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.

he Survey of Consumer Finances (SCF) is a periodic survey sponsored by the U.S. Federal Reserve, conducted every three years. Its primary purpose is to gather comprehensive information on the financial status of households in the United States. Covering diverse topics such as income, assets, liabilities, and demographic characteristics, the SCF aims to present a detailed and accurate portrayal of the economic well-being of American families. This valuable dataset serves as a crucial resource for researchers, policymakers, and the public, enabling in-depth analysis of economic dynamics, wealth distribution, and income inequality trends over time. Through a combination of detailed interviews and supplementary surveys, the SCF plays a significant role in enhancing our understanding of the economic landscape within U.S. households.

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 1963 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, 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 marriage, family, and family planning. 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.

The CIS (Canadian Income Survey) Dataset contains detailed demographic, economic, and employment-related data of individuals across different provinces in Canada. The dataset is designed to assess key factors affecting income levels, employment history, and financial well-being at an individual level.

🔹 Dataset Overview

Total Variables: 36 (Covering demographic, employment, and financial attributes) Purpose: Used for analyzing income distribution, labor market trends, and economic well-being in Canada. Data Type: A mix of categorical, numerical, and binary data (e.g., Age, Gender, Income, Employment Status). Key Topics Covered: Demographics: Age, Gender, Marital Status, Immigrant Status Education & Employment: Highest Education, Years Worked, Weeks Employed Financial Data: Income after tax, Capital Gains, Pension, Investments Social Benefits: Childcare Benefits, Employment Insurance, Government Assistance

🔹 Significance of the Dataset ✔ Helps policymakers understand income inequality and poverty levels. ✔ Used for research on employment patterns and financial security. ✔ Supports decision-making on government subsidies and social welfare programs.

The purpose of the RHFS is to provide current and continuous measure of the financial health and property characteristics of single-family and multifamily rental housing properties in the United States. The survey provides information on the financing of single-family and multifamily rental housing properties with emphasis on new originations for purchase, refinancing, and loan terms associated with these originations. In addition, the survey includes information on property characteristics, such as number of units, amenities available, rental income and expenditure information. This survey was conducted in 2012 and will be conducted in 2015.

The 2001 Residential Finance Survey (RFS) was sponsored by the Department of Housing and Urban Development (HUD) and conducted by the Census Bureau. The RFS is a follow-on survey to the 2000 decennial census designed to collect, process, and produce information about the financing of all nonfarm, residential properties. Previous RF surveys have been integral parts of the decennial censuses since 1950. Primary users of RFS data in addition to HUD include the Bureau of Economic Analysis, Fannie Mae and Freddie Mac, and the Congress. Data are collected, tabulated, and presented for properties, the standard unit of reference for financial transactions related to housing. In the RFS, a property is defined as all the buildings and land covered by a single first mortgage. The sample for the RFS is stratified by property size, with large properties overrepresented in the sample. Very large properties are selected with certainty to control their effect on the reliability of the estimates. The RFS is the only standardized single source of detailed information on property, mortgage, and financial characteristics for multiunit properties. Both property owners and mortgage lenders are interviewed, resulting in more accurate information on property and mortgage characteristics. As part of the decennial census, the RFS is mandatory. This is important in collecting information from mortgage lenders.

Abstract

Financial services sector, like other economic sectors of Azerbaijan, has been characterized with fast development rate. Banking, insurance and post services hold leading positions among those services. Individuals are one of the major consumers of those services. Thus, more than 3.6 million people already use payment cards and about 500,000 people take consumer credits. Increase of financial literacy and better protection of consumer rights contribute to more efficient access of population to financial services. First of all, current status of financial literacy of population should be studied and problems revealed, to this end.

Increase of financial literacy and better protection of consumer rights became more urgent issues over the last decade. Fast integration of Azerbaijan into the world economy made it necessary to study those issues and implement appropriate measures in the country.

