Country profiles present the latest key development data drawn from the World Development Indicators (WDI) database, the World Bank's primary database for cross-country comparable development data.

Overview of World Bank main indicators.

Overview of World Bank main indicators.

Themes: Economy, Business, SME, Economic development, Employment Keywords: world bank, profile License: CC BY 4.0 Language: English Modified: August 4, 2023 8:13 AM Publisher: The World Bank Reference: https://data.worldbank.org/

COPYRIGHT © 2021 by the World Bank Group 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org This work is a product of the staff of the World Bank Group (WBG) and with external contributions. The opinions, findings, interpretations, and conclusions expressed in this work are those of the authors and do not necessarily reflect the views or the official policy or position of the WBG, its Board of Executive Directors, or the governments it represents. The WBG does not guarantee the accuracy of the data included in this work and do not make any warranty, express or implied, nor assume any liability or responsibility for any consequence of their use. This publication follows the WBG’s practice in references to member designations, borders, and maps. The boundaries, colors, denominations, and other information shown on any map in this work, or the use of the term “country” do not imply any judgment on the part of the WBG, its Boards, or the governments it represents, concerning the legal status of any territory or geographic area or the endorsement or acceptance of such boundaries. The mention of any specific companies or products of manufacturers does not imply that they are endorsed or recommended by the WBG in preference to others of a similar nature that are not mentioned.

Context

There can be multiple motivations for analyzing country specific data, ranging from identifying successful approaches in healthcare policy to identifying business investment opportunities, and many more. Often, all these various goals would have to analyze a substantially overlapping set of parameters. Thus, it would be very good to have a broad set of country specific indicators at one place.

This data-set is an effort in that direction. Of-course there are still plenty more parameters out there. If anyone is interested to integrate more parameters to this dataset, you are more than welcome.

Content

This dataset contains about 95 statistical indicators of the 66 countries. It covers a broad spectrum of areas including

General Information Broader Economic Indicators Social Indicators Environmental & Infrastructure Indicators Military Spending Healthcare Indicators Trade Related Indicators e.t.c.

This data-set for the year 2017 is an amalgamation of data from SRK's Country Statistics - UNData, Numbeo and World Bank.

The entire data-set is contained in one file described below:

soci_econ_country_profiles.csv - The first column contains the country names followed by 95 columns containing the various indicator variables.

Acknowledgements

This is a data-set built on top of SRK's Country Statistics - UNData which was primarily sourced from UNData.

Additional data such as "Cost of living index", "Property price index", "Quality of life index" have been extracted from Numbeo and a number of metrics related to "trade", "healthcare", "military spending", "taxes" etc are extracted from World Bank data source. Given that this is an amalgamation of data from three different sources, only those countries(about 66) which have sufficient data across all the three sources are considered.

Please read the Numbeo terms of use and policieshere Please read the WorldBank terms of use and policies here Please read the UN terms of use and policies here

Photo Credits : Louis Maniquet on Unsplash

Data that captures industry and country-specific employment growth based on updates to LinkedIn member profiles.

This dataset is part of the LinkedIn - World Bank partnership, which helps governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes.

Visualizations for many of these data are available at linkedindata.worldbank.org. The data cover 2015-2019, are refreshed on an annual basis, and are available for 140 countries.

Additional experimental data is available by request via the Development Data Partnership.

Abstract

The Country Opinion Survey in Thailand assists the World Bank Group (WBG) in gaining a better understanding of how stakeholders in Thailand perceive the WBG. It provides the WBG with systematic feedback from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society in Thailand on 1) their views regarding the general environment in Thailand; 2) their overall attitudes toward the WBG in Thailand; 3) overall impressions of the WBG’s effectiveness and results, knowledge work and activities, and communication and information sharing in Thailand; and 4) their perceptions of the WBG’s future role in Thailand.

Geographic coverage

• Bangkok and vicinity
• Northern Thailand
• Southern Thailand
• Northeastern Thailand
• Central Thailand

Analysis unit

Stakeholder

Universe

Opinion leaders from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society.

