100+ datasets found
  1. d

    Money Management and Financial Literacy

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Apr 23, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DC Health, Cancer and Chronic Disease Prevention Bureau, Public Health Analyst (2025). Money Management and Financial Literacy [Dataset]. https://catalog.data.gov/dataset/money-management-and-financial-literacy
    Explore at:
    Dataset updated
    Apr 23, 2025
    Dataset provided by
    DC Health, Cancer and Chronic Disease Prevention Bureau, Public Health Analyst
    Description

    These services help with money management, financial planning, and insurance education. These services are not all dementia-specific but are inclusive of those living with dementia or who are planning for future memory loss. We include larger organizations that provide these services but have not included individual/private financial planners.

  2. Financial literacy index in Indonesia 2013-2025

    • statista.com
    Updated Sep 5, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Financial literacy index in Indonesia 2013-2025 [Dataset]. https://www.statista.com/statistics/1369454/indonesia-financial-literacy-index/
    Explore at:
    Dataset updated
    Sep 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Indonesia
    Description

    In 2024, Indonesia's financial literacy index was around ***** percent. Although the index has been increasing since 2013, the national financial literacy was still considerably low and indicates that there was still a substantial portion of the population who does not understand financial service providers, their products, features, advantages, and risks, which hinders the development of Open Finances. This measure consists of a survey to assess the level of knowledge, skills, confidence, attitudes, and behavior related to financial services and products.

  3. Financial-Behavior

    • kaggle.com
    zip
    Updated Nov 20, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ziya (2024). Financial-Behavior [Dataset]. https://www.kaggle.com/datasets/ziya07/financial-behavior
    Explore at:
    zip(30268 bytes)Available download formats
    Dataset updated
    Nov 20, 2024
    Authors
    Ziya
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset contains 500 tweets related to financial literacy and consumer behavior, designed for tasks such as sentiment analysis, emotion classification, and behavior prediction. The dataset was generated to support research in financial literacy education and consumer behavior modeling, incorporating realistic tweet structures and metadata.

    Dataset Features tweet_content (string): The text of the tweets, reflecting various financial literacy topics and emotions.

    emotion (categorical): The emotion expressed in the tweet, selected from:

    Positive Fear Anticipation Disgust Surprise sentiment_score (float): A numerical score representing the sentiment of the tweet, ranging from -1 (negative sentiment) to 1 (positive sentiment).

    likes (integer): Number of likes the tweet received (simulated).

    retweets (integer): Number of retweets the tweet received (simulated).

    replies (integer): Number of replies the tweet received (simulated).

    topic_tags (categorical): The main financial topic discussed in the tweet, selected from:

    Savings Investment Budgeting Debt Management Financial Planning Credit Scores Spending Habits financial_behavior (categorical): A classification of the financial behavior implied by the tweet, categorized as:

    Good behavior Moderate behavior Risky behavior Potential Use Cases Sentiment analysis and emotion classification. Behavioral modeling for financial decision-making. Testing machine learning algorithms for financial literacy. Educational applications for personalized financial learning platforms. Simulating tweet analysis in social media mining studies.

  4. Latin America: financial literacy 2022, by country

    • statista.com
    Updated Nov 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Latin America: financial literacy 2022, by country [Dataset]. https://www.statista.com/statistics/1188528/latin-america-financial-literacy-pisa/
    Explore at:
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Latin America, Peru, Brazil
    Description

    In 2022, Peruvian students reached the highest financial literacy score among the Latin American countries analyzed by the program for international student assessment (PISA), with ***. Brazil followed with a mean score of ***.

  5. i

    Grant Giving Statistics for Financial Literacy First

    • instrumentl.com
    Updated Aug 24, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Grant Giving Statistics for Financial Literacy First [Dataset]. https://www.instrumentl.com/990-report/financial-literacy-first
    Explore at:
    Dataset updated
    Aug 24, 2024
    Variables measured
    Total Assets, Total Giving
    Description

    Financial overview and grant giving statistics of Financial Literacy First

  6. o

    Replication data for: Keeping It Simple: Financial Literacy and Rules of...

