Spreadsheet: 3e4c5781-9372-4489-b3f6-1ca535c67f2d
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, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Andorra | AND | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Afghanistan | AFG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.5 | 18.6000003814697 | 18.3999996185303 | 18.7000007629395 | 18.7000007629395 | 18.7000007629395 | 18.6000003814697 | 18.6000003814697 | 18.6000003814697 | 18 | 17.8999996185303 | 18 | 18.6000003814697 | 17.7000007629395 | 12.5 | 12.3999996185303 | 12.6000003814697 | 12.3000001907349 | 12.6999998092651 | 12.3999996185303 | 12.3999996185303 | 13.1000003814697
Angola | AGO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8 | 8.30000019073486 | 9.19999980926514 | 8 | 7.40000009536743 | 7.19999980926514 | 7.90000009536743 | 8.10000038146973 | 8 | 8 | 8 | 7.5 | 8 | 7.69999980926514 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7.5 | 8 | 8 | 8 | 7.90000009536743
Albania | ALB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.5 | 28.1000003814697 | 33.0999984741211 | 33 | 32.9000015258789 | 30 | 32.2999992370605 | 29.5 | 29.7999992370605 | 14.3000001907349 | 28.8999996185303 | 15.6999998092651 | 12.3999996185303 | 12.5 | 12.1999998092651 | 13.1000003814697 | 12.6999998092651 | 13.8999996185303 | 16.3999996185303 | 17.1000003814697 | 17.2000007629395 | 17.8999996185303
Andean Region | ANR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Arab World | ARB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.72034125072796 | 20.50034594204593 | 21.45008188311525 | 21.22643331748577 | 21.49133201597287 | 21.25489272738554 | 20.40176786625296 | 19.93343855042441 | 19.32178428052814 | 20.98284157166536 | 20.95740415014173 | 21.13722160245021 | 21.13379409568887 | 20.03618035992268 | 19.8582003889617 | 18.90426225929484 | 17.56914901043459 | 17.59719168305593 | 18.16190926922569 | 18.29625549755807 | 19.42201735072604 | 19.51843686787495
United Arab Emirates | ARE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 6.19999980926514 | 6.19999980926514 | 4.80000019073486 | 2.29999995231628 | 12 | 6.90000009536743 | 6.40000009536743 | 5.90000009536743 | 5.80000019073486 | 6 | 6.30000019073486 | 6.5 | 6.80000019073486 | 7 | 7.69999980926514 | 8.39999961853027 | 12.8999996185303 | 12.8000001907349 | 12.6999998092651 | 12.6000003814697 | 11.6000003814697
Argentina | ARG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.40000009536743 | 6.5 | 13.3000001907349 | 14.6000003814697 | 22.2999992370605 | 20.2000007629395 | 18.2000007629395 | 15 | 15.6999998092651 | 17.1000003814697 | 17.5 | 18.7999992370605 | 18.7999992370605 | 14.6000003814697 | 12.6000003814697 | 12.6000003814697 | 11 | 9.80000019073486 | 9.89999961853027 | 9.19999980926514 | 8.60000038146973 | 8.39999961853027
Armenia | ARM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.3999996185303 | 21.1000003814697 | 20.7999992370605 | 25.2999992370605 | 31.3999996185303 | 24.1000003814697 | 21.2000007629395 | 31.3999996185303 | 21.7999992370605 | 29 | 40.0999984741211 | 33.7999992370605 | 35.2000007629395 | 36.2999992370605 | 34.7000007629395 | 27.3999996185303 | 36.2000007629395 | 32.0999984741211 | 19.8999996185303 | 21.3999996185303 | 20.2999992370605 | 20.7000007629395
American Samoa | ASM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
[NAME] and [NAME] | ATG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Australia | AUS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.19999980926514 | 10 | 10.1000003814697 | 9.39999961853027 | 8.10000038146973 | 8.19999980926514 | 8.19999980926514 | 7.40000009536743 | 6.69999980926514 | 6.09999990463257 | 6.40000009536743 | 6.19999980926514 | 6 | 5.5 | 5.19999980926514 | 4.90000009536743 | 4.80000019073486 | 4.59999990463257 | 5.40000009536743 | 5.40000009536743 | 5.30000019073486 | 5.30000019073486
Austria | AUT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 3.79999995231628 | 4.59999990463257 | 4 | 4.30000019073486 | 4.5 | 4.69999980926514 | 4.59999990463257 | 3.90000009536743 | 3.79999995231628 | 3.79999995231628 | 3.90000009536743 | 4.19999980926514 | 5.40000009536743 | 5.40000009536743 | 5.19999980926514 | 5 | 4.09999990463257 | 4.5 | 4.19999980926514 | 4.30000019073486 | 4.30000019073486
Azerbaijan | AZE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.59999990463257 | 6.69999980926514 | 6.59999990463257 | 6.59999990463257 | 4.90000009536743 | 6.59999990463257 | 6.5 | 6.40000009536743 | 5 | 5.30000019073486 | 5.30000019073486 | 7.30000019073486 | 5.09999990463257 | 5 | 6.59999990463257 | 6.80000019073486 | 6.69999980926514 | 6.5
Burundi | BDI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8 | 8.19999980926514 | 8.5 | 8.39999961853027 | 8.60000038146973 | 8.60000038146973 | 8.30000019073486 | 8.10000038146973 | 8.5 | 8.5 | 8.5 | 8.5 | 8.5 | 8.39999961853027 | 8.39999961853027 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.19999980926514 | 8.10000038146973 | 8.19999980926514
Belgium | BEL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6000003814697 | 9.5 | 10.8000001907349 | 12.3999996185303 | 12.1999998092651 | 12.3999996185303 | 11.6000003814697 | 11.6999998092651 | 10.1999998092651 | 8.30000019073486 | 6.90000009536743 | 8.60000038146973 | 8.89999961853027 | 9.5 | 9.5 | 9.30000019073486 | 8.39999961853027 | 7.59999990463257 | 8.10000038146973 | 8.5 | 7.19999980926514 | 7.40000009536743
Benin | [NAME] | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.600000023841858 | 0.600000023841858 | 0.5 | 0.5 | 0.5 | 0.5 | 0.699999988079071 | 0.899999976158142 | 0.699999988079071 | 0.600000023841858 | 0.5 | 0.400000005960464 | 0.899999976158142 | 0.600000023841858 | 0.699999988079071 | 1.29999995231628 | 1.20000004768372 | 1.10000002384186 | 1.10000002384186 | 1.20000004768372 | 1.20000004768372 | 1.10000002384186
[NAME] | BFA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.89999997615814 | 1.70000004768372 | 2.29999995231628 | 1.89999997615814 | 1.70000004768372 | 1.79999995231628 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 2.20000004768372 | 1.70000004768372 | 2.09999990463257 | 2 | 2 | 1.89999997615814 | 1.70000004768372 | 2.40000009536743 | 2.40000009536743 | 2.40000009536743 | 2.29999995231628 | 2.40000009536743 | 2.29999995231628
Bangladesh | BGD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.70000004768372 | 3.20000004768372 | 3 | 2.79999995231628 | 2.59999990463257 | 2.20000004768372 | 2.70000004768372 | 2.20000004768372 | 3 | 3.29999995231628 | 3.40000009536743 | 3.5 | 4.59999990463257 | 5.30000019073486 | 6.5 | 5.40000009536743 | 5.5 | 5.59999990463257 | 6.40000009536743 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514
Bulgaria | BGR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.7000007629395 | 13.6999998092651 | 21.1000003814697 | 19.7000007629395 | 15.3999996185303 | 13.1999998092651 | 13.3000001907349 | 11.8000001907349 | 13.6000003814697 | 15.8000001907349 | 18.7000007629395 | 17.2999992370605 | 13.1999998092651 | 11.6000003814697 | 9.80000019073486 | 9.30000019073486 | 7.30000019073486 | 5.69999980926514 | 6.59999990463257 | 9.5 | 10.1000003814697 | 10.8000001907349
Bahrain | BHR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6000003814697 | 16.6000003814697 | 15.3000001907349 | 14.1999998092651 | 10.6999998092651 | 10.6000003814697 | 10.6000003814697 | 10.3999996185303 | 10.3000001907349 | 12.8999996185303 | 10.1999998092651 | 12.6000003814697 | 14.8999996185303 | 19.2000007629395 | 19.1000003814697 | 19 | 18.8999996185303 | 18.7000007629395 | 18.6000003814697 | 18.5 | 18.3999996185303 | 18
Bahamas, The | BHS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12 | 15.6000003814697 | 13.1999998092651 | 14.8000001907349 | 11.6999998092651 | 14.5 | 11.3000001907349 | 9.69999980926514 | 9.39999961853027 | 8.80000019073486 | 7.40000009536743 | 9.30000019073486 | 11.6999998092651 | 11.1000003814697 | 11.3000001907349 | 8.5 | 9.19999980926514 | 9.60000038146973 | 15.6999998092651 | 15.5 | 15.1000003814697 | 15.1000003814697
Bosnia and Herzegovina | BIH | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.7000007629395 | 25.5 | 27 | 29.6000003814697 | 26.7999992370605 | 27.2999992370605 | 30.5 | 28.3999996185303 | 27.7000007629395 | 27 | 29.5 | 26.3999996185303 | 27.7999992370605 | 31.3999996185303 | 27.8999996185303 | 35.5999984741211 | 33.7000007629395 | 27.3999996185303 | 25.7000007629395 | 29.7000007629395 | 30 | 30.5
Belarus | BLR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.3000001907349 | 9.89999961853027 | 10 | 9.80000019073486 | 9.89999961853027 | 10.5 | 10.6999998092651 | 10.6000003814697 | 10.3999996185303 | 10.3999996185303 | 10.3999996185303 | 10.3000001907349 | 10.3999996185303 | 10.5 | 10.3999996185303 | 10.3000001907349 | 10.3000001907349 | 10.1999998092651 | 9.89999961853027 | 10.1000003814697 | 10 | 9.69999980926514
Belize | BLZ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 17.1000003814697 | 15.5 | 16.2000007629395 | 18.2000007629395 | 18.7000007629395 | 21.1000003814697 | 21.7999992370605 | 20.5 | 16.6000003814697 | 13.6999998092651 | 15 | 15.3000001907349 | 15.6000003814697 | 17.2999992370605 | 13.8000001907349 | 12.5 | 12 | 12.3999996185303 | 12 | 12 | 11.3999996185303
Bermuda | BMU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Bolivia | BOL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6.69999980926514 | 5.90000009536743 | 6.5 | 6.5 | 6.30000019073486 | 6.09999990463257 | 5.90000009536743 | 5.30000019073486 | 5.90000009536743 | 6.40000009536743 | 6.80000019073486 | 6.19999980926514 | 5.30000019073486 | 6.59999990463257 | 6.5 | 6.30000019073486 | 3.5 | 4.09999990463257 | 4.09999990463257 | 4 | 3.90000009536743
Brazil | BRA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1000003814697 | 8 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 8.69999980926514 | 9.89999961853027 | 11.5 | 12.1000003814697 | 12 | 11.8999996185303 | 11.6000003814697 | 12.3999996185303 | 11.6999998092651 | 12.1999998092651 | 11 | 10.8000001907349 | 9.69999980926514 | 11.1000003814697 | 10.5 | 9 | 9.10000038146973
Barbados | BRB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.1000003814697 | 26.1000003814697 | 29.3999996185303 | 28.3999996185303 | 23.1000003814697 | 17.8999996185303 | 18.2999992370605 | 16.3999996185303 | 13.3999996185303 | 11.6000003814697 | 11.8999996185303 | 12.3000001907349 | 12.6999998092651 | 11.8000001907349 | 11 | 10.5 | 8.89999961853027 | 9.80000019073486 | 12.1000003814697 | 13 | 13.5 | 13.8999996185303
[NAME] | BRN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 4.59999990463257 | 4.09999990463257 | 5.09999990463257 | 4.80000019073486 | 4.5 | 3.90000009536743 | 3.90000009536743 | 4.80000019073486 | 4.40000009536743 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 3.59999990463257 | 3.5 | 3.5 | 3.5 | 3.40000009536743 | 3.70000004768372 | 3.90000009536743 | 4 | 4
Bhutan | BTN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.29999995231628 | 2.40000009536743 | 2.40000009536743 | 2.5 | 3.90000009536743 | 1.89999997615814 | 2 | 1.79999995231628 | 1.79999995231628 | 2.09999990463257 | 2.40000009536743 | 2.29999995231628 | 2.20000004768372 | 3.09999990463257 | 3.40000009536743 | 3.59999990463257 | 4.59999990463257 | 4.90000009536743 | 5.80000019073486 | 4.30000019073486 | 4.80000019073486 | 2.29999995231628
