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.

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.

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.

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.

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.

"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, including:Income and employmentSavings and safety netsPast financial experiencesFinancial behaviors, skills, and attitudes ....Download the complete survey data as a CSV file, published September 2017. This public use file (PUF) doesn't include personally identifying information of the respondents."-CFPB website

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.

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.

Abstract

The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

Geographic coverage

National Coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

Research instrument

The English version of the questionnaire is provided for download.

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: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

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.

Financial Access Survey (FAS) indicators are expressed as ratios to GDP, land area, or adult population to facilitate cross-economy comparisons. Provision of FAS data is voluntary.

The Financial Access Survey draws on the IMF's Monetary and Financial Statistics Manual and Compilation Guide (http://data.imf.org/api/document/download?key=61061648)

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.

Abstract

The Russia Financial Literacy diagnostic survey was undertaken as part of the preparation for the World Bank supported Russia Financial literacy and Financial education program in 2008.

The survey was conducted by the National Agency for Financial Studies (NAFS) in 2008 by request of the World Bank.

The national representative survey was aimed to provide information on the initial level of financial literacy (i.e. financial planning and managing debt, attitudes to/understanding of personal responsibilities and consumer rights in the area of financial services, knowledge of financial products/services, etc.). The survey asked basic questions on features of financial behavior, attitudes to and demand for financial education of the Russian population.

Geographic coverage

National

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

The Board uses the Senior Financial Officer Survey (FR 2023) to gather qualitative and limited quantitative information about liability management, the provision of financial services, and the functioning of key financial markets. Results of each survey are available in PDF format.

The National Public Education Financial Survey, 2007-08 (NPEFS 2007-08), is a study that is part of the Common Core of Data's National Public Education Financial Survey program; program data is available since 1987 at . CCD-NPEFS 2007-08 (https://nces.ed.gov/ccd/stfis.asp) is a cross-sectional survey that collected information about revenues and expenditures for public elementary and secondary education. The information is drawn from the state education agencies' administrative records systems; no additional data are collected from schools or districts. NPEFS data are used in calculating states' Title I grants. The study was conducted using responding agencies' existing administrative records. The universe of state education agencies was sampled. The study's response rate was 100 percent. Key statistics produced from CCD-NPEFS 2007-08 are on revenues by source and expenditures by function and object. Average daily attendance is also collected on the NPEFS.

Abstract

The survey is the follow-up of the Diagnostic Review on Consumer Protection and Financial Literacy conducted by the World Bank in 2008-2009. The Diagnostic Review in Romania was the fourth in a World Bank-sponsored pilot program to assess consumer protection and financial literacy in developing and middle-income countries.1 The objectives of this Review were three-fold to: (1) refine a set of good practices for assessing consumer protection and financial literacy, including financial literacy; (2) conduct a review of the existing rules and practices in Romania compared to the good practices; and (3) provide recommendations on ways to improve consumer protection and financial literacy in Romania. The Diagnostic Review was prepared at the request of the National Authority for Consumers' Protection (ANPC), whose request was endorsed by the Ministry of Economy and Finance. Support was provided by the National Bank of Romania (BNR), which supervises banks and non-bank credit institutions. Further assistance was given by the supervisory commissions for securities (CNVM), insurance (CSA) and private pensions (CSSPP).

The Diagnostic Review found that the basic foundations needed for consumer protection and financial literacy are in place in Romania but they benefit from further strengthening support. The Review proposes improvements in six areas: consumer awareness, information and disclosure for consumers, professional competence, dispute resolution, financial education and financial literacy surveys.

Consequently, in 2010 the World Bank commissioned a nation-wide survey of the levels of financial literacy. A consultant (sociologist Manuela Sofia Stanculescu) developed the survey methodology (sampling methodology and questionnaire) in line with the Financial Literacy Survey in Russia (the World Bank, 2008) and the baseline survey Financial Capability in the UK (Financial Services Authority, 2005).2 The final form of the questionnaire was agreed with representatives of the National Bank of Romania (BNR), the Romanian Banking Institute (IBR), the National Authority for Consumers' Protection (ANPC), and the Financial Companies Association in Romania (ALB). The Institute for World Economy (Romanian Academy) collected the data in May 2010.

The main objective of this work is the establishment (and later the evaluation) of a well targeted national program of financial education.

Geographic coverage

National

Analysis unit

Household, individual

Universe

Non-institutionalized persons aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the survey is probabilistic, two-stage, stratified, representative at national level with an error of +/- 3% at a 95% confidence level.

The sample is based on two stratification criteria: (i) historical region (8 regions) and (ii) type of locality (7 types depending on the city size, in urban areas, and on the synthetic index of community development,4 in the rural ones).

