Spreadsheet: c96269e4-cd03-42b2-b1df-05ba41a3234d
Sheet: Sheet1

Data Source | World Development Indicators | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18 | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Unnamed: 22 | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Unnamed: 30 | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Unnamed: 34 | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Unnamed: 38 | Unnamed: 39 | Unnamed: 40 | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Unnamed: 44 | Unnamed: 45 | Unnamed: 46 | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Unnamed: 50 | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Unnamed: 56 | Unnamed: 57
Country Name | Country Code | Indicator Name | Indicator Code | 1960 | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013
Aruba | ABW | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Andorra | AND | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Afghanistan | AFG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.5 | 18.5 | 18.5 | 18.3999996185303 | 18.3999996185303 | 18.3999996185303 | 18.2999992370605 | 18.2999992370605 | 18.2999992370605 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.2000007629395 | 19.2999992370605 | 19.3999996185303 | 19.3999996185303 | 19.5 | 19.3999996185303 | 19.5 | 19.5 | 19.5
Angola | AGO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 13.1999998092651 | 13.8000001907349 | 13 | 12.5 | 12.3999996185303 | 12.8000001907349 | 13 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.6000003814697 | 12.8999996185303 | 12.6999998092651 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.6000003814697 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349
Albania | ALB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.1000003814697 | 24.7000007629395 | 32 | 31 | 29.2000007629395 | 26.3999996185303 | 28.1000003814697 | 26.5 | 27.7999992370605 | 24.6000003814697 | 35.5 | 22.7000007629395 | 20.5 | 20.7000007629395 | 20.6000003814697 | 21.2999992370605 | 22.2999992370605 | 26.5 | 25.2000007629395 | 25.7999992370605 | 25.8999996185303 | 26.2999992370605
Andean Region | ANR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Arab World | ARB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.54143790419763 | 27.44142180285608 | 28.21475641456619 | 28.70778653935804 | 29.17567164268328 | 28.14039679405291 | 27.60304401854584 | 27.39680144271473 | 26.15136466472111 | 28.64763578378432 | 28.94593359534726 | 29.02415581128109 | 29.6576116425132 | 29.30634459250913 | 27.79766504191717 | 26.7303192276582 | 25.46590764889629 | 24.94909714475249 | 24.52687819236106 | 25.07157348114465 | 26.59118486471195 | 26.97964097348936
United Arab Emirates | ARE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.69999980926514 | 6.80000019073486 | 6.90000009536743 | 5.59999990463257 | 6.09999990463257 | 10.3000001907349 | 7.5 | 6.80000019073486 | 6.19999980926514 | 6 | 6.40000009536743 | 6.80000019073486 | 7.30000019073486 | 7.69999980926514 | 7.80000019073486 | 8.10000038146973 | 8.39999961853027 | 11 | 10.8999996185303 | 10.8999996185303 | 10.8999996185303 | 11
Argentina | ARG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.1999998092651 | 12.6000003814697 | 20.7999992370605 | 21.2000007629395 | 33.0999984741211 | 30.6000003814697 | 25.2999992370605 | 22.5 | 23.5 | 26.2000007629395 | 30.3999996185303 | 34.2999992370605 | 35.7999992370605 | 27.8999996185303 | 24.3999996185303 | 25.2000007629395 | 20.3999996185303 | 18.7999992370605 | 21.2000007629395 | 19.5 | 18.7999992370605 | 17.5
Armenia | ARM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.4000015258789 | 40.4000015258789 | 40.5 | 43.4000015258789 | 46.2000007629395 | 41.5999984741211 | 40.7000007629395 | 51.4000015258789 | 40.5 | 47.7000007629395 | 48.2000007629395 | 53.9000015258789 | 55.9000015258789 | 47.2000007629395 | 55.5 | 44.9000015258789 | 58.2999992370605 | 55.2000007629395 | 40.2999992370605 | 38.2000007629395 | 38.5999984741211 | 38.2999992370605
American Samoa | ASM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
[NAME] and [NAME] | ATG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Australia | AUS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.5 | 19.3999996185303 | 18.7000007629395 | 17.1000003814697 | 15.3999996185303 | 15.6999998092651 | 16.1000003814697 | 14.6000003814697 | 13.3000001907349 | 12.1000003814697 | 13.5 | 12.8000001907349 | 12 | 11.3999996185303 | 10.6000003814697 | 10 | 9.30000019073486 | 8.80000019073486 | 11.5 | 11.5 | 11.3000001907349 | 11.6999998092651
Austria | AUT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.70000004768372 | 4.09999990463257 | 4.69999980926514 | 5 | 5.19999980926514 | 6.30000019073486 | 6.30000019073486 | 5.69999980926514 | 5.09999990463257 | 5.09999990463257 | 5.59999990463257 | 6.19999980926514 | 7 | 9.60000038146973 | 10.3000001907349 | 9 | 8.60000038146973 | 8 | 9.89999961853027 | 8.80000019073486 | 8.30000019073486 | 8.69999980926514
Azerbaijan | AZE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 12.3000001907349 | 11.8999996185303 | 11.5 | 12.3000001907349 | 13.8999996185303 | 12.8999996185303 | 13.8000001907349 | 13.3000001907349 | 13.6999998092651 | 13.6000003814697 | 13.1000003814697 | 13 | 12.8000001907349 | 13.6999998092651 | 16.5 | 13.8999996185303 | 14.3999996185303 | 13.6999998092651 | 14.6000003814697 | 14.5 | 14.1999998092651
Burundi | BDI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 13 | 13.1999998092651 | 13.1000003814697 | 13.3000001907349 | 13.3000001907349 | 13 | 12.8999996185303 | 13 | 13 | 13 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303
Belgium | BEL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.8999996185303 | 13.1999998092651 | 18.5 | 22 | 21.6000003814697 | 20.5 | 21.2999992370605 | 20.3999996185303 | 22.6000003814697 | 15.3000001907349 | 15.3999996185303 | 17.7999992370605 | 21.8999996185303 | 21.2000007629395 | 21.5 | 20.5 | 18.7999992370605 | 17.8999996185303 | 21.8999996185303 | 22.3999996185303 | 18.7000007629395 | 19.7999992370605
Benin | [NAME] | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1 | 1.70000004768372 | 1.39999997615814 | 1.20000004768372 | 1.10000002384186 | 0.899999976158142 | 1.10000002384186 | 1.39999997615814 | 1.20000004768372 | 1.10000002384186 | 0.899999976158142 | 0.800000011920929 | 1.5 | 1.60000002384186 | 1.60000002384186 | 2 | 2 | 1.89999997615814 | 1.89999997615814 | 2 | 2 | 1.79999995231628
[NAME] | BFA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 3.79999995231628 | 5 | 4.19999980926514 | 3.90000009536743 | 3.90000009536743 | 3.70000004768372 | 3.79999995231628 | 3.70000004768372 | 4.80000019073486 | 3.70000004768372 | 4.69999980926514 | 4.5 | 4.40000009536743 | 4.30000019073486 | 3.70000004768372 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486 | 5.30000019073486
Bangladesh | BGD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 8.80000019073486 | 8.30000019073486 | 7.80000019073486 | 7.30000019073486 | 6.19999980926514 | 7.80000019073486 | 6.40000009536743 | 8.60000038146973 | 9.39999961853027 | 9 | 8.5 | 6.30000019073486 | 7.19999980926514 | 8.60000038146973 | 9 | 9.19999980926514 | 9.39999961853027 | 10.8999996185303 | 8.19999980926514 | 8.19999980926514 | 8.89999961853027
Bulgaria | BGR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.9000015258789 | 27.5 | 42.7999992370605 | 40.2000007629395 | 31.7000007629395 | 27.5 | 28.1000003814697 | 25.2000007629395 | 29.3999996185303 | 33.4000015258789 | 39.0999984741211 | 35.5 | 27 | 24.2999992370605 | 22.2000007629395 | 19.2999992370605 | 15 | 12.6999998092651 | 16.1000003814697 | 23.1000003814697 | 25.1000003814697 | 28.2000007629395
Bahrain | BHR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.7000007629395 | 24.3999996185303 | 23.3999996185303 | 22.3999996185303 | 20.5 | 20.2999992370605 | 22.2000007629395 | 21.3999996185303 | 20 | 21.7999992370605 | 19.2999992370605 | 21.2000007629395 | 23.1000003814697 | 26.6000003814697 | 26.6000003814697 | 26.6000003814697 | 26.7000007629395 | 26.7000007629395 | 26.7000007629395 | 26.7999992370605 | 26.7999992370605 | 27.5
Bahamas, The | BHS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.6000003814697 | 26.7000007629395 | 23.5 | 24.2999992370605 | 20.7999992370605 | 23.7999992370605 | 22.2000007629395 | 15.3000001907349 | 15.5 | 15.3000001907349 | 15.1000003814697 | 19.2000007629395 | 24.2000007629395 | 23.2000007629395 | 20.2000007629395 | 15.6999998092651 | 18.8999996185303 | 19.1000003814697 | 31.2000007629395 | 30.8999996185303 | 30.2000007629395 | 29.2999992370605
Bosnia and Herzegovina | BIH | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 47.5 | 48.9000015258789 | 54 | 56.7000007629395 | 51.2999992370605 | 52.4000015258789 | 58.0999984741211 | 54.5 | 53 | 51.4000015258789 | 56.5 | 49.9000015258789 | 52.7999992370605 | 58.0999984741211 | 52.7999992370605 | 62.5 | 58.5 | 47.7000007629395 | 48.7000007629395 | 57.2000007629395 | 57.0999984741211 | 57.5
Belarus | BLR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.7000007629395 | 20.2000007629395 | 20.2999992370605 | 20.1000003814697 | 20.1000003814697 | 21.1000003814697 | 21.6000003814697 | 21.3999996185303 | 21.1000003814697 | 21.2000007629395 | 21.2000007629395 | 21.2000007629395 | 21.2999992370605 | 21.5 | 21.3999996185303 | 21.3999996185303 | 21.2999992370605 | 21.3999996185303 | 20.8999996185303 | 21.2000007629395 | 21.1000003814697 | 20.7999992370605
Belize | BLZ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.1000003814697 | 19.2999992370605 | 17.6000003814697 | 20.7999992370605 | 23.6000003814697 | 25.2000007629395 | 23.7000007629395 | 25 | 22 | 19.5 | 16.2000007629395 | 17.7999992370605 | 18.3999996185303 | 18.8999996185303 | 19.2000007629395 | 17.1000003814697 | 15.5 | 15 | 15.6999998092651 | 15.1999998092651 | 15.3999996185303 | 14.6999998092651
Bermuda | BMU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Bolivia | BOL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.09999990463257 | 8.89999961853027 | 7.80000019073486 | 8.69999980926514 | 8.69999980926514 | 8.5 | 8.30000019073486 | 8 | 7.19999980926514 | 8 | 8.80000019073486 | 9.30000019073486 | 8.5 | 7.19999980926514 | 9 | 8.89999961853027 | 8.69999980926514 | 4.90000009536743 | 5.69999980926514 | 5.59999990463257 | 5.5 | 5.40000009536743
Brazil | BRA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.6000003814697 | 11.8999996185303 | 11.3999996185303 | 11.3999996185303 | 11.3999996185303 | 12.6000003814697 | 14.3999996185303 | 17.2000007629395 | 18.2000007629395 | 18 | 17.7999992370605 | 18 | 19 | 18 | 19.2999992370605 | 17.7000007629395 | 16.7000007629395 | 15.3999996185303 | 17.7000007629395 | 17.2000007629395 | 15.1999998092651 | 15.5
Barbados | BRB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.9000015258789 | 41.5999984741211 | 43.5999984741211 | 42.2000007629395 | 38.0999984741211 | 28.2999992370605 | 30.2000007629395 | 24.6000003814697 | 22.2000007629395 | 19.7999992370605 | 23 | 23.5 | 26 | 22.2000007629395 | 20.6000003814697 | 19.7999992370605 | 16.8999996185303 | 18.5 | 22.7999992370605 | 24.7000007629395 | 25.7000007629395 | 26.3999996185303
[NAME] | BRN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6000003814697 | 11.1999998092651 | 10 | 12.6000003814697 | 12 | 11.3999996185303 | 9.80000019073486 | 9.89999961853027 | 12.1999998092651 | 11.3999996185303 | 10.8999996185303 | 11.1999998092651 | 11.6000003814697 | 10 | 10 | 10 | 10 | 9.80000019073486 | 10.6000003814697 | 11.1999998092651 | 11.3000001907349 | 11.3999996185303