Botswana | BWA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.2999992370605 | 24.2999992370605 | 24.7999992370605 | 22.7000007629395 | 23.1000003814697 | 23.6000003814697 | 23.2000007629395 | 23.5 | 23.5 | 27.6000003814697 | 25.7999992370605 | 24.2000007629395 | 26.8999996185303 | 25.8999996185303 | 24.8999996185303 | 19.8999996185303 | 21.3999996185303 | 24.3999996185303 | 21.3999996185303 | 21.7000007629395 | 21.7000007629395 | 21
Sub-Saharan Africa (IFC classification) | CAA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Central African Republic | CAF | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 7.80000019073486 | 7.80000019073486 | 8.39999961853027 | 7.69999980926514 | 7.90000009536743 | 7.90000009536743 | 8 | 8.10000038146973 | 8.10000038146973 | 8.39999961853027 | 8 | 8 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.80000019073486 | 7.80000019073486
Canada | CAN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.69999980926514 | 10.1999998092651 | 10.6999998092651 | 9.80000019073486 | 9.10000038146973 | 9.30000019073486 | 8.89999961853027 | 8 | 7.30000019073486 | 6.69999980926514 | 6.90000009536743 | 7.09999990463257 | 7.19999980926514 | 6.90000009536743 | 6.5 | 6.09999990463257 | 5.59999990463257 | 5.59999990463257 | 7 | 7.19999980926514 | 7 | 6.80000019073486
East Asia and the Pacific (IFC classification) | CEA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Central Europe and the Baltics | CEB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.2549367810105 | 10.80884109933961 | 12.22472563426251 | 12.39700690522062 | 11.47809528674849 | 10.55421057048 | 10.07419922680736 | 9.6706218790658 | 10.64814500601749 | 12.7875672686747 | 13.58786178977057 | 14.07479765572675 | 13.42901155892837 | 13.11473629577895 | 12.59351348294642 | 10.53301396088933 | 8.139367978224817 | 6.944172652482299 | 8.391531856260706 | 9.847044810654225 | 9.902832480160365 | 10.14789800887475
Europe and Central Asia (IFC classification) | CEU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Switzerland | CHE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.40000009536743 | 3.5 | 4.59999990463257 | 4.30000019073486 | 3.79999995231628 | 4 | 3.90000009536743 | 4.19999980926514 | 3.59999990463257 | 3.09999990463257 | 3.5 | 3.09999990463257 | 4.5 | 4.80000019073486 | 5.09999990463257 | 4.69999980926514 | 4.5 | 4 | 4.5 | 5 | 4.40000009536743 | 4.5
Channel Islands | CHI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Chile | CHL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8999996185303 | 10.6999998092651 | 10.3999996185303 | 9.89999961853027 | 8.80000019073486 | 7.90000009536743 | 7.69999980926514 | 7.59999990463257 | 10.6999998092651 | 10.1000003814697 | 9.69999980926514 | 9.60000038146973 | 9.69999980926514 | 10.5 | 9.80000019073486 | 9.39999961853027 | 8.60000038146973 | 9.60000038146973 | 10.8000001907349 | 9.69999980926514 | 8.69999980926514 | 7.90000009536743
China | CHN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 3.70000004768372 | 3.59999990463257 | 3.59999990463257 | 3.79999995231628 | 3.79999995231628 | 3.90000009536743 | 4 | 3.90000009536743 | 3.79999995231628 | 3.79999995231628 | 3.70000004768372 | 3.59999990463257 | 3.59999990463257 | 3.40000009536743 | 3.29999995231628 | 3.09999990463257 | 3.59999990463257 | 3.59999990463257 | 3.40000009536743 | 3.59999990463257 | 3.70000004768372
Cote d'Ivoire | CIV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 5.59999990463257 | 5 | 4.5 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743 | 3.29999995231628
Latin America and the Caribbean (IFC classification) | CLA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Middle East and North Africa (IFC classification) | CME | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Cameroon | CMR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.30000019073486 | 6.30000019073486 | 6.30000019073486 | 6.30000019073486 | 3.79999995231628 | 9 | 8.60000038146973 | 8.19999980926514 | 7.80000019073486 | 6.69999980926514 | 8.30000019073486 | 6.09999990463257 | 6.19999980926514 | 5 | 4.90000009536743 | 4.19999980926514 | 4.5 | 5.09999990463257 | 5.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514
Congo, Rep. | COG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 7.80000019073486 | 7.90000009536743 | 8.10000038146973 | 7.69999980926514 | 7.59999990463257 | 7.80000019073486 | 7.59999990463257 | 7.90000009536743 | 7.40000009536743 | 7.59999990463257 | 7.5 | 7.69999980926514 | 7.5 | 7.30000019073486 | 7.40000009536743 | 7.69999980926514 | 7.40000009536743 | 7.30000019073486 | 7.19999980926514 | 7.40000009536743 | 7.40000009536743
Colombia | COL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.2000007629395 | 15.1000003814697 | 16 | 16 | 16 | 18.8999996185303 | 17.2999992370605 | 18.6000003814697 | 20.1000003814697 | 21.6000003814697 | 19.2000007629395 | 19 | 15.5 | 15.3000001907349 | 14.8000001907349 | 13.5 | 14.8999996185303 | 17.5 | 15.6000003814697 | 15.1000003814697 | 14.1000003814697 | 13.5
Comoros | COM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.5 | 7.80000019073486 | 8.10000038146973 | 8.39999961853027 | 8 | 8.19999980926514 | 8 | 8.10000038146973 | 8 | 8 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 8 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.5 | 7.5
Cabo Verde | CPV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.60000038146973 | 8.5 | 8.19999980926514 | 8.19999980926514 | 8.19999980926514 | 8.19999980926514 | 8.19999980926514 | 8.19999980926514 | 8 | 8.19999980926514 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.19999980926514 | 8 | 8 | 8.10000038146973 | 8.10000038146973 | 8 | 8 | 7.90000009536743
Costa Rica | CRI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 5.69999980926514 | 5.40000009536743 | 6 | 6.80000019073486 | 8.60000038146973 | 7.69999980926514 | 8.39999961853027 | 8.30000019073486 | 7 | 7.90000009536743 | 8.10000038146973 | 8.39999961853027 | 8.69999980926514 | 9.69999980926514 | 9 | 7.09999990463257 | 6.40000009536743 | 10.3000001907349 | 9.69999980926514 | 10.6000003814697 | 10.5
South Asia (IFC classification) | CSA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Caribbean small states | CSS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.21682176069432 | 22.03262138635948 | 22.5191045757438 | 22.20577375559499 | 22.13750934500481 | 22.15572796947869 | 21.72092268724078 | 20.33692815443213 | 20.65956011747582 | 18.77625629872369 | 18.8325322292077 | 18.14252418379422 | 16.8409643518874 | 15.55519770037741 | 14.88773445519473 | 13.75322627001391 | 12.69033279404477 | 13.37576751351342 | 13.97147258670871 | 14.59538501406179 | 14.9250182451273 | 15.29545733297556
Cuba | CUB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.90000009536743 | 4.59999990463257 | 4.90000009536743 | 4 | 9.89999961853027 | 9 | 8.39999961853027 | 7.40000009536743 | 7.5 | 6.40000009536743 | 4.90000009536743 | 3.90000009536743 | 2.70000004768372 | 2.29999995231628 | 2.29999995231628 | 2.20000004768372 | 1.89999997615814 | 2 | 2 | 3 | 2.90000009536743 | 2.90000009536743
[NAME] | CUW | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Cayman Islands | CYM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Cyprus | CYP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.60000038146973 | 2.5 | 8.60000038146973 | 4.30000019073486 | 4.90000009536743 | 5.5 | 4.09999990463257 | 7.19999980926514 | 6.69999980926514 | 7.40000009536743 | 5.80000019073486 | 4.09999990463257 | 4.5 | 5.30000019073486 | 6.40000009536743 | 5.40000009536743 | 4.40000009536743 | 4.19999980926514 | 5.5 | 6.40000009536743 | 7.59999990463257 | 11
Czech Republic | CZE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.09999990463257 | 3.79999995231628 | 5.40000009536743 | 5.19999980926514 | 4.80000019073486 | 4.69999980926514 | 5.90000009536743 | 8.30000019073486 | 10.5 | 10.6000003814697 | 9.89999961853027 | 9 | 9.89999961853027 | 9.89999961853027 | 9.80000019073486 | 8.80000019073486 | 6.69999980926514 | 5.59999990463257 | 7.69999980926514 | 8.5 | 7.90000009536743 | 8.19999980926514
Germany | DEU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 8.39999961853027 | 9.60000038146973 | 10.1000003814697 | 9.39999961853027 | 9.60000038146973 | 10.6000003814697 | 9.89999961853027 | 8.89999961853027 | 8.10000038146973 | 7.90000009536743 | 8.30000019073486 | 8.80000019073486 | 10 | 10.8999996185303 | 10.1999998092651 | 8.80000019073486 | 7.69999980926514 | 7.30000019073486 | 6.59999990463257 | 5.59999990463257 | 5.19999980926514
Djibouti | DJI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Dominica | DMA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Denmark | DNK | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10 | 9.89999961853027 | 11.1000003814697 | 9 | 8.60000038146973 | 8.39999961853027 | 6.5 | 6.40000009536743 | 5.90000009536743 | 5 | 4.80000019073486 | 5 | 6.09999990463257 | 6 | 5.30000019073486 | 4.5 | 4.19999980926514 | 3.70000004768372 | 5.30000019073486 | 6.5 | 7.5 | 7.5
Dominican Republic | DOM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.5 | 36.2000007629395 | 34.2999992370605 | 27.1000003814697 | 25.7000007629395 | 27.6000003814697 | 25.8999996185303 | 23.7000007629395 | 22.6000003814697 | 23.6000003814697 | 22.2000007629395 | 18.7999992370605 | 26.7000007629395 | 29.2999992370605 | 28.6000003814697 | 25.8999996185303 | 25.6000003814697 | 22.6000003814697 | 23 | 18.5 | 19 | 19.2000007629395
Algeria | DZA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 37.4000015258789 | 41.7000007629395 | 42 | 44.2000007629395 | 51.2999992370605 | 53.9000015258789 | 45.5 | 45.7999992370605 | 45.7000007629395 | 53.7000007629395 | 49.5 | 44.9000015258789 | 39.2000007629395 | 22.2999992370605 | 25.8999996185303 | 20.6000003814697 | 22.7999992370605 | 18.2000007629395 | 18.2999992370605 | 19.3999996185303 | 19.2999992370605 | 18.6000003814697
East Asia & Pacific (developing only) | EAP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.329791854001063 | 3.677648642076867 | 3.824979809716305 | 3.839424509791678 | 3.849072831381736 | 3.870192307855943 | 4.003981150605743 | 4.266297940032053 | 4.206554347339534 | 4.109933973642652 | 4.524464603452858 | 4.434662843969959 | 4.486277203918661 | 4.518386783416791 | 4.336778023280706 | 4.197627394755655 | 3.839979627711756 | 4.130858866286085 | 4.062588816894726 | 3.918694485657357 | 3.959803864579987 | 4.034005340938949
East Asia & Pacific (all income levels) | EAS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.191123344009552 | 3.611029073181421 | 3.777263462210818 | 3.795967964523742 | 3.809719043290845 | 3.831624202663833 | 3.964561515016623 | 4.304624143421944 | 4.265492318353699 | 4.141259710736204 | 4.530028232546197 | 4.459745280716243 | 4.506749816632979 | 4.498318329831283 | 4.316835850060905 | 4.152968573158653 | 3.8141052914964 | 4.081776503965571 | 4.092993933367974 | 3.955577164639583 | 3.961027268606724 | 4.021653399705093
Europe & Central Asia (developing only) | ECA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.649783393799018 | 9.998596279732508 | 11.01966059707636 | 10.0294750824049 | 9.849244666470605 | 10.0329802234773 | 10.44727574609322 | 10.87835148083278 | 10.91886854513231 | 10.75379214019965 | 10.86978903605759 | 10.72403550883432 | 10.36142985333612 | 10.46122016267039 | 10.18074800790298 | 10.05826348796643 | 9.628885943739633 | 9.323892585317173 | 10.49380392396178 | 10.4893139871048 | 10.15564401755876 | 9.96561369947612
