{ "data_id": "43753", "name": "Country-Socioeconomic-Status-Scores-Part-II", "exact_name": "Country-Socioeconomic-Status-Scores-Part-II", "version": 1, "version_label": "v1.0", "description": "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 countrys 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 Banks World Development Indicators Database and the United Nations Common Database.\nSee 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. \nVARIABLE DESCRIPTIONS: \nunid: ISO numeric country code (used by the United Nations) \nwbid: ISO alpha country code (used by the World Bank) \nSES: Country socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) \ncountry: Short country name \nyear: Survey year \ngdppc: GDP per capita: Single time-series (imputed) \nyrseduc: Completed years of education in the adult (15+) population \nregion5: Five category regional coding schema\nregionUN: United Nations regional coding schema\nDATA SOURCES: \nThe dataset was compiled by Shawn Dorius (sdoriusiastate.edu) from a large number of data sources, listed below. GDP per Capita: \n\nMaddison, 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. \nWorld 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 \nBarro, 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\/ \nMaddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13. \nUnited Nations Population Division. 2009.", "format": "arff", "uploader": "Dustin Carrion", "uploader_id": 30123, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-24 07:51:42", "update_comment": null, "last_update": "2022-03-24 07:51:42", "licence": "Database: Open Database, Contents: Database Contents", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102578\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Country-Socioeconomic-Status-Scores-Part-II", "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 countrys 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 " ], "weight": 5 }, "qualities": { "NumberOfInstances": 1036, "NumberOfFeatures": 10, "NumberOfClasses": null, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 5, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.009652509652509652, "PercentageOfNumericFeatures": 50, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": null, "PercentageOfMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Computer Systems" }, { "uploader": "38960", "tag": "Machine Learning" } ], "features": [ { "name": "unid", "index": "0", "type": "numeric", "distinct": "74", "missing": "0", "min": "12", "max": "894", "mean": "440", "stdev": "250" }, { "name": "wbid", "index": "1", "type": "string", "distinct": "74", "missing": "0" }, { "name": "country", "index": "2", "type": "string", "distinct": "74", "missing": "0" }, { "name": "year", "index": "3", "type": "numeric", "distinct": "14", "missing": "0", "min": "1880", "max": "2010", "mean": "1945", "stdev": "40" }, { "name": "ses", "index": "4", "type": "numeric", "distinct": "281", "missing": "0", "min": "1", "max": "99", "mean": "52", "stdev": "29" }, { "name": "class", "index": "5", "type": "string", "distinct": "3", "missing": "0" }, { "name": "gdppc", "index": "6", "type": "numeric", "distinct": "863", "missing": "0", "min": "324", "max": "62268", "mean": "5260", "stdev": "8920" }, { "name": "yrseduc", "index": "7", "type": "numeric", "distinct": "782", "missing": "0", "min": "0", "max": "13", "mean": "4", "stdev": "3" }, { "name": "region5", "index": "8", "type": "string", "distinct": "5", "missing": "0" }, { "name": "regionUN", "index": "9", "type": "string", "distinct": "17", "missing": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }