Explore the Penn World Table dataset featuring key economic indicators like real GDP, population, human capital index, and more. Access detailed information and analysis for various countries.

Expenditure, GDP, PPP, output, Population, working hours, Index, Household, Consumption, Capital , IRR, prices

Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Latvia, Lebanon, Lesotho, Liberia, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Venezuela, Yemen, Zambia, Zimbabwe, World Follow data.kapsarc.org for timely data to advance energy economics research. When using these data, please refer to the following paper:Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt

Abstract copyright UK Data Service and data collection copyright owner. The OECD's quarterly national accounts (QNA) dataset presents data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1947 or whenever available:- GDP expenditure and output approaches (current prices and volume estimates);- GDP income approach (current prices);- Gross fixed capital formation (current prices and volume estimates) broken down separately by type of asset or product and by institutional sector;- Disposable income and Real disposable income components;- Saving and net lending (current prices);- Population and Employment (in persons);- Employment by industry (in persons and hours worked);- Compensation of employees (current prices);- Household final consumption expenditure by durability (current prices and volume estimates).Please note that OECD reference year changed from 2010 to 2015 on Tuesday 3rd of December, 2019. These data were first provided by the UK Data Service in October 2006. Main Topics: The database covers:Gross Domestic Productlendingsavingincomehousehold final consumption expendituredetailed accounts for population and employmentexchange rates and purchasing power paritiestotal employment, self-employment, and employment by industry sectorGross Domestic Product by type of expenditure and by industrygross fixed capital formation by product and by institutional sectorcomponents of disposable income. 1947 2021 Afghanistan Albania Algeria Andorra Angola Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Rep... Chad Channel Islands Chile China Colombia Comoros Congo Costa Rica Croatia Cuba Curacao Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic EMPLOYMENT EXCHANGE RATES EXPENDITURE Economic conditions... Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Europe European Union Coun... Faroe Islands Finland France GROSS DOMESTIC PRODUCT Gabon Gambia Georgia Germany October 1990 Ghana Gibraltar Greece Grenada Guatemala Guinea Guinea Bissau Honduras Hong Kong Hungary INCOME INDUSTRIES Iceland India Indonesia Iran Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kosovo Kuwait Kyrgyzstan Latvia Lebanon Lesotho Liberia Lithuania Luxembourg Macao Macedonia Madagascar Malawi Malaysia Mali Malta Mauritania Mauritius Mexico Moldova Montenegro Morocco Mozambique Multi nation NATIONAL ACCOUNTING NATIONAL INCOME Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Romania Russia Rwanda Saint Lucia Saint Martin Saint Vincent Saotome Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Korea Spain Sri Lanka Sudan Surinam Swaziland Switzerland Tajikistan Tanzania Thailand Togo Trinidad and Tobago Turkey Turkmenistan Uganda Ukraine United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela Vietnam Virgin Islands USA Zambia Zimbabwe

Abstract

If a donor gives aid for a project that the recipient government would have undertaken anyway, then the aid is financing some expenditure other than the intended project. The notion that aid in this sense may be "fungible," while long recognized, has recently been receiving some empirical support. The paper "What Does Aid to Africa Finance?" focuses on Sub-Saharan Africa—the region with the largest GDP share of aid—and presents results that indicate that aid may be partially fungible, and suggests some reasons why.

This database contains data used for the analysis.

Geographic coverage

The database includes data from Botswana, Burkina Faso, Cameroon, Ethiopia, The Gambia, Ghana, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mauritius, Nigeria, Sudan, Swaziland, Zaire, Zambia, and Zimbabwe.

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

3The Africa Infrastructure Country Diagnostic (AICD) was an unprecedented knowledge program on Africa’s infrastructure that grew out of the pledge by the G8 Summit of 2005 at Gleneagles to substantially increase ODA assistance to Africa, particularly to the infrastructure sector, and the subsequent formation of the Infrastructure Consortium for Africa (ICA). The AICD study was founded on the recognition that sub-Saharan Africa (SSA) suffers from a very weak infrastructural base, and that this is a key factor in the SSA region failing to realize its full potential for economic growth, international trade, and poverty reduction.The study broke new ground, with primary data collection efforts covering network service infrastructures (ICT, power, water & sanitation, road transport, rail transport, sea transport, and air transport) from 2001 to 2006 in 24 selected African countries. Between them, these countries account for 85 percent of the sub-Saharan Africa population, GDP, and infrastructure inflows. The countries included in the initial study were: Benin, Burkina Faso, Cameroon, Cape Verde, Chad, Côte d’Ivoire, Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mozambique, Namibia, Niger, Nigeria, Rwanda, South Africa, Senegal, Sudan, Tanzania, Uganda, and Zambia.The study also represents an unprecedented effort to collect detailed economic and technical data on African infrastructure in relation to the fiscal costs of each of the sectors, future sector investment needs, and sector performance indicators. As a result, it has been possible for the first time to portray the magnitude of the continent’s infrastructure challenges and to provide detailed and substantiated estimates on spending needs, funding gaps, and the potential efficiency dividends to be derived from policy reforms.