Spreadsheet: 85657782-0338-4dc9-ba82-3ffe0890ddf1
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
Arab World | ARB | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.7203399725964 | 20.50034650384591 | 21.45008126822618 | 21.2264328180915 | 21.49133065257147 | 21.2548921583504 | 20.40176733541092 | 19.93343875217206 | 19.32178517952802 | 20.98284150734084 | 20.95740483440112 | 21.13722199786381 | 21.13379424598196 | 20.03618071738376 | 19.85820010448012 | 18.90426283823367 | 17.56914957100892 | 17.59719203664115 | 18.16190866368643 | 18.29625566024603 | 19.42201675935307 | 19.51843721538397
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
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.21682113246989 | 22.03261855111677 | 22.51910016728097 | 22.20576961358646 | 22.13750407865415 | 22.15573190364816 | 21.72093049854835 | 20.33692918231092 | 20.65955511442359 | 18.77625299911707 | 18.8325344715507 | 18.14252341272791 | 16.84096858674789 | 15.55519681783037 | 14.8877329916086 | 13.75321861438481 | 12.690337453235 | 13.37576563915391 | 13.97147272113838 | 14.59538617567643 | 14.92501950535124 | 15.29545788629498
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.329791850570261 | 3.677648630308876 | 3.824979813328491 | 3.839424505455254 | 3.849072824516587 | 3.870192308934616 | 4.003981140428508 | 4.266297938950638 | 4.206554351948013 | 4.109933979552418 | 4.524464606865761 | 4.434662834399867 | 4.486277211316401 | 4.518386778006788 | 4.336778223171282 | 4.197638277036629 | 3.840002851155852 | 4.130884174437194 | 4.062614456777366 | 3.918713065649334 | 3.959816952686084 | 4.034018303706012
East Asia & Pacific (all income levels) | EAS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.191123343954199 | 3.611029064493442 | 3.77726347161596 | 3.795967954199661 | 3.809719031327517 | 3.831624203017236 | 3.964561508716011 | 4.304624143819852 | 4.265492326976982 | 4.141259715909463 | 4.530028235128329 | 4.45974527075163 | 4.506749822874738 | 4.498318325370691 | 4.316836034227767 | 4.152978571020821 | 3.81412651784516 | 4.081799810323705 | 4.093016994258206 | 3.955593687711863 | 3.961039157324313 | 4.021664338062056
Europe & Central Asia (developing only) | ECA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.659283509144304 | 10.01253776588508 | 11.03625067369942 | 10.04525523367857 | 9.864469288524182 | 10.04635813060616 | 10.4630186098983 | 10.89273157648514 | 10.9342022315705 | 10.75681051330446 | 10.88547483579852 | 10.72820121647499 | 10.36307474109796 | 10.46283572194672 | 10.18234379281791 | 10.06071799817606 | 9.631488773089384 | 9.328017514725179 | 10.49951355750048 | 10.49627273408306 | 10.16490773611463 | 9.9769034137633
Europe & Central Asia (all income levels) | ECS | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.39396900655664 | 9.400582200177722 | 10.45966939711755 | 10.9494202422094 | 10.9475536299365 | 10.98311607931405 | 11.44366542393582 | 11.58259173994788 | 11.36852357741379 | 10.59416335382783 | 9.77200005509417 | 9.600453582469473 | 9.58075825032312 | 9.627539577411499 | 9.287761030798196 | 8.800721433155891 | 7.858769948440029 | 7.636967959830239 | 9.054321355532865 | 9.248280983710071 | 9.061805967128931 | 9.321325566991506
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.40236631219807 | 11.86294290960611 | 13.19172631625892 | 14.05315536368165 | 13.82617721866046 | 13.89716009179739 | 13.91826449449139 | 13.390462611859 | 12.55700620737215 | 11.37695481429362 | 9.884959268607275 | 10.05836869462591 | 10.11438679119638 | 10.44165075390126 | 10.15298944745381 | 9.520827260899742 | 8.543424441430746 | 8.344246268474738 | 9.727371952254856 | 10.31285206342979 | 10.39858296366114 | 11.55314443270531
