variables: 904781

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

This data as json

id name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
904781 50% of the median - Share of population in poverty (Post-tax national) (Estimated) %   2024-05-28 15:35:29 2024-07-25 23:07:56     1913-2022 6538   % 
{
    "name": "50% of the median - Share of population in poverty (Post-tax national) (Estimated)",
    "unit": "%",
    "shortUnit": "%",
    "tolerance": 5,
    "numDecimalPlaces": 0
}
 0     headcount_ratio_50_median_posttax_nat grapher/wid/2024-05-24/world_inequality_database/world_inequality_database#headcount_ratio_50_median_posttax_nat   2 major   50% of the median - Share of population in poverty (Post-tax national) (Estimated)       Share of the population living below the poverty line of 50% of the median   
[
    "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.",
    "The data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.",
    "These underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
    "In the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/)."
]
 We extract estimations of Gini, mean, percentile thresholds, averages, and shares via the [`wid` Stata command](https://github.com/thomasblanchet/wid-stata-tool). We calculate threshold and share ratios by dividing different thresholds and shares, respectively. This data has been estimated by calculating the 50% of the median, and then checking that value against the closest threshold in the percentile distribution. The headcount ratio is then the percentile, the share of the population below that threshold. Interpolations and extrapolations are excluded by using the option `exclude` in the Stata command.     
{
    "$schema": "https://files.ourworldindata.org/schemas/grapher-schema.003.json",
    "originUrl": "https://ourworldindata.org/economic-inequality"
}
 float 
[]
 72ef521e1b2899733ae567911a87d691 961e30b291223edc17f41380ffa5ca4d

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