[LUU_2LU4_SEX_AGE_RT] Composite rate of labour underutilization (LU4) by sex and age -- ILO modelled estimates, Nov. 2022 (%)
Updated on DBnomics on December 18, 2023 (4:52 AM).
[ref_area] Reference area
- [AFG] Afghanistan
- [AGO] Angola
- [ALB] Albania
- [ARE] United Arab Emirates
- [ARG] Argentina
- [ARM] Armenia
- [AUS] Australia
- [AUT] Austria
- [AZE] Azerbaijan
- [BDI] Burundi
- [BEL] Belgium
- [BEN] Benin
- [BFA] Burkina Faso
- [BGD] Bangladesh
- [BGR] Bulgaria
- [BHR] Bahrain
- [BHS] Bahamas
- [BIH] Bosnia and Herzegovina
- [BLR] Belarus
- [BLZ] Belize
- [BOL] Bolivia
- [BRA] Brazil
- [BRB] Barbados
- [BRN] Brunei Darussalam
- [BTN] Bhutan
- [BWA] Botswana
- [CAF] Central African Republic
- [CAN] Canada
- [CHA] Channel Islands
- [CHE] Switzerland
- [CHL] Chile
- [CHN] China
- [CIV] Côte d'Ivoire
- [CMR] Cameroon
- [COD] Congo, Democratic Republic of the
- [COG] Congo
- [COL] Colombia
- [COM] Comoros
- [CPV] Cabo Verde
- [CRI] Costa Rica
- [CUB] Cuba
- [CYP] Cyprus
- [CZE] Czechia
- [DEU] Germany
- [DJI] Djibouti
- [DNK] Denmark
- [DOM] Dominican Republic
- [DZA] Algeria
- [ECU] Ecuador
- [EGY] Egypt
- [ERI] Eritrea
- [ESH] Western Sahara
- [ESP] Spain
- [EST] Estonia
- [ETH] Ethiopia
- [FIN] Finland
- [FJI] Fiji
- [FRA] France
- [GAB] Gabon
- [GBR] United Kingdom
- [GEO] Georgia
- [GHA] Ghana
- [GIN] Guinea
- [GMB] Gambia
- [GNB] Guinea-Bissau
- [GNQ] Equatorial Guinea
- [GRC] Greece
- [GTM] Guatemala
- [GUM] Guam
- [GUY] Guyana
- [HKG] Hong Kong, China
- [HND] Honduras
- [HRV] Croatia
- [HTI] Haiti
- [HUN] Hungary
- [IDN] Indonesia
- [IND] India
- [IRL] Ireland
- [IRN] Iran, Islamic Republic of
- [IRQ] Iraq
- [ISL] Iceland
- [ISR] Israel
- [ITA] Italy
- [JAM] Jamaica
- [JOR] Jordan
- [JPN] Japan
- [KAZ] Kazakhstan
- [KEN] Kenya
- [KGZ] Kyrgyzstan
- [KHM] Cambodia
- [KOR] Korea, Republic of
- [KWT] Kuwait
- [LAO] Lao People's Democratic Republic
- [LBN] Lebanon
- [LBR] Liberia
- [LBY] Libya
- [LCA] Saint Lucia
- [LKA] Sri Lanka
- [LSO] Lesotho
- [LTU] Lithuania
- [LUX] Luxembourg
- [LVA] Latvia
- [MAC] Macau, China
- [MAR] Morocco
- [MDA] Moldova, Republic of
- [MDG] Madagascar
- [MDV] Maldives
- [MEX] Mexico
- [MKD] North Macedonia
- [MLI] Mali
- [MLT] Malta
- [MMR] Myanmar
- [MNE] Montenegro
- [MNG] Mongolia
- [MOZ] Mozambique
- [MRT] Mauritania
- [MUS] Mauritius
- [MWI] Malawi
- [MYS] Malaysia
- [NAM] Namibia
- [NCL] New Caledonia
- [NER] Niger
- [NGA] Nigeria
- [NIC] Nicaragua
- [NLD] Netherlands
- [NOR] Norway
- [NPL] Nepal
- [NZL] New Zealand
- [OMN] Oman
- [PAK] Pakistan
- [PAN] Panama
- [PER] Peru
- [PHL] Philippines
- [PNG] Papua New Guinea
- [POL] Poland
- [PRI] Puerto Rico
- [PRK] Korea, Democratic People's Republic of
- [PRT] Portugal
- [PRY] Paraguay
- [PSE] Occupied Palestinian Territory
- [PYF] French Polynesia
- [QAT] Qatar
- [ROU] Romania