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.40279893925609 | 10.86492694609442 | 12.1498625306998 | 12.6091219007599 | 12.20055048843655 | 11.99815025163139 | 11.78349619277537 | 11.27637227369123 | 10.88571108907314 | 10.55677027779328 | 9.700969741256936 | 9.920512597436945 | 9.815450040605326 | 9.97593042362083 | 9.726694999089949 | 8.999492617502717 | 7.891324877207524 | 7.494569236017999 | 8.895690072520782 | 9.595805164319874 | 9.723190974162197 | 10.55508980634339
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.303090704441606 | 7.690709064978479 | 8.20522728647323 | 8.505703237424418 | 8.386593591256092 | 8.344786599921427 | 8.457275589395195 | 8.539517258166706 | 8.323356010959513 | 7.669033415272373 | 7.228985201650987 | 7.462521651924175 | 7.56062234812428 | 7.481314557495048 | 7.127558398973023 | 6.623333785317763 | 5.969961955990939 | 6.118994407438342 | 7.771754815893739 | 8.029992317827515 | 7.82264249204913 | 7.881439429873568
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.85170967611277 | 7.888371573225078 | 7.866267634328716 | 7.771426992980357 | 7.83205213571925 | 8.320528953295927 | 8.133882755570486 | 8.038269638786055 | 8.042727764390326 | 8.06069040674726 | 8.100559858390069 | 7.728550790865562 | 7.495175310406013 | 7.099576728954188 | 6.627327605847135 | 6.867333571598955 | 6.638960044917252 | 6.74794499137479 | 6.833450515772963 | 6.798223397781848 | 6.840738341671153 | 6.842779695636335
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.60885513660921 | 8.164734848660746 | 8.34958542266639 | 8.404758634852792 | 9.766355196937889 | 10.41227551104344 | 10.33008034970894 | 10.5296090755032 | 10.71639881836982 | 10.89704714814423 | 10.70126283796203 | 11.01295316222486 | 11.34383656288686 | 10.64116618445778 | 10.18400577694271 | 9.2613759005971 | 8.891388632403661 | 8.509632843419359 | 9.243267102821644 | 8.924577696383645 | 8.15882248300985 | 8.065630941433188
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.71338369047876 | 8.361564553196699 | 8.528198128571042 | 8.559356002509626 | 9.820710043717067 | 10.4304643449331 | 10.33097501053581 | 10.53117728103961 | 10.75154262041626 | 10.88612899220291 | 10.69352798472064 | 10.99488311311153 | 11.31255444939367 | 10.64401520741428 | 10.19314307927871 | 9.306243635476513 | 8.910233413402091 | 8.552823709292092 | 9.304389213186564 | 8.967882155535303 | 8.200251586897746 | 8.088112780282955
Least developed countries: UN classification | LDC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.587814676498837 | 6.585494996807054 | 6.448667750170345 | 6.47396628717693 | 6.620204126467503 | 6.609002334609098 | 6.758530621591995 | 6.615835569274383 | 6.519636164749866 | 6.744634053504674 | 6.732171843370808 | 6.476630751181462 | 6.577534922377061 | 6.472503608974742 | 6.490309602205415 | 6.482355236302704 | 6.303880399264141 | 6.450131710432021 | 6.649569024646106 | 6.453053408123972 | 6.491582009101872 | 6.491079546595042
Low income | LIC | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.920565959398604 | 5.913974678080179 | 5.748834320256728 | 5.734059573714894 | 5.916511585197423 | 6.076421468068014 | 6.11678936875669 | 6.067245133094866 | 5.974597221837628 | 6.09999838904319 | 6.111095417636439 | 5.922691750178302 | 5.951212650167533 | 5.832830471841633 | 5.838258238432134 | 5.845045156357692 | 5.691954054790192 | 5.870140980290802 | 6.059932844622264 | 5.828861736972488 | 5.864097560604281 | 5.873961717329016
[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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.688462606466391 | 6.015799158512614 | 6.549883939869573 | 6.234671121463951 | 6.040522871707854 | 6.195623053178953 | 6.536986078416834 | 6.455276133090396 | 6.626379200294574 | 6.818036180165499 | 7.422063503386852 | 7.649275595051045 | 7.489278095360302 | 7.366316276885522 | 7.686052642031713 | 7.403710584959142 | 6.542060857990057 | 6.64700325433647 | 6.495075978589272 | 6.745768805751903 | 6.672491206186948 | 6.544771075347797
