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Consumer confidence index
Consumer confidence index
Consumer confidence index
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A consumer confidence index (CCI) is an economic indicator published by various organizations in several countries.

In simple terms, increased consumer confidence indicates economic growth in which consumers are spending money, indicating higher consumption. Decreasing consumer confidence implies slowing economic growth, and so consumers are likely to decrease their spending. The idea is that the more confident people feel about the economy and their jobs and incomes, the more likely they are to make purchases. Declining consumer confidence is a sign of slowing economic growth and may indicate that the economy is headed into trouble.

Usage

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Manufacturers, retailers, banks and the government monitor changes in the CCI in order to factor in the data in their decision-making processes. While index changes of less than 5% are often dismissed as inconsequential, moves of 5% or more often indicate a change in the direction of the economy.

A month-on-month decreasing trend suggests consumers have a negative outlook on their ability to secure and retain good jobs. Thus, manufacturers may expect consumers to avoid retail purchases, particularly large-ticket items that require financing. Manufacturers may pare down inventories to reduce overhead or delay investing in new projects and facilities. Likewise, banks can anticipate a decrease in lending activity, mortgage applications and credit card use. When faced with a down-trending index, the government has a variety of options, such as issuing a tax rebate or taking other fiscal or monetary action to stimulate the economy.

Conversely, a rising trend in consumer confidence indicates improvements in consumer buying patterns. Manufacturers can increase production and hiring. Banks can expect increased demand for credit. Builders can prepare for a rise in home construction, and government can anticipate improved tax revenues based on the increase in consumer spending.

Consumer-demand surveys versus consumer-confidence and -sentiment surveys

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Consumer-demand surveys are interview-based statistical surveys that measure the percentage of households that will buy a car, white goods, PCs, TVs, home furnishings, kitchenware, or toys in, for example, the next three-month period. The surveys provide a percentage of those who will purchase more, less, or the same amount of food and clothing in the next three months than in the corresponding period the year before. If you ask people about their purchasing behavior within the coming six or 12 months, there will be more of those who "hope to be able to buy", than if consumers are asked about what they will purchase in the next three months. The shorter the time spans, the closer to actual behavior.

Consumer confidence and sentiment surveys measure how people are doing financially, how they look at the overall economy of the country or business conditions in the country, if they think that the government is doing a good or a poor job and if people think that it is a good or a bad time to buy a car or to buy or sell a house.

When the business cycle is fairly stable, consumer demand surveys and consumer confidence and sentiment indices will often correlate closely and indicate the same direction of the economy, but in times with a high degree of economic or political uncertainty or during a prolonged crisis, the two types of consumer surveys might differ significantly. In 2011, confidence and sentiment surveys went up from March to April, while consumer demand surveys dropped significantly. In August 2011, the confidence and sentiment surveys dropped significantly and stayed low during September and October, while consumer demand surveys showed resilience, a development confirmed later by official statistics.

A 2022 study found that the consumer confidence index always plays a positive and statistically significant function in the development of consumption.[1]

In Canada

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The Conference Board of Canada's index of consumer confidence has been ongoing since 1980. It is constructed from responses to four attitudinal questions posed to a random sample of Canadian households. Those surveyed are asked to give their views about their households' current and expected financial positions and the short-term employment outlook. They are also asked to assess whether now is a good or a bad time to make a major purchase, such as a house, car or other big-ticket items.

In Indonesia

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Consumer Survey-Bank Indonesia (CS-BI) is a monthly survey that has been conducted since October 1999 by Bank Indonesia.[2] The survey represents the consumer confidence about the overall economic condition, general price level, household income, and consumption plans three and six months ahead. Since January 2007, the survey is conducted with approximately 4,600 household respondents (stratified random sampling) in 18 cities: Jakarta, Bandung, Semarang, Surabaya, Medan, Makassar, Bandar Lampung, Palembang, Banjarmasin, Padang, Pontianak, Samarinda, Manado, Denpasar, Mataram, Pangkal Pinang, Ambon, and Banten. At a significance level of 99%, the survey has a sampling error of 2%. Data canvassing run through interviews by phone and direct visits in particular cities that is based on rotational system. The Balance Score Method (net balance + 100) has been adopted to construct the index, where the index above 100 points indicates optimism (positive responses) and vice versa. The consumer confidence index (CCI), is an average of the current economic condition index (CECI) and consumer expectation index (CEI).

Other indexes

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Danareksa conducts a monthly consumer survey to produce the Consumer Confidence Index.[3]

In the Republic of Ireland

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In the Republic of Ireland, KBC Bank Ireland (formerly IIB Bank) and the Economic and Social Research Institute (a think-tank) have published a monthly consumer sentiment index since January 1996.[4]

In the United States

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US consumer confidence index 1966–2012[needs update]

In the United States, The Conference Board, an independent economic research organization, issues monthly measures of consumer confidence based on 5,000 households. Such measurement is indicative of the consumption component level of the gross domestic product. The Federal Reserve looks at the CCI when determining interest rate changes.

Consumer confidence is defined by The Conference Board as the degree of optimism on the state of the United States economy that consumers are expressing through their activities of savings and spending. Global consumer confidence is not measured. Country-by-country analysis indicates huge variance around the globe. In an interconnected global economy, tracking international consumer confidence is a lead indicator of economic trends.[5]

The consumer confidence index started in 1967 and is benchmarked to 1985 = 100.[how?] The index is calculated each month on the basis of a household survey of consumers' opinions on current conditions and future expectations of the economy. Opinions on current conditions make up 40% of the index, with expectations of future conditions comprising the remaining 60%. In the glossary on its website, The Conference Board defines the Consumer Confidence Survey as "a monthly report detailing consumer attitudes and buying intentions, with data available by age, income and region".

