Personal Finance Education Market Outlook

According to our latest research, the global market size for Personal Finance Education reached $1.82 billion in 2024. The market is demonstrating robust momentum, expanding at a CAGR of 7.6% during the forecast period. By 2033, the market is projected to attain a value of $3.54 billion, fueled by the growing recognition of financial literacy as a crucial life skill, the integration of digital learning platforms, and increasing regulatory mandates for financial education in schools and workplaces. This growth trajectory highlights the sector’s vital role in empowering individuals across all age groups to make informed financial decisions, manage debt, and plan for long-term financial well-being.

One of the primary growth factors propelling the Personal Finance Education Market is the escalating complexity of financial products and services. As consumers encounter a broader array of investment options, credit products, and digital banking solutions, the need for comprehensive financial education becomes imperative. The proliferation of fintech innovations, such as cryptocurrencies and decentralized finance, has further accentuated the gap in financial knowledge. Consequently, educational institutions, employers, and financial service providers are increasingly investing in tailored financial literacy programs to equip individuals with the skills necessary to navigate these evolving financial landscapes. This trend is particularly pronounced among younger demographics, who are entering the workforce with limited exposure to personal finance concepts but face significant financial decisions related to student loans, credit management, and retirement planning.

Another significant driver is the widespread adoption of technology-enabled learning platforms. The digital transformation of education has revolutionized the delivery of personal finance education, making it more accessible, engaging, and customizable. Online courses, mobile applications, and interactive tools have democratized access to financial literacy resources, enabling users to learn at their own pace and according to their unique needs. The COVID-19 pandemic accelerated this shift, as remote learning became the norm and organizations sought scalable solutions for educating diverse populations. This digital shift has also facilitated the integration of gamification, personalized feedback, and real-time progress tracking, which have proven effective in enhancing learner engagement and retention in personal finance education programs.

Regulatory initiatives and public-private partnerships are also playing a pivotal role in market expansion. Governments and regulatory bodies across several regions are mandating the inclusion of financial literacy in school curricula and workplace training programs. These policies are designed to address pressing societal issues such as rising consumer debt, inadequate retirement savings, and financial vulnerability. In parallel, collaborations between educational institutions, financial institutions, non-profits, and private companies are fostering the development and dissemination of high-quality financial education content. These joint efforts are enabling the creation of standardized frameworks, assessment tools, and certification programs, further professionalizing the field and ensuring consistent learning outcomes.

From a regional perspective, North America leads the global Personal Finance Education Market, accounting for more than 38% of the total market share in 2024. This dominance is attributed to strong regulatory support, high digital adoption rates, and a mature ecosystem of financial education providers. Europe and Asia Pacific are also witnessing substantial growth, driven by rising awareness of financial literacy, expanding middle-class populations, and government-led initiatives. While Latin America and the Middle East & Africa currently represent smaller shares of the market, these regions are expected to exhibit above-average growth rates over the forecast period, spurred by increasing smartphone penetration and targeted financial inclusion programs.

Delivery Method Analysis

The Delivery Method segment of the Personal Finance Education Market is characterized by a diverse array of channels, each catering to different learning preferences and accessibility needs. Online courses have emerged as the most significant delivery mechanism, capturing a substantial share of the market d

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

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.

The table shows the average monthly pocket money per age group

AbstractWe study the effect of inconsistent time preferences on actual and planned retirement timing decisions in two independent datasets. Theory predicts that hyperbolic time preferences can lead to dynamically inconsistent retirement timing. In an online experiment with more than 2,000 participants, we find that time-inconsistent participants retire on average 1.75 years earlier than time-consistent participants do. The planned retirement age of non-retired participants decreases with age. This negative age effect is about twice as strong among time-inconsistent participants. The temptation of early retirement seems to rise in the final years of approaching retirement. Consequently, time-inconsistent participants have a higher probability of regretting their retirement decision. We find similar results for a representative household survey (German SAVE panel). Using smoking behavior and overdraft usage as time preference proxies, we confirm that time-inconsistent participants retire earlier and that non-retirees reduce their planned retirement age within the panel.MethodsWe conduct an online experiment in cooperation with a large and well-circulated German newspaper, the Frankfurter Allgemeine Zeitung (FAZ). Participants are recruited via a link on the newspaper's website and two announcements in the print edition. In total, 3,077 participants complete the experiment, which takes them on average 11 minutes. Participants answer questions about retirement planning, time preferences, risk preferences, financial literacy, and demographics. The initial sample for this study consists of 256 retired participants and 2,173 non-retired participants.Usage NotesOur dataset: STATA Do File is attached Additional Datasets: In addition, a German Household Panle is used in this paper. The data cannot be uploaded by us but is available via the Max Planck Institute (https://www.mpisoc.mpg.de/en/social-policy-mea/research/save-2001-2013/). We upload the Do-Files used in the analysis and the results in an excel format (xlsx).

