Spreadsheet: 9c5d2e41-5339-4892-adc5-0f070c0b74a0
Sheet: Sheet1

Data Source | World Development Indicators | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18 | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Unnamed: 22 | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Unnamed: 30 | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Unnamed: 34 | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Unnamed: 38 | Unnamed: 39 | Unnamed: 40 | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Unnamed: 44 | Unnamed: 45 | Unnamed: 46 | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Unnamed: 50 | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Unnamed: 56 | Unnamed: 57
Country Name | Country Code | Indicator Name | Indicator Code | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014
Aruba | ABW | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Andorra | AND | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Afghanistan | AFG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.3999996185303 | 31.3999996185303 | 31.3999996185303 | 31.3999996185303 | 31.3999996185303 | 31.3999996185303 | 31.3999996185303 | 31.2999992370605 | 31.3999996185303 | 31.2999992370605 | 31.2999992370605 | 31.2999992370605 | 31.2999992370605 | 31.2999992370605 | 25.3999996185303 | 25.3999996185303 | 25.5 | 25.3999996185303 | 25.5 | 25.3999996185303 | 25.3999996185303 | 26.5
Angola | AGO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 14 | 15.5 | 13.5 | 12.5 | 12.1999998092651 | 13.1999998092651 | 13.6000003814697 | 13.3999996185303 | 13.3999996185303 | 13.3999996185303 | 12.5 | 13.3000001907349 | 12.8000001907349 | 12.1000003814697 | 12.1000003814697 | 12 | 12.6000003814697 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.1000003814697
Albania | ALB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.1000003814697 | 28 | 33.2999992370605 | 33.2999992370605 | 33.0999984741211 | 29.2999992370605 | 32.7999992370605 | 28.6000003814697 | 29.1000003814697 | 23.1000003814697 | 27.5 | 22.1000003814697 | 17 | 17.2999992370605 | 17.1000003814697 | 19 | 17.7000007629395 | 25.3999996185303 | 25.6000003814697 | 23.7000007629395 | 23.7999992370605 | 24.2999992370605
Andean Region | ANR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Arab World | ARB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.62865053592574 | 41.27276796438295 | 42.62571170995264 | 42.31554828333049 | 43.17069313038342 | 42.58115719178116 | 41.18439551815745 | 40.73025844076818 | 37.07777619412101 | 41.45952484335515 | 42.18470102174864 | 39.56245199566315 | 39.40419398835747 | 39.9259446978141 | 42.06672384975591 | 40.65171810880398 | 39.27124740720718 | 39.14079150360777 | 40.3531047518334 | 40.86942135637669 | 42.05646173222633 | 42.69701203676861
United Arab Emirates | ARE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8999996185303 | 11.8999996185303 | 11.8000001907349 | 9.19999980926514 | 5.59999990463257 | 21.3999996185303 | 12.6000003814697 | 11.6999998092651 | 10.8000001907349 | 10.6000003814697 | 11 | 11.5 | 12 | 12.3999996185303 | 12.6999998092651 | 13.8000001907349 | 14.8999996185303 | 22.5 | 22.2000007629395 | 22.2999992370605 | 22.5 | 21.5
Argentina | ARG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1999998092651 | 12 | 26.7999992370605 | 24.7999992370605 | 38.2000007629395 | 35 | 30.2999992370605 | 25.3999996185303 | 24.7999992370605 | 32 | 31.2999992370605 | 36.7999992370605 | 39.9000015258789 | 31.8999996185303 | 28.3999996185303 | 32.0999984741211 | 25.6000003814697 | 22.2999992370605 | 24.7000007629395 | 23.8999996185303 | 22.3999996185303 | 20.6000003814697
Armenia | ARM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 47 | 47 | 46.9000015258789 | 53.7999992370605 | 55.2999992370605 | 51.2999992370605 | 46.9000015258789 | 62.9000015258789 | 47.0999984741211 | 58.5999984741211 | 56.2999992370605 | 66 | 68.3000030517578 | 55.7999992370605 | 68.0999984741211 | 54.7000007629395 | 71.6999969482422 | 67.9000015258789 | 47.0999984741211 | 48.5 | 45 | 45.7000007629395
American Samoa | ASM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
[NAME] and [NAME] | ATG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Australia | AUS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.3999996185303 | 17.7999992370605 | 17.5 | 16.3999996185303 | 14.8000001907349 | 14.8000001907349 | 14.6999998092651 | 13.8000001907349 | 12.6000003814697 | 11.3000001907349 | 12.3000001907349 | 11.6999998092651 | 11.3000001907349 | 10.8999996185303 | 10.3999996185303 | 9.5 | 9.19999980926514 | 8.60000038146973 | 10.3999996185303 | 11.1000003814697 | 10.8000001907349 | 10.8999996185303
Austria | AUT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.40000009536743 | 4 | 4.69999980926514 | 5.19999980926514 | 5.59999990463257 | 6.5 | 7.09999990463257 | 6.59999990463257 | 5.69999980926514 | 5.19999980926514 | 5.5 | 5.80000019073486 | 6.5 | 10 | 9.80000019073486 | 9.30000019073486 | 9.10000038146973 | 8.19999980926514 | 9.30000019073486 | 8.69999980926514 | 8.69999980926514 | 8.60000038146973
Azerbaijan | AZE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 10.3999996185303 | 10.3999996185303 | 10.5 | 10.8000001907349 | 13.1999998092651 | 13.6000003814697 | 12.6999998092651 | 9.10000038146973 | 12.6999998092651 | 12.8000001907349 | 13.3000001907349 | 9.89999961853027 | 10.6999998092651 | 10.3000001907349 | 15.1999998092651 | 10 | 9.89999961853027 | 14.6000003814697 | 13.1999998092651 | 14.8999996185303 | 14.1999998092651
Burundi | BDI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1999998092651 | 13.5 | 14.1000003814697 | 13.8999996185303 | 14.1999998092651 | 14.1999998092651 | 13.6000003814697 | 13.1999998092651 | 13.6999998092651 | 13.6999998092651 | 13.5 | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.1999998092651 | 13.1999998092651 | 13.1999998092651 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.5
Belgium | BEL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 15.3000001907349 | 19.7000007629395 | 23.5 | 23.7999992370605 | 24.5 | 25.7000007629395 | 23 | 22.3999996185303 | 18.2000007629395 | 16.7000007629395 | 18.3999996185303 | 21.3999996185303 | 22.5 | 22.1000003814697 | 22.5 | 20.7999992370605 | 18.7000007629395 | 22.5 | 22.3999996185303 | 18.7999992370605 | 18.8999996185303
Benin | [NAME] | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.899999976158142 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 1.10000002384186 | 1.60000002384186 | 1.20000004768372 | 1 | 0.699999988079071 | 0.600000023841858 | 1.70000004768372 | 0.899999976158142 | 1 | 2.59999990463257 | 2.40000009536743 | 2.20000004768372 | 2.09999990463257 | 2.70000004768372 | 2.70000004768372 | 2.20000004768372
[NAME] | BFA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.20000004768372 | 2.90000009536743 | 3.79999995231628 | 3.20000004768372 | 3 | 3 | 2.79999995231628 | 2.90000009536743 | 2.79999995231628 | 3.59999990463257 | 2.79999995231628 | 3.59999990463257 | 3.40000009536743 | 3.40000009536743 | 3.29999995231628 | 2.79999995231628 | 4 | 4 | 4 | 3.90000009536743 | 4 | 3.90000009536743
Bangladesh | BGD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.90000009536743 | 8.10000038146973 | 7.5 | 6.90000009536743 | 6.30000019073486 | 5.09999990463257 | 6.90000009536743 | 5.19999980926514 | 7.80000019073486 | 9 | 8.60000038146973 | 8.10000038146973 | 5.59999990463257 | 7.5 | 11.3000001907349 | 10.3000001907349 | 10.5 | 10.8000001907349 | 12.5 | 8.80000019073486 | 8.80000019073486 | 9.30000019073486
Bulgaria | BGR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.6000003814697 | 26.2999992370605 | 40.7999992370605 | 38.2999992370605 | 30.2000007629395 | 26.2000007629395 | 26.7000007629395 | 23.8999996185303 | 27.8999996185303 | 29.5 | 35.0999984741211 | 31.3999996185303 | 23.8999996185303 | 23.6000003814697 | 20.8999996185303 | 20.1000003814697 | 15.8999996185303 | 11.3000001907349 | 13.8000001907349 | 21.6000003814697 | 23.7000007629395 | 26.1000003814697
Bahrain | BHR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.0999984741211 | 30.1000003814697 | 29.2999992370605 | 28.6000003814697 | 27.7999992370605 | 27.3999996185303 | 29.6000003814697 | 28.6000003814697 | 26.8999996185303 | 28 | 26.2000007629395 | 27.7000007629395 | 29.2000007629395 | 31.6000003814697 | 31.7000007629395 | 31.6000003814697 | 31.6000003814697 | 31.5 | 31.2999992370605 | 31.3999996185303 | 31.2000007629395 | 32.2999992370605
Bahamas, The | BHS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.5 | 30.7999992370605 | 26.7000007629395 | 27.7000007629395 | 23.7999992370605 | 29.8999996185303 | 28.7000007629395 | 21 | 21.2999992370605 | 20 | 16.5 | 21.2000007629395 | 28.3999996185303 | 26.7999992370605 | 23.8999996185303 | 18.3999996185303 | 21.6000003814697 | 22.3999996185303 | 36.5999984741211 | 36.2999992370605 | 35.4000015258789 | 34.5
Bosnia and Herzegovina | BIH | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 52.2999992370605 | 53.7000007629395 | 56.2000007629395 | 60.7000007629395 | 55 | 56.2999992370605 | 60.4000015258789 | 58.5999984741211 | 57 | 55.4000015258789 | 60.7000007629395 | 53.7000007629395 | 56.9000015258789 | 60.5999984741211 | 56.9000015258789 | 65.6999969482422 | 62.7999992370605 | 52.2000007629395 | 52.5999984741211 | 61.5 | 59 | 59.7999992370605
Belarus | BLR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2000007629395 | 21.6000003814697 | 21.7000007629395 | 21.3999996185303 | 21.3999996185303 | 22.7000007629395 | 23.2000007629395 | 23 | 22.7999992370605 | 22.8999996185303 | 22.7999992370605 | 22.8999996185303 | 23 | 23.2000007629395 | 23.1000003814697 | 23.1000003814697 | 23 | 23.1000003814697 | 22.6000003814697 | 23 | 22.8999996185303 | 22.3999996185303
Belize | BLZ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.7999992370605 | 28.1000003814697 | 25.6000003814697 | 30.3999996185303 | 32.2000007629395 | 33 | 37 | 36.9000015258789 | 35.2000007629395 | 28.7000007629395 | 23.7000007629395 | 25.8999996185303 | 26.6000003814697 | 27.2000007629395 | 28.5 | 24.3999996185303 | 22 | 21.2999992370605 | 21.8999996185303 | 21.5 | 21.6000003814697 | 20.7999992370605
Bermuda | BMU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Bolivia | BOL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.80000019073486 | 10.8999996185303 | 9.60000038146973 | 10.6999998092651 | 10.6999998092651 | 10.3999996185303 | 10.1000003814697 | 9.69999980926514 | 8.80000019073486 | 9.80000019073486 | 10.1999998092651 | 11.8999996185303 | 10.3999996185303 | 8.80000019073486 | 11 | 10.8000001907349 | 10.6000003814697 | 5.90000009536743 | 6.90000009536743 | 6.80000019073486 | 6.59999990463257 | 6.59999990463257
Brazil | BRA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.2000007629395 | 15 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 16.1000003814697 | 18.2999992370605 | 22.2000007629395 | 22.7999992370605 | 22.7000007629395 | 22.3999996185303 | 22.7000007629395 | 24.5 | 23.2999992370605 | 24.8999996185303 | 22.8999996185303 | 21.7999992370605 | 20.2999992370605 | 23 | 22.2000007629395 | 19.5 | 19.7000007629395
Barbados | BRB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 36.7000007629395 | 47.4000015258789 | 47.7000007629395 | 50.5 | 43.0999984741211 | 31.8999996185303 | 35.0999984741211 | 29.6000003814697 | 27.1000003814697 | 22.1000003814697 | 25.8999996185303 | 26 | 28.5 | 25.1000003814697 | 23.2999992370605 | 22.3999996185303 | 19.1000003814697 | 20.8999996185303 | 25.7999992370605 | 27.8999996185303 | 29 | 29.7999992370605