Each month, The Conference Board surveys 5,000 US households. The survey consists of five questions that ask the respondents' opinions about the following:[6]

  1. Current business conditions
  2. Business conditions for the next six months
  3. Current employment conditions
  4. Employment conditions for the next six months
  5. Total family income for the next six months

Survey participants are asked to answer each question as "positive", "negative" or "neutral." The preliminary results from the consumer confidence survey are released on the last Tuesday of each month at 10am EST.

Once the data have been gathered, a proportion known as the "relative value" is calculated for each question separately. Each question's positive responses are divided by the sum of its positive and negative responses. The relative value for each question is then compared against each relative value from 1985. This comparison of the relative values results in an "index value" for each question.

The index values for all five questions are then averaged together to form the consumer confidence index; the average of index values for questions one and three form the present situation index, and the average of index values for questions two, four and five form the expectations index. The data are calculated for the United States as a whole and for each of the country's nine census regions.

Other indexes

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In addition to the Conference Board's CCI, other survey-based indices attempt to track consumer confidence in the United States:

Given the potential for sampling biases of individual survey reports, researchers and investors try sometimes to average the values of different index reports into a single aggregated measure of consumer confidence.

References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia

Consumer confidence index

View on Grokipedia
from Grokipedia
The Consumer Confidence Index (CCI) is an economic indicator that quantifies prevailing consumer sentiment regarding current business conditions, employment opportunities, and short-term income expectations through standardized monthly surveys, with the primary U.S. measure compiled by The Conference Board from responses by approximately 3,000 households. The index combines a Present Situation Index, evaluating perceptions of the existing economic environment, and an Expectations Index, projecting future developments, normalized to a base value of 100 in 1985, where readings above 100 signal optimism and below indicate pessimism. As of February 2026, the latest available reading stood at 91.2 (1985=100), up 2.2 points from a revised 89.0 in January 2026. This value was released on February 24, 2026, with the March 2026 index scheduled for release on March 31, 2026. As consumer expenditures account for about two-thirds of U.S. gross domestic product, the CCI functions as a leading predictor of spending behavior on durable goods, housing, and services, with empirical correlations showing elevated confidence levels preceding expansions in retail sales and economic growth. Initiated by The Conference Board as a bimonthly gauge in 1967 and transitioned to monthly in 1977, the CCI has tracked sentiment across multiple business cycles, though its Expectations component exhibits volatility and occasional divergence from actual outcomes, underscoring its role as a sentiment barometer rather than a deterministic forecast.

Definition and Conceptual Foundations

Core Definition and Purpose

The Consumer Confidence Index (CCI) is an that quantifies the prevailing level of optimism or pessimism among consumers regarding current conditions, labor market prospects, , and short-term economic outlook. Derived from structured surveys of representative samples, it aggregates responses to targeted questions about perceptions of economic and future expectations, yielding a normalized index value typically benchmarked against a base period such as 1985=100. This measure reflects the psychological dimension of economic , where sentiment influences on durables and services beyond immediate necessities. The core purpose of the CCI is to serve as a forward-looking gauge of , given that consumer expenditures constitute the largest share of GDP in consumer-driven economies. By capturing attitudinal shifts that precede behavioral changes, such as increased retail purchases or deferred investments, the index aids in predicting economic cycles; elevated readings often correlate with accelerating growth, while sharp declines have presaged downturns, as observed prior to recessions. Policymakers at central banks and fiscal authorities monitor it to calibrate interest rates or stimulus, while businesses use it to adjust production and . Investors treat it as a sentiment , with divergences from hard data like rates highlighting potential misalignments in market expectations. Variations in CCI construction exist across providers, yet all prioritize empirical polling over speculative modeling to ground the indicator in direct input. For example, indices emphasize relative responses—favorable minus unfavorable—to isolate directional trends, mitigating absolute opinion volatility. This approach underscores the causal link between and spending: empirically, a 1-point CCI rise has been associated with modest upticks in consumption growth, though is probabilistic rather than deterministic, as external shocks like or geopolitical events can override sentiment.

Distinction from Consumer Demand and Sentiment Surveys

The (CCI) measures subjective perceptions of current economic conditions and expectations for the future, derived from survey responses on topics such as prospects, conditions, and , rather than observable purchasing behavior. In contrast, quantifies actual expenditures on , typically tracked through objective data like monthly retail sales figures from the U.S. Census Bureau, which reported $709.8 billion in total sales for August 2025. While elevated CCI levels often correlate with subsequent rises in demand—reflecting anticipated spending intentions—divergences occur when perceptual optimism does not translate into action, as seen during periods of high or tightened credit, where consumers delay purchases despite positive sentiment. CCI, while based on sentiment surveys, differs from broader consumer sentiment surveys in methodology, scope, and emphasis. The Conference Board's CCI, for example, polls approximately 3,000 U.S. households monthly on five principal questions covering present-day situations and six-month expectations, yielding separate sub-indices for current conditions (weighted 40%) and expectations (60%), with a baseline of 100 from 1985. By comparison, the of Michigan's Sentiment Index surveys a smaller sample of 500 households with more extensive queries on personal financial trajectories and economic policies, resulting in an index that historically trends lower—averaging about 20 points below CCI—and focuses less on explicit buying intentions for durables like automobiles or homes. These distinctions arise from varying question design and respondent weighting, leading to occasional divergences; for instance, in September 2025, CCI stood at 98.7 while sentiment was 70.1, highlighting how CCI's labor-market focus may yield more stable readings amid policy uncertainty. Such methodological variances underscore that CCI prioritizes forward-looking confidence as a predictor of , whereas general sentiment surveys may capture dissatisfaction or policy-specific anxieties without direct ties to consumption plans, potentially amplifying volatility from transient events like election cycles. Empirical analyses, including those from the Federal Reserve Bank of , indicate that while both serve as leading indicators, CCI's inclusion of purchase intention questions provides marginally stronger short-term forecasts for retail demand compared to sentiment aggregates alone.