In view of the above mentioned facts, the Central Bank of the Republic of Azerbaijan, World Bank and SECO decided to carry out a financial literacy research of the population. The main objective of that project was to conduct a "Financial Literacy Survey", create a Single Database and prepare a Report reflecting outcomes of the survey.

Geographic coverage

The survey covered Baku (including 11 administrative districts), Ganja, Sumgait, Shirvan, Khirdalan, Sheki, Lankaran, Yevlakh, Nakhchivan, Guba, Gusar, Aghsu, Bilesuvar, Berde, Tovuz, Masalli cities, 2 settlements and 37 villages (see: table 1.1 of the survey report). 54% of survey participants live in urban (Baku- 23%) and 46% in rural areas. This is a similar pattern to the national demographic status.

Analysis unit

Household, individual

Universe

The survey was carried out among people above 18 years old (18 also included) (except for those not capable of being interviewed) with the latest birthday date within a year.

Kind of data

Sample survey data [ssd]

Sampling procedure

Definition of sampling frame and scale

1200 respondents were defined as a sample frame in 8 economic regions (2 economic regions of the country are under occupation) and Baku city. The main reason for conducting the survey among 1200 respondents is to ensure representativeness and financial feasibility of the project. Urban and rural ratio was set at 54% and 46% in line with statistic indicators. For detailed information see Table 1.1 of the survey report.

Preparation of the survey plan and implementation of survey sampling

Sampling was carried out at 2 stages: i) at the first stage, it was conducted while taking into account distribution of population by capital city, other urban and rural areas and economic regions with preliminary sampling units being street and villages (each preliminary sampling unit includes 15 respondents); ii) At the second stage, streets within the sampled cities and villages within economic regions were randomly selected. For example, according to results of the first stage of the sampling, a survey should be carried out among 45 respondents in Guba region and 15 respondents should be selected in urban areas and 30 respondents in rural areas. In view of the fact that primary sampling unit consists 15 respondents, 1 street within Guba town or its settlements and 2 villages among rural areas should be randomly selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was prepared based on the analogical questionnaire used in Russia and submitted by the Central Bank. The questionnaire was translated into Azerbaijani language, questions were adjusted to the country context, irrelevant questions were removed and new ones introduced. Meetings were arranged with representatives of the Central Bank and other relevant organizations, as well as their comments were discussed through e-mail during the preparation period of the questionnaire. The final version of the questionnaire was consisted of 65 questions and mainly covered such issues as registration of household's income and expenditures, financial awareness, financial literacy on basic calculations, violation of consumer rights during the use of financial services, access to financials services, payments cards and socio-demographic status of respondents. The questionnaire was prepared in Azerbaijani language and then, translated into English.

Cleaning operations

Entering and cleaning data, and creation of a Single Database

An operator entered and analyzed data through relevant software (SPSS). All questionnaires were coded during the entering process of data. An database specialist undertook additional control and regulation works to clean data. A Single Database was checked through preliminary analysis after major logic examination.

A Single Database was created at SPSS software based on questions of the questionnaire. Answers given by 1207 respondents were entered into the Single Database.

The Consumer Financial Protection Bureau’s (CFPB’s) Making Ends Meet (MEM) survey program is a general financial survey conducted regularly by the Office of Research at the CFPB. The surveys cover financial decision-making, perceptions, expectations, well-being, marketing and usage of different consumer finance products. This public use file (PUF) consists of surveys from the initial Making Ends Meet sample in 2019 (Sample 1) as well as surveys from all samples from 2022 forward (Sample 3 and later).The CFPB has released information and research based on these surveys and the related credit panel data for the last several years and is now making the data from the surveys public. These public use files also include select credit panel variables for the respondents to the 2019 survey and its follow-up surveys in 2020 and 2021. (Later surveys do not have credit variables.) These data will allow researchers to compare consumers’ financial status along several dimensions, including financial wellbeing, difficulty paying bills and expenses, and ability to cover expenses following income loss.The data is divided into folders by sample numbers. Also included is a user's manual with information about the survey and codebook. The parameters for the different samples are listed in the user's manual.