    • openicpsr.org
    • dataverse.harvard.edu
    • +1more
    Updated Apr 1, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alejandro Drexler; Greg Fischer; Antoinette Schoar (2014). Replication data for: Keeping It Simple: Financial Literacy and Rules of Thumb [Dataset]. http://doi.org/10.3886/E113888V1
    Explore at:
    Dataset updated
    Apr 1, 2014
    Dataset provided by
    American Economic Association
    Authors
    Alejandro Drexler; Greg Fischer; Antoinette Schoar
    Description

    Micro-entrepreneurs often lack the financial literacy required to make important financial decisions. We conducted a randomized evaluation with a bank in the Dominican Republic to compare the impact of two distinct programs: standard accounting training versus a simplified, rule-of-thumb training that taught basic financial heuristics. The rule-of-thumb training significantly improved firms' financial practices, objective reporting quality, and revenues. For micro-entrepreneurs with lower skills or poor initial financial practices, the impact of the rule-of-thumb training was significantly larger than that of the standard accounting training, suggesting that simplifying training programs might improve their effectiveness for less sophisticated individuals.

  7. d

    Data from: PISA 2012 Results: Students and Money (Volume VI) Financial...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Mar 30, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Department of State (2021). PISA 2012 Results: Students and Money (Volume VI) Financial Literacy Skills for the 21st Century [Dataset]. https://catalog.data.gov/dataset/pisa-2012-results-students-and-money-volume-vi-financial-literacy-skills-for-the-21st-cent
    Explore at:
    Dataset updated
    Mar 30, 2021
    Dataset provided by
    U.S. Department of State
    Description

    This sixth volume of PISA 2012 results examines 15-year-old students’ performance in financial literacy in the 18 countries and economies that participated in this optional assessment. It also discusses the relationship of financial literacy to students’ and their families’ background and to students’ mathematics and reading skills. The volume also explores students’ access to money and their experience with financial matters. In addition, it provides an overview of the current status of financial education in schools and highlights relevant case studies.

  8. i

    Grant Giving Statistics for Financial Literacy Institute I

    • instrumentl.com
    Updated Nov 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Grant Giving Statistics for Financial Literacy Institute I [Dataset]. https://www.instrumentl.com/990-report/financial-literacy-institute
    Explore at:
    Dataset updated
    Nov 27, 2025
    Variables measured
    Total Assets
    Description

    Financial overview and grant giving statistics of Financial Literacy Institute I

  9. w

    Large-Scale Financial Education Program Impact Evaluation 2011-2012 - Mexico...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Sep 4, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    David McKenzie (2014). Large-Scale Financial Education Program Impact Evaluation 2011-2012 - Mexico [Dataset]. https://microdata.worldbank.org/index.php/catalog/2049
    Explore at:
    Dataset updated
    Sep 4, 2014
    Dataset provided by
    David McKenzie
    Miriam Bruhn
    Gabriel Lara Ibarra
    Time period covered
    2011 - 2012
    Area covered
    Mexico
    Description

    Abstract

    To educate consumers about responsible use of financial products, many governments, non-profit organizations and financial institutions have started to provide financial literacy courses. However, participation rates for non-compulsory financial education programs are typically extremely low.

    Researchers from the World Bank conducted randomized experiments around a large-scale financial literacy course in Mexico City to understand the reasons for low take-up among a general population, and to measure the impact of this financial education course. The free, 4-hour financial literacy course was offered by a major financial institution and covered savings, retirement, and credit use. Motivated by different theoretical and logistics reasons why individuals may not attend training, researchers randomized the treatment group into different subgroups, which received incentives designed to provide evidence on some key barriers to take-up. These incentives included monetary payments for attendance equivalent to $36 or $72 USD, a one-month deferred payment of $36 USD, free cost transportation to the training location, and a video CD with positive testimonials about the training.

    A follow-up survey conducted on clients of financial institutions six months after the course was used to measure the impacts of the training on financial knowledge, behaviors and outcomes, all relating to topics covered in the course.

    The baseline dataset documented here is administrative data received from a screener that was used to get people to enroll in the financial course. The follow-up dataset contains data from the follow-up questionnaire.