Historical Development

Origins and Early Pioneers

The concept of systematically measuring consumer confidence emerged in the post-World War II era as sought to incorporate psychological factors into macroeconomic forecasting, recognizing that consumer spending drives a significant portion of economic activity. Hungarian-American and George Katona, working at the of Michigan's Survey Center (now part of the Institute for Social Research), pioneered the first empirical surveys of consumer attitudes in 1946. These initial annual surveys, which evolved to quarterly in 1952, queried households on perceptions of current economic conditions, personal finances, and short-term buying intentions, laying the groundwork for quantitative indices by linking subjective expectations to observable spending behavior. Katona's approach emphasized , arguing that consumer decisions hinge on perceived rather than objective realities, a departure from purely aggregate data models prevalent at the time. Katona's Index of Consumer Sentiment, first computed from these surveys, provided an early benchmark for predicting durable goods purchases and overall demand fluctuations, with showing correlations to recessions as early as the . By the mid-1960s, his had demonstrated predictive value, influencing policymakers during economic expansions and contractions, such as the 1960-1961 downturn. This university-led initiative marked the of formalized consumer confidence measurement, prioritizing direct empirical polling over indirect proxies like retail sales . In parallel, , a non-profit research organization, developed its own Consumer Confidence Index in 1967 to offer a standardized, -oriented gauge amid growing postwar affluence and credit expansion. Unlike Katona's academic focus on psychological dynamics, 's survey targeted broader sentiment on , , and conditions, surveying approximately 3,000 households monthly from its outset. This index quickly gained traction among investors and officials for its timeliness, with initial readings reflecting optimism in the late boom before signaling downturns like the 1970 recession. Together, these efforts by Katona and established consumer confidence indices as distinct tools for anticipating shifts, distinct from contemporaneous sentiment polls by entities like the Opinion Research Corporation.

Evolution in the United States

The University of Michigan's Index of Consumer Sentiment, developed by psychologist George Katona in 1946, marked an early milestone in systematic consumer attitude measurement in the United States, initially focusing on post-World War II economic behavior and evolving into a quarterly survey by the that gauged perceptions of current conditions and future expectations. This index, based on telephone interviews with approximately 500 respondents, emphasized psychological factors influencing spending and laid foundational principles for later surveys by linking sentiment to actual economic outcomes. In 1967, launched its Consumer Confidence Survey (CCS) as a bimonthly mail-based poll of 3,500 households, aiming to provide a broader, more frequent alternative to academic measures and quickly establishing itself as a key private-sector indicator of economic health. By June 1977, the CCS transitioned to monthly releases to better capture economic fluctuations, expanding its sample to 5,000 households and incorporating questions on present situation and expectations indices, with the overall Consumer Confidence Index normalized to a base of 1985=100. This shift enhanced its utility for policymakers and investors, as the index demonstrated for recessions, often declining sharply prior to downturns like those in 1980, 1990, and 2001. Methodological refinements continued into the , including a partial shift from to and online surveys starting in the to improve response rates and representativeness, while maintaining historical continuity by keeping pre-2021 data unchanged after a 2021 update that adjusted weighting for demographics and incorporated additional expectations questions on and . The Conference Board's index gained prominence over the Michigan survey due to its larger sample and alignment with business cycles, influencing decisions and becoming a staple in economic reporting, though both indices have shown occasional divergences attributable to question phrasing differences rather than underlying trends. Despite criticisms from some economists questioning its forward-looking accuracy amid structural economic changes like , empirical analyses confirm its correlation with GDP growth and consumption with lags of 3-6 months.

Global Adoption and Standardization

The adoption of consumer confidence indices beyond the began in during the post-World War II era, with early surveys emerging in the late 1940s and gaining momentum through institutional coordination in the 1970s and 1980s. The launched the Joint Harmonised Programme of Business and Consumer Surveys, which standardized across member states using a common set of questions focused on households' financial situation, general economic outlook, expectations, and major purchases over the next 12 months. This , implemented monthly since the program's , ensured methodological consistency by balancing responses (e.g., positive minus negative percentages, adjusted for "don't know" replies) to produce comparable indicators, with data series extending back to 1985 for the euro area. By the 1990s, similar surveys proliferated in other countries, driven by recognition of consumer expectations as leading indicators of . The Organisation for Economic Co-operation and Development () played a pivotal role in global starting in the late , compiling and normalizing national consumer confidence series from member and partner economies to enable cross-border . transforms disparate national indices—often based on varying survey designs—into a standardized form with a long-term mean of 100 and standard deviation of 10, typically over reference periods like 1961–2010, by applying z-score normalization: z=x−μσz = \frac{x - \mu}{\sigma}, where xx is the national value, μ\mu the historical mean, and σ\sigma the standard deviation, then rescaling to the target parameters. This output-focused approach accommodates input differences (e.g., question sets or sample sizes) while prioritizing comparability of final indicators, distinguishing it from the EU's input-harmonized questionnaire. As of the 2000s, coverage extended to over 30 countries, integrating into composite leading indicators for forecasting consumption and GDP trends. By the 21st century, consumer confidence surveys had diffused to at least 45 countries worldwide, encompassing nearly all developed economies and select emerging markets such as , , and , often adapted by national statistical offices or central banks. Standardization efforts beyond official bodies remain partial, with private firms like and producing global aggregates from proprietary or licensed national data, though these lack the uniform normalization of metrics and exhibit variability due to non-harmonized sampling (e.g., ' 29-country index since 2010). Despite widespread use, challenges persist in full comparability, as economic structures and cultural response biases influence raw data, prompting ongoing research into output harmonization over rigid question alignment. This global framework underscores consumer confidence's role in international economic monitoring, with standardized indices correlating empirically with cross-country consumption growth differentials.

Methodology and Data Collection

Survey Design and Questions

The design of consumer confidence surveys typically involves monthly or polling of representative samples, stratified by demographics such as age, , , and urban/rural residence to ensure national coverage. Samples range from 500 to 5,000 respondents, with response rates adjusted for non-response bias through weighting. Questions focus on subjective perceptions rather than objective data, capturing qualitative assessments of economic conditions to gauge potential spending , as consumers drive about 70% of U.S. GDP. In the United States, the Conference Board's Consumer Confidence Survey, conducted since 1967, queries approximately 5,000 households on five specific questions, divided into present situation (two questions) and expectations (three questions). These are: (1) appraisal of current conditions as better, same, or worse than a year ago; (2) appraisal of current conditions in their area; (3) expectations for conditions six months hence; (4) expectations for conditions six months hence; and (5) expectations for total family six months hence. Responses use qualitative scales (e.g., "better," "worse," "same"), with "don't know" options excluded from index calculations to emphasize decisive views. The University of Michigan's Surveys of Consumers, ongoing since 1946 and published monthly since 1952, employs a more extensive questionnaire of about 50 core questions across 500 interviews, but derives its Index of Consumer Sentiment from five principal questions assessing personal finances and broader economic conditions. These include: (1) current personal financial situation relative to a year ago; (2) expected personal financial situation a year ahead; (3) appraisal of current business conditions; (4) expected business conditions a year ahead; and (5) favorability of buying conditions for durable goods like houses and cars. The survey uses random-digit dialing for probability sampling, with recent shifts to online modes requiring methodological adjustments for continuity, as phone-based responses historically showed higher sentiment levels due to respondent selection effects. Internationally, harmonized designs under frameworks like the or standardize questions for comparability, often mirroring U.S. models but adapted for local contexts, such as including eurozone-specific expectations. For instance, the 's consumer confidence indicator aggregates responses to questions on financial situation, general economic situation, expectations, and major purchase intentions over the next 12 months, polled via national statistical offices. These designs prioritize forward-looking expectations, as empirical analysis shows they correlate more strongly with future consumption than backward-looking views, though surveys can exhibit volatility from or transient events like policy announcements.

Index Calculation and Normalization

The calculation of consumer confidence indices relies on survey data from representative consumer samples, employing a diffusion index methodology to quantify the balance between optimistic and pessimistic responses. For each core question—typically covering perceptions of current business conditions, employment prospects, and future economic outlook—a relative score is computed as the of positive responses minus the of negative responses, divided by the corresponding base-period value and multiplied by 100 to form an index component. Neutral or "don't know" responses are generally excluded from the positive-negative differential but contribute to the denominator in some formulations, ensuring the score reflects the intensity of sentiment divergence. Sub-indices are then derived by averaging the relative scores of grouped questions: for instance, a present situation sub-index from queries on current economic conditions and a expectations sub-index from forward-looking ones on and . The composite index aggregates these, often as an unweighted average or with fixed weights (e.g., greater emphasis on expectations in some models to capture forward momentum), without logarithmic transformations or advanced that might introduce model-dependent biases. In the Consumer Confidence Index, the composite is the average of its present situation and expectations sub-indices, based on responses to five specific questions from approximately 3,000 U.S. households monthly. Similarly, the Index of Consumer Sentiment averages relative scores across five principal questions, supplemented by supplementary ones for robustness, from a telephone survey of about 500 households yielding around 300 usable responses per month. Normalization standardizes the composite index to a value of 100 during a reference base period, facilitating intertemporal and cross-index comparisons by anchoring historical averages. For the index, this base is 1985, selected for its representation of stable post-recessionary growth, with the index value computed as the average of monthly figures that year set to 100. The index uses the first quarter of 1966 as its base, reflecting early data availability and normalized via the of relative scores across questions. This scaling preserves the raw sentiment differentials while enabling readings above 100 to indicate above-base optimism and below to signal pessimism, though base selection can subtly influence trend interpretations if economic structures shift over decades. Variations exist internationally, such as the OECD's harmonized approach aligning bases to recent years for comparability, but core diffusion-based normalization remains consistent to avoid arbitrary rescaling that could mask underlying causal drivers like volatility.

Frequency, Revisions, and Data Sources

The leading consumer confidence indices, such as Consumer Confidence Index (CCI) and the Index of Consumer Sentiment (ICS), are compiled and released on a monthly basis to capture timely shifts in household attitudes. Other indices, including those standardized by the across member countries, follow monthly schedules where national statistical agencies conduct surveys, though some or regional variants operate quarterly to align with data availability constraints. For CCI, surveys are conducted online by Toluna using a panel exceeding 36 million consumers, targeting approximately 3,000 completed responses per month across four weekly waves, with data cutoff around the 21st of the reference month. The index is released as a single figure on the last Tuesday of each month at 10:00 a.m. ET, reflecting seasonally adjusted responses without a formal preliminary release; however, minor revisions to the prior month's data occur occasionally with additional responses incorporated the following month, typically involving an extra 1,000 respondents to refine estimates. In contrast, the ICS features a two-stage release process: a preliminary estimate issued on the second Friday of the month based on initial survey responses, followed by a final revision on the fourth Friday incorporating expanded data. This structure allows for adjustments reflecting late-arriving responses, as evidenced by the October 2025 preliminary reading of 55.0 being revised downward to 53.6 in the final. The underlying data derive from the Surveys of Consumers, a longstanding telephone-based poll of roughly 500 households, focusing on personal financial assessments and economic outlooks. Data sources for consumer confidence indices universally rely on direct household surveys rather than administrative records, ensuring primary insights into subjective perceptions, though methodological shifts—such as The Conference Board's transition from / to online in 2021—have prompted benchmark adjustments to maintain comparability, including a one-time 1.8-point downward shift in the CCI series. These surveys prioritize representative national samples, often stratified by demographics, to minimize bias, with response rates and weighting schemes disclosed to support transparency.