United Arab Emirates AE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Secondary Education Or More: % of Population Aged 15+ data was reported at 88.876 % in 2017. This records an increase from the previous number of 84.649 % for 2014. United Arab Emirates AE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Secondary Education Or More: % of Population Aged 15+ data is updated yearly, averaging 84.649 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 88.876 % in 2017 and a record low of 61.333 % in 2011. United Arab Emirates AE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Secondary Education Or More: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Arab Emirates – Table AE.World Bank: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (secondary education or more, % of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Abstract

Many of North Volta Rural Bank's customers who are salaried workers, and therefore receive their pay via direct deposit to NVRB, make frequent use of high interest payday loans (temporary overdrafts). As part of a randomized controlled trial, including 245 men and 75 women, NVRB offered a product to these customers in which they commit to having a fixed amount taken directly from their salary and put in a commitment savings account, for an 18-month period.

The key questions this study is designed to answer are (i) How do individuals adjust their finances in response to regular, automated savings withdrawals? (ii) What do they spend the lump sum on? (iii) Are there any long-term impacts of having participated in the commitment savings program on economic activities, savings, debt, or spending behavior? (iv) How are these impacts different for men versus for women?

The baseline survey data collection for this study took place during September and October 2013. This baseline dataset includes data from 318 individuals: 243 men and 75 women.

Geographic coverage

The study sample is comprised of individuals holding bank accounts with North Volta Rural Bank (NVRB), which is a fairly small bank with just eight branches, all of which are in the northern part of Ghana’s Volta Region. NVRB’s eight branches are located in eight communities across five districts: Dambai in Kratchi East District; Abotoase in the Biakoye District; Ayoma, Guaman and Jasikan in Jasikan District; Kedjebi and Papase in Kedjebi District; and Nkwanta in the Nkwanta South District. Study participants reside in predominantly rural communities in the following districts: Jasikan, Kratchi East, Kratchi West, Biakoye, Nkwanta North, Nkwanta South. Additionally, some study participants live in the larger municipalities of Hohoe and Kpando.

Analysis unit

Individuals

Universe

This baseline survey dataset is comprised of 318 individuals who are account-holders with North Volta Rural Bank and who have their salary directly deposited into an NVRB account, and who consented to participate in this baseline survey.

Gender: 243 are men and 75 are women.

Occupation: All are salaried workers. 31 are staff of NVRB, and most of the other 287 individuals are civil servants. Many are also involved in other livelihood activities.

Education: Most study participants are secondary school graduates.

Age: All are between the ages of 18 and 57 at the time of baseline. 18 is the minimum age for holding a bank account with NVRB, and the study sought to exclude individuals who would retire during the study’s two-year duration, and Ghanaian civil servants are required to retire at age 60. At baseline, the average age of study participants was 30.

Residence: All resided in the study area at the time of the baseline survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Data was collected from individuals using a household survey administered to the study participants. The survey was written and administered in English, and took approximately 90 to 120 minutes to administer.

The questionnaire covers the following: 1 - Respondent ID and survey information 2 - Demographics 3- Questions using a 10-step ladder 4 - Expenditures 5 - Hypothetical use of a hypothetical lump-sum transfer 6 - General questions on finances, financial strain, self-control, and financial literacy 7 - Time preferences 8 - Household roster, including financial support provided to individuals outside of the household 9 - Food security and financial shocks 10 - Housing quality and household assets 11 - Income 12 - Savings 13 - Debt 14 - Intra-household decision-making and preference alignment 15 - Livestock 16 - Land

Cleaning operations

Survey responses were recorded on paper, and were entered using double-data entry and reconciliation.