Kind of data

Sample survey data [ssd]

Sampling procedure

From May to June 2019, 390 stakeholders of the WBG in Thailand were invited to provide their opinions on the WBG’s work in the country by participating in a Country Opinion Survey. Participants were drawn from the Office of the President, Prime Minister; office of a minister; office of a parliamentarian; ministries/ministerial departments/implementation agencies; Project Management Units (PMUs) overseeing implementation of WBG projects; consultants/ contractors working on WBG-supported projects/programs; local governments; bilateral and multilateral agencies; private sector organizations; the financial sector/private banks; private foundations; NGOs and community-based organizations; the media; independent government institutions; trade unions; faith-based groups; youth groups; academia/research institutes/think tanks; judiciary branch; and other organizations.

Mode of data collection

Other [oth]

Research instrument

The questionnaire used to collect the survey data consisted of the following 8 sections:

A. General Issues Facing Thailand B. Overall Attitudes toward the World Bank Group C. World Bank Group's Effectiveness and Results D. The World Bank Group's Knowledge Work and Activities (i.e., analysis studies, research, data, reports, conferences) E. Working with the World Bank Group F. The Future Role of the World Bank Group in Thailand G. Communication and Information Sharing H. Background Information

The questionnaire was prepared in English and Thailand

Response rate

52%

National statistical systems are facing significant challenges. These challenges arise from increasing demands for high quality and trustworthy data to guide decision making, coupled with the rapidly changing landscape of the data revolution. To help create a mechanism for learning amongst national statistical systems, the World Bank has developed improved Statistical Performance Indicators (SPI) to monitor the statistical performance of countries. The SPI focuses on five key dimensions of a country’s statistical performance: (i) data use, (ii) data services, (iii) data products, (iv) data sources, and (v) data infrastructure. This will replace the Statistical Capacity Index (SCI) that the World Bank has regularly published since 2004.The SPI focus on five key pillars of a country’s statistical performance: (i) data use, (ii) data services, (iii) data products, (iv) data sources, and (v) data infrastructure. The SPI are composed of more than 50 indicators and contain data for 186 countries. This set of countries covers 99 percent of the world population. The data extend from 2016-2023, with some indicators going back to 2004.For more information, consult the academic article published in the journal Scientific Data. https://www.nature.com/articles/s41597-023-01971-0. For further details, please refer to https://documents.worldbank.org/en/publication/documents-reports/documentdetail/815721616086786412/measuring-the-statistical-performance-of-countries-an-overview-of-updates-to-the-world-bank-statistical-capacity-index

The database (version August 2022) is built upon the released Global Subnational Atlas of Poverty (GSAP) (World Bank, 2021). In this database, we assemble a new panel dataset that provides (headcount) poverty rates using the daily poverty lines of US $1.90, $3.20, and $5.50 (based on the revised 2011 Purchasing Power Parity (PPP) dollars). This database is generated using household income and consumption surveys from the World Bank’s Global Monitoring Database (GMD), which underlie country official poverty statistics, and offers the most detailed subnational poverty data on a global scale to date. The Global Subnational Atlas of Poverty (GSAP) is produced by the World Bank’s Poverty and Equity Global Practice, coordinated by the Data for Goals (D4G) team, and supported by the six regional statistics teams in the Poverty and Equity Global Practice, and Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) at the World Bank. The Global Monitoring Database (GMD) is the World Bank’s repository of multitopic income and expenditure household surveys used to monitor global poverty and shared prosperity. The household survey data are typically collected by national statistical offices in each country, and then compiled, processed, and harmonized. The process is coordinated by the Data for Goals (D4G) team and supported by the six regional statistics teams in the Poverty and Equity Global Practice. Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) also contributed historical data from before 1990, and recent survey data from Luxemburg Income Studies (LIS). Selected variables have been harmonized to the extent possible such that levels and trends in poverty and other key sociodemographic attributes can be reasonably compared across and within countries over time. The GMD’s harmonized microdata are currently used in Poverty and Inequality Platform (PIP), World Bank’s Multidimensional Poverty Measures (WB MPM), the Global Database of Shared Prosperity (GDSP), and Poverty and Shared Prosperity Reports. Reference: World Bank. (2021). World Bank estimates based on data from the Global Subnational Atlas of Poverty, Global Monitoring Database. World Bank: Washington. https://datacatalog.worldbank.org/search/dataset/0042041

