This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the countries in this dataset have a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS:

unid: ISO numeric country code (used by the United Nations)

wbid: ISO alpha country code (used by the World Bank)

SES: Country socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174)

country: Short country name

year: Survey year

gdppc: GDP per capita: Single time-series (imputed)

yrseduc: Completed years of education in the adult (15+) population

region5: Five category regional coding schema

regionUN: United Nations regional coding schema

DATA SOURCES:

The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita:

1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls.

2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm

3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/

4. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.

5. United Nations Population Division. 2009.

The Gross Domestic Product per capita in the United States was last recorded at 75491.61 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in the United States, when adjusted by Purchasing Power Parity is equivalent to 425 percent of the world's average. This dataset provides - United States GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in Canada was last recorded at 44401.72 US dollars in 2024. The GDP per Capita in Canada is equivalent to 352 percent of the world's average. This dataset provides - Canada GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in Philippines was last recorded at 3925.30 US dollars in 2024. The GDP per Capita in Philippines is equivalent to 31 percent of the world's average. This dataset provides - Philippines GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Analysis of ‘Canada National & Provincial Per Capita Income’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/charlesluan/canada-national-provincial-capita-income-762019 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Filtered data which only remains 10 provinces and national capita income, median income, with 16 years old & over, both sexes, in 2019 constant dollar

• The raw data had been already adjusted by 2019 constant dollar, from 1976-2019

• Please be aware territories of Canada were not listed in the original dataset

• For example, the 2018 Canada national average income is not equal to the average of 10 provinces income, since territories are not in the list.

• My practicing data exploration of this dataset: Facts of Individuals Income in Canada, 1976 - 2019

Acknowledgements

Data source:
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas **Raw data version: ** Table: 11-10-0239-01 (formerly CANSIM 206-0052) **Release date: ** 2021-03-23

Inspiration

I was really surprised when revealing these rows, it seems like there isn't much growth since 1976 Canada average income is 40,800 dollars while 2019 is 49,000 dollars. (Please be noticed these are adjusted by 2019 constant dollar)

Please correct me if I was wrong. Thank you

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Country Socioeconomic Status Scores: 1880-2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sdorius/globses on 14 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the world’s people live in a country with a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS: UNID: ISO numeric country code (used by the United Nations) WBID: ISO alpha country code (used by the World Bank) SES: Socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) country: Short country name year: Survey year SES: Socioeconomic status score (1-99) for each of 174 countries gdppc: GDP per capita: Single time-series (imputed) yrseduc: Completed years of education in the adult (15+) population popshare: Total population shares

DATA SOURCES: The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita: 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. Maddison population data in 000s; GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls. 2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm 3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/ Total Population 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
2. United Nations Population Division. 2009.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘🏦 US Retail Sales Per Capita by Store Type’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/us-retail-sales-per-capita-by-store-type-2000-20e on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

I have added a column on the right that shows the compound annual growth rate (CGR) of per capita spending from 2000 to 2015.

source:

This dataset was created by Gary Hoover and contains around 0 samples along with Unnamed: 15, Unnamed: 9, technical information and other features such as: - Unnamed: 18 - Unnamed: 12 - and more.

How to use this dataset

• Analyze Unnamed: 4 in relation to Unnamed: 10
• Study the influence of Unnamed: 14 on Unnamed: 1
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Gary Hoover

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

The Gross Domestic Product per capita in Jamaica was last recorded at 5312.40 US dollars in 2024. The GDP per Capita in Jamaica is equivalent to 42 percent of the world's average. This dataset provides - Jamaica GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in Zimbabwe was last recorded at 1420.80 US dollars in 2024. The GDP per Capita in Zimbabwe is equivalent to 11 percent of the world's average. This dataset provides the latest reported value for - Zimbabwe GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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 indicator is calculated as the ratio of real GDP to the average population of a specific year. GDP measures the value of total final output of goods and services produced by an economy within a certain period of time. It includes goods and services that have markets (or which could have markets) and products which are produced by general government and non-profit institutions. It is a measure of economic activity and is also used as a proxy for the development in a country’s material living standards. However, it is a limited measure of economic welfare. For example, neither does GDP include most unpaid household work nor does GDP take account of negative effects of economic activity, like environmental degradation.

The indicator is calculated as the ratio of real GDP to the average population of a specific year. GDP measures the value of total final output of goods and services produced by an economy within a certain period of time. It includes goods and services that have markets (or which could have markets) and products which are produced by general government and non-profit institutions. It is a measure of economic activity and is also used as a proxy for the development in a country’s material living standards. However, it is a limited measure of economic welfare. For example, neither does GDP include most unpaid household work nor does GDP take account of negative effects of economic activity, like environmental degradation.

Analysis of ‘👣 Ecological Footprint per capita ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/nfa-2016-editione on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

National Footprint Accounts 2016 Edition

Dataset provides Ecological Footprint per capita data for years 1961-2012 in global hectares (gha).

