[EMP_2TRU_SEX_AGE_GEO_NB] Time-related underemployment by sex, age and rural / urban areas -- ILO modelled estimates, Nov. 2020 (thousands)
Retrieved by DBnomics on September 4, 2023 (6:24 AM).
[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
[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
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[XA_1829] ILO - Modelled Estimates
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[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
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[XA_1848] ILO - Modelled Estimates
[XA_1849] ILO - Modelled Estimates
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[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
[XA_1913] ILO - Modelled Estimates
[XA_1914] ILO - Modelled Estimates
[XA_1916] ILO - Modelled Estimates
[XA_1920] ILO - Modelled Estimates
[XA_1921] ILO - Modelled Estimates
[XA_1922] ILO - Modelled Estimates
[XA_1924] ILO - Modelled Estimates
[XA_1928] ILO - Modelled Estimates
[XA_1931] ILO - Modelled Estimates
[XA_1932] ILO - Modelled Estimates
[XA_1934] ILO - Modelled Estimates
[XA_1935] ILO - Modelled Estimates
[XA_1936] ILO - Modelled Estimates
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[XA_1939] ILO - Modelled Estimates
[XA_1940] ILO - Modelled Estimates
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[XA_1943] ILO - Modelled Estimates
[XA_1944] ILO - Modelled Estimates
[XA_1946] ILO - Modelled Estimates
[XA_1947] ILO - Modelled Estimates
[XA_1949] ILO - Modelled Estimates
[XA_1950] ILO - Modelled Estimates
[XA_1956] ILO - Modelled Estimates
[XA_1957] ILO - Modelled Estimates
[XA_1960] ILO - Modelled Estimates
[XA_1964] ILO - Modelled Estimates
[XA_1972] ILO - Modelled Estimates
[XA_1976] ILO - Modelled Estimates
[XA_1978] ILO - Modelled Estimates
[XA_1980] ILO - Modelled Estimates
[XA_1982] ILO - Modelled Estimates
[XA_1984] ILO - Modelled Estimates
[XA_1987] ILO - Modelled Estimates
[XA_1988] ILO - Modelled Estimates
[XA_1990] ILO - Modelled Estimates
[XA_1992] ILO - Modelled Estimates
[XA_1996] ILO - Modelled Estimates
[XA_2000] ILO - Modelled Estimates
[XA_2002] ILO - Modelled Estimates
[XA_2004] ILO - Modelled Estimates
[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
[XA_2097] ILO - Modelled Estimates
[XA_2098] ILO - Modelled Estimates
[XA_2100] ILO - Modelled Estimates
[XA_2101] ILO - Modelled Estimates
[XA_2102] ILO - Modelled Estimates
[XA_2104] ILO - Modelled Estimates
[XA_2108] ILO - Modelled Estimates
[XA_2109] ILO - Modelled Estimates
[XA_2110] ILO - Modelled Estimates
[XA_2112] ILO - Modelled Estimates
[XA_2113] ILO - Modelled Estimates
[XA_2114] ILO - Modelled Estimates
[XA_2115] ILO - Modelled Estimates
[XA_2116] ILO - Modelled Estimates
[XA_2117] ILO - Modelled Estimates
[XA_2118] ILO - Modelled Estimates
[XA_2120] ILO - Modelled Estimates
[XA_2121] ILO - Modelled Estimates
[XA_2122] ILO - Modelled Estimates
[XA_2124] ILO - Modelled Estimates
[XA_2125] ILO - Modelled Estimates
[XA_2126] ILO - Modelled Estimates
[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
[XA_2144] ILO - Modelled Estimates
[XA_2145] ILO - Modelled Estimates
[XA_2146] ILO - Modelled Estimates
[XA_2148] ILO - Modelled Estimates
[XA_2149] ILO - Modelled Estimates
[XA_2150] ILO - Modelled Estimates
[XA_2152] ILO - Modelled Estimates
[XA_2153] ILO - Modelled Estimates
[XA_2156] ILO - Modelled Estimates
[XA_2158] ILO - Modelled Estimates
[XA_2160] ILO - Modelled Estimates
[XA_2162] ILO - Modelled Estimates
[XA_2164] ILO - Modelled Estimates
[XA_2165] ILO - Modelled Estimates
[XA_2166] ILO - Modelled Estimates
[XA_2168] ILO - Modelled Estimates
[XA_2170] ILO - Modelled Estimates
