Spreadsheet: aae56ae7-e39f-4304-8095-e04a6645276a
Sheet: Sheet1

Data Source | World Development Indicators | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18 | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Unnamed: 22 | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Unnamed: 30 | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Unnamed: 34 | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Unnamed: 38 | Unnamed: 39 | Unnamed: 40 | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Unnamed: 44 | Unnamed: 45 | Unnamed: 46 | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Unnamed: 50 | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Unnamed: 56 | Unnamed: 57
Country Name | Country Code | Indicator Name | Indicator Code | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014
Aruba | ABW | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Andorra | AND | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Afghanistan | AFG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8999996185303 | 15.8000001907349 | 15.8999996185303 | 18.2000007629395 | 18.2999992370605 | 18.2000007629395 | 18.2999992370605 | 18.1000003814697 | 18.2999992370605 | 18.2999992370605 | 18.1000003814697
Angola | AGO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3000001907349 | 12.1000003814697 | 12.3999996185303 | 12.6000003814697 | 12.6999998092651 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.6000003814697 | 12.3999996185303 | 12.5 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6000003814697 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303
Albania | ALB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.7999992370605 | 22.1000003814697 | 31 | 29.2000007629395 | 26 | 24.1000003814697 | 24.1000003814697 | 24.7999992370605 | 26.7000007629395 | 25.7999992370605 | 42.2999992370605 | 23.2000007629395 | 23.2999992370605 | 23.2000007629395 | 23.2999992370605 | 22.8999996185303 | 25.5 | 27.2999992370605 | 24.8999996185303 | 27.2999992370605 | 27.2000007629395 | 27.6000003814697
Andean Region | ANR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Arab World | ARB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.29657289187619 | 23.55156341862548 | 23.94652636911866 | 24.43665796236977 | 24.91536236598557 | 23.96305922767316 | 23.60115175790588 | 23.445897183195 | 22.88170392652192 | 24.80400412873673 | 24.79672374572497 | 25.71579592622894 | 26.25510103599409 | 25.66947489977366 | 23.27607675699545 | 22.24631902800181 | 21.30794116450892 | 20.56385901661865 | 19.61718622360806 | 20.13787632025617 | 21.69740511016443 | 22.00283379988223
United Arab Emirates | ARE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 5.90000009536743 | 5.90000009536743 | 4.90000009536743 | 6.30000019073486 | 7.80000019073486 | 6.30000019073486 | 5.69999980926514 | 5.19999980926514 | 5 | 5.19999980926514 | 5.5 | 5.80000019073486 | 6.09999990463257 | 6.40000009536743 | 6.59999990463257 | 6.69999980926514 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8.10000038146973 | 8.39999961853027
Argentina | ARG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 13.1000003814697 | 17 | 18.8999996185303 | 29.7999992370605 | 27.7999992370605 | 22.1000003814697 | 20.7000007629395 | 22.7000007629395 | 22.6000003814697 | 29.8999996185303 | 32.5999984741211 | 33 | 25.2999992370605 | 21.8999996185303 | 20.7999992370605 | 17 | 16.6000003814697 | 18.7999992370605 | 16.7999992370605 | 16.6000003814697 | 15.6000003814697
Armenia | ARM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 35.4000015258789 | 35.5999984741211 | 35.9000015258789 | 35.7000007629395 | 39.2000007629395 | 34 | 35.9000015258789 | 42.0999984741211 | 35.2000007629395 | 39 | 41.7999992370605 | 44.5 | 46.2999992370605 | 40.7000007629395 | 46.2000007629395 | 37.7000007629395 | 48.7999992370605 | 46.4000015258789 | 36 | 32.2999992370605 | 35 | 34.0999984741211
American Samoa | ASM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
[NAME] and [NAME] | ATG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Australia | AUS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.5 | 20.7999992370605 | 19.7999992370605 | 17.7000007629395 | 15.8999996185303 | 16.3999996185303 | 17.2999992370605 | 15.3999996185303 | 14 | 12.8000001907349 | 14.6000003814697 | 13.8000001907349 | 12.6000003814697 | 11.8000001907349 | 10.8999996185303 | 10.5 | 9.5 | 9 | 12.5 | 11.8999996185303 | 11.8999996185303 | 12.3999996185303
Austria | AUT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4 | 4.19999980926514 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486 | 6.19999980926514 | 5.59999990463257 | 5 | 4.59999990463257 | 5 | 5.69999980926514 | 6.5 | 7.5 | 9.30000019073486 | 10.6999998092651 | 8.80000019073486 | 8.19999980926514 | 7.80000019073486 | 10.3999996185303 | 8.89999961853027 | 7.90000009536743 | 8.80000019073486
Azerbaijan | AZE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.8000001907349 | 14 | 13.1999998092651 | 12.3999996185303 | 13.6000003814697 | 14.5 | 12.1999998092651 | 14.8999996185303 | 17.2999992370605 | 14.6999998092651 | 14.3999996185303 | 12.8000001907349 | 15.8999996185303 | 14.8999996185303 | 17 | 17.7999992370605 | 17.6000003814697 | 18.7999992370605 | 12.6999998092651 | 17 | 13.8999996185303 | 14.3000001907349
Burundi | BDI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3999996185303 | 12.3000001907349 | 12.3000001907349 | 12.3000001907349 | 12.3000001907349 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349
Belgium | BEL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1000003814697 | 11.3000001907349 | 17.3999996185303 | 20.7000007629395 | 19.7999992370605 | 17.2999992370605 | 17.6000003814697 | 18.2999992370605 | 22.7000007629395 | 12.8999996185303 | 14.3999996185303 | 17.2999992370605 | 22.2999992370605 | 20.2000007629395 | 21 | 18.7999992370605 | 17.1000003814697 | 17.2999992370605 | 21.5 | 22.3999996185303 | 18.7000007629395 | 20.5
Benin | [NAME] | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.10000002384186 | 2.40000009536743 | 2 | 1.60000002384186 | 1.29999995231628 | 1.10000002384186 | 1.20000004768372 | 1.29999995231628 | 1.20000004768372 | 1.20000004768372 | 1.10000002384186 | 1.10000002384186 | 1.29999995231628 | 2.29999995231628 | 2.20000004768372 | 1.39999997615814 | 1.5 | 1.60000002384186 | 1.70000004768372 | 1.29999995231628 | 1.29999995231628 | 1.39999997615814
[NAME] | BFA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.09999990463257 | 4.59999990463257 | 6.09999990463257 | 5 | 4.69999980926514 | 4.69999980926514 | 4.40000009536743 | 4.59999990463257 | 4.40000009536743 | 5.80000019073486 | 4.5 | 5.69999980926514 | 5.40000009536743 | 5.30000019073486 | 5.19999980926514 | 4.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.5
Bangladesh | BGD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.30000019073486 | 9.30000019073486 | 8.80000019073486 | 8.39999961853027 | 8.10000038146973 | 7.09999990463257 | 8.5 | 7.19999980926514 | 9.10000038146973 | 9.60000038146973 | 9.19999980926514 | 8.80000019073486 | 6.69999980926514 | 7 | 6.69999980926514 | 8.10000038146973 | 8.30000019073486 | 8.5 | 9.80000019073486 | 7.80000019073486 | 7.80000019073486 | 8.60000038146973