Major Indices by Region

United States Indices

The maintains two leading consumer confidence indices: the (CCI) and the (ICS). These surveys capture household perceptions of current economic conditions and future expectations, serving as gauges of potential spending behavior. Both indices aggregate responses to targeted questions on personal finances, business climates, and employment prospects, though they employ distinct methodologies and emphases. The Conference Board CCI, launched in 1967 initially as a bimonthly mail survey before transitioning to monthly telephone polling, draws from approximately 5,000 households. It splits into the Present Situation Index, evaluating current business and labor conditions in respondents' local areas, and the Expectations Index, projecting short-term outlooks for income, business expansion, and job availability. Normalized to a base of 1985=100, the composite index reflects weighted averages of these components, with local framing in questions like job availability "in your area" fostering a regionally attuned perspective. The survey prioritizes labor market signals, often aligning more closely with employment data than inflationary pressures. In contrast, the ICS originated in the late 1940s under George Katona to integrate psychological factors into , evolving to monthly releases with preliminary and final estimates from surveys of about 500 households. Questions probe national economic conditions, personal financial trajectories, and buying climate for durables, with heavier weighting toward expectations—such as anticipated price changes over the next year—compared to the CCI. Indexed to 1966=100, it includes an Index of Consumer Expectations component designated by the U.S. Department of Commerce as a monthly since 1989. This national scope and sensitivity distinguish it, often yielding lower readings than the CCI during periods of rising prices. Key methodological variances influence their trajectories and interpretations:
AspectConference Board CCIUniversity of Michigan ICS
Inception1967 (bimonthly, later monthly)Late 1940s (monthly since 1978)
Sample Size~5,000 households~500 households
Survey ModeMonthly telephoneTwo-stage telephone (preliminary/final)
Geographic FocusLocal ("in your area")National
Key EmphasisLabor market, expectations
Base Year1985=1001966=100
ComponentsPresent Situation, ExpectationsCurrent, Expectations (Commerce-designated)
These differences can lead to divergences; for instance, the CCI typically registers higher values and greater volatility, better capturing job-related , while the ICS proves more responsive to cost-of-living concerns. Both correlate with aggregate consumption but face scrutiny for short-term predictive reliability amid structural economic shifts.

Conference Board Consumer Confidence Index

The Consumer Confidence Index (CCI) measures U.S. consumers' perceptions of prevailing and expected and labor market conditions, serving as a gauge of economic sentiment. Developed by , a non-profit organization, the index originated in 1967 as a bimonthly measure and transitioned to monthly publication to provide timelier insights into consumer attitudes. The CCI derives from a monthly telephone survey of approximately 3,000 households, selected through random-digit dialing and stratified to represent the U.S. by demographics including age, , and . Responses inform two sub-indices: the Present Situation Index (PSI), based on appraisals of current business conditions and employment availability; and the Expectations Index (EI), assessing outlooks for business and employment six months ahead plus total family over the same period. Each sub-index averages diffusion-style scores from its constituent questions, where the score equals the proportion of positive responses divided by the sum of positive and negative responses (excluding neutrals), seasonally adjusted and normalized to the 1985 average equaling 100. The overall CCI equals the simple average of the PSI and EI, also base 1985=100, with values above 100 indicating greater optimism than the base period. Post-stratification weights adjust raw data for non-response biases and alignment with demographics, while the survey incorporates supplementary questions on buying intentions for durables, homes, and autos, though these do not factor into the core CCI. The index releases on the last Tuesday of each month, covering the prior month's data, and influences assessments of potential given that personal consumption comprises about 70% of U.S. GDP. Higher CCI readings correlate empirically with increased retail sales and , though the index's forward-looking Expectations component can amplify volatility from transient sentiment shifts. The most recent reading, for February 2026, stood at 91.2 (1985=100), up 2.2 points from a revised 89.0 in January 2026. It was released on February 24, 2026. The March 2026 index is not yet available, as it is scheduled for release on March 31, 2026.

University of Michigan Index of Consumer Sentiment

The Index of Consumer Sentiment is a monthly derived from the Surveys of Consumers, conducted by the 's Institute for Social Research. Established in 1946, it gauges consumer attitudes toward personal finances and broader economic conditions through and online interviews with approximately 500 households nationwide. The index serves as a forward-looking measure, with indicating its components correlate strongly with future patterns. The index is constructed from responses to five core questions: perceptions of recent changes in household financial situations; expectations for household finances over the next year; short-term economic outlook; long-term economic outlook (five years ahead); and current buying conditions for major household durables. Each question's score is computed as the difference between the proportion of favorable and unfavorable responses, multiplied by 100, then averaged across the five questions and normalized to a base value of 100 in 1966. It comprises two sub-indices: the Index of Current Economic Conditions, emphasizing present assessments, and the Index of Expectations, focusing on future outlooks, with the overall index weighting these roughly equally. Preliminary results are released mid-month based on two-thirds of the sample, followed by final figures at month-end incorporating the full dataset. Methodological updates, such as the integration of web-based responses starting in April 2024, have maintained high correlation (0.97) with prior telephone-only series, ensuring continuity despite shifts in data collection. The index's is approximately ±3.29 points at 95% for monthly readings, reflecting its reliance on probabilistic sampling.