- [RUS] Russian Federation
- [RWA] Rwanda
- [SAU] Saudi Arabia
- [SDN] Sudan
- [SEN] Senegal
- [SGP] Singapore
- [SLB] Solomon Islands
- [SLE] Sierra Leone
- [SLV] El Salvador
- [SOM] Somalia
- [SRB] Serbia
- [SSD] South Sudan
- [STP] Sao Tome and Principe
- [SUR] Suriname
- [SVK] Slovakia
- [SVN] Slovenia
- [SWE] Sweden
- [SWZ] Eswatini
- [SYR] Syrian Arab Republic
- [TCD] Chad
- [TGO] Togo
- [THA] Thailand
- [TJK] Tajikistan
- [TKM] Turkmenistan
- [TLS] Timor-Leste
- [TON] Tonga
- [TTO] Trinidad and Tobago
- [TUN] Tunisia
- [TUR] Türkiye
- [TWN] Taiwan, China
- [TZA] Tanzania, United Republic of
- [UGA] Uganda
- [UKR] Ukraine
- [URY] Uruguay
- [USA] United States
- [UZB] Uzbekistan
- [VCT] Saint Vincent and the Grenadines
- [VEN] Venezuela, Bolivarian Republic of
- [VIR] United States Virgin Islands
- [VNM] Viet Nam
- [VUT] Vanuatu
- [WSM] Samoa
- [X01] World
- [X02] World: Low income
- [X03] World: Lower-middle income
- [X04] World: Upper-middle income
- [X05] World: High income
- [X06] Africa
- [X07] Africa: Low income
- [X08] Africa: Lower-middle income
- [X09] Africa: Upper-middle income
- [X10] Northern Africa
- [X11] Northern Africa: Lower-middle income
- [X13] Sub-Saharan Africa
- [X14] Sub-Saharan Africa: Low income
- [X15] Sub-Saharan Africa: Lower-middle income
- [X16] Sub-Saharan Africa: Upper-middle income
- [X17] Central Africa
- [X18] Eastern Africa
- [X19] Southern Africa
- [X20] Western Africa
- [X21] Americas
- [X23] Americas: Lower-middle income
- [X24] Americas: Upper-middle income
- [X25] Americas: High income
- [X26] Latin America and the Caribbean
- [X28] Latin America and the Caribbean: Lower-middle income
- [X29] Latin America and the Caribbean: Upper-middle income
- [X30] Latin America and the Caribbean: High income
- [X31] Caribbean
- [X32] Central America
- [X33] South America
- [X34] Northern America
- [X35] Northern America: High income
- [X36] Arab States
- [X37] Arab States: Lower-middle income
- [X38] Arab States: Upper-middle income
- [X39] Arab States: High income
- [X40] Asia and the Pacific
- [X41] Asia and the Pacific: Low income
- [X42] Asia and the Pacific: Lower-middle income
- [X43] Asia and the Pacific: Upper-middle income
- [X44] Asia and the Pacific: High income
- [X45] Eastern Asia
- [X48] Eastern Asia: High income
- [X49] South-Eastern Asia and the Pacific
- [X51] South-Eastern Asia and the Pacific: Lower-middle income
- [X52] South-Eastern Asia and the Pacific: Upper-middle income
- [X53] South-Eastern Asia and the Pacific: High income
- [X54] South-Eastern Asia
- [X55] Pacific Islands
- [X56] Southern Asia
- [X58] Southern Asia: Lower-middle income
- [X60] Europe and Central Asia
- [X61] Europe and Central Asia: Lower-middle income
- [X62] Europe and Central Asia: Upper-middle income
- [X63] Europe and Central Asia: High income