Bulgaria | BGR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 38.5 | 28.8999996185303 | 44.7999992370605 | 42.0999984741211 | 33.2000007629395 | 28.7000007629395 | 29.2999992370605 | 26.2999992370605 | 30.6000003814697 | 36 | 42.4000015258789 | 38.7999992370605 | 29.2000007629395 | 24.7999992370605 | 23.2000007629395 | 18.7000007629395 | 14.3999996185303 | 13.6000003814697 | 17.6000003814697 | 24 | 26.1000003814697 | 29.6000003814697
Bahrain | BHR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.8999996185303 | 22.2999992370605 | 21.2000007629395 | 20.2000007629395 | 17.7999992370605 | 17.6000003814697 | 19.2000007629395 | 18.3999996185303 | 17.2000007629395 | 19.2999992370605 | 16.7000007629395 | 18.8999996185303 | 21 | 24.8999996185303 | 24.8999996185303 | 24.8999996185303 | 24.7999992370605 | 24.7999992370605 | 24.7999992370605 | 24.7000007629395 | 24.7000007629395 | 25.3999996185303
Bahamas, The | BHS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.1000003814697 | 23.6000003814697 | 21.1000003814697 | 21.7999992370605 | 18.3999996185303 | 18.7999992370605 | 16.7000007629395 | 10 | 10.3000001907349 | 11.1000003814697 | 13.8999996185303 | 17.3999996185303 | 20.5 | 20 | 16.7999992370605 | 13.1999998092651 | 16.6000003814697 | 16.2000007629395 | 26.3999996185303 | 26.2000007629395 | 25.6000003814697 | 24.7000007629395
Bosnia and Herzegovina | BIH | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 44.2000007629395 | 45.5 | 52.5 | 53.7999992370605 | 48.5999984741211 | 49.7999992370605 | 56.7000007629395 | 51.9000015258789 | 50.4000015258789 | 48.9000015258789 | 53.7999992370605 | 47.5 | 50.2999992370605 | 56.5999984741211 | 50.2999992370605 | 60.5 | 55.9000015258789 | 44.9000015258789 | 46.5 | 54.5999984741211 | 55.9000015258789 | 56.0999984741211
Belarus | BLR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.2000007629395 | 18.8999996185303 | 19 | 18.8999996185303 | 18.8999996185303 | 19.7000007629395 | 20.2000007629395 | 20 | 19.7000007629395 | 19.8999996185303 | 19.7999992370605 | 19.7999992370605 | 19.8999996185303 | 20.2000007629395 | 20.1000003814697 | 20.1000003814697 | 20 | 20.1000003814697 | 19.6000003814697 | 20 | 19.8999996185303 | 19.6000003814697
Belize | BLZ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.3999996185303 | 14.6000003814697 | 13.3000001907349 | 15.8000001907349 | 19.3999996185303 | 21.7999992370605 | 17.7000007629395 | 19.3999996185303 | 15.6000003814697 | 14.8999996185303 | 12.3000001907349 | 13.5 | 13.8000001907349 | 14.1000003814697 | 13.6999998092651 | 12.6000003814697 | 11.3999996185303 | 11.1000003814697 | 11.8999996185303 | 11.3000001907349 | 11.5 | 10.8999996185303
Bermuda | BMU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Bolivia | BOL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 7.5 | 6.59999990463257 | 7.30000019073486 | 7.30000019073486 | 7.09999990463257 | 6.90000009536743 | 6.69999980926514 | 6 | 6.69999980926514 | 7.69999980926514 | 7.40000009536743 | 7.09999990463257 | 6 | 7.5 | 7.40000009536743 | 7.30000019073486 | 4 | 4.69999980926514 | 4.59999990463257 | 4.5 | 4.5
Brazil | BRA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.1000003814697 | 9.89999961853027 | 9.69999980926514 | 9.69999980926514 | 9.69999980926514 | 10.3000001907349 | 11.6999998092651 | 13.8000001907349 | 15 | 14.8999996185303 | 14.6000003814697 | 14.6000003814697 | 15.1000003814697 | 14.1999998092651 | 15.3000001907349 | 13.8000001907349 | 12.8999996185303 | 11.8000001907349 | 13.8000001907349 | 13.3999996185303 | 12 | 12.3000001907349
Barbados | BRB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.2000007629395 | 36.4000015258789 | 40.2000007629395 | 35.5 | 33.9000015258789 | 25 | 26.1000003814697 | 20.3999996185303 | 18.2000007629395 | 17.8999996185303 | 20.6000003814697 | 21.3999996185303 | 23.8999996185303 | 19.8999996185303 | 18.5 | 17.7000007629395 | 15.1000003814697 | 16.6000003814697 | 20.5 | 22.1000003814697 | 23 | 23.7000007629395
[NAME] | BRN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 10.6999998092651 | 9.30000019073486 | 12.3000001907349 | 11.6000003814697 | 10.8999996185303 | 9.10000038146973 | 9.19999980926514 | 11.6999998092651 | 10.6999998092651 | 10.1999998092651 | 10.6000003814697 | 11 | 9.30000019073486 | 9.30000019073486 | 9.30000019073486 | 9.19999980926514 | 9.10000038146973 | 9.89999961853027 | 10.3999996185303 | 10.5 | 10.6000003814697
Bhutan | BTN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 5.09999990463257 | 5.5 | 5.80000019073486 | 6.80000019073486 | 3.70000004768372 | 3.90000009536743 | 3.40000009536743 | 3.40000009536743 | 4 | 4.5 | 4.40000009536743 | 4.19999980926514 | 5.90000009536743 | 5.59999990463257 | 8 | 9.69999980926514 | 10.1000003814697 | 11 | 6.59999990463257 | 6.40000009536743 | 6.40000009536743
Botswana | BWA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 37.2000007629395 | 31.2000007629395 | 33.0999984741211 | 36.2999992370605 | 35.4000015258789 | 31.7000007629395 | 26.8999996185303 | 13.6000003814697 | 37 | 36.4000015258789 | 34.4000015258789 | 32 | 35.5 | 34.2999992370605 | 33 | 26.3999996185303 | 19 | 32.7999992370605 | 17.7000007629395 | 26.8999996185303 | 26.8999996185303 | 26.3999996185303
Sub-Saharan Africa (IFC classification) | CAA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Central African Republic | CAF | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3000001907349 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303
Canada | CAN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.5 | 19.7000007629395 | 19.7000007629395 | 17.8999996185303 | 16.2999992370605 | 16.8999996185303 | 17.1000003814697 | 16.5 | 15.3000001907349 | 13.8000001907349 | 14.5 | 15.3999996185303 | 15.3000001907349 | 14.8999996185303 | 14.1999998092651 | 12.8999996185303 | 12.3000001907349 | 13 | 17.8999996185303 | 17.1000003814697 | 15.8999996185303 | 15.8999996185303
East Asia and the Pacific (IFC classification) | CEA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Central Europe and the Baltics | CEB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.52056140842139 | 21.70550084525819 | 24.62458868703088 | 25.51699930964155 | 23.27274383700063 | 21.25921453458525 | 19.46087358127578 | 20.08210298311522 | 24.2193892615613 | 26.95210066051013 | 30.06856002695494 | 31.01824151752469 | 29.118130815533 | 29.47935375526464 | 27.33454008862618 | 22.95957417952871 | 17.95194646656668 | 15.70856074748845 | 21.97615913088761 | 24.42326293170616 | 24.88507163040416 | 25.62026792825793