European and OECD Indices

The European Commission's Consumer Confidence Indicator (CCI), produced by the Directorate-General for Economic and Financial Affairs, aggregates survey responses from households across member states and applicant countries to gauge perceptions of the economic outlook. It forms a key component of the broader Economic Sentiment Indicator and is calculated monthly as the of balances from four standardized qualitative questions concerning households' financial situation over the past year, expected financial situation over the next year, general economic situation over the next 12 months, and expected trends. The balance method subtracts the proportion of negative responses from positive ones, yielding values typically ranging from -100 (universal ) to +100 (universal ), with long-term averages around -11 for the aggregate. Surveys are harmonized and conducted by national partner institutes, ensuring comparability, though coverage distinguishes between the full (currently 27 members) and the euro area subset. Flash estimates of the EC CCI are released mid-month, followed by final figures incorporating additional data, with revisions possible but infrequent due to the qualitative nature of responses. This indicator has tracked cyclical shifts since the 1980s, declining sharply during events like the (to below -30) and the 2020 pandemic (to around -25), reflecting causal links to income uncertainty and spending restraint rather than mere sentiment volatility. National variations persist—e.g., higher confidence in versus —but the aggregate prioritizes empirical survey balances over weighted GDP adjustments, avoiding over-reliance on potentially biased macroeconomic priors. The Organisation for Economic Co-operation and Development (OECD) publishes a standardized Consumer Confidence Index (CCI) drawing from national tendency surveys of OECD member countries, including most European nations, to provide cross-country comparability on household expectations. Unlike the EC's balance-of-opinions approach, the OECD CCI normalizes raw survey data—typically from questions on personal finances, general economy, unemployment, and savings—by first converting quarterly series to monthly via interpolation, applying smoothing filters, setting long-term means to 100 with standard deviations of 10, and amplitude-adjusting to align with detrended GDP cycles. This process mitigates national methodological divergences but introduces smoothing that may lag real-time shifts, with values above 100 signaling optimism and potential consumption growth, and below indicating caution. OECD aggregates, such as for the euro area, update monthly and correlate with private consumption forecasts, though empirical tests show modest predictive power beyond GDP components due to forward-looking biases in responses. Coverage spans 38 members, emphasizing causal realism by linking confidence to verifiable drivers like trends rather than institutional narratives, with European sub-indices often mirroring EC patterns but standardized for global benchmarking. Both EC and indices rely on voluntary surveys of thousands per country, introducing non-response biases more pronounced in low-trust environments, yet their persistence as leading gauges stems from historical correlations with expenditure data over alternative quantitative metrics.

Indices in Other Countries

In , the National Bureau of Statistics (NBS) computes a monthly Consumer Confidence Index from surveys of approximately 6,000 urban households across 18 provinces and municipalities, assessing perceptions of current and future income, conditions, and major purchase intentions such as durable . The index is scaled from 0 (extreme pessimism) to 200 (extreme optimism), with a reading of 100 denoting neutrality; values above 100 signal optimism, as observed in early before declining amid economic pressures. This metric, initiated in 1990, correlates with retail sales trends but has faced scrutiny for potential underreporting due to state-influenced survey responses in a censored environment. India's (RBI) conducts a bi-monthly Consumer Confidence Survey covering around 6,000 urban households in 19 major cities, evaluating sentiments on the general economic situation, scenario, personal finances, prices, and spending. The survey yields a composite index alongside separate Current Economic Conditions Index and Future Expectations Index, both normalized around historical averages; for instance, the overall index rose to 96.5 in July 2025 from 95.4 in May, reflecting mild improvement in urban optimism. A parallel rural survey tracks semi-urban and rural households nationwide, highlighting disparities such as lower rural confidence tied to agricultural incomes. In , the Fundação Getulio Vargas (FGV) IBRE produces a monthly Consumer Confidence Index through face-to-face interviews with about 2,100 in seven metropolitan areas, querying views on personal finances, the economic outlook, and buying conditions for durables. The index, ranging typically from 0 to 200 with 100 as neutral, derives from balances of positive versus negative responses; it stood at 100.05 in September 2025, edging up amid policy shifts but remaining subdued by high interest rates and concerns. Complementary sub-indices track present situations and expectations, aiding forecasts of consumption, which constitutes over 60% of GDP. Russia's Federal State Statistics Service (Rosstat) compiles a quarterly Consumer Confidence Index from nationwide surveys of roughly 5,000 individuals aged 16 and older, focusing on assessments of current financial positions, expected income changes, and durable goods purchases. The index uses a balance method (positive minus negative responses, scaled -100 to +100), recording -9 in Q3 2025, indicative of persistent caution despite wartime fiscal supports boosting short-term stability. Alternative polls by the (VCIOM) provide similar sentiment gauges, though official data may reflect methodological adjustments for geopolitical volatility. In , the Bureau for Economic Research (BER), in partnership with First National Bank (FNB), issues a quarterly Consumer Confidence Index based on telephone surveys of 2,500 households across urban and rural areas, measuring net optimism on the , personal finances, and spending intentions via balance statistics. Ranging from -100 (universal pessimism) to +100, the index rebounded to -10 in Q2 2025 from a low of -20, buoyed by political transitions but hampered by exceeding 32%. Established in the , it serves as a leading indicator for retail trade, with readings below -6 historically signaling contractionary pressures.