[NAME] | BRN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1999998092651 | 12 | 10.8999996185303 | 13.1999998092651 | 12.6999998092651 | 12.1999998092651 | 10.6999998092651 | 10.8000001907349 | 12.8000001907349 | 12.1000003814697 | 11.6999998092651 | 12 | 12.3000001907349 | 10.8999996185303 | 10.8999996185303 | 10.8999996185303 | 10.8999996185303 | 10.6999998092651 | 11.6000003814697 | 12.3000001907349 | 12.3000001907349 | 12.5
Bhutan | BTN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 6.09999990463257 | 6.30000019073486 | 6.5 | 9 | 4.80000019073486 | 5 | 4.30000019073486 | 4.30000019073486 | 5.09999990463257 | 5.69999980926514 | 5.59999990463257 | 5.40000009536743 | 7.5 | 7.30000019073486 | 8.89999961853027 | 11.5 | 12.6000003814697 | 15.1000003814697 | 10.1999998092651 | 10.1999998092651 | 6.40000009536743
Botswana | BWA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 47.2999992370605 | 39.4000015258789 | 41.9000015258789 | 44.5999984741211 | 43.7999992370605 | 40.0999984741211 | 33.5999984741211 | 15.3999996185303 | 45.5999984741211 | 46.2999992370605 | 43.5999984741211 | 39.7999992370605 | 45.0999984741211 | 43.5 | 41.9000015258789 | 33.5999984741211 | 25.2999992370605 | 41.5999984741211 | 23 | 39.5999984741211 | 39.7999992370605 | 37.5
Sub-Saharan Africa (IFC classification) | CAA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Central African Republic | CAF | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 13.8000001907349 | 13.6999998092651 | 13.3000001907349 | 13.1999998092651 | 14.1999998092651 | 13 | 13.3000001907349 | 13.3000001907349 | 13.5 | 13.6000003814697 | 13.6000003814697 | 14.1000003814697 | 13.3999996185303 | 13.3999996185303 | 13.1999998092651 | 13.3000001907349 | 13.3999996185303 | 13.5 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349
Canada | CAN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 14.5 | 14.3999996185303 | 13.6999998092651 | 13.1999998092651 | 13.8000001907349 | 15.3000001907349 | 13.6000003814697 | 12.6999998092651 | 11.3999996185303 | 11.1000003814697 | 11.6999998092651 | 11.8999996185303 | 11.8000001907349 | 10.6000003814697 | 10.3999996185303 | 10 | 10 | 12.3000001907349 | 12.3000001907349 | 12.3999996185303 | 12.6000003814697
East Asia and the Pacific (IFC classification) | CEA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Central Europe and the Baltics | CEB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.48247168153919 | 22.87359231084075 | 26.24898071576293 | 26.7334310520104 | 25.19135511518072 | 24.11908798789143 | 22.16470947425536 | 20.68528743676776 | 24.19052111364568 | 26.76259155234602 | 29.4642977554084 | 31.09619527580727 | 30.7260378681723 | 29.64975371138477 | 27.68909243711887 | 24.59240198910677 | 19.47325837688449 | 17.85982005237741 | 20.94526141676738 | 24.72861300416842 | 26.46398857732168 | 27.24970941507594
Europe and Central Asia (IFC classification) | CEU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Switzerland | CHE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.40000009536743 | 4.30000019073486 | 6.90000009536743 | 6.09999990463257 | 5.30000019073486 | 4.09999990463257 | 3.79999995231628 | 7 | 5.69999980926514 | 4.09999990463257 | 5.5 | 3.90000009536743 | 8.69999980926514 | 7.40000009536743 | 9.10000038146973 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 9 | 8.39999961853027 | 7.80000019073486 | 8.10000038146973
Channel Islands | CHI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Chile | CHL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.7000007629395 | 22.7999992370605 | 21.8999996185303 | 21.2000007629395 | 19.7999992370605 | 18.5 | 18.3999996185303 | 18.1000003814697 | 25 | 24.8999996185303 | 23.2999992370605 | 24.2999992370605 | 24.8999996185303 | 24.7000007629395 | 23.8999996185303 | 21.6000003814697 | 20.7999992370605 | 22.8999996185303 | 24.5 | 21.7000007629395 | 21.1000003814697 | 19.2000007629395
China | CHN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 6.69999980926514 | 6.69999980926514 | 6.90000009536743 | 7.30000019073486 | 7.40000009536743 | 7.5 | 7.80000019073486 | 7.90000009536743 | 7.59999990463257 | 7.69999980926514 | 7.5 | 7.30000019073486 | 7.30000019073486 | 7 | 6.80000019073486 | 6.5 | 7.40000009536743 | 7.5 | 7.30000019073486 | 7.5 | 7.80000019073486
Cote d'Ivoire | CIV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 8.39999961853027 | 7.59999990463257 | 6.80000019073486 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.30000019073486 | 5.5 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.19999980926514 | 5.30000019073486 | 5.5 | 5.19999980926514
Latin America and the Caribbean (IFC classification) | CLA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Middle East and North Africa (IFC classification) | CME | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Cameroon | CMR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 6.69999980926514 | 16 | 15.1999998092651 | 14.3999996185303 | 13.6999998092651 | 11.6999998092651 | 14.6999998092651 | 10.6999998092651 | 10.8999996185303 | 8.69999980926514 | 8.60000038146973 | 7.40000009536743 | 7.90000009536743 | 8.89999961853027 | 9.19999980926514 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743
Congo, Rep. | COG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3999996185303 | 13.3999996185303 | 13.6999998092651 | 14 | 13.3000001907349 | 13.3000001907349 | 13.6000003814697 | 13.3000001907349 | 13.8000001907349 | 13 | 13.3000001907349 | 13.3000001907349 | 13.5 | 13.3000001907349 | 13 | 13.1000003814697 | 13.6999998092651 | 13.1999998092651 | 13 | 13 | 13.3000001907349 | 13.3000001907349
Colombia | COL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.7000007629395 | 26.7999992370605 | 28.3999996185303 | 28.7000007629395 | 28.7999992370605 | 31.7000007629395 | 31.2000007629395 | 33.7999992370605 | 36.5 | 39.2999992370605 | 32.2999992370605 | 32.5 | 27.5 | 28.2000007629395 | 29.2999992370605 | 26.1000003814697 | 30.8999996185303 | 35.2000007629395 | 30.3999996185303 | 29.5 | 27.6000003814697 | 26.2000007629395
Comoros | COM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14 | 13 | 13.3999996185303 | 14 | 13.3000001907349 | 13.6999998092651 | 13.3000001907349 | 13.5 | 13.5 | 13.5 | 13.3000001907349 | 13.3000001907349 | 13.3999996185303 | 13.6000003814697 | 13.3000001907349 | 13.5 | 13.6000003814697 | 13.5 | 13.5 | 13.3999996185303 | 13.3999996185303 | 13.3999996185303
Cabo Verde | CPV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 13.3999996185303 | 13.1000003814697 | 13.1000003814697 | 13 | 13.1000003814697 | 13 | 13 | 12.6999998092651 | 13.1000003814697 | 13.1000003814697 | 13.1999998092651 | 13.1999998092651 | 13.3000001907349 | 13.1000003814697 | 12.8999996185303 | 13 | 13.1000003814697 | 13.3000001907349 | 13.1999998092651 | 13.1999998092651 | 13.1999998092651
Costa Rica | CRI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1999998092651 | 10.1000003814697 | 10.1000003814697 | 11.8999996185303 | 13.6999998092651 | 16.8999996185303 | 16.5 | 17.8999996185303 | 16.6000003814697 | 15 | 17 | 17.7000007629395 | 18.7000007629395 | 18.7999992370605 | 21.7000007629395 | 20.2000007629395 | 15.5 | 13.6999998092651 | 22.3999996185303 | 21.2999992370605 | 22.2000007629395 | 22.2999992370605
South Asia (IFC classification) | CSA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Caribbean small states | CSS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.37285463621757 | 40.85185161118693 | 41.12747153073111 | 40.13617840179894 | 42.81323838918257 | 44.22954172366543 | 41.88262653210835 | 41.01950398887936 | 43.03866431439884 | 38.78300520640911 | 40.3666423864045 | 39.3743672473326 | 32.83793490518601 | 34.56109384509389 | 32.71226048073677 | 30.4459987650664 | 28.40526556674212 | 30.05515543462042 | 31.29781938086882 | 34.52666042630104 | 34.77694293594666 | 36.84988316465528
Cuba | CUB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 8.19999980926514 | 8.80000019073486 | 7.40000009536743 | 18.2000007629395 | 16.8999996185303 | 16 | 14.1999998092651 | 14.6000003814697 | 12.6000003814697 | 9.60000038146973 | 7.69999980926514 | 5.40000009536743 | 5.09999990463257 | 4.40000009536743 | 3.79999995231628 | 3.5 | 3.90000009536743 | 3.90000009536743 | 5.69999980926514 | 5.59999990463257 | 5.80000019073486
[NAME] | CUW | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Cayman Islands | CYM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Cyprus | CYP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.6000003814697 | 4.90000009536743 | 19.8999996185303 | 7.90000009536743 | 8.39999961853027 | 9.10000038146973 | 7.09999990463257 | 13.1000003814697 | 13.3999996185303 | 13.3000001907349 | 10.1000003814697 | 7 | 8.30000019073486 | 9.10000038146973 | 13.6999998092651 | 10.6999998092651 | 8.89999961853027 | 8.89999961853027 | 13.3999996185303 | 16.5 | 20.2999992370605 | 25.6000003814697
Czech Republic | CZE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 7.40000009536743 | 10.5 | 9.80000019073486 | 8.69999980926514 | 8.30000019073486 | 10.3000001907349 | 14.8000001907349 | 18.6000003814697 | 17.2999992370605 | 17.2000007629395 | 17.2000007629395 | 18.7999992370605 | 19.5 | 19.1000003814697 | 18.7000007629395 | 11 | 9.89999961853027 | 16.7000007629395 | 18.5 | 17.8999996185303 | 18.8999996185303
Germany | DEU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 6.80000019073486 | 7.80000019073486 | 8.30000019073486 | 8 | 9 | 9.60000038146973 | 8.19999980926514 | 7.90000009536743 | 7.5 | 7.09999990463257 | 8 | 8.60000038146973 | 10.8000001907349 | 14 | 12.6000003814697 | 11.1000003814697 | 10 | 9.80000019073486 | 8.80000019073486 | 7.80000019073486 | 7.40000009536743
Djibouti | DJI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Dominica | DMA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Denmark | DNK | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 12.5 | 14.6999998092651 | 10.1999998092651 | 12.3000001907349 | 12.5 | 9.89999961853027 | 7.59999990463257 | 10.3999996185303 | 7 | 9.19999980926514 | 7.5 | 9.19999980926514 | 7.40000009536743 | 8.60000038146973 | 7.5 | 7.40000009536743 | 8.60000038146973 | 10.3000001907349 | 11.6999998092651 | 12.6999998092651 | 13.5
Dominican Republic | DOM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 50.2999992370605 | 58.5 | 58.2999992370605 | 42.7000007629395 | 41.7999992370605 | 45.2000007629395 | 44.4000015258789 | 41.5 | 39.4000015258789 | 34.5 | 31.8999996185303 | 26.1000003814697 | 45.7000007629395 | 50.2999992370605 | 49.0999984741211 | 44.7000007629395 | 44.5 | 40.0999984741211 | 42 | 35.0999984741211 | 35.7999992370605 | 36
Algeria | DZA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 53.5 | 59.2000007629395 | 59.2000007629395 | 61.7000007629395 | 68.3000030517578 | 68.5999984741211 | 63.7999992370605 | 65.1999969482422 | 63.7999992370605 | 73.8000030517578 | 66.8000030517578 | 62.7999992370605 | 57 | 43.5999984741211 | 44.5 | 34.9000015258789 | 40.2999992370605 | 35.2000007629395 | 35.0999984741211 | 38.2999992370605 | 38.2000007629395 | 36
East Asia & Pacific (developing only) | EAP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.228264318951972 | 7.442812926586908 | 8.408015370924092 | 8.731816744079907 | 8.464306223386696 | 8.750462989617619 | 8.999911620744385 | 10.01111087448484 | 10.23294013799907 | 9.983700310230404 | 11.09197870349805 | 11.33646970187486 | 11.12961345621343 | 11.45188672670387 | 11.40044922636742 | 10.8906622065225 | 9.76373674156095 | 10.18819036581779 | 10.05801602961847 | 10.04439143682243 | 9.929005430400197 | 10.30066502627655
East Asia & Pacific (all income levels) | EAS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.930285056008701 | 7.321207050928439 | 8.267776101951245 | 8.528737091724073 | 8.301552220950796 | 8.581604784823366 | 8.828877180046556 | 9.963108818417826 | 10.19110645269187 | 9.876000251078276 | 10.93484615944388 | 11.15240111745941 | 10.99451486590271 | 11.27905783484331 | 11.18689158164869 | 10.7014773351823 | 9.610818602886923 | 9.999224476961137 | 9.98298479547078 | 9.97632323394368 | 9.809396523119572 | 10.16377897743696