Abstract

The Country Opinion Survey in Ethiopia assists the World Bank Group (WBG) in gaining a better understanding of how stakeholders in Ethiopia perceive the WBG. It provides the WBG with systematic feedback from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society in Ethiopia on 1) their views regarding the general environment in Ethiopia; 2) their overall attitudes toward the WBG in Ethiopia; 3) overall impressions of the WBG’s effectiveness and results, knowledge work and activities, and communication and information sharing in Ethiopia; and 4) their perceptions of the WBG’s future role in Ethiopia.

Geographic coverage

Addis Ababa and Outside Addis Ababa.

Analysis unit

Stakeholder

Universe

Opinion leaders from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society.

Kind of data

Sample survey data [ssd]

Sampling procedure

From May to June 2018, 300 stakeholders of the WBG in Ethiopia were invited to provide their opinions on the WBG’s work in the country by participating in a Country Opinion Survey. Participants were drawn from the Office of the President, Prime Minister; office of a Minister; office of a Parliamentarian; ministries/ministerial departments/implementation agencies; Project Management Units (PMUs) overseeing implementation of WBG projects; consultants/ contractors working on WBG-supported projects/programs; local governments; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/ private banks; NGOs/community based organizations; the media; independent government institutions; trade unions; faith-based groups; youth groups; academia/research institutes/think tanks; the judiciary branch; and other organizations.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consisted of 8 Sections:

A. General Issues Facing Ethiopia B. Overall Attitudes toward the World Bank Group C. World Bank Group's Effectiveness and Results D. The World Bank Group's Knowledge Work and Activities (i.e., analysis studies, research, data, reports, conferences) E. Working with the World Bank Group F. The Future Role of the World Bank Group in Ethiopia G. Communication and Information Sharing H. Background Information

Response rate

64%

The World Bank Group’s Country Climate and Development Reports (CCDRs) are new core diagnostic reports that integrate climate change and development considerations. They will help countries prioritize the most impactful actions that can reduce greenhouse gas (GHG) emissions and boost adaptation, while delivering on broader development goals. This CCDR identifies near-term policy and investment priorities that will support Bangladesh to continue progress in building resilience to the effects of climate change. Section 1 describes Bangladesh’s vulnerability to the effects of climate change and outlines estimates of the cost of mitigation and adaptation investments through 2030. Section 2 lays out the Government of Bangladesh’s existing climate commitments and plans, and evaluates the institutional capacities required to meet them. Section 3 highlights priority sector-level interventions to build climate resilience while meeting development goals. Section 4 presents potential synergies between decarbonization and development. Section 5 discusses the macroeconomic and distributional impacts of climate scenarios and identifies priority actions to support adaptation and growth. The CCDR provides additional analysis to prioritize actions to accelerate climate resilient development in line with Bangladesh’s goals.

