Patterns of educational attainment vary greatly across countries, and across population groups within countries. In some countries, virtually all children complete basic education whereas in others large groups fall short. The primary purpose of this database, and the associated research program, is to document and analyze these differences using a compilation of a variety of household-based data sets: Demographic and Health Surveys (DHS); Multiple Indicator Cluster Surveys (MICS); Living Standards Measurement Study Surveys (LSMS); as well as country-specific Integrated Household Surveys (IHS) such as Socio-Economic Surveys.As shown at the website associated with this database, there are dramatic differences in attainment by wealth. When households are ranked according to their wealth status (or more precisely, a proxy based on the assets owned by members of the household) there are striking differences in the attainment patterns of children from the richest 20 percent compared to the poorest 20 percent.In Mali in 2012 only 34 percent of 15 to 19 year olds in the poorest quintile have completed grade 1 whereas 80 percent of the richest quintile have done so. In many countries, for example Pakistan, Peru and Indonesia, almost all the children from the wealthiest households have completed at least one year of schooling. In some countries, like Mali and Pakistan, wealth gaps are evident from grade 1 on, in other countries, like Peru and Indonesia, wealth gaps emerge later in the school system.The EdAttain website allows a visual exploration of gaps in attainment and enrollment within and across countries, based on the international database which spans multiple years from over 120 countries and includes indicators disaggregated by wealth, gender and urban/rural location. The database underlying that site can be downloaded from here.

World Religions Across Regions

Analyzing Adherence Across Regions, States and the Global System

By Correlates of War Project [source]

About this dataset

The World Religion Project (WRP) is an ambitious endeavor to conduct a comprehensive analysis of religious adherence throughout the world from 1945 to 2010. This cutting-edge project offers unparalleled insight into the religious behavior of people in different countries, regions, and continents during this time period. Its datasets provide important information about the numbers and percentages of adherents across a multitude of different religions, religion families, and non-religious affiliations.

The WRP consists of three distinct datasets: the national religion dataset, regional religion dataset, and global religion dataset. Each is focused on understanding individually specific realms for varied analysis approaches - from individual states to global systems. The national dataset provides data on number of adherents by state as well as percentage population practicing a given faith group in five-year increments; focusing attention to how this number evolves from nation to nation over time. Similarly, regional data is provided at five year intervals highlighting individual region designations with one modification – Pacific Ocean states have been reclassified into their own Oceania category according to Country Code Number 900 or above). Finally at a global level – all states are aggregated in order that we may understand a snapshot view at any five-year interval between 1945‐2010 regarding relationships between religions or religio‐families within one location or transnationally.

This project was developed in three stages: firstly forming a religions tree (a systematic classification), secondly collecting data such as this provided by WRP according to that classification structure – lastly cleaning the data so discrepancies may be reconciled and imported where needed with gaps selected when unknown values were encountered during collection process . We would encourage anyone wishing details undergoing more detailed reading/analysis relating various use applications for these rich datasets - please contact Zeev Maoz (University California Davis) & Errol A Henderson _(Pennsylvania State University)

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How to use the dataset

The World Religions Project (WRP) dataset offers a comprehensive look at religious adherence around the world within a single dataset. With this dataset, you can track global religious trends over a period of 65 years and explore how they’ve changed during that time. By exploring the WRP data set, you’ll gain insight into cross-regional and cross-time patterns in religious affiliation around the world.

Research Ideas

• Analyzing historical patterns of religious growth and decline across different regions
• Creating visualizations to compare religious adherence in various states, countries, or globally
• Studying the impact of governmental policies on religious participation over time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: WRP regional data.csv | Column name | Description | |:-----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | Year | Reference year for data collection. (Integer) | | Region | World region according to Correlates Of War (COW) Regional Systemizations with one modification (Oceania category for COW country code ...

Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data was reported at 66.721 % in 2014. This records an increase from the previous number of 60.007 % for 2011. Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 63.364 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 66.721 % in 2014 and a record low of 60.007 % in 2011. Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.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) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Trinidad and Tobago TT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 83.250 % in 2017. Trinidad and Tobago TT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 83.250 % from Dec 2017 (Median) to 2017, with 1 observations. Trinidad and Tobago TT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Trinidad and Tobago – Table TT.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 (richest 60%, share 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).