Europe & Central Asia (all income levels) | ECS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.3915546025408 | 9.396674294190577 | 10.4551006412518 | 10.94526880102153 | 10.94359164949325 | 10.9787036016545 | 11.43954258628572 | 11.5801320594369 | 11.36640969495583 | 10.59157175977527 | 9.767542933030436 | 9.598460132794651 | 9.579310779162896 | 9.626678348081631 | 9.286730550575918 | 8.799700935265726 | 7.857439025022508 | 7.634461491912628 | 9.051786399630721 | 9.244534168213583 | 9.058416740719974 | 9.320001089869324
Ecuador | ECU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.30000019073486 | 9 | 7.40000009536743 | 10.1999998092651 | 7.40000009536743 | 8 | 9.19999980926514 | 6.69999980926514 | 8.10000038146973 | 9.60000038146973 | 11.1999998092651 | 11.1999998092651 | 12.3000001907349 | 8.80000019073486 | 8.60000038146973 | 8.19999980926514 | 6.59999990463257 | 7.90000009536743 | 8.60000038146973 | 6.59999990463257 | 5.5 | 5.90000009536743
Egypt, Arab Rep. | EGY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.8999996185303 | 21.1000003814697 | 26.2000007629395 | 26.2000007629395 | 27.1000003814697 | 22 | 20.7999992370605 | 20.6000003814697 | 19.8999996185303 | 22.2999992370605 | 23.2999992370605 | 25.6000003814697 | 25.7000007629395 | 26.1000003814697 | 27.1000003814697 | 25.2000007629395 | 19.5 | 20.8999996185303 | 23.3999996185303 | 22.2000007629395 | 27.5 | 27.1000003814697
Euro area | EMU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.4023664437816 | 11.86294284267067 | 13.19172629302806 | 14.05315526523699 | 13.82617734148124 | 13.89716018061637 | 13.91826433410471 | 13.39046260994756 | 12.55700609529823 | 11.37696287334605 | 9.88513752537072 | 10.05760841254304 | 10.11301763775989 | 10.44181643322919 | 10.15303927848597 | 9.522000590963804 | 8.544577632867824 | 8.343497172088263 | 9.727614456485727 | 10.31202172468877 | 10.40112110183182 | 11.55327221102813
Eritrea | ERI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.69999980926514 | 8.69999980926514 | 8.10000038146973 | 7.80000019073486 | 8.69999980926514 | 8.39999961853027 | 8.5 | 8.80000019073486 | 8.89999961853027 | 9.5 | 8.5 | 8.80000019073486 | 9 | 8.80000019073486 | 8.69999980926514 | 8.80000019073486 | 8.60000038146973 | 9.10000038146973 | 8.39999961853027 | 8.39999961853027 | 8 | 8.10000038146973
Spain | ESP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.5 | 26.2000007629395 | 29.8999996185303 | 32.0999984741211 | 31.2999992370605 | 30.2999992370605 | 28.8999996185303 | 27.2000007629395 | 23.5 | 20.8999996185303 | 15.3999996185303 | 16.6000003814697 | 16.1000003814697 | 15.1999998092651 | 12.3000001907349 | 11.6999998092651 | 11 | 13.1999998092651 | 18.5 | 20.6000003814697 | 22.2999992370605 | 25.6000003814697
Estonia | EST | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.39999997615814 | 3.29999995231628 | 6 | 6.90000009536743 | 8.80000019073486 | 9 | 9.5 | 8.5 | 10.1000003814697 | 11.5 | 13.1000003814697 | 8.5 | 10.3999996185303 | 8.69999980926514 | 7 | 5.59999990463257 | 3.90000009536743 | 5.30000019073486 | 10.6000003814697 | 14.3000001907349 | 11.8000001907349 | 9.19999980926514
Ethiopia | ETH | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8000001907349 | 11.8999996185303 | 10.6000003814697 | 11.1000003814697 | 12.8999996185303 | 13 | 13 | 13 | 13.1000003814697 | 12.5 | 12 | 11 | 10.1000003814697 | 9.19999980926514 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027
European Union | EUU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.40279909115112 | 10.86492692252326 | 12.14986253661542 | 12.60912190735418 | 12.20055055829921 | 11.99815033721868 | 11.78349607201358 | 11.27637234747584 | 10.8857109341226 | 10.55380810256468 | 9.700941476064495 | 9.919907440263625 | 9.81431784920299 | 9.97554643052027 | 9.726129386271356 | 8.999411706952513 | 7.890920975240755 | 7.492463636512515 | 8.89410095410228 | 9.593644535109561 | 9.723414470014886 | 10.55457415008491
Fragile and conflict affected situations | FCS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.744860108106803 | 8.788805002116836 | 8.635604006128888 | 8.633840139925288 | 8.49852989281161 | 8.731262532223345 | 8.877482137796298 | 8.810731162287716 | 8.360958759966927 | 8.539454272913733 | 8.63129432361301 | 8.540470946773125 | 8.659312729021456 | 8.551195162641376 | 8.221640760086093 | 8.375342604307312 | 8.42655188755084 | 8.457133195282923 | 8.310425613399488 | 8.40046189219978 | 8.336881474793193 | 8.349237856813138
Finland | FIN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5 | 9.60000038146973 | 14.3999996185303 | 14.8999996185303 | 15.1000003814697 | 14.8000001907349 | 13 | 12.1000003814697 | 10.6000003814697 | 10.6000003814697 | 9.69999980926514 | 9.10000038146973 | 8.89999961853027 | 9 | 8.69999980926514 | 8 | 7.19999980926514 | 6.69999980926514 | 7.5 | 7.69999980926514 | 7.09999990463257 | 7
Fiji | FJI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.60000038146973 | 7.69999980926514 | 8.39999961853027 | 8 | 7.5 | 7.80000019073486 | 9.19999980926514 | 11.5 | 11.1000003814697 | 10.6000003814697 | 8.5 | 8 | 11.8000001907349 | 6.59999990463257 | 6.40000009536743 | 9.10000038146973 | 12.1999998092651 | 12.6000003814697 | 12.1999998092651 | 12.1000003814697 | 11.8999996185303 | 11.8000001907349
France | FRA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 12.6999998092651 | 13.3000001907349 | 14.3999996185303 | 14 | 14.3999996185303 | 14.3000001907349 | 14 | 13.8999996185303 | 12.1999998092651 | 10.5 | 9.80000019073486 | 9.60000038146973 | 10.3000001907349 | 9.80000019073486 | 9.69999980926514 | 8.60000038146973 | 7.90000009536743 | 9.30000019073486 | 9.69999980926514 | 9.69999980926514 | 10
Faeroe Islands | FRO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Micronesia, Fed. [NAME]. | FSM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Gabon | GAB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.2999992370605 | 19.7999992370605 | 15.6999998092651 | 17.3999996185303 | 19.5 | 21.2000007629395 | 23.1000003814697 | 22.7000007629395 | 22.3999996185303 | 22 | 21.6000003814697 | 21.2999992370605 | 20.8999996185303 | 20.6000003814697 | 20.2000007629395 | 20 | 19.7000007629395 | 22.3999996185303 | 25.5 | 27.5 | 27.5 | 26.2000007629395
United Kingdom | GBR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 7.40000009536743 | 7.80000019073486 | 7.40000009536743 | 6.90000009536743 | 6.40000009536743 | 5.90000009536743 | 5.40000009536743 | 5.09999990463257 | 4.90000009536743 | 4.19999980926514 | 4.40000009536743 | 4.19999980926514 | 4.30000019073486 | 4.30000019073486 | 5 | 5 | 4.80000019073486 | 6.5 | 6.80000019073486 | 7.09999990463257 | 7.40000009536743
Georgia | GEO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 10.3000001907349 | 10.8999996185303 | 11.8000001907349 | 13.1000003814697 | 11.8000001907349 | 11.8000001907349 | 11.8999996185303 | 12.1999998092651 | 10.3999996185303 | 10.6999998092651 | 11 | 11.5 | 11.8000001907349 | 12.6999998092651 | 11.6999998092651 | 12.6000003814697 | 16.1000003814697 | 15.6000003814697 | 15.1000003814697 | 14 | 13.8999996185303
Ghana | GHA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 5.90000009536743 | 10.3999996185303 | 6.19999980926514 | 3.5 | 10.3000001907349 | 7.30000019073486 | 7.80000019073486 | 11 | 10.6999998092651 | 10.6000003814697 | 10.6000003814697 | 7.90000009536743 | 6.90000009536743 | 3.79999995231628 | 3.70000004768372 | 3.70000004768372 | 3.70000004768372 | 3.70000004768372 | 3.70000004768372 | 3.59999990463257 | 3.59999990463257
Guinea | GIN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.70000004768372 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.59999990463257 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372
Gambia, The | GMB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.60000038146973 | 8.39999961853027 | 8.30000019073486 | 8.39999961853027 | 8.69999980926514 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.39999961853027 | 8.39999961853027 | 8.80000019073486 | 8.19999980926514 | 8.19999980926514 | 8.5 | 8.39999961853027 | 8.30000019073486 | 8.19999980926514 | 8.10000038146973 | 8.10000038146973 | 8.60000038146973 | 8.19999980926514
Guinea-Bissau | GNB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 8 | 8 | 8.10000038146973 | 8 | 8 | 7.90000009536743 | 9.39999961853027 | 7.69999980926514 | 7.69999980926514 | 7.90000009536743 | 8.10000038146973 | 8 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.80000019073486 | 7.69999980926514 | 8
Equatorial Guinea | GNQ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 6.30000019073486 | 7.19999980926514 | 6.90000009536743 | 6.80000019073486 | 5.09999990463257 | 3.20000004768372 | 6.5 | 6.5 | 6.80000019073486 | 5.30000019073486 | 6.90000009536743 | 7.09999990463257 | 6.30000019073486 | 7.40000009536743 | 7.80000019073486 | 7.09999990463257 | 7.40000009536743 | 8.10000038146973 | 8.10000038146973 | 7.80000019073486 | 7.80000019073486
Greece | GRC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 12.8000001907349 | 14.1999998092651 | 13.6000003814697 | 13.6999998092651 | 15.3000001907349 | 14.6999998092651 | 16.5 | 17.7999992370605 | 16.6000003814697 | 15.3000001907349 | 15.6000003814697 | 14.8999996185303 | 16.2000007629395 | 15.1999998092651 | 13.6000003814697 | 12.6999998092651 | 11.3999996185303 | 13.1000003814697 | 16.1000003814697 | 21.2999992370605 | 28.1000003814697
Grenada | GRD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Greenland | GRL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Guatemala | GTM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.59999990463257 | 3 | 2.79999995231628 | 5 | 3.90000009536743 | 5.40000009536743 | 4.69999980926514 | 2.29999995231628 | 1.70000004768372 | 1.60000002384186 | 3.70000004768372 | 3.40000009536743 | 3.70000004768372 | 3.5 | 3.40000009536743 | 3 | 3.29999995231628 | 3.70000004768372 | 4.19999980926514 | 4.90000009536743 | 5
Guam | GUM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Guyana | GUY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.5 | 19 | 24 | 30.1000003814697 | 37.4000015258789 | 33.2999992370605 | 29.2999992370605 | 26.3999996185303 | 31.6000003814697 | 19.7000007629395 | 32.7000007629395 | 30.2000007629395 | 28.2999992370605 | 29.7000007629395 | 26.7000007629395 | 33.7000007629395 | 25.6000003814697 | 29.5 | 26.5 | 25.2000007629395 | 25.2000007629395 | 26.2000007629395
High income | HIC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.303090761253488 | 7.69070907809084 | 8.205227347190716 | 8.505703261144284 | 8.38659367280936 | 8.345157382916781 | 8.458894511155442 | 8.542500407924184 | 8.327267498639326 | 7.668214236312084 | 7.229064788362056 | 7.46218603547861 | 7.559821605342012 | 7.480410482577498 | 7.12633095215969 | 6.622134617833834 | 5.968700546242154 | 6.117311549808255 | 7.770351482985244 | 8.027894032172215 | 7.821131555178704 | 7.882235178708741
Hong Kong SAR, China | HKG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.60000002384186 | 1.89999997615814 | 1.89999997615814 | 1.70000004768372 | 2.90000009536743 | 2.40000009536743 | 2 | 3.90000009536743 | 5.19999980926514 | 4 | 3.90000009536743 | 5.90000009536743 | 6.19999980926514 | 5.5 | 4.40000009536743 | 3.70000004768372 | 3.29999995231628 | 3 | 4.30000019073486 | 3.5 | 2.79999995231628 | 2.70000004768372
