{"id":1107892,"name":"Female share of low pay earners","unit":"%","createdAt":"2025-09-17T14:52:35.000Z","updatedAt":"2025-09-17T14:52:35.000Z","coverage":"","timespan":"1995-2022","datasetId":7213,"shortUnit":"%","columnOrder":0,"shortName":"female_share_of_low_pay_earners","catalogPath":"grapher/un/2025-08-12/ilostat/ilostat#female_share_of_low_pay_earners","descriptionShort":"Percentage of low pay workers, among all low pay workers, who are female.","descriptionFromProducer":"**With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures.** This measure of earnings dispersion refers to the percentage of low pay workers, among all low pay workers, who are female. For more information, refer to the [Gender Equality and Non-Discrimination Indicators (GEND) database description](https://ilostat.ilo.org/methods/concepts-and-definitions/description-gender-equality-and-non-discrimination-indicators/).","descriptionProcessing":"","type":"float","datasetName":"ILOSTAT","updatePeriodDays":365,"datasetVersion":"2025-08-12","nonRedistributable":false,"display":{"name":"Female share of low pay earners","unit":"%","shortUnit":"%","tolerance":5,"numDecimalPlaces":1},"schemaVersion":2,"processingLevel":"minor","presentation":{"attributionShort":"ILO"},"descriptionKey":["Workers are considered _low pay_ if their hourly earnings at all jobs are less than two-thirds of median hourly earnings."],"dimensions":{"years":{"values":[{"id":2020},{"id":2021},{"id":2018},{"id":2019},{"id":2022},{"id":2007},{"id":2008},{"id":2009},{"id":2010},{"id":2011},{"id":2016},{"id":2014},{"id":2017},{"id":2012},{"id":2013},{"id":2015},{"id":1998},{"id":2000},{"id":2002},{"id":2004},{"id":2006},{"id":1995},{"id":1996},{"id":1997},{"id":1999},{"id":2001},{"id":2003},{"id":2005}]},"entities":{"values":[{"id":15,"name":"Afghanistan","code":"AFG"},{"id":16,"name":"Albania","code":"ALB"},{"id":21,"name":"Argentina","code":"ARG"},{"id":22,"name":"Armenia","code":"ARM"},{"id":23,"name":"Australia","code":"AUS"},{"id":24,"name":"Austria","code":"AUT"},{"id":39,"name":"Bulgaria","code":"BGR"},{"id":31,"name":"Belize","code":"BLZ"},{"id":37,"name":"Brazil","code":"BRA"},{"id":38,"name":"Brunei","code":"BRN"},{"id":44,"name":"Canada","code":"CAN"},{"id":7,"name":"Switzerland","code":"CHE"},{"id":43,"name":"Cameroon","code":"CMR"},{"id":170,"name":"Colombia","code":"COL"},{"id":166,"name":"Costa Rica","code":"CRI"},{"id":279,"name":"Curacao","code":"CUW"},{"id":163,"name":"Cyprus","code":"CYP"},{"id":162,"name":"Czechia","code":"CZE"},{"id":6,"name":"Germany","code":"DEU"},{"id":161,"name":"Denmark","code":"DNK"},{"id":160,"name":"Dominican Republic","code":"DOM"},{"id":201,"name":"Ecuador","code":"ECU"},{"id":9,"name":"Spain","code":"ESP"},{"id":155,"name":"Finland","code":"FIN"},{"id":3,"name":"France","code":"FRA"},{"id":1,"name":"United Kingdom","code":"GBR"},{"id":147,"name":"Guinea","code":"GIN"},{"id":149,"name":"Greece","code":"GRC"},{"id":148,"name":"Guatemala","code":"GTM"},{"id":138,"name":"Hungary","code":"HUN"},{"id":136,"name":"Indonesia","code":"IDN"},{"id":207,"name":"Iceland","code":"ISL"},{"id":133,"name":"Israel","code":"ISR"},{"id":119,"name":"Lithuania","code":"LTU"},{"id":210,"name":"Luxembourg","code":"LUX"},{"id":122,"name":"Latvia","code":"LVA"},{"id":111,"name":"Moldova","code":"MDA"},{"id":211,"name":"Maldives","code":"MDV"},{"id":113,"name":"Mexico","code":"MEX"},{"id":115,"name":"Mali","code":"MLI"},{"id":212,"name":"Malta","code":"MLT"},{"id":112,"name":"Mongolia","code":"MNG"},{"id":116,"name":"Malaysia","code":"MYS"},{"id":5,"name":"Netherlands","code":"NLD"},{"id":106,"name":"New Zealand","code":"NZL"},{"id":101,"name":"Pakistan","code":"PAK"},{"id":97,"name":"Peru","code":"PER"},{"id":96,"name":"Philippines","code":"PHL"},{"id":11,"name":"Poland","code":"POL"},{"id":95,"name":"Portugal","code":"PRT"},{"id":98,"name":"Paraguay","code":"PRY"},{"id":12,"name":"Russia","code":"RUS"},{"id":85,"name":"Slovakia","code":"SVK"},{"id":10,"name":"Sweden","code":"SWE"},{"id":75,"name":"Thailand","code":"THA"},{"id":64,"name":"Tanzania","code":"TZA"},{"id":68,"name":"Uganda","code":"UGA"},{"id":63,"name":"Uruguay","code":"URY"},{"id":62,"name":"Uzbekistan","code":"UZB"},{"id":238,"name":"Venezuela","code":"VEN"},{"id":84,"name":"Vietnam","code":"VNM"},{"id":61,"name":"Yemen","code":"YEM"},{"id":81,"name":"South Africa","code":"ZAF"}]}},"origins":[{"id":8697,"title":"ILOSTAT","description":"The ILO’s main online database, ILOSTAT, maintained by the Department of Statistics, is the world’s largest repository of labour market statistics. It covers all countries and regions and a wide range of labour-related topics, including employment, unemployment, wages, working time and labour productivity, to name a few. It includes time series going back as far as 1938; annual, quarterly and monthly labour statistics; country-level, regional and global estimates; and even projections of the main labour market indicators.","producer":"International Labour Organization","citationFull":"International Labour Organization. (2025). ILO modelled estimates database, ILOSTAT [database]. Available from https://ilostat.ilo.org/data/.","attributionShort":"ILO","urlMain":"https://ilostat.ilo.org/","dateAccessed":"2025-09-17","datePublished":"2025-09-16","license":{"url":"https://www.ilo.org/rights-and-permissions#data","name":"CC BY 4.0"}}]}