[EMP_2EMP_SEX_GEO_STE_NB] Employment by sex, rural / urban areas and status in employment -- ILO modelled estimates, Nov. 2021 (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
[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
[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
[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
[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
[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
[X80] Northern Africa: Low 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
[X94] Arab States: 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
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[XA_15736] ILO - Modelled Estimates
[XA_15966] ILO - Modelled Estimates
[XA_1829] ILO - Modelled Estimates
[XA_1830] ILO - Modelled Estimates
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[XA_1914] ILO - Modelled Estimates
[XA_1916] ILO - Modelled Estimates
[XA_1920] ILO - Modelled Estimates
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[XA_1922] ILO - Modelled Estimates
[XA_1928] ILO - Modelled Estimates
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[XA_1939] ILO - Modelled Estimates
[XA_1940] ILO - Modelled Estimates
[XA_1942] ILO - Modelled Estimates
[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
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[XA_1960] ILO - Modelled Estimates
[XA_1972] ILO - Modelled Estimates
[XA_1976] ILO - Modelled Estimates
[XA_1978] ILO - Modelled Estimates
[XA_1980] ILO - Modelled Estimates
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[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
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[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
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[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_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_8415] ILO - Modelled Estimates
[XA_8416] ILO - Modelled Estimates
[XA_8417] 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
[GEO_COV_NAT] Area type: National
[GEO_COV_RUR] Area type: Rural
[GEO_COV_URB] Area type: Urban
[STE_AGGREGATE_EES] Status in employment (Aggregate): Employees
[STE_AGGREGATE_SLF] Status in employment (Aggregate): Self-employed
[STE_AGGREGATE_TOTAL] Status in employment (Aggregate): Total
[STE_ICSE93_1] Status in employment (ICSE-93): 1. Employees
[STE_ICSE93_2] Status in employment (ICSE-93): 2. Employers
[STE_ICSE93_3] Status in employment (ICSE-93): 3. Own-account workers
[STE_ICSE93_5] Status in employment (ICSE-93): 5. Contributing family workers
[STE_ICSE93_TOTAL] Status in employment (ICSE-93): Total
[SEX_F] Sex: Female
[SEX_M] Sex: Male
[SEX_T] Sex: Total
[A] Annual
Search filters
Reference area [ref_area] (275)
Source [source] (275)
Classification 1 [classif1] (3)
Classification 2 [classif2] (8)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 19,800 series:
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Female – Annual
- from
- 2005=14.664
- to
- 2020=110.468
- min:
- 14.454
- max:
- 164.618
- avg:
- 61.519
- σ:
- 52.999
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Male – Annual
- from
- 2005=448.526
- to
- 2020=1,192.025
- min:
- 448.526
- max:
- 1,385.68
- avg:
- 888.248
- σ:
- 344.572
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Total – Annual
- from
- 2005=463.19
- to
- 2020=1,302.493
- min:
- 463.19
- max:
- 1,550.298
- avg:
- 949.767
- σ:
- 395.322
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Female – Annual
- from
- 2005=848.518
- to
- 2020=1,370.703
- min:
- 848.518
- max:
- 1,804.808
- avg:
- 1,206.229
- σ:
- 322.8
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Male – Annual
- from
- 2005=4,283.364
- to
- 2020=5,640.922
- min:
- 4,283.364
- max:
- 5,862.446
- avg:
- 5,031.988
- σ:
- 484.806