Honduras | HND | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 5.69999980926514 | 4.30000019073486 | 5.19999980926514 | 4 | 4.09999990463257 | 4.40000009536743 | 4.69999980926514 | 6.5 | 8.5 | 6.30000019073486 | 4 | 3.70000004768372 | 4 | 4.19999980926514 | 6.09999990463257 | 6.09999990463257 | 6.09999990463257
Heavily indebted poor countries (HIPC) | HPC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.851709675702605 | 7.888371662469844 | 7.866267777677521 | 7.77142708812127 | 7.832052205800533 | 8.320528888316215 | 8.133882741844127 | 8.038269732635971 | 8.0427279387913 | 8.060690265693962 | 8.100559894999067 | 7.728550624333307 | 7.495175203232946 | 7.099576680033545 | 6.627327642036975 | 6.867333609735378 | 6.638960119598631 | 6.7479450682448 | 6.833450488826367 | 6.798223318645754 | 6.840738280775626 | 6.842779835549294
Croatia | HRV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 11.5 | 11.6000003814697 | 11.8999996185303 | 11.6999998092651 | 11.1999998092651 | 11.1000003814697 | 11.5 | 14.1000003814697 | 16.7999992370605 | 21.3999996185303 | 17.2999992370605 | 15.6999998092651 | 15.3000001907349 | 13.8999996185303 | 12.8000001907349 | 11.1000003814697 | 10.1000003814697 | 10.3999996185303 | 12.3999996185303 | 13.3000001907349 | 15.6999998092651
Haiti | HTI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.5 | 15.6000003814697 | 15.6999998092651 | 16.2000007629395 | 14.3000001907349 | 14.6999998092651 | 14.6999998092651 | 14.6999998092651 | 8.30000019073486 | 8.5 | 8.80000019073486 | 8.80000019073486 | 8.69999980926514 | 9.30000019073486 | 8.5 | 8.39999961853027 | 8.30000019073486 | 8.5 | 8.19999980926514 | 9.30000019073486 | 7.80000019073486 | 8
Hungary | HUN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.5 | 8.69999980926514 | 10.3000001907349 | 9.30000019073486 | 8.69999980926514 | 8.80000019073486 | 7.80000019073486 | 7 | 6.30000019073486 | 5.59999990463257 | 5 | 5.40000009536743 | 5.59999990463257 | 6.09999990463257 | 7.5 | 7.80000019073486 | 7.59999990463257 | 8 | 9.69999980926514 | 10.6999998092651 | 10.8999996185303 | 10.6000003814697
Indonesia | IDN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.80000019073486 | 3 | 5.19999980926514 | 6 | 4.59999990463257 | 5.30000019073486 | 5.5 | 6.30000019073486 | 6.80000019073486 | 6.5 | 10.3000001907349 | 11.1000003814697 | 12.6000003814697 | 12.6999998092651 | 14.1000003814697 | 13.1999998092651 | 10.8999996185303 | 9.80000019073486 | 8.5 | 8.89999961853027 | 8.19999980926514 | 8.19999980926514
Isle of Man | IMN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
India | IND | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.19999980926514 | 4.30000019073486 | 3.90000009536743 | 4.09999990463257 | 4.09999990463257 | 4.40000009536743 | 3.90000009536743 | 4 | 4.19999980926514 | 4 | 4.69999980926514 | 4 | 3.90000009536743 | 5 | 4.90000009536743 | 3.90000009536743 | 4.30000019073486 | 3.90000009536743 | 4.40000009536743 | 4.30000019073486 | 4
Not classified | INX | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Ireland | IRL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.6000003814697 | 15.3000001907349 | 15.8000001907349 | 14.6999998092651 | 12.1000003814697 | 11.8000001907349 | 10.1999998092651 | 7.30000019073486 | 5.59999990463257 | 4.30000019073486 | 3.5 | 3.70000004768372 | 4 | 3.79999995231628 | 4 | 4.19999980926514 | 4.19999980926514 | 4.59999990463257 | 8.19999980926514 | 9.80000019073486 | 10.8000001907349 | 11
Iran, Islamic Rep. | IRN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.7999992370605 | 20.3999996185303 | 19.7999992370605 | 19.2000007629395 | 18.7000007629395 | 18.2999992370605 | 18.5 | 18.2999992370605 | 18 | 20.6000003814697 | 18.7000007629395 | 20 | 18.8999996185303 | 15.8000001907349 | 18.3999996185303 | 17.6000003814697 | 16.1000003814697 | 17.1000003814697 | 17.2999992370605 | 21 | 20.7000007629395 | 20
Iraq | IRQ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.7999992370605 | 31.1000003814697 | 26.7999992370605 | 27.8999996185303 | 29.1000003814697 | 30.2999992370605 | 30 | 29.6000003814697 | 28 | 28.2000007629395 | 28.2999992370605 | 28.1000003814697 | 33.9000015258789 | 35.4000015258789 | 27.3999996185303 | 26.6000003814697 | 25.6000003814697 | 23.2000007629395 | 23 | 22.8999996185303 | 22.8999996185303 | 22.5
Iceland | ISL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.90000009536743 | 4.90000009536743 | 5.59999990463257 | 5.5 | 4.90000009536743 | 4.09999990463257 | 4.5 | 3.29999995231628 | 2.59999990463257 | 2.90000009536743 | 2.5 | 2.90000009536743 | 3.09999990463257 | 2.90000009536743 | 2.59999990463257 | 3.09999990463257 | 2.29999995231628 | 2.59999990463257 | 5.69999980926514 | 6.69999980926514 | 6.19999980926514 | 5.69999980926514
Israel | ISR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3999996185303 | 13.8999996185303 | 12.1000003814697 | 10 | 8.60000038146973 | 7.80000019073486 | 8.80000019073486 | 9.19999980926514 | 9.39999961853027 | 9.19999980926514 | 9.69999980926514 | 10.6000003814697 | 11.3000001907349 | 11.3999996185303 | 9.5 | 9 | 7.90000009536743 | 6.5 | 7.5 | 6.5 | 5.59999990463257 | 7
Italy | ITA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8000001907349 | 13.8000001907349 | 14.6999998092651 | 15.1999998092651 | 16 | 16.1000003814697 | 16.2999992370605 | 16.3999996185303 | 16.2000007629395 | 14.8000001907349 | 13 | 12.6000003814697 | 11.8999996185303 | 10.1999998092651 | 10 | 8.80000019073486 | 7.90000009536743 | 8.5 | 9.30000019073486 | 9.69999980926514 | 9.60000038146973 | 11.8999996185303
Jamaica | JAM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.6000003814697 | 22.2999992370605 | 22.5 | 22 | 22.3999996185303 | 22.8999996185303 | 23.7000007629395 | 22.2999992370605 | 22.7999992370605 | 22.3999996185303 | 21.1000003814697 | 19.7000007629395 | 17 | 15.8000001907349 | 15.1000003814697 | 13.3000001907349 | 13 | 14.5 | 14.8000001907349 | 16.1000003814697 | 16.7000007629395 | 17.6000003814697
Jordan | JOR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.8999996185303 | 31 | 37.0999984741211 | 34.2999992370605 | 27.2000007629395 | 25.3999996185303 | 25.1000003814697 | 16.7999992370605 | 25.3999996185303 | 21.8999996185303 | 23.3999996185303 | 24.5 | 23.1000003814697 | 17.1000003814697 | 27 | 25.8999996185303 | 26.7000007629395 | 25.5 | 25 | 22.7999992370605 | 22 | 21
Japan | JPN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.20000004768372 | 2.20000004768372 | 2.70000004768372 | 3 | 3.29999995231628 | 3.40000009536743 | 3.40000009536743 | 4 | 4.5 | 4.5 | 4.80000019073486 | 5.09999990463257 | 4.90000009536743 | 4.40000009536743 | 4.19999980926514 | 3.79999995231628 | 3.70000004768372 | 3.79999995231628 | 4.69999980926514 | 4.5 | 4.09999990463257 | 4
Kazakhstan | KAZ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 14 | 12.3000001907349 | 9.10000038146973 | 13.3999996185303 | 15.8000001907349 | 15.6999998092651 | 15.8000001907349 | 16.2999992370605 | 15.3999996185303 | 12.5 | 11.1000003814697 | 10.3999996185303 | 9.80000019073486 | 9.80000019073486 | 9.39999961853027 | 8.80000019073486 | 7.90000009536743 | 7.59999990463257 | 7 | 6.5 | 6.40000009536743
Kenya | [NAME] | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 11.6000003814697 | 11.5 | 11.3000001907349 | 11.1000003814697 | 11.1000003814697 | 11.3000001907349 | 11 | 11.1000003814697 | 11 | 10.8999996185303 | 11 | 10.8999996185303 | 10.8000001907349 | 10.6999998092651 | 10.6999998092651 | 10.6000003814697 | 10.6999998092651 | 10.6000003814697 | 10.5 | 10.5 | 10.5
Kyrgyz Republic | KGZ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.19999980926514 | 8.80000019073486 | 9.10000038146973 | 8.80000019073486 | 9.39999961853027 | 9.5 | 9.30000019073486 | 11.1000003814697 | 9.19999980926514 | 8.39999961853027 | 8.69999980926514 | 14.1999998092651 | 11.1000003814697 | 9.19999980926514 | 9 | 9 | 9.10000038146973 | 9.19999980926514 | 9.69999980926514 | 9.89999961853027 | 10 | 9.60000038146973
Cambodia | KHM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.09999990463257 | 2 | 2.09999990463257 | 1.60000002384186 | 1.70000004768372 | 1.79999995231628 | 2 | 2.20000004768372 | 2.40000009536743 | 2.70000004768372 | 1.79999995231628 | 1.89999997615814 | 2 | 2 | 1.89999997615814 | 1.89999997615814 | 1.79999995231628 | 1.79999995231628 | 1.89999997615814 | 1.70000004768372 | 1.60000002384186 | 1.60000002384186
Kiribati | KIR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
St. Kitts and Nevis | KNA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Korea, Rep. | KOR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.79999995231628 | 2 | 2.09999990463257 | 1.79999995231628 | 1.60000002384186 | 1.5 | 2.20000004768372 | 5.5 | 4.90000009536743 | 3.5 | 3.20000004768372 | 2.59999990463257 | 3.20000004768372 | 3.20000004768372 | 3.29999995231628 | 2.79999995231628 | 2.59999990463257 | 2.59999990463257 | 2.90000009536743 | 3.29999995231628 | 3 | 2.90000009536743
Kosovo | KSV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Kuwait | KWT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1 | 1.20000004768372 | 0.800000011920929 | 0.699999988079071 | 0.600000023841858 | 0.600000023841858 | 0.600000023841858 | 0.600000023841858 | 0.600000023841858 | 0.699999988079071 | 0.699999988079071 | 0.899999976158142 | 1.10000002384186 | 1.39999997615814 | 2.09999990463257 | 1.29999995231628 | 1.29999995231628 | 1.20000004768372 | 1.29999995231628 | 1.29999995231628 | 1.29999995231628 | 1.20000004768372
Latin America & Caribbean (developing only) | LAC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.60885532856567 | 8.164734778657873 | 8.349585416176664 | 8.404758298806446 | 9.766355341996345 | 10.41227565965518 | 10.3300802191104 | 10.52960894440091 | 10.71639905539245 | 10.89704720835028 | 10.70126263940491 | 11.01295304309101 | 11.34383645306865 | 10.64116630034172 | 10.18400579290344 | 9.261376114525058 | 8.891388561811958 | 8.509632815799526 | 9.243267090386428 | 8.924577709945387 | 8.158822465752248 | 8.065630931547211
Lao PDR | LAO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.89999997615814 | 2.09999990463257 | 2.09999990463257 | 2.09999990463257 | 2.20000004768372 | 1.60000002384186 | 1.70000004768372 | 1.70000004768372 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.5 | 1.79999995231628 | 2 | 1.20000004768372 | 1.10000002384186 | 1.20000004768372 | 1.20000004768372 | 1.20000004768372 | 1.10000002384186 | 1.10000002384186 | 1.10000002384186
Lebanon | LBN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8999996185303 | 10.6999998092651 | 10.5 | 10.8999996185303 | 10.3000001907349 | 10.3000001907349 | 10.3000001907349 | 10.1999998092651 | 10.1999998092651 | 10.1999998092651 | 10.1999998092651 | 10.3000001907349 | 10.5 | 10.3000001907349 | 10.3999996185303 | 10.3999996185303 | 11 | 11 | 10.8999996185303 | 10.8000001907349 | 10.6999998092651 | 10.6000003814697
Liberia | LBR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 4.30000019073486 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 5.09999990463257 | 4.19999980926514 | 4 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 3.70000004768372
Libya | LBY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8999996185303 | 15.1999998092651 | 15.1999998092651 | 15.3000001907349 | 14.8000001907349 | 15.3000001907349 | 15.1000003814697 | 15.1000003814697 | 15 | 15.1000003814697 | 14.8000001907349 | 14.6999998092651 | 15.1000003814697 | 14.6999998092651 | 14.8000001907349 | 14.3999996185303 | 14.3000001907349 | 14 | 13.6999998092651 | 13.6999998092651 | 11.5 | 15.6000003814697