Latvia LV: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 96.342 % in 2017. This records an increase from the previous number of 92.683 % for 2014. Latvia LV: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 93.049 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 96.342 % in 2017 and a record low of 92.683 % in 2014. Latvia LV: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Latvia – Table LV.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 (richest 60%, share 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).

This dataset provides values for GOLD RESERVES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Netherlands NL: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 99.537 % in 2017. This records an increase from the previous number of 99.524 % for 2014. Netherlands NL: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 99.524 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.537 % in 2017 and a record low of 98.093 % in 2011. Netherlands NL: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Netherlands – Table NL.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 (richest 60%, share 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).

Syria SY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 22.833 % in 2011. Syria SY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 22.833 % from Dec 2011 (Median) to 2011, with 1 observations. Syria SY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Syrian Arab Republic – Table SY.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 (richest 60%, share 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).

Context

This dataset contains all the stats of Gender Statistics 2022 - World Bank.

Details

The Gender Statistics database is a comprehensive source for the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, at least one modern method of contraception. It is usually measured for women ages 15-49 who are married or in union. Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception.

Number of male sole proprietors is the number of newly registered sole proprietors owned by female individuals in the calendar year. A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.

Percentage of women aged 15–49 who have gone through partial or total removal of the female external genitalia or other injury to the female genital organs for cultural or other non-therapeutic reasons. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households. Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered. Women who own house both alone and jointly (% of women age 15-49): Q4 is the percentage of women age 15-49 who alone as well as jointly with someone else own a house which is legally registered with their name or cannot be sold without their signature. "Both alone and jointly" Implies a woman owns a house alone and another house jointly with someone else. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.

Number of infants dying before reaching one year of age. Male population between the ages 75 to 79.

The percentage of respondents who report using mobile money, a debit or credit card, or a mobile phone to make a payment from an account, or report using the internet to pay bills or to buy something online, in the past 12 months. It also includes respondents who report paying bills, sending or receiving remittances, receiving payments for agricultural products, receiving government transfers, receiving wages, or receiving a public sector pension directly from or into a financial institution account or through a mobile money account in the past 12 months, male (% age 15+).

Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.

Metadata

Coverage & Extent

• Granularity List : National
• Temporal Coverage : 1959 - 2021
• Periodicity : Annual
• Acronym : Gender Stats
• Recommended Citation: Gender Statistics, The World Bank
• Languages Supported : English
• Source Type : World Bank Group
• Source: : Gender Statistics, The World Bank
• Harvest Source : World Bank Data API
• Dates
  • First Published Date : Jul 18, 2010
  • Last Updated on : Jun 22, 2022
• Update Frequency : Quarter

Download

kaggle API Command !kaggle datasets download -d azminetoushikwasi/gender-statistics-wb

Disclaimer

The data collected are all publicly available and it's intended for educational purposes only.

Acknowledgement

https://datacatalog.worldbank.org/search/dataset/0037654

Portugal PT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 95.581 % in 2017. This records an increase from the previous number of 92.740 % for 2014. Portugal PT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 92.740 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 95.581 % in 2017 and a record low of 86.442 % in 2011. Portugal PT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Portugal – Table PT.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 (richest 60%, share 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).

This dataset provides a comprehensive panel data structure covering 27 EU member states from 2007 to 2020. It includes economic, social, governance, and development indicators alongside data on EU funds allocated as a percentage of GDP. The primary objective of this dataset is to facilitate the analysis of the impact of EU funding on socio-economic progress across different countries and periods.The time period covered: 2007–2020Geographical coverage: 27 EU member statesTemporal resolution: Annual observationsThe dataset contains yearly observations for each country, with the following key indicators:EU Funds (EUfunds) – Ratio of annual EU funds paid to member states as a percentage of GDP (European Commission).Human Development Index (HDI) – Composite index of life expectancy, education, and income (UNDP).GINI Index (GINI) – Measure of income inequality (0 = perfect equality, 100 = maximum inequality, World Bank).Economic Sentiment Indicator (ESI ave.) – Business and consumer confidence indicator (European Commission).Economic Complexity Index (ECI) – Measure of a country’s ability to produce knowledge-intensive goods (Harvard Growth Lab).Educational Attainment (Educ.att.) – Percentage of the population with secondary or higher education (World Bank).Gender Parity Index (GPI) – Ratio of female-to-male school enrollment rates (World Bank).Index of Economic Freedom – Score based on property rights, trade freedom, and government intervention (Heritage Foundation).Governance Indicators (World Bank Governance Indicators):Control of Corruption (Contr.of.Corr.)Rule of Law (Rule.of.Law)Regulatory Quality (Regul.Qual.)Political Stability and Absence of Violence (Pol.stab.and.Abs.viol.)Voice and Accountability (Voice.and.Account.)Government Effectiveness (Gov.effect.)Sustainable Development Goals (SDG Index) – Composite measure of progress toward the UN SDGs (Sustainable Development Solutions Network).This dataset provides a rich foundation for empirical analysis, policy evaluation, and academic research on the role of EU funding in economic and social development.

