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

The Gross Domestic Product (GDP) in South Africa was worth 400.26 billion US dollars in 2024, according to official data from the World Bank. The GDP value of South Africa represents 0.38 percent of the world economy. This dataset provides the latest reported value for - South Africa GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Sub-Saharan Africa Regional Economic Outlook (AFRREO)

Explore GDP per capita data and national accounts information with this comprehensive dataset. Gain insights into economic trends and comparisons across various countries. Click now to access the data!

GDP, National Accounts, ITEM

Afghanistan, Albania, Algeria, Andorra, 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, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, 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, Kiribati, Kuwait, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, ZimbabweFollow data.kapsarc.org for timely data to advance energy economics research..GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current international dollars based on the 2011 ICP round.

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

The greatest economy in Africa is that of Nigeria. Gross domestic product (GDP), which represents the total cost of goods and services generated in Nigeria, is a key indicator of the country's economic development. In this data analysis, we will decide on the potential future of Nigeria's growth and examine some potential variables that could slow down the country's pace of development. We will also examine the role that leadership may play in the country's economy's expansion.

To read more https://rb.gy/rlqdk

Sub-Saharan Africa Regional Economic Outlook (AFRREO)

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, 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, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, 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, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

GDP by industry gross value-added in Kenya, Nigeria, Botswana and South Africa.

Context and Content

The dataset blends the University of Groningen's Penn World Table Productivity dataset, the Bank of Canada's Commodity Indices and the World Bank's GDP dataset. The blend is specifically created to answer the question: "What factors contribute most to, or are most indicative of, recessions in Africa?"

Content

The dataset has 49 feature variables and 1 target variable (i.e. the ‘growthbucket’ variable). There is a total of 486 samples in the dataset. 92.81% of the samples belong to the “0”, or “No_Recession” class. And, 7.82% of the samples belong to the “1” or “Recession” class. In short, the dataset has a class imbalance. It is useful for learning techniques for dealing with class imbalance like Cost-Sensitive Classification, Oversampling and Undersampling. For descriptions of the variables, see the attached file named: VariableDefinitions.csv

Years Covered: 2000 to 2017.

Countries Covered: 27 African Countries Including: Morocco, South Africa, Tanzania, Rwanda, Eswatini, Togo, Burkina Faso, Angola, Tunisia, Nigeria, Kenya, Burundi, Benin, Namibia, Central African Republic, Sudan, Gabon, Niger, Sierra Leone, Lesotho, Mauritania, Senegal, Mauritius, Botswana, Cameroon, Zimbabwe and Mozambique.

Acknowledgements

University of Groningen: 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

Bank of Canada: Bank of Canada (2019). Commodity Price Index. [online] Bankofcanada.ca. Available at: https://www.bankofcanada.ca/rates/price-indexes/bcpi/ [Accessed 28 June 2019].

World Bank: World Bank (2019). GDP Growth (Annual %). [online] databank.worldbank.org. Available at: http://api.worldbank.org/v2/en/indicator/NY.GDP.MKTP.KD.ZG?downloadformat=excel [Accessed 27 June 2019].

Inspiration

A question: "What factors contribute most to, or are most indicative of, recessions in Africa?"

Explore annual GDP growth rates for various countries with this dataset. Analyze trends and patterns related to GDP growth to make informed decisions. Click here for more information!