Europe and Central Asia (IFC classification) | CEU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Switzerland | CHE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 5 | 7.09999990463257 | 5.40000009536743 | 5.69999980926514 | 5.09999990463257 | 7.90000009536743 | 4.40000009536743 | 5.59999990463257 | 5.69999980926514 | 5.5 | 7.19999980926514 | 8.30000019073486 | 8 | 8.39999961853027 | 7.90000009536743 | 6.80000019073486 | 6.69999980926514 | 7.90000009536743 | 7.19999980926514 | 7.59999990463257 | 8.80000019073486
Channel Islands | CHI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Chile | CHL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.1000003814697 | 17.3999996185303 | 16.7999992370605 | 16.2999992370605 | 14.8000001907349 | 13.5 | 12.8000001907349 | 13.6999998092651 | 20.2000007629395 | 19.5 | 19.8999996185303 | 20.3999996185303 | 19.1000003814697 | 18.7999992370605 | 17.3999996185303 | 16.3999996185303 | 16.1000003814697 | 17.7999992370605 | 21.5 | 16.6000003814697 | 15.1999998092651 | 14.3999996185303
China | CHN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6000003814697 | 9.60000038146973 | 9.60000038146973 | 9.80000019073486 | 10.3999996185303 | 10.6000003814697 | 10.8000001907349 | 11.1999998092651 | 11.3000001907349 | 11 | 11 | 10.6999998092651 | 10.3999996185303 | 10.3999996185303 | 10.1000003814697 | 9.69999980926514 | 9.19999980926514 | 10.6000003814697 | 10.8000001907349 | 10.3999996185303 | 10.8000001907349 | 11.3000001907349
Cote d'Ivoire | CIV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 10.5 | 9.5 | 8.39999961853027 | 6.5 | 6.5 | 6.5 | 6.5 | 6.5 | 6.40000009536743 | 6.5 | 6.5 | 6.40000009536743 | 6.5 | 6.5 | 6.5 | 6.5 | 6.5 | 6.5 | 6.5 | 6.40000009536743 | 6.59999990463257
Latin America and the Caribbean (IFC classification) | CLA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Middle East and North Africa (IFC classification) | CME | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Cameroon | CMR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.30000019073486 | 9.30000019073486 | 9.30000019073486 | 9.30000019073486 | 5.90000009536743 | 14 | 13.3999996185303 | 12.6999998092651 | 12.1000003814697 | 10.3000001907349 | 12.8999996185303 | 9.39999961853027 | 9.5 | 7.69999980926514 | 7.5 | 6.5 | 6.90000009536743 | 7.80000019073486 | 8.10000038146973 | 6.59999990463257 | 6.59999990463257 | 6.5
Congo, Rep. | COG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.5
Colombia | COL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.2999992370605 | 15.6999998092651 | 16.7000007629395 | 17.5 | 17.8999996185303 | 19.2999992370605 | 19 | 20.2000007629395 | 21.5 | 22.8999996185303 | 19.6000003814697 | 19.8999996185303 | 16.6000003814697 | 18.3999996185303 | 18.6000003814697 | 17.2000007629395 | 19.5 | 21.5 | 17.7999992370605 | 17.2000007629395 | 16.1000003814697 | 14.6999998092651
Comoros | COM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 12.5 | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303
Cabo Verde | CPV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.5 | 12.5 | 12.5
Costa Rica | CRI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.3999996185303 | 7.09999990463257 | 7.90000009536743 | 7 | 10.8000001907349 | 10.3000001907349 | 9.89999961853027 | 9.30000019073486 | 11.3000001907349 | 9.39999961853027 | 12.3000001907349 | 12.3999996185303 | 13.3999996185303 | 12.3000001907349 | 11.3999996185303 | 11 | 8.60000038146973 | 9.80000019073486 | 15.5 | 14.3999996185303 | 13.8999996185303 | 13.5
South Asia (IFC classification) | CSA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Caribbean small states | CSS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.41714089739974 | 23.24831365528842 | 25.10472918003585 | 24.87298756511869 | 28.99292185648869 | 26.34418711141305 | 25.70055882416022 | 26.01946156699772 | 24.93066090261624 | 23.35105949907426 | 24.46100816514721 | 23.72630212254487 | 20.94590018303641 | 22.02482010737358 | 21.02198432445666 | 18.40336122842891 | 17.29456566204368 | 18.39091419926259 | 20.55216405525079 | 22.49515980001548 | 22.83363530793651 | 24.20582244848931
Cuba | CUB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 7 | 7.5 | 6.30000019073486 | 15.5 | 14.3999996185303 | 13.6000003814697 | 12 | 12.3999996185303 | 10.6999998092651 | 8.19999980926514 | 6.59999990463257 | 4.59999990463257 | 4 | 3.79999995231628 | 3.5 | 4.19999980926514 | 3.20000004768372 | 3.29999995231628 | 4.80000019073486 | 4.69999980926514 | 4.90000009536743
[NAME] | CUW | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Cayman Islands | CYM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Cyprus | CYP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.6000003814697 | 4.5 | 21 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.5 | 6.69999980926514 | 12.3999996185303 | 6.30000019073486 | 5.59999990463257 | 7.5 | 8.30000019073486 | 7.80000019073486 | 12.3999996185303 | 8.5 | 10.1999998092651 | 8.10000038146973 | 12.8000001907349 | 15.3000001907349 | 22.2000007629395 | 27.7999992370605
Czech Republic | CZE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 6.09999990463257 | 6.90000009536743 | 7.80000019073486 | 7.19999980926514 | 6.40000009536743 | 7.5 | 10.8000001907349 | 15.8999996185303 | 16.6000003814697 | 16 | 15 | 16.6000003814697 | 21.1000003814697 | 19.3999996185303 | 16.6000003814697 | 10.6000003814697 | 9.89999961853027 | 16.6000003814697 | 18.2000007629395 | 18 | 19.7999992370605
Germany | DEU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.90000009536743 | 5.69999980926514 | 7.40000009536743 | 8.19999980926514 | 8.30000019073486 | 9.60000038146973 | 10.6999998092651 | 9.69999980926514 | 9.30000019073486 | 9.19999980926514 | 9.30000019073486 | 11.3999996185303 | 12.3000001907349 | 14.1000003814697 | 16.1000003814697 | 14.3000001907349 | 12.1999998092651 | 10.6000003814697 | 12 | 10.3999996185303 | 9.10000038146973 | 8.80000019073486
Djibouti | DJI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Dominica | DMA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Denmark | DNK | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6999998092651 | 12.1000003814697 | 14.3999996185303 | 10.1999998092651 | 7.80000019073486 | 9 | 6.59999990463257 | 6.69999980926514 | 9.39999961853027 | 6.5 | 7.30000019073486 | 7.30000019073486 | 9.19999980926514 | 8.89999961853027 | 8.60000038146973 | 7.90000009536743 | 7.59999990463257 | 7.40000009536743 | 13.1999998092651 | 16.1000003814697 | 15.6999998092651 | 14.6999998092651
Dominican Republic | DOM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 26.1000003814697 | 26.6000003814697 | 26.8999996185303 | 22.5 | 21 | 21 | 19.6000003814697 | 18.6000003814697 | 17.8999996185303 | 16.2999992370605 | 17.5 | 17.5 | 21.8999996185303 | 24.1000003814697 | 23.5 | 21.3999996185303 | 21.2000007629395 | 19.8999996185303 | 21.7000007629395 | 18.7999992370605 | 19.6000003814697 | 19.2000007629395
Algeria | DZA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 35.9000015258789 | 39.7000007629395 | 39.7000007629395 | 41.4000015258789 | 45 | 44.2999992370605 | 42.7999992370605 | 43.7000007629395 | 42.0999984741211 | 48.2000007629395 | 43.0999984741211 | 42.0999984741211 | 39.7000007629395 | 40.2999992370605 | 28.1000003814697 | 21.8999996185303 | 25.2000007629395 | 21.8999996185303 | 19.2999992370605 | 19.1000003814697 | 19.1000003814697 | 18.7999992370605
