[EIP_2EET_SEX_GEO_RT] Share of youth not in employment, education or training (NEET) by sex and rural / urban areas-- ILO modelled estimates, Nov. 2020 (%)
Updated on DBnomics on September 4, 2023 (6:24 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
- [X12] Northern Africa: Upper-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
- [X22] Americas: Low income
- [X23] Americas: Lower-middle income
- [X24] Americas: Upper-middle income
- [X25] Americas: High income
- [X26] Latin America and the Caribbean
- [X27] Latin America and the Caribbean: Low income
- [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
- [X46] Eastern Asia: Low income
- [X47] Eastern Asia: Upper-middle income
- [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
- [X57] Southern Asia: Low income
- [X58] Southern Asia: Lower-middle income
- [X59] Southern Asia: Upper-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
- [X71] Eastern Europe: Lower-middle income
- [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
- [X81] Sub-Saharan Africa: High income
- [X82] European Union 28
- [X83] G20
- [X84] ASEAN
- [X85] BRICS
- [X86] Eastern Asia: Lower-middle income
- [X87] World excluding BRICS
- [X88] G7
- [X89] MENA
- [X90] Arab League
- [X91] CARICOM
- [X92] European Union 27
- [X93] Africa: High income
- [X94] Arab States: Low income
- [X95] Europe and Central Asia: Low income
- [X96] Central and Western Asia: Low income
- [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_13328] 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_15725] ILO - Modelled Estimates
- [XA_15726] ILO - Modelled Estimates
- [XA_15736] ILO - Modelled Estimates
- [XA_15737] ILO - Modelled Estimates
- [XA_15738] 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
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- [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
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- [XA_1978] ILO - Modelled Estimates
- [XA_1980] ILO - Modelled Estimates
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- [XA_1987] ILO - Modelled Estimates
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- [XA_1990] ILO - Modelled Estimates
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- [XA_1996] ILO - Modelled Estimates
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- [XA_2004] ILO - Modelled Estimates
- [XA_2007] ILO - Modelled Estimates
- [XA_2008] ILO - Modelled Estimates
- [XA_2009] ILO - Modelled Estimates
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- [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
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- [XA_2034] ILO - Modelled Estimates
- [XA_2036] ILO - Modelled Estimates
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- [XA_2054] ILO - Modelled Estimates
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- [XA_2128] ILO - Modelled Estimates
- [XA_2129] ILO - Modelled Estimates
- [XA_2130] ILO - Modelled Estimates
- [XA_2132] ILO - Modelled Estimates
- [XA_2133] ILO - Modelled Estimates
- [XA_2134] ILO - Modelled Estimates
- [XA_2136] ILO - Modelled Estimates
- [XA_2137] ILO - Modelled Estimates
- [XA_2138] ILO - Modelled Estimates
- [XA_2140] ILO - Modelled Estimates
- [XA_2142] ILO - Modelled Estimates
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- [XA_2145] ILO - Modelled Estimates
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- [XA_2152] ILO - Modelled Estimates
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- [XA_2165] ILO - Modelled Estimates
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- [XA_2189] ILO - Modelled Estimates
- [XA_2190] ILO - Modelled Estimates
- [XA_2192] ILO - Modelled Estimates
- [XA_2193] ILO - Modelled Estimates
- [XA_2198] 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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- [XA_8376] ILO - Modelled Estimates
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- [XA_8388] ILO - Modelled Estimates