- [X64] Northern, Southern and Western Europe
- [X65] Northern, Southern and Western Europe: Upper-middle income
- [X66] Northern, Southern and Western Europe: High income
- [X67] Northern Europe
- [X68] Southern Europe
- [X69] Western Europe
- [X70] Eastern Europe
- [X72] Eastern Europe: Upper-middle income
- [X73] Eastern Europe: High income
- [X74] Central Asia
- [X75] Central and Western Asia: Lower-middle income
- [X76] Central and Western Asia: Upper-middle income
- [X77] Central and Western Asia: High income
- [X78] Central and Western Asia
- [X79] Western Asia
- [X82] European Union 28
- [X83] G20
- [X84] ASEAN
- [X85] BRICS
- [X87] World excluding BRICS
- [X88] G7
- [X89] MENA
- [X90] Arab League
- [X91] CARICOM
- [X92] European Union 27
- [X94] Arab States: Low income
- [X97] APEC
- [YEM] Yemen
- [ZAF] South Africa
- [ZMB] Zambia
- [ZWE] Zimbabwe
[source] Source
- [XA_12987] ILO - Modelled Estimates
- [XA_12988] ILO - Modelled Estimates
- [XA_12989] ILO - Modelled Estimates
- [XA_12990] ILO - Modelled Estimates
- [XA_13329] ILO - Modelled Estimates
- [XA_14065] ILO - Modelled Estimates
- [XA_14066] ILO - Modelled Estimates
- [XA_15672] ILO - Modelled Estimates
- [XA_15716] ILO - Modelled Estimates
- [XA_15724] ILO - Modelled Estimates
- [XA_15736] ILO - Modelled Estimates
- [XA_16111] ILO - Modelled Estimates
- [XA_1829] ILO - Modelled Estimates
- [XA_1830] ILO - Modelled Estimates
- [XA_1832] ILO - Modelled Estimates
- [XA_1835] ILO - Modelled Estimates
- [XA_1836] ILO - Modelled Estimates
- [XA_1837] ILO - Modelled Estimates
- [XA_1839] ILO - Modelled Estimates
- [XA_1843] ILO - Modelled Estimates
- [XA_1848] ILO - Modelled Estimates
- [XA_1849] ILO - Modelled Estimates
- [XA_1850] ILO - Modelled Estimates
- [XA_1852] ILO - Modelled Estimates
- [XA_1854] ILO - Modelled Estimates
- [XA_1858] ILO - Modelled Estimates
- [XA_1862] ILO - Modelled Estimates
- [XA_1866] ILO - Modelled Estimates
- [XA_1868] ILO - Modelled Estimates
- [XA_1869] ILO - Modelled Estimates
- [XA_1871] ILO - Modelled Estimates
- [XA_1872] ILO - Modelled Estimates
- [XA_1874] ILO - Modelled Estimates
- [XA_1875] ILO - Modelled Estimates
- [XA_1877] ILO - Modelled Estimates
- [XA_1881] ILO - Modelled Estimates
- [XA_1883] ILO - Modelled Estimates
- [XA_1884] ILO - Modelled Estimates
- [XA_1885] ILO - Modelled Estimates
- [XA_1893] ILO - Modelled Estimates
- [XA_1897] ILO - Modelled Estimates
- [XA_1901] ILO - Modelled Estimates
- [XA_1905] ILO - Modelled Estimates
- [XA_1907] ILO - Modelled Estimates
- [XA_1909] ILO - Modelled Estimates
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- [XA_1914] ILO - Modelled Estimates
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- [XA_1920] ILO - Modelled Estimates
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- [XA_2007] ILO - Modelled Estimates