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 1967 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 1967 survey covered the respondent's attitudes toward national economic conditions (e.g., the effect of 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. Information about housing was also gathered, e.g., previous and present home ownership, value of respondent's dwelling, and mortgage information. In addition, the survey explored in detail the respondent's employment history, e.g., working conditions, job transfers, skills in equipment operation, past and expected career changes, and work attitudes. Personal data include age and education of head, household composition, and occupation.

School District Finance Survey, 2012-13 (F-33 2012-13), is a study that is part of the Common Core of Data (CCD) program; program data available since 1990 at . F-33 2012-13 (https://nces.ed.gov/ccd/f33ageninfo.asp) is a universe survey that is designed to provide finance data for all local education agencies (LEAs) that provide free public elementary and secondary education in the United States. The data file for F-33 2012-13 contains records representing the public elementary and secondary education agencies in the 50 United States and the District of Columbia. Key statistics produced from F-33 2012-13 are expenditures by object and function, indebtedness, and revenues by source. The F-33 is collaboration by the National Center for Education Statistics (NCES) and the Census Bureau. Census is the primary collection agent. Census refers to the collection as the Annual Survey of Local Government Finances: School Systems and releases its own version of the data file and publication based on that file. The NCES and Census files differ in their inclusion of independent charter school districts, the classification of some revenue items, and the inclusion of some expenditure items.

The FR 3033p is the first part of a two-stage survey series, which has been conducted at regular five-year intervals since 1955. It is a census survey designed to identify the universe of finance companies eligible for potential inclusion in the FR 3033s. It gathers limited information including total assets, areas of specialization, and information on the corporate structure of such companies. The second part of these information collections, the FR 3033s, collects balance sheet data on major categories of consumer and business credit receivables and major liabilities, along with income and expenses, and is used to gather information on the scope of a company's operations and loan and lease servicing activities. In addition, additional questions were added to collect lending information related to the COVID-19 impacts.

Abstract

The survey on financial literacy among the citizens of Bosnia and Herzegovina was conducted within a larger project that aims at creating the Action Plan for Consumer Protection in Financial Services.

The conclusion about the need for an Action Plan was reached by the representatives of the World Bank, the Federal Ministry of Finance, the Central Bank of Bosnia and Herzegovina, supervisory authorities for entity financial institutions and non-governmental organizations for the protection of consumer rights, based on the Diagnostic Review on Consumer Protection and Financial Literacy in Bosnia and Herzegovina conducted by the World Bank in 2009-2010. This diagnostic review was conducted at the request of the Federal Ministry of Finance, as part of a larger World Bank pilot program to assess consumer protection and financial literacy in developing countries and middle-income countries. The diagnostic review in Bosnia and Herzegovina was the eighth within this project.

The financial literacy survey, whose results are presented in this report, aims at establishing the basic situation with respect to financial literacy, serving on the one hand as a preparation for the educational activities plan, and on the other as a basis for measuring the efficiency of activities undertaken.

Geographic coverage

Data collection was based on a random, nation-wide sample of citizens of Bosnia and Herzegovina aged 18 or older (N = 1036).

Analysis unit

Household, individual

Universe

Population aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

SUMMARY

In Bosnia and Herzegovina, as is well known, there is no completely reliable sample frame or information about universe. The main reasons for such a situation are migrations caused by war and lack of recent census data. The last census dates back to 1991, but since then the size and distribution of population has significantly changed. In such a situation, researchers have to combine all available sources of population data to estimate the present size and structure of the population: estimates by official statistical offices and international organizations, voters? lists, list of polling stations, registries of passport and ID holders, data from large random surveys etc.

The sample was three-stage stratified: in the first stage by entity, in the second by county/region and in the third by type of settlement (urban/rural). This means that, in the first stage, the total sample size was divided in two parts proportionally to number of inhabitants by entity, while in the second stage the subsample size for each entity was further divided by regions/counties. In the third stage, the subsample for each region/county was divided in two categories according to settlement type (rural/urban).