Low & middle income | LMY | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.159055151231312 | 5.597869627268423 | 5.77993667393122 | 5.635294439605961 | 5.801369653724626 | 5.962206558366215 | 6.135125476788208 | 6.238797873946006 | 6.302011056039571 | 6.354126739418493 | 6.537455880751881 | 6.610502314974727 | 6.550927831271919 | 6.385000579195869 | 6.413283626241764 | 6.182459611581078 | 5.749320508074621 | 5.942051303640306 | 6.059318569260499 | 6.024049526117668 | 5.981880690747065 | 5.967022433022876
[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
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.73455597441908 | 20.67748500977916 | 21.35656103234344 | 20.90341345511478 | 21.02098689631245 | 20.64837981313601 | 19.4883820263152 | 19.2874813711879 | 18.65735719987229 | 20.60627063508196 | 20.38413771313198 | 20.8286388287417 | 20.64096514275265 | 19.00894746865106 | 19.31622266277089 | 18.23331084346922 | 16.68076158086267 | 16.84559580688615 | 17.4594298415486 | 18.17202256397805 | 19.14216811742888 | 19.14447893565278
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.198486180547294 | 5.545397438670659 | 5.785135213265337 | 5.618756981792217 | 5.781999419203339 | 5.942876163042768 | 6.138249393575877 | 6.268190603071227 | 6.358310696614777 | 6.398362983811602 | 6.612374843475665 | 6.732672724780778 | 6.658508672803239 | 6.484975371107662 | 6.518331332578872 | 6.245518468469718 | 5.760279246915341 | 5.956109823499969 | 6.059195777007612 | 6.064000519169824 | 6.006253220490155 | 5.986505774136923
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.06821798360318 | 21.38448521170092 | 22.41551255520545 | 22.56481316313207 | 23.16152038111489 | 22.13747555881017 | 20.81930613584874 | 20.58108656716544 | 20.47634857530135 | 22.74074004179523 | 22.48636562035634 | 22.81241140143669 | 22.17625554649575 | 19.93763911412545 | 21.01601774479812 | 19.61943325573804 | 17.91947107161553 | 18.18249445274595 | 18.78298794893037 | 19.7023672982418 | 21.0757110959146 | 20.74989513266612
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.82806989525753 | 7.413087320590773 | 7.102145775406707 | 6.464944139776765 | 6.033424626079917 | 5.870871713005803 | 5.470096683596163 | 5.023767336235105 | 4.685628995333592 | 4.448100742049562 | 4.920428747672908 | 5.843244125517389 | 5.856421537149763 | 5.647192642292148 | 5.33614436532879 | 4.847036930880574 | 4.706437845343158 | 5.510668675828217 | 7.982055689530681 | 8.537433040804244 | 8.33579520746916 | 7.778975599350074
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.52850198072573 | 5.948740396080963 | 6.547374972744636 | 8.319940190491245 | 9.21390792904432 | 9.445053666035443 | 11.10889429422629 | 12.39024136343089 | 12.22447259499928 | 10.18895865081452 | 8.782355338158606 | 8.0165871731243 | 8.376920810001128 | 8.075171066242293 | 7.233555257536834 | 7.065209418881429 | 6.031553029640508 | 6.297964774361135 | 8.060458004236756 | 7.447854110920042 | 6.691789948813422 | 6.188618608539729
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.568837207755914 | 8.075851741786062 | 8.559339027575716 | 8.543725383533008 | 8.217327311447242 | 8.124348631244029 | 7.93809249283002 | 7.795820417261012 | 7.524382797367261 | 7.153466322739126 | 6.916081613252303 | 7.34933521112158 | 7.391896462677448 | 7.358160606572158 | 7.105534361089046 | 6.531640995437096 | 5.957132655156604 | 6.082052949022934 | 7.712190693832459 | 8.148949283886841 | 8.055895939038802 | 8.231046249579647
OECD members | OED | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.415921676928663 | 7.871287529829881 | 8.354719242340508 | 8.334502914276104 | 8.210951528263298 | 7.989885356771853 | 7.8183910877865 | 7.583073671251007 | 7.272696763398329 | 6.875706118481286 | 6.694047697732975 | 7.150242832477812 | 7.210967739413081 | 7.255774630949857 | 6.969148606414024 | 6.439697293049022 | 5.929005395487681 | 6.074939064002661 | 7.693870376314949 | 8.087558726921094 | 7.962485182878235 | 8.072502614664716
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.12856806199487 | 20.44883538130138 | 20.62943564481068 | 20.29326723028602 | 19.82361204830742 | 19.2203614311797 | 20.87792773586418 | 19.95548341071385 | 18.54983826916572 | 21.34603952964313 | 20.6123269669493 | 19.30424335793166 | 20.59947606921377 | 20.58405153897536 | 20.26544577418974 | 18.88277093588761 | 17.42693848216472 | 19.95645362607948 | 18.59368652086915 | 17.26016753215476 | 17.02265886764971 | 16.59313983053985
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.85196601039956 | 4.666595370268749 | 4.584535971163616 | 4.217815325233209 | 4.459482158790456 | 4.496751170464515 | 4.874178058852655 | 4.310021545648277 | 4.467673911910067 | 4.711849504270101 | 4.631468041019086 | 5.160971692840183 | 4.746298354691592 | 4.6647588801787 | 5.622351007218805 | 5.285068471156396 | 4.506407552724142 | 4.831604529764427 | 4.733644331051662 | 4.899919020945522 | 4.836192392443223 | 4.641925014351117
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
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.235351135040196 | 9.157332629438311 | 9.30553002921072 | 8.839774544138212 | 8.6799482017836 | 9.314056591937886 | 9.439882957486397 | 9.540826646560692 | 9.718337609742571 | 9.697860757414727 | 9.62108872207798 | 9.459282018882288 | 9.242399241685565 | 8.703968314327774 | 8.389868924096875 | 8.510406249102664 | 8.223272581476742 | 8.394224050108905 | 8.327073502390432 | 8.261917240121157 | 8.320892886468249 | 8.290661412488657
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.233790643848293 | 9.154282281077705 | 9.303319283988309 | 8.837769371749447 | 8.678026610374758 | 9.309790081447947 | 9.433603073961926 | 9.537780658716416 | 9.715115138286075 | 9.69496620891929 | 9.61676576361603 | 9.456707292419082 | 9.240223037563354 | 8.701502604488361 | 8.388847447639526 | 8.50966993103654 | 8.222100645637697 | 8.393183767879638 | 8.326834534099392 | 8.261745973236259 | 8.320340923642718 | 8.290140139646917
Small states | SST | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.97922282285494 | 20.43693939588895 | 20.70430891777244 | 20.3580870059897 | 19.98502066899059 | 19.58728701511956 | 20.5750717960842 | 19.61558989856229 | 18.74998229872612 | 20.10418684498842 | 19.56781479602369 | 18.47073431512979 | 19.0882529412523 | 18.59096509914326 | 18.18138497597527 | 17.00867366708322 | 15.80581520837019 | 17.74557367691772 | 16.99299221194548 | 16.22244438836388 | 16.13935066114905 | 15.94016938826608
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.939521775223114 | 5.295016631505892 | 5.37043772819269 | 5.280368438164694 | 5.640305686642365 | 5.803457002721844 | 5.919212481744742 | 6.164704496704158 | 6.209397725565727 | 6.165085111699584 | 6.155294964714276 | 6.208860837038504 | 6.173803422084432 | 5.960621237007823 | 5.810112627533319 | 5.547586863904867 | 5.292634055273485 | 5.544870176420558 | 5.801236920955307 | 5.662340754285723 | 5.609500005928663 | 5.650803814822802
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.69325614149451 | 6.111946348576452 | 6.367983587305668 | 6.322956686219765 | 6.415928825977605 | 6.524973347595505 | 6.679934030398892 | 6.772768865775451 | 6.771333368461391 | 6.65809115989116 | 6.695144399564684 | 6.803644102913536 | 6.778738038863326 | 6.630866435886815 | 6.572569647850678 | 6.281057495378569 | 5.798767185221654 | 5.981830050159433 | 6.443867460950227 | 6.473731619841372 | 6.390123207334102 | 6.387784654384501
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