Ecological Footprint is a measure of how much area of biologically productive land and water an individual, population, or activity requires to produce all the resources it consumes and to absorb the waste it generates, using prevailing technology and resource management practices. The Ecological Footprint is measured in global hectares. Because trade is global, an individual or country's Footprint includes land or sea from all over the world. Without further specification, Ecological Footprint generally refers to the Ecological Footprint of consumption. Ecological Footprint is often referred to in short form as Footprint.

This dataset was created by Global Footprint Network and contains around 8000 samples along with Quality Score, Year, technical information and other features such as: - Country Code - Ef Percap - and more.

How to use this dataset

• Analyze Country in relation to Quality Score
• Study the influence of Year on Country Code
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Global Footprint Network

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

This data set records the statistical data of per capita net income index of farmers and herdsmen in Qinghai Province from 1980 to 2000, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Per capita net income index of farmers and herdsmen over the years 1980-1998.xls Per capita net income index of farmers and herdsmen over the years 1980-1999.xls Per capita net income index of farmers and herdsmen over the years 1980-2000.xls The data table structure is the same. For example, the per capita net income index of farmers and herdsmen from 1980 to 1998 has four fields Field 1: year Field 2: net income per capita Field 3: month on month index Field 4: fixed base index

The Gross Domestic Product per capita in Tanzania was last recorded at 1120.77 US dollars in 2024. The GDP per Capita in Tanzania is equivalent to 9 percent of the world's average. This dataset provides the latest reported value for - Tanzania GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The basic econometric model for the suggested interaction effect of resource endowments and institutional quality on economic growth is borrowed from Boschini et al., 2007 and Brunnschweiler, 2007. The approximation for institutional quality must be carefully chosen. The standard proxy variables that are typically employed in the literature with respect to the resource curse are indices such as ICRG, BERI, BI ratings (pioneered by Knack and Keefer, 1995; Mauro, 1995), and the Worldwide Governance Indicators (WGI) suggested by Kaufmann et al. (2010). However, a potential bias in these indicators may arise from the fact that they are based on the subjective assessments of respondents. For instance, the evaluators may be more likely report that governance in a country is good during times of strong economic performance. The use of CIM also has potential risks if the measure is idiosyncratic and irrelevant to contract enforcement and property rights. Clague et al. (1999) reviewed case studies from several countries and found that CIM is a good measure of institutional quality, though some country examples demonstrate idiosyncratic cases. We also use the indicators of governance used by Kaufmann et al. (2010) such as Voice and Accountability (VA), Political Stability and the Absence of Violence (PA), Government Effectiveness (GE), Regulatory Quality (RQ), Rule of Law (RL), and Control of Corruption (CC)—with CIM, was illustrated to examine the suitability of CIM as an institutional quality variable. Purpose: The data obtained is employed for investigation of dissertation. My main objective in this analysis was to assess the impact of resource rent shares of income per capita through various resource curse channels. I hypothesized that natural resource abundance only encourages economic development in countries with high quality economic institutions.

This dataset contains the annual historical series of CO2 Emissions and Drivers ( Kaya Decomposition) from 1971-2020Note: Identifying drivers of CO2 emissions trends This table presents the decomposition of CO2 emissions into four driving factors following the Kaya identity1, which is generally presented in the form: Kaya identity C = P (G/P) (E/G) (C/E) where: "C = CO2 emissions; P = populationG = GDPE = primary energy consumption" "The identity expresses, for a given time, CO2 emissions as the product of population, per capita economic output (G/P), energy intensity of the economy (E/G) and carbon intensity of the energy mix (C/E).Because of possible non-linear interactions between terms, the sum of the percentage changes of the four factors, e.g. (Py-Px)/Px, will not generally add up to the percentage change of CO2 emissions (Cy-Cx)/Cx. However, relative changes of CO2 emissions in time can be obtained from relative changes of the four factors as follows:" Kaya identity: relative changes in time Cy/Cx = Py/Px (G/P)y/(G/P)x (C/E)y/(C/E)x where x and y represent for example two different years. In this table, the Kaya decomposition is presented as: "CO2 emissions and driversCO2 = P (GDP/P) (TES/GDP) (CO2/TES) " where: "C = CO2 emissions; P = populationGDP/P = GDP/population *TES/GDP = Total primary energy consumption per GDP *CO2/TES = CO2 emissions per unit TES" * GDP in 2015 USD, based on purchasing power parities. "The Kaya identity can be used to discuss the primary driving forces of CO2 emissions. For example, it shows that, globally, increases in population and GDP per capita have been driving upwards trends in CO2 emissions, more than offsetting the reduction in energy intensity. In fact, the carbon intensity of the energy mix is almost unchanged, due to the continued dominance of fossil fuels - particularly coal - in the energy mix, and to the slow uptake of low-carbon technologies.However, it should be noted that there are important caveats in the use of the Kaya identity. Most important, the four terms on the right-hand side of equation should be considered neither as fundamental driving forces in themselves, nor as generally independent from each other."

The Gross Domestic Product per capita in Philippines was last recorded at 10375.94 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in Philippines, when adjusted by Purchasing Power Parity is equivalent to 58 percent of the world's average. This dataset provides - Philippines GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.