East Asia & Pacific (developing only) | EAP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.94266591715478 | 9.125360924234203 | 9.73375951224377 | 10.01209083363098 | 10.02651997706407 | 10.29410407117676 | 10.64021052006317 | 11.679134028912 | 11.79595493262077 | 11.87048589819094 | 12.13645937528273 | 12.41548660737659 | 12.01893704525116 | 12.19329594606832 | 12.0180331354208 | 11.68350864292916 | 10.83418955288161 | 11.58760758012843 | 11.75417223424952 | 11.2116944077257 | 11.25357276538087 | 11.70028059209446
East Asia & Pacific (all income levels) | EAS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.62925597094639 | 8.97149875865309 | 9.585975381395102 | 9.794946868961288 | 9.789576736125769 | 10.08390614138281 | 10.43371094527435 | 11.73559022309541 | 11.87831909485306 | 11.84515885246432 | 12.10014625552722 | 12.35148468424063 | 12.01644868426903 | 12.12716247585123 | 11.92920903813471 | 11.56183207378397 | 10.73465514761153 | 11.42631142190209 | 11.71955686698729 | 11.1993453639771 | 11.19692737152534 | 11.56314167770638
Europe & Central Asia (developing only) | ECA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.31133772347879 | 19.4605441925587 | 20.98266022930867 | 19.28388475763925 | 18.18259679281671 | 18.19265722030061 | 18.32360995287278 | 19.50693924707994 | 20.13413430715772 | 19.37658787153793 | 20.19664274669126 | 21.11773574711242 | 20.73658078085358 | 20.63537072068877 | 19.93587774783324 | 19.28420442975121 | 19.23318581597304 | 18.88582353380125 | 21.42779010403676 | 20.62022675237861 | 19.56565109565533 | 19.18109008336539
Europe & Central Asia (all income levels) | ECS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.9758277707324 | 17.25793284865579 | 19.71259338601791 | 20.07854852889874 | 19.44050967556236 | 19.59015616153354 | 20.05424893496986 | 20.53037864980703 | 20.15556827168815 | 18.90008999504061 | 18.51875272695319 | 18.7892915580522 | 19.13628858477573 | 19.02959126347488 | 18.46956938027198 | 17.70782334483548 | 16.52859575206355 | 16.28878604588867 | 20.67774777180269 | 20.56498977436345 | 20.11108197657317 | 21.12970028716567
Ecuador | ECU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3999996185303 | 11 | 9.19999980926514 | 12.6999998092651 | 9.30000019073486 | 10.1000003814697 | 11.8000001907349 | 8.60000038146973 | 10.3999996185303 | 12.5 | 14 | 14.3999996185303 | 16.2000007629395 | 11.6000003814697 | 11.6000003814697 | 11 | 9 | 10.8000001907349 | 11.8000001907349 | 9.10000038146973 | 7.69999980926514 | 8.30000019073486
Egypt, Arab Rep. | EGY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.6000003814697 | 17.2999992370605 | 21.2000007629395 | 21.2999992370605 | 21.8999996185303 | 17.7000007629395 | 16.7000007629395 | 16.2999992370605 | 14.1000003814697 | 17.2000007629395 | 19.3999996185303 | 21.7000007629395 | 21.6000003814697 | 21.8999996185303 | 22.7000007629395 | 20.8999996185303 | 17.2999992370605 | 15.8000001907349 | 15.1000003814697 | 14.8000001907349 | 23.6000003814697 | 23.7999992370605
Euro area | EMU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.24621831868836 | 16.485768390189 | 20.7414981056062 | 22.51629302259945 | 21.23780856537763 | 21.77444931068599 | 21.55396188376784 | 20.09917347531967 | 19.17753635437919 | 17.13914937421701 | 15.42868450719027 | 16.45490164669054 | 16.79969602436649 | 17.45655784681519 | 17.54579194605034 | 16.25379454868955 | 14.86455057808819 | 15.83394563682946 | 21.41569193232521 | 22.28190114288871 | 22.66097023623468 | 25.86602604518621
Eritrea | ERI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3999996185303 | 12.6000003814697 | 12.6999998092651 | 12.3999996185303 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.1999998092651 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5
Spain | ESP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.2000007629395 | 27.2000007629395 | 37.4000015258789 | 38.4000015258789 | 34.5999984741211 | 34.4000015258789 | 31.7000007629395 | 28.2000007629395 | 22.6000003814697 | 20.2999992370605 | 16.6000003814697 | 18.8999996185303 | 19.8999996185303 | 19.2999992370605 | 17.2000007629395 | 15.3999996185303 | 15.6999998092651 | 24.5 | 39.5999984741211 | 43.7999992370605 | 49 | 55.5
Estonia | EST | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.79999995231628 | 7 | 12.5 | 14.3999996185303 | 14.1000003814697 | 17.2999992370605 | 20.7999992370605 | 17.1000003814697 | 22.2999992370605 | 24.6000003814697 | 17.2999992370605 | 14.3000001907349 | 20.5 | 23.5 | 16.6000003814697 | 10 | 12.1999998092651 | 12.6000003814697 | 31.8999996185303 | 35.5999984741211 | 23.8999996185303 | 23.5
Ethiopia | ETH | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.30000019073486 | 5.40000009536743 | 5.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.40000009536743 | 6.19999980926514 | 5.90000009536743 | 5.40000009536743 | 5 | 4.5 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514
European Union | EUU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.62296915860785 | 17.99486066611222 | 21.71158174350493 | 22.83025345131455 | 21.27541385421815 | 21.21422057040795 | 20.28515174659192 | 19.19572643240184 | 19.59261767486396 | 18.81729878539599 | 18.40232111250969 | 19.41584629319235 | 19.25980343796914 | 19.57815564575685 | 19.42916999872824 | 17.8207999471276 | 15.75600123193756 | 15.876034686528 | 21.47263270731177 | 22.45408552990235 | 22.90082667202468 | 25.33194995628575
Fragile and conflict affected situations | FCS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.49276680682098 | 15.52707173356182 | 14.94433436583613 | 15.17969471358815 | 14.9707448704134 | 15.27490724428299 | 15.5317274056131 | 15.38486164989704 | 14.54643711583972 | 14.94824746480074 | 15.38281035611818 | 15.67757980828366 | 16.56284885827844 | 16.22120574774307 | 15.03368099744317 | 15.05778105626651 | 14.97766945204813 | 15.12291270026477 | 14.74220512849376 | 15.44911254140104 | 15.33364920539692 | 15.39827552819044
Finland | FIN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.3999996185303 | 26 | 31.1000003814697 | 31.5 | 25.7999992370605 | 24.2999992370605 | 22 | 20.1000003814697 | 18.7000007629395 | 19 | 17.3999996185303 | 18.5 | 19.3999996185303 | 19.5 | 18.3999996185303 | 17 | 14.8000001907349 | 15.3000001907349 | 22.1000003814697 | 21.6000003814697 | 19.3999996185303 | 17.6000003814697
Fiji | FJI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.6999998092651 | 9.80000019073486 | 10.8000001907349 | 10.3999996185303 | 9.89999961853027 | 11.1000003814697 | 12 | 15.1000003814697 | 14.3999996185303 | 13.8000001907349 | 11.1000003814697 | 10.6999998092651 | 15.8000001907349 | 8.80000019073486 | 8.69999980926514 | 12.3999996185303 | 15.6999998092651 | 17.2999992370605 | 16.7999992370605 | 16.5 | 16.2000007629395 | 16.2000007629395
