amplify uncertainty across equities, bonds, and currencies.
December is less about what the data says—and more about how much trust it deserves.

Why Jobs Data Broke First: The CPS Survey Gap

U.S. employment data comes from two sources.
Payrolls are derived from employer surveys, while the unemployment rate and labor force participation come from the Current Population Survey (CPS).
During the shutdown, CPS data collection was suspended.
As a result, October 2025’s unemployment rate was not published, marking the first such omission since 1948.
This absence goes beyond a single headline number.
Participation rates, demographic employment trends, and labor market quality indicators were also lost.
That makes it far harder to explain why job growth may look strong while consumption and wage momentum soften—adding friction to both market narratives and Fed policy expectations.

Why CPI Became an “Abnormal” Dataset

Inflation data faces even deeper structural issues.
According to Reuters, the October CPI report was formally canceled, and the Bureau of Labor Statistics confirmed that most of the missing data would not be reconstructed.
As a result, November CPI lacks a clean month-over-month comparison base.
Some CPI components may be published without meaningful m/m changes, weakening short-term inflation signals.
Timing also matters.
Because price collection resumed late, holiday discounts and Black Friday pricing may be overrepresented, potentially understating underlying inflation pressure.
In short, this is not just missing data—it is distorted inflation measurement.

The Fed’s Dilemma: When Data Weakens, Words Matter More

The Federal Reserve has long emphasized CPI and employment as its primary policy inputs.
But when data reliability declines, policy guidance shifts away from numbers and toward interpretation and communication.
That is why Fed speeches, press conferences, and Summary of Economic Projections now carry outsized influence.
In data-distorted environments, tone often moves markets more than statistics.
For investors, this means traditional “beat or miss” reactions become less relevant.

How Investors Should Read Data in This Cycle

Category

Normal Conditions

Post-Shutdown Reality

CPI Analysis

Monthly changes

3–6 month inflation trends

Jobs Data

Unemployment + payrolls

Payrolls alone are insufficient

Policy Forecasting

Data-driven

Fed communication-driven

Market Reaction

Gradual

Event-driven volatility

The key takeaway is simple.
December data is provisional, not definitive.

The December 2025 CPI and employment releases reflect a rare period of data dysfunction caused by the U.S. government shutdown.
Overreacting to single releases may lead to mispricing risk.
Instead, investors should focus on trend normalization, Fed interpretation, and confirmation from future revisions.
This is a market environment where context matters more than precision.

References

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