Bhutan | BTN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.5 | 5.80000019073486 | 6.09999990463257 | 7.69999980926514 | 4.19999980926514 | 4.40000009536743 | 3.79999995231628 | 3.79999995231628 | 4.5 | 5.09999990463257 | 4.90000009536743 | 4.80000019073486 | 6.59999990463257 | 6.40000009536743 | 8.39999961853027 | 10.6000003814697 | 11.3999996185303 | 13.1000003814697 | 8.39999961853027 | 8.39999961853027 | 6.40000009536743
Botswana | BWA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41.9000015258789 | 35.0999984741211 | 37.2000007629395 | 40.2000007629395 | 39.4000015258789 | 35.5999984741211 | 30.1000003814697 | 14.3999996185303 | 41.0999984741211 | 41.0999984741211 | 38.7000007629395 | 35.7000007629395 | 40.0999984741211 | 38.7000007629395 | 37.2999992370605 | 29.7999992370605 | 22 | 37 | 20.2999992370605 | 33 | 33.0999984741211 | 31.7000007629395
Sub-Saharan Africa (IFC classification) | CAA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Central African Republic | CAF | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13 | 13 | 13 | 12.8000001907349 | 12.8000001907349 | 13.1999998092651 | 12.6999998092651 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 13.1000003814697 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349
Canada | CAN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8000001907349 | 17.2000007629395 | 17.2000007629395 | 15.8999996185303 | 14.8000001907349 | 15.3999996185303 | 16.2000007629395 | 15.1000003814697 | 14.1000003814697 | 12.6999998092651 | 12.8999996185303 | 13.6999998092651 | 13.6999998092651 | 13.3999996185303 | 12.3999996185303 | 11.6999998092651 | 11.1999998092651 | 11.6000003814697 | 15.1999998092651 | 14.8000001907349 | 14.1999998092651 | 14.3000001907349
East Asia and the Pacific (IFC classification) | CEA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Central Europe and the Baltics | CEB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.89158038293423 | 22.17205435509749 | 25.28644650561007 | 26.05636585712368 | 24.11302319903046 | 22.49777024939897 | 20.64997454936184 | 20.37336045095732 | 24.22792596072863 | 26.91267973389468 | 29.79224738689453 | 31.00911901768289 | 29.79968044640684 | 29.55697759960732 | 27.48635582576503 | 23.68489875303788 | 18.64030529257862 | 16.64094726924781 | 21.52601132828463 | 24.56278096183267 | 25.51064306254777 | 26.2845631254111
Europe and Central Asia (IFC classification) | CEU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Switzerland | CHE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.20000004768372 | 4.69999980926514 | 7 | 5.69999980926514 | 5.5 | 4.59999990463257 | 5.90000009536743 | 5.59999990463257 | 5.59999990463257 | 5 | 5.5 | 5.59999990463257 | 8.5 | 7.69999980926514 | 8.80000019073486 | 7.69999980926514 | 7.09999990463257 | 7 | 8.39999961853027 | 7.80000019073486 | 7.69999980926514 | 8.39999961853027
Channel Islands | CHI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Chile | CHL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.8999996185303 | 19.2000007629395 | 18.5 | 18 | 16.5 | 15.1999998092651 | 14.8000001907349 | 15.3000001907349 | 21.8999996185303 | 21.3999996185303 | 21.1000003814697 | 21.7000007629395 | 21.2000007629395 | 21 | 19.7999992370605 | 18.2999992370605 | 17.7999992370605 | 19.7000007629395 | 22.7000007629395 | 18.7000007629395 | 17.6000003814697 | 16.2999992370605
China | CHN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 8.19999980926514 | 8.19999980926514 | 8.39999961853027 | 8.89999961853027 | 9.10000038146973 | 9.19999980926514 | 9.60000038146973 | 9.60000038146973 | 9.39999961853027 | 9.39999961853027 | 9.19999980926514 | 8.89999961853027 | 9 | 8.69999980926514 | 8.30000019073486 | 8 | 9.19999980926514 | 9.30000019073486 | 9 | 9.30000019073486 | 9.69999980926514
Cote d'Ivoire | CIV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 9.80000019073486 | 8.80000019073486 | 7.80000019073486 | 6 | 6 | 6 | 6 | 6 | 6.09999990463257 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6.09999990463257 | 6
Latin America and the Caribbean (IFC classification) | CLA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Middle East and North Africa (IFC classification) | CME | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Cameroon | CMR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1000003814697 | 10.1000003814697 | 10.1000003814697 | 10.1000003814697 | 6.30000019073486 | 14.8999996185303 | 14.1999998092651 | 13.5 | 12.8000001907349 | 11 | 13.6999998092651 | 10 | 10.1000003814697 | 8.10000038146973 | 8 | 6.90000009536743 | 7.40000009536743 | 8.30000019073486 | 8.60000038146973 | 7 | 6.90000009536743 | 6.90000009536743
Congo, Rep. | COG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.8999996185303 | 13 | 13.1000003814697 | 12.8999996185303 | 12.8999996185303 | 13 | 12.8999996185303 | 13.1000003814697 | 12.8000001907349 | 12.8999996185303 | 12.8000001907349 | 13 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 13 | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.8999996185303 | 12.8999996185303
Colombia | COL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23 | 19 | 20.2000007629395 | 21.1000003814697 | 21.5 | 23.6000003814697 | 23.2999992370605 | 25.2000007629395 | 27.2000007629395 | 29.2999992370605 | 24.7000007629395 | 25.1000003814697 | 21.1000003814697 | 22.5 | 23 | 20.7999992370605 | 24.1000003814697 | 27.1000003814697 | 23 | 22.2999992370605 | 20.8999996185303 | 19.5
Comoros | COM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 12.6000003814697 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651
Cabo Verde | CPV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6000003814697 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.6000003814697 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349
Costa Rica | CRI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6000003814697 | 8 | 8.60000038146973 | 8.60000038146973 | 11.6999998092651 | 12.3000001907349 | 12 | 12.1999998092651 | 13.1000003814697 | 11.3000001907349 | 14 | 14.3000001907349 | 15.1999998092651 | 14.5 | 15.1000003814697 | 14.3999996185303 | 11.1000003814697 | 11.1999998092651 | 18 | 17 | 17 | 16.7999992370605
South Asia (IFC classification) | CSA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Caribbean small states | CSS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.54046359668014 | 30.49641632564813 | 31.6970429760841 | 31.2407921382163 | 34.92284465854591 | 33.89926844339626 | 32.43080283464514 | 32.29871702319232 | 32.17892445025846 | 29.34616337358774 | 30.61602060729201 | 29.61381781975484 | 25.42319979353851 | 26.90685778489889 | 25.62615670109627 | 23.01692572086084 | 21.49989678925128 | 22.92027834744223 | 24.57943253884629 | 27.07653269538499 | 27.4879569112492 | 29.10508991752409
Cuba | CUB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.69999980926514 | 7.40000009536743 | 7.90000009536743 | 6.69999980926514 | 16.3999996185303 | 15.3000001907349 | 14.5 | 12.8000001907349 | 13.1999998092651 | 11.3999996185303 | 8.69999980926514 | 7 | 4.90000009536743 | 4.40000009536743 | 4 | 3.59999990463257 | 3.90000009536743 | 3.5 | 3.5 | 5.19999980926514 | 5.09999990463257 | 5.30000019073486
[NAME] | CUW | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Cayman Islands | CYM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Cyprus | CYP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.2000007629395 | 4.69999980926514 | 20.5 | 7.80000019073486 | 8.10000038146973 | 8.30000019073486 | 7.30000019073486 | 9.5 | 12.8999996185303 | 9.5 | 7.59999990463257 | 7.30000019073486 | 8.30000019073486 | 8.30000019073486 | 13 | 9.39999961853027 | 9.69999980926514 | 8.39999961853027 | 13.1000003814697 | 15.8000001907349 | 21.2999992370605 | 26.7999992370605
Czech Republic | CZE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 6.59999990463257 | 8.39999961853027 | 8.69999980926514 | 7.80000019073486 | 7.19999980926514 | 8.60000038146973 | 12.5 | 17 | 16.8999996185303 | 16.5 | 15.8999996185303 | 17.5 | 20.3999996185303 | 19.2999992370605 | 17.5 | 10.8000001907349 | 9.89999961853027 | 16.7000007629395 | 18.2999992370605 | 18 | 19.3999996185303
Germany | DEU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6.19999980926514 | 7.59999990463257 | 8.19999980926514 | 8.19999980926514 | 9.39999961853027 | 10.1999998092651 | 9 | 8.69999980926514 | 8.39999961853027 | 8.30000019073486 | 9.80000019073486 | 10.6000003814697 | 12.6000003814697 | 15.1999998092651 | 13.5 | 11.6999998092651 | 10.3999996185303 | 11 | 9.69999980926514 | 8.5 | 8.10000038146973
Djibouti | DJI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Dominica | DMA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Denmark | DNK | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 12.3000001907349 | 14.5 | 10.1999998092651 | 9.89999961853027 | 10.6000003814697 | 8.19999980926514 | 7.19999980926514 | 9.89999961853027 | 6.69999980926514 | 8.19999980926514 | 7.40000009536743 | 9.19999980926514 | 8.19999980926514 | 8.60000038146973 | 7.69999980926514 | 7.5 | 8 | 11.8000001907349 | 13.8999996185303 | 14.1999998092651 | 14.1000003814697
Dominican Republic | DOM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.9000015258789 | 38.2999992370605 | 38.4000015258789 | 29.8999996185303 | 28.6000003814697 | 29.8999996185303 | 28.7999992370605 | 27.2000007629395 | 26 | 23.2000007629395 | 23 | 20.7000007629395 | 31 | 34.0999984741211 | 33.4000015258789 | 30.3999996185303 | 30.2999992370605 | 27.8999996185303 | 29.7000007629395 | 25.2999992370605 | 26.1000003814697 | 26
Algeria | DZA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 38.7000007629395 | 42.9000015258789 | 43 | 45 | 49.2000007629395 | 48.7999992370605 | 46.5999984741211 | 47.5 | 45.9000015258789 | 52.5 | 47 | 45.5 | 42.5 | 40.7999992370605 | 30.6000003814697 | 23.8999996185303 | 27.5 | 23.8999996185303 | 21.7000007629395 | 22.2000007629395 | 22.2000007629395 | 21.6000003814697
East Asia & Pacific (developing only) | EAP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.02536320906043 | 8.279734602351855 | 9.035057643966985 | 9.331868787814695 | 9.224233960029816 | 9.516621398226716 | 9.780548091671038 | 10.83892073389266 | 10.94605092632349 | 10.94348824220168 | 11.53735305716919 | 11.83998969341418 | 11.47347493918053 | 11.76953351351504 | 11.65635484155066 | 11.20032950245215 | 10.321029961682 | 10.9356525055348 | 10.95074804988229 | 10.61207284056216 | 10.59268590814567 | 10.97828230072028
East Asia & Pacific (all income levels) | EAS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.726641385333412 | 8.143519509109268 | 8.892025868006046 | 9.126033640286602 | 9.02427069381456 | 9.322929789602759 | 9.594733196835378 | 10.83642791137274 | 10.97416118626574 | 10.87524616751512 | 11.44430693052606 | 11.71990892796801 | 11.41534392167095 | 11.6538958512835 | 11.50796417075877 | 11.04843652701865 | 10.19112941830926 | 10.75526918581889 | 10.8936946740339 | 10.57091028981394 | 10.50083350565898 | 10.8412170687387