The database (version August 2022) is built upon the released Global Subnational Atlas of Poverty (GSAP) (World Bank, 2021). In this database, we assemble a new panel dataset that provides different measures of inequality. This database is generated using household income and consumption surveys from the World Bank’s Global Monitoring Database (GMD), which underlie country official poverty statistics, and offers the most detailed subnational poverty data on a global scale to date. The Global Subnational Atlas of Poverty (GSAP) is produced by the World Bank’s Poverty and Equity Global Practice, coordinated by the Data for Goals (D4G) team, and supported by the six regional statistics teams in the Poverty and Equity Global Practice, and Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) at the World Bank. The Global Monitoring Database (GMD) is the World Bank’s repository of multitopic income and expenditure household surveys used to monitor global poverty and shared prosperity. The household survey data are typically collected by national statistical offices in each country, and then compiled, processed, and harmonized. The process is coordinated by the Data for Goals (D4G) team and supported by the six regional statistics teams in the Poverty and Equity Global Practice. Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) also contributed historical data from before 1990, and recent survey data from Luxemburg Income Studies (LIS). Selected variables have been harmonized to the extent possible such that levels and trends in poverty and other key sociodemographic attributes can be reasonably compared across and within countries over time. The GMD’s harmonized microdata are currently used in Poverty and Inequality Platform (PIP), World Bank’s Multidimensional Poverty Measures (WB MPM), the Global Database of Shared Prosperity (GDSP), and Poverty and Shared Prosperity Reports. Reference: World Bank. (2021). World Bank estimates based on data from the Global Subnational Atlas of Poverty, Global Monitoring Database. World Bank: Washington. https://datacatalog.worldbank.org/search/dataset/0042041

The presented cross-sectional dataset can be employed to analyze the governmental, trade, and competitiveness relationships of official COVID-19 reports. It contains 18 COVID-19 variables generated based on the official reports of 138 countries, as well as an additional 2163 governance, trade, and competitiveness indicators from the World Bank Group GovData360 and TCdata360 platforms in a preprocessed form. The current version was compiled on July 27, 2020. Note that this version uses 20-40-60-80-day time windows and the first test data are based on the first country reports on tests.

Please cite as: • Kurbucz, M. T. (2020). A Joint Dataset of Official COVID-19 Reports and the Governance, Trade and Competitiveness Indicators of World Bank Group Platforms. Data in Brief, 105881.

Data generation: • Data generation (data_generation. Rmd): Datasets were generated with this R Notebook. It can be used to update datasets and customize the data generation process.

Datasets: • Country data (country_data.txt): Country data. • Metadata (metadata.txt): The metadata of selected GovData360 and TCdata360 indicators. • Joint dataset (joint_dataset.txt): The joint dataset of COVID-19 variables and preprocessed GovData360 and TCdata360 indicators. • Correlation matrix (correlation_matrix.txt): The Kendall rank correlation matrix of the joint dataset.

Raw data of figures and tables: • Raw data of Fig. 2 (raw_data_fig2.txt): The raw data of Fig. 2. • Raw data of Fig. 3 (raw_data_fig3.txt): The raw data of Fig. 3. • Raw data of Table 1 (raw_data_table1.txt): The raw data of Table 1. • Raw data of Table 2 (raw_data_table2.txt): The raw data of Table 2. • Raw data of Table 3 (raw_data_table3.txt): The raw data of Table 3.

At 463,000 square kilometers, Papua New Guinea (PNG) is the largest Pacific island state. Located in the South West Pacific, it is bound by the Gulf of Guinea and the Coral Sea to the south, Indonesia to the west, the Solomon Sea to the east, and the Bismarck Sea to the northeast. PNG comprises the eastern half of New Guinea island, four additional islands (Manus, New Ireland, New Britain, and Bougainville), and 600 smaller islets and atolls to the north and east. PNG is home to a diverse range of ecosystems, including mountain glaciers, humid tropical rainforests, swampy wetlands, and immaculate coral reefs. Approximately 30% of the country’s landmass is covered by forests and four of the world’s remaining significant forests are found in PNG. In addition to harboring abundant natural resources such as gold, copper, oil and natural gas, PNG boasts 7% of the world’s biodiversity.

The World Bank’s ESG Data Draft dataset provides information on 17 key sustainability themes spanning environmental, social, and governance categories. In order to shift financial flows so that they are better aligned with global goals, the World Bank Group (WBG) is working to provide financial markets with improved data and analytics that shed light on countries’ sustainability performance. Along with new information and tools, the World Bank will also develop research on the correlation between countries’ sustainability performance and the risk and return profiles of relevant investments.