    Geographic coverage

    Mexico City

    Analysis unit

    -Individuals

    Universe

    Participants in a financial education evaluation

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Researchers used three different approaches to obtain a sample for the experiment.

    The first one was to send 40,000 invitation letters from a collaborating financial institution asking about interest in participating. However, only 42 clients (0.1 percent) expressed interest.

    The second approach was to advertise through Facebook, with an ad displayed 16 million times to individuals residing in Mexico City, receiving 119 responses.

    The third approach was to conduct screener surveys on streets in Mexico City and outside branches of the partner institution. Together this yielded a total sample of 3,503 people. Researchers divided this sample into a control group of 1,752 individuals, and a treatment group of 1,751 individuals, using stratified randomization. A key variable used in stratification was whether or not individuals were financial institution clients. The analysis of treatment impacts is based on the sample of 2,178 individuals who were financial institution clients.

    The treatment group received an invitation to participate in the financial education course and the control group did not receive this invitation. Those who were selected for treatment were given a reminder call the day before their training session, which was at a day and time of their choosing.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The follow-up survey was conducted between February and July 2012 to measure post-training financial knowledge, behavior and outcomes. The questionnaire was relatively short (about 15 minutes) to encourage participation.

    Interviewers first attempted to conduct the follow-up survey over the phone. If the person did not respond to the survey during the first attempt, researchers offered one a 500 pesos (US$36) Walmart gift card for completing the survey during the second attempt. If the person was still unavailable for the phone interview, a surveyor visited his/her house to conduct a face-to-face interview. If the participant was not at home, the surveyor delivered a letter with information about the study and instructions for how to participate in the survey and to receive the Walmart gift card. Surveyors made two more attempts (three attempts in total) to conduct a face-to-face interview if a respondent was not at home.

    Response rate

    72.8 percent of the sample was interviewed in the follow-up survey. The attrition rate was slightly higher in the treatment group (29 percent) than in the control group (25.3 percent).

  10. Level of self assessed financial literacy in the U.S. 2014, by investable...

    • statista.com
    Updated Sep 16, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2014). Level of self assessed financial literacy in the U.S. 2014, by investable assets [Dataset]. https://www.statista.com/statistics/379652/self-assessed-financial-literacy-usa-by-investable-assets/
    Explore at:
    Dataset updated
    Sep 16, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 16, 2014 - Jul 21, 2014
    Area covered
    United States
    Description

    This statistic presents the level of self assessed financial literacy in the United States in 2014, by investable assets. During the survey period, it was found that ** percent of the respondents with investable assets worth ******* U.S. dollars and more admitted that they were very financially literate.

  11. w

    Financial Literacy Survey 2009 - Azerbaijan

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Sep 26, 2013
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Azerbaijan Micro-finance Association (AMFA) (2013). Financial Literacy Survey 2009 - Azerbaijan [Dataset]. https://microdata.worldbank.org/index.php/catalog/1024
    Explore at:
    Dataset updated
    Sep 26, 2013
    Dataset authored and provided by
    Azerbaijan Micro-finance Association (AMFA)
    Time period covered
    2009
    Area covered
    Azerbaijan
    Description

    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.

  12. Financial Literacy Meta-analysis - Extracted Data (Final).pdf

    • figshare.com
    pdf
    Updated May 25, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Danny Jang; Linda D Simpson (2025). Financial Literacy Meta-analysis - Extracted Data (Final).pdf [Dataset]. http://doi.org/10.6084/m9.figshare.29144621.v1
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 25, 2025
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Danny Jang; Linda D Simpson
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset accompanies the meta-analysis titled "What Actually Works? A Meta-Analysis of Financial Literacy Interventions Across Age Groups and Delivery Methods." It contains coded data from 12 high-rigor quantitative studies evaluating financial literacy programs for youth aged 10 to 24. Variables include study identifiers, sample sizes, age group, delivery method, intervention type, instructional intensity, follow-up timing, outcome domain (knowledge, behavior, attitudes), effect sizes (Hedges’ g), and moderator codes. The dataset was used to calculate pooled effect sizes and conduct moderator analysis using a random-effects model.