St. Lucia | LCA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Latin America & Caribbean (all income levels) | LCN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.71338385593739 | 8.361564528344612 | 8.528198311342631 | 8.559355752213824 | 9.820710226395718 | 10.43046451867778 | 10.33097486897039 | 10.53117720017161 | 10.7515428533118 | 10.88612907712868 | 10.69352780505452 | 10.99488299584218 | 11.31255433448246 | 10.64401531177642 | 10.19314309412758 | 9.306243840890742 | 8.910233346255875 | 8.552823690191552 | 9.304389226499714 | 8.967882184886543 | 8.200209079105441 | 8.088023878540897
Latin America and the Caribbean | LCR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Least developed countries: UN classification | LDC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.587814768401508 | 6.585494940212477 | 6.448667947927289 | 6.473966424040403 | 6.620204176220992 | 6.609002347422362 | 6.758530748120144 | 6.615835686432935 | 6.519636360393706 | 6.744633920991929 | 6.732171958015575 | 6.47663058590846 | 6.57753477194764 | 6.472503695884726 | 6.490309395675276 | 6.48233919026526 | 6.303845190867741 | 6.450103097659481 | 6.649559940113133 | 6.45307638469773 | 6.491599075350496 | 6.491100436883813
Low income | LIC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.892627980073618 | 5.889870566155077 | 5.721643898187799 | 5.709903152571972 | 5.889455088551557 | 6.05010376241141 | 6.092520701202722 | 6.029169068256643 | 5.950397733834616 | 6.0829828281561 | 6.092290330255944 | 5.863692480196708 | 5.915396698546607 | 5.809895308769242 | 5.816698200472545 | 5.823602879934861 | 5.669035346784724 | 5.847980171947515 | 6.035978002668602 | 5.802314784285727 | 5.837439893865792 | 5.850107188707396
[NAME] | LIE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
[NAME] | LKA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23 | 21.8999996185303 | 22.1000003814697 | 20.6000003814697 | 19.6000003814697 | 18.1000003814697 | 16.7000007629395 | 13.6999998092651 | 13.5 | 11.6000003814697 | 12.1000003814697 | 13.6999998092651 | 13 | 13.1000003814697 | 12 | 9.80000019073486 | 9.10000038146973 | 8.10000038146973 | 8.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.40000009536743
Lower middle income | LMC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.698566368819788 | 6.026775705642875 | 6.559603618036773 | 6.244106143148721 | 6.05278127778177 | 6.207580074447068 | 6.546995210916727 | 6.471993920057018 | 6.635574418387031 | 6.823676210119626 | 7.426535827336005 | 7.671842465674197 | 7.501380902159297 | 7.372317998582345 | 7.690344879631894 | 7.409044578325068 | 6.550736651293954 | 6.655803728050254 | 6.506295838275903 | 6.757027890108484 | 6.684274828304556 | 6.555580727610631
Low & middle income | LMY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.15826806426994 | 5.596763891682639 | 5.778678368869484 | 5.634144209330186 | 5.800295869683952 | 5.961255223959045 | 6.134036159971022 | 6.237776421916557 | 6.300940465370653 | 6.353758857046117 | 6.53641428617562 | 6.610103865577369 | 6.550686582950591 | 6.384760277672565 | 6.413060419377766 | 6.182183866150304 | 5.749026241447379 | 5.941693959454155 | 6.058821600001721 | 6.023470304508139 | 5.981160963652872 | 5.966192106417236
[NAME] | LSO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.7999992370605 | 45.0999984741211 | 47.4000015258789 | 46.2999992370605 | 40 | 35.5 | 48.0999984741211 | 40.9000015258789 | 33.4000015258789 | 45.5 | 45.0999984741211 | 40.4000015258789 | 47.2999992370605 | 44.2000007629395 | 44.7999992370605 | 40.2000007629395 | 32.7999992370605 | 27.7999992370605 | 28.2000007629395 | 26.5 | 27.1000003814697 | 29.7999992370605
Lithuania | LTU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 10 | 13.3999996185303 | 15.6000003814697 | 15.3000001907349 | 13.8999996185303 | 13.8999996185303 | 11.8000001907349 | 12 | 13.6000003814697 | 14.1000003814697 | 12.8000001907349 | 13.1999998092651 | 11.6000003814697 | 8.30000019073486 | 5.40000009536743 | 4.40000009536743 | 5.59999990463257 | 10.3999996185303 | 14.5 | 12.8999996185303 | 11.5
Luxembourg | LUX | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.09999990463257 | 2.70000004768372 | 3 | 4.30000019073486 | 4.40000009536743 | 4.69999980926514 | 3.70000004768372 | 4.19999980926514 | 3.40000009536743 | 3.09999990463257 | 2.20000004768372 | 3.59999990463257 | 4.69999980926514 | 7.09999990463257 | 5.80000019073486 | 6.19999980926514 | 4.69999980926514 | 6 | 6.09999990463257 | 5.09999990463257 | 6.30000019073486 | 5.90000009536743
Latvia | LVA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6999998092651 | 11.3999996185303 | 11.1999998092651 | 14.6999998092651 | 11.1999998092651 | 10.6999998092651 | 14.6000003814697 | 13.5 | 13.3000001907349 | 13.3999996185303 | 11.5 | 11.6000003814697 | 10.8000001907349 | 10.3999996185303 | 8.69999980926514 | 6.09999990463257 | 5.59999990463257 | 6.90000009536743 | 13.8999996185303 | 15.6999998092651 | 13.8000001907349 | 13.8000001907349
Macao SAR, China | MAC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.5 | 2.59999990463257 | 1.79999995231628 | 2.40000009536743 | 3.40000009536743 | 4 | 2.59999990463257 | 3.40000009536743 | 4.40000009536743 | 4.5 | 4.5 | 4.59999990463257 | 4.80000019073486 | 4.09999990463257 | 4 | 3.79999995231628 | 2.70000004768372 | 2.70000004768372 | 2.79999995231628 | 2.09999990463257 | 2.09999990463257 | 1.70000004768372
St. Martin (French part) | MAF | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Morocco | MAR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.1000003814697 | 12.8999996185303 | 12.6999998092651 | 12.3999996185303 | 12.1999998092651 | 12 | 11.8000001907349 | 11.5 | 13.3000001907349 | 13.1999998092651 | 12.5 | 12.6000003814697 | 12.8999996185303 | 11.3999996185303 | 11.5 | 9.69999980926514 | 8.60000038146973 | 9.89999961853027 | 9.5 | 9.69999980926514 | 10.1999998092651 | 9.89999961853027
Mexico and Central America | MCA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Monaco | MCO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Moldova | MDA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.30000019073486 | 5.59999990463257 | 5.09999990463257 | 5.30000019073486 | 5.59999990463257 | 5.40000009536743 | 6.5 | 4.5 | 8.89999961853027 | 7.19999980926514 | 5.90000009536743 | 5.59999990463257 | 6.30000019073486 | 6.30000019073486 | 6 | 5.80000019073486 | 3.90000009536743 | 3.40000009536743 | 4.90000009536743 | 5.69999980926514 | 5.59999990463257 | 4.30000019073486
Madagascar | MDG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4 | 4.30000019073486 | 4 | 4.69999980926514 | 4.09999990463257 | 4 | 3.59999990463257 | 3.5 | 3.5 | 3.40000009536743 | 5 | 5.5 | 6.19999980926514 | 4.80000019073486 | 3.5 | 4.19999980926514 | 5.09999990463257 | 5.40000009536743 | 5 | 4.59999990463257 | 4.59999990463257 | 4.59999990463257
Maldives | MDV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.1000003814697 | 19.7000007629395 | 19.3999996185303 | 18.7000007629395 | 18.3999996185303 | 19 | 19.3999996185303 | 19.2000007629395 | 18.5 | 19.1000003814697 | 19.7999992370605 | 20.6000003814697 | 21.2999992370605 | 20.7999992370605 | 22.2000007629395 | 23.6000003814697 | 20.2000007629395 | 20.5 | 19.5 | 18.5 | 18.2000007629395 | 17.7999992370605
Middle East & North Africa (all income levels) | MEA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.73455641984358 | 20.67748408816518 | 21.35656147665446 | 20.90341280215975 | 21.02098837978306 | 20.64838049803094 | 19.48838221513993 | 19.28748117089336 | 18.65735663950003 | 20.60627085600392 | 20.38413675517463 | 20.82863841599321 | 20.64096515056011 | 19.00894735336098 | 19.31622293342769 | 18.23331050837774 | 16.68076104800425 | 16.84559524594136 | 17.45943022414727 | 18.17202284256006 | 19.14216817156791 | 19.14447865913267
Mexico | MEX | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4 | 4 | 4.80000019073486 | 8.60000038146973 | 6.80000019073486 | 6.09999990463257 | 4.90000009536743 | 3.5 | 3.20000004768372 | 3.29999995231628 | 3.5 | 3.59999990463257 | 4.69999980926514 | 3.59999990463257 | 3.5 | 3.70000004768372 | 3.90000009536743 | 4.80000019073486 | 5.19999980926514 | 5.19999980926514 | 4.90000009536743
Marshall Islands | MHL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Middle income | MIC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.201758833890444 | 5.548575833519168 | 5.788122357299599 | 5.621573962841246 | 5.785430872862554 | 5.946351246049232 | 6.141046923705679 | 6.273205711187171 | 6.360694974718802 | 6.400489632872194 | 6.613798007936681 | 6.741586265354109 | 6.663727198102888 | 6.488018300790773 | 6.521139349666267 | 6.248665461833009 | 5.764186307101718 | 5.959871485875513 | 6.063352489890984 | 6.068386660161785 | 6.010673531736925 | 5.990311199161815
Macedonia, FYR | MKD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32 | 32 | 31.7999992370605 | 32.2999992370605 | 33.0999984741211 | 36.2000007629395 | 36.7000007629395 | 37.9000015258789 | 33.2000007629395 | 34.7999992370605 | 32 | 32.4000015258789 | 36.2999992370605 | 37.9000015258789 | 38.4000015258789 | 37.2000007629395 | 35.5999984741211 | 34.2000007629395 | 32.7999992370605 | 32.2999992370605 | 30.7999992370605 | 30.2999992370605
[NAME] | MLI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3999996185303 | 12.1999998092651 | 11.8000001907349 | 11.8999996185303 | 12.3000001907349 | 11.8999996185303 | 11.5 | 11.6999998092651 | 11.3999996185303 | 11.5 | 11.6999998092651 | 11.8000001907349 | 12.1000003814697 | 12.3999996185303 | 12 | 11.6000003814697 | 11.8000001907349 | 11.6000003814697 | 11.8000001907349 | 11.1000003814697 | 11.1999998092651 | 11.3000001907349
Malta | MLT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 8.30000019073486 | 8.69999980926514 | 8.80000019073486 | 9.39999961853027 | 8.69999980926514 | 8.60000038146973 | 8.10000038146973 | 8.60000038146973 | 6.59999990463257 | 8.10000038146973 | 8.30000019073486 | 9.80000019073486 | 8.19999980926514 | 8.80000019073486 | 8.60000038146973 | 7.5 | 6.90000009536743 | 7.80000019073486 | 7 | 7.19999980926514 | 7.40000009536743
Myanmar | MMR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.19999980926514 | 5.19999980926514 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.19999980926514 | 5.59999990463257 | 4.80000019073486 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.59999990463257 | 4.5 | 4.5 | 4.5 | 4.40000009536743 | 4.80000019073486 | 4.69999980926514 | 4.59999990463257 | 4.59999990463257 | 4.5
Middle East & North Africa (developing only) | MNA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.06821799663176 | 21.3844848924467 | 22.4155134782866 | 22.56481333401906 | 23.16152038855642 | 22.13747625411021 | 20.81930661748839 | 20.58108610131832 | 20.47634852153926 | 22.74074015217066 | 22.48636527893944 | 22.81241157707075 | 22.17625546653922 | 19.93763938217751 | 21.01601771856857 | 19.61943320732 | 17.91947074363712 | 18.18249399695942 | 18.78298809007281 | 19.70236697368034 | 21.07571125681656 | 20.74989492470435
Montenegro | MNE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.8999996185303 | 20.3999996185303 | 21 | 21.7000007629395 | 30.3999996185303 | 30.8999996185303 | 21.1000003814697 | 21.2999992370605 | 21.5 | 32 | 21 | 21.2000007629395 | 21.2999992370605 | 30.7999992370605 | 31.8999996185303 | 26.2000007629395 | 20.7999992370605 | 18 | 20.5 | 20.7000007629395 | 20 | 20.3999996185303