- [XA_2008] ILO - Modelled Estimates
- [XA_2009] ILO - Modelled Estimates
- [XA_2010] ILO - Modelled Estimates
- [XA_2012] ILO - Modelled Estimates
- [XA_2014] ILO - Modelled Estimates
- [XA_2015] ILO - Modelled Estimates
- [XA_2016] ILO - Modelled Estimates
- [XA_2017] ILO - Modelled Estimates
- [XA_2018] ILO - Modelled Estimates
- [XA_2024] ILO - Modelled Estimates
- [XA_2028] ILO - Modelled Estimates
- [XA_2029] ILO - Modelled Estimates
- [XA_2030] ILO - Modelled Estimates
- [XA_2031] ILO - Modelled Estimates
- [XA_2034] ILO - Modelled Estimates
- [XA_2036] ILO - Modelled Estimates
- [XA_2039] ILO - Modelled Estimates
- [XA_2044] ILO - Modelled Estimates
- [XA_2048] ILO - Modelled Estimates
- [XA_2054] ILO - Modelled Estimates
- [XA_2056] ILO - Modelled Estimates
- [XA_2060] ILO - Modelled Estimates
- [XA_2064] ILO - Modelled Estimates
- [XA_2068] ILO - Modelled Estimates
- [XA_2070] ILO - Modelled Estimates
- [XA_2075] ILO - Modelled Estimates
- [XA_2080] ILO - Modelled Estimates
- [XA_2081] ILO - Modelled Estimates
- [XA_2082] ILO - Modelled Estimates
- [XA_2083] ILO - Modelled Estimates
- [XA_2084] ILO - Modelled Estimates
- [XA_2085] ILO - Modelled Estimates
- [XA_2086] ILO - Modelled Estimates
- [XA_2088] ILO - Modelled Estimates
- [XA_2089] ILO - Modelled Estimates
- [XA_2090] ILO - Modelled Estimates
- [XA_2092] ILO - Modelled Estimates
- [XA_2093] ILO - Modelled Estimates
- [XA_2096] ILO - Modelled Estimates
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- [XA_2110] ILO - Modelled Estimates
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- [XA_2113] ILO - Modelled Estimates
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- [XA_2174] ILO - Modelled Estimates
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- [XA_2203] ILO - Modelled Estimates
- [XA_2206] ILO - Modelled Estimates
- [XA_2232] ILO - Modelled Estimates
- [XA_2234] ILO - Modelled Estimates
- [XA_8368] ILO - Modelled Estimates
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[classif1] Classification 1
- [AGE_YTHADULT_Y15-24] Age (Youth, adults): 15-24
- [AGE_YTHADULT_YGE15] Age (Youth, adults): 15+
- [AGE_YTHADULT_YGE25] Age (Youth, adults): 25+
[sex] Sex
- [SEX_F] Sex: Female
- [SEX_M] Sex: Male
- [SEX_T] Sex: Total
[frequency] Frequency
- [A] Annual
Search filters
Reference area [ref_area] (271)
Source [source] (271)
Classification 1 [classif1] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 2,439 series:
- from
- 2005=46.633
- to
- 2022=52.413
- min:
- 46.301
- max:
- 55.709
- avg:
- 51.476
- σ:
- 3.2
- from
- 2005=44.043
- to
- 2022=50.461
- min:
- 43.639
- max:
- 55.504
- avg:
- 50.224
- σ:
- 4.124
- from
- 2005=25.722
- to
- 2022=29.391
- min:
- 25.281
- max:
- 33.307
- avg:
- 29.719
- σ:
- 2.779
- from
- 2005=24.484
- to