Photo by Christian Bowen on Unsplash

Data Source: World Bank | Data Bank | World Development Indicators

Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

Total fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.

World Bank Country Study Reports are among the many reports originally prepared for internal use as part of the continuing analysis by the Bank of the economic and related conditions of its developing member countries and of its dialogues with the governments. Some of the reports are published in this series with the least possible delay of the use of the governments and the academic, business and financial, and development communities. The typescript of this paper therefore has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. Some sources cited in this paper may be informal documents that are not readily available.Available online SLIC also hold a copy of the draft summary version|3 copiesCall Number: 338.54 CIT [EL]Physical Description: ix, 71 p. + maps ; 29 cm

Provides key ratios and select metrics from quarterly financial statements. Dataset based on unaudited data. Values are in millions of US$ equivalent, rounded to 2 decimal places. Our goal is to make raw data publicly available in open data format as soon as it is approved for public release through other channels, please refer to the official sources: http://documents.worldbank.org/curated/en/docsearch/collection-title/World%2520Bank%2520financial%2520statements?colT=World%2520Bank%2520financial%2520statements (IBRD/IDA), http://www.ifc.org/wps/wcm/connect/topics_ext_content/ifc_external_corporate_site/ifc+finance/investor+information/financial+statements (IFC) and https://www.miga.org/resources/reports/annual-reports/ (MIGA).

Abstract

The Country Opinion Survey in Philippines assists the World Bank Group (WBG) in gaining a better understanding of how stakeholders in Philippines perceive the WBG. It provides the WBG with systematic feedback from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society in Philippines on 1) their views regarding the general environment in Philippines; 2) their overall attitudes toward the WBG in Philippines; 3) overall impressions of the WBG’s effectiveness and results, knowledge work and activities, and communication and information sharing in Philippines; and 4) their perceptions of the WBG’s future role in Philippines.

Geographic coverage

• Metro Manila
• Luzon
• Visayas
• Mindanao

Analysis unit

Stakeholder

Universe

Opinion leaders from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society.

Kind of data

Sample survey data [ssd]

Sampling procedure

From April through May 2019, 910 stakeholders of the WBG in the Philippines were invited to provide their opinions on the WBG’s work in the country by participating in a Country Opinion Survey (COS). Participants were drawn from the office of the President, office of a Minister, office of a Parliamentarian, employees of ministries/ministerial departments/implementation agencies, Project Management Units (PMUs) overseeing implementation of projects or consultants/contractors working on WBG-supported projects/programs, local government officials or staff, bilateral agencies, multilateral agencies, private sector organizations, the financial sector/private banks, private foundations, NGOs/community-based organizations (CBOs), the media, independent government institutions, trade unions, faith-based groups, youth groups, academia/research institutes/think tanks, and the judiciary branch.

Mode of data collection

Other [oth]

Research instrument

The questionnaire consisted of 8 Sections:

A. General Issues Facing Philippines B. Overall Attitudes toward the World Bank Group C. World Bank Group's Effectiveness and Results D. The World Bank Group's Knowledge Work and Activities (i.e., analysis studies, research, data, reports, conferences) E. Working with the World Bank Group F. The Future Role of the World Bank Group in The Philippines G. Communication and Information Sharing H. Background Information

Response rate

49%

Quarterly updates for condensed balance sheets. Dataset based on unaudited data. Values are in millions of US$ equivalent, rounded to 2 decimal places. Our goal is to make raw data publicly available in open data format as soon as it is approved for public release through other channels, please refer to the official versions: http://documents.worldbank.org/curated/en/docsearch/collection-title/World%2520Bank%2520financial%2520statements?colT=World%2520Bank%2520financial%2520statements (IBRD/IDA), http://www.ifc.org/wps/wcm/connect/topics_ext_content/ifc_external_corporate_site/ifc+finance/investor+information/financial+statements (IFC) and https://www.miga.org/resources/reports/annual-reports/ (MIGA).