Europe & Central Asia (developing only) | ECA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.13165308713155 | 19.40843000121232 | 21.06225017424577 | 19.31941361997094 | 18.38611216487451 | 18.57524772422941 | 19.03683260857056 | 19.76760049816723 | 20.0991352062471 | 19.45367239560809 | 20.13353009245957 | 21.1467865628352 | 20.93804052846117 | 20.86616273109943 | 20.3197063187992 | 19.9165101270307 | 19.67403485290527 | 19.36479048056178 | 21.83777487341457 | 21.11365622244739 | 20.41487681860995 | 19.9279182258562
Europe & Central Asia (all income levels) | ECS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.97523046344985 | 18.01838977267418 | 20.3915911650767 | 20.80425975168617 | 20.5531604950764 | 20.71769018382533 | 21.24668233059223 | 21.44544216698806 | 21.10496033259623 | 19.74993285732898 | 19.12622414469698 | 19.32599336617077 | 19.72249926930192 | 19.65777349473091 | 19.13039718565632 | 18.43117157953186 | 17.03283764376389 | 16.8469273490048 | 20.62756971406646 | 20.68660174708816 | 20.4680897192765 | 21.32153167806838
Ecuador | ECU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6000003814697 | 13.1999998092651 | 11 | 15.3000001907349 | 11.1999998092651 | 12.1999998092651 | 14.1999998092651 | 10.3999996185303 | 12.6000003814697 | 15.1999998092651 | 17.2999992370605 | 17.6000003814697 | 19.7000007629395 | 14.3000001907349 | 14.1999998092651 | 13.3999996185303 | 10.8999996185303 | 13.1999998092651 | 14.3999996185303 | 11.1000003814697 | 9.39999961853027 | 10.1000003814697
Egypt, Arab Rep. | EGY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.7000007629395 | 26.3999996185303 | 32.0999984741211 | 32.4000015258789 | 32.5999984741211 | 26.2000007629395 | 24.7000007629395 | 24.1000003814697 | 20.8999996185303 | 25.5 | 29 | 28 | 29.1000003814697 | 30.3999996185303 | 33.7000007629395 | 31.3999996185303 | 26.1000003814697 | 25.7999992370605 | 27 | 26.2999992370605 | 35.5 | 35.7000007629395
Euro area | EMU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.04470396999377 | 19.08529606671712 | 22.8324223584756 | 24.46024814640031 | 23.99101775112913 | 24.49058622899126 | 24.28144099618878 | 22.46027344297885 | 21.46236874268224 | 19.05629597915697 | 17.07718794640397 | 17.79674156899648 | 17.88824956154931 | 18.49986574699751 | 18.68080452379011 | 17.52970117658994 | 16.01648230518778 | 16.55076654578057 | 21.20732269480022 | 22.28204588950812 | 22.9350202341577 | 25.89549184776859
Eritrea | ERI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.8999996185303 | 12.6000003814697 | 12.3999996185303 | 12.8999996185303 | 12.6999998092651 | 12.6999998092651 | 12.8999996185303 | 13 | 13.3000001907349 | 12.6999998092651 | 12.8999996185303 | 13 | 12.8999996185303 | 12.8999996185303 | 13 | 12.8999996185303 | 13.3000001907349 | 12.8999996185303 | 12.8999996185303 | 12.6999998092651 | 12.6999998092651
Spain | ESP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.7999992370605 | 33.2999992370605 | 42.2000007629395 | 44.0999984741211 | 41.7000007629395 | 41.5 | 38.7000007629395 | 35.2999992370605 | 29.3999996185303 | 26.2999992370605 | 21.2999992370605 | 22.8999996185303 | 23.3999996185303 | 22.7000007629395 | 20.2999992370605 | 18.5 | 18.7999992370605 | 25.5 | 38.5 | 42.4000015258789 | 47.2999992370605 | 54.2999992370605
Estonia | EST | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.70000004768372 | 6.80000019073486 | 12.1000003814697 | 13.8999996185303 | 13.8999996185303 | 16 | 18.5 | 14.8999996185303 | 22 | 23.5 | 24.5 | 17.2999992370605 | 24.1000003814697 | 23.6000003814697 | 15.8000001907349 | 11.8999996185303 | 10.1000003814697 | 12 | 27.7999992370605 | 33.2999992370605 | 22.6000003814697 | 21.1000003814697
Ethiopia | ETH | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.3000001907349 | 10.3000001907349 | 9.60000038146973 | 9.89999961853027 | 11.5 | 11.6000003814697 | 11.6000003814697 | 11.6000003814697 | 11.6000003814697 | 11.1999998092651 | 10.8000001907349 | 9.89999961853027 | 9.10000038146973 | 8.30000019073486 | 7.59999990463257 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514
European Union | EUU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.26745579841024 | 19.35339078200813 | 22.78696283547323 | 23.81766059544535 | 22.95905903038943 | 22.90638971050703 | 22.06829205372941 | 20.58303292404183 | 20.82069500689725 | 19.86038623119981 | 19.17919260920804 | 20.00316604439916 | 19.86267432387365 | 20.1039874813574 | 19.99041083848256 | 18.54460939816361 | 16.46389464257707 | 16.32112852506726 | 20.8498895841069 | 22.19644177102274 | 22.91460621671127 | 25.09132341473644
Fragile and conflict affected situations | FCS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.14871260730929 | 17.1716415778983 | 16.48913085062955 | 16.6928012408057 | 16.53034924824473 | 16.93339512925238 | 17.15267535281649 | 16.97818008738221 | 16.17790418485963 | 16.71024776581958 | 17.03912866692575 | 17.24839912210596 | 17.87824004745582 | 17.71279187454141 | 16.69607014518305 | 16.78927638097411 | 16.68222061448499 | 16.73145743813079 | 16.34757212953168 | 17.03320543448337 | 16.90186540945503 | 16.9547116741226
Finland | FIN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15 | 24.5 | 30.7999992370605 | 31.1000003814697 | 27 | 25 | 23.2999992370605 | 22.1000003814697 | 20.2999992370605 | 20.2999992370605 | 18.7000007629395 | 19.3999996185303 | 20.3999996185303 | 19.3999996185303 | 18.8999996185303 | 17.6000003814697 | 15.8000001907349 | 15.6999998092651 | 20.5 | 20.2999992370605 | 18.8999996185303 | 17.7000007629395
Fiji | FJI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6000003814697 | 11.6000003814697 | 12.8000001907349 | 12.3999996185303 | 11.8000001907349 | 12.8999996185303 | 14.5 | 18.2000007629395 | 17.3999996185303 | 16.7000007629395 | 13.5 | 12.8999996185303 | 19.2000007629395 | 10.6999998092651 | 10.6000003814697 | 15.1000003814697 | 19.7999992370605 | 21.1000003814697 | 20.5 | 20.2999992370605 | 20 | 19.8999996185303
France | FRA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.2999992370605 | 21.2000007629395 | 25 | 28.2999992370605 | 26.6000003814697 | 27.1000003814697 | 28.5 | 25.8999996185303 | 26.2000007629395 | 20.5 | 18 | 19 | 17.5 | 20 | 20.3999996185303 | 21.3999996185303 | 18.8999996185303 | 18.3999996185303 | 23 | 22.7000007629395 | 21.8999996185303 | 23.7000007629395
Faeroe Islands | FRO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Micronesia, Fed. [NAME]. | FSM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Gabon | GAB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 37.5 | 39.5999984741211 | 41.7999992370605 | 40.7000007629395 | 39.7000007629395 | 38.9000015258789 | 38.2000007629395 | 38.2999992370605 | 38.4000015258789 | 38.5 | 38.5999984741211 | 38.7000007629395 | 38.9000015258789 | 39 | 39.0999984741211 | 39.2000007629395 | 39.2999992370605 | 38.2999992370605 | 37.2999992370605 | 34.5 | 34.5 | 36.7999992370605
United Kingdom | GBR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.8999996185303 | 15.8999996185303 | 17.7999992370605 | 16.6000003814697 | 15.6999998092651 | 15.1999998092651 | 13.8999996185303 | 12.6000003814697 | 12.5 | 12 | 10.6000003814697 | 11.1999998092651 | 11.6999998092651 | 11.1000003814697 | 12.3999996185303 | 14.1000003814697 | 14.5 | 14.5 | 19.1000003814697 | 19.5 | 20.2000007629395 | 21.2999992370605
Georgia | GEO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.8999996185303 | 25.3999996185303 | 26 | 26.5 | 29.7999992370605 | 27 | 26.7999992370605 | 27.1000003814697 | 24.2000007629395 | 20.8999996185303 | 20 | 27.5 | 24.3999996185303 | 27.7999992370605 | 27.8999996185303 | 29.2999992370605 | 31 | 35.7999992370605 | 38.9000015258789 | 36.7999992370605 | 36.5999984741211 | 35.5
Ghana | GHA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.3000001907349 | 15.1000003814697 | 15.3999996185303 | 10.1000003814697 | 6.30000019073486 | 15.3000001907349 | 15.1000003814697 | 15.1000003814697 | 16.2000007629395 | 16.2999992370605 | 15.8999996185303 | 15.8000001907349 | 16 | 16.1000003814697 | 8 | 6.40000009536743 | 6.40000009536743 | 6.30000019073486 | 6.5 | 6.40000009536743 | 6.09999990463257 | 6.40000009536743
Guinea | GIN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514
Gambia, The | GMB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8999996185303 | 13.1000003814697 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 13.1000003814697 | 12.8000001907349 | 12.8000001907349 | 13 | 13 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 13.1000003814697 | 12.8999996185303
Guinea-Bissau | GNB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 13.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.8999996185303 | 13 | 13 | 12.8999996185303 | 12.8000001907349 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 13
Equatorial Guinea | GNQ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.1999998092651 | 12.6000003814697 | 12.5 | 12.5 | 11.6999998092651 | 10.8999996185303 | 12.3999996185303 | 12.3000001907349 | 12.5 | 11.6999998092651 | 12.5 | 12.6000003814697 | 12.1000003814697 | 12.6999998092651 | 12.8999996185303 | 12.5 | 12.6000003814697 | 13 | 13 | 12.8000001907349 | 12.8999996185303
Greece | GRC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.5 | 23.7999992370605 | 27.7000007629395 | 26.3999996185303 | 26.3999996185303 | 29.2999992370605 | 29.2999992370605 | 28.7000007629395 | 30.6000003814697 | 28.5 | 27.2999992370605 | 26.2999992370605 | 26.2000007629395 | 26.2999992370605 | 25.3999996185303 | 24.7000007629395 | 22.5 | 21.7999992370605 | 25.5 | 32.5 | 43.9000015258789 | 54.7999992370605
Grenada | GRD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Greenland | GRL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Guatemala | GTM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 6.59999990463257 | 4.19999980926514 | 4 | 7.19999980926514 | 5.59999990463257 | 7.80000019073486 | 6.80000019073486 | 3.29999995231628 | 2.40000009536743 | 2.29999995231628 | 5.40000009536743 | 4.90000009536743 | 5.40000009536743 | 5.19999980926514 | 4.90000009536743 | 4.40000009536743 | 4.90000009536743 | 5.40000009536743 | 6.19999980926514 | 7.19999980926514 | 7.30000019073486
Guam | GUM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Guyana | GUY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41.5999984741211 | 27.2999992370605 | 34.0999984741211 | 41.5 | 49.5 | 45.4000015258789 | 41.2000007629395 | 44.2999992370605 | 42 | 33.7000007629395 | 45.2999992370605 | 50.2000007629395 | 44 | 45.2000007629395 | 45.9000015258789 | 44.0999984741211 | 36.0999984741211 | 36.2000007629395 | 35.2999992370605 | 38.0999984741211 | 41.0999984741211 | 42
High income | HIC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.49775702734352 | 14.96970482504667 | 16.28016396711616 | 16.65217378276639 | 16.54411009636017 | 16.7236346064589 | 16.97124082456536 | 17.32143909966947 | 16.85057494895668 | 15.60525859114509 | 15.31568823476737 | 15.67640574160621 | 16.26894125912714 | 15.95513225462635 | 15.393152686065 | 14.82380471080526 | 13.56393269516328 | 14.08108519976776 | 17.92637975820895 | 18.28728911247491 | 17.60472643453478 | 18.14774851457599
Hong Kong SAR, China | HKG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 4.40000009536743 | 4.5 | 4.40000009536743 | 6.80000019073486 | 6.59999990463257 | 5.09999990463257 | 10.6999998092651 | 14.3000001907349 | 11.1000003814697 | 11.5 | 15 | 14.8999996185303 | 12 | 10.6999998092651 | 10.3999996185303 | 9 | 8.69999980926514 | 12.5 | 12.1000003814697 | 9.5 | 9.10000038146973
