Once a month, on the last Tuesday, The Conference Board asks roughly 3,200 American households five questions about the economy. The answers get converted into a diffusion-style index with 1985 set to 100, published at 10:00 a.m. Eastern, and within a day or two a stack of charts appears treating the result as a forecast. It isn’t one. The Consumer Confidence Index (CCI) is a reading of how Americans say they feel about the economy — nothing more, nothing less. Its nearest relatives are the University of Michigan’s Consumer Sentiment Index, the Present Situation and Expectations components sitting beneath both series, and the Michigan expectations series that feeds The Conference Board’s own Leading Economic Index. Every one of those numbers records stated opinion at a point in time. Not one of them measures spending, hiring, or output. The most common failure in charts built on these releases is treating a mood reading as a forecast of hard data, and that failure is what this article is about: what the index can support, what it can’t, and how to read both the releases and the charts with the same discipline you’d bring to an election poll.
What the Consumer Confidence Index Actually Measures
Start with the instrument, because the instrument sets the limits. Each month The Conference Board fields an online questionnaire to about 3,200 households, weighted to Census benchmarks for age, income, and region. Five questions. Two concern the present: how respondents rate current business conditions, and whether jobs are currently “plentiful” or “not so plentiful.” Three look six months out: expected business conditions, expected employment conditions, expected family income. The headline index averages the five resulting scores. The release also reports a Present Situation Index built from the first pair, an Expectations Index from the second trio, and components on plans to buy homes, automobiles, and major appliances. The full release, tables included, lives on The Conference Board’s consumer confidence page.
The diffusion arithmetic deserves a closer look, because it decides what any chart built on the index can honestly claim. For each question, the share of positive responses plus half the share of neutrals forms a balance measure, which is then scaled against the 1985 base. Three things follow. The index has no natural units — 100 isn’t “good” and isn’t “neutral”; it is simply the average level of 1985, a benchmarking convention. The balance of opinion drifts with question wording, sample composition, and whatever the political climate of the moment happens to be. And with a few thousand respondents, a headline move of two or three points sits comfortably inside what sampling variation alone can produce. The Conference Board itself cautions against reading small monthly movements as signal. A chart that headlines them is amplifying measurement error, whether its author knows it or not.
What the survey never observes
Here is the boundary of the instrument. The questionnaire never sees a receipt, a payroll stub, or a bank statement. It records answers to opinion questions, and opinions cost the respondent nothing to give. That puts the CCI in the same family as a horse-race poll: a carefully sampled measurement of what people say, with no mechanism for verifying what they will actually do. So when a chart overlays the CCI on retail sales or GDP and suggests the sentiment line “leads” the hard line, it is asserting a causal claim the survey was never designed to test. The chart can look persuasive. It is still overreaching.
What a Prediction Would Actually Require
For a sentiment reading to function as a prediction, a whole chain has to hold: stated attitudes would need to translate into spending intentions, intentions into actual outlays, and household outlays in aggregate into the hard measures published by BEA, Census, and BLS. Each link leaks. Attitudes respond to salient prices — gasoline above all — and to political identity. Spending responds to income, credit conditions, and balance sheets. The empirical record shows a positive but loose association between sentiment and subsequent consumption growth, punctuated by some well-documented false positives. The gap between mood and money is not a footnote to these series. It is the central fact about them.
The June 2022 test case
The cleanest recent demonstration arrived in mid-2022. The University of Michigan’s Consumer Sentiment Index fell to 50.0 in June 2022, the lowest reading in a series extending back to the early 1950s, and The Conference Board’s index slid sharply alongside it. If sentiment were a reliable leading indicator of behavior, a hard-data contraction should have followed. It did not. BEA’s Table 1.1.1 shows real personal consumption expenditures rising in every quarter of 2022. Census MARTS releases showed nominal retail sales growing year over year straight through the holiday season. BLS payroll counts kept expanding while the unemployment rate sat near five-decade lows. What had deteriorated was the price of gasoline — regular pump prices crossed $5 per gallon in June 2022 in EIA weekly data — along with the cumulative weight of inflation. The sentiment charts implied a recession the hard data never confirmed. Later commentary coined “vibecession” for the divergence. The coinage was glib; the gap it named was real and measurable.
Stated Opinion Behaves Like Polling Data
Readers of this site already work with election polls, and the analogy transfers almost exactly. A sentiment index is a cross-sectional poll of economic opinion, carrying everything a poll carries: sampling error, question-wording effects, mode effects, and house differences between survey organizations. Two of the distortions deserve names.
Partisan anchoring. Research by Atif Mian, Amir Sufi, and coauthors documented a sharp partisan divergence in economic expectations after the 2016 election: reported moods moved in opposite directions depending on the party of the sitting president, and the gap has widened across successive cycles. So when a sentiment chart shows a plunge immediately after an administration change, part of the movement may be political identity rather than economic experience. That matters enormously in an election year, and chart captions almost never disclose it.
Salience rather than measurement. UCLA’s Ed Leamer has observed that Michigan’s sentiment series tracks gasoline prices remarkably closely — in many stretches, more closely than it tracks the labor market. Gasoline is the one macro price most households encounter weekly, in foot-high numerals at the curb. A sentiment index is partly a high-frequency read on the salience of that price. That is useful information, so long as nobody mistakes it for a forecast of aggregate demand.
What Sentiment Measures Are Genuinely Good For
None of this makes the CCI useless. It makes the index an attitude instrument, and attitude instruments have honest jobs. Four of them:
- A high-frequency mood read. Monthly, on a fixed release schedule, available before most hard data covering the same period.
