The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families balance sheets, pensions, income, and demographic characteristics. Information is also included from related surveys of pension providers and the earlier such surveys conducted by the Federal Reserve Board. No other study for the country collects comparable information. Data from the SCF are widely used, from analysis at the Federal Reserve and other branches of government to scholarly work at the major economic research centers.The survey has contained a panel element over two periods. Respondents to the 1983 survey were re-interviewed in 1986 and 1989. Respondents to the 2007 survey were re-interviewed in 2009.The study is sponsored by the Federal Reserve Board in cooperation with the Department of the Treasury. Since 1992, data have been collected by the National Opinion Research Center (NORC) at the University of Chicago.

This data collection is one in a series of financial surveys of consumers conducted annually since 1946. In a nationally representative sample, the head of each spending unit (usually the husband, the main earner, or the owner of the home) was interviewed. The basic unit of reference in the study was the spending unit, but some family data are also available. The questions in the 1955 survey covered the respondent's attitudes toward national economic conditions and price activity, as well as the respondent's own financial situation. Other questions examined the spending unit head's occupation, and the nature and amount of the spending unit's income, debts, liquid assets, changes in liquid assets, savings, and actual and expected purchases of cars and other major durables. In addition, the survey explored in detail the subject of housing, e.g., previous and present home ownership, value of respondent's dwelling, satisfaction with home and space, expected duration of tenure there, mortgage information, budgeting, handling of family finances, use of installment plans, and changes in liquid assets. Personal data include number of people in the spending unit, age, sex, and education of the head, and the race and sex of the respondent. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03600.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

This study was conducted by the Consumer Finance Research Group operating out of CHRR at Ohio State University. This study of U.S. households collects current data on credit usage, balance sheets and incomes integrated with extensive data on credit card usage. This survey will collect thousands of observations each year using a nationally representative sample with breakouts by region and demographics. Full information can be found at https://chrr.osu.edu/consumer-finance-monthly.

The purpose of this data collection effort was to provide an accurate representation of the distribution of elements composing family balance sheets across families in the United States. To that end, the 1989 Survey of Consumer Finances was designed to gather household-level information closely comparable to that obtained in the SURVEY OF CONSUMER FINANCES, 1983 (ICPSR 9751). Detailed data were collected on the composition of household budgets, the terms of loans, and relationships with financial institutions. Information was also obtained on employment history and pension rights of the survey respondent and the spouse or partner of the respondent. In addition to recording data on the economic assets and liabilities of families, the survey examined the attitudes of consumers toward credit use and their reactions to consumer credit regulations. Demographic variables include age, sex, marital status, housing, and financial independence.

Abstract (en): The purpose of this data collection effort was to provide an accurate representation of the distribution of elements composing family balance sheets across families in the United States. To that end, the 1998 Survey of Consumer Finances was designed to gather household-level information closely comparable to that obtained in the SURVEY OF CONSUMER FINANCES, 1995 (ICPSR 2193). Detailed data were collected on the composition of household budgets, the terms of loans, and relationships with financial institutions. Information was also obtained on the employment history and pension rights of the survey respondent and the spouse or partner of the respondent. Detailed data were also gathered on characteristics of the survey respondent's housing and vehicle(s). In addition to recording data on the economic assets and liabilities of families, the survey examined the attitudes of consumers toward credit use and their reactions to consumer credit regulations, and lines of credit. Demographic variables include age, sex, marital status, housing, and financial independence. Households within the 48 contiguous United States. The Survey of Consumer Finances (SCF) is based on a dual-frame sample design (see Arthur B. Kennickell and R. Louise Woodburn, "Consistent Weight Design for the 1989, 1992, and 1995 SCFs, and the Distribution of Wealth," August 1997, http://www.federalreserve.gov/pubs/oss/oss2/method.html for more details). One set of the survey cases was selected from a standard multistage area probability design. This part of the sample, which contributed 2,813 cases to the final set of interviews, is intended to provide good coverage of characteristics, such as home ownership, that are broadly distributed in the population. The other set of the survey cases was selected as a list sample from statistical records (the Individual Tax File) derived from tax data by the Statistics of Income Division of the Internal Revenue Service. These records were made available under strict rules governing confidentiality, the rights of potential respondents to refuse participation in the survey, and the types of information that can be made available. This second sample was designed to disproportionately select families that were likely to be relatively wealthy (see Arthur B. Kennickell, "List Sample Design for the 1998 Survey of Consumer Finances," April 1998, http://www.federalreserve.gov/pubs/oss/oss2/method.html, for a more extended discussion of the design of the list sample). The list sample contributed 1,496 cases to the final set of interviews. Because of the complexity of the SCF design, users cannot apply some of the standard procedures for variance estimation. A set of sample replicates has been created with bootstrap techniques and analysis weights have been computed independently for each replicate. Analysts may use these weights to make approximate estimates of sampling variance. Replicate weights corresponding to both X42000 and X42001 are available. See the codebook for more details. 2006-03-30 File QU3155.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB3155.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File AP3155.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. Funding insitution(s): Board of Governors of the Federal Reserve System. United States Department of the Treasury. Office of the Comptroller of the Currency. United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging. United States Small Business Administration. Government Accountability Office. United States Congress. Joint Committee on Taxation. The data have been optimized and thus have a different record length from the original provided by the principal investigators.The SAS transport files were created using the SAS XPORT engine.