France | FRA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.7999992370605 | 18.2999992370605 | 23.2000007629395 | 26.7999992370605 | 23.3999996185303 | 24.7999992370605 | 26.7000007629395 | 24 | 24.7000007629395 | 19 | 16 | 17.5 | 16.5 | 19.7000007629395 | 19.2999992370605 | 20.2000007629395 | 18.1000003814697 | 18.2999992370605 | 23.7999992370605 | 22 | 21 | 23.7999992370605
Faeroe Islands | FRO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Micronesia, Fed. [NAME]. | FSM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Gabon | GAB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.5 | 37.9000015258789 | 42.5 | 40.2999992370605 | 38.2000007629395 | 36.5999984741211 | 35 | 35.2999992370605 | 35.5 | 35.7000007629395 | 36 | 36.2000007629395 | 36.4000015258789 | 36.7000007629395 | 36.9000015258789 | 37.0999984741211 | 37.4000015258789 | 35.2000007629395 | 33.0999984741211 | 29.5 | 29.5 | 32.2999992370605
United Kingdom | GBR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.1000003814697 | 19.2999992370605 | 21.3999996185303 | 19.7000007629395 | 18.3999996185303 | 18.3999996185303 | 16.1000003814697 | 14.3000001907349 | 14.5 | 13.5 | 12.1999998092651 | 13.1999998092651 | 13.5 | 12 | 13.8000001907349 | 15.8999996185303 | 16 | 16.2999992370605 | 22 | 21.5 | 22.2000007629395 | 24.1000003814697
Georgia | GEO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27 | 24.2999992370605 | 24.2999992370605 | 23.8999996185303 | 28.2000007629395 | 24.5 | 23.8999996185303 | 24.7000007629395 | 24 | 21.3999996185303 | 20.2000007629395 | 27.8999996185303 | 19.7999992370605 | 24.7000007629395 | 26.5 | 28.2000007629395 | 27.7999992370605 | 32.7000007629395 | 36 | 34.0999984741211 | 33.9000015258789 | 32.9000015258789
Ghana | GHA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 13.1000003814697 | 12.1000003814697 | 8.39999961853027 | 5.59999990463257 | 12.8999996185303 | 12.5 | 12.3999996185303 | 12.8000001907349 | 16.2000007629395 | 13.8000001907349 | 12.8000001907349 | 13.1999998092651 | 13.6000003814697 | 7.19999980926514 | 5.80000019073486 | 5.80000019073486 | 5.80000019073486 | 5.80000019073486 | 5.80000019073486 | 5.90000009536743 | 6
Guinea | GIN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.09999990463257 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.19999980926514 | 5.09999990463257 | 5.19999980926514 | 5.19999980926514 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.09999990463257 | 5.19999980926514 | 5.09999990463257 | 5.09999990463257 | 5.19999980926514 | 5.09999990463257
Gambia, The | GMB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3000001907349 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.3000001907349 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.3000001907349 | 12.5
Guinea-Bissau | GNB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303
Equatorial Guinea | GNQ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.8999996185303 | 12.5 | 12.6000003814697 | 12.6000003814697 | 13.3000001907349 | 14.5 | 12.6999998092651 | 12.6999998092651 | 12.6000003814697 | 13.3000001907349 | 12.6000003814697 | 12.6000003814697 | 12.8999996185303 | 12.5 | 12.3999996185303 | 12.6000003814697 | 12.6000003814697 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.5
Greece | GRC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.5 | 16.7999992370605 | 19.7999992370605 | 19.3999996185303 | 18.8999996185303 | 21 | 21.7000007629395 | 21.1000003814697 | 22.7000007629395 | 21.8999996185303 | 20.8999996185303 | 19.7000007629395 | 18.7000007629395 | 18.8999996185303 | 18.6000003814697 | 17.5 | 15.6000003814697 | 16.7999992370605 | 19.2000007629395 | 26.5 | 38.2000007629395 | 48.0999984741211
Grenada | GRD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Greenland | GRL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Guatemala | GTM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6 | 3.79999995231628 | 3.59999990463257 | 6.5 | 5 | 7 | 6.09999990463257 | 3 | 2.20000004768372 | 2 | 4.90000009536743 | 4.40000009536743 | 4.90000009536743 | 4.59999990463257 | 4.30000019073486 | 3.90000009536743 | 4.30000019073486 | 4.80000019073486 | 5.5 | 6.40000009536743 | 6.5
Guam | GUM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Guyana | GUY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 38.4000015258789 | 21.2000007629395 | 28.2999992370605 | 36.5999984741211 | 45.7999992370605 | 41.7999992370605 | 37.9000015258789 | 43.5999984741211 | 39.5 | 31.3999996185303 | 42 | 43.2000007629395 | 41.9000015258789 | 44.0999984741211 | 46.2999992370605 | 40.2000007629395 | 32.7000007629395 | 33.7999992370605 | 32.7000007629395 | 34.4000015258789 | 39.2000007629395 | 39.7000007629395
High income | HIC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.01202551576896 | 14.67068514952425 | 16.03831855652113 | 16.31477696342207 | 15.81118057902765 | 16.06774718554009 | 16.28132821976952 | 16.92424646703314 | 16.3836061442292 | 15.22503912045911 | 15.18878411405586 | 15.5901123021283 | 16.11722505949854 | 15.68432592452423 | 15.31841228918205 | 14.56685052794119 | 13.51352582466672 | 14.09737921298876 | 18.67969125103368 | 18.83996001390434 | 17.89295162251315 | 18.40124136291196
Hong Kong SAR, China | HKG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.59999990463257 | 4.80000019073486 | 4.90000009536743 | 5.09999990463257 | 7.69999980926514 | 7.59999990463257 | 5.69999980926514 | 12.1999998092651 | 15.6999998092651 | 11.8999996185303 | 13.6000003814697 | 18.1000003814697 | 18.2000007629395 | 15 | 13.6999998092651 | 13 | 11 | 10.5 | 15.1000003814697 | 14.1000003814697 | 11.1000003814697 | 10.6999998092651
Honduras | HND | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.5 | 4.40000009536743 | 4.40000009536743 | 4.5 | 4.40000009536743 | 6 | 4.5 | 5.40000009536743 | 7.09999990463257 | 6.69999980926514 | 6 | 4.90000009536743 | 6.09999990463257 | 7.80000019073486 | 5.30000019073486 | 4.19999980926514 | 4 | 4.19999980926514 | 4.5 | 6.59999990463257 | 6.59999990463257 | 6.69999980926514
Heavily indebted poor countries (HIPC) | HPC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.46895414193971 | 10.4798133458073 | 10.48917657550146 | 10.34848417391575 | 10.14800782141914 | 10.63377554201247 | 10.4340131928344 | 10.35973977835457 | 10.19013810789383 | 10.32624434980966 | 10.52712634355528 | 10.16553867318551 | 10.24142960795558 | 9.927911361684895 | 9.47175719715244 | 9.615563832876092 | 9.373845028890807 | 9.525386809740624 | 9.68261218530276 | 9.788792146150934 | 9.783496584640233 | 9.738727310888127
Croatia | HRV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 41.5999984741211 | 24.3999996185303 | 22.2999992370605 | 21.1000003814697 | 22.7000007629395 | 23.8999996185303 | 23.6000003814697 | 31.2999992370605 | 35.5 | 39.9000015258789 | 46.7000007629395 | 34.2999992370605 | 33.7999992370605 | 29.3999996185303 | 30.2999992370605 | 27.2999992370605 | 21 | 18.7000007629395 | 23.5 | 31.7999992370605 | 36.4000015258789 | 43.2999992370605
