World Bank

Note: No further updates planned by source Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.

Climate Change Knowledge Portal, Temperature and Rainfall: Historical Data (CRU Observed)

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Education Statistics Publication: https://datacatalog.worldbank.org/dataset/education-statistics License: http://creativecommons.org/licenses/by/4.0/   The World Bank EdStats All Indicator Query holds over 4,000 internationally comparable indicators that describe education access, progression, completion, literacy, teachers, population, and expenditures. The indicators cover the education cycle from pre-primary to vocational and tertiary education.

1: Most surveys were administered using the Enterprise Surveys Global Methodology as outlined in the Methodology page, while some others did not strictly adhere to the Enterprise Surveys Global Methodology. For example, for surveys which do not follow the Global Methodology, the Universe under consideration may have consisted of only manufacturing firms or the questionnaire used may have been different from the standard global questionnaire. Data users should exercise caution when comparing raw data and point estimates between surveys that did and did not adhere to the Enterprise Surveys Global Methodology. For surveys which did not adhere to the Global Methodology plus Afghanistan 2008, any inference from one of these surveys is representative only for the data sample itself. 2: Regional and "all countries" averages of indicators are computed by taking a simple average of country-level point estimates. For each economy, only the latest available year of survey data is used in this computation. Only surveys, posted during the years 2009-2017, and adhering to the Enterprise Surveys Global Methodology are used to compute these regional and "all countries" averages. 3: Descriptions of firm subgroup levels, e.g. how the ex post groupings are constructed, are provided in the Indicator Descriptions (PDF, 710KB) document. 4: Statistics derived from less than or equal to five firms are displayed with an "n.a." to maintain confidentiality and should be distinguished from ".." which indicates missing values. Also note for three growth-related indicators under the "Performance" topic, these indicators are not computed when they are derived from less than 30 firms. 5: Standard errors are labeled "n.c.", meaning not computed, for the following:    1) indicators for all surveys that were not conducted using the Enterprise Surveys Global Methodology and    2) for indicator breakdowns by ex post groupings: exporter or ownership type, and gender of the top manager.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Gender Statistics Publication: https://datacatalog.worldbank.org/dataset/gender-statistics License: http://creativecommons.org/licenses/by/4.0/

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Financial Development Publication: https://datacatalog.worldbank.org/dataset/global-financial-development License: http://creativecommons.org/licenses/by/4.0/   The Global Financial Development Database is an extensive dataset of financial system characteristics for 206 economies. The database includes measures of (1) size of financial institutions and markets (financial depth), (2) degree to which individuals can and do use financial services (access), (3) efficiency of financial intermediaries and markets in intermediating resources and facilitating financial transactions (efficiency), and (4) stability of financial institutions and markets (stability).For a complete description of the dataset and a discussion of the underlying literature, see: Martin Cihak; Asli Demirguc-Kunt; Erik Feyen; and Ross Levine, 2012. "Benchmarking Financial Systems Around the World." World Bank Policy Research Working Paper 6175, World Bank, Washington, D.C.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Financial Inclusion (Global Findex) Database Publication: https://datacatalog.worldbank.org/dataset/global-financial-inclusion-global-findex-database License: http://creativecommons.org/licenses/by/4.0/   The Global Financial Inclusion Database provides 850+ country-level indicators of financial inclusion summarized for all adults and disaggregated by key demographic characteristics-gender, age, education, income, employment status and rural residence. Covering more than 140 economies, the indicators of financial inclusion measure how people save, borrow, make payments and manage risk. The reference citation for the data is: Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. World Bank: Washington, DC.

GPSS data (Accounts & Access, retail payment transactions and RTGS transactions – volumes and values). The World Bank’s Global Payment Systems Survey (GPSS) surveys national and regional central banks and monetary authorities on the status of payment systems. The GPSS is the only global survey that combines quantitative and qualitative measures of payment system development and covers all aspects of national payment systems – from infrastructure and the legal and regulatory environment to technological and business model innovations, international remittances, and oversight framework. The GPSS aims to take an accurate snapshot of payment systems worldwide to obtain information on payment system reforms and the factors which hinder and/or facilitate them in order to help guide policy-dialogue at the international and national levels, and World Bank Group technical assistance. In April 2007, the World Bank launched the first Global Payment Systems Survey among national central banks to collect information on the situation of national payment and securities settlement systems worldwide and provide a payment systems snapshot of both advanced and emerging economies in order to identify main issues that should guide the agenda of authorities, multilateral and market players in the field over the next few years.

Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

This dataset presents HNP data by wealth quintile since 1990s to present. It covers more than 70 indicators, including childhood diseases and interventions, nutrition, sexual and reproductive health, mortality, and other determinants of health, for more than 90 low- and middle-income countries. The data sources are Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS).

Purchasing Power Parities and the Real Size of World Economies. A Comprehensive Report of the 2011 International Comparison Program

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: ESCAP-World Bank: International Trade Costs Publication: https://datacatalog.worldbank.org/dataset/escap-world-bank-international-trade-costs License: http://creativecommons.org/licenses/by/4.0/   The Trade Costs Dataset provides estimates of bilateral trade costs in agriculture and manufactured goods for the 1995-2015 period. It is built on trade and production data collected in 178 countries. Symmetric bilateral trade costs are computed using the Inverse Gravity Framework (Nov. 2009), which estimates trade costs for each country pair using bilateral trade and gross national output. Trade costs are available for two sectors: trade in manufactured goods, and agriculture. Energy is excluded.

Internet users are individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.

The Joint External Debt Hub (JEDH) -jointly developed by the Bank for International Settlements (BIS), the International Monetary Fund (IMF), the Organization for Economic Cooperation and Development (OECD) and the World Bank (WB) -brings together external debt data and selected foreign assets from international creditor / market and national debtor sources. The JEDH replaces the Joint BIS-IMF-OECD-WB Statistics on External Debt, a website that was launched in 1999 to provide international data, mainly from creditor sources, on the external debt of developing and transition countries and territories.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Millennium Development Goals Publication: https://datacatalog.worldbank.org/dataset/millennium-development-goals License: http://creativecommons.org/licenses/by/4.0/   Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Millennium Development Goals (MDGs). The MDGs focus the efforts of the world community on achieving significant, measurable improvements in people's lives by the year 2015: they establish targets and yardsticks for measuring development results. Gender Parity Index (GPI)= Value of indicator for Girls/ Value of indicator for Boys. For e.g GPI=School enrolment for Girls/School enrolment for Boys. A value of less than one indicates differences in favor of boys, whereas a value near one (1) indicates that parity has been more or less achieved. The greater the deviation from 1 greater the disparity is.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Population Estimates And Projections Publication: https://datacatalog.worldbank.org/dataset/population-estimates-and-projections License: http://creativecommons.org/licenses/by/4.0/   This database presents population and other demographic estimates and projections from 1960 to 2050. They are disaggregated by age-group and sex and covers more than 200 economies.

The World Bank updated the global poverty lines in September 2022. The Poverty data are now expressed in 2017 Purchasing Power Parity (PPP) prices, versus 2011 PPP in previous editions. The new global poverty lines of $2.15, $3.65, and $6.85 reflect the typical national poverty lines of low-income, lower-middle-income, and upper-middle-income countries in 2017 prices.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly External Debt Statistics GDDS Publication: https://datacatalog.worldbank.org/dataset/quarterly-external-debt-statistics-gdds License: http://creativecommons.org/licenses/by/4.0/   The World Bank launched the new Quarterly External Debt Statistics (QEDS) GDDS database. This database is consistent with the classifications and definitions of the 2013 External Debt Statistics: Guide for Compilers and Users (2013 EDS Guide) and Sixth Edition of Balance of Payments and International Investment Position Manual (BPM6). The QEDS GDDS database provides external debt data, starting from 2002Q4, for an extension of countries that participate in the IMF's General Data Dissemination System (GDDS).

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly External Debt Statistics SDDS Publication: https://datacatalog.worldbank.org/dataset/quarterly-external-debt-statistics-sdds License: http://creativecommons.org/licenses/by/4.0/   In October 2014, the World Bank launched the new Quarterly External Debt Statistics (QEDS) SDDS database. This database is consistent with the classifications and definitions of the 2013 External Debt Statistics: Guide for Compilers and Users (2013 EDS Guide) and Sixth Edition of Balance of Payments and International Investment Position Manual (BPM6). The QEDS SDDS database provides detailed external debt data starting from 1998Q1. Data are published individually by countries that subscribe to the IMF’s Special Data Dissemination Standard (SDDS), as well as, GDDS participating countries that are in a position to produce the external debt data prescribed by the SDDS.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly Public Sector Debt Publication: https://datacatalog.worldbank.org/dataset/quarterly-public-sector-debt License: http://creativecommons.org/licenses/by/4.0/   Quarterly Public Sector Debt (QPSD) database, jointly developed by the World Bank and the International Monetary Fund, brings together detailed public sector debt data of selected countries. The QPSD database includes country and cross-country tables, and specific public debt components. The data represent the following sectors on an as-available basis: General government; otherwise Central government; otherwise Budgetary central government; Non Financial public corporations and Financial public corporations and a table presenting the total public sector debt.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Services Trade Restrictions Database Publication: https://datacatalog.worldbank.org/dataset/services-trade-restrictions-database License: http://creativecommons.org/licenses/by/4.0/ The Services Trade Restrictions Database collects information on applied services trade policies across 103 countries, 18 services sectors (covering telecommunications, finance, transportation, retail and professional services) and key modes of service supply. It contains qualitative policy information as well as a preliminary quantification of applied measures' restrictiveness. Data Coverage 2012-2016