Mongolia | MNG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 5.90000009536743 | 6.59999990463257 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7 | 7 | 7 | 6.40000009536743 | 7.30000019073486 | 6.80000019073486 | 6.5 | 7.19999980926514 | 5.19999980926514 | 6.19999980926514 | 5.90000009536743 | 4.5 | 4.80000019073486
Northern Mariana Islands | MNP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Mozambique | MOZ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 8.69999980926514 | 8.10000038146973 | 8.19999980926514 | 8.39999961853027 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 8.19999980926514 | 7.69999980926514 | 7.69999980926514 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.69999980926514 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486
Mauritania | MRT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.8999996185303 | 27.7000007629395 | 27.2000007629395 | 28.2999992370605 | 26.7999992370605 | 27.2000007629395 | 28.3999996185303 | 27.5 | 27.1000003814697 | 27.6000003814697 | 27.5 | 27.6000003814697 | 27.1000003814697 | 27.7999992370605 | 27.5 | 27.2000007629395 | 26.7999992370605 | 26.7000007629395 | 26.7999992370605 | 26.6000003814697 | 26.7000007629395 | 26.5
[NAME] | MUS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.8999996185303 | 14.6999998092651 | 14.6000003814697 | 14.3999996185303 | 13.1000003814697 | 13.1000003814697 | 13 | 12.8999996185303 | 12.8000001907349 | 11.8999996185303 | 11.1000003814697 | 11.8999996185303 | 12.8000001907349 | 13.6000003814697 | 16.5 | 15.5 | 14.3999996185303 | 12.6000003814697 | 12.3000001907349 | 12.8000001907349 | 12.3999996185303 | 12.3999996185303
[NAME] | MWI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 9.30000019073486 | 8.39999961853027 | 9.5 | 8.19999980926514 | 8.39999961853027 | 8.60000038146973 | 8.89999961853027 | 8.80000019073486 | 9 | 9.30000019073486 | 9.10000038146973 | 8.89999961853027 | 9 | 9.10000038146973 | 9 | 8.69999980926514 | 8.69999980926514 | 8.69999980926514 | 8.80000019073486 | 8.80000019073486 | 8.89999961853027
Malaysia | MYS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 4.09999990463257 | 4.5 | 4.19999980926514 | 3.40000009536743 | 2.70000004768372 | 2.59999990463257 | 3.40000009536743 | 3.29999995231628 | 3.09999990463257 | 3.90000009536743 | 3.90000009536743 | 3.90000009536743 | 3.79999995231628 | 3.79999995231628 | 3.59999990463257 | 3.40000009536743 | 3.59999990463257 | 3.90000009536743 | 3.59999990463257 | 3.29999995231628 | 3.20000004768372
North America | NAC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.828069895395595 | 7.413087309999335 | 7.102145788124012 | 6.464944145870542 | 6.033424636569931 | 5.870871724135694 | 5.470096676505109 | 5.023767317433212 | 4.685629010875359 | 4.448100751091876 | 4.92042874537355 | 5.843244121731257 | 5.856421527784748 | 5.647192636254971 | 5.336144364934431 | 4.847036932140826 | 4.706437841528163 | 5.510668675865066 | 7.982055689845033 | 8.53743306827445 | 8.335792747227941 | 7.778961753086362
Namibia | NAM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.3999996185303 | 21.5 | 21.5 | 21.1000003814697 | 21.2000007629395 | 21.2000007629395 | 21 | 21.1000003814697 | 21.1000003814697 | 21.6000003814697 | 23.6000003814697 | 20.3999996185303 | 21.6000003814697 | 24.6000003814697 | 21.5 | 24.2000007629395 | 21.5 | 43.2000007629395 | 33.2999992370605 | 23.7999992370605 | 21.7999992370605 | 18.7999992370605
New Caledonia | NCL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
[NAME] | NER | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.90000009536743 | 4.09999990463257 | 3.90000009536743 | 3.90000009536743 | 4.09999990463257 | 4 | 4.09999990463257 | 4 | 4.09999990463257 | 4.09999990463257 | 4 | 4 | 4 | 4.09999990463257 | 4 | 4 | 4.09999990463257 | 4 | 4.09999990463257 | 4 | 4.09999990463257 | 4
Nigeria | NGA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.30000019073486 | 7.40000009536743 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.09999990463257 | 7.40000009536743 | 7.40000009536743 | 7.5 | 7.5 | 7.40000009536743 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743
Nicaragua | NIC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 2.59999990463257 | 3 | 3.40000009536743 | 3.90000009536743 | 5.19999980926514 | 4.30000019073486 | 3.70000004768372 | 3.90000009536743 | 4.09999990463257 | 8.19999980926514 | 6.80000019073486 | 5.59999990463257 | 5 | 4.69999980926514 | 5.80000019073486 | 6.19999980926514 | 7.40000009536743 | 7.09999990463257 | 7.09999990463257
Netherlands | NLD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.89999961853027 | 7.80000019073486 | 7.69999980926514 | 8 | 8.69999980926514 | 8.10000038146973 | 7.09999990463257 | 5.80000019073486 | 4.90000009536743 | 3.5 | 2.5 | 2.90000009536743 | 3.79999995231628 | 5 | 5.09999990463257 | 4.40000009536743 | 3.59999990463257 | 3 | 3.5 | 4.5 | 4.40000009536743 | 5.19999980926514
High income: nonOECD | NOC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.52850189672155 | 5.948740428665447 | 6.54737544529076 | 8.319940421104466 | 9.21390828561884 | 9.444717164855314 | 11.10986936065637 | 12.39238846046229 | 12.22785478993917 | 10.18930257407598 | 8.782328587857592 | 8.01633758940354 | 8.376738851692494 | 8.075263407343536 | 7.233622764994022 | 7.065235446969617 | 6.031516944197044 | 6.297958835625715 | 8.060460512716002 | 7.447866107905087 | 6.691666731764806 | 6.190392999652674
Norway | NOR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5 | 5.09999990463257 | 5.19999980926514 | 4.69999980926514 | 4.59999990463257 | 4.80000019073486 | 4 | 3.29999995231628 | 3 | 3.20000004768372 | 3.40000009536743 | 3.70000004768372 | 3.90000009536743 | 3.79999995231628 | 4.40000009536743 | 3.40000009536743 | 2.5 | 2.40000009536743 | 2.59999990463257 | 3 | 3.09999990463257 | 2.79999995231628
Nepal | NPL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.79999995231628 | 1.60000002384186 | 1.79999995231628 | 1.89999997615814 | 2.09999990463257 | 3.90000009536743 | 3.20000004768372 | 2.59999990463257 | 1.60000002384186 | 2.40000009536743 | 3.29999995231628 | 2.5 | 1.89999997615814 | 1.89999997615814 | 2.29999995231628 | 2.40000009536743 | 2.29999995231628 | 2.40000009536743 | 2.40000009536743 | 2.40000009536743 | 2.40000009536743 | 2.40000009536743
New Zealand | NZL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.69999980926514 | 9.69999980926514 | 8.89999961853027 | 7.80000019073486 | 6.5 | 6.30000019073486 | 6.80000019073486 | 7.59999990463257 | 6.69999980926514 | 6 | 5.40000009536743 | 5.5 | 5.09999990463257 | 4.5 | 4.09999990463257 | 4.19999980926514 | 4 | 4.19999980926514 | 6.09999990463257 | 6.80000019073486 | 6.80000019073486 | 7.30000019073486
High income: OECD | OEC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.568837292513388 | 8.075851746548379 | 8.559339022987233 | 8.543725366027187 | 8.217327348028883 | 8.124348678894554 | 7.938092456156122 | 7.795820429340965 | 7.524382747203567 | 7.151479175827751 | 6.916145573140192 | 7.348907837855251 | 7.390868892130189 | 7.357024791443461 | 7.104031843018964 | 6.530139612959664 | 5.955605883579459 | 6.07999436499533 | 7.710447166916624 | 8.146532422441984 | 8.05432426197913 | 8.230948882061695
OECD members | OED | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.415921757575279 | 7.871287538278026 | 8.35471924248961 | 8.33450289527714 | 8.210951561689505 | 7.989885403261037 | 7.818391052889784 | 7.583073686545077 | 7.272696719102197 | 6.873862149967437 | 6.694111217848653 | 7.149846772406158 | 7.210004885571414 | 7.254714756562532 | 6.967734559827682 | 6.438296478737224 | 5.927615629638876 | 6.073087939805418 | 7.692295118612384 | 8.085350628807245 | 7.961002406357086 | 8.072419364652392
Oman | OMN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 16.8999996185303 | 16.5 | 16.2000007629395 | 16.2999992370605 | 16.3999996185303 | 16.8999996185303 | 17.1000003814697 | 17.2999992370605 | 17.5 | 17.5 | 17.2000007629395 | 16.8999996185303 | 16.7999992370605 | 16.6000003814697 | 16.3999996185303 | 16.1000003814697 | 15.8999996185303 | 15.3000001907349 | 15.1000003814697 | 14.8999996185303 | 14.6999998092651
Other small states | OSS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.12857006954165 | 20.44882447599861 | 20.62943438631348 | 20.29326142549011 | 19.82361317667717 | 19.22036825657355 | 20.87791947585875 | 19.95548405587058 | 18.54984147832984 | 21.34603830948017 | 20.61232311020618 | 19.30423577314708 | 20.5994704348485 | 20.58405365980532 | 20.26551795032299 | 18.88697523726911 | 17.43352150750025 | 19.9690556649575 | 18.60868452633945 | 17.27770400445716 | 17.03494585012745 | 16.60617464792041
Pakistan | PAK | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.7000007629395 | 14.1999998092651 | 9.89999961853027 | 9.30000019073486 | 14 | 14.8999996185303 | 17.2000007629395 | 15 | 15.1999998092651 | 16.1000003814697 | 16.7000007629395 | 16.5 | 15.6999998092651 | 13.1000003814697 | 12.3000001907349 | 9.80000019073486 | 8.69999980926514 | 8.80000019073486 | 8.80000019073486 | 8.80000019073486 | 8.80000019073486 | 8.89999961853027
Panama | PAN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.7000007629395 | 21.5 | 20.2999992370605 | 20.5 | 20.2000007629395 | 20.2999992370605 | 18.2999992370605 | 20.8999996185303 | 17.1000003814697 | 17.7999992370605 | 18.8999996185303 | 18.5 | 18.1000003814697 | 16.5 | 13.3999996185303 | 11.8999996185303 | 8.80000019073486 | 7.69999980926514 | 9 | 8.60000038146973 | 5 | 5.09999990463257
Peru | PER | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6.19999980926514 | 7.09999990463257 | 4.80000019073486 | 4.40000009536743 | 5.5 | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 5.69999980926514 | 4.19999980926514 | 5.19999980926514 | 6.30000019073486 | 5.19999980926514 | 5.19999980926514 | 4.5 | 4.40000009536743 | 4.40000009536743 | 4.30000019073486 | 3.90000009536743 | 3.79999995231628 | 3.79999995231628
Philippines | PHL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6000003814697 | 9.89999961853027 | 10.1999998092651 | 9.60000038146973 | 9.60000038146973 | 8.19999980926514 | 8.60000038146973 | 9.69999980926514 | 9.5 | 11.1999998092651 | 11.8000001907349 | 11.8000001907349 | 11.3999996185303 | 12.8000001907349 | 7.69999980926514 | 7.5 | 7 | 7 | 7.5 | 7.30000019073486 | 7 | 7.09999990463257
Palau | PLW | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
[NAME] | PNG | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 2.79999995231628 | 2.59999990463257 | 3.09999990463257 | 3.5 | 3 | 3.59999990463257 | 3.09999990463257 | 3.20000004768372 | 3.40000009536743 | 3.29999995231628 | 3.20000004768372 | 3.09999990463257 | 3.20000004768372 | 3.09999990463257 | 3.09999990463257 | 2.90000009536743 | 2.90000009536743 | 2.90000009536743 | 2.79999995231628 | 2.70000004768372 | 2.79999995231628
Poland | POL | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.1000003814697 | 14.6000003814697 | 15.5 | 15.8999996185303 | 14.6000003814697 | 13.8000001907349 | 13.1000003814697 | 12.1999998092651 | 13.3999996185303 | 18 | 19.7000007629395 | 20.7999992370605 | 20.3999996185303 | 19.8999996185303 | 19.1000003814697 | 14.8999996185303 | 10.3000001907349 | 7.90000009536743 | 8.60000038146973 | 10 | 10.3999996185303 | 10.8999996185303