The Survey of Consumer Finances (SCF) is conducted annually to obtain work experience and income information from Canadian households. The Survey provides up-to-date information on the distribution and sources of income, before and after taxes, for families and individuals. With this file, users may identify specific family types, such as two-parent and lone-parent families. Information is also provided on earnings, transfers, and total income for the head and the spouse of the census family unit, as well as personal and labour-related characteristics. This reference year for this file is 1994. Commencing with the 1998 microdata files, annual cross-sectional income data will be sourced from the Survey of Labour and Income Dynamics (SLID). The purpose of this file is to enable users to combine the other Survey of Consumer Finances and Household Income, Facilities and Equipment files into custom-tailored household and sub-household units. This file consists of one record for each child and adult in the surveys' samples. Each key file record has the identification numbers for the correponding household, economic family, census family, and individual. Each record has the household (HH), economic family (EF), census family (CF), and the individual 15+ microdata tape identification numbers of the individual.

The surveys in this collection are used to gather qualitative and quantitative information directly from users or potential users of Board publications, resources, and conference materials, such as consumers (consumer surveys) and stakeholders (stakeholder surveys). Stakeholders may include, but are not limited to, nonprofits, community development organizations, consumer groups, conference attendees, financial institutions and other financial companies offering consumer financial products and services, other for profit companies, state or local agencies, and researchers from academic, government, policy and other institutions. Publications and resources may include reports and brochures, as well as audio and visual content, whether delivered in print, online, or through other means. The frequency of the survey and content of the questions will vary as needs arise for feedback on different resources and from different audiences.

Extract from 2016 SCF focused on studying the impacts of race and education on inheritances

The Community Credit research project explores pathways for trusted collaboration between credit unions and the communities they serve. To understand the experiences of people historically underserved by the consumer financial services industry, we focused in particular on the lived experience of low-income residents in Southern California. As part of a larger, mixed-methods study, in 2022 we conducted an online survey investigating people’s everyday financial practices, evolving perceptions of trust and risk, and their unmet financial needs. The general population survey data was collected between April 15 and April 22, 2022. The credit union data was collected between May 3 and July 18, 2022. This data set contains the responses of the survey participants after excluding any personally identifying data. All study materials and procedures were approved by the University of California, Irvine Office of Human Research Protections and the Institutional Review Board (protocol ID 20216839)...., Survey data was collected via the Qualtrics platform. The survey contains 52 questions. It was distributed to the general population in zip codes within the counties of Los Angeles and Orange. It was also distributed directly to members of a large credit union headquartered in Orange County (“large†according to NCUA asset classes). Participants were eligible to complete the survey if they live in Orange County or Los Angeles County, are older than 18, and have a combined household income of less than $100,000. Incomplete responses have been removed. The survey yielded 1,370 complete responses (1,213 from the general population participants and 157 from members of the large credit union)., Note that the files do not contain all the responses from the survey questions. Responses that provided potentially identifying information were removed. Survey participants’ gender, education status, employment status, and marital status were removed; data on these elements are provided in aggregate in the readme file. Responses are segmented into two files reflecting participants from the general population (“Gen Pop†) and from the credit union (“CU†).