Taking into the account the lack of a reliable and complete list of citizens to be used as a sample frame, a multistage sampling method was applied. The list of polling stations was used as a frame for the selection of primary sampling units (PSU). Polling station territories are a good choice for such a procedure since they have been recently updated, for the general elections held in October 2010. The list of polling station territories contains a list of addresses of housing units that are certainly occupied.

In the second stage, households were used as a secondary sampling unit. Households were selected randomly by a random route technique. In total, 104 PSU were selected with an average of 10 respondents per PSU. The respondent from the selected household was selected randomly using the Trohdal-Bryant scheme.

In total, 1036 citizens were interviewed with a satisfactory response rate of around 60% (table 1). A higher refusal rate is recorded among middle-age groups (table 2). The theoretical margin of error for a random sample of this size is +/-3.0%.

Due to refusals, the sample structure deviated from the estimated population structure by gender, age and education level. Deviations were corrected by RIM weighting procedure.

MORE DETAILED INFORMATION

IPSOS designed a representative sample of approximately 1.000 residents age 18 and over, proportional to the adult populations of each region, based on age, sex, region and town (settlement) type.

For this research we designed three-stage stratified representative sample. First we stratify sample at entity level, regional level and then at settlement type level for each region.

Sample universe:

Population of B&H -18+; 1991 Census figures and estimated population dynamics, census figures of refugees and IDPs, 1996. Central Election Commision - 2008; CIPS - 2008;

Sampling frame:

Polling stations territory (approximate size of census units) within strata defined by regions and type of settlements (urban and rural) Polling stations territories are chosen to be used as primary units because it enables the most reliable sample selection, due to the fact that for these units the most complete data are available (dwelling register - addresses)

Type of sample:

Three stage random representative stratified sample

Definition and number of PSU, SSU, TSU, and sampling points

• PSU - Polling station territory Definition: Polling stations territories are defined by street(s) name(s) and dwelling numbers; each polling station territory comprises approximately 300 households, with exception of the settlements with less than 300 HH which are defined as one unite. Number of PSUs in sample universe: 4710
• SSU - Household Definition: One household comprises people living in the same apartment and sharing the expenditure for food
• TSU - Respondent Definition: Member of the HH , 18+ Number of TSUs in sample universe: = 2.966.766
• Sampling points Approximately 10 respondents per one PSU, total 104

Stratification, purpose and method

• First level strata: Federation of B&H Republika Srpska Brc ko District
• Second level strata: 10 cantons 2 regions -
• Third level strata: urban and rural settlements
• Purpose: Optimisation of the sample plan, and reducing the sampling error

• Method: The strata are defined by criteria of optimal geographical and cultural uniformity

• Selection procedure of PSU, SSU, and respondent Stratification, purpose and method

• PSU Type of sampling of the PSU: Polling station territory chosen with probability proportional to size (PPS) Method of selection: Cumulative (Lachirie method)

• SSU Type of sampling of the SSU: Sample random sampling without replacement Method of selection: Random walk - Random choice of the starting point

• TSU - Respondent Type of sampling of respondent: Sample random sampling without replacement Method of selection: TCB (Trohdal-Bryant scheme)

• Sample size N=1036 respondents

• Sampling error Marginal error +/-3.0%

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey was modelled after the identical survey conducted in Romania. The questionnaire used in the Financial Literacy Survey in Romania was localized for Bosnia and Herzegovina, including adaptations to match the Bosnian context and methodological improvements in wording of questions.

Cleaning operations

Before data entry, 100% logic and consistency controls are performed first by local supervisors and once later by staff in central office.

Verification of correct data entry is assured by using BLAISE system for data entry (commercial product of Netherlands statistics), where criteria for logical and consistency control are defined in advance.

Response rate

• Nobody at home: 2,8%
• Eligible person is not home: 2,8%
• Refusal : 32,79%
• Given up after a minimum of two visits: 0,82%
• Other (excluded after control): 0,29%
• Finished: 60,5%

Context

Understanding factors that support consumer financial well-being can help practitioners and policymakers empower more families to lead better financial lives to serve their own goals.