This dataset was used in the publication of "All Roads Lead to Paris: The Eight Pathways to Renewable Energy Target Adoption" in the journal of Energy Research & Social Science. The objective was to compile data on the first national adoption of a renewable energy target in each country to analyze its mechanisms of diffusion (learning, economic competition, emulation, and coercion). The data were compiled for 187 countries for the period ranging from 1975 to 2017. The list of countries was gathered from the Annex I of IRENA's "Renewable Energy Target Setting" report. We used primarily the IEA policies database (https://www.iea.org/policies) to identify the first adoption of a renewable energy target in each country. Other sources were used when data was unavailable in such repository for specific countries. Additionally, we include the data gathered from various sources, as they were used in our paper for measuring variables. The variables in this dataset include: target adoption (or “Target”, from various sources listed in the dataset); year of adoption (or “Year”, from various sources listed in the dataset); cumulative membership to energy-related international environmental agreements (or “IEA”, with data from Mitchell’s International Environmental Agreements Database Project); net energy imports as a percentage of energy use (or “Energy”, with data from the World Bank); a similarity index (or “Similarity”, created with data from the Polity Index, population and GDP per capita from the World Bank, and revenue from the World Bank); official development assistance as a percentage of gross national income (or “ODAGNI”, with data from the World Bank and OECD); income level (“Income”, with data from the World bank); and the international price for oil (“Oil”, with data from the Federal Reserve Bank of St. Louis). For more details, refer to the manuscript. Note that in 2018 the “IEA’s policy database” was actually the “IEA/IRENA RE Policies and Measures database”. The links for the sources for renewable energy target adoption for Norway and Albania were lost in the transition from one to the other; all other sources could be retrieved by the authors.

Saudi Arabia SA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 76.443 % in 2017. This records an increase from the previous number of 72.873 % for 2014. Saudi Arabia SA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 72.873 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 76.443 % in 2017 and a record low of 54.899 % in 2011. Saudi Arabia SA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.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 (richest 60%, share 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).

Mexico MX: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 44.016 % in 2017. This records a decrease from the previous number of 45.653 % for 2014. Mexico MX: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 44.016 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 45.653 % in 2014 and a record low of 36.780 % in 2011. Mexico MX: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.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 (richest 60%, share 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).

Brazil BR: Account: Income: Richest 60%: % Aged 15+ data was reported at 74.624 % in 2014. This records an increase from the previous number of 67.101 % for 2011. Brazil BR: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 70.863 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 74.624 % in 2014 and a record low of 67.101 % in 2011. Brazil BR: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.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) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 70.582 % in 2017. Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 70.582 % from Dec 2017 (Median) to 2017, with 1 observations. Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Libya – Table LY.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 (richest 60%, share 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).

Chad TD: Account: Income: Richest 60%: % Aged 15+ data was reported at 15.185 % in 2014. This records an increase from the previous number of 10.492 % for 2011. Chad TD: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 12.839 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 15.185 % in 2014 and a record low of 10.492 % in 2011. Chad TD: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.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) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Peru PE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 52.982 % in 2017. This records an increase from the previous number of 37.776 % for 2014. Peru PE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 37.776 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 52.982 % in 2017 and a record low of 30.667 % in 2011. Peru PE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.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 (richest 60%, share 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).

Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 36.793 % in 2017. This records an increase from the previous number of 30.833 % for 2011. Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 33.813 % from Dec 2011 (Median) to 2017, with 2 observations. The data reached an all-time high of 36.793 % in 2017 and a record low of 30.833 % in 2011. Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.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 (richest 60%, share 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).

Niger NE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 18.867 % in 2017. This records an increase from the previous number of 7.300 % for 2014. Niger NE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 7.300 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 18.867 % in 2017 and a record low of 2.478 % in 2011. Niger NE: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Niger – Table NE.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 (richest 60%, share 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).