Honduras | HND | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.59999990463257 | 5.19999980926514 | 5.19999980926514 | 5.30000019073486 | 5.19999980926514 | 7.09999990463257 | 5.40000009536743 | 6.5 | 7.40000009536743 | 7.09999990463257 | 6.69999980926514 | 5.90000009536743 | 7.90000009536743 | 10.1999998092651 | 7.19999980926514 | 5.19999980926514 | 4.90000009536743 | 5.19999980926514 | 5.59999990463257 | 8.10000038146973 | 8.10000038146973 | 8.19999980926514
Heavily indebted poor countries (HIPC) | HPC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.79049603476813 | 11.87117940831052 | 11.79371885134858 | 11.60906505857086 | 11.44446221919813 | 12.04793985926805 | 11.92119773001249 | 11.80569723645656 | 11.62083706190151 | 11.61931897310133 | 11.77287926407063 | 11.40208377360052 | 11.40829047717545 | 10.98857645004525 | 10.38059651322399 | 10.58602586339432 | 10.27530228337353 | 10.4252663749463 | 10.63666656384401 | 10.72417322992668 | 10.74958681736538 | 10.70913906875091
Croatia | HRV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.2999992370605 | 25.8999996185303 | 25.1000003814697 | 24.3999996185303 | 25.2000007629395 | 25.3999996185303 | 25.1000003814697 | 30.3999996185303 | 34.4000015258789 | 38.7000007629395 | 45.5 | 36.2999992370605 | 35.7999992370605 | 32.7999992370605 | 32.4000015258789 | 29 | 24.2000007629395 | 22.2000007629395 | 25.6000003814697 | 33.5 | 36.9000015258789 | 44.2000007629395
Haiti | HTI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.5 | 26.2999992370605 | 26.8999996185303 | 28.5 | 23.7000007629395 | 24.8999996185303 | 25.2000007629395 | 25.2999992370605 | 17.2999992370605 | 17.7000007629395 | 18.2000007629395 | 18 | 17.8999996185303 | 18.7999992370605 | 17.6000003814697 | 17.5 | 17.2000007629395 | 17.7999992370605 | 17.2999992370605 | 19.2000007629395 | 16.7000007629395 | 17.3999996185303
Hungary | HUN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21 | 18.7999992370605 | 22.8999996185303 | 20.8999996185303 | 18.6000003814697 | 17.8999996185303 | 16 | 14 | 12.8999996185303 | 12.6000003814697 | 11.1999998092651 | 12.5 | 13.3000001907349 | 15.3999996185303 | 19.3999996185303 | 19.1000003814697 | 18 | 19.7999992370605 | 26.3999996185303 | 26.5 | 26 | 28.1000003814697
Indonesia | IDN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.7000007629395 | 8.30000019073486 | 13.8000001907349 | 15.8999996185303 | 12.6999998092651 | 14.3999996185303 | 14.6999998092651 | 17.7000007629395 | 17.7999992370605 | 18.1000003814697 | 22.5 | 26.2999992370605 | 26.3999996185303 | 28.6000003814697 | 32.7000007629395 | 30.8999996185303 | 25.6000003814697 | 23.5 | 22.5 | 22.6000003814697 | 21.2000007629395 | 21.6000003814697
Isle of Man | IMN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
India | IND | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 9 | 9.60000038146973 | 8.19999980926514 | 8.89999961853027 | 8.89999961853027 | 10.1000003814697 | 8.5 | 8.80000019073486 | 10 | 9 | 9.89999961853027 | 9.5 | 9 | 9.89999961853027 | 10 | 9.19999980926514 | 10.1000003814697 | 9.69999980926514 | 10.1999998092651 | 10.1999998092651 | 9.69999980926514
Not classified | INX | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Ireland | IRL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.2000007629395 | 22.7999992370605 | 25.1000003814697 | 23.1000003814697 | 18.8999996185303 | 18.1000003814697 | 15.8999996185303 | 11.3999996185303 | 8.60000038146973 | 6.5 | 6.19999980926514 | 7.80000019073486 | 8.10000038146973 | 8.30000019073486 | 8.60000038146973 | 8.60000038146973 | 9.10000038146973 | 12.8000001907349 | 24.5 | 27.7999992370605 | 29.1000003814697 | 30.2999992370605
Iran, Islamic Rep. | IRN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2999992370605 | 23.5 | 23.1000003814697 | 22.7999992370605 | 22.3999996185303 | 22.3999996185303 | 22.6000003814697 | 22.6000003814697 | 22.3999996185303 | 25.7000007629395 | 23.5 | 25.2999992370605 | 24.1000003814697 | 20.3999996185303 | 23.8999996185303 | 23.3999996185303 | 22 | 22.8999996185303 | 24.3999996185303 | 28.3999996185303 | 28.3999996185303 | 28.8999996185303
Iraq | IRQ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 37.7000007629395 | 37.0999984741211 | 32.2999992370605 | 34.0999984741211 | 35.9000015258789 | 37.7000007629395 | 37.7000007629395 | 37.7000007629395 | 35.9000015258789 | 36.5 | 37.2000007629395 | 37.2000007629395 | 51.9000015258789 | 51.7999992370605 | 37.2999992370605 | 36.5 | 35.2999992370605 | 32.2000007629395 | 32.2000007629395 | 32.2000007629395 | 32.2999992370605 | 32.0999984741211
Iceland | ISL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.90000009536743 | 9.80000019073486 | 9.89999961853027 | 11.5 | 10.8999996185303 | 8.39999961853027 | 7.69999980926514 | 6 | 4.40000009536743 | 4.69999980926514 | 4.80000019073486 | 7.19999980926514 | 8.10000038146973 | 7.90000009536743 | 7 | 8.10000038146973 | 6.90000009536743 | 8 | 15.6999998092651 | 16 | 14.5 | 13.5
Israel | ISR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.3999996185303 | 23.1000003814697 | 20.7999992370605 | 16.7000007629395 | 14.8999996185303 | 13.5 | 14.8999996185303 | 17 | 16.7000007629395 | 16.8999996185303 | 18.3999996185303 | 20.7999992370605 | 22.1000003814697 | 20.3999996185303 | 17.7999992370605 | 18.2999992370605 | 16.1000003814697 | 12.6999998092651 | 14.6000003814697 | 13.6999998092651 | 11.6000003814697 | 12.1999998092651
Italy | ITA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.2999992370605 | 27.7999992370605 | 29.7999992370605 | 31.3999996185303 | 33.0999984741211 | 34.5 | 34.2999992370605 | 33.5999984741211 | 32.7999992370605 | 31.3999996185303 | 27.7000007629395 | 27.1000003814697 | 26.8999996185303 | 24.5 | 24 | 21.6000003814697 | 20.2999992370605 | 21.2000007629395 | 25.3999996185303 | 27.7999992370605 | 29.1000003814697 | 35.2999992370605
Jamaica | JAM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.3999996185303 | 28.1000003814697 | 30.5 | 28.3999996185303 | 35.5999984741211 | 36.0999984741211 | 35.2000007629395 | 35.5 | 36.4000015258789 | 34.0999984741211 | 35.5999984741211 | 31.5 | 22.5 | 28.6000003814697 | 25.7000007629395 | 22.7000007629395 | 22.2000007629395 | 25.5 | 26.5 | 30 | 29.5 | 32.9000015258789
Jordan | JOR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.6000003814697 | 36.2000007629395 | 40.7999992370605 | 38.4000015258789 | 30.7999992370605 | 29.1000003814697 | 27.8999996185303 | 26.7999992370605 | 28.1000003814697 | 27.8999996185303 | 33.5999984741211 | 34.7000007629395 | 34.2999992370605 | 27.2999992370605 | 32.5 | 30.1000003814697 | 29.3999996185303 | 28.8999996185303 | 28.6000003814697 | 30.1000003814697 | 31.6000003814697 | 31.2999992370605
Japan | JPN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.5 | 4.40000009536743 | 5.09999990463257 | 5.5 | 6.09999990463257 | 6.69999980926514 | 6.59999990463257 | 7.69999980926514 | 9.30000019073486 | 9.19999980926514 | 9.69999980926514 | 10.1000003814697 | 10.1999998092651 | 9.5 | 8.69999980926514 | 8 | 7.69999980926514 | 7.19999980926514 | 9.10000038146973 | 9.19999980926514 | 8 | 7.90000009536743
Kazakhstan | KAZ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.6000003814697 | 13.6999998092651 | 13.3999996185303 | 8.89999961853027 | 13.1000003814697 | 15.3999996185303 | 15.3999996185303 | 15.5 | 16 | 15.1000003814697 | 12.3000001907349 | 16.6000003814697 | 14.3999996185303 | 14.1000003814697 | 9.60000038146973 | 9.19999980926514 | 8.69999980926514 | 7.40000009536743 | 6.80000019073486 | 6 | 5.30000019073486 | 4.19999980926514
Kenya | [NAME] | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 17.2999992370605 | 17.2999992370605 | 17.2000007629395 | 17.1000003814697 | 17.1000003814697 | 17.2000007629395 | 17.1000003814697 | 17.1000003814697 | 17.2000007629395 | 17.1000003814697 | 17.2000007629395 | 17.1000003814697 | 17 | 17 | 17 | 17 | 17.1000003814697 | 17.1000003814697 | 17 | 17 | 17
Kyrgyz Republic | KGZ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8000001907349 | 14.8999996185303 | 14.8000001907349 | 13.8999996185303 | 15.1000003814697 | 15.8000001907349 | 15.5 | 17.2999992370605 | 15 | 13.6000003814697 | 14.1000003814697 | 20 | 16.6000003814697 | 15.1999998092651 | 14.3999996185303 | 14.6000003814697 | 14.8999996185303 | 15.3999996185303 | 16.7999992370605 | 16.6000003814697 | 16 | 15.3999996185303
Cambodia | KHM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 4.40000009536743 | 4.59999990463257 | 3.5 | 3.79999995231628 | 4.19999980926514 | 4.59999990463257 | 5 | 5.40000009536743 | 5.80000019073486 | 3.79999995231628 | 4 | 3.90000009536743 | 3.79999995231628 | 3.59999990463257 | 3.70000004768372 | 3.70000004768372 | 3.90000009536743 | 4.30000019073486 | 3.79999995231628 | 3.79999995231628 | 3.79999995231628
Kiribati | KIR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
St. Kitts and Nevis | KNA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Korea, Rep. | KOR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.40000009536743 | 8.80000019073486 | 7.09999990463257 | 6.09999990463257 | 6 | 7.40000009536743 | 15.8999996185303 | 14.1000003814697 | 10.8999996185303 | 10.3000001907349 | 8.60000038146973 | 10.1000003814697 | 10.3999996185303 | 10.1999998092651 | 9.89999961853027 | 8.89999961853027 | 9.30000019073486 | 9.89999961853027 | 9.80000019073486 | 9.69999980926514 | 8.89999961853027
Kosovo | KSV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Kuwait | KWT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.69999980926514 | 4.5 | 4.09999990463257 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4.59999990463257 | 4.69999980926514 | 6.5 | 7.80000019073486 | 10.3999996185303 | 12.1000003814697 | 9.5 | 9.69999980926514 | 9.5 | 9.69999980926514 | 9.69999980926514 | 9.5 | 9.19999980926514
Latin America & Caribbean (developing only) | LAC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.18480830107856 | 11.53727223699427 | 11.98398201333559 | 12.33275849847204 | 14.35426740506779 | 14.70187752103763 | 14.27501460927708 | 14.99864140816262 | 15.11903740266876 | 15.63751312904044 | 15.32565242138873 | 16.29677182052353 | 16.78805484443498 | 15.99885748440088 | 15.64292087427434 | 14.4944366039396 | 13.83367093571922 | 13.54048323033735 | 15.03744139696907 | 14.59059665098327 | 13.75436623948483 | 13.55708078624745
Lao PDR | LAO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5 | 5.40000009536743 | 5.59999990463257 | 5.69999980926514 | 5.80000019073486 | 4.40000009536743 | 4.59999990463257 | 4.5 | 4.40000009536743 | 4.40000009536743 | 4.30000019073486 | 4.30000019073486 | 4.90000009536743 | 5.69999980926514 | 3.29999995231628 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372
Lebanon | LBN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.7000007629395 | 21 | 20.7999992370605 | 22 | 20.7999992370605 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.2000007629395 | 21.1000003814697 | 21.1000003814697 | 21.2999992370605 | 20.7999992370605 | 21 | 21.2999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7999992370605 | 22.7000007629395 | 22.7999992370605
Liberia | LBR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 4.69999980926514 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486 | 4.69999980926514 | 4.69999980926514 | 5.19999980926514 | 4.69999980926514 | 4.90000009536743 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.80000019073486 | 5 | 5 | 4.40000009536743