A person’s financial well-being comes from their sense of financial security and freedom of choice—both in the present and when considering the future. We measured it using our 10-item Financial Well-Being Scale.

The survey dataset includes respondents’ scores on that scale, as well as measures of individual and household characteristics that research suggests may influence adults’ financial well-being.

Content

Variables relating to question in this dataset include Income and employment, Savings and safety nets, Past financial experiences, and Financial behaviors, skills, and attitudes.

For reference on specific fields, a codebook is available online here.

Acknowledgements

This survey was originally conducted by the US Consumer Finance Protection Bureau and published online in October 2017 here.

The Rental Housing Finance Survey provides a current and continuous measure of financial, mortgage, and property characteristics of rental housing properties in the United States. The survey focuses on the financing of rental housing properties, with emphasis on new mortgages, refinanced mortgages, or similar devices such as deeds of trust or land contracts, and the characteristics of debt originations. The 2018 RHFS included single-family residential and multifamily residential properties with at least one housing unit intended for rent. Data collection was conducted from June 2018 through November 2018.

The Survey of Consumer Finances (SCF) dataset, provided by the Federal Reserve, offers comprehensive insights into the financial condition of U.S. households. This dataset is invaluable for researchers, policymakers, and analysts interested in understanding consumer behavior, wealth distribution, and economic trends in the United States.

The SCF dataset includes detailed information on household income, assets, liabilities, and various demographic characteristics. It is collected every three years and serves as a crucial resource for analyzing the financial well-being of American families.

Key Features: Income Data: Information on various sources of income, including wages, investments, and government assistance. Asset Ownership: Detailed accounts of household assets, such as real estate, retirement accounts, stocks, and other investments. Liabilities:Comprehensive details on household debts, including mortgages, credit card debts, and student loans. Demographics: Data covering age, education, race, and family structure, allowing for nuanced analysis of financial trends across different segments of the population.

Use Cases: Economic research and analysis, Policy formulation and assessment, Understanding wealth inequality, Consumer behavior studies

Citing the Dataset:

When using this dataset in your research, please ensure to cite the Federal Reserve Board and the SCF as the original source.

Note: The dataset is intended for educational and research purposes. Users are encouraged to adhere to ethical guidelines when analyzing and interpreting the data.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Colombia is 1000.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

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 1954 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, 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. This was the first year that questions were asked regarding plans to make additions and repairs to homes. The 1954 survey emphasized the respondent's contractual payments, e.g., mortgages, rent, property taxes, and installment debt. Respondents were asked about the desirability of using an installment plan and the wisest place to put savings. A separate subsection of the survey contained questions for farmers. (The separate farmer's questionnaire, used in the 1947-1953 surveys, was dropped.) 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/ICPSR03608.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. This data collection is one in a series of financial surveys of consumers conducted annually from 1946 to 1971. 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 1968 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 1968 survey covered the respondent's attitudes toward national economic conditions (e.g., the effect of income tax, interest rates, the stock market, 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. Personal data include age and education of head, household composition, and occupation.

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.

1) Data Introduction • The Finance Data Dataset is a survey-based dataset collected via Google Forms during the COVID-19 lockdown. It includes various questions related to individuals' investment behavior, preferences, information sources, and expected returns.

2) Data Utilization (1) Characteristics of the Finance Data Dataset: • The dataset reflects behavioral finance attributes such as preferences for investment instruments (e.g., stocks, bonds, gold, public provident funds), investment purposes, investment horizons, and information acquisition channels.

(2) Applications of the Finance Data Dataset: • Development of AI-based investment profiling and recommendation models: The survey data can be used to build classification models for predicting investment behavior, as well as personalized financial product recommendation systems. • Financial education and consumer behavior research: Insights into investment objectives, risk tolerance, and time preferences can be utilized for designing financial literacy programs and customized financial consulting services.