Europe & Central Asia (developing only) | ECA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.68457310804569 | 19.18573201226085 | 21.07282137292874 | 19.22904475504001 | 18.48040821999383 | 18.94785912328768 | 20.02944961143067 | 20.06911296069596 | 20.10101782652672 | 19.45515994448161 | 19.96282921696584 | 21.11340160042576 | 21.11038446624359 | 21.30180722128219 | 21.02074657349688 | 21.06798000377184 | 20.5025694009212 | 20.23467906408365 | 22.50970722300204 | 22.12332707542346 | 21.90203826878346 | 21.36510834333792
Europe & Central Asia (all income levels) | ECS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.19316098545792 | 18.97465160703105 | 21.28008205181642 | 21.71500456368836 | 21.93095440335439 | 22.11972284320527 | 22.85373941752585 | 22.61724186956912 | 22.35480409238177 | 20.81136594252634 | 19.8898781890339 | 20.03499666032957 | 20.46562964094052 | 20.56686994761582 | 20.06916713359992 | 19.4904095512244 | 17.82161773345108 | 17.65108131890691 | 20.69292066897188 | 21.01523712494054 | 21.14610674896008 | 21.81969038910411
Ecuador | ECU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.7000007629395 | 17.2000007629395 | 14.3000001907349 | 19.7999992370605 | 14.3999996185303 | 15.6999998092651 | 18.3999996185303 | 13.3999996185303 | 16.2000007629395 | 19.5 | 21.7999992370605 | 22.3999996185303 | 25.1000003814697 | 18.1000003814697 | 18.1000003814697 | 17.2000007629395 | 13.8999996185303 | 16.7999992370605 | 18.5 | 14.1999998092651 | 12 | 12.8999996185303
Egypt, Arab Rep. | EGY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 50.2999992370605 | 46.7000007629395 | 57.2000007629395 | 57.5999984741211 | 59 | 47.7000007629395 | 45 | 44.2000007629395 | 37.4000015258789 | 45.7000007629395 | 51.7000007629395 | 40.5 | 45.0999984741211 | 50 | 60.5999984741211 | 56.0999984741211 | 48.2000007629395 | 50.7999992370605 | 56.7000007629395 | 54.5999984741211 | 65 | 64.9000015258789
Euro area | EMU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.66476974201079 | 22.45431418488148 | 25.60110865557359 | 27.04815069900349 | 27.51321445772821 | 27.97497411836301 | 27.83609700480537 | 25.58882991994484 | 24.37091181653328 | 21.56247254538576 | 19.26538748116132 | 19.58340741214332 | 19.41949225110757 | 19.92893347669002 | 20.14766875344614 | 19.27283441169827 | 17.54362678144017 | 17.50699601539541 | 21.09453022767711 | 22.33782168279277 | 23.40775493544204 | 26.01059279069387
Eritrea | ERI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 13.5 | 12.6999998092651 | 12.1000003814697 | 13.3999996185303 | 12.8999996185303 | 13 | 13.3999996185303 | 13.6000003814697 | 14.5 | 13 | 13.3999996185303 | 13.8000001907349 | 13.5 | 13.3999996185303 | 13.6999998092651 | 13.5 | 14.3000001907349 | 13.3000001907349 | 13.3999996185303 | 13 | 13.1000003814697
Spain | ESP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 39 | 41.7000007629395 | 48.7999992370605 | 51.5999984741211 | 50.7999992370605 | 50.7000007629395 | 47.7000007629395 | 44.5999984741211 | 38.2999992370605 | 34.0999984741211 | 27.7999992370605 | 28.2000007629395 | 28 | 27.2999992370605 | 24.2000007629395 | 22.3999996185303 | 22.7000007629395 | 26.7000007629395 | 37.0999984741211 | 40.5999984741211 | 45.2999992370605 | 52.9000015258789
Estonia | EST | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 6.5 | 11.5 | 13.3000001907349 | 13.6000003814697 | 14.1999998092651 | 15.1999998092651 | 11.8000001907349 | 21.7000007629395 | 21.8999996185303 | 33.7000007629395 | 21.8999996185303 | 30.2999992370605 | 23.7000007629395 | 14.6999998092651 | 14.6999998092651 | 7 | 11.3999996185303 | 22.1000003814697 | 30.2000007629395 | 20.7999992370605 | 18
Ethiopia | ETH | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16 | 16.1000003814697 | 14.3000001907349 | 15.1000003814697 | 17.5 | 17.5 | 17.5 | 17.5 | 17.5 | 16.7999992370605 | 16.2000007629395 | 14.8000001907349 | 13.6000003814697 | 12.3999996185303 | 11.3999996185303 | 11.5 | 11.5 | 11.5 | 11.6000003814697 | 11.5 | 11.5 | 11.5
European Union | EUU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.45576708553774 | 21.18580985292024 | 24.29794340070795 | 25.17651397107861 | 25.14330590351183 | 25.10803186010124 | 24.41052883527251 | 22.43207642647898 | 22.40492574010284 | 21.21616114127939 | 20.25271923718011 | 20.8617974516469 | 20.75976185202865 | 20.85150019493108 | 20.74421817103444 | 19.56967770070248 | 17.42162153163322 | 16.92990092804511 | 20.2319417349401 | 21.94914991447522 | 23.08881894408832 | 24.93980315669634
Fragile and conflict affected situations | FCS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.60778785112043 | 22.54960604721099 | 21.39725704919105 | 21.81647395824336 | 21.67602183701464 | 22.43499406571576 | 22.44480791828294 | 22.26251961753517 | 21.34874791958264 | 22.35802084602851 | 22.64676226656195 | 22.42842323834986 | 21.3355008203703 | 22.33476276354594 | 22.03922252256175 | 22.43955660066849 | 22.38672385309681 | 22.00684077363675 | 21.67273755573292 | 22.31091913833408 | 22.05686331434227 | 22.11529151980194
Finland | FIN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1999998092651 | 22.7000007629395 | 30.3999996185303 | 30.7000007629395 | 28.7000007629395 | 26 | 25 | 24.5 | 22.2000007629395 | 21.7999992370605 | 20.2000007629395 | 20.5 | 21.5 | 19.2999992370605 | 19.3999996185303 | 18.3999996185303 | 16.7999992370605 | 16.2000007629395 | 18.7999992370605 | 18.8999996185303 | 18.3999996185303 | 17.8999996185303
Fiji | FJI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.1000003814697 | 15.6999998092651 | 17.2000007629395 | 16.6000003814697 | 15.6999998092651 | 16.3999996185303 | 19.2000007629395 | 24.1000003814697 | 23 | 22 | 17.7999992370605 | 16.7999992370605 | 25.2000007629395 | 14.1000003814697 | 13.8999996185303 | 19.7999992370605 | 26.8999996185303 | 27.6000003814697 | 26.7000007629395 | 26.6000003814697 | 26.3999996185303 | 26.1000003814697
France | FRA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2999992370605 | 24.6000003814697 | 27.2999992370605 | 30 | 30.2999992370605 | 30 | 30.7999992370605 | 28.2999992370605 | 28.1000003814697 | 22.5 | 20.5 | 20.7999992370605 | 18.7999992370605 | 20.2999992370605 | 21.7999992370605 | 23 | 19.8999996185303 | 18.5 | 22.1000003814697 | 23.5 | 23 | 23.6000003814697
Faeroe Islands | FRO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Micronesia, Fed. [NAME]. | FSM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Gabon | GAB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.2000007629395 | 41.5999984741211 | 41 | 41.2999992370605 | 41.5 | 41.7999992370605 | 42 | 42 | 41.9000015258789 | 41.9000015258789 | 41.9000015258789 | 41.7999992370605 | 41.7999992370605 | 41.7999992370605 | 41.7000007629395 | 41.7000007629395 | 41.7000007629395 | 42 | 42.2999992370605 | 40.5 | 40.4000015258789 | 42.2000007629395
United Kingdom | GBR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3999996185303 | 11.8999996185303 | 13.6000003814697 | 12.8999996185303 | 12.6000003814697 | 11.3999996185303 | 11.3999996185303 | 10.6999998092651 | 10.3000001907349 | 10.3000001907349 | 8.80000019073486 | 9 | 9.69999980926514 | 10.1000003814697 | 10.8000001907349 | 12.1000003814697 | 12.8000001907349 | 12.3000001907349 | 15.8999996185303 | 17.2000007629395 | 17.8999996185303 | 18.2000007629395
Georgia | GEO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.2000007629395 | 27 | 28.3999996185303 | 30.2000007629395 | 32 | 30.5 | 30.6000003814697 | 30.3999996185303 | 24.3999996185303 | 20.2999992370605 | 19.7000007629395 | 26.8999996185303 | 31.2999992370605 | 32.5999984741211 | 30.2999992370605 | 31.2000007629395 | 36.5 | 41.0999984741211 | 43.7000007629395 | 41.4000015258789 | 41.2000007629395 | 40
Ghana | GHA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.7000007629395 | 16.7999992370605 | 18.1000003814697 | 11.5 | 6.90000009536743 | 17.5 | 17.5 | 17.6000003814697 | 19.5 | 16.5 | 18.1000003814697 | 18.8999996185303 | 18.7999992370605 | 18.7000007629395 | 8.89999961853027 | 7.09999990463257 | 7 | 6.90000009536743 | 7.19999980926514 | 6.90000009536743 | 6.30000019073486 | 6.80000019073486
Guinea | GIN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.09999990463257
Gambia, The | GMB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3999996185303 | 13.3000001907349 | 13.1000003814697 | 13.3000001907349 | 13.8999996185303 | 13.1000003814697 | 13.1999998092651 | 13.1000003814697 | 13.1000003814697 | 13.1999998092651 | 13.1999998092651 | 13.8000001907349 | 13.1000003814697 | 13.1000003814697 | 13.6999998092651 | 13.5 | 13.3000001907349 | 13.1999998092651 | 13.1000003814697 | 13.1000003814697 | 13.8999996185303 | 13.3000001907349
Guinea-Bissau | GNB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1999998092651 | 13.5 | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.1000003814697 | 15.8000001907349 | 13 | 13 | 13.3999996185303 | 13.6999998092651 | 13.6000003814697 | 13.3999996185303 | 13.3000001907349 | 13.3999996185303 | 13.3999996185303 | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.1999998092651 | 13.6000003814697
Equatorial Guinea | GNQ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 11.1999998092651 | 12.8000001907349 | 12.3999996185303 | 12.3000001907349 | 9.30000019073486 | 5.69999980926514 | 11.8999996185303 | 11.8000001907349 | 12.3000001907349 | 9.5 | 12.1999998092651 | 12.6000003814697 | 11 | 12.8999996185303 | 13.5 | 12.3000001907349 | 12.6000003814697 | 13.8999996185303 | 13.8000001907349 | 13.3000001907349 | 13.3999996185303
Greece | GRC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.7000007629395 | 33.4000015258789 | 38.2999992370605 | 36.2000007629395 | 36.7999992370605 | 40.2999992370605 | 39.5999984741211 | 38.7999992370605 | 40.5 | 37.2000007629395 | 35.5999984741211 | 34.9000015258789 | 36.2999992370605 | 36 | 34.5 | 34.4000015258789 | 31.7999992370605 | 28.6000003814697 | 33.7000007629395 | 40.4000015258789 | 51.2000007629395 | 62.9000015258789
Grenada | GRD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Greenland | GRL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Guatemala | GTM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 8.19999980926514 | 5.19999980926514 | 4.90000009536743 | 8.80000019073486 | 6.80000019073486 | 9.60000038146973 | 8.30000019073486 | 4 | 3 | 2.79999995231628 | 6.59999990463257 | 6 | 6.69999980926514 | 6.30000019073486 | 5.90000009536743 | 5.30000019073486 | 5.90000009536743 | 6.59999990463257 | 7.5 | 8.80000019073486 | 8.80000019073486
Guam | GUM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Guyana | GUY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 48.0999984741211 | 39.0999984741211 | 44.7000007629395 | 50.5 | 56.2999992370605 | 52 | 47.5999984741211 | 45.7999992370605 | 47.2999992370605 | 38.7999992370605 | 52.7000007629395 | 65.6999969482422 | 48.5999984741211 | 47.5 | 44.9000015258789 | 52.4000015258789 | 43.2000007629395 | 41.2999992370605 | 40.9000015258789 | 45.7999992370605 | 45 | 46.9000015258789
High income | HIC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.56320563395233 | 15.90255804136022 | 17.13223508896169 | 17.33958976002774 | 17.6837267265659 | 18.0937027288674 | 18.35843421974098 | 18.39598482687964 | 17.63151775568664 | 16.33415196707009 | 15.70692950161049 | 16.14448775001147 | 16.99251257359652 | 16.91951014319805 | 15.86195640973516 | 15.55257384442094 | 14.1036922641952 | 14.64957386610294 | 17.7327837882093 | 18.26226432912772 | 17.80931491079824 | 18.52057635361007