Data appraisal

A minimum of 10% of survey participants were visited by an independent auditor who completed an audit questionnaire with the household, which was then compared to the household survey for that individual. Discrepancies found during the audit resulted in additional training, guidance, and changes in personnel as needed.

Vietnam VN: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Primary Education Or Less: % of Population Aged 15+ data was reported at 13.047 % in 2017. This records a decrease from the previous number of 15.341 % for 2014. Vietnam VN: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Primary Education Or Less: % of Population Aged 15+ data is updated yearly, averaging 13.047 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 15.341 % in 2014 and a record low of 4.506 % in 2011. Vietnam VN: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Primary Education Or Less: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (primary education or less, % of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

The A*CENSUS, the first comprehensive survey of individuals in the archival profession since 1982, was designed to collect baseline demographic data on archivists in the workforce in the United States, identify the knowledge and skills archivists need to do their jobs and adapt to future demands, and gauge the capacity of graduate and continuing education programs to deliver the necessary knowledge and skills. Detailed information was collected from all respondents in the following subject areas: basic demographic information (age, gender, race/ethnicity), employment (full/part-time, average hours per week, type of employer, years employed, functions), education (degrees, majors, years awarded), training and continuing education (sources, delivery formats and methods, support from employer for obtaining, barriers to obtaining, topical priorities), career paths (impetus for first archival job, careers prior to entering archival work, plans to leave archival work including retirement), professional association affiliation (membership in archival and other associations, support from employer for participation, impetus for joining), leadership/professional involvement (conference attendance, presentations, publications authored, teaching experience, leadership positions in archival and nonarchival organizations, strength of ties to archival profession), and issues of greatest importance.

Most of the new vehicles in the United States in 2025 were acquired using some kind of financing, such as loans or leases. Meanwhile, only slightly over a ***** of used cars were purchased using some financing option. Over ** percent of new cars had financing, a figure that has remained relatively stable in the past three years. In 2025, the share of used cars acquired with financing was somewhat lower than in 2022. The interest rates for automobile loans in the United States have significantly risen since early 2022, which has increased the burden on borrowers. How common is delinquency in the context of auto financing? The delinquency rate refers to the proportion of loans within a portfolio or market segment that are past due or in default. In 2024, the share of 90+ delinquent auto loans in the United States stood at nearly **** percent. However, the share of auto loan borrowers who had loan payments that were overdue by at least 90 days had risen significantly by 2024. Which age group exhibits more auto loan delinquency? There are several factors that can influence the likelihood of a certain group having higher delinquency rates, such as financial literacy, income disparities, credit histories, and age. When looking at the delinquency rate by age group in the U.S. in 2023, it could be observed that people aged 18 to 29 had the highest share of car loans that eventually led to serious delinquency. In contrast, people that were over 50 years old had a much lower serious average delinquency rate at less than *** percent that year.

Argentina AR: Account: Primary Education or Less: % Aged 15+ data was reported at 52.268 % in 2014. This records an increase from the previous number of 28.272 % for 2011. Argentina AR: Account: Primary Education or Less: % Aged 15+ data is updated yearly, averaging 40.270 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 52.268 % in 2014 and a record low of 28.272 % in 2011. Argentina AR: Account: Primary Education or Less: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (primary education or less, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

The debt settlement solution market is experiencing significant growth, driven by rising consumer debt levels and increasing awareness of debt relief options. While precise market size figures for the base year (2025) are unavailable, a reasonable estimate, considering the average market growth of similar financial services and consulting sectors, could place the market value at approximately $5 billion in 2025. This is based on a projected CAGR (let's assume a CAGR of 10% for illustrative purposes, reflecting a healthy but realistic growth rate within the financial services sector) and taking into account factors like increased personal debt, economic downturns, and the evolving regulatory landscape affecting the debt relief industry. The market is segmented by various service types (negotiation with creditors, debt consolidation, bankruptcy assistance, etc.), customer demographics (age, income, debt type), and geographic location. Key market drivers include the persistent rise in household debt, particularly student loan debt and credit card debt, coupled with limited financial literacy among consumers, making them vulnerable to unsustainable debt burdens. Growing marketing and advertising efforts by debt relief companies also contribute to market growth. However, market growth faces several restraints. Stringent regulatory frameworks and increased scrutiny from consumer protection agencies are shaping industry practices and potentially limiting aggressive marketing. Economic fluctuations directly impact consumer debt levels and their ability to afford debt settlement services. Furthermore, the negative perception associated with debt settlement, despite its potential benefits in certain situations, continues to deter some consumers seeking relief. The competitive landscape is also intensifying with both established players like National Debt Relief and Freedom Debt Relief, and new entrants vying for market share. Successful companies will need to differentiate themselves through superior customer service, transparent pricing, and a proven track record of successful debt settlements, navigating a complex regulatory environment while effectively communicating the value proposition to consumers. Future market growth will depend on economic conditions, regulatory changes, and the continued development of innovative and consumer-friendly debt solutions.

