variables: 904574

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
904574 P90/P50 ratio (Pretax) (Extrapolated)     2024-05-28 15:35:10 2024-07-25 23:07:39     1820-2022 6538     
{
    "name": "P90/P50 ratio (Pretax) (Extrapolated)",
    "tolerance": 5,
    "numDecimalPlaces": 1
}
 0     p90_p50_ratio_pretax_extrapolated grapher/wid/2024-05-24/world_inequality_database/world_inequality_database#p90_p50_ratio_pretax_extrapolated   2 major   P90/P50 ratio (Pretax) (Extrapolated)       The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income.   
[
    "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.",
    "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/)."
]
 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. Interpolations and extrapolations are included.     
{
    "$schema": "https://files.ourworldindata.org/schemas/grapher-schema.003.json",
    "originUrl": "https://ourworldindata.org/economic-inequality"
}
 float 
[]
 81a9d893e2950bb5a19c796d95513d49 60c6560163aa60b3d95607773dc54b80

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