Hong Kong SAR, China | HKG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.59999990463257 | 4 | 4.09999990463257 | 3.59999990463257 | 5.90000009536743 | 5.59999990463257 | 4.5 | 9.10000038146973 | 12.6999998092651 | 10.3999996185303 | 9.30000019073486 | 11.8999996185303 | 11.6999998092651 | 9.10000038146973 | 7.90000009536743 | 8.10000038146973 | 7.19999980926514 | 7 | 10.1000003814697 | 10.3000001907349 | 8 | 7.40000009536743
Honduras | HND | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6999998092651 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 9.89999961853027 | 7.40000009536743 | 9 | 8 | 7.90000009536743 | 8.19999980926514 | 8.39999961853027 | 12.1000003814697 | 15.8000001907349 | 11.5 | 7.40000009536743 | 6.90000009536743 | 7.40000009536743 | 7.90000009536743 | 11.5 | 11.5 | 11.5
Heavily indebted poor countries (HIPC) | HPC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.69113310831803 | 13.85885305446523 | 13.6743694524708 | 13.49984392469806 | 13.41673128011024 | 14.1133691350416 | 14.10103546793431 | 13.90338182588802 | 13.68479903338137 | 13.54845332123526 | 13.67948772261042 | 13.29490315090891 | 13.24650877190482 | 12.73076220534488 | 11.69614216547705 | 11.92718242736244 | 11.55435323649857 | 11.69386278411558 | 11.98889168881865 | 12.02958883632895 | 12.07390673577611 | 12.08989549552554
Croatia | HRV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 38.7000007629395 | 27.7999992370605 | 28.5 | 28.5 | 28.2000007629395 | 27.2000007629395 | 26.8999996185303 | 29.2000007629395 | 33.2000007629395 | 37.4000015258789 | 43.9000015258789 | 38.9000015258789 | 38.5 | 37.2000007629395 | 35.2000007629395 | 31.2999992370605 | 28.5 | 27.3999996185303 | 28.8999996185303 | 35.9000015258789 | 37.5999984741211 | 45.4000015258789
Haiti | HTI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.6000003814697 | 32.2000007629395 | 32.5999984741211 | 33.7000007629395 | 30.2000007629395 | 31.1000003814697 | 31.3999996185303 | 31.3999996185303 | 20.5 | 20.7999992370605 | 21.1000003814697 | 21 | 20.8999996185303 | 21.6000003814697 | 20.7000007629395 | 20.6000003814697 | 20.3999996185303 | 20.7999992370605 | 20.5 | 21.8999996185303 | 20 | 20.6000003814697
Hungary | HUN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.2999992370605 | 14.8999996185303 | 18.1000003814697 | 16.3999996185303 | 15.5 | 16.3999996185303 | 14.5 | 11.6000003814697 | 11.3999996185303 | 11.1000003814697 | 9.89999961853027 | 11.8000001907349 | 12.8000001907349 | 14.3999996185303 | 19.1000003814697 | 19.7999992370605 | 18.6000003814697 | 20.7999992370605 | 24.2000007629395 | 24.7999992370605 | 24.6000003814697 | 27.2000007629395
Indonesia | IDN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.7999992370605 | 8.60000038146973 | 15.1999998092651 | 17.3999996185303 | 13.8000001907349 | 15.8999996185303 | 16.2000007629395 | 19.2999992370605 | 19.2999992370605 | 18.3999996185303 | 24.7999992370605 | 29 | 29.7999992370605 | 32.5 | 38 | 34.9000015258789 | 27.7000007629395 | 25.7000007629395 | 23.2999992370605 | 25.3999996185303 | 23.7000007629395 | 24.2000007629395
Isle of Man | IMN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
India | IND | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.89999961853027 | 9 | 9.60000038146973 | 8 | 8.89999961853027 | 8.80000019073486 | 10.3000001907349 | 8.39999961853027 | 8.69999980926514 | 10.1000003814697 | 9 | 10.1999998092651 | 9.5 | 9 | 10.3999996185303 | 10.3999996185303 | 9.19999980926514 | 10.3000001907349 | 9.80000019073486 | 11.3999996185303 | 11.3999996185303 | 10.6000003814697
Not classified | INX | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Ireland | IRL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2000007629395 | 20.8999996185303 | 22.7999992370605 | 20.6000003814697 | 17.2999992370605 | 17 | 14.8999996185303 | 11 | 8.39999961853027 | 6.90000009536743 | 5.80000019073486 | 6.59999990463257 | 7.09999990463257 | 7.5 | 8 | 8.19999980926514 | 8.10000038146973 | 9.89999961853027 | 17.2999992370605 | 21.5 | 22.7999992370605 | 24
Iran, Islamic Rep. | IRN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.8999996185303 | 32.5999984741211 | 32.2000007629395 | 31.8999996185303 | 31.6000003814697 | 31.2999992370605 | 32.4000015258789 | 31.7000007629395 | 30.7999992370605 | 35.2999992370605 | 32.2999992370605 | 34.4000015258789 | 32.5999984741211 | 27.5 | 33.5999984741211 | 32.5999984741211 | 29.7999992370605 | 33.7000007629395 | 32.0999984741211 | 40.7999992370605 | 40.5999984741211 | 40.5
Iraq | IRQ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 64.6999969482422 | 63.7000007629395 | 55.5 | 58.5999984741211 | 61.7000007629395 | 64.6999969482422 | 64.5999984741211 | 64.5999984741211 | 61.5 | 62.5 | 63.5 | 63.5999984741211 | 54.9000015258789 | 67.3000030517578 | 63.5999984741211 | 62.0999984741211 | 60.0999984741211 | 54.7000007629395 | 54.7000007629395 | 54.7000007629395 | 54.7999992370605 | 53.7000007629395
Iceland | ISL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.90000009536743 | 10.8999996185303 | 9.69999980926514 | 10 | 8.60000038146973 | 7.59999990463257 | 7 | 5.59999990463257 | 4.40000009536743 | 3.59999990463257 | 4.30000019073486 | 4.40000009536743 | 6.90000009536743 | 6.69999980926514 | 5.80000019073486 | 7.30000019073486 | 6.09999990463257 | 7.30000019073486 | 11.8999996185303 | 13.8999996185303 | 10.6999998092651 | 12.3000001907349
Israel | ISR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.8999996185303 | 25.2999992370605 | 23.2000007629395 | 19.1000003814697 | 17.1000003814697 | 15.1000003814697 | 16 | 17.5 | 17.3999996185303 | 16.7999992370605 | 18.2000007629395 | 20.7000007629395 | 22.2000007629395 | 21.2000007629395 | 18.6000003814697 | 19.1000003814697 | 17.1000003814697 | 13.3999996185303 | 13.6000003814697 | 13 | 11.3999996185303 | 12.8000001907349
Italy | ITA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.7999992370605 | 32.5 | 34.5999984741211 | 35.4000015258789 | 38 | 39.5 | 40.5 | 38.4000015258789 | 38.2999992370605 | 35.2999992370605 | 31.5 | 31.6000003814697 | 31.1000003814697 | 29.1000003814697 | 27.5 | 25.2999992370605 | 23.3999996185303 | 24.7000007629395 | 28.7000007629395 | 29.3999996185303 | 32.0999984741211 | 37.5
Jamaica | JAM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 44.7000007629395 | 40.5 | 41.4000015258789 | 39.4000015258789 | 46.7999992370605 | 49.7999992370605 | 47 | 47.5999984741211 | 49.7000007629395 | 45.5 | 47.5 | 40.9000015258789 | 29.1000003814697 | 36.7999992370605 | 33.0999984741211 | 29.2000007629395 | 28.6000003814697 | 33.2000007629395 | 32.5999984741211 | 37.0999984741211 | 37.4000015258789 | 41.5999984741211
Jordan | JOR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 44.4000015258789 | 58.7000007629395 | 71.8000030517578 | 67.1999969482422 | 53.7999992370605 | 50.7000007629395 | 48.5 | 33.9000015258789 | 48.2999992370605 | 41.4000015258789 | 46.2999992370605 | 46.5 | 48.7000007629395 | 34.2000007629395 | 52.0999984741211 | 47.2999992370605 | 49.2000007629395 | 50.5999984741211 | 48.0999984741211 | 49.7000007629395 | 48.7999992370605 | 51.0999984741211
Japan | JPN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.09999990463257 | 5.30000019073486 | 5.30000019073486 | 6.09999990463257 | 6.69999980926514 | 6.30000019073486 | 7.30000019073486 | 8.19999980926514 | 7.90000009536743 | 8.69999980926514 | 8.69999980926514 | 8.60000038146973 | 8.30000019073486 | 7.40000009536743 | 7.19999980926514 | 7.09999990463257 | 6.5 | 8 | 8 | 7.09999990463257 | 7.09999990463257
Kazakhstan | KAZ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.5 | 15.8000001907349 | 15.3000001907349 | 10.3000001907349 | 15.1000003814697 | 17.8999996185303 | 17.7999992370605 | 18 | 18.5 | 17.5 | 14.1999998092651 | 18.5 | 16.2000007629395 | 15.5 | 11.1000003814697 | 10.6999998092651 | 10 | 8.19999980926514 | 8.30000019073486 | 6.5 | 5.80000019073486 | 4.69999980926514
Kenya | [NAME] | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.6000003814697 | 17.7999992370605 | 17.7000007629395 | 17.5 | 17.2999992370605 | 17.2999992370605 | 17.7000007629395 | 17.3999996185303 | 17.5 | 17.6000003814697 | 17.2999992370605 | 17.6000003814697 | 17.3999996185303 | 17.2000007629395 | 17.1000003814697 | 17.1000003814697 | 17 | 17.5 | 17.3999996185303 | 17.1000003814697 | 17.2000007629395 | 17.2999992370605
Kyrgyz Republic | KGZ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.7000007629395 | 16 | 16.3999996185303 | 16 | 16.7999992370605 | 18.1000003814697 | 17.2000007629395 | 19.6000003814697 | 16.7000007629395 | 15.3000001907349 | 16 | 21 | 18.2999992370605 | 17.7000007629395 | 16.2000007629395 | 16.2000007629395 | 16.7000007629395 | 17.3999996185303 | 19.2999992370605 | 20.1000003814697 | 20.2999992370605 | 19.1000003814697
Cambodia | KHM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 4.80000019073486 | 4.90000009536743 | 3.79999995231628 | 4.09999990463257 | 4.5 | 4.90000009536743 | 5.30000019073486 | 5.80000019073486 | 6.30000019073486 | 4.09999990463257 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4 | 4.09999990463257 | 4 | 4.19999980926514 | 4.5 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257
Kiribati | KIR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
St. Kitts and Nevis | KNA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Korea, Rep. | KOR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6.19999980926514 | 6.59999990463257 | 5.69999980926514 | 5 | 4.5 | 6.19999980926514 | 12.3000001907349 | 11.3000001907349 | 8.69999980926514 | 8.39999961853027 | 7.19999980926514 | 8.80000019073486 | 9.10000038146973 | 8.69999980926514 | 8.69999980926514 | 6.90000009536743 | 7.69999980926514 | 8.30000019073486 | 8.80000019073486 | 7.90000009536743 | 8.39999961853027
Kosovo | KSV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Kuwait | KWT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.59999990463257 | 4.40000009536743 | 3.20000004768372 | 2.90000009536743 | 2.5 | 2.90000009536743 | 2.90000009536743 | 2.90000009536743 | 2.79999995231628 | 3.20000004768372 | 3.20000004768372 | 4.5 | 5.40000009536743 | 7.19999980926514 | 10.8000001907349 | 6.40000009536743 | 6.59999990463257 | 6.30000019073486 | 6.59999990463257 | 6.59999990463257 | 6.59999990463257 | 6.09999990463257
Latin America & Caribbean (developing only) | LAC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.94390893680293 | 14.36190208871019 | 15.13979382099454 | 15.12758221876362 | 18.05720106621025 | 18.81345028091646 | 18.37527442936968 | 19.15460980900658 | 18.97480893134576 | 19.54146744655856 | 18.80441411523688 | 20.03300649792967 | 21.04690986098617 | 20.32784995975878 | 19.52365153938382 | 18.36182202637818 | 17.45251885055736 | 17.107840411729 | 18.56590348931705 | 18.08183615821887 | 16.92238102151694 | 16.6396432642243
Lao PDR | LAO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.79999995231628 | 4.19999980926514 | 4.30000019073486 | 4.40000009536743 | 4.5 | 3.40000009536743 | 3.5 | 3.5 | 3.40000009536743 | 3.40000009536743 | 3.29999995231628 | 3.29999995231628 | 3.79999995231628 | 4.40000009536743 | 2.5 | 2.5 | 2.5 | 2.5 | 2.5 | 2.5 | 2.5 | 2.5
Lebanon | LBN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.6000003814697 | 20.1000003814697 | 19.7999992370605 | 21.2000007629395 | 19.8999996185303 | 20.1000003814697 | 20.1000003814697 | 20.2000007629395 | 20.2000007629395 | 20.2999992370605 | 20.2000007629395 | 20.2000007629395 | 20.3999996185303 | 19.7999992370605 | 20.1000003814697 | 20.5 | 22.2999992370605 | 22.2999992370605 | 22.2999992370605 | 22.2000007629395 | 22 | 21.7999992370605