This study was in response to Grant Number HHS-2020-ACF-OZA-ZB-1817 from the Office of Family Assistance (OFA) within the Administration for Children and Families (ACF, U.S. Department of Health and Human Services (HHS). Study enrollment began on April 1, 2021, and continued through March 1, 2024. The sample size for the study was 1,403. The goal of the descriptive evaluation was to assess the extent to which participation in the program was associated with improved parenting, co-parenting, and financial attitudes and behaviors among program participants. The aim of the AVANCE-Houston FRAMEWorks program was to promote healthy family relationships and economic stability, particularly in areas with a high number of single-family households, high poverty rates, low educational attainment, and high incidences of domestic violence. We believe this report can inform practitioners in the HMRF field and beyond about innovative approaches that help adults from predominately low-income households build the skills necessary to engage in healthy relationships and economic behaviors. Primary research questions for this study are as follows: a) How did parenting attitude outcomes change from program enrollment to program completion? b) How did parenting behavior outcomes change from program enrollment to one year after enrollment? c) How did partner relationship attitude outcomes change from program enrollment to program completion? d) How did partner relationship behavior outcomes change from program enrollment to one year after enrollment? e) How did employment attitude outcomes change from program enrollment to one year after enrollment? f) How did financial readiness behavior outcomes change from program enrollment to one year after enrollment? Secondary research questions for this study are as follows: g) How did participant outcomes above change from program enrollment to program completion or one year after enrollment when delivering the SSHF curriculum with a virtual format compared to an in-person format? h) How did participant outcomes above change from program enrollment to program completion or one year after enrollment when delivering the SSHF curriculum in English-language compared to Spanish-language? Implementation study research questions are as follows: a) To what extent is the SSHF curriculum received by program participants? b) What were the unplanned adaptations to key intervention components? Participants in the study resided in the greater Houston, TX area. At 76%, the majority of AVANCE FRAMEWorks participants received the program virtually. The average age of participants was 40 years, and almost three-fourths reported that they were in a relationship. The average age of their youngest child was just above eight years of age. Most (75%) participants were female. The majority of participants (64%) indicated they were Hispanic, with exactly 50% reporting their race as White and 26% as Black or African American. About 44% of participants reported having full-time employment, and 35% reported being either unemployed or a stay-at-home parent/homemaker at the time of survey completion. Paired t-tests were conducted on continuous constructs using timepoint 1 (nFORM Entrance, OLLE Pre) and timepoint 2 (nFORM Exit, OLLE Post, OLLE Follow-Up) data. For categorical variables—such as yes/no questions about having a checking or savings account or a resume—McNemar’s chi-square tests were used to compare pre- to post-test differences in proportions. Statistical significance was set at p<0.05, and no adjustments for multiple comparisons were made. Tests were reported in terms of p-values. Results were significant and positive for participants’ partner relationships, financial readiness, and employment outlook. We did not find a significant association with the parenting attitudes outcome, measured from baseline to post-program, or parenting behaviors outcome, measured from baseline to one-year post-enrollment. When analyzing virtual and in-person subgroups, we found the same positive results in the group of participants who received the program virtually compared to the overall results. We also found similar results for participants who received the program in person; however, there was not a significant association with employment outlook. We found high rates of program retention, with 95% of participants reaching the required number of curriculum hours on average.

