Spreadsheet: 3d2894b4-ee4e-46da-b0b4-dc6f759b4fbb
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 | 1960 | 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
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
Arab World | ARB | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.62865053592574 | 41.27276796438294 | 42.62571170995264 | 42.31554828333048 | 43.17069313038342 | 42.58115719178116 | 41.18439551815745 | 40.73025844076817 | 37.07777619412101 | 41.45952484335514 | 42.18470102174863 | 39.56245199566316 | 39.40419398835747 | 39.9259446978141 | 42.0667238497559 | 40.65171810880398 | 39.27124740720718 | 39.14079150360777 | 40.35310475183341 | 40.86942135637669 | 42.05646173222635 | 42.6970120367686
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
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 | 40.85185161118692 | 41.12747153073111 | 40.13617840179894 | 42.81323838918257 | 44.22954172366543 | 41.88262653210835 | 41.01950398887936 | 43.03866431439884 | 38.7830052064091 | 40.36664238640449 | 39.3743672473326 | 32.83793490518601 | 34.56109384509389 | 32.71226048073677 | 30.4459987650664 | 28.40526556674212 | 30.05515543462042 | 31.29781938086882 | 34.52666042630104 | 34.77694293594666 | 36.84988316465529
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 | 7.442812926586907 | 8.40801537092409 | 8.731816744079905 | 8.464306223386696 | 8.75046298961762 | 8.999911620744387 | 10.01111087448484 | 10.23294013799907 | 9.983700310230404 | 11.09197870349805 | 11.33646970187486 | 11.12961345621343 | 11.45188672670388 | 11.4004504698999 | 10.89073939737898 | 9.763937613754521 | 10.18848036877622 | 10.05840827202747 | 10.04485726883741 | 9.9293634315319 | 10.30100616893612
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.9302850560087 | 7.321207050928439 | 8.267776101951245 | 8.528737091724071 | 8.301552220950795 | 8.581604784823366 | 8.828877180046558 | 9.963108818417822 | 10.19110645269187 | 9.876000251078278 | 10.93484615944388 | 11.15240111745941 | 10.9945148659027 | 11.27905783484332 | 11.18689276539035 | 10.70155083364789 | 9.61100855378377 | 9.999499929593576 | 9.98335352040029 | 9.976760862748648 | 9.809734119843919 | 10.16410143414113
Europe & Central Asia (developing only) | ECA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.68761317430149 | 19.19372413665211 | 21.08319463251374 | 19.24001331707984 | 18.49126132804753 | 18.9556225734299 | 20.03953826896149 | 20.07633267334916 | 20.10903997061272 | 19.45846344893438 | 19.9697021892349 | 21.11423789245581 | 21.10711076918757 | 21.29876746309325 | 21.01779324721016 | 21.06636888622016 | 20.50023063274264 | 20.23941189907848 | 22.51286157310892 | 22.12513688026203 | 21.90682978495674 | 21.37186569207801
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.19371861095117 | 18.97737115919978 | 21.28350823697768 | 21.71806743302801 | 21.93378923282053 | 22.122367232343 | 22.85571038164893 | 22.61447822177449 | 22.35287181307136 | 20.81573039978605 | 19.89224887275686 | 20.03714554655575 | 20.46743878544686 | 20.56944183928611 | 20.07225088866657 | 19.49427583789736 | 17.8262142216671 | 17.65989318994899 | 20.70299270367325 | 21.02713043022172 | 21.16034856017269 | 21.81962887208467
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 | 25.58882991994485 | 24.37091181653328 | 21.56245095799252 | 19.26461753947912 | 19.58677526159443 | 19.42857836633996 | 19.94099891137819 | 20.16041092343059 | 19.28617755737046 | 17.55895501931273 | 17.52728853629584 | 21.11974540026302 | 22.36810607810256 | 23.43873543322981 | 26.01032050901862
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 | 24.29794340070796 | 25.17651397107861 | 25.14330590351183 | 25.10803186010123 | 24.41052883527252 | 22.43207642647898 | 22.40492574010284 | 21.22420151217499 | 20.252531615674 | 20.86389992285083 | 20.76499662758122 | 20.85848202756932 | 20.75179965124539 | 19.57788156890688 | 17.4316147252226 | 16.94387166277537 | 20.24973516731463 | 21.9691639978252 | 23.10899744405035 | 24.94089195879772
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 | 15.90255804136023 | 17.1322350889617 | 17.33958976002773 | 17.68372672656589 | 18.09280030258059 | 18.35535075493999 | 18.3894568046477 | 17.62433578480626 | 16.33652781497299 | 15.70667024672154 | 16.14545452635406 | 16.99504282559229 | 16.92337749641126 | 15.86673201634407 | 15.5576079447766 | 14.10929890180965 | 14.65617034664263 | 17.74112217896402 | 18.27262812160512 | 17.82126896270054 | 18.51968099243539