Puerto Rico | PRI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 13.5 | 13.5 | 11.5 | 10.8000001907349 | 11.8000001907349 | 12.3999996185303 | 12.1999998092651 | 9.69999980926514 | 7.5 | 9.5 | 10.8000001907349 | 11 | 8.89999961853027 | 10.3000001907349 | 10.6999998092651 | 9.60000038146973 | 9.89999961853027 | 12.6000003814697 | 12.6000003814697 | 12.8000001907349 | 12.8999996185303
Korea, Dem. Rep. | PRK | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.70000004768372 | 2.70000004768372 | 2.5 | 2.29999995231628 | 2.29999995231628 | 4.09999990463257 | 4 | 4.30000019073486 | 3.90000009536743 | 3.90000009536743 | 4.09999990463257 | 3.90000009536743 | 3.90000009536743 | 3.79999995231628 | 3.79999995231628 | 3.79999995231628 | 3.70000004768372 | 3.90000009536743 | 4.19999980926514 | 3.70000004768372 | 3.70000004768372 | 3.90000009536743
Portugal | PRT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.59999990463257 | 4.80000019073486 | 6.30000019073486 | 7.59999990463257 | 7.80000019073486 | 7.90000009536743 | 7.19999980926514 | 6.19999980926514 | 5 | 4.90000009536743 | 5 | 6 | 7.19999980926514 | 7.59999990463257 | 8.69999980926514 | 8.89999961853027 | 9.60000038146973 | 8.80000019073486 | 10.1000003814697 | 11.8999996185303 | 13.1000003814697 | 15.6000003814697
Paraguay | PRY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.5 | 5.90000009536743 | 9 | 8 | 3.90000009536743 | 5.30000019073486 | 6.69999980926514 | 6.69999980926514 | 7.5 | 9.19999980926514 | 9.19999980926514 | 13.6000003814697 | 10.1000003814697 | 9.30000019073486 | 7.30000019073486 | 8.39999961853027 | 7.69999980926514 | 7.59999990463257 | 8.19999980926514 | 7.09999990463257 | 7.19999980926514 | 7.80000019073486
Pacific island small states | PSS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
French Polynesia | PYF | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Qatar | QAT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 4.90000009536743 | 4.90000009536743 | 5.09999990463257 | 5.30000019073486 | 5.59999990463257 | 5.69999980926514 | 3.40000009536743 | 2.29999995231628 | 1.39999997615814 | 2.40000009536743 | 3.59999990463257 | 5.19999980926514 | 7.30000019073486 | 5.80000019073486 | 4.40000009536743 | 2.5 | 2.09999990463257 | 1.79999995231628 | 2.59999990463257 | 3.90000009536743 | 3.79999995231628
Romania | [NAME] | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 8.10000038146973 | 8.19999980926514 | 8.30000019073486 | 8.69999980926514 | 7.30000019073486 | 5.80000019073486 | 5.40000009536743 | 5.5 | 6.30000019073486 | 5.90000009536743 | 7.5 | 6.30000019073486 | 6.09999990463257 | 6.40000009536743 | 6.09999990463257 | 5.40000009536743 | 4.69999980926514 | 5.80000019073486 | 6.5 | 6.80000019073486 | 6.40000009536743
Russian Federation | RUS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8000001907349 | 5.19999980926514 | 5.80000019073486 | 8 | 9.19999980926514 | 9.30000019073486 | 11.3999996185303 | 12.8999996185303 | 12.8999996185303 | 10.3999996185303 | 8.60000038146973 | 7.59999990463257 | 7.90000009536743 | 7.5 | 6.90000009536743 | 6.69999980926514 | 5.59999990463257 | 5.90000009536743 | 7.69999980926514 | 6.80000019073486 | 6 | 5.09999990463257
Rwanda | RWA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.5 | 0.300000011920929 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.400000005960464 | 0.300000011920929 | 0.400000005960464
South Asia | SAS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.85196606276029 | 4.666595361323661 | 4.584535874007115 | 4.217815337852755 | 4.459482091574766 | 4.496751125850443 | 4.874178034816156 | 4.310021461144579 | 4.4676739850716 | 4.711849463985306 | 4.631468101690797 | 5.160971671192752 | 4.74629835465168 | 4.664758917332078 | 5.622351030388638 | 5.285068501433706 | 4.506407546174152 | 4.831604496713022 | 4.733644342188032 | 4.899918990223165 | 4.836192421075851 | 4.641925043295181
Saudi Arabia | SAU | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2999992370605 | 21.2999992370605 | 19.5 | 10.1000003814697 | 10.5 | 20.2999992370605 | 19.3999996185303 | 19.3999996185303 | 8.30000019073486 | 8.89999961853027 | 8.60000038146973 | 11 | 16.3999996185303 | 21 | 11.1999998092651 | 15.1999998092651 | 14.6000003814697 | 14.3000001907349 | 16.2999992370605 | 16.8999996185303 | 14.8999996185303 | 20.7999992370605
[NAME] | SCE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Sudan | SDN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.6000003814697 | 19.8999996185303 | 20.3999996185303 | 20.2000007629395 | 20.2999992370605 | 20.5 | 23.2999992370605 | 21.2000007629395 | 21.2000007629395 | 21.2000007629395 | 20.3999996185303 | 20.2999992370605 | 20.3999996185303 | 20.2999992370605 | 19.8999996185303 | 20.2999992370605 | 20.2999992370605 | 20 | 20 | 19.8999996185303 | 19.8999996185303 | 19.7999992370605
Senegal | SEN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13 | 13.1000003814697 | 13.1000003814697 | 13.1999998092651 | 12.8000001907349 | 13 | 12.8999996185303 | 12.6999998092651 | 12.6999998092651 | 12.8999996185303 | 12.8000001907349 | 13.1000003814697 | 12.6000003814697 | 12.6999998092651 | 12.6999998092651 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651
Singapore | SGP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.90000009536743 | 2.5 | 2.40000009536743 | 2.5 | 2.5 | 2.40000009536743 | 2.20000004768372 | 3.79999995231628 | 4.09999990463257 | 4.09999990463257 | 4 | 5.19999980926514 | 5.59999990463257 | 4.69999980926514 | 4.40000009536743 | 3.90000009536743 | 3.20000004768372 | 3.40000009536743 | 4.5 | 3.29999995231628 | 3 | 3
Solomon Islands | SLB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.59999990463257 | 5.30000019073486 | 5.80000019073486 | 5.59999990463257 | 5.5 | 6 | 6.09999990463257 | 6 | 6 | 6.90000009536743 | 6.40000009536743 | 6 | 5.40000009536743 | 5.30000019073486 | 5 | 5.40000009536743 | 5.30000019073486 | 5.19999980926514 | 5.90000009536743 | 5.09999990463257 | 5 | 5.30000019073486
Sierra Leone | SLE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.5 | 2.5 | 2.29999995231628 | 2.29999995231628 | 2.5 | 2.70000004768372 | 2.59999990463257 | 2.40000009536743 | 2.5 | 2.29999995231628 | 2.09999990463257 | 2 | 2.20000004768372 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.29999995231628 | 2.20000004768372
El Salvador | SLV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 5.30000019073486 | 6.5 | 5.09999990463257 | 5.90000009536743 | 6.5 | 5.40000009536743 | 5.90000009536743 | 4.69999980926514 | 4.5 | 4.40000009536743 | 3.5 | 3.5 | 3.90000009536743 | 4.19999980926514 | 3.90000009536743 | 3.70000004768372 | 3.5 | 4.40000009536743 | 4.19999980926514 | 4.09999990463257 | 4.19999980926514
[NAME] | SMR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Somalia | SOM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 8.30000019073486 | 8.19999980926514 | 8.5 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8.19999980926514 | 8.10000038146973 | 8.19999980926514 | 8.19999980926514 | 8.10000038146973 | 8 | 8 | 8 | 8.10000038146973 | 8 | 8 | 8 | 8.10000038146973
Serbia | SRB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.8999996185303 | 16.6000003814697 | 19.8999996185303 | 17.8999996185303 | 15.8000001907349 | 15.5 | 16.2000007629395 | 16.1000003814697 | 16 | 14.6999998092651 | 14.8999996185303 | 16.1000003814697 | 17.7000007629395 | 21.5 | 24.2000007629395 | 24.7000007629395 | 21.1000003814697 | 15.8000001907349 | 19.5 | 22.3999996185303 | 22.2999992370605 | 22.6000003814697
Sub-Saharan Africa (developing only) | SSA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.235351190097582 | 9.157332553117302 | 9.3055301330794 | 8.83977464133817 | 8.679948115277229 | 9.314056622252036 | 9.439883055513139 | 9.540826715723115 | 9.718337686387365 | 9.697860642094934 | 9.621088849167974 | 9.459281738343524 | 9.242399058911365 | 8.703968284470204 | 8.389868985491205 | 8.510406246946959 | 8.223272666752882 | 8.394223992696746 | 8.32707366921646 | 8.261917252470631 | 8.32089279234425 | 8.290660191637164
South Sudan | SSD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Sub-Saharan Africa (all income levels) | SSF | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.233790695389658 | 9.154282211079034 | 9.303319385932967 | 8.837769459101002 | 8.678026531454892 | 9.309790128206199 | 9.433603142192135 | 9.53778072629424 | 9.715115205091626 | 9.694966102295567 | 9.616765878670606 | 9.456707007963548 | 9.240222857090407 | 8.701502565886182 | 8.388847510607397 | 8.509669927108817 | 8.222100731518076 | 8.393183708017704 | 8.326834700396985 | 8.261745985361957 | 8.32034083061335 | 8.290138919556876
Small states | SST | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.97922625835494 | 20.43693420151345 | 20.70430903053607 | 20.35808558575878 | 19.98502279207183 | 19.58728966937198 | 20.57506307263718 | 19.61558815213453 | 18.74998715154736 | 20.10418734122279 | 19.56781220831355 | 18.47073064940947 | 19.08825001247751 | 18.5909674896082 | 18.18142495628297 | 17.01103988897801 | 15.80950802692812 | 17.75267186340377 | 17.00195712689258 | 16.23355124553421 | 16.14725072133115 | 15.94872390407889
Sao Tome and Principe | STP | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Suriname | SUR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.3999996185303 | 23.5 | 22.5 | 15.5 | 11.3000001907349 | 15.3000001907349 | 14.5 | 14.3999996185303 | 20.3999996185303 | 20.2000007629395 | 19.2999992370605 | 19.6000003814697 | 19.2999992370605 | 19.2000007629395 | 19.6000003814697 | 19.5 | 19.6000003814697 | 19.7000007629395 | 19.7999992370605 | 19.5 | 19.2999992370605 | 19.2999992370605
Slovak Republic | SVK | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.1999998092651 | 12.6000003814697 | 14.1000003814697 | 13.8000001907349 | 12.6999998092651 | 12.8000001907349 | 13.1000003814697 | 16.2999992370605 | 18.5 | 18.6000003814697 | 18.7000007629395 | 17.7000007629395 | 19.1000003814697 | 17.2000007629395 | 14.6999998092651 | 12.5 | 11.1000003814697 | 12.8999996185303 | 14.6000003814697 | 13.5 | 14.5
Slovenia | SVN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 4.90000009536743 | 6.59999990463257 | 7 | 6.80000019073486 | 6.59999990463257 | 6.90000009536743 | 7.40000009536743 | 7.40000009536743 | 7.09999990463257 | 6 | 6.80000019073486 | 7.09999990463257 | 6.80000019073486 | 7 | 7.19999980926514 | 5.90000009536743 | 4.90000009536743 | 5.80000019073486 | 7.09999990463257 | 8.19999980926514 | 9.39999961853027
Sweden | SWE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 4.69999980926514 | 7.80000019073486 | 8.30000019073486 | 8.39999961853027 | 9.60000038146973 | 9.80000019073486 | 8.10000038146973 | 6.90000009536743 | 5.5 | 4.80000019073486 | 4.80000019073486 | 5.30000019073486 | 6.30000019073486 | 7.69999980926514 | 7.30000019073486 | 6.59999990463257 | 6.69999980926514 | 8.10000038146973 | 8.60000038146973 | 7.80000019073486 | 7.80000019073486
Swaziland | SWZ | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.7999992370605 | 24.6000003814697 | 24.5 | 24.5 | 22.7999992370605 | 23.6000003814697 | 25.7999992370605 | 25.7999992370605 | 25.8999996185303 | 25.8999996185303 | 26 | 26 | 26 | 26.1000003814697 | 26.1000003814697 | 26.1000003814697 | 26.1000003814697 | 26.1000003814697 | 26.1000003814697 | 26 | 25.8999996185303 | 25.7999992370605