Goal 8Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allTarget 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 per cent gross domestic product growth per annum in the least developed countriesIndicator 8.1.1: Annual growth rate of real GDP per capitaNY_GDP_PCAP: Annual growth rate of real GDP per capita (%)Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, including through a focus on high-value added and labour-intensive sectorsIndicator 8.2.1: Annual growth rate of real GDP per employed personSL_EMP_PCAP: Annual growth rate of real GDP per employed person (%)Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial servicesIndicator 8.3.1: Proportion of informal employment in total employment, by sector and sexSL_ISV_IFEM: Proportion of informal employment, by sector and sex (ILO harmonized estimates) (%)Target 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadIndicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDPEN_MAT_FTPRPG: Material footprint per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollar)EN_MAT_FTPRPC: Material footprint per capita, by type of raw material (tonnes)EN_MAT_FTPRTN: Material footprint, by type of raw material (tonnes)Indicator 8.4.2: Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDPEN_MAT_DOMCMPT: Domestic material consumption, by type of raw material (tonnes)EN_MAT_DOMCMPG: Domestic material consumption per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollars)EN_MAT_DOMCMPC: Domestic material consumption per capita, by type of raw material (tonnes)Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal valueIndicator 8.5.1: Average hourly earnings of employees, by sex, age, occupation and persons with disabilitiesSL_EMP_EARN: Average hourly earnings of employees by sex and occupation (local currency)Indicator 8.5.2: Unemployment rate, by sex, age and persons with disabilitiesSL_TLF_UEM: Unemployment rate, by sex and age (%)SL_TLF_UEMDIS: Unemployment rate, by sex and disability (%)Target 8.6: By 2020, substantially reduce the proportion of youth not in employment, education or trainingIndicator 8.6.1: Proportion of youth (aged 15–24 years) not in education, employment or trainingSL_TLF_NEET: Proportion of youth not in education, employment or training, by sex and age (%)Target 8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labour, including recruitment and use of child soldiers, and by 2025 end child labour in all its formsIndicator 8.7.1: Proportion and number of children aged 5–17 years engaged in child labour, by sex and ageSL_TLF_CHLDEC: Proportion of children engaged in economic activity and household chores, by sex and age (%)SL_TLF_CHLDEA: Proportion of children engaged in economic activity, by sex and age (%)Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employmentIndicator 8.8.1: Fatal and non-fatal occupational injuries per 100,000 workers, by sex and migrant statusSL_EMP_FTLINJUR: Fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)SL_EMP_INJUR: Non-fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)Indicator 8.8.2: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation, by sex and migrant statusSL_LBR_NTLCPL: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislationTarget 8.9: By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and productsIndicator 8.9.1: Tourism direct GDP as a proportion of total GDP and in growth rateST_GDP_ZS: Tourism direct GDP as a proportion of total GDP (%)Target 8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to banking, insurance and financial services for allIndicator 8.10.1: (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adultsFB_ATM_TOTL: Number of automated teller machines (ATMs) per 100,000 adultsFB_CBK_BRCH: Number of commercial bank branches per 100,000 adultsIndicator 8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service providerFB_BNK_ACCSS: Proportion of adults (15 years and older) with an account at a financial institution or mobile-money-service provider, by sex (% of adults aged 15 years and older)Target 8.a: Increase Aid for Trade support for developing countries, in particular least developed countries, including through the Enhanced Integrated Framework for Trade-related Technical Assistance to Least Developed CountriesIndicator 8.a.1: Aid for Trade commitments and disbursementsDC_TOF_TRDCMDL: Total official flows (commitments) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBMDL: Total official flows (disbursement) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBML: Total official flows (disbursement) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_TRDCML: Total official flows (commitments) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)Target 8.b: By 2020, develop and operationalize a global strategy for youth employment and implement the Global Jobs Pact of the International Labour OrganizationIndicator 8.b.1: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategySL_CPA_YEMP: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategy

Colombia CO: Account: Primary Education or Less: % Aged 15+ data was reported at 19.622 % in 2014. This records an increase from the previous number of 15.748 % for 2011. Colombia CO: Account: Primary Education or Less: % Aged 15+ data is updated yearly, averaging 17.685 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 19.622 % in 2014 and a record low of 15.748 % in 2011. Colombia CO: Account: Primary Education or Less: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (primary education or less, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

