Dataset replaced by: http://data.europa.eu/euodp/data/dataset/e7XSsvplRDKyJkFqPz9B2w Please be aware that annual and quarterly national accounts' volume figures are expressed in chain-linked volumes with a reference year 2005. Thus, the figures for this indicator are not comparable with previous releases. For more information, click here. GDP includes goods and services that have markets (or which could have markets) and products which are produced by general government and non-profit institutions. For measuring the growth rate of real GDP, the GDP at current prices are valued in prices of the previous year and the thus computed volume changes are imposed on the level of a reference year; this is called a chain-linked series. Accordingly, price movements will not inflate the growth rate. Real GDP per capita is calculated as the ratio of real GDP to the average population of a specific year. It is often used as an indicator of how well off a country is, since it is a measure of average real income in that country. However, it is not a complete measure of economic welfare. For example, GDP does not include most unpaid household work. Neither does GDP take account of negative effects of economic activity, like environmental degradation. Real GDP per capita is based on rounded figures. Discrepancies in tables between totals and percentages are due to rounding.

Data from 1st of June 2022. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."

Graph and download economic data for Real gross domestic product per capita (A939RX0Q048SBEA) from Q1 1947 to Q4 2024 about per capita, real, GDP, and USA.

This map contains Gross Domestic Product - the total value of goods produced and services provided - by country, per capita in 2016, expressed in 2016 US Dollars. Expressing the GDP in "per capita" terms allows for better comparisons across countries. Total GDP is available in an accompanying map. GDP as a measure has been largely criticized as an incomplete measure of productivity and wealth, as it does not take into account production in the informal economy, quality of life, degradation to the environment, or income distribution. However, GDP is an internationally comparable measure, used in everything from banks setting interest rates to political campaign speeches.Source: World Bank, World Development Indicators.

This dataset provides both quarterly and annual estimates of the value of the goods and services produced in Iowa as provided by the U.S. Department of Commerce, Bureau of Economic Analysis in tables SAGDP2N, SAGDP9N, SAGDP10N, SQGDP2, and SQGDP9. Annual data is available beginning in 1997, and quarterly beginning 2005. The data include breakdowns of industries' contributions. Quarterly estimates are presented as an annual rate. Gross domestic product (GDP) is the measure of the market value of all final goods and services produced within Iowa in a particular period of time. In concept, an industry's GDP by state, referred to as its "value added", is equivalent to its gross output (sales or receipts and other operating income, commodity taxes, and inventory change) minus its intermediate inputs (consumption of goods and services purchased from other U.S. industries or imported). The Iowa GDP a state counterpart to the Nation's GDP, the Bureau's featured and most comprehensive measure of U.S. economic activity. Iowa GDP differs from national GDP for the following reasons: Iowa GDP excludes and national GDP includes the compensation of federal civilian and military personnel stationed abroad and government consumption of fixed capital for military structures located abroad and for military equipment, except office equipment; and Iowa GDP and national GDP have different revision schedules. GDP is reported in millions of current dollars. Real GDP is an inflation-adjusted measure of Iowa's gross product that is based on national prices for the goods and services produced within Iowa. The real estimates of gross domestic product (GDP) are measured in millions of chained dollars. The annual per capita real GDP is also provided and is measured in chained dollars. In calculating the per capita real GDP, the real GDP is divided by the Census Bureau’s annual midyear (July 1) population estimates for the year.

In the distributed global GDP dataset sub-national GRP and national GDP data are allocated to 30 arc second (approximately 1km) grid cells in proportion to the population residing in that cell. The method also distinguishes between rural and urban population, assuming the latter to have a higher GDP per capita. Input data are from 1) a global time-series dataset of GDP, with subnational gross regional product (GRP) for 74 countries, compiled by the World Bank Development Economics Research Group (DECRG). 2) Gridded population projections for the year 2009, based on a population grid for the year 2005 provided by LandScanTM Global Population Database (Oak Ridge, TN: Oak Ridge National Laboratory). This dataset has been extrapolated to year 2010 by UNEP/GRID-Geneva. Unit is estimated value of production per cell, in thousand of constant 2000 USD. Cell level anomalies may occur due to poor alignment of multiple input data sources, and it is strongly recommended that users attempt to verify information, or consult original sources, in order to determine suitability for a particular application. This product was compiled by DECRG for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing World Bank DECRG, Washington, DC, extrapolation UNEP/GRID-Geneva.