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Total – Annual
- from
- 2005=5,131.882
- to
- 2020=7,011.625
- min:
- 5,131.882
- max:
- 7,667.254
- avg:
- 6,238.217
- σ:
- 797.948
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Female – Annual
- from
- 2005=863.182
- to
- 2020=1,481.17
- min:
- 863.182
- max:
- 1,969.426
- avg:
- 1,267.748
- σ:
- 374.723
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Male – Annual
- from
- 2005=4,731.89
- to
- 2020=6,832.948
- min:
- 4,731.89
- max:
- 7,248.126
- avg:
- 5,920.236
- σ:
- 824.216
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Total – Annual
- from
- 2005=5,595.073
- to
- 2020=8,314.118
- min:
- 5,595.073
- max:
- 9,217.552
- avg:
- 7,187.984
- σ:
- 1,190.812
[AFG.XA_2198.GEO_COV_NAT.STE_ICSE93_1.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (ICSE-93): 1. Employees – Sex: Female – Annual
- from
- 2005=14.664
- to
- 2020=110.468
- min:
- 14.454
- max:
- 164.618
- avg:
- 61.519
- σ:
- 52.999
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_F.A] | 14.664 | 15.39 | 14.454 | 15.579 | 16.082 | 17.496 | 24.013 | 28.131 | 38.291 | 53.855 | 76.32 | 105.416 | 136.321 | 153.199 | 164.618 | 110.468 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_M.A] | 448.526 | 470.425 | 489.011 | 517.067 | 564.309 | 621.593 | 705.37 | 790.283 | 893.356 | 1007.18 | 1128.287 | 1248.621 | 1371.099 | 1379.135 | 1385.68 | 1192.025 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_T.A] | 463.19 | 485.815 | 503.465 | 532.646 | 580.391 | 639.089 | 729.384 | 818.414 | 931.647 | 1061.035 | 1204.607 | 1354.037 | 1507.42 | 1532.334 | 1550.298 | 1302.493 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_F.A] | 848.518 | 864.7 | 875.445 | 890.154 | 907.276 | 936.254 | 994.69 | 1061.734 | 1171.946 | 1286.644 | 1403.553 | 1519.978 | 1642.842 | 1720.42 | 1804.808 | 1370.703 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_M.A] | 4283.364 | 4393.376 | 4467.596 | 4548.741 | 4603.324 | 4688.237 | 4836.15 | 4984.322 | 5122.226 | 5244.347 | 5344.239 | 5401.529 | 5439.229 | 5651.76 | 5862.446 | 5640.922 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_T.A] | 5131.882 | 5258.076 | 5343.041 | 5438.895 | 5510.6 | 5624.491 | 5830.84 | 6046.056 | 6294.172 | 6530.991 | 6747.792 | 6921.506 | 7082.071 | 7372.181 | 7667.254 | 7011.625 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_F.A] | 863.182 | 880.091 | 889.899 | 905.733 | 923.358 | 953.75 | 1018.703 | 1089.864 | 1210.238 | 1340.499 | 1479.873 | 1625.393 | 1779.163 | 1873.619 | 1969.426 | 1481.17 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_M.A] | 4731.89 | 4863.8 | 4956.607 | 5065.808 | 5167.633 | 5309.83 | 5541.52 | 5774.605 | 6015.582 | 6251.528 | 6472.526 | 6650.15 | 6810.329 | 7030.896 | 7248.126 | 6832.948 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_T.A] | 5595.073 | 5743.891 | 5846.507 | 5971.541 | 6090.991 | 6263.581 | 6560.223 | 6864.469 | 7225.82 | 7592.026 | 7952.398 | 8275.543 | 8589.492 | 8904.515 | 9217.552 | 8314.118 |
[AFG.XA_2198.GEO_COV_NAT.STE_ICSE93_1.SEX_F.A] | 14.664 | 15.39 | 14.454 | 15.579 | 16.082 | 17.496 | 24.013 | 28.131 | 38.291 | 53.855 | 76.32 | 105.416 | 136.321 | 153.199 | 164.618 | 110.468 |
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Reference area [ref_area] (275)
Source [source] (275)
Classification 1 [classif1] (3)
Classification 2 [classif2] (8)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 19,800 series:
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Female – Annual
- from
- 2005=14.664
- to
- 2020=110.468
- min:
- 14.454
- max:
- 164.618
- avg:
- 61.519
- σ:
- 52.999
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Male – Annual
- from
- 2005=448.526
- to
- 2020=1,192.025
- min:
- 448.526
- max:
- 1,385.68
- avg:
- 888.248
- σ:
- 344.572
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Employees – Sex: Total – Annual