This data collection contains information from the first wave of High School and Beyond (HSB), a longitudinal study of American youth conducted by the National Opinion Research Center on behalf of the National Center for Education Statistics (NCES). Data were collected from 58,270 high school students (28,240 seniors and 30,030 sophomores) and 1,015 secondary schools in the spring of 1980. Many items overlap with the NCES's NATIONAL LONGITUDINAL STUDY OF THE CLASS OF 1972 (ICPSR 8085). The HSB study's data are contained in eight files. Part 1 (School Data) contains data from questionnaires completed by high school principals about various school attributes and programs. Part 2 (Student Data) contains data from surveys administered to students. Included are questionnaire responses on family and religious background, perceptions of self and others, personal values, extracurricular activities, type of high school program, and educational expectations and aspirations. Also supplied are scores on a battery of cognitive tests including vocabulary, reading, mathematics, science, writing, civics, spatial orientation, and visualization. To gather the data in Part 3 (Parent Data), a subsample of the seniors and sophomores surveyed in HSB was drawn, and questionnaires were administered to one parent of each of 3,367 sophomores and of 3,197 seniors. The questionnaires contain a number of items in common with the student questionnaires, and there are a number of items in common between the parent-of-sophomore and the parent-of-senior questionnaires. This is a revised file from the one originally released in Autumn 1981, and it includes 22 new analytically constructed variables imputed by NCES from the original survey data gathered from parents. The new data are concerned primarily with the areas of family income, liabilities, and assets. Other data in the file concentrate on financing of post-secondary education, including numerous parent opinions and projections concerning the educational future of the student, anticipated financial aid, student's plans after high school, expected ages for student's marriage and childbearing, estimated costs of post-secondary education, and government financial aid policies. Also supplied are data on family size, value of property and other assets, home financing, family income and debts, and the age, sex, marital, and employment status of parents, plus current income and expenses for the student. Part 4 (Language Data) provides information on each student who reported some non-English language experience, with data on past and current exposure to and use of languages. In Parts 5-6, there are responses from 14,103 teachers about 18,291 senior and sophomore students from 616 schools. Students were evaluated by an average of four different teachers who had the opportunity to express knowledge or opinions of HSB students whom they had taught during the 1979-1980 school year. Part 5 (Teacher Comment Data: Seniors) contains 67,053 records, and Part 6 (Teacher Comment Data: Sophomores) contains 76,560 records. Questions were asked regarding the teacher's opinions of their student's likelihood of attending college, popularity, and physical or emotional handicaps affecting school work. The sophomore file also contains questions on teacher characteristics, e.g., sex, ethnic origin, subjects taught, and time devoted to maintaining order. The data in Part 7 (Twins and Siblings Data) are from students in the HSB sample identified as twins, triplets, or other siblings. Of the 1,348 families included, 524 had twins or triplets only, 810 contained non-twin siblings only, and the remaining 14 contained both types of siblings. Finally, Part 8 (Friends Data) contained the first-, second-, and third-choice friends listed by each of the students in Part 2, along with identifying information allowing links between friendship pairs.

Egypt EG: Account: Primary Education or Less: % Aged 15+ data was reported at 8.399 % in 2014. This records an increase from the previous number of 5.373 % for 2011. Egypt EG: Account: Primary Education or Less: % Aged 15+ data is updated yearly, averaging 6.886 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 8.399 % in 2014 and a record low of 5.373 % in 2011. Egypt EG: Account: Primary Education or Less: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Egypt – Table EG.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (primary education or less, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

In most countries basic education is nowadays perceived not only as a right, but also as a duty – governments are typically expected to ensure access to basic education, while citizens are often required by law to attain education up to a certain basic level.1

This was not always the case: the advancement of these ideas began in the mid-19th century, when most of today’s industrialized countries started expanding primary education, mainly through public finances and government intervention. Data from this early period shows that government funds to finance the expansion of education came from a number of different sources, but taxes at the local level played a crucial role. The historical role of local funding for public schools is important to help us understand changes – or persistence – in regional inequalities.

The second half of the 20th century marked the beginning of education expansion as a global phenomenon. Available data shows that by 1990 government spending on education as a share of national income in many developing countries was already close to the average observed in developed countries.2

This global education expansion in the 20th century resulted in a historical reduction in education inequality across the globe: in the period 1960-2010 education inequality went down every year, for all age groups and in all world regions. Recent estimates of education inequality across age groups suggest that further reductions in schooling inequality are still to be expected within developing countries.3

Recent cross-country data from UNESCO tells us that the world is expanding government funding for education today, and these additional public funds for education are not necessarily at the expense of other government sectors. Yet behind these broad global trends, there is substantial cross-country – and cross-regional – heterogeneity. In high-income countries, for instance, households shoulder a larger share of education expenditures at higher education levels than at lower levels – but in low-income countries, this is not the case.

