variables: 904563

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
904563 Palma ratio (Post-tax disposable) (Extrapolated)     2024-05-28 15:35:09 2024-07-25 23:07:39     1970-2022 6538     
{
    "name": "Palma ratio (Post-tax disposable) (Extrapolated)",
    "tolerance": 5,
    "numDecimalPlaces": 1
}
 0     palma_ratio_posttax_dis_extrapolated grapher/wid/2024-05-24/world_inequality_database/world_inequality_database#palma_ratio_posttax_dis_extrapolated   2 major   Palma ratio (Post-tax disposable) (Extrapolated)       The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality.   
[
    "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received, but does not include in-kind benefits and therefore does not add up to national income.",
    "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 
[]
 de3382d895c3c7c1bbe3440b25959c90 246187dcee3e23eb29f471d1cf7278ce

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