United States SCE: Debt Delinquency Expectation: Probability of Missing Minimum Debt Payment Over the Next 3 Months data was reported at 13.944 % in Apr 2025. This records an increase from the previous number of 13.594 % for Mar 2025. United States SCE: Debt Delinquency Expectation: Probability of Missing Minimum Debt Payment Over the Next 3 Months data is updated monthly, averaging 12.114 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 17.168 % in Sep 2013 and a record low of 9.201 % in Feb 2022. United States SCE: Debt Delinquency Expectation: Probability of Missing Minimum Debt Payment Over the Next 3 Months data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H085: Survey of Consumer Expectations: Financial.

This data collection is one in a series of financial surveys of consumers conducted annually since 1946. In a nationally representative sample, the head of each family unit was interviewed. Starting in 1966, in order to examine the effect that increased car ownership was having on American families, the data collected in this series were organized so that they could be analyzed by both family unit and car unit. The 1970 data are based on car unit. Survey questions regarding automobiles included number of drivers and car owners in the family, make and model of each car, purchase method, car financing and installment debt, and expectations of car purchases in the coming year. Other questions in the 1970 survey covered the respondent's attitudes toward national economic conditions (e.g., the effect of income tax, Vietnam War involvement, and relations with other communist countries on United States business) and price activity, as well as the respondent's own financial situation. Other questions examined the family unit head's occupation, and the nature and amount of the family's income, debts, liquid assets, changes in liquid assets, savings, investment preferences, and actual and expected purchases of major durables. In addition, the survey explored in detail the subject of housing, e.g., previous and present home ownership, value of respondent's dwelling, and mortgage information. Questions in this survey also focused on life insurance coverage, mutual funds, and credit card use. Personal data include age and education of head, household composition, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07450.v2. We highly recommend using the ICPSR version as have made this dataset available in multiple data formats.

The 2017 National Financial Well-Being in America Survey, conducted for the CFPB Offices of Financial Education and Financial Protection for Older Americans, was an online survey conducted to measure the financial well-being of adults in the United States. These data were created as a foundation for internal and external research into financial well-being and are relevant to work being done by researchers in the Office of Research who have access to the (deidentified) data.

The 2017 Global FICP Survey tracks the prevalence of key policy, legal, regulatory, and supervisory efforts to advance financial inclusion and financial consumer protection, including: national financial inclusion strategies, nonbank e-money issuers, agent-based delivery models, simplified customer due diligence, legal frameworks and institutional arrangements for financial consumer protection, disclosure and transparency, fair treatment of consumers, dispute resolution, and financial capability. Financial sector authorities in 124 jurisdictions responded to the 2017 Global FICP Survey. The survey covers regulated financial service providers offering retail credit, deposit, and/or payment products and services. The reporting period was from November 2016 to June 2017.

Consumer Spending in the United States increased to 16445.70 USD Billion in the second quarter of 2025 from 16345.80 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Consumer Spending - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

The FinScope survey tool was developed by FinMark Trust as a nationally representative survey of consumer perceptions about financial services and issues. FinScope provides insights into how people source their income and manage their financial lives. It looks at the use of, and demand for, financial services as well as attitudes, vulnerability, coping behaviour and consumption patterns. By exploring the use of informal as well as formal financial products, FinScope aims to create a picture of the role that the formal and informal sectors play in a country’s financial market.

Geographic coverage

National Coverage

Analysis unit

Individuals

Universe

The survey covered all usual household residents age 16 and above in Zambia.