- 2022=27.212
- min:
- 24.145
- max:
- 29.963
- avg:
- 27.221
- σ:
- 2.057
- from
- 2005=25.119
- to
- 2022=28.32
- min:
- 24.726
- max:
- 31.266
- avg:
- 28.493
- σ:
- 2.377
- from
- 2005=18.616
- to
- 2022=21.223
- min:
- 18.256
- max:
- 23.636
- avg:
- 21.265
- σ:
- 1.966
- from
- 2005=15.022
- to
- 2022=16.631
- min:
- 14.67
- max:
- 19.188
- avg:
- 16.901
- σ:
- 1.809
- from
- 2005=16.854
- to
- 2022=18.963
- min:
- 16.496
- max:
- 21.446
- avg:
- 19.114
- σ:
- 1.849
- from
- 2005=49.734
- to
- 2022=46.912
- min:
- 45.036
- max:
- 70.378
- avg:
- 54.619
- σ:
- 7.651
- from
- 2005=52.512
- to
- 2022=44.584
- min:
- 43.492
- max:
- 69.022
- avg:
- 53.448
- σ:
- 6.835
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AGO.XA_2010.AGE_YTHADULT_Y15-24.SEX_M.A] | 46.633 | 46.517 | 46.366 | 46.301 | 46.398 | 53.828 | 52.452 | 52.545 | 52.937 | 53.414 | 53.512 | 53.599 | 53.6 | 53.679 | 53.728 | 55.709 | 52.943 | 52.413 |
[AGO.XA_2010.AGE_YTHADULT_Y15-24.SEX_T.A] | 44.043 | 43.901 | 43.737 | 43.64 | 43.639 | 55.504 | 52.475 | 52.322 | 52.426 | 52.582 | 52.684 | 52.77 | 52.783 | 52.865 | 52.914 | 54.424 | 50.855 | 50.461 |
[AGO.XA_2010.AGE_YTHADULT_YGE15.SEX_F.A] | 25.722 | 25.604 | 25.477 | 25.371 | 25.281 | 33.307 | 30.205 | 30.655 | 31.182 | 31.686 | 31.73 | 31.779 | 31.786 | 31.832 | 31.85 | 32.52 | 29.566 | 29.391 |
[AGO.XA_2010.AGE_YTHADULT_YGE15.SEX_M.A] | 24.484 | 24.385 | 24.259 | 24.166 | 24.145 | 27.202 | 26.213 | 27.149 | 28.165 | 29.183 | 29.197 | 29.223 | 29.195 | 29.215 | 29.214 | 29.963 | 27.4 | 27.212 |
[AGO.XA_2010.AGE_YTHADULT_YGE15.SEX_T.A] | 25.119 | 25.01 | 24.883 | 24.783 | 24.726 | 30.343 | 28.241 | 28.929 | 29.695 | 30.452 | 30.481 | 30.518 | 30.508 | 30.542 | 30.552 | 31.266 | 28.501 | 28.32 |
[AGO.XA_2010.AGE_YTHADULT_YGE25.SEX_F.A] | 18.616 | 18.506 | 18.402 | 18.32 | 18.256 | 22.297 | 20.23 | 21.135 | 22.055 | 22.935 | 23.021 | 23.105 | 23.151 | 23.221 | 23.262 | 23.636 | 21.396 | 21.223 |
[AGO.XA_2010.AGE_YTHADULT_YGE25.SEX_M.A] | 15.022 | 14.907 | 14.794 | 14.712 | 14.678 | 15.747 | 14.67 | 16.054 | 17.429 | 18.772 | 18.844 | 18.917 | 18.95 | 19.012 | 19.053 | 19.188 | 16.842 | 16.631 |
[AGO.XA_2010.AGE_YTHADULT_YGE25.SEX_T.A] | 16.854 | 16.741 | 16.63 | 16.547 | 16.496 | 19.078 | 17.487 | 18.627 | 19.77 | 20.878 | 20.956 | 21.035 | 21.074 | 21.141 | 21.183 | 21.446 | 19.15 | 18.963 |
[ALB.XA_2137.AGE_YTHADULT_Y15-24.SEX_F.A] | 49.734 | 49.694 | 50.625 | 58.736 | 55.483 | 61.239 | 45.295 | 54.126 | 66.798 | 70.378 | 68.549 | 58.545 | 53.573 | 50.595 | 45.036 | 49.676 | 48.15 | 46.912 |
[ALB.XA_2137.AGE_YTHADULT_Y15-24.SEX_M.A] | 52.512 | 52.409 | 53.725 | 54.124 | 51.963 | 57.501 | 49.351 | 55.699 | 60.069 | 69.022 | 64.059 | 61.738 | 52.688 | 45.747 | 43.492 | 47.532 | 45.853 | 44.584 |
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