Haiti | HTI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.5 | 21.5 | 22.2999992370605 | 24.2999992370605 | 18.2999992370605 | 19.7999992370605 | 20.2000007629395 | 20.2999992370605 | 14.6999998092651 | 15.1999998092651 | 15.6999998092651 | 15.5 | 15.3000001907349 | 16.3999996185303 | 14.8999996185303 | 14.8000001907349 | 14.5 | 15.1999998092651 | 14.6000003814697 | 17 | 13.8999996185303 | 14.8000001907349
Hungary | HUN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.1000003814697 | 21.7999992370605 | 26.6000003814697 | 24.3999996185303 | 20.7000007629395 | 19 | 17 | 15.6999998092651 | 13.8999996185303 | 13.6999998092651 | 12.1000003814697 | 13.1000003814697 | 13.6999998092651 | 16.2000007629395 | 19.6000003814697 | 18.6000003814697 | 17.7000007629395 | 19.1000003814697 | 28.1000003814697 | 27.7999992370605 | 27.1000003814697 | 28.7000007629395
Indonesia | IDN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17 | 8.10000038146973 | 12.8999996185303 | 14.8000001907349 | 11.8999996185303 | 13.3999996185303 | 13.8000001907349 | 16.6000003814697 | 16.7999992370605 | 18 | 20.8999996185303 | 24.3999996185303 | 24.2000007629395 | 26.1000003814697 | 29.1000003814697 | 28.2000007629395 | 24.2000007629395 | 22 | 21.8999996185303 | 20.7999992370605 | 19.5 | 20
Isle of Man | IMN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
India | IND | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9 | 9.10000038146973 | 9.60000038146973 | 8.30000019073486 | 9 | 9 | 10.1000003814697 | 8.60000038146973 | 8.80000019073486 | 9.89999961853027 | 9.10000038146973 | 9.69999980926514 | 9.39999961853027 | 9 | 9.80000019073486 | 9.80000019073486 | 9.19999980926514 | 10 | 9.69999980926514 | 9.80000019073486 | 9.80000019073486 | 9.39999961853027
Not classified | INX | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Ireland | IRL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.7999992370605 | 24.2999992370605 | 27 | 25.1000003814697 | 20.2999992370605 | 19.1000003814697 | 16.7999992370605 | 11.8000001907349 | 8.69999980926514 | 6.19999980926514 | 6.5 | 8.80000019073486 | 9 | 8.89999961853027 | 9.10000038146973 | 9 | 9.89999961853027 | 15.5 | 31.2999992370605 | 34.0999984741211 | 35.2000007629395 | 36.4000015258789
Iran, Islamic Rep. | IRN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.6000003814697 | 21.7000007629395 | 21.2999992370605 | 20.8999996185303 | 20.6000003814697 | 20.6000003814697 | 20.5 | 20.6000003814697 | 20.5 | 23.5 | 21.3999996185303 | 22.8999996185303 | 21.7000007629395 | 18.2999992370605 | 20.8999996185303 | 20.6000003814697 | 19.7999992370605 | 20.1000003814697 | 22.3999996185303 | 25.2000007629395 | 25.1000003814697 | 25.7999992370605
Iraq | IRQ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.7999992370605 | 33.4000015258789 | 29 | 30.6000003814697 | 32.2000007629395 | 33.9000015258789 | 33.7999992370605 | 33.7999992370605 | 32.2000007629395 | 32.7000007629395 | 33.2999992370605 | 33.2999992370605 | 51.5 | 49.4000015258789 | 33.2999992370605 | 32.5 | 31.5 | 28.7000007629395 | 28.6000003814697 | 28.6000003814697 | 28.7000007629395 | 28.6000003814697
Iceland | ISL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.80000019073486 | 8.89999961853027 | 10.1000003814697 | 12.8999996185303 | 13.1000003814697 | 9.19999980926514 | 8.30000019073486 | 6.40000009536743 | 4.40000009536743 | 5.69999980926514 | 5.30000019073486 | 9.69999980926514 | 9.30000019073486 | 9.19999980926514 | 8.30000019073486 | 8.89999961853027 | 7.69999980926514 | 8.80000019073486 | 19.7000007629395 | 18.2000007629395 | 18.3999996185303 | 14.6000003814697
Israel | ISR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.2000007629395 | 21.2000007629395 | 18.6000003814697 | 14.5 | 12.8000001907349 | 12.1000003814697 | 13.8999996185303 | 16.5 | 16.1000003814697 | 17 | 18.6000003814697 | 20.8999996185303 | 22.1000003814697 | 19.7000007629395 | 16.8999996185303 | 17.2999992370605 | 15.1000003814697 | 11.8999996185303 | 15.6999998092651 | 14.6000003814697 | 11.8999996185303 | 11.6000003814697
Italy | ITA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24 | 24.2000007629395 | 26.1000003814697 | 28.5 | 29.6000003814697 | 30.7000007629395 | 29.7000007629395 | 30.2000007629395 | 28.6000003814697 | 28.3999996185303 | 24.7999992370605 | 23.7000007629395 | 23.8999996185303 | 21.2000007629395 | 21.5 | 19.1000003814697 | 18.2999992370605 | 18.8999996185303 | 23.2999992370605 | 26.7999992370605 | 27.1000003814697 | 33.7000007629395
Jamaica | JAM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.5 | 17.8999996185303 | 21.3999996185303 | 19.2999992370605 | 26.2999992370605 | 24.8999996185303 | 25.6000003814697 | 25.7000007629395 | 25.7000007629395 | 25.2999992370605 | 26.5 | 24.3999996185303 | 17.7000007629395 | 22.2999992370605 | 19.8999996185303 | 17.6000003814697 | 17.2999992370605 | 19.5 | 22.1000003814697 | 24.7999992370605 | 23.6000003814697 | 26.5
Jordan | JOR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 29.7999992370605 | 32.9000015258789 | 36.0999984741211 | 33.7999992370605 | 27.1000003814697 | 25.5 | 24.3999996185303 | 25.7000007629395 | 24.7000007629395 | 25.6000003814697 | 31.2000007629395 | 32.5 | 31.5 | 26.1000003814697 | 28.7999992370605 | 26.5 | 24.3999996185303 | 23.6000003814697 | 23.7000007629395 | 25.1000003814697 | 27.2999992370605 | 26.3999996185303
Japan | JPN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.69999980926514 | 4.59999990463257 | 4.90000009536743 | 5.59999990463257 | 6.09999990463257 | 6.80000019073486 | 6.90000009536743 | 8.19999980926514 | 10.3000001907349 | 10.5 | 10.6999998092651 | 11.3999996185303 | 11.6000003814697 | 10.6000003814697 | 9.89999961853027 | 8.80000019073486 | 8.30000019073486 | 7.90000009536743 | 10.1000003814697 | 10.3999996185303 | 8.89999961853027 | 8.69999980926514
Kazakhstan | KAZ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1000003814697 | 11.8999996185303 | 11.6999998092651 | 7.69999980926514 | 11.3000001907349 | 13.3999996185303 | 13.3000001907349 | 13.3999996185303 | 13.8000001907349 | 13.1000003814697 | 10.6000003814697 | 15 | 12.8000001907349 | 12.8999996185303 | 8.30000019073486 | 8 | 7.5 | 6.80000019073486 | 5.5 | 5.5 | 4.80000019073486 | 3.79999995231628
Kenya | [NAME] | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.8999996185303 | 16.7999992370605 | 16.7999992370605 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.7999992370605 | 16.8999996185303 | 16.8999996185303 | 16.7999992370605 | 16.8999996185303 | 16.7999992370605 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.7999992370605 | 16.7999992370605 | 16.8999996185303 | 16.8999996185303 | 16.7999992370605
Kyrgyz Republic | KGZ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15 | 13.8999996185303 | 13.3999996185303 | 12.1000003814697 | 13.6999998092651 | 13.8999996185303 | 14.1000003814697 | 15.5 | 13.6999998092651 | 12.3000001907349 | 12.8000001907349 | 19.2000007629395 | 15.3999996185303 | 13.5 | 13.3000001907349 | 13.6000003814697 | 13.8000001907349 | 14.1000003814697 | 15.3000001907349 | 14.3999996185303 | 13.3000001907349 | 13.1000003814697
