variables: 904572

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
904572 P50/P10 ratio (Pretax) (Extrapolated)     2024-05-28 15:35:10 2024-07-25 23:07:39     1820-2022 6538     
{
    "name": "P50/P10 ratio (Pretax) (Extrapolated)",
    "tolerance": 5,
    "numDecimalPlaces": 1
}
 0     p50_p10_ratio_pretax_extrapolated grapher/wid/2024-05-24/world_inequality_database/world_inequality_database#p50_p10_ratio_pretax_extrapolated   2 major   P50/P10 ratio (Pretax) (Extrapolated)       The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population.   
[
    "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 
[]
 fd028b496c15401095304f77d4003ec5 862d93c5cda6e5956ef6df6431ecb0e0

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