- [XA_8389] ILO - Modelled Estimates
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- [XA_8391] ILO - Modelled Estimates
- [XA_8392] ILO - Modelled Estimates
- [XA_8393] ILO - Modelled Estimates
- [XA_8394] ILO - Modelled Estimates
- [XA_8395] ILO - Modelled Estimates
- [XA_8396] ILO - Modelled Estimates
- [XA_8397] ILO - Modelled Estimates
- [XA_8398] ILO - Modelled Estimates
- [XA_8399] ILO - Modelled Estimates
- [XA_8400] ILO - Modelled Estimates
- [XA_8401] ILO - Modelled Estimates
- [XA_8402] ILO - Modelled Estimates
- [XA_8403] ILO - Modelled Estimates
- [XA_8404] ILO - Modelled Estimates
- [XA_8405] ILO - Modelled Estimates
- [XA_8406] ILO - Modelled Estimates
- [XA_8407] ILO - Modelled Estimates
- [XA_8408] ILO - Modelled Estimates
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- [XA_8425] ILO - Modelled Estimates
- [XA_8426] ILO - Modelled Estimates
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[classif1] Classification 1
- [GEO_COV_NAT] Area type: National
- [GEO_COV_RUR] Area type: Rural
- [GEO_COV_URB] Area type: Urban
[sex] Sex
- [SEX_F] Sex: Female
- [SEX_M] Sex: Male
- [SEX_T] Sex: Total
[frequency] Frequency
- [A] Annual
Search filters
Reference area [ref_area] (283)
Source [source] (283)
Classification 1 [classif1] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 2,547 series:
- from
- 2005=11.517
- to
- 2019=5.452
- min:
- 4.858
- max:
- 12.09
- avg:
- 7.96
- σ:
- 2.57
- from
- 2005=10.464
- to
- 2019=6.877
- min:
- 6.483
- max:
- 12.846
- avg:
- 8.71
- σ:
- 1.756
- from
- 2005=6.139
- to
- 2019=2.878
- min:
- 2.817
- max:
- 6.5
- avg:
- 4.296
- σ:
- 1.366
- from
- 2005=8.408
- to
- 2019=2.275
- min:
- 2.029
- max:
- 8.408
- avg:
- 4.543
- σ:
- 2.557
- from
- 2005=7.313
- to
- 2019=2.572
- min:
- 2.416
- max:
- 7.313
- avg:
- 4.428
- σ:
- 1.961
- from
- 2005=11.389
- to
- 2019=11.687
- min:
- 9.697
- max:
- 17.836
- avg:
- 12.61
- σ:
- 2.431
- from
- 2005=13.657
- to
- 2019=7.648
- min:
- 6.804
- max:
- 15.742
- avg:
- 10.303
- σ:
- 2.691
- from
- 2005=12.481
- to
- 2019=9.723
- min:
- 9.151
- max:
- 16.826
- avg:
- 11.488
- σ:
- 1.992
- from
- 2005=36.21
- to
- 2019=25.438
- min:
- 25.438
- max:
- 36.96
- avg:
- 31.828
- σ:
- 3.596
- from
- 2005=29.738
- to
- 2019=26.18
- min:
- 25.018
- max:
- 30.852
- avg:
- 27.595
- σ:
- 2.071
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AGO.XA_2010.GEO_COV_NAT.SEX_M.A] | 11.517 | 11.334 | 10.924 | 9.946 | 9.662 | 12.09 | 7.662 | 6.994 | 6.548 | 6.24 | 6.065 | 4.858 | 4.941 | 5.17 | 5.452 |
[AGO.XA_2010.GEO_COV_NAT.SEX_T.A] | 10.464 | 10.284 | 9.962 | 9.075 | 8.855 | 12.846 | 10.009 | 9.13 | 8.308 | 7.792 | 7.35 | 6.483 | 6.546 | 6.676 | 6.877 |
[AGO.XA_2010.GEO_COV_RUR.SEX_F.A] | 6.139 | 6.028 | 5.882 | 5.365 | 5.267 | 6.5 | 4.292 | 3.909 | 3.484 | 3.229 | 2.977 | 2.817 | 2.832 | 2.84 | 2.878 |
[AGO.XA_2010.GEO_COV_RUR.SEX_M.A] | 8.408 | 8.268 | 7.97 | 7.255 | 7.05 | 6.74 | 3.196 | 2.915 | 2.72 | 2.588 | 2.509 | 2.029 | 2.064 | 2.158 | 2.275 |
[AGO.XA_2010.GEO_COV_RUR.SEX_T.A] | 7.313 | 7.188 | 6.964 | 6.344 | 6.192 | 6.624 | 3.733 | 3.402 | 3.094 | 2.902 | 2.739 | 2.416 | 2.442 | 2.493 | 2.572 |
[AGO.XA_2010.GEO_COV_URB.SEX_F.A] | 11.389 | 11.168 | 10.872 | 9.899 | 9.697 | 17.836 | 17.242 | 15.738 | 14.091 | 13.096 | 12.125 | 11.365 | 11.44 | 11.503 | 11.687 |
[AGO.XA_2010.GEO_COV_URB.SEX_M.A] | 13.657 | 13.44 | 12.949 | 11.786 | 11.445 | 15.742 | 10.709 | 9.782 | 9.169 | 8.744 | 8.506 | 6.804 | 6.922 | 7.248 | 7.648 |
[AGO.XA_2010.GEO_COV_URB.SEX_T.A] | 12.481 | 12.261 | 11.87 | 10.805 | 10.536 | 16.826 | 14.076 | 12.85 | 11.704 | 10.985 | 10.368 | 9.151 | 9.246 | 9.435 | 9.723 |
[ALB.XA_2137.GEO_COV_NAT.SEX_F.A] | 36.21 | 36.96 | 36.753 | 30.925 | 36.332 | 33.575 | 32.578 | 29.614 | 32.15 | 32.691 | 31.271 | 27.615 | 27.535 | 27.779 | 25.438 |
[ALB.XA_2137.GEO_COV_NAT.SEX_M.A] | 29.738 | 30.436 | 30.852 | 25.442 | 25.531 | 25.801 | 27.703 | 25.896 | 29.92 | 30.209 | 28.474 | 27.185 | 25.018 | 25.538 | 26.18 |
Showing results 11 - 20 / 2,547