Liberia | LBR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 4.90000009536743 | 4.80000019073486 | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 5.80000019073486 | 4.69999980926514 | 6.09999990463257 | 4.09999990463257 | 3.70000004768372 | 4.40000009536743 | 5.09999990463257 | 6.69999980926514 | 6.59999990463257 | 5.5
Libya | LBY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.1000003814697 | 30.2000007629395 | 30.2000007629395 | 30.5 | 29.7999992370605 | 30.5 | 30.3999996185303 | 30.3999996185303 | 30.3999996185303 | 30.6000003814697 | 30.2999992370605 | 30.2999992370605 | 31 | 30.6000003814697 | 31 | 30.7000007629395 | 30.7000007629395 | 30.5 | 30.2999992370605 | 30.6000003814697 | 27.3999996185303 | 34.4000015258789
St. Lucia | LCA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Latin America & Caribbean (all income levels) | LCN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.32435592730258 | 14.86451044403344 | 15.53077060599962 | 15.48114315938212 | 18.23836824217208 | 18.94306593967645 | 18.5169028421936 | 19.280143231428 | 19.22899427963759 | 19.73107481475357 | 18.99772308915053 | 20.21693698189679 | 21.20606890674221 | 20.48850186132304 | 19.70260661746678 | 18.54455958513263 | 17.60933738492517 | 17.31773771233196 | 18.78639016640785 | 18.24968898469394 | 17.11573347589586 | 16.78952686376223
Latin America and the Caribbean | LCR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Least developed countries: UN classification | LDC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.82044253136337 | 12.94256707790222 | 12.65489817239965 | 12.74956479045615 | 12.76337658328361 | 12.46984787548612 | 13.01689853602036 | 12.60179507525441 | 12.71900583343461 | 13.29186053610916 | 13.0289476893857 | 12.62981377466423 | 12.04863280092599 | 12.12958406118987 | 12.61852911196293 | 12.70905464145973 | 12.4517001539828 | 12.68823305214017 | 13.19319070871178 | 12.83399800121605 | 12.87302873324484 | 12.95042405031516
Low income | LIC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.82163402561233 | 11.02724841985314 | 10.77446097698192 | 10.69580667197303 | 10.86162211299145 | 10.8534935118037 | 11.24304466801101 | 10.88983658336558 | 11.12505231015613 | 11.45630273795895 | 11.32071091393138 | 10.92654657819168 | 10.220974060334 | 10.29422309400906 | 10.66320087779455 | 10.74934491206933 | 10.51899955695871 | 10.84006593911293 | 11.31692125768973 | 10.5802960492337 | 10.64834626920958 | 10.78270121384286
[NAME] | LIE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
[NAME] | LKA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 57.0999984741211 | 52.9000015258789 | 47.2000007629395 | 47.7999992370605 | 45 | 43.2000007629395 | 41.4000015258789 | 32.2999992370605 | 35 | 31.2999992370605 | 32.2999992370605 | 36.2000007629395 | 34.2000007629395 | 35.9000015258789 | 37.5999984741211 | 27.6000003814697 | 27.2999992370605 | 25 | 27.6000003814697 | 24.2000007629395 | 24.2000007629395 | 24.1000003814697
Lower middle income | LMC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.77037409731414 | 13.01975826227377 | 14.12275081066926 | 13.39279953187265 | 13.70668799923754 | 13.76862037048653 | 14.73900231571875 | 14.03102995500121 | 14.25909905208983 | 15.86341886251845 | 16.22031250795587 | 16.40546321547225 | 16.04898674311012 | 15.9616908518852 | 17.0361927929952 | 16.1789478299764 | 14.56982187128414 | 15.10075619973545 | 14.8758797070138 | 15.74771315283656 | 15.88985755837447 | 15.5398032694131
Low & middle income | LMY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.68944653938126 | 12.5289770367903 | 13.21894094868941 | 12.86408028533512 | 13.47418868142433 | 13.75979034226063 | 14.33368769163808 | 14.17115417073825 | 14.41733728781224 | 15.27956519610381 | 15.37072758833976 | 15.51244039615023 | 15.1762950165606 | 14.87895050154912 | 15.30364259162156 | 14.64773844444947 | 13.68699389219233 | 14.12899104269983 | 14.34805171440284 | 14.69299739119861 | 14.68334984122126 | 14.60997952894638
[NAME] | LSO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 53.7000007629395 | 56.2000007629395 | 58.5999984741211 | 57.4000015258789 | 50.9000015258789 | 46.2000007629395 | 59.2999992370605 | 51.7999992370605 | 43.9000015258789 | 56.7999992370605 | 56.5 | 51.5 | 58.9000015258789 | 55.7000007629395 | 56.4000015258789 | 51.7000007629395 | 44 | 41.9000015258789 | 42.4000015258789 | 40.0999984741211 | 41 | 44.4000015258789
Lithuania | LTU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 26.7999992370605 | 15.3999996185303 | 31.1000003814697 | 28.3999996185303 | 28 | 25.6000003814697 | 21.7999992370605 | 18.7999992370605 | 20.8999996185303 | 27.2999992370605 | 24.6000003814697 | 21.6000003814697 | 32.5999984741211 | 16.8999996185303 | 15.3000001907349 | 9.69999980926514 | 10.1000003814697 | 14.6000003814697 | 21.6000003814697 | 30.7999992370605 | 29.1000003814697 | 21.7999992370605
Luxembourg | LUX | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.5 | 2.40000009536743 | 3.79999995231628 | 7.30000019073486 | 7.80000019073486 | 8.30000019073486 | 9.19999980926514 | 7.09999990463257 | 7.40000009536743 | 7.30000019073486 | 5.40000009536743 | 9 | 12.1999998092651 | 22.3999996185303 | 16.2000007629395 | 15.1999998092651 | 17.5 | 23.8999996185303 | 17.7000007629395 | 10.1000003814697 | 20.7000007629395 | 18.3999996185303
Latvia | LVA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2999992370605 | 21 | 20.7000007629395 | 26.7999992370605 | 20.7999992370605 | 20.2999992370605 | 26.6000003814697 | 26 | 19.5 | 21.7000007629395 | 21.5 | 26.2999992370605 | 22.8999996185303 | 25.7999992370605 | 16.2000007629395 | 14.6999998092651 | 10.1000003814697 | 13.1000003814697 | 28.6000003814697 | 33.7999992370605 | 30.7000007629395 | 29.2999992370605
Macao SAR, China | MAC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 3.40000009536743 | 3.20000004768372 | 5 | 5.40000009536743 | 6.09999990463257 | 6.69999980926514 | 7.90000009536743 | 8.19999980926514 | 6.59999990463257 | 7 | 7.59999990463257 | 8.5 | 8.10000038146973 | 6.09999990463257 | 5.69999980926514 | 3.90000009536743 | 4.30000019073486 | 5.90000009536743 | 3.40000009536743 | 4.69999980926514 | 3
St. Martin (French part) | MAF | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Morocco | MAR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.1000003814697 | 15.8999996185303 | 15.6000003814697 | 15.3000001907349 | 15.1000003814697 | 14.8000001907349 | 14.6000003814697 | 14.3000001907349 | 16.7000007629395 | 16 | 16.6000003814697 | 16.8999996185303 | 15.8999996185303 | 14.3999996185303 | 14.3999996185303 | 14.1000003814697 | 15 | 16.2000007629395 | 16.2999992370605 | 16.2000007629395 | 17.2999992370605 | 15.6999998092651
Mexico and Central America | MCA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Monaco | MCO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Moldova | MDA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1000003814697 | 13.8999996185303 | 13.8000001907349 | 14.3000001907349 | 14.8000001907349 | 14.6000003814697 | 16.5 | 12.8000001907349 | 23.5 | 15 | 14.1000003814697 | 12.6999998092651 | 17.1000003814697 | 17.7000007629395 | 18.3999996185303 | 16 | 13.8999996185303 | 12.6000003814697 | 14.8000001907349 | 14.8999996185303 | 15.8999996185303 | 13.5
Madagascar | MDG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.59999990463257 | 5.59999990463257 | 4.59999990463257 | 5.40000009536743 | 5.09999990463257 | 4.59999990463257 | 3.29999995231628 | 3.20000004768372 | 3.20000004768372 | 2.79999995231628 | 5.30000019073486 | 6.19999980926514 | 7.19999980926514 | 5 | 2.79999995231628 | 5.30000019073486 | 5.40000009536743 | 5.90000009536743 | 6.30000019073486 | 6.59999990463257 | 6.59999990463257 | 6
Maldives | MDV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.9000015258789 | 33.9000015258789 | 33.9000015258789 | 35.0999984741211 | 35.0999984741211 | 34.5 | 34 | 34.2000007629395 | 35.2000007629395 | 34.5 | 33.7999992370605 | 33.2000007629395 | 32.5 | 33.2000007629395 | 31.7999992370605 | 30.5 | 33.9000015258789 | 33.2999992370605 | 34.2000007629395 | 35.2000007629395 | 35.2000007629395 | 34.7000007629395
Middle East & North Africa (all income levels) | MEA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.09000136204937 | 41.09578580667587 | 42.14747682898383 | 41.71265153844254 | 42.38228590159113 | 41.69050494419217 | 40.43690136937135 | 40.03654419312865 | 36.6205313971058 | 41.40385593921722 | 41.37036943717065 | 39.6484009437436 | 39.07366527653137 | 38.24381100954811 | 41.58965723861753 | 40.16909113927013 | 38.3627845766359 | 39.22440330236243 | 40.02107657347702 | 42.49087844459572 | 43.59862589374528 | 44.2667656634977
Mexico | MEX | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.69999980926514 | 6 | 6.30000019073486 | 8.19999980926514 | 15.1000003814697 | 12.1999998092651 | 10.3000001907349 | 8.60000038146973 | 6.09999990463257 | 6.19999980926514 | 6.59999990463257 | 7.80000019073486 | 8.19999980926514 | 10.6000003814697 | 7.40000009536743 | 7.40000009536743 | 7.5 | 8.39999961853027 | 10.5 | 10.1000003814697 | 10.3999996185303 | 9.89999961853027
Marshall Islands | MHL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Middle income | MIC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.08862103108304 | 12.74251457471293 | 13.57444620646704 | 13.1866334200296 | 13.87145001798596 | 14.21114206795648 | 14.82341715537433 | 14.70063976659843 | 14.95666455071014 | 15.91301905671813 | 16.04682807437871 | 16.2812771194829 | 16.00940777736766 | 15.65249510933091 | 16.09122194487706 | 15.31500029507308 | 14.23520342311997 | 14.70618333057254 | 14.88964678800407 | 15.44447280927647 | 15.44093879824231 | 15.35162039836626
Macedonia, FYR | MKD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 56.7999992370605 | 56.7000007629395 | 56.4000015258789 | 55.5999984741211 | 54.0999984741211 | 62.7999992370605 | 60.5999984741211 | 74.5 | 61.7999992370605 | 62.5 | 57.9000015258789 | 59.0999984741211 | 66.5999984741211 | 65 | 62.2000007629395 | 60.9000015258789 | 58.2999992370605 | 57.4000015258789 | 59.5 | 53.4000015258789 | 54.7999992370605 | 51.7000007629395
[NAME] | MLI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.6000003814697 | 15.6000003814697 | 15.1000003814697 | 15.1999998092651 | 15.6999998092651 | 15.1000003814697 | 14.6000003814697 | 14.8999996185303 | 14.5 | 14.6000003814697 | 14.8000001907349 | 15 | 15.3000001907349 | 15.6999998092651 | 15.1999998092651 | 14.6000003814697 | 15 | 14.6999998092651 | 14.8999996185303 | 14 | 14.3000001907349 | 14.3000001907349
Malta | MLT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 11.8000001907349 | 14 | 12.8999996185303 | 18 | 13.1000003814697 | 12.5 | 12.6999998092651 | 13.1999998092651 | 10.3999996185303 | 14.3000001907349 | 13.8000001907349 | 19.2000007629395 | 17.8999996185303 | 16.2000007629395 | 14.5 | 11.3999996185303 | 10.1999998092651 | 12.8999996185303 | 11.6000003814697 | 14.1000003814697 | 14.6999998092651
Myanmar | MMR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 13 | 13.6000003814697 | 12.5 | 12.3000001907349 | 12.5 | 12.3999996185303 | 12.3000001907349 | 12.3000001907349 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 13.1000003814697 | 13 | 13 | 13 | 12.8999996185303
Middle East & North Africa (developing only) | MNA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.57106505331572 | 40.86903136812445 | 42.05380105415617 | 42.85788867139183 | 43.78389297619792 | 41.82615235512653 | 40.45791809095807 | 39.99737195272181 | 38.02045448053361 | 43.06817797028959 | 43.0793695200232 | 40.61206716499267 | 39.10998329467456 | 38.04455830344742 | 42.7404985162209 | 40.4364285528858 | 38.71718554948973 | 39.46397250447064 | 40.11078729121557 | 42.99177679388294 | 45.23784883590868 | 44.97258232201513