[XA_2172] ILO - Modelled Estimates
[XA_2173] ILO - Modelled Estimates
[XA_2174] ILO - Modelled Estimates
[XA_2176] ILO - Modelled Estimates
[XA_2178] ILO - Modelled Estimates
[XA_2180] ILO - Modelled Estimates
[XA_2181] ILO - Modelled Estimates
[XA_2182] ILO - Modelled Estimates
[XA_2184] ILO - Modelled Estimates
[XA_2185] ILO - Modelled Estimates
[XA_2186] ILO - Modelled Estimates
[XA_2188] ILO - Modelled Estimates
[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
[XA_2202] ILO - Modelled Estimates
[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
[XA_8371] ILO - Modelled Estimates
[XA_8372] ILO - Modelled Estimates
[XA_8373] ILO - Modelled Estimates
[XA_8374] ILO - Modelled Estimates
[XA_8375] ILO - Modelled Estimates
[XA_8376] ILO - Modelled Estimates
[XA_8377] ILO - Modelled Estimates
[XA_8378] ILO - Modelled Estimates
[XA_8379] ILO - Modelled Estimates
[XA_8380] ILO - Modelled Estimates
[XA_8381] ILO - Modelled Estimates
[XA_8382] ILO - Modelled Estimates
[XA_8383] ILO - Modelled Estimates
[XA_8384] ILO - Modelled Estimates
[XA_8385] ILO - Modelled Estimates
[XA_8386] ILO - Modelled Estimates
[XA_8387] ILO - Modelled Estimates
[XA_8388] ILO - Modelled Estimates
[XA_8389] ILO - Modelled Estimates
[XA_8390] ILO - Modelled Estimates
[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
[XA_8409] ILO - Modelled Estimates
[XA_8410] ILO - Modelled Estimates
[XA_8411] ILO - Modelled Estimates
[XA_8412] ILO - Modelled Estimates
[XA_8413] ILO - Modelled Estimates
[XA_8414] ILO - Modelled Estimates
[XA_8415] ILO - Modelled Estimates
[XA_8416] ILO - Modelled Estimates
[XA_8417] ILO - Modelled Estimates
[XA_8418] ILO - Modelled Estimates
[XA_8419] ILO - Modelled Estimates
[XA_8420] ILO - Modelled Estimates
[XA_8421] ILO - Modelled Estimates
[XA_8422] ILO - Modelled Estimates
[XA_8423] ILO - Modelled Estimates
[XA_8424] ILO - Modelled Estimates
[XA_8425] ILO - Modelled Estimates
[XA_8426] ILO - Modelled Estimates
[XA_8427] ILO - Modelled Estimates
[XA_8428] ILO - Modelled Estimates
[XA_8429] ILO - Modelled Estimates
[XA_8430] ILO - Modelled Estimates
[XA_8431] ILO - Modelled Estimates
[XA_8432] ILO - Modelled Estimates
[XA_8434] ILO - Modelled Estimates
[XA_8435] ILO - Modelled Estimates
[XA_8436] ILO - Modelled Estimates
[XA_8437] ILO - Modelled Estimates
[XA_8438] ILO - Modelled Estimates
[XA_8439] ILO - Modelled Estimates
[XA_8440] ILO - Modelled Estimates
[XA_8441] ILO - Modelled Estimates
[XA_8442] ILO - Modelled Estimates
[XA_8443] ILO - Modelled Estimates
[XA_8444] ILO - Modelled Estimates
[XA_8445] ILO - Modelled Estimates
[XA_8446] ILO - Modelled Estimates
[XA_8447] ILO - Modelled Estimates
[XA_8448] ILO - Modelled Estimates
[XA_8449] ILO - Modelled Estimates
[XA_8450] ILO - Modelled Estimates
[AGE_YTHADULT_Y15-24] Age (Youth, adults): 15-24
[AGE_YTHADULT_YGE15] Age (Youth, adults): 15+
[AGE_YTHADULT_YGE25] Age (Youth, adults): 25+
[GEO_COV_NAT] Area type: National
[GEO_COV_RUR] Area type: Rural
[GEO_COV_URB] Area type: Urban
[SEX_F] Sex: Female
[SEX_M] Sex: Male
[SEX_T] Sex: Total
[A] Annual
Search filters
Reference area [ref_area] (283)
Source [source] (283)
Classification 1 [classif1] (3)
Classification 2 [classif2] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 7,641 series:
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Female – Annual
- from
- 2005=85.742
- to
- 2019=195.855
- min:
- 84.759
- max:
- 195.855
- avg:
- 122.994
- σ:
- 40.041
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Male – Annual
- from
- 2005=335.01
- to
- 2019=478.977
- min:
- 335.01
- max:
- 478.977
- avg:
- 396.429
- σ:
- 49.581
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Total – Annual