- Component spreads. The gap between the Expectations Index and the Present Situation Index often says more than the headline. Expectations sagging below current conditions is a different signal from everything falling together.
- Salience tracking. Paired with EIA pump-price data, sentiment maps what households are reacting to — which turns the 2022 divergence into an explainable story rather than a puzzle.
- A cross-check, not a substitute. Set beside BLS payroll growth, Census retail sales, and BEA consumption, a sentiment divergence is itself a finding worth reporting.
One detail from the publisher’s own methodology makes the point better than any outside critique could. Since 2012, The Conference Board’s Leading Economic Index has used the University of Michigan’s Index of Consumer Expectations as its consumer component — not the CCI’s own expectations series. Even the organization that publishes the headline index does not treat it as a leading input. That should set the ceiling for everyone else.
How to Read the Release Like an Analyst
This is the working checklist I apply before writing about any sentiment release on this site:
- Open the tables, not just the press release. The release summarizes; the tables separate Present Situation from Expectations and report the plans-to-buy components. Most of the analytical content lives there.
- Pair the two houses. The Conference Board surveys roughly 3,200 households on a six-month horizon; Michigan surveys roughly 600 with an expectations window of up to five years, publishing preliminary figures mid-month and finals at month’s end through its Surveys of Consumers data portal. When both houses agree, the mood shift is probably real. When they diverge, report the divergence as a finding rather than choosing whichever series fits your chart.
- Check moves against the noise band. A two-point change in the headline is not a story. Look for multi-month trends and component-level confirmation.
- Reproduce before you publish. Both series are on FRED — CONCONF for the Conference Board index, UMCSENT for Michigan. Download, replot, and verify any chart you intend to critique or republish. Reproduction catches truncated axes and convenient start dates faster than any other technique I know.
- Standardize before comparing. If you must put sentiment beside a growth rate, convert both to z-scores or year-over-year changes and label the transformation in the caption. An index level against a growth rate on dual axes is a chart that has already chosen its own conclusion.
Chart Criticism: Five Recurring Failures
After several years of checking sentiment coverage, the same five failures keep turning up:
- Dual-axis manufacture of correlation. Give yourself two free axes and a scaling slider, and you can make the CCI line kiss any other line you like. The visual match is an artifact of the scaling choices, not the data.
- Recession shading as causal insinuation. Shaded NBER recession bars beneath a sentiment line imply the line “called” them. Sentiment has false positives — 2022 is a large one — and an honest caption discloses that record.
- The missing base-year note. Charts that drop the 1985 = 100 benchmark invite readers to interpret 100 as neutral or healthy. It is neither; it is a benchmarking convention.
- Levels against growth rates. Plotting an index level beside real PCE growth or retail growth compares quantities with different units and different variances. Standardize, or do not publish the overlay.
- Headlining noise. “Consumer confidence plunges,” run on a 2.7-point move inside the sampling band, is a headline about measurement error. Disclose the band or drop the adjective.
The better chart is unglamorous and reproducible: both sentiment series standardized, real PCE growth standardized, everything on a single axis, with a caption naming the 2022 divergence as the most instructive episode in the modern record. A scatter of sentiment against spending growth at various lags, with the R² reported even when it disappoints, is more honest than any dual-axis overlay. Boring charts that survive reproduction are the goal of this column. I’m comfortable with boring.
Frequently Asked Questions
A few of these questions come up every time the column touches sentiment data.
Is the Consumer Confidence Index a leading indicator of recession?
Not on its own. The headline CCI is best read as a coincident measure of the national mood. The expectations components carry more forward-looking content — Michigan’s expectations series has sat inside the Leading Economic Index since 2012 — but the record includes prominent false positives, including the 2022 sentiment collapse that was followed by continued growth in real consumer spending. Treat a sentiment drop as one corroborating data point, never a standalone forecast.
How is the Conference Board index different from Michigan’s Consumer Sentiment Index?
Sample size (about 3,200 households versus roughly 600), expectations horizon (six months versus up to five years), fielding schedule, and base year (1985 = 100 versus the first quarter of 1966 = 100). The two correlate strongly month to month but disagree on levels, and the disagreements — driven by question wording and timing — are the survey-house equivalent of polling house effects.
Why did sentiment hit record lows in 2022 while consumer spending kept growing?
Because the two measure different things. Sentiment tracked salient prices, gasoline above all, along with political identity; spending tracked income growth, credit access, and household balance sheets. BEA data show real personal consumption expenditures rising through every quarter of 2022 even as Michigan’s index posted the lowest readings in its history.
How big a monthly change in the CCI is meaningful?
A move of two or three points in the headline sits inside the range sampling variation can produce. Look for multi-month trends, component-level confirmation — Present Situation and Expectations moving together — and agreement between the two major survey houses before treating any single monthly change as signal.
Where can I get the data to reproduce these charts?
The Conference Board publishes the full release and tables on its consumer confidence page; the University of Michigan maintains a public data portal for the Surveys of Consumers; and FRED carries both series — CONCONF and UMCSENT — for immediate download.
Where This Column Goes Next
This article opens a recurring Chart Check lane on sentiment and expectations data at JRL Charts Online. The next installment walks through the 2022 sentiment–spending divergence step by step in FRED: pulling CONCONF and UMCSENT, downloading real PCE from BEA, standardizing both, and building the single-axis overlay an honest version of this story requires, with every transformation listed so you can replicate it. A short glossary of survey terms — diffusion index, base year, house effect — is planned alongside it. If you run across a sentiment chart worth checking, send it in. The standing rule of this column applies: critique the method, never the messenger.