On the eve of a major inflation test for US equities, Wall Street is facing the most severe 'data deception' in history

Article author: Bu Shuqing

Source: Wall Street News

The US Consumer Price Index (CPI) for June will be released tomorrow. Prior to that, the May CPI rose 4.2% year-over-year, while the Personal Consumption Expenditures (PCE) price index increased by 3.4%.Official data paints a picture of 'concerns without crisis.'

However,The University of Michigan’s Consumer Sentiment Index hit a record low in May—the lowest since records began in 1978—and posted the second-lowest reading ever in June.—This index spans five decades that include oil shocks, two stock market bubbles, a pandemic, and six recessions, yet Americans still view the current period as the worst economic time.

This contradiction is prompting deep reflection within the economics community.

Kathryn Anne Edwards, a labor economist and independent policy advisor, wrote in a Bloomberg column thatthe vast gap between official inflation metrics and the public’s lived experience stems from systemic flaws in the current measurement framework.—It uses an averaged 'market basket' to obscure the starkly different inflation realities faced by various household groups. For investors who rely on these data for asset pricing and policy forecasting, this means the key indicators they have long referenced may not accurately reflect the true economic stress.

The U.S. Bureau of Labor Statistics (BLS) tracks monthly price changes for approximately 100,000 goods and services, weighting them based on consumer expenditure surveys to produce the Consumer Price Index (CPI), which reflects the purchasing behavior of a 'typical consumer.'

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

Edwards points out that the fundamental limitation of this framework lies in compressing highly heterogeneous consumer groups into a single average.

The BLS’s own research has already demonstrated that this disparity cannot be ignored: a study covering 2006 to 2023 showed that the lowest-income quintile households experienced an average annual inflation rate about 0.28 percentage points higher than that of the highest-income quintile, amounting to a cumulative gap of 7.7 percentage points.

In other words,Over the past two decades, lower-income households have borne significantly greater inflationary pressure than their wealthier counterparts—a gap largely invisible in the standard CPI.

This kind of 'averaging' has a substantive impact on markets. When investors and policymakers use headline CPI data to gauge the direction of monetary policy, what they see is a statistically smoothed figure—not the actual distribution of inflationary pressures within the economy.

Edwards’s core argument is not to dismantle the existing system, but to highlight that the technical barrier to expanding measurement dimensions is extremely low.

The Bureau of Labor Statistics (BLS) has already done the heavy lifting—collecting monthly price change data for 100,000 goods and services. Building additional sub-indices based on household type (single, married without children, married with minor children, etc.), income level, renter versus homeowner status, age, and other dimensions essentially involves reweighting and presenting the same underlying dataset in different ways.

The BLS already has several precedents: a CPI for the elderly, a CPI for new renters, a CPI that excludes changes in product specifications, and a research series of CPIs segmented by income quintiles.

Although these series are published less frequently than the monthly CPI, they demonstrate the feasibility of this technical approach. Edwards recommends that the current three baskets be expanded by at least tenfold, providing monthly data for each typical household type, while also increasing the sample size of the BLS’s Consumer Expenditure Survey and boosting staffing for its researchers.

Edwards explicitly states that improving the measurement system will not solve the economy’s underlying problems.

She cites multiple sources of pressure currently facing the U.S. economy:Slowing hiring, stagnant wage growth, persistently high prices, rising credit card debt, high interest rates dampening housing market activity, and the potential disruption from artificial intelligence in the labor market.

These structural pressures together explain the deep disconnect between consumer sentiment and official data. In Edwards’s view, the right way to bridge this gap is not to demand greater public trust in existing data, but to make the data system more accurately reflect the lived realities of different population groups.

For market participants, the significance of this discussion lies in this: when tomorrow’s CPI data is released, investors may need to reassess how effectively a single aggregate indicator captures the true inflationary pressures and divergent consumer behaviors characterizing the current economic cycle—divergences that are key variables for understanding the Federal Reserve’s policy trajectory and consumption-side risks.

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