Economic Applications and Impact

Role in Forecasting and Policy-Making

Consumer confidence indices function as leading economic indicators, providing insights into anticipated household spending patterns that comprise approximately 70% of U.S. gross domestic product. By capturing forward-looking expectations on income, employment, and business conditions, these indices enable forecasters to anticipate shifts in aggregate demand, often incorporating them into econometric models for short-term GDP projections. Empirical studies, such as those analyzing the Conference Board index, demonstrate its utility in predicting durable goods expenditures, with statistical significance observed in regressions controlling for lagged income and wealth variables. In macroeconomic , indices like Consumer Confidence Index and the Index of Consumer Sentiment are integrated into nowcasting frameworks, where they signal potential turning points in economic cycles ahead of hard data releases. For instance, declines in consumer confidence have historically preceded slowdowns in real consumption growth, offering incremental predictive power beyond traditional variables like rates. However, their forecasting value is context-dependent; from branches indicates modest improvements in spending forecasts when sentiment data supplement , though they do not consistently outperform simpler autoregressive models in all periods. Central banks and fiscal authorities utilize consumer confidence metrics to inform monetary and stabilization policies, viewing sustained drops as harbingers of reduced spending that may necessitate easing measures. The U.S. , for example, references these indices in assessing demand pressures and expectations, as evidenced in regional presidents' analyses linking confidence rebounds to observed consumption upticks following policy adjustments. In the euro area, the European Central Bank's short-term GDP forecasts incorporate confidence indicators like the Economic Sentiment Indicator, which correlates with consumption dynamics across member states. Policymakers also leverage these gauges for forward guidance, calibrating paths to counteract sentiment-driven contractions, though they remain auxiliary to core data such as and metrics.

Empirical Correlations with Spending and Growth

Empirical studies demonstrate a positive but modest between major consumer confidence indices and subsequent household spending, with evidence of predictive content beyond standard economic fundamentals such as , , and . For the , Consumer Confidence Index exhibits with total personal consumption expenditures and durable goods spending, boosting adjusted R² by 9% and 15%, respectively, in in-sample regressions (p<0.01). Out-of-sample forecasting from 1982 to 1996 shows this index reducing root-mean-square errors by 10% for overall consumption compared to benchmarks excluding confidence. In contrast, the Index of Consumer Sentiment displays limited additional explanatory power for spending categories after controlling for fundamentals. Pre-pandemic data reveal a of approximately 0.6 between index and U.S. consumption growth. For the euro area, consumer confidence explains about 10% of consumption variation in simple models and retains incremental predictive value when augmented with fundamentals like interest rates and , with shocks to confidence accounting for up to 10% of spending variance over short horizons. Consumer confidence indices also correlate positively with , often serving as components in broader sentiment measures that enhance GDP forecasts. In European economies, the Economic Sentiment Indicator—which incorporates consumer confidence—reduces short-term real GDP growth forecast errors by 20-30% relative to autoregressive benchmarks, with particular efficacy in , , and other major countries using Kalman filter approaches. Empirical analyses across nations confirm a long-run cointegrating relationship between consumer confidence and GDP, alongside evidence that confidence shocks amplify growth effects during recessions and low-confidence periods. For the U.S., confidence surveys reflect expectations of income and non-stock wealth growth, indirectly linking to aggregate output via spending channels, though direct GDP predictability weakens when isolating consumer-specific components from broader surveys. These correlations underscore confidence's role in capturing forward-looking perceptions, yet its standalone forecasting power diminishes after accounting for observable macroeconomic variables.

Influence on Financial Markets

Releases of major consumer confidence indices, such as the Consumer Confidence Index and the Index of Consumer Sentiment, often trigger immediate responses in equity markets, as these metrics signal prospective household spending patterns that drive approximately 70% of U.S. GDP. Empirical analyses reveal a positive correlation between consumer confidence levels and returns, with bidirectional evident in the United States, where rising confidence anticipates higher corporate earnings through increased consumption, while stock gains in turn bolster household effects and optimism. For instance, unexpected declines in the indices have been linked to contemporaneous drops in stock indices; the 's index fell to 94.2 in September 2025—a five-month low and below consensus forecasts—prompting a retreat in the amid heightened fears. Conversely, stronger readings, like the rebound to 102 in May 2024, have supported market advances by alleviating concerns over demand weakness. In fixed-income markets, consumer confidence announcements influence bond yields through channels of expected and growth. Low sentiment correlates with elevated consumer worries over borrowing costs, often pressuring yields downward as investors anticipate slower and potential monetary easing; studies incorporating sentiment data into models demonstrate improved predictive accuracy, with negative surprises amplifying volatility in long-term Treasuries. The indices' components on expectations and conditions further transmit signals, as persistent pessimism can reinforce disinflationary trends, flattening s. Currency markets exhibit asymmetric reactions to confidence data, with declines exerting greater downward pressure on the U.S. dollar against major counterparts due to reduced appeal for foreign investment amid subdued growth prospects. Event studies of announcements confirm statistically significant impacts on exchange rates, where negative surprises weaken the dollar more than positive ones strengthen it; for example, the index's downward revision to 53.6 in October 2025 signaled headwinds for the USD, reflecting broader caution on consumption-driven recovery. Higher sentiment, by contrast, draws capital inflows and appreciates the currency via anticipated economic vigor. These influences stem partly from the indices' inclusion of direct consumer outlooks on stock prices and interest rates, which markets interpret as a gauge of retail investor positioning and reinforce feedback loops between sentiment and asset valuations. However, reactions can diverge from fundamentals during periods of wealth-driven optimism, as seen in 2025 when record highs coincided with cracking confidence, highlighting the indices' role in amplifying short-term volatility rather than always dictating long-term trends.