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 | 13.85885305446522 | 13.6743694524708 | 13.49984392469806 | 13.41673128011024 | 14.1133691350416 | 14.10103546793431 | 13.90338182588802 | 13.68479903338137 | 13.54845332123526 | 13.67948772261042 | 13.2949031509089 | 13.24650877190482 | 12.73076220534488 | 11.69614216547705 | 11.92718242736244 | 11.55435323649857 | 11.69386278411558 | 11.98889168881865 | 12.02958883632895 | 12.07390673577611 | 12.08989552365325
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.94390893680292 | 14.36190208871019 | 15.13979382099454 | 15.12758221876361 | 18.05720106621025 | 18.81345028091646 | 18.37527442936968 | 19.15460980900659 | 18.97480893134575 | 19.54146744655856 | 18.80441411523688 | 20.03300649792967 | 21.04690986098617 | 20.32784995975878 | 19.52365153938382 | 18.36182202637819 | 17.45251885055736 | 17.107840411729 | 18.56590348931705 | 18.08183615821886 | 16.92238102151694 | 16.63964325958916
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 | 19.73107481475356 | 18.99772308915053 | 20.21693698189678 | 21.20606890674221 | 20.48850186132304 | 19.70260661746678 | 18.54455958513264 | 17.60933738492517 | 17.31773771233195 | 18.78639016640785 | 18.24968898469394 | 17.11581549244853 | 16.78971543654403
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 | 12.7633765832836 | 12.46984787548612 | 13.01689853602036 | 12.60179507525441 | 12.71900583343461 | 13.29186053610916 | 13.0289476893857 | 12.62981377466423 | 12.04863280092599 | 12.12958406118987 | 12.61853158542177 | 12.70919336669571 | 12.4520430312181 | 12.68872119440615 | 13.19378135084005 | 12.83468222647943 | 12.87352019005147 | 12.95084664329308
Low income | LIC | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.86860725902571 | 11.06664984708062 | 10.8183863821384 | 10.73662338677632 | 10.90702300690192 | 10.90862914737252 | 11.28805599410382 | 10.95524500800018 | 11.16674661016876 | 11.48497067858042 | 11.35556381990108 | 11.00165519532471 | 10.28152001734589 | 10.35024158764968 | 10.70551289221358 | 10.79150260443746 | 10.56736262695856 | 10.89176615560324 | 11.37980261153056 | 10.65418702353865 | 10.72106166144148 | 10.8429692783399
[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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.76568348138866 | 13.01252822295564 | 14.11727333032681 | 13.38658121936256 | 13.69931165641946 | 13.75827594219149 | 14.73312856847438 | 14.01773532806478 | 14.2532566627014 | 15.86477340340363 | 16.22084560485445 | 16.39424349783183 | 16.04341577337961 | 15.95731265980654 | 17.03833823771155 | 16.17891671519889 | 14.56422995923774 | 15.09464930352354 | 14.86394797655787 | 15.73599864511397 | 15.87813853408459 | 15.5305649104782
Low & middle income | LMY | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.68982512032433 | 12.52968708668502 | 13.21980535114109 | 12.86488900015351 | 13.47492727519873 | 13.76037971908278 | 14.33442277236663 | 14.1717662377059 | 14.41798871283341 | 15.27991492540619 | 15.37126653921205 | 15.51270845780533 | 15.17636373126432 | 14.87903628467664 | 15.3037051385702 | 14.64790783851138 | 13.68718954604778 | 14.12951324782159 | 14.34863713864819 | 14.693529923151 | 14.68404646548228 | 14.61076907253743
[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
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.09000136204936 | 41.09578580667588 | 42.14747682898383 | 41.71265153844254 | 42.38228590159113 | 41.69050494419217 | 40.43690136937134 | 40.03654419312866 | 36.62053139710579 | 41.40385593921722 | 41.37036943717067 | 39.6484009437436 | 39.07366527653137 | 38.2438110095481 | 41.58965723861752 | 40.16909113927014 | 38.3627845766359 | 39.22440330236243 | 40.02107657347703 | 42.49087844459572 | 43.59862589374528 | 44.26676568346087
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.08610123435953 | 12.73961185430336 | 13.57218251048966 | 13.18429968523621 | 13.86885002859803 | 14.20716827318969 | 14.82137663565093 | 14.69533660698667 | 14.95524124009943 | 15.91415831113577 | 16.04748141389222 | 16.27560385712923 | 16.00654000875374 | 15.64992711281483 | 16.09112081496416 | 15.31398655594504 | 14.23203709911288 | 14.7030036430736 | 14.88403624201607 | 15.43838163637179 | 15.43476833762318 | 15.34718429111448
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.57106505331573 | 40.86903136812445 | 42.05380105415618 | 42.85788867139183 | 43.78389297619792 | 41.82615235512653 | 40.45791809095807 | 39.99737195272182 | 38.02045448053361 | 43.0681779702896 | 43.07936952002319 | 40.61206716499267 | 39.10998329467458 | 38.04455830344741 | 42.74049851622089 | 40.4364285528858 | 38.71718554948973 | 39.46397250447064 | 40.11078729121556 | 42.99177679388293 | 45.23784883590869 | 44.97258234860253
