The Fog of War and the Markets Part II
The Data Crisis — Why Investors Are Losing Visibility Into the Economy
Economic data used to be the foundation of smart investing. But that foundation is cracking. Fewer people respond to government surveys, so agencies must guess using statistical models. Those guesses often get revised—sometimes by hundreds of thousands of jobs—long after markets have already moved. Investors now face three major risks: misreading the economy, bad policy decisions, and less transparency from public companies. To invest wisely today, you need to see through the fog.
In Part I of this series, I explored how wars and global conflict create uncertainty in financial markets. But fighting isn’t the only thing clouding investors’ view. A quieter problem is growing inside the economic numbers that markets depend on. The data that guide policy and investing are becoming less certain, heavily revised, and often built on guesses rather than hard facts. Investors today must navigate not only the fog of war—but also a growing fog of data.
Modern markets work like giant information processors. Prices move as investors learn new facts about growth, inflation, and jobs. When the data is clear and reliable, markets can slowly find their way toward the truth. But when that data is incomplete, delayed, or heavily adjusted, the signals guiding markets become less reliable. The machine that produces economic truth is breaking down.
1. Statistical Fragility: When Fewer People Answer the Phone
For decades, the best economic reports came from surveys. The government would call businesses and households, ask questions, and publish the results. It worked because people actually answered.
That is no longer true.
Response rates for key government surveys have dropped sharply. Some surveys from the Bureau of Labor Statistics that once got replies from 60-75% of businesses now only hear back from 35-45%. When people stop answering, statisticians have to fill in the blanks using models and educated guesses. The science behind this is sound, but the final numbers become much less solid.
We see the problem most clearly when the government revises major reports.
Take the monthly jobs report. This is one of the most important numbers in global markets. Stock prices, bond yields, and currency values can swing wildly within minutes of its release. But that first report is based on partial information. It gets revised twice in the following months. Then comes a big annual revision when the government compares its estimates to actual payroll records.
In recent years, those annual revisions have wiped out 800,000 to 900,000 jobs—long after the Federal Reserve had already raised or lowered interest rates based on the original “ghost” numbers.
This isn’t cheating or incompetence. It’s simply the reality that first estimates are incomplete. Yet markets treat them as fact.
2. Model Substitution: Trading on Fragments
As survey response rates fall, economists are turning to other sources. Private data companies now offer real-time information from credit card swipes, shipping records, payroll processors, and even satellite images.
These sources can be useful and often arrive faster than official government reports. But they have their own problems.
Private data rarely covers the whole economy. Credit card data misses cash transactions and tends to overlook lower-income households. Payroll data only includes companies that use certain payroll systems. To turn these fragments into national estimates, analysts must build models that guess at what’s missing.
We are moving away from direct measurement and toward statistical guesswork. Markets are trading on mosaics of partial signals rather than one trusted government report. Interpreting the data now matters more than measuring it.
3. Policy Risk: Steering with a Fogged Window
The third problem is policy risk. The Federal Reserve and government leaders rely on the same shaky numbers that investors use. If those numbers are off, policymakers can easily make the wrong call.
When signals are unclear, officials have to decide whether a change in the data reflects a real economic shift or just random noise. History shows that policy mistakes often happen when data is uncertain.
If inflation looks higher than it really is, the Fed might raise rates too much and slow the economy. If jobs look stronger than reality, officials might delay help that people actually need.
There’s also a harder-to-measure issue: politics. Economic numbers shape election debates and budget fights. When data is fuzzy, there’s room for early estimates to lean in a direction that helps those in power. Months later, a quiet revision might correct the record—but by then, the policy decision has already been made. Markets must now react not just to the economy, but to how leaders read imperfect information. That means more sudden swings.
4. The Transparency Trap: Moving Toward Darkness
The data problem isn’t just about government reports. It also affects how companies share information with investors.
In recent years, Donald Trump suggested that requiring companies to report every quarter might be too much work. The idea, which comes up from time to time, is that firms might only need to report twice a year. Supporters say this would help companies think long-term. Critics say it would hide important information from investors.
The current system, run by the US Securities and Exchange Commission, is one of the foundations of modern markets. Regular company reports let investors track performance and decide where to put their money. If reports came less often, insiders would know more than regular investors. If public companies started acting more like private ones—where information is scarce and values are murky—markets would suffer. We’d see weaker price discovery, unfair information advantages, and more money flowing to the wrong places. Transparency isn’t red tape. It’s what makes markets work.
5. The Illusion of Precision
There’s also a quieter problem hiding inside the numbers: false precision.
Think about how we measure Gross Domestic Product (GDP). The government tries to estimate all economic activity across a multi-trillion-dollar economy with millions of businesses. Large parts of that calculation have to be approximated through surveys and models. Yet GDP reports are often given to the nearest tenth of a percent.
Imagine the economy as a skyscraper rising 2.5 miles into the sky. Now imagine trying to measure whether it grew by the height of a few bricks on the top floor. That tiny difference is then reported as fact. In reality, GDP is a broad estimate, not a precise measurement. The danger isn’t that GDP is useless—it’s still one of our best tools. The danger is that false precision makes us overconfident in numbers that are really just educated guesses.
6. Narrative Risk: When Stories Beat Facts
These limits lead to one more problem: narrative risk.
Police officers often say that ten witnesses to the same car accident will give ten different stories. Everyone saw the same event, but memory and perspective produce different versions. Economic data works the same way. GDP, jobs, and inflation are complex estimates built from incomplete information. Two analysts looking at the same numbers can reach completely different conclusions. One sees strength. Another sees warning signs.
When public debate becomes dominated by competing stories, the data itself stops being proof and becomes raw material for arguments. The real risk isn’t just statistical error. It’s that fuzzy numbers allow persuasive storytelling to replace honest analysis.
The Investor’s Challenge
Put all of this together, and a clear picture emerges. Survey response rates are falling. Direct measurement is being replaced by modeling. Policy decisions rest on numbers that are less reliable than they used to be. And pressure is building to weaken the rules that keep public markets transparent.
Investors today are not just interpreting the economy. They are interpreting data that is itself increasingly uncertain.
For anyone managing money for the long term, this carries an important lesson. Markets have always required good judgment. But judgment matters even more when the numbers guiding your decisions are less solid than they appear. The challenge isn’t just riding out economic ups and downs. It’s recognizing when your view of the economic landscape itself has started to fade.
We must treat every “precise” government number with healthy skepticism. We are navigating a landscape where the map no longer matches the ground.