Following the agreement of the Millennium Development Goals, the first decade of the 21st century saw an important increase in international financial flows under the umbrella of development assistance. Recent estimates show that development assistance for education has stopped growing since 2010, with notable aggregate reductions in flows going to primary education. These changes in the prioritization of development assistance for education across levels and regions can have potentially large distributional effects, particularly within low-income countries that depend substantially on this source of funding for basic education.4

When analyzing correlates, determinants and consequences of education consumption, the macro data indicates that national expenditure on education does not explain well cross-country differences in learning outcomes. This suggests that for any given level of expenditure, the output achieved depends crucially on the mix of many inputs.

Re-interview of high school students after ca. 15 years on data on the course of private and occupational life as well as questions on attitudes.

Topics: conclusion of education; contacts with former students; detailed information on school and occupational training as well as activities after leaving high school; type of entitlement to university admission and average grade in high school graduation; reasons for not attending college; questions on sequence of college and vocational training; interest in other training occupations and additional vocational training; desired studies; college goal; planned activity instead of college; identity of original studies desired and actual studies; preferred subjects; conclusion or discontinuation of studies; attitude to studies; change of major; detailed information about preliminary examinations, intermediate examinations and final examinations and information on points in time; sources of income or financing of studies; employment alongside studies and influence of this activity on duration of studies; usable experiences for studies and later occupational career from activities during studies; connection between main focus of studies and first occupational activity; year of first full-time employment; detailed information about occupational development; activity description and changes as well as length of time and area of business of first jobs; occupational position and time worked each week; income changes between start and end of the job; reasons for change of position; satisfaction with occupational development and expected development of one´s own occupational position in the next few years; satisfaction with education up to now; interest in employment; assumed point in time for start of employment; preferred occupation; participation in measures for occupational further education; detailed information about form and content of these courses; judgement on these measures for further education for occupational career; detailed determination of occupational training examinations and final examinations according to topics and point in time as well as grades; detailed information on social origins; occupation of father or substitute father; year of death of father or mother; living together or separation of parents; financial support of parents for personal livelihood; year of setting up one´s own household and members or size of this household; detailed information on partnership relationship; marriage intent; type and length of partnership; attitude to a church wedding; occupation and income of partner; social origins of partner; age difference with partner; number of children; age and sex of children; responsibility for child care; desired number of children; questions on raising children and education style; education aspiration; importance of family; attitude to age; self-classification as young person or adult; judgement on prior course of life and biographical wrong decisions; significant events in life; identification with groups and movements; attribution of occupational success in general as well as relative to oneself; assessment of social class; the meaning of life; importance of areas of life; general private and occupational satisfaction.

Perceived equality of educational chances and general equal opportunities in the Federal Republic; attitude to environment, achievement and work; postmaterialism index; political interest; election biography since 1972; party preference of parents in youth of respondent; participation in demonstrations; and change of religious denomination.

Demography: date of birth; religious denomination; frequency of church attendance; housing conditions and possession of a telephone; consent of respondent to a later re-interview.

Interviewer rating: number of contact attempts; presence of third persons during interview and their influence on the conversation; judgement on reliability of responses; length of interview and date of interview.

Also encoded was: identification of interviewer.

In Sweden, people with a tertiary education have the highest average monthly salaries. In 2022, it amounted to 35,700 Swedish kronor, whereas people with a secondary or primary education earned 34,200 and 31,300, respectively. In 2022, almost 24 percent of the population in Sweden had a tertiary education.

The highest average salaries in financial institutions and insurance companies

The industry with the highest average monthly salary in Sweden in 2022 was financial institutions and insurance companies, where it amounted to over 57,000 Swedish kronor. Even within industries the salaries vary , and the occupational group with the highest average salary in Sweden in is banking, finance and insurance managers.

Women have lower salaries than men

Not only does the salary in Sweden differ between occupations, sectors, industries, and the level of education and age of the employee. Furthermore, men have a higher average salary than women. In 2022, women’s average earnings were 95 percent of men's.