Criticisms, Limitations, and Debates

Predictive Accuracy and Leading Indicator Status

Empirical assessments of consumer confidence indices, such as the and the , indicate limited and inconsistent predictive accuracy as standalone leading indicators for economic variables like household spending and GDP growth. A study found that while these indices can marginally improve forecasts of nondurable expenditures in certain model , their out-of-sample power diminishes when controlling for and effects, suggesting much of the apparent predictability reflects contemporaneous economic conditions rather than forward-looking insights. Similarly, a 2003 St. Louis Federal Reserve analysis concluded that consumer confidence surveys primarily mirror current economic states, providing coincident rather than leading signals, as sharp declines typically coincide with recessions rather than precede them by a consistent margin. For recession forecasting, sentiment measures exhibit some excess predictive content beyond traditional indicators like yield spreads or industrial production, with a 2015 study showing improved probability estimates for U.S. downturns when incorporating consumer sentiment. However, this edge is not robust across horizons or methodologies; a 2019 Federal Reserve evaluation of leading indicators ranked consumer confidence lower in accuracy for signaling compared to metrics like the , noting that simplistic thresholds (e.g., sentiment below 80) yield high false positives due to the rarity of recessions (only 12% of months since 1971). The index, in particular, demonstrates weaker forecasting for consumption categories relative to alternatives, per a Brookings analysis updated in later reviews, often failing to outperform univariate autoregressions beyond one quarter. Recent data underscores these limitations, with a persistent disconnect between low sentiment readings and resilient spending observed in 2023-2024, where outlays grew despite indices hovering near multi-year lows, implying sentiment captures psychological factors like media-driven more than causal drivers of . A 2025 Kansas City Federal Reserve study reinforced this by demonstrating that adding sentiment data to models using (e.g., retail , ) yields negligible improvements in spending growth forecasts, with root-mean-square errors differing by less than 0.1 points over 1-4 quarters. Policymakers and forecasters thus treat these indices cautiously, valuing them for qualitative context but relying primarily on hard data for quantitative predictions, as standalone use risks amplifying noise from survey volatility or respondent biases.

Sources of Bias and Volatility

Consumer confidence indices, such as those produced by and the , are susceptible to several methodological biases inherent in survey-based . arises when sampled households fail to represent the broader population, potentially skewing results toward more accessible or responsive demographics; for instance, surveys may underrepresent mobile-only users or non-responders with lower . Nonresponse bias further compounds this issue, as evidenced in analyses of the 's Index of Consumer Sentiment, where declining response rates—dropping below 50% in recent decades—correlate with overestimation of sentiment among participants who are often more optimistic or affluent, based on over 200 monthly surveys from 1978 to 2004. Partisan bias introduces systematic distortions, with empirical data showing consumer confidence levels diverging sharply along political lines. During periods of aligned presidential administration, confidence among co-partisans rises by 20-30 points relative to the opposing group, a gap that widened from 21 points under to 25 points under subsequent administrations, as tracked in longitudinal survey data; this effect persists even after controlling for economic fundamentals, suggesting respondents anchor perceptions to rather than objective conditions. Cognitive biases, including and the peak-end rule, amplify these distortions by overweighting recent negative events or media-highlighted downturns in forming sentiment, leading indices to underreflect gradual improvements while reacting disproportionately to transient shocks. Volatility in these indices stems primarily from their forward-looking expectations components, which are highly sensitive to short-term news cycles, expectations, and perceived labor market shifts, often fluctuating 10-20% month-to-month amid events like policy announcements or geopolitical tensions. For example, the University of 's expectations index dropped 17.8% in March 2025 due to heightened uncertainty over interest rates and stock prices, illustrating how subjective forecasts introduce noise unrelated to current economic data. Methodological factors, such as small sample sizes (e.g., 500 households for vs. 3,000 calls for Michigan) and reliance on qualitative responses converted to quantitative scores, exacerbate month-to-month swings, with alone capable of explaining up to 5-point variations. Herding behavior among respondents, where individuals conform to prevailing media narratives, further heightens this instability, as sentiment clusters around amplified pessimism during volatile periods.

Empirical Alternatives and Reforms

Empirical analyses have indicated that traditional consumer confidence indices often fail to provide incremental predictive value for household expenditure beyond objective economic indicators such as unemployment rates, disposable income, and retail sales data. For instance, regressions incorporating lagged values of durable goods purchases and macroeconomic variables typically render confidence measures statistically insignificant, suggesting they largely reflect contemporaneous hard data rather than forward-looking insights. This has prompted economists to favor alternatives grounded in verifiable metrics, including transaction volumes and point-of-sale data, which directly capture spending behavior without relying on subjective self-reports. Alternative indices derived from macroeconomic fundamentals offer a more causal approach to gauging household conditions. The Households' Macroeconomic Environment () index, constructed from quarterly across 22 European countries from 2002 to 2018, aggregates objective variables like GDP growth, , and labor market tightness to proxy consumer outlooks, demonstrating stronger correlations with actual consumption than survey-based sentiment. Similarly, micro-founded indicators, such as the proposed Micro-Consumer Confidence Indicator (MCCI), repurpose survey questions to focus on personal financial trajectories and aggregate expectations, yielding improved alignment with micro-level spending patterns in European datasets. methods, including semantic analysis of online news and , have also emerged as complements or substitutes; a 2023 study using network analysis of textual sources found these approaches forecast fluctuations with higher reliability, mitigating biases from low survey response rates. Reforms to survey methodologies aim to address inherent volatility and sampling biases in legacy phone-based polls. The University of Michigan's Surveys of Consumers transitioned to web interviewing in April 2024, following 14 years of experiments that enhanced representativeness and reduced non-response errors, with preliminary benchmarks showing stabilized sentiment readings post-adjustment. Proposed analytical reforms include fuzzy decision-making frameworks like DEMATEL to reconstruct indices from raw responses, emphasizing causal weights over simple averages and improving for consumption in empirical models. These changes prioritize empirical validation against hard outcomes, though critics note persistent challenges from media-driven sentiment swings that amplify over signal.

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