The Gross Domestic Product per capita in Philippines was last recorded at 3745.65 US dollars in 2023. The GDP per Capita in Philippines is equivalent to 30 percent of the world's average. This dataset provides - Philippines GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita (gross domestic product divided by mid-year population converted to international dollars, using purchasing power parity rates) has been identified as an important determinant of susceptibility and vulnerability by different authors and used in the Disaster Risk Index 2004 (Peduzzi et al. 2009, Schneiderbauer 2007, UNDP 2004) and is commonly used as an indicator for a country's economic development (e.g. Human Development Index). Despite some criticisms (Brooks et al. 2005) it is still considered useful to estimate a population's susceptibility to harm, as limited monetary resources are seen as an important factor of vulnerability. However, collection of data on economic variables, especially sub-national income levels, is problematic, due to various shortcomings in the data collection process. Additionally, the informal economy is often excluded from official statistics. Night time lights satellite imagery of NOAA grid provides an alternative means for measuring economic activity. NOAA scientists developed a model for creating a world map of estimated total (formal plus informal) economic activity. Regression models were developed to calibrate the sum of lights to official measures of economic activity at the sub-national level for some target Country and at the national level for other countries of the world, and subsequently regression coefficients were derived. Multiplying the regression coefficients with the sum of lights provided estimates of total economic activity, which were spatially distributed to generate a 30 arc-second map of total economic activity (see Ghosh, T., Powell, R., Elvidge, C. D., Baugh, K. E., Sutton, P. C., & Anderson, S. (2010).Shedding light on the global distribution of economic activity. The Open Geography Journal (3), 148-161). We adjusted the GDP to the total national GDPppp amount as recorded by IMF (International Monetary Fund) for 2010 and we divided it by the population layer from Worldpop Project. Further, we ran a focal statistics analysis to determine mean values within 10 cell (5 arc-minute, about 10 Km) of each grid cell. This had a smoothing effect and represents some of the extended influence of intense economic activity for local people. Finally we apply a mask to remove the area with population below 1 people per square Km.

This dataset has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Data publication: 2014-06-01

Supplemental Information:

ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).

ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.

The project focused on the following specific objectives:

1. Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;

2. Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;

3. Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;

4. Suggest and analyse new suited adaptation strategies, focused on local needs;

5. Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;

6. Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.

The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Selvaraju Ramasamy

Resource constraints:

copyright

Online resources:

GDP per capita

Project deliverable D4.1 - Scenarios of major production systems in Africa

Climafrica Website - Climate Change Predictions In Sub-Saharan Africa: Impacts And Adaptations

"The resilience of the domestic economic systems of the countries along the Belt and Road reflects the level of resilience of the domestic economic systems of each country, and the higher the value of the data, the stronger the resilience of the domestic economic systems of the countries along the Belt and Road. The resilience of domestic economic systems includes macroeconomic development resilience, industrial and service sector development resilience, and the data products are prepared with reference to the World Bank statistical database, using GDP per capita, gross fixed capital formation as a percentage of GDP, inflation as measured by GDP deflator, and gross savings as measured by GDP deflator for countries along the Belt and Road from 2000 to 2019. The resilience products of the domestic economic system are prepared through a comprehensive diagnosis based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator, using year-on-year data of six indicators: GDP per capita, gross fixed capital formation as a percentage of GDP, gross savings as a percentage of GDP, industrial value added as a percentage of GDP, and service value added as a percentage of GDP. "The resilience dataset of the domestic economic systems of the countries along the Belt and Road is an important reference for analysing and comparing the resilience of the domestic economic systems of various countries.