Libya | LBY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2000007629395 | 21 | 21.1000003814697 | 21.2999992370605 | 21.2000007629395 | 21.5 | 21.5 | 21.6000003814697 | 21.7000007629395 | 21.8999996185303 | 21.7999992370605 | 21.8999996185303 | 22.2000007629395 | 22 | 22.2000007629395 | 22.1000003814697 | 22.1000003814697 | 22 | 22 | 22.1000003814697 | 21 | 23.8999996185303
St. Lucia | LCA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Latin America & Caribbean (all income levels) | LCN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.58730558890343 | 12.03456120461572 | 12.40944357429829 | 12.70039977880069 | 14.58515288337365 | 14.88581705704596 | 14.45774635573264 | 15.17097040474319 | 15.42032751808284 | 15.87823666426329 | 15.57390191995168 | 16.52126457438368 | 16.98280724508978 | 16.20626645485133 | 15.84284736073 | 14.7053869690091 | 14.03957917565747 | 13.8019115891056 | 15.3524555635479 | 14.82812083107758 | 13.98001510190502 | 13.74710906692973
Latin America and the Caribbean | LCR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Least developed countries: UN classification | LDC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.137318922775 | 11.29912195841247 | 11.14755348674099 | 11.16787317124484 | 11.15326349586996 | 10.93731714627875 | 11.31283858205432 | 10.98956977625962 | 11.05546162648902 | 11.48351386180456 | 11.37624158893365 | 11.03621926946274 | 10.51240238631951 | 10.45180171350613 | 10.66535763449498 | 10.99298332601928 | 10.79693562403026 | 11.02989374591634 | 11.4364618882906 | 11.19235049264419 | 11.22142782876053 | 11.32022572135645
Low income | LIC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.761940972695665 | 9.965622270971581 | 9.835128083859336 | 9.715599909879753 | 9.802104158852607 | 9.897456165240866 | 10.22358535839582 | 9.95179935916679 | 10.06466748200766 | 10.32680314732346 | 10.28217136332313 | 9.895906543660333 | 9.25732790992612 | 9.167531663800288 | 9.298435733857103 | 9.637329262857618 | 9.465267406842532 | 9.74431338774544 | 10.14834781254684 | 9.637792434293738 | 9.671604997454542 | 9.794772186248196
[NAME] | LIE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
[NAME] | LKA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.7999992370605 | 40.5999984741211 | 35.7999992370605 | 35.9000015258789 | 34.5999984741211 | 32.9000015258789 | 31.7999992370605 | 25.7000007629395 | 26.6000003814697 | 24 | 24.8999996185303 | 27.8999996185303 | 26.3999996185303 | 26.7000007629395 | 26.2999992370605 | 21 | 20.5 | 17.8999996185303 | 20.7000007629395 | 18.7999992370605 | 18.7999992370605 | 18.5
Lower middle income | LMC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.58641445748914 | 11.30513612749433 | 12.32960605950184 | 11.70769749244318 | 11.61004384216258 | 11.74118617089538 | 12.54971667536937 | 12.14429458830167 | 12.36012442848236 | 13.45764110961353 | 13.54430565995459 | 14.43562428752773 | 14.05394257969605 | 13.89230078986541 | 14.42835032666928 | 13.98028907304848 | 12.77010756345235 | 13.02321499705372 | 12.82938941219304 | 13.04508674154643 | 13.17916283955204 | 12.97171408094225
Low & middle income | LMY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.34895323117387 | 11.39160598533028 | 11.98285160737621 | 11.68205361659068 | 11.97955657981163 | 12.22398519532308 | 12.65428143812099 | 12.69440782918528 | 12.89929219715221 | 13.51002513591479 | 13.54018355796802 | 13.98669194073513 | 13.73203390315502 | 13.43871697757446 | 13.42006580349811 | 12.95591408101883 | 12.23582482100132 | 12.60656973516238 | 12.85860751262621 | 12.80942422088679 | 12.81046527006766 | 12.81496102967093
[NAME] | LSO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.4000015258789 | 44.5 | 46.5999984741211 | 45.5999984741211 | 39.7999992370605 | 35.7000007629395 | 47.5 | 40.9000015258789 | 34 | 45.2999992370605 | 45 | 40.5999984741211 | 47 | 44.0999984741211 | 44.7000007629395 | 40.4000015258789 | 33.5999984741211 | 34.2999992370605 | 34.7999992370605 | 32.4000015258789 | 33.2999992370605 | 35.9000015258789
Lithuania | LTU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30 | 17.6000003814697 | 25.5 | 32.5999984741211 | 32.0999984741211 | 29.3999996185303 | 26 | 25.2000007629395 | 25.3999996185303 | 28.5 | 31.5 | 20.3999996185303 | 26.7000007629395 | 21.2000007629395 | 15.6999998092651 | 9.80000019073486 | 8.19999980926514 | 13.3999996185303 | 29.2999992370605 | 35.0999984741211 | 31.8999996185303 | 26.2999992370605
Luxembourg | LUX | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 3.5 | 4.40000009536743 | 7.90000009536743 | 7.30000019073486 | 9.30000019073486 | 7.30000019073486 | 6.40000009536743 | 6.80000019073486 | 6.40000009536743 | 6.40000009536743 | 6.90000009536743 | 10.8999996185303 | 16.7999992370605 | 13.6000003814697 | 16.2000007629395 | 15.1999998092651 | 17.7000007629395 | 17.1000003814697 | 14.1999998092651 | 16.7000007629395 | 18.5
Latvia | LVA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.5 | 21.8999996185303 | 21.3999996185303 | 26.1000003814697 | 21.5 | 20.6000003814697 | 25.8999996185303 | 26.8999996185303 | 23.5 | 21.2000007629395 | 22.8999996185303 | 25.6000003814697 | 17.5 | 19.3999996185303 | 13.5 | 12.1999998092651 | 10.8000001907349 | 13.1999998092651 | 33.9000015258789 | 34.7999992370605 | 31 | 28.3999996185303
Macao SAR, China | MAC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.59999990463257 | 3.70000004768372 | 3.70000004768372 | 5.59999990463257 | 6.19999980926514 | 7.09999990463257 | 8.10000038146973 | 10.3999996185303 | 11.3999996185303 | 10 | 10.5 | 11.3999996185303 | 12.6999998092651 | 10.8000001907349 | 8.19999980926514 | 7 | 6.19999980926514 | 5.90000009536743 | 7.69999980926514 | 5.30000019073486 | 5.80000019073486 | 3.79999995231628
St. Martin (French part) | MAF | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Morocco | MAR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.7000007629395 | 17.2999992370605 | 17 | 16.6000003814697 | 16.2999992370605 | 16 | 15.6000003814697 | 15.3000001907349 | 20.3999996185303 | 19.7999992370605 | 18.8999996185303 | 17.6000003814697 | 16.8999996185303 | 15.3999996185303 | 15.6999998092651 | 16.6000003814697 | 17.2999992370605 | 18.3999996185303 | 18.1000003814697 | 17.7000007629395 | 17.7999992370605 | 17.3999996185303
Mexico and Central America | MCA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Monaco | MCO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Moldova | MDA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.6999998092651 | 14.3999996185303 | 14 | 14.1999998092651 | 14.3000001907349 | 14.3000001907349 | 17.7999992370605 | 12.6000003814697 | 25.3999996185303 | 15.8999996185303 | 16.5 | 15.1999998092651 | 18.2000007629395 | 19.7999992370605 | 18.7999992370605 | 17.1000003814697 | 14.3999996185303 | 11.3000001907349 | 15.3000001907349 | 17.7000007629395 | 15.1000003814697 | 13.1000003814697
Madagascar | MDG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4 | 5.09999990463257 | 4.09999990463257 | 4.90000009536743 | 4.5 | 4 | 2.70000004768372 | 2.59999990463257 | 2.59999990463257 | 2.29999995231628 | 4.90000009536743 | 5.80000019073486 | 6.90000009536743 | 4.5 | 2.20000004768372 | 4.69999980926514 | 5 | 5.5 | 5.80000019073486 | 6.19999980926514 | 6.19999980926514 | 5.69999980926514
Maldives | MDV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.1000003814697 | 21.3999996185303 | 21.7000007629395 | 22.6000003814697 | 22.8999996185303 | 22.7999992370605 | 22.7999992370605 | 23.2000007629395 | 24.2000007629395 | 24.1000003814697 | 23.7999992370605 | 23.5 | 23.2000007629395 | 23.7999992370605 | 23 | 22.2000007629395 | 24.5 | 24.1000003814697 | 24.7999992370605 | 25.3999996185303 | 25.3999996185303 | 25.1000003814697
Middle East & North Africa (all income levels) | MEA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 26.8707055358706 | 27.06863065676319 | 27.60724279601782 | 27.89485764693958 | 28.16635051564383 | 27.19305364870766 | 26.67029114577665 | 26.57588989189325 | 25.42915352988689 | 28.33469965425559 | 28.10549089338943 | 28.62881994957944 | 28.88847891708965 | 27.64924653895453 | 27.21366479690987 | 26.20324824225623 | 24.78033674830305 | 24.52305902672083 | 24.51988332334704 | 25.85692534681543 | 27.19355248013177 | 27.64221342341239
Mexico | MEX | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 5.30000019073486 | 5.30000019073486 | 7 | 11.1999998092651 | 9.10000038146973 | 7.19999980926514 | 6.30000019073486 | 4 | 5 | 4.80000019073486 | 5.80000019073486 | 6.09999990463257 | 7.5 | 6.59999990463257 | 6.09999990463257 | 6.59999990463257 | 7 | 10 | 9.39999961853027 | 9.80000019073486 | 9.39999961853027
Marshall Islands | MHL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Middle income | MIC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.70169975436494 | 11.59037790702043 | 12.28925231299932 | 11.96913679777072 | 12.30450167000272 | 12.578438723371 | 13.03183904679277 | 13.12782452120366 | 13.3536514063204 | 14.02572392486164 | 14.07176262677916 | 14.65684410912392 | 14.46700460476686 | 14.14251670638832 | 14.10283635152714 | 13.50983466624349 | 12.70283961493757 | 13.09528099162439 | 13.32922415915565 | 13.37208387347968 | 13.38221810739755 | 13.38238611101919
Macedonia, FYR | MKD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 55.5 | 55.2000007629395 | 57.2000007629395 | 55.2999992370605 | 52.4000015258789 | 61.4000015258789 | 61.2000007629395 | 71.9000015258789 | 62.9000015258789 | 59.9000015258789 | 56.2999992370605 | 58.5 | 65.9000015258789 | 65 | 62.7999992370605 | 59.7000007629395 | 57.7999992370605 | 56.4000015258789 | 55.2000007629395 | 53.7000007629395 | 55.4000015258789 | 53.7999992370605
[NAME] | MLI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8000001907349 | 11.1000003814697 | 11 | 11.1000003814697 | 11.3999996185303 | 11 | 10.6000003814697 | 10.8000001907349 | 10.5 | 10.6000003814697 | 10.8000001907349 | 10.8999996185303 | 11.1000003814697 | 11.3999996185303 | 11 | 10.6999998092651 | 10.8999996185303 | 10.8000001907349 | 10.8999996185303 | 10.3000001907349 | 10.3999996185303 | 10.3000001907349
Malta | MLT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 13.8999996185303 | 14.8999996185303 | 14.5 | 18.6000003814697 | 14.8000001907349 | 14 | 13.3999996185303 | 15 | 11.8999996185303 | 17.6000003814697 | 15.1000003814697 | 17.2000007629395 | 18.5 | 17 | 15.8000001907349 | 13.6999998092651 | 12 | 14.3999996185303 | 13.1000003814697 | 14 | 14.3999996185303
Myanmar | MMR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6000003814697 | 11.5 | 11.5 | 11.3000001907349 | 11.3999996185303 | 11.3999996185303 | 11.6000003814697 | 12.3999996185303 | 11 | 10.6999998092651 | 10.8999996185303 | 10.8999996185303 | 10.6999998092651 | 10.6999998092651 | 10.6999998092651 | 10.8000001907349 | 10.8999996185303 | 11.8000001907349 | 11.6000003814697 | 11.6000003814697 | 11.6000003814697 | 11.5
Middle East & North Africa (developing only) | MNA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.49826642586434 | 27.50273091236415 | 28.04208793943516 | 28.50547586963716 | 28.92430490383765 | 27.72172888450623 | 27.07531106325519 | 26.89913225921942 | 26.08190125630987 | 29.24910677366073 | 28.92122704273935 | 29.27085162745909 | 29.40689494290507 | 28.14596353367899 | 27.73777186749442 | 26.1861997293422 | 25.02971187487553 | 24.85861933813253 | 24.88797133842511 | 26.478926581606 | 28.53776494148007 | 28.69523737114879