Montenegro | MNE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.9000015258789 | 33.9000015258789 | 40.2999992370605 | 42.9000015258789 | 57 | 58.2999992370605 | 41.2999992370605 | 43 | 43 | 60.4000015258789 | 41 | 42.2000007629395 | 43 | 58.9000015258789 | 61.0999984741211 | 50 | 45.7999992370605 | 28.5 | 35.7999992370605 | 47.4000015258789 | 40 | 39.7999992370605
Mongolia | MNG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1999998092651 | 10.1999998092651 | 10.3999996185303 | 13 | 15 | 13.1000003814697 | 13.8999996185303 | 13.6000003814697 | 13.5 | 12.6000003814697 | 13.3999996185303 | 14.3000001907349 | 11.1999998092651 | 13 | 14.1999998092651 | 10.8000001907349 | 13.1000003814697 | 8.60000038146973 | 10.5 | 13.6999998092651 | 10 | 10.6000003814697
Northern Mariana Islands | MNP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Mozambique | MOZ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1000003814697 | 14 | 13 | 13.1000003814697 | 13.3999996185303 | 12.5 | 12.8000001907349 | 12.6999998092651 | 13 | 13.5 | 12.6999998092651 | 12.8999996185303 | 13.1000003814697 | 13 | 13 | 13 | 13.1000003814697 | 13.1000003814697 | 13.1000003814697 | 13.1000003814697 | 13.1000003814697 | 13.1000003814697
Mauritania | MRT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 39.5999984741211 | 39.2999992370605 | 38.7000007629395 | 40.0999984741211 | 38.0999984741211 | 38.7000007629395 | 40.2000007629395 | 39.2000007629395 | 38.5999984741211 | 39.2999992370605 | 39.2000007629395 | 39.4000015258789 | 38.7000007629395 | 39.7000007629395 | 39.2999992370605 | 38.9000015258789 | 38.5 | 38.4000015258789 | 39.0999984741211 | 38.2000007629395 | 38.2999992370605 | 38.2000007629395
[NAME] | MUS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.6000003814697 | 28.7000007629395 | 28.7999992370605 | 28.8999996185303 | 26.3999996185303 | 26.5 | 26.6000003814697 | 26.7000007629395 | 26.7000007629395 | 24.5 | 22.5 | 24.2000007629395 | 26.3999996185303 | 31.6000003814697 | 34.4000015258789 | 30.3999996185303 | 30.5 | 24.6000003814697 | 25.5 | 28.5 | 27.7999992370605 | 28.7999992370605
[NAME] | MWI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.8999996185303 | 15.1999998092651 | 13.8000001907349 | 15.5 | 13.5 | 13.8000001907349 | 14.1000003814697 | 14.5 | 14.3000001907349 | 14.6000003814697 | 15 | 14.5 | 14.1999998092651 | 14.1999998092651 | 14.5 | 14.5 | 13.8999996185303 | 14 | 13.8999996185303 | 14.1000003814697 | 14.3000001907349 | 14.3999996185303
Malaysia | MYS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.30000019073486 | 11 | 12.1999998092651 | 11.3999996185303 | 9.39999961853027 | 7.69999980926514 | 7.40000009536743 | 9.10000038146973 | 9.39999961853027 | 8.5 | 11.1999998092651 | 11.3000001907349 | 11.6999998092651 | 11.5 | 11.6000003814697 | 11 | 11.1999998092651 | 11.5 | 12.1000003814697 | 11.6000003814697 | 10.8000001907349 | 10.8000001907349
North America | NAC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.80989432743431 | 13.59866396979671 | 12.86737665364651 | 12.16697844665855 | 12.02716946001319 | 11.81465627700245 | 11.41794782731209 | 10.34789207930341 | 9.988096409465731 | 9.319653482179453 | 9.92370593825229 | 11.42842227050599 | 11.71889937967286 | 11.25658292603435 | 10.32827382454105 | 9.947081054267453 | 9.637748550003984 | 11.35796859304929 | 14.83410811937403 | 15.73907537079196 | 15.65916242402813 | 14.68313078248455
Namibia | NAM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 39.2999992370605 | 39.5 | 39.7000007629395 | 34.2000007629395 | 36.2000007629395 | 38.0999984741211 | 41.2999992370605 | 42.4000015258789 | 43.5 | 46.0999984741211 | 46.7999992370605 | 36.5999984741211 | 44.7999992370605 | 47.7999992370605 | 43.0999984741211 | 47.5 | 41.2999992370605 | 64.6999969482422 | 55.7999992370605 | 47.7999992370605 | 44.9000015258789 | 40
New Caledonia | NCL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
[NAME] | NER | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 6.19999980926514 | 5.90000009536743 | 5.80000019073486 | 6.19999980926514 | 5.80000019073486 | 5.90000009536743 | 5.5 | 5.90000009536743 | 6 | 5.69999980926514 | 5.80000019073486 | 5.69999980926514 | 6 | 5.69999980926514 | 5.80000019073486 | 5.90000009536743 | 5.59999990463257 | 6 | 5.59999990463257 | 5.90000009536743 | 5.80000019073486
Nigeria | NGA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.1000003814697 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349 | 13.3000001907349
Nicaragua | NIC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.5 | 6.30000019073486 | 6.59999990463257 | 4.40000009536743 | 4.80000019073486 | 5.19999980926514 | 5.5 | 9.69999980926514 | 6.69999980926514 | 4.69999980926514 | 5.40000009536743 | 6.09999990463257 | 16 | 13.3999996185303 | 11.1000003814697 | 9.69999980926514 | 8.30000019073486 | 10.3000001907349 | 11.1000003814697 | 13.3999996185303 | 13.1999998092651 | 12.8999996185303
Netherlands | NLD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12 | 8.5 | 9.5 | 9 | 12.6999998092651 | 11.6000003814697 | 10.3000001907349 | 9.19999980926514 | 8.10000038146973 | 5.90000009536743 | 4.5 | 4.80000019073486 | 6.5 | 8.10000038146973 | 8.39999961853027 | 7.09999990463257 | 6.19999980926514 | 5.19999980926514 | 6.09999990463257 | 8.60000038146973 | 7.80000019073486 | 10
High income: nonOECD | NOC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.8481022783916 | 18.23604908571215 | 19.25888450129779 | 19.80323787076484 | 21.49014280720123 | 23.91126928095411 | 26.27236927861473 | 29.19038438737244 | 25.0354780468645 | 22.82644058811811 | 20.68296281903212 | 20.14095454769432 | 23.22613051012619 | 23.12146553282152 | 20.01699889761284 | 21.54971436250027 | 19.13148550239228 | 20.38369617153423 | 24.11114529049849 | 23.25734282698677 | 20.12358603257224 | 22.16546715420703
Norway | NOR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8000001907349 | 12.3999996185303 | 13 | 11.8999996185303 | 11.6000003814697 | 12.3999996185303 | 10.8000001907349 | 9.19999980926514 | 9.30000019073486 | 10.6000003814697 | 10 | 10.1999998092651 | 10.5 | 10.5 | 11.3000001907349 | 8.69999980926514 | 6.59999990463257 | 6.80000019073486 | 8 | 7.69999980926514 | 7.90000009536743 | 7.30000019073486
Nepal | NPL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.29999995231628 | 2.09999990463257 | 2.40000009536743 | 2.59999990463257 | 2.79999995231628 | 5.09999990463257 | 4.30000019073486 | 3.40000009536743 | 2.09999990463257 | 3.09999990463257 | 4.40000009536743 | 3.40000009536743 | 2.5 | 2.59999990463257 | 3 | 3.20000004768372 | 3.09999990463257 | 3.29999995231628 | 3.29999995231628 | 3.29999995231628 | 3.29999995231628 | 3.29999995231628
New Zealand | NZL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 16.8999996185303 | 16.2999992370605 | 14.6999998092651 | 12.1999998092651 | 11.5 | 13.3999996185303 | 13.8999996185303 | 13 | 12.3000001907349 | 11.8999996185303 | 11.6999998092651 | 10.6000003814697 | 10.5 | 10.1999998092651 | 10.3000001907349 | 10.1000003814697 | 10.8000001907349 | 17.1000003814697 | 17.3999996185303 | 16.2000007629395 | 18.1000003814697
High income: OECD | OEC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.672793280425 | 15.42540538781419 | 16.6865588676689 | 16.80922044431962 | 16.83458594950494 | 16.75971290746641 | 16.49597277108921 | 15.79106998828476 | 15.80253158795894 | 14.69641170240508 | 14.42665204476348 | 15.09821903194136 | 15.33951014173092 | 15.26115284773033 | 14.7469207581645 | 13.94533563497615 | 12.76299835625511 | 13.13593336577657 | 16.07644974083574 | 16.9927432435251 | 17.23903194836371 | 17.65584469440178
OECD members | OED | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.4719340516897 | 14.1732955626217 | 15.37871998702616 | 15.50390367858075 | 16.32711702250865 | 15.7673331984999 | 15.56358984537345 | 14.59789604620033 | 14.37810923763911 | 13.3540571656985 | 13.37178094005883 | 14.26055934176077 | 14.6383037948489 | 15.03854918594262 | 14.23949306735088 | 13.61449722913178 | 12.68162165742785 | 13.14001461859491 | 16.0310966976194 | 16.54587422255577 | 16.59192984622059 | 16.79377042949931
Oman | OMN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.7000007629395 | 30.7999992370605 | 30.7000007629395 | 30.6000003814697 | 30.6000003814697 | 30.5 | 30.7000007629395 | 30.5 | 30.3999996185303 | 30.6000003814697 | 30.7000007629395 | 30.5 | 30.3999996185303 | 30.5 | 30.6000003814697 | 30.7000007629395 | 30.7000007629395 | 31 | 30.5 | 30.7000007629395 | 30.6000003814697 | 30.6000003814697
Other small states | OSS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.43314033062827 | 31.84156139273901 | 32.78628885516521 | 32.51642903745829 | 32.12056595078184 | 31.22076206397951 | 32.09689659017304 | 29.39366116658947 | 32.06594591090608 | 34.5422103956378 | 33.6347331053668 | 31.3659494105065 | 33.92847731073922 | 34.34123614241226 | 33.756118983027 | 32.07328990114245 | 29.41187446138652 | 33.36856217779282 | 30.49910086314106 | 31.18238087355394 | 30.71444567675094 | 30.06243591160805
Pakistan | PAK | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2000007629395 | 15.5 | 10.8000001907349 | 10.1999998092651 | 18 | 18.7000007629395 | 20.8999996185303 | 18.5 | 21.2000007629395 | 29.3999996185303 | 27.2000007629395 | 20.7000007629395 | 19.2999992370605 | 15.1000003814697 | 13.6999998092651 | 9.80000019073486 | 9 | 10.6999998092651 | 10.6999998092651 | 10.6999998092651 | 10.6999998092651 | 11.1999998092651
Panama | PAN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.7000007629395 | 38 | 35.4000015258789 | 35.9000015258789 | 35.2000007629395 | 37.5 | 35 | 38.5 | 34 | 36.5 | 38.2999992370605 | 37.2000007629395 | 36.4000015258789 | 33 | 28 | 27.7999992370605 | 22.3999996185303 | 20.3999996185303 | 21.8999996185303 | 20.7999992370605 | 14.1000003814697 | 14.3999996185303
Peru | PER | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 10.3999996185303 | 12 | 8.10000038146973 | 7.40000009536743 | 9.39999961853027 | 8.30000019073486 | 8.10000038146973 | 7.90000009536743 | 9.89999961853027 | 7.40000009536743 | 9.10000038146973 | 11.1999998092651 | 9.10000038146973 | 9.10000038146973 | 8 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7 | 6.80000019073486 | 6.90000009536743
Philippines | PHL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2000007629395 | 19.8999996185303 | 20.3999996185303 | 20.2999992370605 | 18.7999992370605 | 17.2000007629395 | 18.1000003814697 | 21 | 22.1000003814697 | 25.6000003814697 | 25.2999992370605 | 27.1000003814697 | 25.2999992370605 | 27.8999996185303 | 19.3999996185303 | 19.7999992370605 | 19.3999996185303 | 19.2999992370605 | 19.2999992370605 | 17.7000007629395 | 16.8999996185303 | 17.1000003814697
Palau | PLW | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
[NAME] | PNG | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.09999990463257 | 5.80000019073486 | 5.5 | 6.30000019073486 | 6.90000009536743 | 6.19999980926514 | 7.09999990463257 | 6.30000019073486 | 6.5 | 6.80000019073486 | 6.59999990463257 | 6.5 | 6.30000019073486 | 6.59999990463257 | 6.30000019073486 | 6.40000009536743 | 6.09999990463257 | 6.09999990463257 | 6.19999980926514 | 6.09999990463257 | 5.80000019073486 | 6
Poland | POL | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27 | 29.7000007629395 | 32 | 34 | 33.2999992370605 | 30.7999992370605 | 27.7000007629395 | 24.8999996185303 | 31.5 | 36.9000015258789 | 41.4000015258789 | 43.7000007629395 | 43.7999992370605 | 42.7999992370605 | 38.9000015258789 | 31.3999996185303 | 23.6000003814697 | 19.7000007629395 | 21 | 25.2999992370605 | 28.7000007629395 | 29.7999992370605
