On the eve of the US stock market’s major inflation test, Wall Street is experiencing the most severe "data deception" in history.

Official inflation data suggests the situation is under control, but U.S. consumer confidence has plunged to its lowest level in nearly half a century—this disconnect is shaking the market’s fundamental trust in macro data.

The U.S. June CPI data will be released tomorrow. Prior to this, the Consumer Price Index for May rose 4.2% year-over-year, and the Personal Consumption Expenditures Price Index (PCE) increased 3.4%. Official data depicts a scenario of “hidden concerns, but no crisis.”

However, the University of Michigan Consumer Sentiment Index hit a historic low in May since records began in 1978, and the June reading is the second lowest ever—during the fifty years covered by this index, there have been oil crises, two stock market bubbles, a pandemic, and six recessions, yet Americans still regard the present as the worst economic period.

This contradiction is causing deep reflection among economists.

Labor economist and independent policy advisor Kathryn Anne Edwards wrote in a Bloomberg column that the huge gap between official inflation indicators and people’s real experiences originates from systemic flaws in the current measurement system—it uses an averaged “market basket” to mask drastically different inflation realities among various household groups. For investors who rely on these figures for asset pricing and policy forecasts, this means the core indicators they have depended on for years may not actually reflect the real economic pressure.

One number hides millions of inflation experiences

The U.S. Bureau of Labor Statistics (BLS) tracks the price changes of about 100,000 goods and services monthly, weighting them through consumer expenditure surveys to produce the CPI that reflects “typical consumer” purchases.

Currently, the BLS maintains only three sets of consumer baskets: all consumers, all urban consumers, and urban wage earners and clerical workers.

Edwards points out that the fundamental limitation of this framework is that it compresses highly heterogeneous consumer groups into a single average value.

BLS’s own research has proven these differences cannot be ignored: a study covering 2006 to 2023 showed the annual inflation rate for households in the lowest income quintile was about 0.28 percentage points higher than those in the highest quintile, amounting to a cumulative gap of 7.7 percentage points.

In other words, over nearly two decades, poor people have actually borne much greater inflation pressure than the wealthy, yet this disparity is virtually invisible in the standard CPI.

This “averaging” approach has a real impact on the market. When investors and policymakers use the headline CPI to judge monetary policy direction, what they see is a statistically smoothed number—not the true distribution of economic stress within the economy.

Data foundation exists—what is lacking is policy will

Edwards’s main argument is not to overthrow the existing system, but to highlight how easy it would be to expand the measurement dimensions technologically.

BLS has already done the hardest work—collecting price changes for 100,000 goods and services every month. On this basis, building more detailed indices by household type (single, married without children, married with minor children, etc.), income level, renting or owning a home, age, etc., is essentially just reweighting and presenting the same raw data differently.

The BLS already has several precedents: CPI for the elderly, CPI for new renters, CPI that excludes product specification changes, and a CPI research series divided by income quintile.

Although these series are published less frequently than the monthly CPI, they prove the technical feasibility. Edwards suggests the current three baskets should at least be expanded tenfold, provide monthly data for each typical household type, and increase the number of BLS researchers as well as expand consumer expenditure survey sample sizes.

Beyond data distortion, genuine economic stress cannot be ignored

Edwards makes clear that improving the measurement system does not solve the underlying economic problems.

She outlines multiple pressures facing the U.S. economy: sluggish hiring, stagnating wage growth, persistently high prices, rising credit card debt, high interest rates dampening housing market activity, and the potential impact of artificial intelligence on the job market.

These structural pressures together explain why there is such a deep rift between consumer confidence and official data. In Edwards’ view, the correct solution is not to ask the public to trust the current data more, but to make the data system more accurately reflect the lived realities of different groups.

For market participants, the significance of this discussion is: as tomorrow’s CPI data is released, investors may need to reassess to what extent a single aggregate indicator can truly capture real inflation pressures and differentiated consumer behavior in the current economic cycle—and this differentiation is key to understanding the Federal Reserve’s policy trajectory and consumption-side risks.

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