Kind of data

Sample survey data [ssd]

Sampling procedure

Much like the previous survey in the series, the Finscope 2005 used a stratified, multi-stage cluster sampling approach. Stratification was done at the province and urban/rural level before cluster sampling was performed using enumerator areas as PSUs. The sampling frame for the survey was developed by the Zambian Central Statistical Office (CSO) based on the 2000 Zambian population census. The survey used three-stage stratified cluster sampling to create the sample population. Stratification was done at the province and urban/rural levels before cluster sampling was performed using enumerator areas as PSUs. 400 EAs were selected with probability proportional to size. Within each EA, 10 households were randomly selected. In the third stage, one eligible (aged 16 and above) member of the household was randomly selected using a Kish grid. Further details of the sampling methodology are provided in Annex 1 of the final report for the 2009 Zambian Finscope.

Mode of data collection

Face-to-face [f2f]

Research instrument

A single questionnaire was used for the Zambian Finscope 2009. The questionnaire design phase included 14 focus group discussions and the facilitation of a stakeholder workshop in August 2009, which was attended by a broad cross-section of stakeholders within the financial sector.

These activities assisted in adapting the FinScope Zambia 2005 questionnaire to include notable developments that had taken place in Zambia’s financial sector and economy as a whole since the first survey was conducted, while at the same time allowing for comparisons with the 2005 data.

The revised questionnaire was translated into Zambia’s seven vernacular languages and included questions on the following topics: • Household information and demographics • Farming and fishing • Income and expenditure • Access to infrastructure • Financial literacy and awareness • Attitudes and perceptions towards finance • Savings • Borrowing • Product penetration and banking • Insurance • Informal finance • Remittances • Psychographics

Cleaning operations

Prior to data capture, a data entry programme was developed, tested and refined using the Census and Survey Processing (CSPro) software package. This process was carried out in close consultation with FinMark Trust to ensure that the survey indicator values could be calculated. Nine data operators and two data supervisors were trained to familiarise them with the data entry programme and also to facilitate their understanding of the questionnaire.

The completed questionnaires were checked before being captured. Data inputting was carried out from November to December 2009, after which the data was cleaned, weighted, validated and converted into Statistical Package for the Social Sciences (SPSS) software. Following the submission of preliminary findings to the FSDP Secretariat by FinMark Trust, a second validation procedure was performed in January using additional population projections and other survey data. This resulted in slight adjustments to the weighting. Further information on the cleaning, weighting and validation process is available in Annex 2 of the 2009 Report.

DataFirst did some editing of the data before release. The original version of the Zambian Finscope 2009 had a large number of geographic variables, many of which ended up being excluded. Some were excluded because they weren't actually usable without a private codebook, others because they could potentially lead to identification of individuals in the dataset. The final set of geographic variables included were province, district, and an urban/rural binary variable.

The original datafile also contained a number of variables that detailed surveyor, supervisor, and visitation information. These were also excluded from the distributed datafile. Also excluded were variables used only for informing placement in the Kish grid.