Sint Maarten (Dutch part) | SXM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Seychelles | SYC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Syrian Arab Republic | SYR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.5 | 22.6000003814697 | 17.3999996185303 | 17.1000003814697 | 16.3999996185303 | 22.8999996185303 | 19.2999992370605 | 16.7000007629395 | 17.7999992370605 | 22.2000007629395 | 27.3999996185303 | 24.1000003814697 | 21 | 21.8999996185303 | 22.6000003814697 | 24.1000003814697 | 25.6000003814697 | 24.1000003814697 | 22.1000003814697 | 23 | 22.8999996185303 | 22.2999992370605
Turks and Caicos Islands | TCA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Chad | TCD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 8.19999980926514 | 8.39999961853027 | 8.10000038146973 | 8.39999961853027 | 8.30000019073486 | 8.10000038146973 | 8.10000038146973 | 8.39999961853027 | 8.5 | 7.90000009536743 | 8 | 7.80000019073486 | 7 | 8.10000038146973 | 8.5 | 8.5 | 8.39999961853027 | 8.60000038146973 | 7.90000009536743 | 8.5 | 8.30000019073486
Togo | TGO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.30000019073486 | 8.5 | 9.10000038146973 | 7.69999980926514 | 8 | 8 | 8.19999980926514 | 8.5 | 8.19999980926514 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.10000038146973 | 8.19999980926514 | 8.19999980926514 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8 | 8 | 7.90000009536743 | 7.90000009536743
Thailand | THA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.70000004768372 | 1.39999997615814 | 1.5 | 1.60000002384186 | 1.39999997615814 | 1.20000004768372 | 1 | 3.40000009536743 | 3 | 2.29999995231628 | 2.5 | 1.70000004768372 | 1.39999997615814 | 1.29999995231628 | 1.20000004768372 | 1.10000002384186 | 1.10000002384186 | 1 | 1.5 | 1 | 0.699999988079071 | 0.600000023841858
Tajikistan | TJK | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 10.5 | 11.3000001907349 | 10.6999998092651 | 11.1000003814697 | 11.6999998092651 | 11.8000001907349 | 11.8999996185303 | 11.8999996185303 | 12 | 12.1000003814697 | 12.1000003814697 | 12.1000003814697 | 12.1000003814697 | 12 | 12 | 12 | 12 | 11.8999996185303 | 11.8999996185303 | 11.8000001907349 | 11.8000001907349
Turkmenistan | TKM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3000001907349 | 11.1999998092651 | 11 | 10.6000003814697 | 11.1000003814697 | 11.3000001907349 | 11.1000003814697 | 11.6000003814697 | 11.8999996185303 | 11.8999996185303 | 12 | 11.8999996185303 | 11.8999996185303 | 11.8000001907349 | 11.8000001907349 | 11.6999998092651 | 11.6999998092651 | 11.8000001907349 | 11.6000003814697 | 11.6000003814697 | 11.6999998092651 | 11.3999996185303
Timor-Leste | TLS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10 | 9.60000038146973 | 9.30000019073486 | 8.89999961853027 | 8.69999980926514 | 8.60000038146973 | 8.69999980926514 | 9.60000038146973 | 8.80000019073486 | 8.5 | 12.6000003814697 | 11.6999998092651 | 10.8999996185303 | 10 | 9.19999980926514 | 8.39999961853027 | 8.60000038146973 | 7.80000019073486 | 7 | 5.69999980926514 | 5.69999980926514 | 5.59999990463257
Tonga | TON | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Trinidad and Tobago | TTO | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.7000007629395 | 23.6000003814697 | 23.3999996185303 | 21.7999992370605 | 20.5 | 21.1000003814697 | 19.6000003814697 | 18.7999992370605 | 16.7000007629395 | 15.1000003814697 | 14.1999998092651 | 14.3999996185303 | 14.5 | 11.3999996185303 | 11 | 8.80000019073486 | 7.90000009536743 | 6.19999980926514 | 6.30000019073486 | 7 | 7.30000019073486 | 6.69999980926514
Tunisia | TUN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19 | 19 | 18.8999996185303 | 17 | 18.2999992370605 | 17.7999992370605 | 17.2999992370605 | 20 | 18.6000003814697 | 18.1000003814697 | 17.3999996185303 | 17.5 | 16.5 | 15.6999998092651 | 15.6000003814697 | 14 | 13.8999996185303 | 13.8999996185303 | 14.8999996185303 | 14.6000003814697 | 14.5 | 14.3000001907349
Turkey | TUR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 7.59999990463257 | 9.10000038146973 | 7.90000009536743 | 7.09999990463257 | 5.80000019073486 | 7.59999990463257 | 6.59999990463257 | 7.40000009536743 | 6.09999990463257 | 7.30000019073486 | 9.30000019073486 | 9.89999961853027 | 10.8000001907349 | 11 | 10.8999996185303 | 10.8000001907349 | 11.3999996185303 | 14.1000003814697 | 12.8000001907349 | 11.1000003814697 | 10.6999998092651
Tuvalu | TUV | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Tanzania | TZA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 4.5 | 4.80000019073486 | 4.90000009536743 | 6 | 6.59999990463257 | 6 | 6.19999980926514 | 6 | 6.59999990463257 | 6.5 | 4.59999990463257 | 4.19999980926514 | 3.70000004768372 | 3.20000004768372 | 5.59999990463257 | 2.59999990463257 | 3.20000004768372 | 3.20000004768372 | 3.79999995231628 | 4.5 | 4.5
Uganda | UGA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 3 | 2.59999990463257 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.79999995231628 | 2.79999995231628 | 3.29999995231628 | 3.79999995231628 | 4 | 3.70000004768372 | 2.90000009536743 | 2.29999995231628 | 2.29999995231628 | 2.40000009536743 | 3.40000009536743 | 4.80000019073486 | 4.80000019073486 | 4.80000019073486 | 4.90000009536743
Ukraine | UKR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.5 | 7.30000019073486 | 8.5 | 6.80000019073486 | 5.40000009536743 | 7.30000019073486 | 8.60000038146973 | 10.8999996185303 | 11.1999998092651 | 11.1999998092651 | 10.5 | 9.19999980926514 | 8.69999980926514 | 8.30000019073486 | 6.80000019073486 | 6.5 | 6.09999990463257 | 6.09999990463257 | 8.39999961853027 | 7.69999980926514 | 7.59999990463257 | 7.30000019073486
Upper middle income | UMC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.938100823459062 | 5.293014425662061 | 5.368138623700649 | 5.278260736787345 | 5.638352017954142 | 5.801719613670515 | 5.917220831876742 | 6.162840257920895 | 6.207438256711742 | 6.164397194244455 | 6.153346140918305 | 6.208090913618251 | 6.173323934035695 | 5.960137107592894 | 5.809644338005618 | 5.547020004233803 | 5.292050866898856 | 5.544167199956388 | 5.800271737658271 | 5.661192368634542 | 5.608067683148202 | 5.649151288209347
Uruguay | URY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 11.5 | 11.1000003814697 | 12.5 | 13.1999998092651 | 13.8999996185303 | 12.5 | 14.8000001907349 | 14 | 13.3000001907349 | 12.6000003814697 | 11.8000001907349 | 11.1000003814697 | 12.5 | 12.1999998092651 | 14.3999996185303 | 12.5 | 10.3999996185303 | 9.89999961853027 | 9.10000038146973 | 7.80000019073486 | 8
United States | USA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.5 | 7.09999990463257 | 6.69999980926514 | 6.09999990463257 | 5.69999980926514 | 5.5 | 5.09999990463257 | 4.69999980926514 | 4.40000009536743 | 4.19999980926514 | 4.69999980926514 | 5.69999980926514 | 5.69999980926514 | 5.5 | 5.19999980926514 | 4.69999980926514 | 4.59999990463257 | 5.5 | 8.10000038146973 | 8.69999980926514 | 8.5 | 7.90000009536743
Uzbekistan | UZB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 11 | 11.3999996185303 | 11.3000001907349 | 11.5 | 11.6000003814697 | 11.6999998092651 | 11.6999998092651 | 11.6999998092651 | 11.6000003814697 | 11.6000003814697 | 11.6000003814697 | 11.6000003814697 | 11.6999998092651 | 11.6999998092651 | 11.6999998092651 | 11.8000001907349 | 11.8000001907349 | 11.6999998092651 | 11.6999998092651 | 11.6000003814697 | 11.6000003814697
St. Vincent and the Grenadines | VCT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Venezuela, RB | VEN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8999996185303 | 8.89999961853027 | 7.69999980926514 | 8.60000038146973 | 12.1000003814697 | 16.1000003814697 | 13.5 | 12.6999998092651 | 16 | 14.3000001907349 | 14.6000003814697 | 18.7999992370605 | 20.2999992370605 | 18.1000003814697 | 13.6999998092651 | 11.1000003814697 | 8.19999980926514 | 7.40000009536743 | 8.39999961853027 | 9.19999980926514 | 9.30000019073486 | 8.80000019073486
Virgin Islands (U.S.) | VIR | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Vietnam | VNM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 2.59999990463257 | 3.40000009536743 | 2.5 | 2 | 1.70000004768372 | 2.59999990463257 | 2.09999990463257 | 2.40000009536743 | 2.20000004768372 | 3.29999995231628 | 2.29999995231628 | 2.70000004768372 | 2.40000009536743 | 2.29999995231628 | 2.5 | 2.5 | 2.59999990463257 | 2.59999990463257 | 2.5 | 2.20000004768372 | 2.20000004768372
[NAME] | VUT | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
West Bank and Gaza | PSE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.3999996185303 | 20.3999996185303 | 19.7999992370605 | 19 | 19.2000007629395 | 18.5 | 15.8000001907349 | 11.1000003814697 | 9.10000038146973 | 10.8999996185303 | 13.8000001907349 | 16.7999992370605 | 17.6000003814697 | 20.2999992370605 | 20.2999992370605 | 20.5 | 19.5 | 23.7000007629395 | 20 | 19.5 | 16.5 | 18
World | WLD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.692684505715428 | 6.111131295166778 | 6.367050922094097 | 6.322104013572309 | 6.415128884318391 | 6.524518284787213 | 6.679727265939724 | 6.772976037744919 | 6.771744946486258 | 6.65766123101471 | 6.694369952737724 | 6.803274745782632 | 6.778359555908612 | 6.630421944912989 | 6.572074724908615 | 6.280539920852245 | 5.798236562331092 | 5.981157199362117 | 6.442974415597453 | 6.472550365909083 | 6.388981044296388 | 6.387231071593337
Samoa | WSM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS
Yemen, Rep. | YEM | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.7999992370605 | 23.2999992370605 | 21.1000003814697 | 25 | 23.5 | 22.1000003814697 | 23.6000003814697 | 25.2999992370605 | 22.6000003814697 | 26.3999996185303 | 23 | 23 | 23.2999992370605 | 23 | 25.7000007629395 | 25 | 24.2999992370605 | 23.7000007629395 | 23 | 28 | 27.6000003814697 | 27.1000003814697
South Africa | ZAF | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30 | 27.6000003814697 | 29.7000007629395 | 23.6000003814697 | 19.8999996185303 | 24.6000003814697 | 26.7000007629395 | 29.6000003814697 | 30.3999996185303 | 29 | 27.8999996185303 | 31.3999996185303 | 31.2000007629395 | 28.8999996185303 | 28.3999996185303 | 27.3999996185303 | 26.7000007629395 | 26.3999996185303 | 26.1000003814697 | 27.3999996185303 | 27.7999992370605 | 27.7999992370605
Congo, Dem. Rep. | COD | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.19999980926514 | 8.30000019073486 | 8.39999961853027 | 8 | 7.80000019073486 | 7.90000009536743 | 8.10000038146973 | 7.90000009536743 | 8 | 8.10000038146973 | 7.90000009536743 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.5 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.69999980926514 | 7.5 | 7.5 | 7.5
Zambia | ZMB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8999996185303 | 16.1000003814697 | 16.6000003814697 | 16 | 15.6000003814697 | 12.8999996185303 | 12.1999998092651 | 10.1000003814697 | 10.3000001907349 | 10.8999996185303 | 12.6999998092651 | 12.3000001907349 | 13 | 13.3000001907349 | 13.6000003814697 | 13.3999996185303 | 13.3000001907349 | 13.3999996185303 | 13.1999998092651 | 11.6000003814697 | 11.6000003814697 | 11.3000001907349
Zimbabwe | ZWE | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 4.30000019073486 | 4.5 | 3.79999995231628 | 4.19999980926514 | 4.5 | 4.90000009536743 | 4.80000019073486 | 4.5 | 4.69999980926514 | 4.69999980926514 | 4.59999990463257 | 4.5 | 4.30000019073486 | 4.30000019073486 | 4.19999980926514 | 4.19999980926514 | 4.5 | 4 | 4 | 3.90000009536743 | 3.70000004768372