  13. Data Financial Literacy.xlsx

    • figshare.com
    xlsx
    Updated May 16, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sri Rahayu Hijrah Hati (2024). Data Financial Literacy.xlsx [Dataset]. http://doi.org/10.6084/m9.figshare.25837177.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    May 16, 2024
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Sri Rahayu Hijrah Hati
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This study examines the effects of religiosity and Islamic financial literacy on Muslims' financial behavior and well-being

  14. i

    Grant Giving Statistics for Financial Literacy of South Texas Foundation

    • instrumentl.com
    Updated Feb 26, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2022). Grant Giving Statistics for Financial Literacy of South Texas Foundation [Dataset]. https://www.instrumentl.com/990-report/financial-literacy-of-south-texas-foundation-formerly-cccssa-foundation
    Explore at:
    Dataset updated
    Feb 26, 2022
    Area covered
    South Texas, Texas
    Variables measured
    Total Assets, Total Giving, Average Grant Amount
    Description

    Financial overview and grant giving statistics of Financial Literacy of South Texas Foundation

  15. Data from: Financial Literacy Resources

    • clevelandfed.org
    Updated Sep 22, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Reserve Bank of Cleveland (2023). Financial Literacy Resources [Dataset]. https://www.clevelandfed.org/financial-literacy-resources
    Explore at:
    Dataset updated
    Sep 22, 2023
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Description

    Get ready for an adventure! Browse our collection of free and fun educational games that are designed to engage students while teaching them personal finance concepts and skills.

  16. w

    Identifying Combined Effects of Financial Education on Migrant Households in...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Apr 2, 2015
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    David McKenzie (2015). Identifying Combined Effects of Financial Education on Migrant Households in Indonesia 2010-2012, Randomized Experiment - Indonesia [Dataset]. https://microdata.worldbank.org/index.php/catalog/2235
    Explore at:
    Dataset updated
    Apr 2, 2015
    Dataset provided by
    Bilal Zia
    Yoko Doi
    David McKenzie
    Time period covered
    2010 - 2012
    Area covered
    Indonesia
    Description

    Abstract

    Policymakers and much of the migration literature have long worried that the majority of remittances are used for consumption purposes, not savings or investment, reducing their long-term development potential. One of the main policy responses to try and increase savings from remittances and improve financial management among remittance receivers has been the introduction of financial literacy programs for migrants and/or their families.

    Researchers from the World Bank conducted a randomized experiment in Indonesia in the context of a pilot program on financial literacy for female overseas migrant workers and their families. The program was developed as a partnership between the Government of Indonesia and the World Bank, and implemented in Greater Malang area and Blitar District of East Java Province. The training program emphasized financial planning and management, savings, debt management, sending and receiving remittances, and understanding migrant insurance. One key policy question is whether such information is best delivered to the migrant worker herself, to someone in their remaining household, or to both. The experiment directly tested these options using three treatment groups: a group in which only the migrant worker receives training, a group in which the main remittance receiver or decision-maker in the remaining household receives training, and a group in which both receive training.

    The baseline survey was conducted on a rolling basis from February to June 2010 to coincide with the training cycle. After the training, three rounds of follow-up surveys were administered to family members left behind. The follow-up surveys were conducted from March 2011 to January 2012, at time intervals corresponding to the migrant being 9, 15, and 19 months abroad on average. The follow-up data was then used to measure impacts on the financial knowledge, behaviors, and remittance and savings outcomes of the remaining household.

    Researchers collaborated with Malang's Manpower and Transmigration Office and 11 migrant workers' recruiting agencies (PPTKIS) based in Greater Malang to obtain a sample of 400 migrant workers and their families.

    Geographic coverage

    Greater Malang

    Analysis unit

    • Migrant workers
    • Family members of migrant workers

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The recruitment of respondents was conducted on a rolling basis, with the project team periodically contacting the 11 PPTKIS (Privately-owned Indonesian Manpower Placement Company) to obtain lists of workers originating in the Greater Malang and Blitar districts who were recruited by these companies to work abroad. The PPTKIS selected workers who were either staying in their dormitory facilities while undergoing training, or otherwise lived close by. These PPTKIs recruit both males and females, but the males typically do not come and stay in dormitory accommodation, so males were only selected if they lived nearby. They did not screen workers for interest in participating in training, so the workers should be considered as broadly representative of Indonesian female migrants. Researchers set a target sample size of 400 households, and continued to collect workers in batches from these recruiting agencies until this target had been met.