GDP growth (annual %), GDP, Growth Rates

Kenya, Spain, Syrian Arab Republic, Bosnia and Herzegovina, El Salvador, Italy, Sint Maarten (Dutch part), Comoros, Kosovo, Argentina, Bulgaria, Guinea-Bissau, Slovenia, Guinea, Belize, Low income, Lower middle income, New Caledonia, St. Kitts and Nevis, Benin, World, Kyrgyz Republic, United Arab Emirates, Ethiopia, Burundi, Korea, Rep., Low & middle income, Euro area, Libya, Luxembourg, Namibia, Kiribati, India, Burkina Faso, East Asia & Pacific (excluding high income), Tajikistan, Lao PDR, Equatorial Guinea, Niger, Liechtenstein, Palau, Hong Kong SAR, China, Switzerland, Tonga, Qatar, Turkiye, Middle East & North Africa (excluding high income), Indonesia, Iraq, Fiji, Central Europe and the Baltics, Isle of Man, Costa Rica, Finland, Small states, Singapore, Slovak Republic, Netherlands, Turks and Caicos Islands, Europe & Central Asia (IDA & IBRD countries), Japan, Bhutan, Belgium, Australia, Denmark, Heavily indebted poor countries (HIPC), Middle East & North Africa (IDA & IBRD countries), Uzbekistan, Pacific island small states, Mongolia, Gabon, St. Vincent and the Grenadines, Ukraine, Venezuela, RB, Latvia, Macao SAR, China, Vietnam, Arab World, Myanmar, Latin America & Caribbean (excluding high income), Haiti, Micronesia, Fed. Sts., Nicaragua, Panama, San Marino, Gambia, The, Guatemala, IDA & IBRD total, Azerbaijan, Chad, Zimbabwe, Mali, Bolivia, Grenada, Mexico, East Asia & Pacific (IDA & IBRD countries), Timor-Leste, Dominica, Peru, Malawi, Trinidad and Tobago, Nauru, Monaco, Tuvalu, Egypt, Arab Rep., Virgin Islands (U.S.), Sao Tome and Principe, Cabo Verde, IDA only, Mozambique, Oman, Yemen, Rep., Albania, New Zealand, Latin America & Caribbean, Rwanda, Cameroon, Lesotho, Solomon Islands, Germany, Bangladesh, Papua New Guinea, Maldives, Moldova, Antigua and Barbuda, Congo, Dem. Rep., Romania, Portugal, Africa Western and Central, Mauritius, France, Uruguay, Tanzania, Colombia, South Asia (IDA & IBRD), Honduras, South Sudan, Sudan, Cuba, Least developed countries: UN classification, South Asia, Tunisia, Guyana, Nepal, Barbados, Brunei Darussalam, United States, Canada, Lebanon, Africa Eastern and Southern, Sub-Saharan Africa (excluding high income), Angola, Bahamas, The, Fragile and conflict affected situations, Malta, Middle East & North Africa, Turkmenistan, Cote d'Ivoire, Northern Mariana Islands, Thailand, Seychelles, North Macedonia, Afghanistan, Russian Federation, IBRD only, Iran, Islamic Rep., Malaysia, Djibouti, Europe & Central Asia (excluding high income), Norway, Dominican Republic, French Polynesia, Jordan, Nigeria, Lithuania, Estonia, Eswatini, Vanuatu, Late-demographic dividend, St. Lucia, Cambodia, Curacao, Kuwait, Belarus, American Samoa, Bahrain, Somalia, Pre-demographic dividend, Ghana, Sierra Leone, Jamaica, Ecuador, European Union, Post-demographic dividend, Brazil, Central African Republic, Chile, Puerto Rico, Pakistan, Uganda, United Kingdom, IDA total, Marshall Islands, Czechia, Channel Islands, Poland, Togo, Latin America & the Caribbean (IDA & IBRD countries), Sweden, Iceland, Armenia, Georgia, Montenegro, Europe & Central Asia, Hungary, IDA blend, Sub-Saharan Africa (IDA & IBRD countries), Paraguay, Zambia, Andorra, OECD members, Bermuda, Early-demographic dividend, Croatia, Upper middle income, Algeria, Samoa, Eritrea, Suriname, Mauritania, Guam, China, Sri Lanka, Congo, Rep., Liberia, Greece, Botswana, East Asia & Pacific, West Bank and Gaza, Philippines, Cayman Islands, Saudi Arabia, South Africa, High income, Serbia, Caribbean small states, Greenland, Cyprus, Aruba, Ireland, Israel, Kazakhstan, Morocco, Madagascar, Other small states, Sub-Saharan Africa, Senegal, Middle income, Austria, North America Follow data.kapsarc.org for timely data to advance energy economics research.

There are over one million economic time series specifically focused on Africa in the most extensive African economic dataset available today. Our datasets consist of a blend of data sourced nationally from National Statistical Offices, Central Banks, and other national institutions, alongside international data from the IMF, World Bank, and other global organizations.

This supplementary dataset includes secondary data collected during the study on the mediating effect of transport energy consumption in the relationship between non-renewable energy consumption and CO2 emissions. The indicators included in the dataset are CO2 per capita, oil products, transport energy consumption, clean energy access, GDP per capita, industry, renewable energy consumption, agricultural land, trade and urban population. Countries included in the sample are Angola, Botswana, Cameroon, Congo, Democratic Republic of the Congo, Egypt, Ethiopia, Gabon, Ghana, Ivory Coast, Kenya, Morocco, Mozambique, Niger, Nigeria, Rwanda, Senegal, South Africa, Tanzania, Uganda, Tunisia, and Zambia. The research dataset was retrieved from the World Bank database and the International Energy Agency website. This resource aims to enhance transparency and facilitate further research.

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

Annual data (covering 1990-2019) on domestic electricity consumption (ELC), renewable electric power generation (RELG), gross domestic product (GDP), and population,(TP) for Egypt, Algeria, South Africa, and Nigeria. ELC and RELG are measured in TWh, and TP and GDP are measured in million people and purchasing power parity constant 2017 international dollars, respectively. The file also contains data on electric power demand forecast and renewable electric power and transition pathways for each of the four countries.

HIV literature has grown exponentially since it was named the virus that causes acquired immunodeficiency syndrome (AIDS). Bibliometric analysis is a practical approach for quantitatively and qualitatively assessing scientific research. This work aims to describe HIV research output in Africa by country from 1986 until 2020. We conducted a search of the PubMed database in June 2021 for a 35-year period spanning 1986 to 2020. We comparatively weighed for countries’ populations, gross domestic product (GDP), and the number of persons living with HIV (PLHIV) by calculating the ratio of the number of publications from each country. We used Poisson regression models to explore the trends in countries’ HIV research output over the study period. The Pearson correlation analysis assessed the association between research output, population size, GDP, and the number of PLHIV.A total of 83,527 articles from African countries on HIV indexed in PubMed were included for analysis. Republic of South Africa, Uganda, Kenya, and Nigeria account for 54% of the total indexed publications with 33.2% (26,907); 8.4% (7,045); 7.3% (6,118); and 5.1% (4,254), respectively. Africa’s proportion of the world’s total HIV publications increased from 5.1% in 1986 to 31.3% in 2020. There was a strong positive and statistically significant correlation between the total indexed HIV publications and countries’ GDP (r = 0.59, P

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