Montenegro | MNE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.5999984741211 | 34.2999992370605 | 36.0999984741211 | 41 | 54.5 | 55.7000007629395 | 40.9000015258789 | 41 | 41 | 57.7999992370605 | 40.9000015258789 | 40.9000015258789 | 41 | 56.2000007629395 | 58.4000015258789 | 47.9000015258789 | 38.5999984741211 | 30.7999992370605 | 35.7999992370605 | 46 | 37.2000007629395 | 41.2999992370605
Mongolia | MNG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8999996185303 | 10.8999996185303 | 10.6999998092651 | 12.8000001907349 | 15.6000003814697 | 12.8999996185303 | 14 | 13.6000003814697 | 13.3999996185303 | 12.1999998092651 | 13.3999996185303 | 14.5 | 11.6000003814697 | 12.1999998092651 | 14.6999998092651 | 10.8000001907349 | 11.6999998092651 | 9.60000038146973 | 9.89999961853027 | 14.3000001907349 | 10.1000003814697 | 11
Northern Mariana Islands | MNP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Mozambique | MOZ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 13.3000001907349 | 12.8000001907349 | 12.8999996185303 | 13 | 12.6000003814697 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349 | 13 | 12.6000003814697 | 12.6999998092651 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349
Mauritania | MRT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 46.7000007629395 | 46.5999984741211 | 46.5999984741211 | 46.5999984741211 | 46.5 | 46.5 | 46.5 | 46.4000015258789 | 46.2999992370605 | 46.2999992370605 | 46.2999992370605 | 46.2000007629395 | 46.0999984741211 | 47.0999984741211 | 46.5999984741211 | 46.2000007629395 | 45.5 | 45.4000015258789 | 45.4000015258789 | 45.2000007629395 | 45.2000007629395 | 45.2999992370605
[NAME] | MUS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22 | 22.1000003814697 | 22.2999992370605 | 22.5 | 22.2999992370605 | 21.2000007629395 | 20.1000003814697 | 21.2000007629395 | 22.3999996185303 | 19.8999996185303 | 17.6000003814697 | 19 | 20.7000007629395 | 25.3999996185303 | 26.1000003814697 | 23 | 24.1000003814697 | 18.7999992370605 | 20.8999996185303 | 23.1000003814697 | 21.7000007629395 | 22.8999996185303
[NAME] | MWI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3000001907349 | 13.8999996185303 | 13.1999998092651 | 14.1000003814697 | 13.1000003814697 | 13.1999998092651 | 13.3999996185303 | 13.6000003814697 | 13.5 | 13.6000003814697 | 13.8000001907349 | 13.5 | 13.3999996185303 | 13.3999996185303 | 13.5 | 13.5 | 13.3000001907349 | 13.3999996185303 | 13.3000001907349 | 13.3999996185303 | 13.5 | 13.5
Malaysia | MYS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.19999980926514 | 10.3999996185303 | 11.6999998092651 | 10.8000001907349 | 9 | 7.30000019073486 | 7.09999990463257 | 9 | 9.89999961853027 | 8.5 | 10.5 | 10.6000003814697 | 11 | 10.8000001907349 | 10.8999996185303 | 10.3999996185303 | 10.6999998092651 | 10.6000003814697 | 11.6000003814697 | 11 | 10.1999998092651 | 10.1999998092651
North America | NAC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.99787959688497 | 14.94653534988152 | 14.13454061269852 | 13.1043036847431 | 12.63463898044269 | 12.60230848688102 | 12.04691421097162 | 11.12506395902451 | 10.57442728206315 | 9.89597051604015 | 10.99974384244443 | 12.43254337143926 | 12.79440346725127 | 12.22246094533372 | 11.58473941912155 | 10.79411773633721 | 10.83775836585633 | 12.95781862078731 | 17.55269976360436 | 18.32892671795365 | 17.18713676199256 | 16.29244465783971
Namibia | NAM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.9000015258789 | 35.0999984741211 | 35.2999992370605 | 32 | 33.2999992370605 | 34.7000007629395 | 36.7999992370605 | 38.4000015258789 | 40.0999984741211 | 43.9000015258789 | 43.0999984741211 | 33.5 | 42 | 42.2999992370605 | 39.0999984741211 | 42.7999992370605 | 36.9000015258789 | 59.9000015258789 | 51.5999984741211 | 44.0999984741211 | 40.0999984741211 | 34.2000007629395
New Caledonia | NCL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
[NAME] | NER | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514
Nigeria | NGA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6000003814697 | 13.6000003814697 | 13.6999998092651 | 13.6000003814697 | 13.6000003814697 | 13.6999998092651 | 13.6999998092651 | 13.6999998092651 | 13.6000003814697 | 13.6999998092651 | 13.8000001907349 | 14.1999998092651 | 13.8000001907349 | 13.8000001907349 | 13.6999998092651 | 13.6999998092651 | 13.8000001907349 | 13.6999998092651 | 13.8000001907349 | 13.8000001907349 | 13.8000001907349 | 13.6999998092651
Nicaragua | NIC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.09999990463257 | 4.90000009536743 | 5.19999980926514 | 3.59999990463257 | 3.79999995231628 | 4.09999990463257 | 4.30000019073486 | 7.59999990463257 | 5.19999980926514 | 3.70000004768372 | 4.30000019073486 | 4.80000019073486 | 12.5 | 10.6000003814697 | 8.89999961853027 | 8.60000038146973 | 6.80000019073486 | 8.5 | 9.19999980926514 | 11.1000003814697 | 10.8999996185303 | 10.5
Netherlands | NLD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1000003814697 | 8.10000038146973 | 10.3999996185303 | 11.3000001907349 | 12.1000003814697 | 11.3999996185303 | 9.69999980926514 | 8.69999980926514 | 7.40000009536743 | 5.30000019073486 | 4.40000009536743 | 4.59999990463257 | 6.59999990463257 | 8 | 8.19999980926514 | 6.59999990463257 | 5.90000009536743 | 5.30000019073486 | 6.59999990463257 | 8.69999980926514 | 7.59999990463257 | 9.5
High income: nonOECD | NOC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.98910322711623 | 15.06615328852129 | 15.88948467036894 | 17.65179123121675 | 19.28111893525272 | 19.90801686744535 | 22.80841077603174 | 25.86615011204927 | 23.00167196217404 | 20.66564980329501 | 19.06201692521125 | 17.51483913049659 | 19.26213155082648 | 18.57402092333577 | 17.25906919711338 | 18.57459805490149 | 16.35230127967629 | 16.21214811465534 | 19.76690685477551 | 18.94816911907337 | 16.84587650034014 | 17.36275631610469
Norway | NOR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6000003814697 | 13.6999998092651 | 13.6999998092651 | 12.3999996185303 | 11.6999998092651 | 12.1000003814697 | 10.3999996185303 | 8.89999961853027 | 9.30000019073486 | 9.89999961853027 | 10.1999998092651 | 11.1999998092651 | 11.5 | 11.5 | 11.8000001907349 | 8.60000038146973 | 7.30000019073486 | 7.5 | 9.10000038146973 | 9.30000019073486 | 8.60000038146973 | 8.60000038146973
Nepal | NPL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.40000009536743 | 3.09999990463257 | 3.40000009536743 | 3.70000004768372 | 4 | 7.40000009536743 | 6.09999990463257 | 4.90000009536743 | 2.90000009536743 | 4.40000009536743 | 6.19999980926514 | 4.69999980926514 | 3.5 | 3.5 | 4.19999980926514 | 4.40000009536743 | 4.30000019073486 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5
New Zealand | NZL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.3999996185303 | 19.2000007629395 | 17.8999996185303 | 15.5 | 12.3000001907349 | 12.1999998092651 | 13.6000003814697 | 15 | 14.1999998092651 | 13.5 | 12.1000003814697 | 11.8000001907349 | 10.5 | 9.69999980926514 | 9.69999980926514 | 9.89999961853027 | 10 | 11.3000001907349 | 16.5 | 17.1000003814697 | 17.2999992370605 | 17.7000007629395
High income: OECD | OEC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.95801045114596 | 14.94983159170381 | 16.36230669579296 | 16.43714643934946 | 15.93573693188011 | 15.99713843499335 | 15.60521801792866 | 15.27099497187491 | 15.33961671536163 | 14.33628417246982 | 14.3582285736663 | 15.19877651548727 | 15.48174488396637 | 15.26027441801727 | 14.89526453486411 | 13.8204304012001 | 12.81773183919357 | 13.51291519301356 | 17.44046319924327 | 18.1154768900207 | 17.79707400714707 | 18.34033088399991
OECD members | OED | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.14203949400062 | 13.95436170512374 | 15.19802570105529 | 15.31408792130052 | 15.34997567550228 | 14.98001060937584 | 14.46600400369145 | 14.05134148068045 | 13.86903212776197 | 13.05153664681029 | 13.26738185725599 | 14.28305653783824 | 14.65122506919392 | 14.66419080840933 | 14.23735490087711 | 13.25358276324267 | 12.56647103375643 | 13.21617054437653 | 17.09251789447324 | 17.27639173511676 | 16.80969989588495 | 17.10985473140398
Oman | OMN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2999992370605 | 21.2999992370605 | 21.2000007629395 | 21.2000007629395 | 21.2999992370605 | 21.2999992370605 | 21.3999996185303 | 21.5 | 21.5 | 21.7000007629395 | 21.8999996185303 | 21.8999996185303 | 22.1000003814697 | 22.2000007629395 | 22.2000007629395 | 22.1000003814697 | 21.8999996185303 | 21.7999992370605 | 21.3999996185303 | 21.1000003814697 | 20.7999992370605 | 20.6000003814697
Other small states | OSS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.12744847560418 | 27.89547122893335 | 28.80042880777706 | 28.84367956027614 | 28.63921251805786 | 27.59942214195693 | 28.14823382171601 | 25.73204478825021 | 28.39099379995427 | 30.71425147280393 | 29.78771467346286 | 27.63032430987613 | 29.99521573381209 | 30.10807686461211 | 29.57767009226173 | 28.0692975257936 | 25.53586475628845 | 29.70428136684032 | 26.96106970845095 | 27.05631113841472 | 26.33679444709006 | 25.91397265136162
Pakistan | PAK | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1999998092651 | 8.60000038146973 | 7.19999980926514 | 7.5 | 8.89999961853027 | 9.30000019073486 | 10 | 10.3999996185303 | 11 | 13.3999996185303 | 13.6000003814697 | 13.5 | 13.1000003814697 | 11.8000001907349 | 11.1000003814697 | 8.80000019073486 | 7.59999990463257 | 7.90000009536743 | 7.90000009536743 | 8 | 8 | 8.19999980926514
Panama | PAN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.7000007629395 | 28.7000007629395 | 26.7000007629395 | 27.2999992370605 | 26.8999996185303 | 29.6000003814697 | 27 | 28.5 | 24.7000007629395 | 29 | 29.6000003814697 | 28.1000003814697 | 27.7000007629395 | 25.1000003814697 | 21.2000007629395 | 19.5 | 15.6000003814697 | 14.3000001907349 | 15.3999996185303 | 14.8999996185303 | 11.8999996185303 | 11.8999996185303
Peru | PER | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 9.69999980926514 | 11.1999998092651 | 7.5 | 6.90000009536743 | 8.80000019073486 | 7.69999980926514 | 7.59999990463257 | 7.40000009536743 | 9.19999980926514 | 6.90000009536743 | 8.5 | 10.5 | 8.5 | 8.5 | 7.5 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 6.5 | 6.40000009536743 | 6.5
Philippines | PHL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2999992370605 | 16.7999992370605 | 17 | 16.6000003814697 | 15.8999996185303 | 14.1999998092651 | 15.3999996185303 | 18.5 | 19.5 | 23 | 21 | 23.8999996185303 | 21.8999996185303 | 23.2999992370605 | 16.8999996185303 | 18.1000003814697 | 17.5 | 17.2000007629395 | 17.3999996185303 | 15.5 | 14.8999996185303 | 14.8999996185303
Palau | PLW | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
[NAME] | PNG | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 4.90000009536743 | 4.59999990463257 | 5.40000009536743 | 6.09999990463257 | 5.30000019073486 | 6.30000019073486 | 5.5 | 5.69999980926514 | 6 | 5.80000019073486 | 5.59999990463257 | 5.5 | 5.69999980926514 | 5.5 | 5.59999990463257 | 5.19999980926514 | 5.30000019073486 | 5.30000019073486 | 5.19999980926514 | 4.90000009536743 | 5.09999990463257
Poland | POL | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.8999996185303 | 27.2999992370605 | 29.5 | 31.8999996185303 | 30.6000003814697 | 28 | 24.2999992370605 | 22.8999996185303 | 29.5 | 34.7000007629395 | 40.2999992370605 | 43.2000007629395 | 42.5 | 40.4000015258789 | 37.4000015258789 | 29.6000003814697 | 21.5 | 17.1000003814697 | 20.3999996185303 | 23.6000003814697 | 25.6000003814697 | 26.3999996185303