The sample volume is 2048,5 out of which 148 cases represent a boost of persons aged 16, 17 or those had their 18th birthday after November 2009.6 Respondents were randomly selected from electoral registers corresponding to 185 voting sections (randomly selected), located in 141 localities (77 communes, 63 towns/cities and the capital Bucharest).

The sample includes a slight over-representation of men, rural respondents, and elderly particularly due to the boost of young but also to the fact that people left abroad concentrate among the 25-44 age category. Nevertheless, the sample fairly reproduces the structure (by gender, age categories and area of residence) of the country population 16+ years according to the data for 2009 provided by the National Institute for Statistics. Socio-demographic structure of the sample is presented in table 3 of the survey report.

Demographic data and data regarding the use of financial services were collected for all members of respondents? households. In the respondents? households live 5406 persons overall. This extended sample has also a slight over-representation of rural respondents and an under-representation of children (0-14 years) and persons 25-24 years (most probably young people who left abroad with children).

MORE INFORMATION ON THE SAMPLING METHODOLOGY

Sample volume: 2,200 non-institutionalized persons aged 18 or older. In addition, the sample will be boosted with 180 persons aged 16-18 years old. Overall, at least 2,000 valid questionnaires should be completed during fieldwork.

Type of the sample: Probabilistic, two-stage, stratified, representative at national level, with an error of +/- 2.8% at a 95% confidence level.

Stratification criteria: The sampling scheme is based on two stratification criteria

(a) Historical region (8 regions) (b) Type of locality, with 7 theoretical strata

i. Urban areas - 4 strata 1. very small towns under 30 thou inhabitants 2. small towns 30,001-100 thou inhabitants 3. medium cities 100,001-199 thou inhabitants 4. large cities 200 thou inhabitants or more

ii. Rural areas - 3 strata determined based on the synthetic index of community development 37 1. poor communes (the 30% communes with the lowest level of development within the country) 2. medium developed communes 3. developed communes (the 30% communes with the highest level of development within the country).

Sampling stages: The sampling scheme includes two stages.

Sampling units: There are two sampling units corresponding to the two sampling stages. In the first sampling stage, voting sections are selected and in the second stage, non-institutionalized persons aged 18 years or more.

Selection: Random selection in all sampling stages.

Sampling scheme: In the first stage the sample is distributed proportionally with the volume of population for each of the 56(= 8 x 7) theoretical strata different from zero.

The corresponding number of voting sections for each strata is determined taking into account on the one hand, the volume of each strata sub-sample (= sample size x share of total population in that strata) and, on the other hand, a minimum level of 10 questionnaires for each sampling point. The voting sections which will represent sampling points are then randomly selected based on the exhaustive national list of voting sections (the latest available from the Permanent Electoral Authority).

The sample has 188 sampling points (voting sections) of which 104 are in urban areas, and 84 are in rural localities, including the capital city.

For each sampling point is computed the number of corresponding questionnaires by dividing the strata sub-sample by the number of sampling points of that strata. In the second sampling stage, the electoral registers corresponding to the voting sections (selected as sampling points) are used as sampling frame. Non-institutionalized persons aged 18 or more are randomly selected from the electoral registers based on the mechanical step method.

In those localities where the electoral registers are not available (or the municipality do not grant access), the random route method will be used. All these cases will be specified and explained in the fieldwork report, except for Bucharest, where the random route method will be used for all voting sections, as the rate of replacement from electoral registers is high in all national representative surveys.

The electoral registers include only persons 18 years or more. Accordingly, the sample will include a boost of persons aged 16, 17 or persons that had their 18th birthday after November 2009.39 For each voting section, one person aged 16-18 years will be added. They will be selected based on the random route method.

Mode of data collection

Face-to-face [f2f]

Response rate

The overall response rate of the survey is 95.2%. More detailed information is provided in "Table 2 Response rates and quality of the sampling frame by sampling method (%) " of the survey report.

The National Public Education Financial Survey, 2011-12 (NPEFS 2011-12), is a study that is part of the Common Core of Data's National Public Education Financial Survey program; program data is available since 1987 at . CCD-NPEFS 2011-12 [https://nces.ed.gov/ccd/stfis.asp] is a cross-sectional survey that gathers data on the financing of education. NPEFS data are used in calculating states' Title I grants. The study was conducted using responding agencies' existing administrative records. The universe of state education agencies was sampled. The study's response rate has not been calculated as of May 2013. Key statistics produced from CCD-NPEFS 2011-12 will collect data on attendance, revenue, and expenditure data from which NCES determines a State's 'average per-pupil expenditure' (SPPE) for elementary and secondary education.

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.