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 | 15.73907529808099 | 15.6591676250331 | 14.6831560273641
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.84810227839159 | 18.23604908571216 | 19.25888450129779 | 19.80323787076484 | 21.49014280720122 | 23.91813897482142 | 26.27931485750517 | 29.19663777764685 | 25.03128480037353 | 22.82732352514104 | 20.68315120283576 | 20.14263864423279 | 23.22759139013904 | 23.12085204751897 | 20.01645809787717 | 21.54944388465481 | 19.13181807098567 | 20.38384085463163 | 24.11112591001072 | 23.25725063387819 | 20.1236804864193 | 22.15499438339133
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 | 16.4959727710892 | 15.79106998828476 | 15.80253158795894 | 14.70184749447256 | 14.42640628061762 | 15.09960908012176 | 15.34323474851668 | 15.2666115713352 | 14.75347244855362 | 13.95267300251431 | 12.77106403672283 | 13.14545695888935 | 16.08841114366588 | 17.00703125826155 | 17.25448511946887 | 17.65580911823872
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 | 13.35858681172253 | 13.3715652812113 | 14.26169677129457 | 14.64135894042105 | 15.04291257068746 | 14.2448431488605 | 13.62042574274719 | 12.68800415689019 | 13.14748601355849 | 16.04050111396381 | 16.55740572800864 | 16.60453496581636 | 16.79373176174098
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 | 29.39366116658946 | 32.06594591090608 | 34.5422103956378 | 33.6347331053668 | 31.3659494105065 | 33.92847731073922 | 34.34123614241226 | 33.75594206712307 | 32.06237633744069 | 29.39752819946398 | 33.33687228038983 | 30.46614008476309 | 31.1343433863515 | 30.68019274734569 | 30.02102736194329
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 | 8.92181471772428 | 10.27574580654347 | 10.16577953673081 | 11.66594168837996 | 9.68492994896555 | 10.48613111418341 | 12.49857881980875 | 11.46852796362457 | 11.66299697263619 | 10.71404055347644 | 10.11440151379924 | 11.31879540735902 | 10.65132957061915 | 9.692554165876567 | 10.70398671598168 | 10.54312191506593 | 11.29678292389996 | 11.30064565620718 | 10.85057818199359
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
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.65254347917871 | 16.47224822566449 | 16.64280218003545 | 15.51367329166751 | 14.94470116062249 | 16.00031678674211 | 16.41211133396062 | 15.95514020875375 | 16.21340071217994 | 15.96919296110203 | 16.33746402235705 | 16.18215938007749 | 16.27049177701448 | 15.70759316075931 | 14.94412600946743 | 14.92718887886786 | 14.60165220578196 | 14.67335800440059 | 14.84493987981933 | 14.87531479534376 | 14.87109691434874 | 14.85961544592322
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 | 15.51189265216044 | 14.9432519749997 | 15.99674021267464 | 16.40644831073217 | 15.95298185007359 | 16.21099918910883 | 15.9671256096345 | 16.33342958902562 | 16.17968079390663 | 16.26807843237966 | 15.70433941879687 | 14.94265268131859 | 14.92612463018054 | 14.59988830850234 | 14.67173555997824 | 14.84418938761223 | 14.87445281775986 | 14.86983275730031 | 14.85844246227654
Small states | SST | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.44038019202988 | 33.49681422032996 | 34.21606879120846 | 33.68328331176008 | 34.06286610780662 | 33.81230166765591 | 33.82605299821769 | 31.87309759281352 | 34.13328928543084 | 34.74776591265287 | 34.32864633725185 | 32.44260919360122 | 32.97486088106859 | 33.32298427590999 | 32.47734838765548 | 30.95012559430509 | 28.78272046699349 | 32.0444971891174 | 30.20940370334059 | 31.36428748935027 | 31.05908123460141 | 30.9981773470953
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.50312719222904 | 12.49891489042532 | 13.07633936790996 | 12.9943942835968 | 14.03293427043704 | 14.65450178744085 | 14.91178886151904 | 15.40634573929529 | 15.70461839267709 | 15.96733511335692 | 15.860914470396 | 16.1489344146018 | 15.96760584170834 | 15.32843614874831 | 15.10469724068301 | 14.41187434610532 | 13.88322205857474 | 14.28680617265718 | 14.90575503461819 | 15.10918193609981 | 14.92996094321204 | 15.1310660624554
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.17375184014845 | 13.09045232911948 | 13.86403450537585 | 13.59478114606282 | 14.15572026180646 | 14.45405282748502 | 14.97160870177557 | 14.83281407562415 | 14.91466432362721 | 15.441605504359 | 15.42191793262647 | 15.60692198110671 | 15.44326603970577 | 15.17491876975886 | 15.38414412393833 | 14.77635257792565 | 13.74616080766796 | 14.202408737788 | 14.81399385179893 | 15.18054243391285 | 15.10799497886942 | 15.1347125887537
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