Cambodia | KHM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4 | 4.09999990463257 | 4.30000019073486 | 3.20000004768372 | 3.5 | 3.79999995231628 | 4.19999980926514 | 4.5 | 4.90000009536743 | 5.30000019073486 | 3.5 | 3.70000004768372 | 3.5 | 3.40000009536743 | 3.20000004768372 | 3.40000009536743 | 3.40000009536743 | 3.59999990463257 | 4.09999990463257 | 3.59999990463257 | 3.5 | 3.5
Kiribati | KIR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
St. Kitts and Nevis | KNA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Korea, Rep. | KOR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.10000038146973 | 8.80000019073486 | 11.1999998092651 | 8.69999980926514 | 7.40000009536743 | 7.69999980926514 | 8.69999980926514 | 19.7999992370605 | 16.8999996185303 | 13.1000003814697 | 12.3999996185303 | 10.1000003814697 | 11.5 | 11.8999996185303 | 11.8999996185303 | 11.3000001907349 | 11 | 11.1000003814697 | 11.6000003814697 | 11 | 11.8000001907349 | 9.60000038146973
Kosovo | KSV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Kuwait | KWT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 6.69999980926514 | 5.30000019073486 | 4.80000019073486 | 5.19999980926514 | 4.90000009536743 | 4.90000009536743 | 4.80000019073486 | 4.69999980926514 | 5.40000009536743 | 5.40000009536743 | 7.5 | 9 | 12 | 12.6999998092651 | 11 | 11.1000003814697 | 10.8999996185303 | 11 | 11 | 10.8000001907349 | 10.6999998092651
Latin America & Caribbean (developing only) | LAC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.02081501382761 | 9.964265924517822 | 10.20591428146383 | 10.71882843785877 | 12.23937980810006 | 12.31044013475983 | 11.7861107550514 | 12.41900738736862 | 12.68574126939471 | 13.18948121698384 | 13.03148776510864 | 13.79463495508839 | 13.97942842530421 | 13.17289176193413 | 13.00909858705056 | 11.85501122541235 | 11.35891663480708 | 11.08113998651395 | 12.57154753274109 | 12.16243830265549 | 11.56835931158904 | 11.39973948838822
Lao PDR | LAO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.30000019073486 | 6.90000009536743 | 7.09999990463257 | 7.19999980926514 | 7.40000009536743 | 5.59999990463257 | 5.80000019073486 | 5.69999980926514 | 5.59999990463257 | 5.59999990463257 | 5.5 | 5.40000009536743 | 6.19999980926514 | 7.19999980926514 | 4.09999990463257 | 4 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4 | 4.09999990463257 | 4
Lebanon | LBN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.7000007629395 | 21.3999996185303 | 21.2000007629395 | 22.2999992370605 | 21.2000007629395 | 21.3999996185303 | 21.3999996185303 | 21.3999996185303 | 21.5 | 21.5 | 21.3999996185303 | 21.5 | 21.6000003814697 | 21.2000007629395 | 21.3999996185303 | 21.7000007629395 | 23.1000003814697 | 23.1000003814697 | 23.1000003814697 | 23.1000003814697 | 23.1000003814697 | 23.2999992370605
Liberia | LBR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.69999980926514 | 4.59999990463257 | 4.69999980926514 | 3.59999990463257 | 5.30000019073486 | 5.69999980926514 | 5.09999990463257 | 4.5 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743
Libya | LBY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18 | 18.7999992370605
St. Lucia | LCA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Latin America & Caribbean (all income levels) | LCN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.44276189703837 | 10.45742383926864 | 10.65196957003736 | 11.09432663093755 | 12.49970624990588 | 12.52628962065966 | 11.99340521655819 | 12.61862628230863 | 13.01848324918758 | 13.46551541509515 | 13.31969309715451 | 14.0557821009512 | 14.20442065319395 | 13.41389598739889 | 13.23038842290726 | 12.09323521031886 | 11.60586709807053 | 11.38521509410834 | 12.95549394861515 | 12.44305291603414 | 11.8134973715859 | 11.620951284486
Latin America and the Caribbean | LCR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Least developed countries: UN classification | LDC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.13266291391831 | 10.28016756400999 | 10.21966960166042 | 10.26569889643403 | 10.24216261440843 | 10.07096358062649 | 10.31755910493649 | 10.02368460157618 | 10.01661966501812 | 10.37111380565002 | 10.39709861142564 | 10.10871392553264 | 9.620643086776035 | 9.504941800898488 | 9.419437338250919 | 9.898270617661934 | 9.764311236062538 | 10.00383174201972 | 10.33254054496537 | 10.18936879383005 | 10.19105766627565 | 10.31279788993062
Low income | LIC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.01931795838972 | 9.191604250413071 | 9.152182443083989 | 9.048850986155193 | 9.122283068225276 | 9.299992266325715 | 9.576578239733303 | 9.324704729364186 | 9.331771706018383 | 9.541513061618735 | 9.609595504681252 | 9.236652666874923 | 8.640518843907932 | 8.476070232357396 | 8.316531153943313 | 8.810842112192988 | 8.695706204122487 | 8.956500487274875 | 9.314991189933291 | 8.955703740278096 | 8.948222226907905 | 9.088115934393429
[NAME] | LIE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
[NAME] | LKA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.7999992370605 | 33.7000007629395 | 28.8999996185303 | 29 | 28 | 26.7000007629395 | 26.2999992370605 | 21.2000007629395 | 21.7999992370605 | 20.2000007629395 | 20.7999992370605 | 23.2999992370605 | 21.7999992370605 | 21.2999992370605 | 20.7000007629395 | 17.1000003814697 | 16.6000003814697 | 14 | 16.8999996185303 | 16 | 16 | 15.5
Lower middle income | LMC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.66185789620671 | 10.67434075218262 | 11.50124677248727 | 10.93150950898137 | 10.87545142066465 | 10.99464228003901 | 11.77551122698874 | 11.4254306182847 | 11.62832714125616 | 12.72051921204205 | 12.58348586738669 | 13.52961878010531 | 13.10381992799147 | 12.92651244759478 | 13.28343526550107 | 12.95198732515418 | 11.99225908360358 | 12.14951034944712 | 12.0194154620507 | 11.95073028199884 | 12.06587241103825 | 11.93301514342609
Low & middle income | LMY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.02690154758271 | 11.16648446840173 | 11.62918824109712 | 11.36057494344207 | 11.61962382242344 | 11.80612185091881 | 12.1889772754613 | 12.26925775229815 | 12.47675042724144 | 13.05402351412066 | 13.02027041774083 | 13.44474004186199 | 13.17389234607356 | 12.84815997369893 | 12.68550923950824 | 12.28840120410216 | 11.67746134373458 | 12.05476456365746 | 12.34809880216224 | 12.14016986181532 | 12.13995347017721 | 12.19130355929871
[NAME] | LSO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.9000015258789 | 35.7999992370605 | 37.7999992370605 | 36.9000015258789 | 31.6000003814697 | 27.7999992370605 | 38.4000015258789 | 32.4000015258789 | 26.1000003814697 | 36.4000015258789 | 36.0999984741211 | 32.2000007629395 | 38.0999984741211 | 35.5 | 36.0999984741211 | 32.2999992370605 | 26.2000007629395 | 29 | 29.5 | 27.1000003814697 | 28 | 29.8999996185303