Puerto Rico | PRI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34 | 31.7999992370605 | 25.7000007629395 | 23.3999996185303 | 23.7999992370605 | 26.2999992370605 | 25.2999992370605 | 25.2999992370605 | 20.1000003814697 | 16.5 | 20.7999992370605 | 23.7999992370605 | 23.6000003814697 | 19.3999996185303 | 21.2000007629395 | 21.8999996185303 | 19.2999992370605 | 21 | 23.2000007629395 | 22.2000007629395 | 24.7000007629395 | 25.2999992370605
Korea, Dem. Rep. | PRK | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.19999980926514 | 5.09999990463257 | 5 | 5 | 8 | 8 | 8.80000019073486 | 8 | 7.90000009536743 | 8.39999961853027 | 8.10000038146973 | 8.10000038146973 | 7.69999980926514 | 7.90000009536743 | 7.80000019073486 | 7.69999980926514 | 8.19999980926514 | 8.69999980926514 | 7.69999980926514 | 7.69999980926514 | 8.10000038146973
Portugal | PRT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.1000003814697 | 11.3999996185303 | 14.8000001907349 | 16.7000007629395 | 17.8999996185303 | 19.6000003814697 | 18.6000003814697 | 12.8999996185303 | 10.8000001907349 | 11.6000003814697 | 12.1000003814697 | 13.8999996185303 | 17 | 17.6000003814697 | 19.1000003814697 | 18.3999996185303 | 20.2999992370605 | 20.2000007629395 | 21.5 | 23.7000007629395 | 31.7000007629395 | 39.2000007629395
Paraguay | PRY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16 | 10.3000001907349 | 17.3999996185303 | 15.3999996185303 | 7.09999990463257 | 9.5 | 12 | 12.1000003814697 | 13.5 | 17.2999992370605 | 17.2999992370605 | 24.8999996185303 | 20.2999992370605 | 19 | 14.8999996185303 | 17.2999992370605 | 18.1000003814697 | 16.5 | 17 | 15.8999996185303 | 16.5 | 17.5
Pacific island small states | PSS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
French Polynesia | PYF | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Qatar | QAT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.69999980926514 | 12.3000001907349 | 12.8999996185303 | 13.6000003814697 | 14.3999996185303 | 15.1999998092651 | 15.1999998092651 | 8.60000038146973 | 5.69999980926514 | 3.5 | 6 | 9.5 | 14 | 19.7000007629395 | 15.8999996185303 | 12 | 7.19999980926514 | 5.69999980926514 | 4.80000019073486 | 7.09999990463257 | 10.3000001907349 | 10.3999996185303
Romania | [NAME] | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.7999992370605 | 24.3999996185303 | 24.3999996185303 | 24.2999992370605 | 23.2999992370605 | 24.3999996185303 | 19.2999992370605 | 17.1000003814697 | 15.3999996185303 | 15.8000001907349 | 17 | 21.8999996185303 | 20 | 18.7000007629395 | 18.5 | 20.2000007629395 | 18.7999992370605 | 18.2999992370605 | 20.2000007629395 | 21.8999996185303 | 24 | 23.2999992370605
Russian Federation | RUS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.3999996185303 | 12.8999996185303 | 13.8999996185303 | 17.5 | 20 | 20.5 | 23.8999996185303 | 27.5 | 26 | 22.2000007629395 | 19.2000007629395 | 16.8999996185303 | 18.7999992370605 | 18.7000007629395 | 16.8999996185303 | 17.1000003814697 | 14.3999996185303 | 15.1000003814697 | 18.8999996185303 | 17.2999992370605 | 15.5 | 15.1999998092651
Rwanda | RWA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.5 | 0.5 | 0.600000023841858 | 0.699999988079071 | 0.400000005960464 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5
South Asia | SAS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.95514039341556 | 10.35180770015059 | 10.22632904117786 | 8.921814717724281 | 10.27574580654347 | 10.16577953673081 | 11.66594168837996 | 9.684929948965548 | 10.48613111418341 | 12.49857881980876 | 11.46852796362457 | 11.66299697263619 | 10.71404055347644 | 10.11440151379924 | 11.31879540735902 | 10.65132957061915 | 9.692554165876567 | 10.70398671598168 | 10.54312191506594 | 11.29678292389996 | 11.30064565620718 | 10.85057817835891
Saudi Arabia | SAU | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 47.2999992370605 | 55.0999984741211 | 55.2999992370605 | 35.7999992370605 | 36.9000015258789 | 55.2999992370605 | 55.4000015258789 | 55.4000015258789 | 27 | 31 | 29.7999992370605 | 37.7000007629395 | 50.4000015258789 | 52.7000007629395 | 38.5 | 50.4000015258789 | 47.4000015258789 | 50.7999992370605 | 55.2000007629395 | 54.2999992370605 | 40.2000007629395 | 55.5
[NAME] | SCE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Sudan | SDN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 26.7999992370605 | 26.2000007629395 | 26.6000003814697 | 26.5 | 26.5 | 26.7000007629395 | 29.2999992370605 | 27.3999996185303 | 27.3999996185303 | 27.5 | 26.7000007629395 | 26.6000003814697 | 26.7999992370605 | 26.7000007629395 | 26.3999996185303 | 26.7999992370605 | 26.7999992370605 | 26.5 | 26.6000003814697 | 26.5 | 26.2999992370605 | 26.5
Senegal | SEN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.7000007629395 | 18.7999992370605 | 18.7999992370605 | 18.8999996185303 | 18.3999996185303 | 18.7000007629395 | 18.6000003814697 | 18.2999992370605 | 18.2999992370605 | 18.6000003814697 | 18.5 | 18.8999996185303 | 18.2999992370605 | 18.3999996185303 | 18.3999996185303 | 18.7000007629395 | 18.3999996185303 | 18.6000003814697 | 18.7000007629395 | 18.5 | 18.7000007629395 | 18.6000003814697
Singapore | SGP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10 | 6.40000009536743 | 6.40000009536743 | 6.90000009536743 | 7 | 7.30000019073486 | 6.80000019073486 | 12.1999998092651 | 13.1999998092651 | 13.5 | 14.1000003814697 | 18.7000007629395 | 20.2000007629395 | 17 | 15.8000001907349 | 13.8999996185303 | 11.8000001907349 | 12.6000003814697 | 17.2000007629395 | 12.1000003814697 | 11.6000003814697 | 11.1999998092651
Solomon Islands | SLB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.3999996185303 | 13.1000003814697 | 12.8000001907349 | 12.6000003814697 | 13.3000001907349 | 13.5 | 13.3000001907349 | 13.5 | 14.6999998092651 | 14.1000003814697 | 13.6999998092651 | 12.8999996185303 | 12.8000001907349 | 12.3999996185303 | 13.1000003814697 | 12.8999996185303 | 12.8000001907349 | 13.8000001907349 | 12.8000001907349 | 12.5 | 13.3000001907349
Sierra Leone | SLE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.79999995231628 | 3.79999995231628 | 3.59999990463257 | 3.5 | 3.79999995231628 | 4.19999980926514 | 4 | 3.59999990463257 | 3.79999995231628 | 3.5 | 3.20000004768372 | 3 | 3.40000009536743 | 3.40000009536743 | 3.5 | 3.5 | 3.40000009536743 | 3.5 | 3.5 | 3.5 | 3.40000009536743 | 3.29999995231628
El Salvador | SLV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.39999961853027 | 11.3999996185303 | 13.6000003814697 | 10.6999998092651 | 13.8999996185303 | 15.1000003814697 | 11.6999998092651 | 13.1999998092651 | 10.3000001907349 | 10.1000003814697 | 9.89999961853027 | 8.39999961853027 | 7.5 | 9.30000019073486 | 10.3999996185303 | 10 | 7.90000009536743 | 8.30000019073486 | 10.3000001907349 | 9.89999961853027 | 9.89999961853027 | 10
[NAME] | SMR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Somalia | SOM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 13.5 | 13.3000001907349 | 13.8000001907349 | 13.1999998092651 | 13.1999998092651 | 13.1999998092651 | 13.3000001907349 | 13.3000001907349 | 13.3999996185303 | 13.1999998092651 | 13.3999996185303 | 13.3999996185303 | 13.1999998092651 | 13.1999998092651 | 13.1999998092651 | 13.1999998092651 | 13.3000001907349 | 13.1999998092651 | 13.1999998092651 | 13.1000003814697 | 13.1999998092651
Serbia | SRB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.5999984741211 | 36.2000007629395 | 44.7999992370605 | 39 | 34.4000015258789 | 33.9000015258789 | 35.4000015258789 | 35.0999984741211 | 35.0999984741211 | 32.2999992370605 | 32.9000015258789 | 35.5999984741211 | 39.2999992370605 | 48 | 54.2000007629395 | 54 | 47 | 40.0999984741211 | 47.2000007629395 | 52.4000015258789 | 52.2999992370605 | 52.2000007629395
Sub-Saharan Africa (developing only) | SSA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.6525434791787 | 16.47224822566448 | 16.64280218003545 | 15.51367329166751 | 14.94470116062249 | 16.00031678674211 | 16.41211133396063 | 15.95514020875375 | 16.21340071217993 | 15.96919296110203 | 16.33746402235706 | 16.18215938007749 | 16.27049177701448 | 15.70759316075931 | 14.94412600946742 | 14.92718887886786 | 14.60165220578196 | 14.67335800440059 | 14.84493987981933 | 14.87531479534377 | 14.87109691434874 | 14.85961173129208
South Sudan | SSD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Sub-Saharan Africa (all income levels) | SSF | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.65049626909028 | 16.4688364531915 | 16.64047509357345 | 15.51189265216045 | 14.94325197499969 | 15.99674021267464 | 16.40644831073217 | 15.95298185007359 | 16.21099918910883 | 15.96712560963451 | 16.33342958902563 | 16.17968079390663 | 16.26807843237966 | 15.70433941879688 | 14.94265268131859 | 14.92612463018054 | 14.59988830850234 | 14.67173555997824 | 14.84418938761223 | 14.87445281775986 | 14.86983275730031 | 14.85843875032278
Small states | SST | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.44038019202989 | 33.49681422032997 | 34.21606879120846 | 33.68328331176008 | 34.06286610780661 | 33.8123016676559 | 33.82605299821769 | 31.87309759281351 | 34.13328928543083 | 34.74776591265287 | 34.32864633725185 | 32.44260919360122 | 32.97486088106859 | 33.32298427591 | 32.4774630583493 | 30.95730062128009 | 28.7923613576472 | 32.06519633247256 | 30.23292610167171 | 31.40037726471177 | 31.08528570048617 | 31.03146004137982
Sao Tome and Principe | STP | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Suriname | SUR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41.0999984741211 | 53.0999984741211 | 48.5999984741211 | 37.9000015258789 | 30.2000007629395 | 40 | 39 | 39.9000015258789 | 59.9000015258789 | 59.5 | 57.2999992370605 | 57.7999992370605 | 56.7999992370605 | 56.2999992370605 | 57.2999992370605 | 56.9000015258789 | 57.2000007629395 | 57.5999984741211 | 58.2000007629395 | 57.7000007629395 | 57.4000015258789 | 57.5999984741211
Slovak Republic | SVK | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.7999992370605 | 20.5 | 22.1000003814697 | 26.3999996185303 | 23 | 21.6000003814697 | 22.5 | 23.2000007629395 | 31.8999996185303 | 33.5999984741211 | 35.5 | 35.5 | 31.7000007629395 | 30.8999996185303 | 28.8999996185303 | 27 | 20 | 19.8999996185303 | 26.6000003814697 | 32.0999984741211 | 33.5999984741211 | 32.5
Slovenia | SVN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1999998092651 | 11.1000003814697 | 27.6000003814697 | 23.1000003814697 | 20.2000007629395 | 16.8999996185303 | 19.3999996185303 | 18.2999992370605 | 19.8999996185303 | 18.2999992370605 | 16.6000003814697 | 18.7000007629395 | 20 | 19.2999992370605 | 17.7999992370605 | 16.8999996185303 | 11.1999998092651 | 11.3000001907349 | 13.3999996185303 | 13.8999996185303 | 16.7999992370605 | 21.1000003814697
Sweden | SWE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.59999990463257 | 11.3999996185303 | 19.7999992370605 | 20.5 | 19 | 21.7000007629395 | 21.2999992370605 | 16.7000007629395 | 14.3000001907349 | 11.6999998092651 | 10.8999996185303 | 12.3000001907349 | 13.1000003814697 | 16.5 | 22.1000003814697 | 22 | 20.3999996185303 | 21.5 | 24.1000003814697 | 24 | 22.7000007629395 | 22.7000007629395
Swaziland | SWZ | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 43.5999984741211 | 43.4000015258789 | 43.4000015258789 | 43.5 | 40.9000015258789 | 42.2000007629395 | 45.5 | 45.5999984741211 | 45.5999984741211 | 45.7000007629395 | 45.9000015258789 | 45.7999992370605 | 45.5 | 45.7000007629395 | 45.7000007629395 | 45.5999984741211 | 45.7000007629395 | 45.5999984741211 | 45.9000015258789 | 45.7999992370605 | 46 | 45.7000007629395