Puerto Rico | PRI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 35 | 35 | 31.3999996185303 | 27.6000003814697 | 27 | 28.6000003814697 | 27.8999996185303 | 25.8999996185303 | 23.5 | 21.2000007629395 | 23.2999992370605 | 23.8999996185303 | 24.2999992370605 | 21.2000007629395 | 23.7000007629395 | 22.5 | 22.6000003814697 | 25.3999996185303 | 29.2999992370605 | 30.6000003814697 | 30.1000003814697 | 30.3999996185303
Korea, Dem. Rep. | PRK | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.09999990463257 | 6.09999990463257 | 6 | 5.80000019073486 | 5.80000019073486 | 9.60000038146973 | 9.60000038146973 | 10.5 | 9.60000038146973 | 9.5 | 10.1000003814697 | 9.60000038146973 | 9.69999980926514 | 9.30000019073486 | 9.39999961853027 | 9.30000019073486 | 9.19999980926514 | 9.80000019073486 | 10.3999996185303 | 9.19999980926514 | 9.30000019073486 | 9.69999980926514
Portugal | PRT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 9.80000019073486 | 12.5 | 14.6000003814697 | 16.1000003814697 | 16.5 | 14.8000001907349 | 10.3999996185303 | 8.80000019073486 | 8.60000038146973 | 9.30000019073486 | 11.6000003814697 | 14.3999996185303 | 15.3000001907349 | 16.1000003814697 | 16.2000007629395 | 16.6000003814697 | 16.5 | 20 | 22.2999992370605 | 30.1000003814697 | 37.7000007629395
Paraguay | PRY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.1000003814697 | 8.80000019073486 | 13.1000003814697 | 11.6000003814697 | 6 | 8.10000038146973 | 10.1000003814697 | 10.1000003814697 | 11.6000003814697 | 13.6999998092651 | 13.8000001907349 | 18.6000003814697 | 15 | 14.1999998092651 | 11.1000003814697 | 12.8999996185303 | 12 | 11.6000003814697 | 12.8000001907349 | 11.8999996185303 | 11.8999996185303 | 13
Pacific island small states | PSS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
French Polynesia | PYF | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Qatar | QAT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.40000009536743 | 3.20000004768372 | 3.20000004768372 | 3.20000004768372 | 3.29999995231628 | 3.59999990463257 | 3.79999995231628 | 2.20000004768372 | 1.60000002384186 | 1.10000002384186 | 1.89999997615814 | 3 | 4.30000019073486 | 5.5 | 4.09999990463257 | 2.90000009536743 | 1.79999995231628 | 1.20000004768372 | 0.899999976158142 | 1.29999995231628 | 1.70000004768372 | 1.70000004768372
Romania | [NAME] | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.6000003814697 | 23.2999992370605 | 22.8999996185303 | 22.5 | 20.7999992370605 | 20.7000007629395 | 17.5 | 17 | 17.2999992370605 | 17.7999992370605 | 17.5 | 22.1000003814697 | 19.5 | 22.3999996185303 | 20.2999992370605 | 21.3999996185303 | 20.2000007629395 | 18.7000007629395 | 20.7999992370605 | 22.2000007629395 | 23.8999996185303 | 22.7999992370605
Russian Federation | RUS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.6000003814697 | 12.8999996185303 | 13.6999998092651 | 16.2999992370605 | 18.7000007629395 | 19.2999992370605 | 23.3999996185303 | 27.1000003814697 | 24 | 20.7000007629395 | 18 | 15.5 | 17.6000003814697 | 17.2000007629395 | 15.5 | 16.3999996185303 | 14.3999996185303 | 14.1000003814697 | 18.5 | 17 | 15.3000001907349 | 14.8999996185303
Rwanda | RWA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.800000011920929 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071
South Asia | SAS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.544571976567939 | 9.423779974045312 | 9.632418498671722 | 8.555187519830007 | 9.158616023856547 | 9.117709880111091 | 10.21089866257712 | 8.797980720304261 | 9.288332964052808 | 10.50719454695517 | 9.783948367342306 | 10.4132668302457 | 9.81700105140485 | 9.405690760807808 | 10.16230466561975 | 9.956576444532073 | 9.23697870990559 | 9.928792828041647 | 9.808954603137526 | 9.900179033406364 | 9.900939578162616 | 9.62249023037913
Saudi Arabia | SAU | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.7999992370605 | 25.1000003814697 | 26.7000007629395 | 25.7999992370605 | 26.2999992370605 | 28.3999996185303 | 29.3999996185303 | 30.1000003814697 | 23 | 23.7000007629395 | 24.2999992370605 | 26.8999996185303 | 28.6000003814697 | 27.2000007629395 | 27.2999992370605 | 34.9000015258789 | 30.2000007629395 | 29.7999992370605 | 29.8999996185303 | 29.7999992370605 | 23 | 27.7999992370605
[NAME] | SCE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Sudan | SDN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.2999992370605 | 23.1000003814697 | 23.2999992370605 | 23.2999992370605 | 23.5 | 23.6000003814697 | 24.7000007629395 | 23.8999996185303 | 23.8999996185303 | 24 | 23.7000007629395 | 23.7000007629395 | 23.7000007629395 | 23.7000007629395 | 23.6000003814697 | 23.7000007629395 | 23.7000007629395 | 23.6000003814697 | 23.7000007629395 | 23.6000003814697 | 23.6000003814697 | 23.7999992370605
Senegal | SEN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1999998092651 | 14 | 14.1000003814697 | 14.1000003814697 | 14 | 14 | 14.1000003814697 | 14 | 14.1999998092651 | 14 | 14 | 14 | 14.1000003814697 | 14 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697
Singapore | SGP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.19999980926514 | 6.19999980926514 | 6.09999990463257 | 6.59999990463257 | 6.80000019073486 | 7 | 6.5 | 11.8000001907349 | 12.6999998092651 | 12.5 | 13 | 17.2999992370605 | 18.6000003814697 | 15.6999998092651 | 14.6000003814697 | 12.8000001907349 | 10.8000001907349 | 11.6999998092651 | 15.8999996185303 | 11.1999998092651 | 10.6999998092651 | 10.1999998092651
Solomon Islands | SLB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3000001907349 | 10.5 | 11.5 | 11 | 10.8000001907349 | 11.8000001907349 | 12.1000003814697 | 11.8000001907349 | 12 | 13.8000001907349 | 12.8999996185303 | 12.3000001907349 | 11.1999998092651 | 11 | 10.5 | 11.5 | 11.1999998092651 | 11.1999998092651 | 12.6000003814697 | 11.1000003814697 | 10.8000001907349 | 11.5
Sierra Leone | SLE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 5.19999980926514 | 5.09999990463257 | 5.09999990463257 | 5.19999980926514 | 5.30000019073486 | 5.30000019073486 | 5.09999990463257 | 5.19999980926514 | 5.09999990463257 | 4.90000009536743 | 4.90000009536743 | 5 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5
El Salvador | SLV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 14 | 16.8999996185303 | 13.3000001907349 | 14.1999998092651 | 13.8000001907349 | 13.8999996185303 | 12.8999996185303 | 13 | 13 | 13 | 11.3999996185303 | 11.3000001907349 | 11.3999996185303 | 12.6999998092651 | 12.1999998092651 | 10.8999996185303 | 10.6000003814697 | 13.1999998092651 | 12.6000003814697 | 12.5 | 12.6999998092651
[NAME] | SMR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Somalia | SOM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.8000001907349 | 12.6999998092651 | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651
Serbia | SRB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29 | 32.2000007629395 | 39.5 | 34.7000007629395 | 30.6000003814697 | 30.1000003814697 | 31.3999996185303 | 31.2000007629395 | 31.2000007629395 | 28.7000007629395 | 29.2000007629395 | 31.6000003814697 | 34.9000015258789 | 42.5999984741211 | 48.0999984741211 | 46.7999992370605 | 42.7999992370605 | 34.2000007629395 | 41.7000007629395 | 45.4000015258789 | 45.4000015258789 | 45.9000015258789
Sub-Saharan Africa (developing only) | SSA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.24768215870446 | 15.17926890345516 | 15.41375655619809 | 14.36481418647424 | 13.84870389445988 | 14.82823055321687 | 15.11584092490711 | 14.75402545804481 | 14.92991380276833 | 14.94833948203077 | 15.34254252875137 | 15.22525147731928 | 15.23617609398005 | 14.56795598322394 | 13.86584461423118 | 13.8619443491395 | 13.57343389479374 | 13.68397982006133 | 13.88144335542845 | 13.96296420769734 | 13.88162067686419 | 13.83845919031357
South Sudan | SSD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Sub-Saharan Africa (all income levels) | SSF | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.24604233856725 | 15.17732877957464 | 15.41204249429098 | 14.36374157325953 | 13.84796077352548 | 14.82655217787853 | 15.11360170902505 | 14.75276707488045 | 14.92847690100865 | 14.94695453463168 | 15.34038468218429 | 15.22354827945391 | 15.23443551457158 | 14.56624307856664 | 13.86500099755891 | 13.86122452649328 | 13.57260889662803 | 13.68312973374124 | 13.88074224363417 | 13.96219157015932 | 13.88074996601962 | 13.83770496384651
Small states | SST | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.53933395949621 | 27.72269632770821 | 28.69714578350563 | 28.55017052645698 | 29.35489338189645 | 28.40253522604394 | 28.42524343662122 | 26.84420850342945 | 28.59676366305302 | 29.51536384650167 | 29.05590346250963 | 27.27785560219982 | 28.17933122192867 | 28.34644488018522 | 27.68558625741724 | 26.19092717969622 | 24.17597731749658 | 27.58093514092327 | 25.96217367983317 | 26.53917636108684 | 26.08096943010222 | 26.11642338682544
Sao Tome and Principe | STP | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Suriname | SUR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.7000007629395 | 41.7999992370605 | 34.7000007629395 | 29.7999992370605 | 27.7999992370605 | 28.7999992370605 | 28 | 28.2999992370605 | 33.5999984741211 | 33.2999992370605 | 31.3999996185303 | 32 | 31.1000003814697 | 30.7999992370605 | 31.7999992370605 | 31.7000007629395 | 32.0999984741211 | 32.5999984741211 | 33.2000007629395 | 32.9000015258789 | 32.7000007629395 | 33.4000015258789
Slovak Republic | SVK | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.8999996185303 | 20 | 23 | 27.2999992370605 | 24.7000007629395 | 21 | 22.5 | 25 | 33.7000007629395 | 36.7999992370605 | 38.9000015258789 | 37.4000015258789 | 33.2000007629395 | 32.7999992370605 | 30 | 26.6000003814697 | 20.2000007629395 | 18.8999996185303 | 27.3999996185303 | 33.7000007629395 | 33.2000007629395 | 34
Slovenia | SVN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6000003814697 | 10.3000001907349 | 32.2000007629395 | 22 | 19.2999992370605 | 16.8999996185303 | 16.6000003814697 | 17.7000007629395 | 18.5 | 16.3999996185303 | 15.6999998092651 | 16.7000007629395 | 17.5 | 16.2000007629395 | 16 | 14 | 10.1000003814697 | 10.5 | 13.6999998092651 | 14.6999998092651 | 15.8000001907349 | 20.7000007629395
Sweden | SWE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 14 | 23.2999992370605 | 23.2000007629395 | 20.2000007629395 | 22.1000003814697 | 22.1000003814697 | 17.3999996185303 | 14.8999996185303 | 12.1000003814697 | 12 | 13 | 13.8999996185303 | 17.2000007629395 | 22.5 | 21.5 | 19.7999992370605 | 20.7999992370605 | 25.2999992370605 | 25.2000007629395 | 23.1000003814697 | 24.1000003814697
Swaziland | SWZ | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.0999984741211 | 42 | 42 | 42 | 41.5 | 41.7999992370605 | 42 | 42 | 42 | 42.0999984741211 | 42.0999984741211 | 42.0999984741211 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42.0999984741211 | 41.9000015258789
Sint Maarten (Dutch part) | SXM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Seychelles | SYC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Syrian Arab Republic | SYR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.8999996185303 | 18.1000003814697 | 14.1000003814697 | 14 | 13.6000003814697 | 18.2999992370605 | 17.3999996185303 | 13.8999996185303 | 14.8999996185303 | 18.7999992370605 | 23 | 28.1000003814697 | 19.2999992370605 | 19.2000007629395 | 18.8999996185303 | 18.3999996185303 | 19 | 21.8999996185303 | 16.1000003814697 | 19.2999992370605 | 19.2999992370605 | 19.2999992370605
