The SNL Global Banking data delivers harmonized line items and key ratios for banks across the globe.

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

For more information, see the World Bank website.

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Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

http://data.worldbank.org/data-catalog/ed-stats

https://cloud.google.com/bigquery/public-data/world-bank-education

Citation: The World Bank: Education Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

Of total government spending, what percentage is spent on education?

Global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept are presented. Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds.For the first time, a comprehensive picture of bilateral global migration over the last half of the twentieth century emerges. The data reveal that the global migrant stock increased from 92 to 165 million between 1960 and 2000. South-North migration is the fastest growing component of international migration in both absolute and relative terms. The United States remains the most important migrant destination in the world, home to one fifth of the world™s migrants and the top destination for migrants from no less than sixty sending countries. Migration to Western Europe remains largely from elsewhere in Europe. The oil-rich Persian Gulf countries emerge as important destinations for migrants from the Middle East, North Africa and South and South-East Asia. Finally, although the global migrant stock is still predominantly male, the proportion of women increased noticeably between 1960 and 2000.

United States FB: IL: IBF Only: BM: NC: Branches of Nonrelated Foreign Bank data was reported at 20.000 USD mn in Dec 2019. This records an increase from the previous number of 0.000 USD mn for Sep 2019. United States FB: IL: IBF Only: BM: NC: Branches of Nonrelated Foreign Bank data is updated quarterly, averaging 0.000 USD mn from Sep 2009 (Median) to Dec 2019, with 42 observations. The data reached an all-time high of 37.000 USD mn in Jun 2019 and a record low of 0.000 USD mn in Sep 2019. United States FB: IL: IBF Only: BM: NC: Branches of Nonrelated Foreign Bank data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.KB046: Balance Sheet: Foreign Banks: Illinois.

Mexico Monetary Base: Use: Bank Deposits at the Central Bank data was reported at 1,543.533 MXN mn in Mar 2019. This records an increase from the previous number of 1,115.938 MXN mn for Feb 2019. Mexico Monetary Base: Use: Bank Deposits at the Central Bank data is updated monthly, averaging 0.813 MXN mn from Dec 1985 (Median) to Mar 2019, with 400 observations. The data reached an all-time high of 7,419.725 MXN mn in May 2018 and a record low of 0.000 MXN mn in Apr 2016. Mexico Monetary Base: Use: Bank Deposits at the Central Bank data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.KA002: Monetary Base: Monthly.

The Doing Business project provides objective measures of business regulations and their enforcement across 190 economies. Economies are ranked on their ease of doing business, from 1–190. The rankings are determined by sorting the aggregate scores (formerly called distance to frontier) on 10 topics, each consisting of several indicators, giving equal weight to each topic. More details: http://www.doingbusiness.org.

NOTE: Doing Business has been discontinued as of 9/16/2021. Click here for more information.

Commercial Banks Income: Year to Date: Russian Standard Bank data was reported at 347,871,161.000 RUB th in Dec 2018. This records an increase from the previous number of 277,281,268.000 RUB th for Sep 2018. Commercial Banks Income: Year to Date: Russian Standard Bank data is updated quarterly, averaging 152,896,009.500 RUB th from Mar 2007 (Median) to Dec 2018, with 48 observations. The data reached an all-time high of 862,863,179.000 RUB th in Dec 2015 and a record low of 23,829,346.000 RUB th in Mar 2011. Commercial Banks Income: Year to Date: Russian Standard Bank data remains active status in CEIC and is reported by The Central Bank of the Russian Federation. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAJ002: Commercial Banks: Income: ytd.

Dataset

This dataset was created by Sindhu inti

Contents

The World Bank’s Knowledge Assessment Methodology (KAM: www.worldbank.org/kam) is an online interactive tool that produces the Knowledge Economy Index (KEI)–an aggregate index representing a country’s or region’s overall preparedness to compete in the Knowledge Economy (KE). The KEI is based on a simple average of four subindexes, which represent the four pillars of the knowledge economy:  Economic Incentive and Institutional Regime (EIR)  Innovation and Technological Adoption  Education and Training  Information and Communications Technologies (ICT) Infrastructure The EIR comprises incentives that promote the efficient use of existing and new knowledge and the flourishing of entrepreneurship. An efficient innovation system made up of firms, research centers, universities, think tanks, consultants, and other organizations can tap into the growing stock of global knowledge, adapt it to local needs, and create new technological solutions. An educated and appropriately trained population is capable of creating, sharing, and using knowledge. A modern and accessible ICT infrastructure serves to facilitate the effective communication, dissemination, and processing of information.

A toxicology database that focuses on the toxicology of potentially hazardous chemicals. It provides information on human exposure, industrial hygiene, emergency handling procedures, environmental fate, regulatory requirements, nanomaterials, and related areas. The information in HSDB has been assessed by a Scientific Review Panel.