analyze the consumer expenditure survey (ce) with r the consumer expenditure survey (ce) is the primo data source to understand how americans spend money. participating households keep a running diary about every little purchase over the year. those diaries are then summed up into precise expenditure categories. how else are you gonna know that the average american household spent $34 (±2) on bacon, $826 (±17) on cellular phones, and $13 (±2) on digital e-readers in 2011? an integral component of the market basket calculation in the consumer price index, this survey recently became available as public-use microdata and they're slowly releasing historical files back to 1996. hooray! for a t aste of what's possible with ce data, look at the quick tables listed on their main page - these tables contain approximately a bazillion different expenditure categories broken down by demographic groups. guess what? i just learned that americans living in households with $5,000 to $9,999 of annual income spent an average of $283 (±90) on pets, toys, hobbies, and playground equipment (pdf page 3). you can often get close to your statistic of interest from these web tables. but say you wanted to look at domestic pet expenditure among only households with children between 12 and 17 years old. another one of the thirteen web tables - the consumer unit composition table - shows a few different breakouts of households with kids, but none matching that exact population of interest. the bureau of labor statistics (bls) (the survey's designers) and the census bureau (the survey's administrators) have provided plenty of the major statistics and breakouts for you, but they're not psychic. if you want to comb through this data for specific expenditure categories broken out by a you-defined segment of the united states' population, then let a little r into your life. fun starts now. fair warning: only analyze t he consumer expenditure survey if you are nerd to the core. the microdata ship with two different survey types (interview and diary), each containing five or six quarterly table formats that need to be stacked, merged, and manipulated prior to a methodologically-correct analysis. the scripts in this repository contain examples to prepare 'em all, just be advised that magnificent data like this will never be no-assembly-required. the folks at bls have posted an excellent summary of what's av ailable - read it before anything else. after that, read the getting started guide. don't skim. a few of the descriptions below refer to sas programs provided by the bureau of labor statistics. you'll find these in the C:\My Directory\CES\2011\docs directory after you run the download program. this new github repository contains three scripts: 2010-2011 - download all microdata.R lo op through every year and download every file hosted on the bls's ce ftp site import each of the comma-separated value files into r with read.csv depending on user-settings, save each table as an r data file (.rda) or stat a-readable file (.dta) 2011 fmly intrvw - analysis examples.R load the r data files (.rda) necessary to create the 'fmly' table shown in the ce macros program documentation.doc file construct that 'fmly' table, using five quarters of interviews (q1 2011 thru q1 2012) initiate a replicate-weighted survey design object perform some lovely li'l analysis examples replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using unimputed variables replicate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t -tests using unimputed variables create an rsqlite database (to minimize ram usage) containing the five imputed variable files, after identifying which variables were imputed based on pdf page 3 of the user's guide to income imputation initiate a replicate-weighted, database-backed, multiply-imputed survey design object perform a few additional analyses that highlight the modified syntax required for multiply-imputed survey designs replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using imputed variables repl icate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t-tests using imputed variables replicate the %proc_reg() and %proc_logistic() macros found in "ce macros.sas" and provide some examples of regressions and logistic regressions using both unimputed and imputed variables replicate integrated mean and se.R match each step in the bls-provided sas program "integr ated mean and se.sas" but with r instead of sas create an rsqlite database when the expenditure table gets too large for older computers to handle in ram export a table "2011 integrated mean and se.csv" that exactly matches the contents of the sas-produced "2011 integrated mean and se.lst" text file click here to view these three scripts for...

This data collection is one in a series of financial surveys of consumers conducted annually since 1946. In a nationally representative sample, the head of each family unit was interviewed. The 1964 data are based on the family unit. The questions in the 1964 survey covered the respondent's attitudes toward national economic conditions and price activity, as well as the respondent's own financial situation. Other questions examined the family unit head's occupation, and the nature and amount of the family's income, debts, liquid assets, changes in liquid assets, savings, investment preferences, and actual and expected purchases of cars and other major durables. In addition, the survey explored in detail the subject of housing, e.g., previous and present home ownership, value of respondent's dwelling, and mortgage information. The survey also gathered detailed information on savings, assets, and stock ownership. Personal data include age and education of head, household composition, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07444.v3. We highly recommend using the ICPSR version as have made this dataset available in multiple data formats.

• Built from a random subset of respondents (stratified by gender, location, and age) from a separate nationally representative study • Respondents filtered to include only those that had conducted a financial transaction on their phone or with an agent in the last 90 days • Sample size: 609 respondents • Survey dates: November 1–22, 2021

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Aug 2025 about savings, personal, rate, and USA.

"This dataset includes consumer-submitted reviews from over 5086 companies, covering both product- and service-based businesses. It’s built to support CX, AI, and analytics teams seeking structured insight into what real customers say, feel, and expect — across the Telecommunications industry.

Each review includes:

• Authentic customer reviews (text, rating, pros and cons)
• Labeled sentiment and tone (positive, neutral, negative)
• Service context across industries: purchase, delivery, support, return, usage
• Industry and company filters (fully customizable per buyer request)
• Optional metadata: platform, review length, timestamp, geo-location

The list may vary based on the industry and can be customized as per your request.

Use this dataset to:

• Track public perception trends across specific brands or verticals
• Segment sentiment insights by industry, region, or company
• Power NLP pipelines that require diverse tone, emotion, and domain specificity
• Build dashboards or LLM prompts grounded in real user language
• Train review summarization, classification, or escalation engines

This dataset offers flexibility for custom delivery-by industry, domain, or company, making it ideal for teams needing scalable consumer voice data tailored to specific strategic goals."