Turks and Caicos Islands | TCA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Chad | TCD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6999998092651 | 12.8999996185303 | 13.1000003814697 | 12.8000001907349 | 13 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 13 | 13 | 12.6000003814697 | 12.6999998092651 | 12.6000003814697 | 12.1000003814697 | 12.6999998092651 | 13 | 13 | 12.8999996185303 | 13 | 12.6000003814697 | 13 | 12.8000001907349
Togo | TGO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 13.1000003814697 | 13.5 | 12.6000003814697 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 13.1000003814697 | 12.8999996185303 | 13 | 13 | 13 | 12.8000001907349 | 12.8999996185303 | 13 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303 | 12.8999996185303
Thailand | THA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 3.5 | 3.79999995231628 | 2.5 | 2.5 | 2.5 | 2.29999995231628 | 7.5 | 8 | 6.90000009536743 | 7.90000009536743 | 5.69999980926514 | 5.09999990463257 | 4.69999980926514 | 4.59999990463257 | 4.90000009536743 | 4.59999990463257 | 5.09999990463257 | 5.90000009536743 | 4 | 2.90000009536743 | 2.79999995231628
Tajikistan | TJK | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.2000007629395 | 19.1000003814697 | 20 | 19.5 | 19.8999996185303 | 20.6000003814697 | 20.8999996185303 | 21.1000003814697 | 21 | 21.2999992370605 | 21.2999992370605 | 21.2999992370605 | 21.2999992370605 | 21.2999992370605 | 21.1000003814697 | 21.2000007629395 | 21.2000007629395 | 21.2000007629395 | 21 | 21.1000003814697 | 21.2000007629395 | 21.2000007629395
Turkmenistan | TKM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.1000003814697 | 20.1000003814697 | 19.8999996185303 | 19.6000003814697 | 20 | 20.3999996185303 | 20.2000007629395 | 21.1000003814697 | 21.6000003814697 | 21.7000007629395 | 21.7000007629395 | 21.5 | 21.6000003814697 | 21.3999996185303 | 21.2999992370605 | 21.2000007629395 | 21.2000007629395 | 21.3999996185303 | 21 | 21.1000003814697 | 21.3999996185303 | 21.1000003814697
Timor-Leste | TLS | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.5 | 15.1999998092651 | 15.1000003814697 | 14.8000001907349 | 14.8000001907349 | 14.8999996185303 | 15.1999998092651 | 16.6000003814697 | 15.1999998092651 | 14.8999996185303 | 20.8999996185303 | 19.7999992370605 | 18.7000007629395 | 17.7000007629395 | 16.7000007629395 | 15.6999998092651 | 16.7000007629395 | 15.8999996185303 | 15.1000003814697 | 13.1000003814697 | 12.8999996185303 | 12.6000003814697
Tonga | TON | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Trinidad and Tobago | TTO | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.5 | 34.4000015258789 | 33.4000015258789 | 31.8999996185303 | 30.7000007629395 | 28.5 | 27.2000007629395 | 26.7000007629395 | 25.2999992370605 | 23.2000007629395 | 21.1000003814697 | 20.7000007629395 | 21 | 16.7000007629395 | 16.3999996185303 | 13 | 11.1999998092651 | 10.3999996185303 | 11.6999998092651 | 14 | 14.6000003814697 | 13.6000003814697
Tunisia | TUN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.2000007629395 | 31 | 31.8999996185303 | 28.7999992370605 | 31.2999992370605 | 31.6000003814697 | 31.8999996185303 | 34.9000015258789 | 32.7999992370605 | 32.4000015258789 | 31.2999992370605 | 32 | 30.5 | 29.5 | 27.7000007629395 | 27 | 27.1000003814697 | 27.3999996185303 | 29.7000007629395 | 29.3999996185303 | 29.2999992370605 | 29.2999992370605
Turkey | TUR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.3000001907349 | 16.2000007629395 | 17.5 | 15.8999996185303 | 15.3999996185303 | 13.3000001907349 | 14.1000003814697 | 13.8999996185303 | 14.6999998092651 | 12.8000001907349 | 15.8999996185303 | 18.7000007629395 | 20 | 20 | 19.2999992370605 | 18.5 | 19.2999992370605 | 19.8999996185303 | 24.6000003814697 | 21.2000007629395 | 17.8999996185303 | 17
Tuvalu | TUV | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Tanzania | TZA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 6.59999990463257 | 6.90000009536743 | 7.09999990463257 | 8.39999961853027 | 8.89999961853027 | 8.39999961853027 | 8.60000038146973 | 8.39999961853027 | 8.89999961853027 | 8.80000019073486 | 6.59999990463257 | 6.5 | 5.5 | 4.69999980926514 | 7.69999980926514 | 3.29999995231628 | 4.40000009536743 | 4.69999980926514 | 5.59999990463257 | 6.59999990463257 | 6.5
Uganda | UGA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 4.40000009536743 | 4 | 4 | 4 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.19999980926514 | 4.80000019073486 | 5.59999990463257 | 6 | 5.5 | 4.30000019073486 | 3.40000009536743 | 3.5 | 3.59999990463257 | 5 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.30000019073486
Ukraine | UKR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1000003814697 | 15.8000001907349 | 18.1000003814697 | 14.5 | 11.5 | 15.6000003814697 | 18.2000007629395 | 23.1000003814697 | 23.7000007629395 | 23.7999992370605 | 22.2999992370605 | 19.6000003814697 | 18.7000007629395 | 15.6999998092651 | 15 | 13.8999996185303 | 13.1000003814697 | 13.1000003814697 | 18.1000003814697 | 16.7999992370605 | 18.2000007629395 | 17.2999992370605
Upper middle income | UMC | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.80164159890748 | 11.84478321164551 | 12.25210645545752 | 12.21762268512601 | 12.9850719744641 | 13.42313444403801 | 13.53165820677692 | 14.17131217668716 | 14.42507112331155 | 14.64309369224297 | 14.64414469066752 | 14.89481518699245 | 14.9060533353771 | 14.40575812330267 | 13.76214175979455 | 13.0171469459802 | 12.63198653155602 | 13.17202934742158 | 13.87036534075501 | 13.73406980837194 | 13.61352526402148 | 13.86655007961799
Uruguay | URY | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.8999996185303 | 20.2999992370605 | 20.2999992370605 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.3999996185303 | 26.7000007629395 | 25.3999996185303 | 24.2000007629395 | 23.1000003814697 | 21.8999996185303 | 20.7999992370605 | 24.1000003814697 | 23.5 | 28.1000003814697 | 24.6000003814697 | 19.5 | 19.2000007629395 | 19.7999992370605 | 17.2999992370605 | 16.2999992370605
United States | USA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.8000001907349 | 14.6999998092651 | 13.8000001907349 | 12.8000001907349 | 12.3999996185303 | 12.3000001907349 | 11.6000003814697 | 10.6999998092651 | 10.1999998092651 | 9.60000038146973 | 10.8000001907349 | 12.3000001907349 | 12.6999998092651 | 12.1000003814697 | 11.5 | 10.6999998092651 | 10.8000001907349 | 13.1000003814697 | 17.7999992370605 | 18.7000007629395 | 17.5 | 16.5
Uzbekistan | UZB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.3999996185303 | 19.8999996185303 | 20.2999992370605 | 20.1000003814697 | 20.2999992370605 | 20.7999992370605 | 21 | 20.8999996185303 | 20.8999996185303 | 20.8999996185303 | 20.8999996185303 | 20.8999996185303 | 20.8999996185303 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.2000007629395 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697 | 21.1000003814697
St. Vincent and the Grenadines | VCT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Venezuela, RB | VEN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.3999996185303 | 14.1999998092651 | 12.5 | 16.1000003814697 | 19.8999996185303 | 24.8999996185303 | 19.7000007629395 | 21.2999992370605 | 25.7999992370605 | 24.2999992370605 | 22.6000003814697 | 28.2000007629395 | 28 | 25.5 | 19.7999992370605 | 17 | 14.3999996185303 | 13.6000003814697 | 15.3999996185303 | 17.5 | 17.3999996185303 | 16.2000007629395
Virgin Islands (U.S.) | VIR | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Vietnam | VNM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 4.40000009536743 | 5.5 | 4.30000019073486 | 3.59999990463257 | 3.09999990463257 | 4.69999980926514 | 3.90000009536743 | 5 | 4.59999990463257 | 5.69999980926514 | 4.09999990463257 | 4.59999990463257 | 4.40000009536743 | 4.19999980926514 | 4.80000019073486 | 4.80000019073486 | 5 | 4.90000009536743 | 4.80000019073486 | 4.30000019073486 | 4.40000009536743
[NAME] | VUT | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
West Bank and Gaza | PSE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.7000007629395 | 38 | 36.7000007629395 | 35.0999984741211 | 35.5999984741211 | 34.4000015258789 | 29.3999996185303 | 20.8999996185303 | 17.2999992370605 | 20.6000003814697 | 34.5999984741211 | 41.7000007629395 | 41.0999984741211 | 39.7999992370605 | 38.7000007629395 | 35.7000007629395 | 35.2000007629395 | 40.2000007629395 | 38.0999984741211 | 37.7000007629395 | 31.5 | 34.5999984741211
World | WLD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.87967617513068 | 11.98709924850697 | 12.69105852013475 | 12.49327276608333 | 12.7182774875942 | 12.94504571822179 | 13.33912991752272 | 13.42060349402315 | 13.51233398051867 | 13.83096552881481 | 13.80854174616935 | 14.23846046171805 | 14.10449404411319 | 13.80299215202798 | 13.70203060373528 | 13.21980333834338 | 12.42157528293621 | 12.8110088845147 | 13.55529162715204 | 13.55661741056585 | 13.45992679265374 | 13.53175309400937
Samoa | WSM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME]
Yemen, Rep. | YEM | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.7000007629395 | 28.2999992370605 | 26 | 31.1000003814697 | 29.3999996185303 | 27.6000003814697 | 29.2000007629395 | 31.1000003814697 | 27.5 | 31.8999996185303 | 27.7000007629395 | 27.6000003814697 | 28.1000003814697 | 27.7999992370605 | 31.2000007629395 | 30.5 | 29.7000007629395 | 29.2000007629395 | 28.6000003814697 | 35.0999984741211 | 34.7999992370605 | 34.7999992370605
South Africa | ZAF | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 47.7999992370605 | 46.2999992370605 | 50.0999984741211 | 39.4000015258789 | 33.5 | 41.7000007629395 | 45.7000007629395 | 43.7000007629395 | 46.2000007629395 | 45.2999992370605 | 50.2000007629395 | 53 | 55.4000015258789 | 51.2999992370605 | 48.4000015258789 | 46.7999992370605 | 46.5999984741211 | 45.5999984741211 | 48.2000007629395 | 50.7999992370605 | 50.2000007629395 | 52
Congo, Dem. Rep. | COD | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3999996185303 | 13.3999996185303 | 13.5 | 13.1999998092651 | 13 | 13.1000003814697 | 13.1999998092651 | 13.1000003814697 | 13.1999998092651 | 13.3000001907349 | 13.1000003814697 | 12.8999996185303 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8999996185303 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349
Zambia | ZMB | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.0999984741211 | 32.4000015258789 | 33.2999992370605 | 32.0999984741211 | 31.2000007629395 | 25.7999992370605 | 24.3999996185303 | 20.2000007629395 | 20.6000003814697 | 21.7000007629395 | 25.2999992370605 | 24.7000007629395 | 25 | 23.7999992370605 | 24.3999996185303 | 25.5 | 25.5 | 24.7999992370605 | 25.7000007629395 | 26.3999996185303 | 26.3999996185303 | 24.8999996185303
Zimbabwe | ZWE | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3000001907349 | 13.3999996185303 | 13.8000001907349 | 11.6999998092651 | 12.8000001907349 | 14 | 16.3999996185303 | 15.1000003814697 | 13.5 | 13.6999998092651 | 13.3000001907349 | 10.8000001907349 | 8.69999980926514 | 7 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 7.19999980926514 | 6.69999980926514 | 6.59999990463257 | 6.59999990463257 | 7