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Wealth Accounting Publication: https://datacatalog.worldbank.org/dataset/wealth-accounting License: http://creativecommons.org/licenses/by/4.0/   The wealth accounting approach provides two related sets of information: comprehensive wealth accounts (a stock measure in total and per capita values), and adjusted net saving (a flow measure). The wealth accounts were updated in 2018, using a new methodology described in The Changing Wealth of Nations 2018.

The ease of doing business score helps assess the absolute level of regulatory performance over time. It captures the gap of each economy from the best regulatory performance observed on each of the indicators across all economies in the Doing Business sample since 2005. One can both see the gap between a particular economy’s performance and the best performance at any point in time and assess the absolute change in the economy’s regulatory environment over time as measured by Doing Business. An economy’s ease of doing business score is reflected on a scale from 0 to 100, where 0 represents the lowest and 100 represents the best performance. For example, an ease of doing business score of 75 in Doing Business 2019 means an economy was 25 percentage points away from the best regulatory performance constructed across all economies and across time. A score of 80 in Doing Business 2020 would indicate the economy is improving   NOTE- The source discontinued this dataset; Reference-Doing Business Legacy (worldbank.org)

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Economic Monitor Publication: https://datacatalog.worldbank.org/dataset/global-economic-monitor License: http://creativecommons.org/licenses/by/4.0/   The dataset Provides daily updates of global economic developments, with coverage of high income- as well as developing countries. Average period data updates are provided for exchange rates, equity markets, interest rates, stripped bond spreads, and emerging market bond indices. Monthly data coverage (updated daily and populated upon availability) is provided for consumer prices, high-tech market indicators, industrial production and merchandise trade.

Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development.

The G20 Basic Set of Financial Inclusion data repository includes detailed data from users and providers of financial services. The Basic Set measures both access to financial services (“supply-side” data) and usage of services (“demand-side” data). The Basic Set covers both individuals and small and medium sized enterprises (SME’s) and includes data from three sources and 192 countries. The five basic set indicators are as follows: 1.The percentage of adults with a formal account; 2. The percentage of adults that use formal credit; 3. The percentage of SME’s with a formal account; 4. The percentage of SME’s that use formal credit; and 5. Bank branch penetration.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Sustainable Energy For All Publication: https://datacatalog.worldbank.org/dataset/sustainable-energy-all License: http://creativecommons.org/licenses/by/4.0/   The “Sustainable Energy for all (SE4ALL)” initiative, launched in 2010 by the UN Secretary General, established three global objectives to be accomplished by 2030: to ensure universal access to modern energy services, to double the global rate of improvement in global energy efficiency, and to double the share of renewable energy in the global energy mix. SE4ALL database supports this initiative and provides country level historical data for access to electricity and non-solid fuel; share of renewable energy in total final energy consumption by technology; and energy intensity rate of improvement.

The primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates

The Worldwide Governance Indicators (WGI) project reports aggregate and individual governance indicators for over 200 countries and territories over the period 1996–2020, for six dimensions of governance:Voice and AccountabilityPolitical Stability and Absence of ViolenceGovernment EffectivenessRegulatory QualityRule of LawControl of Corruption The Worldwide Governance Indicators (WGI) are a research dataset summarizing the views on the quality of governance provided by a large number of enterprise, citizen and expert survey respondents in industrial and developing countries. These data are gathered from a number of survey institutes, think tanks, non-governmental organizations, international organizations, and private sector firms. The WGI do not reflect the official views of the World Bank, its Executive Directors, or the countries they represent. The WGI are not used by the World Bank Group to allocate resources. Measure description: Estimate:-Estimate of governance (ranges from approximately -2.5 (weak) to 2.5 (strong) governance performance) Standard error (StdErr):-Standard error reflects variability around the point estimate of governance. Number of sources (NumSrc):-Number of data sources on which estimate is based Rank:-Percentile rank among all countries (ranges from 0 (lowest) to 100 (highest) rank) Lower:-Lower bound of 90% confidence interval for governance, in percentile rank terms Upper:-Upper bound of 90% confidence interval for governance, in percentile rank terms