Sint Maarten (Dutch part) | SXM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Seychelles | SYC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Syrian Arab Republic | SYR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 35.2000007629395 | 35.4000015258789 | 27.5 | 27.2000007629395 | 26.1000003814697 | 36.2000007629395 | 29.5 | 27 | 29.1000003814697 | 37.7000007629395 | 46 | 43.0999984741211 | 32.7000007629395 | 35.9000015258789 | 39.0999984741211 | 45.2000007629395 | 48 | 46.7999992370605 | 41.7000007629395 | 40.7999992370605 | 40.7999992370605 | 41
Turks and Caicos Islands | TCA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Chad | TCD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 13.3999996185303 | 13.6999998092651 | 13.1999998092651 | 13.6999998092651 | 13.3999996185303 | 13.1999998092651 | 13.1000003814697 | 13.6000003814697 | 13.6999998092651 | 12.6999998092651 | 13 | 12.5 | 11.3000001907349 | 13 | 13.6000003814697 | 13.6000003814697 | 13.5 | 13.6999998092651 | 12.6999998092651 | 13.6000003814697 | 13.3000001907349
Togo | TGO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6000003814697 | 13.8000001907349 | 14.8999996185303 | 12.6000003814697 | 13.1000003814697 | 13 | 13.3000001907349 | 13.8000001907349 | 13.3999996185303 | 13.6999998092651 | 13.6999998092651 | 13.6999998092651 | 13.1999998092651 | 13.3999996185303 | 13.5 | 13.3000001907349 | 13.3999996185303 | 13.3999996185303 | 13.3000001907349 | 13.3000001907349 | 13.1999998092651 | 13.1999998092651
Thailand | THA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.5 | 3.5 | 3.79999995231628 | 2.59999990463257 | 2.5 | 2.40000009536743 | 1.89999997615814 | 6.59999990463257 | 7.40000009536743 | 6.30000019073486 | 7.5 | 5.40000009536743 | 5.19999980926514 | 4.5 | 4.5 | 5.40000009536743 | 4.5 | 5 | 6.59999990463257 | 4.30000019073486 | 3.20000004768372 | 3
Tajikistan | TJK | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.7000007629395 | 20.1000003814697 | 21.3999996185303 | 20.7000007629395 | 21.2999992370605 | 22.3999996185303 | 22.7000007629395 | 22.8999996185303 | 22.7999992370605 | 23 | 23.1000003814697 | 23.1000003814697 | 23.1000003814697 | 23.1000003814697 | 22.8999996185303 | 23 | 23 | 23 | 22.7999992370605 | 22.8999996185303 | 23 | 23
Turkmenistan | TKM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.8999996185303 | 21.8999996185303 | 21.5 | 21 | 21.7000007629395 | 22.2999992370605 | 22 | 22.8999996185303 | 23.3999996185303 | 23.6000003814697 | 23.6000003814697 | 23.3999996185303 | 23.5 | 23.2999992370605 | 23.2999992370605 | 23.2000007629395 | 23.2000007629395 | 23.3999996185303 | 22.8999996185303 | 23.1000003814697 | 23.2999992370605 | 22.8999996185303
Timor-Leste | TLS | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.1000003814697 | 19.8999996185303 | 19.7999992370605 | 19.6000003814697 | 19.5 | 19.6000003814697 | 19.8999996185303 | 21 | 19.7999992370605 | 19.5 | 24.7000007629395 | 23.7000007629395 | 22.7000007629395 | 21.6000003814697 | 20.6000003814697 | 19.6000003814697 | 21.1000003814697 | 21 | 20.7999992370605 | 19.8999996185303 | 19.7999992370605 | 18.2999992370605
Tonga | TON | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Trinidad and Tobago | TTO | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41.2000007629395 | 41.7000007629395 | 39.7999992370605 | 37.2000007629395 | 34.9000015258789 | 36 | 33.5999984741211 | 32.2999992370605 | 30.7000007629395 | 27.6000003814697 | 25.7000007629395 | 25.7999992370605 | 26.3999996185303 | 21.2000007629395 | 21.3999996185303 | 17 | 14 | 12.6999998092651 | 14.3000001907349 | 16.7000007629395 | 17.1000003814697 | 16
Tunisia | TUN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.6000003814697 | 29.1000003814697 | 29.7000007629395 | 26.8999996185303 | 29.2000007629395 | 29.1000003814697 | 29.1000003814697 | 32.5999984741211 | 30.6000003814697 | 30.2000007629395 | 29.2000007629395 | 29.7999992370605 | 28.5 | 27.5 | 26.3999996185303 | 25.2000007629395 | 25.2000007629395 | 25.5 | 27.7000007629395 | 27.2999992370605 | 27.1000003814697 | 27.2000007629395
Turkey | TUR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6000003814697 | 13.3999996185303 | 15.6999998092651 | 13.3000001907349 | 12.8999996185303 | 11 | 14.6999998092651 | 12.5 | 13.6999998092651 | 11.6000003814697 | 14.1000003814697 | 16.6000003814697 | 18.2999992370605 | 20.2000007629395 | 20 | 20.1000003814697 | 20.1000003814697 | 20.6000003814697 | 24.3999996185303 | 22.5 | 20.2000007629395 | 19.3999996185303
Tuvalu | TUV | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Tanzania | TZA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.59999990463257 | 7.5 | 7.90000009536743 | 8.10000038146973 | 9.60000038146973 | 10.1999998092651 | 9.60000038146973 | 9.80000019073486 | 9.60000038146973 | 10.1000003814697 | 9.80000019073486 | 7.5 | 7.19999980926514 | 6.19999980926514 | 5.40000009536743 | 8.80000019073486 | 3.79999995231628 | 5.09999990463257 | 5.40000009536743 | 6.5 | 7.5 | 7.5
Uganda | UGA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 4.80000019073486 | 4.19999980926514 | 4.19999980926514 | 4.30000019073486 | 4.30000019073486 | 4.30000019073486 | 4.40000009536743 | 4.40000009536743 | 5.09999990463257 | 5.90000009536743 | 6.30000019073486 | 5.80000019073486 | 4.59999990463257 | 3.59999990463257 | 3.70000004768372 | 3.79999995231628 | 5.30000019073486 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.80000019073486
Ukraine | UKR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 15.3999996185303 | 17.6000003814697 | 14.1000003814697 | 11.1999998092651 | 15.1000003814697 | 17.7000007629395 | 22.5 | 23.1000003814697 | 23.1000003814697 | 21.7000007629395 | 19.1000003814697 | 18.1000003814697 | 15.3999996185303 | 14.5 | 13.5 | 12.6999998092651 | 12.6999998092651 | 17.5 | 16.2999992370605 | 18.2999992370605 | 16.8999996185303
Upper middle income | UMC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.50230720717244 | 12.4973837598276 | 13.07443281770994 | 12.99260235572644 | 14.03130547209811 | 14.65321897327484 | 14.9101166698001 | 15.40501197721239 | 15.70318644684445 | 15.96656188155622 | 15.85965980204972 | 16.14834896522429 | 15.96751230044557 | 15.32826888752746 | 15.10453177155277 | 14.41148463481908 | 13.88287711144852 | 14.28570612812304 | 14.90457325075105 | 15.1081087567638 | 14.92837963429762 | 15.12922982057914
Uruguay | URY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.2999992370605 | 26.1000003814697 | 26.1000003814697 | 27 | 26.1000003814697 | 25.2999992370605 | 27.1000003814697 | 33.2999992370605 | 31.7999992370605 | 30.3999996185303 | 29.1000003814697 | 27.7000007629395 | 26.5 | 30 | 29.3999996185303 | 35.2000007629395 | 30.6000003814697 | 24.7999992370605 | 24.6000003814697 | 25.3999996185303 | 21.6000003814697 | 21.1000003814697
United States | USA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 13.5 | 12.6999998092651 | 12 | 11.8999996185303 | 11.6000003814697 | 11 | 10 | 9.69999980926514 | 9.10000038146973 | 9.80000019073486 | 11.3999996185303 | 11.6999998092651 | 11.1999998092651 | 10.3000001907349 | 9.89999961853027 | 9.60000038146973 | 11.5 | 15.1000003814697 | 16.1000003814697 | 16 | 14.8999996185303
Uzbekistan | UZB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2999992370605 | 21.3999996185303 | 22.1000003814697 | 21.8999996185303 | 22.2000007629395 | 22.7000007629395 | 22.8999996185303 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 23 | 23 | 23 | 23.1000003814697 | 23.1000003814697 | 23 | 23 | 23 | 23.1000003814697
St. Vincent and the Grenadines | VCT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Venezuela, RB | VEN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.7000007629395 | 17.7000007629395 | 15.6999998092651 | 17.3999996185303 | 25.6000003814697 | 35.0999984741211 | 26.3999996185303 | 26.5 | 32.5999984741211 | 28.2999992370605 | 27.7000007629395 | 34.5 | 35.0999984741211 | 32.0999984741211 | 25.1000003814697 | 22 | 17.5 | 15.8999996185303 | 18.7000007629395 | 21.5 | 21.8999996185303 | 20.5
Virgin Islands (U.S.) | VIR | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Vietnam | VNM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.69999980926514 | 4.69999980926514 | 6.59999990463257 | 4.59999990463257 | 3.59999990463257 | 2.79999995231628 | 4.19999980926514 | 3.70000004768372 | 5.40000009536743 | 4.40000009536743 | 6.90000009536743 | 4.40000009536743 | 4.90000009536743 | 4.69999980926514 | 4.5 | 5.09999990463257 | 5.09999990463257 | 5.40000009536743 | 5.30000019073486 | 5.09999990463257 | 4.59999990463257 | 4.59999990463257
[NAME] | VUT | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
West Bank and Gaza | PSE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41 | 43.5 | 44.7000007629395 | 42.5999984741211 | 43.9000015258789 | 40.7999992370605 | 34.7999992370605 | 24.7999992370605 | 20.3999996185303 | 24.2999992370605 | 29.2999992370605 | 35.5999984741211 | 37.9000015258789 | 44.9000015258789 | 44.5 | 43.2000007629395 | 42.4000015258789 | 47.2000007629395 | 45.9000015258789 | 48.0999984741211 | 36.9000015258789 | 40
World | WLD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.17345513601892 | 13.08988179339894 | 13.86333560823466 | 13.59412852289368 | 14.15512262001216 | 14.45394297198718 | 14.97179872897981 | 14.83374513294603 | 14.91560606057344 | 15.44096529803295 | 15.42150346925457 | 15.60655767254855 | 15.44282060574653 | 15.17421228005272 | 15.38338182730798 | 14.77544635389192 | 13.74518382252194 | 14.20101106447939 | 14.81208723097194 | 15.1783584918142 | 15.10548599559831 | 15.13405030638536
Samoa | WSM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS
Yemen, Rep. | YEM | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 48.5999984741211 | 44.9000015258789 | 41.0999984741211 | 49.4000015258789 | 46.4000015258789 | 43.2999992370605 | 45.5 | 48.2000007629395 | 42.4000015258789 | 49.0999984741211 | 42.5 | 42.2999992370605 | 42.9000015258789 | 42.5 | 47.5999984741211 | 46.4000015258789 | 45.2999992370605 | 44.5 | 43.4000015258789 | 53.2999992370605 | 52.4000015258789 | 51.7000007629395
South Africa | ZAF | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 54.5 | 50.9000015258789 | 55.4000015258789 | 43.5999984741211 | 37 | 46.0999984741211 | 50.5 | 48.2000007629395 | 50.7000007629395 | 47.9000015258789 | 53.0999984741211 | 57.2999992370605 | 59.5 | 57.7000007629395 | 55 | 52.5999984741211 | 53.0999984741211 | 50.5 | 52.5 | 54.9000015258789 | 55.2999992370605 | 57.4000015258789
Congo, Dem. Rep. | COD | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1999998092651 | 14.3999996185303 | 14.6000003814697 | 13.8999996185303 | 13.5 | 13.6999998092651 | 14 | 13.6999998092651 | 13.8999996185303 | 14.1000003814697 | 13.8000001907349 | 13.3000001907349 | 13.1999998092651 | 13.1000003814697 | 13 | 13.1999998092651 | 13.1000003814697 | 13.1000003814697 | 13.3999996185303 | 13.1000003814697 | 13.1000003814697 | 13.1000003814697
Zambia | ZMB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.2999992370605 | 29.6000003814697 | 30.3999996185303 | 29.2999992370605 | 28.5 | 23.6000003814697 | 22.2999992370605 | 18.5 | 18.7999992370605 | 19.7999992370605 | 23.1000003814697 | 22.6000003814697 | 22.7999992370605 | 21.7999992370605 | 22.2999992370605 | 23.2999992370605 | 23.2999992370605 | 22.7000007629395 | 23.5 | 24.1000003814697 | 24.2000007629395 | 22.7999992370605
Zimbabwe | ZWE | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1999998092651 | 10.1999998092651 | 10.6000003814697 | 8.89999961853027 | 9.80000019073486 | 10.6000003814697 | 12.1000003814697 | 11.3999996185303 | 10.3000001907349 | 10.5 | 10.1000003814697 | 9 | 7.90000009536743 | 7 | 6.90000009536743 | 6.80000019073486 | 6.80000019073486 | 7.59999990463257 | 6.19999980926514 | 6.09999990463257 | 6.09999990463257 | 6.30000019073486