- from
- 2005=463.19
- to
- 2020=1,302.493
- min:
- 463.19
- max:
- 1,550.298
- avg:
- 949.767
- σ:
- 395.322
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Female – Annual
- from
- 2005=848.518
- to
- 2020=1,370.703
- min:
- 848.518
- max:
- 1,804.808
- avg:
- 1,206.229
- σ:
- 322.8
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Male – Annual
- from
- 2005=4,283.364
- to
- 2020=5,640.922
- min:
- 4,283.364
- max:
- 5,862.446
- avg:
- 5,031.988
- σ:
- 484.806
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Self-employed – Sex: Total – Annual
- from
- 2005=5,131.882
- to
- 2020=7,011.625
- min:
- 5,131.882
- max:
- 7,667.254
- avg:
- 6,238.217
- σ:
- 797.948
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Female – Annual
- from
- 2005=863.182
- to
- 2020=1,481.17
- min:
- 863.182
- max:
- 1,969.426
- avg:
- 1,267.748
- σ:
- 374.723
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Male – Annual
- from
- 2005=4,731.89
- to
- 2020=6,832.948
- min:
- 4,731.89
- max:
- 7,248.126
- avg:
- 5,920.236
- σ:
- 824.216
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (Aggregate): Total – Sex: Total – Annual
- from
- 2005=5,595.073
- to
- 2020=8,314.118
- min:
- 5,595.073
- max:
- 9,217.552
- avg:
- 7,187.984
- σ:
- 1,190.812
[AFG.XA_2198.GEO_COV_NAT.STE_ICSE93_1.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Status in employment (ICSE-93): 1. Employees – Sex: Female – Annual
- from
- 2005=14.664
- to
- 2020=110.468
- min:
- 14.454
- max:
- 164.618
- avg:
- 61.519
- σ:
- 52.999
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_F.A] | 14.664 | 15.39 | 14.454 | 15.579 | 16.082 | 17.496 | 24.013 | 28.131 | 38.291 | 53.855 | 76.32 | 105.416 | 136.321 | 153.199 | 164.618 | 110.468 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_M.A] | 448.526 | 470.425 | 489.011 | 517.067 | 564.309 | 621.593 | 705.37 | 790.283 | 893.356 | 1007.18 | 1128.287 | 1248.621 | 1371.099 | 1379.135 | 1385.68 | 1192.025 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_EES.SEX_T.A] | 463.19 | 485.815 | 503.465 | 532.646 | 580.391 | 639.089 | 729.384 | 818.414 | 931.647 | 1061.035 | 1204.607 | 1354.037 | 1507.42 | 1532.334 | 1550.298 | 1302.493 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_F.A] | 848.518 | 864.7 | 875.445 | 890.154 | 907.276 | 936.254 | 994.69 | 1061.734 | 1171.946 | 1286.644 | 1403.553 | 1519.978 | 1642.842 | 1720.42 | 1804.808 | 1370.703 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_M.A] | 4283.364 | 4393.376 | 4467.596 | 4548.741 | 4603.324 | 4688.237 | 4836.15 | 4984.322 | 5122.226 | 5244.347 | 5344.239 | 5401.529 | 5439.229 | 5651.76 | 5862.446 | 5640.922 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_SLF.SEX_T.A] | 5131.882 | 5258.076 | 5343.041 | 5438.895 | 5510.6 | 5624.491 | 5830.84 | 6046.056 | 6294.172 | 6530.991 | 6747.792 | 6921.506 | 7082.071 | 7372.181 | 7667.254 | 7011.625 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_F.A] | 863.182 | 880.091 | 889.899 | 905.733 | 923.358 | 953.75 | 1018.703 | 1089.864 | 1210.238 | 1340.499 | 1479.873 | 1625.393 | 1779.163 | 1873.619 | 1969.426 | 1481.17 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_M.A] | 4731.89 | 4863.8 | 4956.607 | 5065.808 | 5167.633 | 5309.83 | 5541.52 | 5774.605 | 6015.582 | 6251.528 | 6472.526 | 6650.15 | 6810.329 | 7030.896 | 7248.126 | 6832.948 |
[AFG.XA_2198.GEO_COV_NAT.STE_AGGREGATE_TOTAL.SEX_T.A] | 5595.073 | 5743.891 | 5846.507 | 5971.541 | 6090.991 | 6263.581 | 6560.223 | 6864.469 | 7225.82 | 7592.026 | 7952.398 | 8275.543 | 8589.492 | 8904.515 | 9217.552 | 8314.118 |
[AFG.XA_2198.GEO_COV_NAT.STE_ICSE93_1.SEX_F.A] | 14.664 | 15.39 | 14.454 | 15.579 | 16.082 | 17.496 | 24.013 | 28.131 | 38.291 | 53.855 | 76.32 | 105.416 | 136.321 | 153.199 | 164.618 | 110.468 |
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