Abstract

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

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

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

Geographic coverage

Localities with less than 100 inhabitants were excluded from the sample. The excluded areas represent approximately 4 percent of the total population

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

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

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

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

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

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

Sample size for Ghana is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

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

United States FB: Incl IBF: CA: Loans to Dep Inst & Acceptances of Oth Bank data was reported at 8.197 USD bn in Dec 2019. This records a decrease from the previous number of 8.622 USD bn for Sep 2019. United States FB: Incl IBF: CA: Loans to Dep Inst & Acceptances of Oth Bank data is updated quarterly, averaging 9.216 USD bn from Sep 2009 (Median) to Dec 2019, with 42 observations. The data reached an all-time high of 14.901 USD bn in Mar 2017 and a record low of 3.471 USD bn in Dec 2009. United States FB: Incl IBF: CA: Loans to Dep Inst & Acceptances of Oth Bank data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.KB045: Balance Sheet: Foreign Banks: California.

This web site includes statistics on poverty and other distributional and social variables from 25 Latin American and Caribbean (LAC) countries. All statistics are computed from microdata of the main household surveys carried out in these countries using a homogenous methodology (data permitting). SEDLAC allows users to monitor the trends in poverty and other distributional and social indicators in the region. The database is available in the form of brief reports, charts and electronic Excel tables with information for each country/year. In addition, the website visitor can carry out dynamic searches online.

Graph and download economic data for Reserves of Depository Institutions: Total (TOTRESNS) from Jan 1959 to Feb 2025 about adjusted, reserves, and USA.

The International Development Association (IDA) credits are public and publicly guaranteed debt extended by the World Bank Group. IDA provides development credits, grants and guarantees to its recipient member countries to help meet their development needs. Credits from IDA are at concessional rates. Data are in U.S. dollars calculated using historical rates. This dataset contains the latest available snapshot of the IDA Statement of Credits and Grants.

United States FFL: TW: PU: Bank data was reported at 25.476 USD bn in May 2018. This records an increase from the previous number of 22.008 USD bn for Apr 2018. United States FFL: TW: PU: Bank data is updated monthly, averaging 24.418 USD bn from Feb 2003 (Median) to May 2018, with 184 observations. The data reached an all-time high of 39.737 USD bn in Feb 2015 and a record low of 14.919 USD bn in Jun 2006. United States FFL: TW: PU: Bank data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.KA024: US Financial Firms Liabilities to Foreigner.

United States FFL: RU: PU: Bank data was reported at 7.176 USD bn in May 2018. This records a decrease from the previous number of 9.112 USD bn for Apr 2018. United States FFL: RU: PU: Bank data is updated monthly, averaging 11.015 USD bn from Feb 2003 (Median) to May 2018, with 184 observations. The data reached an all-time high of 26.206 USD bn in Dec 2008 and a record low of 2.262 USD bn in Aug 2003. United States FFL: RU: PU: Bank data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.KA024: US Financial Firms Liabilities to Foreigner.

Kazakhstan Personal Deposits: Bank Share: Tsesna Bank data was reported at 8.390 % in May 2018. This records a decrease from the previous number of 8.460 % for Apr 2018. Kazakhstan Personal Deposits: Bank Share: Tsesna Bank data is updated monthly, averaging 3.300 % from Jan 2005 (Median) to May 2018, with 161 observations. The data reached an all-time high of 8.640 % in Jan 2017 and a record low of 1.030 % in Jan 2005. Kazakhstan Personal Deposits: Bank Share: Tsesna Bank data remains active status in CEIC and is reported by The National Bank of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.KB017: Second Tier Banks: Share of Total Deposits.

United States FFL: GR: PU: Bank data was reported at 1.425 USD bn in Dec 2014. This records an increase from the previous number of 1.282 USD bn for Nov 2014. United States FFL: GR: PU: Bank data is updated monthly, averaging 1.184 USD bn from Feb 2003 (Median) to Dec 2014, with 143 observations. The data reached an all-time high of 2.657 USD bn in Jul 2013 and a record low of 686.000 USD mn in Mar 2009. United States FFL: GR: PU: Bank data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.KA024: US Financial Firms Liabilities to Foreigner.

China Commercial Bank: Return on Asset: Foreign Bank data was reported at 0.750 % in Dec 2018. This records a decrease from the previous number of 0.820 % for Sep 2018. China Commercial Bank: Return on Asset: Foreign Bank data is updated quarterly, averaging 0.560 % from Mar 2014 (Median) to Dec 2018, with 20 observations. The data reached an all-time high of 1.090 % in Mar 2014 and a record low of 0.250 % in Jun 2016. China Commercial Bank: Return on Asset: Foreign Bank data remains active status in CEIC and is reported by China Banking and Insurance Regulatory Commission. The data is categorized under China Premium Database’s Money and Banking – Table CN.KC: Banking: Income Statement and Its Related.