- from
- 2005=420.752
- to
- 2019=674.832
- min:
- 420.752
- max:
- 674.832
- avg:
- 519.423
- σ:
- 89.128
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Female – Annual
- from
- 2005=72.689
- to
- 2019=163.833
- min:
- 72.529
- max:
- 163.833
- avg:
- 105.574
- σ:
- 33.313
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Male – Annual
- from
- 2005=289.042
- to
- 2019=420.477
- min:
- 289.042
- max:
- 420.477
- avg:
- 348.49
- σ:
- 45.703
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Total – Annual
- from
- 2005=361.73
- to
- 2019=584.311
- min:
- 361.73
- max:
- 584.311
- avg:
- 454.063
- σ:
- 78.61
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Female – Annual
- from
- 2005=13.054
- to
- 2019=32.022
- min:
- 11.786
- max:
- 32.022
- avg:
- 17.421
- σ:
- 7.004
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Male – Annual
- from
- 2005=45.968
- to
- 2019=58.499
- min:
- 43.77
- max:
- 58.499
- avg:
- 47.939
- σ:
- 4.453
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Total – Annual
- from
- 2005=59.022
- to
- 2019=90.521
- min:
- 55.563
- max:
- 90.521
- avg:
- 65.36
- σ:
- 11.426
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15+ – Area type: National – Sex: Female – Annual
- from
- 2005=216.345
- to
- 2019=498.764
- min:
- 216.345
- max:
- 498.764
- avg:
- 315.933
- σ:
- 97.933
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] | 85.742 | 85.732 | 84.759 | 84.979 | 86.423 | 89.045 | 96.584 | 106.147 | 119.114 | 133.328 | 148.265 | 163.161 | 178.566 | 187.216 | 195.855 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] | 335.01 | 339.316 | 342.125 | 344.735 | 349.312 | 357.466 | 373.435 | 391.715 | 407.942 | 423.479 | 437.177 | 446 | 453.365 | 466.374 | 478.977 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] | 420.752 | 425.048 | 426.884 | 429.714 | 435.735 | 446.512 | 470.019 | 497.862 | 527.057 | 556.807 | 585.443 | 609.161 | 631.931 | 653.591 | 674.832 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] | 72.689 | 73.021 | 72.529 | 73.054 | 74.637 | 77.252 | 84.175 | 92.927 | 104.767 | 117.808 | 129.117 | 139.931 | 150.611 | 157.255 | 163.833 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] | 289.042 | 293.757 | 297.197 | 300.489 | 305.508 | 313.696 | 328.824 | 346.087 | 361.698 | 376.792 | 387.94 | 394.789 | 400.399 | 410.649 | 420.477 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] | 361.73 | 366.778 | 369.725 | 373.543 | 380.145 | 390.949 | 412.998 | 439.014 | 466.465 | 494.6 | 517.057 | 534.719 | 551.01 | 567.903 | 584.311 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] | 13.054 | 12.712 | 12.231 | 11.925 | 11.786 | 11.793 | 12.409 | 13.22 | 14.347 | 15.519 | 19.148 | 23.23 | 27.955 | 29.962 | 32.022 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] | 45.968 | 45.559 | 44.928 | 44.246 | 43.804 | 43.77 | 44.612 | 45.628 | 46.244 | 46.688 | 49.238 | 51.212 | 52.966 | 55.725 | 58.499 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] | 59.022 | 58.271 | 57.158 | 56.171 | 55.59 | 55.563 | 57.021 | 58.848 | 60.592 | 62.207 | 68.386 | 74.442 | 80.921 | 85.687 | 90.521 |
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] | 216.345 | 220.172 | 222.476 | 226.285 | 232.149 | 239.83 | 255.311 | 274.604 | 304.726 | 337.981 | 373.698 | 411.289 | 451.03 | 474.328 | 498.764 |
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Reference area [ref_area] (283)
Source [source] (283)
Classification 1 [classif1] (3)
Classification 2 [classif2] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 7,641 series:
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Female – Annual
- from
- 2005=85.742
- to
- 2019=195.855
- min:
- 84.759
- max:
- 195.855
- avg:
- 122.994
- σ:
- 40.041
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Male – Annual
- from
- 2005=335.01
- to
- 2019=478.977
- min:
- 335.01
- max:
- 478.977
- avg:
- 396.429
- σ:
- 49.581
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Total – Annual
- from
- 2005=420.752
- to
- 2019=674.832
- min:
- 420.752
- max:
- 674.832
- avg:
- 519.423
- σ:
- 89.128
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Female – Annual
- from
- 2005=72.689
- to
- 2019=163.833
- min:
- 72.529
- max:
- 163.833
- avg:
- 105.574
- σ:
- 33.313
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Male – Annual
- from
- 2005=289.042
- to
- 2019=420.477
- min:
- 289.042
- max:
- 420.477
- avg:
- 348.49
- σ:
- 45.703
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Total – Annual
- from
- 2005=361.73
- to
- 2019=584.311
- min:
- 361.73
- max:
- 584.311
- avg:
- 454.063
- σ:
- 78.61
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Female – Annual
- from
- 2005=13.054
- to
- 2019=32.022
- min:
- 11.786
- max:
- 32.022
- avg:
- 17.421
- σ:
- 7.004
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Male – Annual
- from
- 2005=45.968
- to
- 2019=58.499
- min:
- 43.77
- max:
- 58.499
- avg:
- 47.939
- σ:
- 4.453
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Total – Annual
- from
- 2005=59.022
- to
- 2019=90.521
- min:
- 55.563
- max:
- 90.521
- avg:
- 65.36
- σ:
- 11.426
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15+ – Area type: National – Sex: Female – Annual
- from
- 2005=216.345
- to
- 2019=498.764
- min:
- 216.345
- max:
- 498.764
- avg:
- 315.933
- σ:
- 97.933
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] | 85.742 | 85.732 | 84.759 | 84.979 | 86.423 | 89.045 | 96.584 | 106.147 | 119.114 | 133.328 | 148.265 | 163.161 | 178.566 | 187.216 | 195.855 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] | 335.01 | 339.316 | 342.125 | 344.735 | 349.312 | 357.466 | 373.435 | 391.715 | 407.942 | 423.479 | 437.177 | 446 | 453.365 | 466.374 | 478.977 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] | 420.752 | 425.048 | 426.884 | 429.714 | 435.735 | 446.512 | 470.019 | 497.862 | 527.057 | 556.807 | 585.443 | 609.161 | 631.931 | 653.591 | 674.832 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] | 72.689 | 73.021 | 72.529 | 73.054 | 74.637 | 77.252 | 84.175 | 92.927 | 104.767 | 117.808 | 129.117 | 139.931 | 150.611 | 157.255 | 163.833 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] | 289.042 | 293.757 | 297.197 | 300.489 | 305.508 | 313.696 | 328.824 | 346.087 | 361.698 | 376.792 | 387.94 | 394.789 | 400.399 | 410.649 | 420.477 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] | 361.73 | 366.778 | 369.725 | 373.543 | 380.145 | 390.949 | 412.998 | 439.014 | 466.465 | 494.6 | 517.057 | 534.719 | 551.01 | 567.903 | 584.311 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] | 13.054 | 12.712 | 12.231 | 11.925 | 11.786 | 11.793 | 12.409 | 13.22 | 14.347 | 15.519 | 19.148 | 23.23 | 27.955 | 29.962 | 32.022 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] | 45.968 | 45.559 | 44.928 | 44.246 | 43.804 | 43.77 | 44.612 | 45.628 | 46.244 | 46.688 | 49.238 | 51.212 | 52.966 | 55.725 | 58.499 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] | 59.022 | 58.271 | 57.158 | 56.171 | 55.59 | 55.563 | 57.021 | 58.848 | 60.592 | 62.207 | 68.386 | 74.442 | 80.921 | 85.687 | 90.521 |
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] | 216.345 | 220.172 | 222.476 | 226.285 | 232.149 | 239.83 | 255.311 | 274.604 | 304.726 | 337.981 | 373.698 | 411.289 | 451.03 | 474.328 | 498.764 |
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