Ahead of the U.S. stock market’s inflation test, Wall Street is facing the most brutal “data deception” in history

Author: Wall Street Insights

Official inflation data shows the situation is under control, but U.S. consumer confidence has fallen to its lowest level in nearly half a century—this gap is shaking the market’s basic trust in macroeconomic data.

U.S. June CPI data will be released tomorrow. Before that, May’s consumer price index rose 4.2% year over year, the personal consumption expenditures price index (PCE) increased 3.4%, and the official figures present a picture of “hidden worries, but no crisis.”

However, the University of Michigan’s consumer sentiment index hit an all-time low in May dating back to 1978, with the June reading being the second-lowest in history. Over the five decades covered by this index—spanning the oil crisis, two stock market bubbles, a pandemic, and six recessions—Americans still view the current period as the worst economic time.

This contradiction is prompting deep reflection among economists.

Labor economist and independent policy adviser Kathryn Anne Edwards, writing in a Bloomberg column, pointed out that the large gap between official inflation indicators and what people truly feel stems from systemic flaws in the current measurement framework—using an averaged “market basket” to conceal drastically different inflation realities across different household groups. For investors who rely on these data for asset pricing and policy forecasting, this means the core indicators they have long used may not be accurately reflecting the true economic pressure.

One number conceals ten thousand kinds of inflation experience

The U.S. Bureau of Labor Statistics (BLS) tracks monthly price changes for about 100k goods and services, and weights them through consumer expenditure surveys to produce a CPI that reflects the purchasing behavior of a “typical consumer.”

At present, the BLS maintains only three sets of consumption baskets: all consumers, all urban consumers, and urban wage earners and clerical workers.

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

BLS research itself has shown the difference is not negligible: a study covering 2006 to 2023 found that the annual average inflation rate for households in the lowest income quintile was about 0.28 percentage points higher than for those in the highest income quintile, with a cumulative gap of 7.7 percentage points.

In other words, over nearly two decades, the inflation pressure actually borne by poorer households has far exceeded that faced by richer households, and this gap is nearly invisible in standard CPI.

The impact of this “averaging” on the market is substantive. When investors and policymakers base their view of the direction of monetary policy on the overall CPI, what they see is a statistically smoothed number—not the true distribution of pressure within the economy.

The data foundation is there; what’s missing is policy will

Edwards’s core argument is not to overturn the existing system, but to point out that the technical threshold for expanding measurement dimensions is very low.

The BLS has already done the most heavy lifting—collecting data on price changes for 100k goods and services each month. On that basis, building more granular indexes by dimensions such as household type (single, married with no children, married with minor children, etc.), income level, renting versus owning a home, age, and more is essentially just reweighting and presenting the same set of raw data in different ways.

The BLS already has several precedents: CPI studies for seniors, for new renters, CPI that excludes changes in product specifications, and CPI research series divided by income quintiles.

These series are published less frequently than monthly CPI, but they demonstrate that the technical path is feasible. Edwards suggested that the current three baskets should at least expand tenfold, and provide monthly data for each type of typical household, while also increasing the number of BLS researchers compiling it and expanding the sample size in the consumer expenditure survey.

Beyond data distortion, real economic pressure cannot be avoided

Edwards made it clear that improvements to the measurement framework cannot solve problems in the economy itself.

She listed multiple pressures the U.S. economy is facing right now: hiring slowdown, sluggish wage growth, prices staying elevated for the long term, credit card debt continuing to rise, high interest rates suppressing housing market vitality, and the potential impact of artificial intelligence on the job market.

Together, these structural pressures explain why there is such a deep rift between consumer confidence and official data. In Edwards’s view, the right way to bridge this contradiction is not to ask the public to trust the existing data more, but to make the data system reflect the lived realities of different groups more faithfully.

For market participants, the significance of this discussion is this: as tomorrow’s CPI data is released, investors may need to reassess to what extent a single aggregate indicator can accurately capture the real inflation pressure and the divergence in consumer behavior across the current economic cycle—divergence that is a key variable for understanding the Fed’s policy path and the risks on the consumer side.