Japan JP: GDP: USD: Adjusted Net National Income per Capita data was reported at 31,117.799 USD in 2016. This records an increase from the previous number of 28,061.824 USD for 2015. Japan JP: GDP: USD: Adjusted Net National Income per Capita data is updated yearly, averaging 25,163.524 USD from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 38,602.869 USD in 2012 and a record low of 1,672.313 USD in 1970. Japan JP: GDP: USD: Adjusted Net National Income per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Gross Domestic Product: Nominal. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted Average;

The Gross Domestic Product per capita in Austria was last recorded at 46338.96 US dollars in 2023. The GDP per Capita in Austria is equivalent to 367 percent of the world's average. This dataset provides the latest reported value for - Austria GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Gross Domestic Product per capita In the Euro Area was last recorded at 55973.92 US dollars in 2023, when adjusted by purchasing power parity (PPP). The GDP per Capita, In the Euro Area, when adjusted by Purchasing Power Parity is equivalent to 315 percent of the world's average. This dataset provides the latest reported value for - Euro Area GDP per capita PPP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States US: GDP: Growth: Adjusted Net National Income per Capita data was reported at 0.235 % in 2016. This records a decrease from the previous number of 3.088 % for 2015. United States US: GDP: Growth: Adjusted Net National Income per Capita data is updated yearly, averaging 2.406 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 7.229 % in 1984 and a record low of -5.162 % in 1974. United States US: GDP: Growth: Adjusted Net National Income per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted average;

This data set provides predicted regional GDP per capita and weighted measures of regional inequality for 178 countries between 1992 and 2012. The income predictions are based on satellite night-time light data (stable lights from DMSP-OLS). A detailed description of the data set is available from the corresponding publication. Please quote our paper if you use the data for your research.

Regression results for GDP per capita growth rate and rewiring measures.

Morocco MA: GDP: Growth: Adjusted Net National Income per Capita data was reported at 5.412 % in 2015. This records an increase from the previous number of 0.275 % for 2014. Morocco MA: GDP: Growth: Adjusted Net National Income per Capita data is updated yearly, averaging 2.467 % from Dec 1971 (Median) to 2015, with 45 observations. The data reached an all-time high of 11.748 % in 1974 and a record low of -7.661 % in 1981. Morocco MA: GDP: Growth: Adjusted Net National Income per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted average;

The Global Earthquake Total Economic Loss Risk Deciles is a 2.5 minute grid of global earthquake total economic loss risks. A process of spatially allocating Gross Domestic Product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational Units to their respective national GDP are determined using sources of various origin. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational Unit. Once the national GDP has been spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data population distributions. A per capita contribution value is determined within each subnational Unit, and then this value is multiplied by the population per grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell by earthquake hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

Peru PE: GDP: Growth: Adjusted Net National Income per Capita data was reported at 1.111 % in 2016. This records an increase from the previous number of 0.950 % for 2015. Peru PE: GDP: Growth: Adjusted Net National Income per Capita data is updated yearly, averaging 2.255 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 127.342 % in 1988 and a record low of -71.307 % in 1990. Peru PE: GDP: Growth: Adjusted Net National Income per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Gross Domestic Product: Annual Growth Rate. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted average;

The Gross Domestic Product per capita in Australia was last recorded at 60408.94 US dollars in 2023, when adjusted by purchasing power parity (PPP). The GDP per Capita, in Australia, when adjusted by Purchasing Power Parity is equivalent to 340 percent of the world's average. This dataset provides - Australia GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

To verify the relationship between trade variables and financial development in Africa. We mobilize data from 39 African economies for the period 1990-2021. To achieve this complex measure, we use the financial development index imported from the International Monetary Fund (IMF) statistical database. The variable to be explained, trade openness (LTRADE), is presented by the logarithm of the sum of exports and imports of goods and services, as a percentage of GDP, the logarithm of the volume of exports of goods and services as a percentage of GDP (LEXP), and the logarithm of the volume of imports of goods and services as a percentage of GDP (LIMP). Control variables are also included, namely, economic growth represented by the logarithm of real GDP per capita (LGDPPC), population growth, which may reflect the size of the domestic market, measured by the logarithm of the total population (LPOP), and external financing represented by the logarithm of net foreign direct investment inflows, as a percentage of GDP (LFDI). Data for these variables were imported from the World Bank's World Development Indicator (WDI).