    As batches of worker names were received from the PPTKIS, they were entered by project staff onto an Excel worksheet in the order listed by the PPTKIS, and a random number generator used to assign individuals to a treatment status. Since batches of workers were often not of size divisible by four, and were of varying numbers, and that the only information available on the workers was basic data supplied by the PPTKIS, the research team did not stratify the randomization. The sample of 400 migrant workers was randomly assigned into one of the following groups:

    • Treatment A: Financial literacy training is provided to the migrant worker only
    • Treatment B: Financial literacy training is provided to the migrant worker's household member only
    • Treatment C: Financial literacy training is provided separately to both the migrant workers and to their household members
    • Group D: Control group with no financial literacy training provided

    Out of the sample of 400 migrant workers, this random assignment resulted in 101 migrant households being assigned to treatment A, 97 - to treatment B, 98 - to treatment C, and 104 - to a control group.

    Mode of data collection

    Face-to-face [f2f]

  17. Financial Literacy and Financial Services Survey 2011 - Bosnia-Herzegovina

    • microdata.worldbank.org
    • microdata.unhcr.org
    • +2more
    Updated Sep 26, 2013
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    IPSOS (2013). Financial Literacy and Financial Services Survey 2011 - Bosnia-Herzegovina [Dataset]. https://microdata.worldbank.org/index.php/catalog/1025
    Explore at:
    Dataset updated
    Sep 26, 2013
    Dataset authored and provided by
    IPSOShttp://www.ipsos.com/
    Time period covered
    2011
    Area covered
    Bosnia and Herzegovina
    Description

    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%
  18. i

    Grant Giving Statistics for American Financial Literacy Council

    • instrumentl.com
    Updated Jun 27, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2022). Grant Giving Statistics for American Financial Literacy Council [Dataset]. https://www.instrumentl.com/990-report/american-financial-literacy-council
    Explore at:
    Dataset updated
    Jun 27, 2022
    Variables measured
    Total Assets
    Description

    Financial overview and grant giving statistics of American Financial Literacy Council

  19. Financial literacy rate in Indonesia 2025, by education level

    • statista.com
    Updated Jun 12, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Financial literacy rate in Indonesia 2025, by education level [Dataset]. https://www.statista.com/statistics/1615722/indonesia-financial-literacy-by-education-level/
    Explore at:
    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Indonesia
    Description

    As of February 2025, the financial literacy rate among Indonesians who completed university was the highest among other education levels, with a share of around ***** percent. In comparison, Indonesians who didn't complete elementary school had a financial literacy rate of **** percent.

  20. w

    Financial Literacy and Financial Services Survey 2010 - Romania

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Sep 26, 2013
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Institute for World Economy (Romanian Academy) (2013). Financial Literacy and Financial Services Survey 2010 - Romania [Dataset]. https://microdata.worldbank.org/index.php/catalog/1027
    Explore at:
    Dataset updated
    Sep 26, 2013
    Dataset authored and provided by
    Institute for World Economy (Romanian Academy)
    Time period covered
    2010
    Area covered
    Romania
    Description

    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.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
DC Health, Cancer and Chronic Disease Prevention Bureau, Public Health Analyst (2025). Money Management and Financial Literacy [Dataset]. https://catalog.data.gov/dataset/money-management-and-financial-literacy

Money Management and Financial Literacy

Explore at:
39 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 23, 2025
Dataset provided by
DC Health, Cancer and Chronic Disease Prevention Bureau, Public Health Analyst
Description

These services help with money management, financial planning, and insurance education. These services are not all dementia-specific but are inclusive of those living with dementia or who are planning for future memory loss. We include larger organizations that provide these services but have not included individual/private financial planners.

Search
Clear search
Close search
Google apps
Main menu