Lithuania | LTU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.4000015258789 | 19.2999992370605 | 21.2999992370605 | 35.5999984741211 | 35 | 32 | 28.6000003814697 | 29.2000007629395 | 28.7999992370605 | 29.5 | 36.5 | 19.5 | 22.1000003814697 | 23.6000003814697 | 16 | 9.89999961853027 | 6.90000009536743 | 12.6000003814697 | 35.2000007629395 | 38.5 | 34.0999984741211 | 29.8999996185303
Luxembourg | LUX | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.79999995231628 | 4.59999990463257 | 5 | 8.5 | 6.80000019073486 | 10.1999998092651 | 5.59999990463257 | 5.80000019073486 | 6.19999980926514 | 5.69999980926514 | 7.09999990463257 | 5.30000019073486 | 9.69999980926514 | 12 | 11.6999998092651 | 17 | 13.5 | 12.5 | 16.6000003814697 | 17.5 | 13.3000001907349 | 18.7000007629395
Latvia | LVA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.5 | 22.7000007629395 | 21.8999996185303 | 25.6000003814697 | 22.1000003814697 | 20.8999996185303 | 25.3999996185303 | 27.6000003814697 | 26.2000007629395 | 20.8999996185303 | 24 | 25.1000003814697 | 13.8000001907349 | 14.8999996185303 | 11.8000001907349 | 10.6000003814697 | 11.3000001907349 | 13.3000001907349 | 37.7999992370605 | 35.7000007629395 | 31.2999992370605 | 27.6000003814697
Macao SAR, China | MAC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.30000019073486 | 4.09999990463257 | 4.19999980926514 | 6.19999980926514 | 7 | 8.30000019073486 | 9.80000019073486 | 13.3999996185303 | 15.5 | 14.1000003814697 | 15 | 16.2999992370605 | 18.3999996185303 | 14.3000001907349 | 10.8999996185303 | 8.5 | 8.69999980926514 | 7.69999980926514 | 9.80000019073486 | 7.5 | 7 | 4.59999990463257
St. Martin (French part) | MAF | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Morocco | MAR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.2999992370605 | 18 | 17.6000003814697 | 17.2000007629395 | 16.7999992370605 | 16.5 | 16.1000003814697 | 15.6999998092651 | 22 | 21.3999996185303 | 19.7000007629395 | 17.8999996185303 | 17.2999992370605 | 15.8000001907349 | 16.2000007629395 | 17.5 | 18.2000007629395 | 19.2000007629395 | 18.7000007629395 | 18.2999992370605 | 18 | 18
Mexico and Central America | MCA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Monaco | MCO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Moldova | MDA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.3000001907349 | 14.8000001907349 | 14.3000001907349 | 14.1000003814697 | 13.8000001907349 | 14.1000003814697 | 18.7999992370605 | 12.3999996185303 | 26.8999996185303 | 16.7000007629395 | 18.5 | 17.5 | 19 | 21.5 | 19.2000007629395 | 17.8999996185303 | 14.8999996185303 | 10.3000001907349 | 15.6999998092651 | 19.8999996185303 | 14.3000001907349 | 12.8999996185303
Madagascar | MDG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.40000009536743 | 4.59999990463257 | 3.5 | 4.5 | 4 | 3.40000009536743 | 2.20000004768372 | 2 | 2.09999990463257 | 1.70000004768372 | 4.5 | 5.40000009536743 | 6.59999990463257 | 4.09999990463257 | 1.70000004768372 | 4.19999980926514 | 4.59999990463257 | 5.09999990463257 | 5.40000009536743 | 5.80000019073486 | 5.80000019073486 | 5.40000009536743
Maldives | MDV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2000007629395 | 17.2000007629395 | 17.2000007629395 | 17.7000007629395 | 17.7000007629395 | 17.3999996185303 | 17.2000007629395 | 17.2999992370605 | 17.7000007629395 | 17.3999996185303 | 17.1000003814697 | 16.7999992370605 | 16.5 | 16.7999992370605 | 16.1000003814697 | 15.5 | 17.1000003814697 | 16.7999992370605 | 17.2999992370605 | 17.7000007629395 | 17.7000007629395 | 17.7000007629395
Middle East & North Africa (all income levels) | MEA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.83000259996536 | 23.31151194099713 | 23.5137371790535 | 23.78360432917027 | 24.10066343900381 | 23.2314233172259 | 22.90241133517751 | 22.8298612205363 | 22.30287783247008 | 24.67002836139096 | 24.18378116297368 | 25.35820153631556 | 25.53568657763335 | 24.16512110052999 | 22.73414338656697 | 21.80129757672983 | 20.78607793993537 | 20.16632735002219 | 19.87503275112659 | 20.87500580515622 | 22.1920241235645 | 22.55644400768452
Mexico | MEX | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 5 | 4.80000019073486 | 6.40000009536743 | 9.10000038146973 | 7.5 | 5.59999990463257 | 5.09999990463257 | 2.90000009536743 | 4.40000009536743 | 3.79999995231628 | 4.69999980926514 | 5 | 5.90000009536743 | 6.09999990463257 | 5.40000009536743 | 6.19999980926514 | 6.19999980926514 | 9.69999980926514 | 9 | 9.5 | 9.10000038146973
Marshall Islands | MHL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Middle income | MIC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.42886237450569 | 11.43649225833229 | 11.97601805141952 | 11.69194643510076 | 11.98556112920047 | 12.18087690258208 | 12.58695744085951 | 12.72522184513382 | 12.97028010990985 | 13.61075547543033 | 13.56448884513715 | 14.11875535438334 | 13.90178470089532 | 13.55219229813681 | 13.39238301970701 | 12.85484195028782 | 12.16741851393749 | 12.56985603497761 | 12.86037185915382 | 12.68917241065407 | 12.70455147188691 | 12.75717367419013
Macedonia, FYR | MKD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 54.5999984741211 | 54.2000007629395 | 57.7999992370605 | 55.0999984741211 | 51.0999984741211 | 60.4000015258789 | 61.5 | 70.1999969482422 | 63.5999984741211 | 58.2000007629395 | 55.4000015258789 | 58.0999984741211 | 65.4000015258789 | 65 | 63.0999984741211 | 59 | 57.5 | 55.7999992370605 | 52.7999992370605 | 53.9000015258789 | 55.7000007629395 | 55.2000007629395
[NAME] | MLI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.5 | 8.39999961853027 | 8.5 | 8.60000038146973 | 8.80000019073486 | 8.5 | 8.19999980926514 | 8.39999961853027 | 8.10000038146973 | 8.19999980926514 | 8.30000019073486 | 8.39999961853027 | 8.60000038146973 | 8.80000019073486 | 8.5 | 8.19999980926514 | 8.39999961853027 | 8.30000019073486 | 8.39999961853027 | 7.90000009536743 | 7.90000009536743 | 7.69999980926514
Malta | MLT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 15.8999996185303 | 15.6999998092651 | 15.8999996185303 | 19.2000007629395 | 16.3999996185303 | 15.3999996185303 | 14 | 16.6000003814697 | 13.3000001907349 | 20.2999992370605 | 16.2999992370605 | 15.5 | 18.8999996185303 | 17.7000007629395 | 16.8999996185303 | 15.6000003814697 | 13.5 | 15.6999998092651 | 14.5 | 14 | 14.1999998092651
Myanmar | MMR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1000003814697 | 10 | 10 | 9.89999961853027 | 9.89999961853027 | 10 | 10.1999998092651 | 11.1999998092651 | 9.39999961853027 | 9.10000038146973 | 9.39999961853027 | 9.30000019073486 | 9.10000038146973 | 9.10000038146973 | 9.10000038146973 | 9.19999980926514 | 9.30000019073486 | 10.3999996185303 | 10.1999998092651 | 10.1999998092651 | 10.1999998092651 | 10.1000003814697
Middle East & North Africa (developing only) | MNA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.25590429654292 | 23.69298733822453 | 23.90184597818832 | 24.19884873582209 | 24.6671753982978 | 23.82078755265306 | 23.39110376055557 | 23.26365404064837 | 22.78684606755308 | 25.38451286280242 | 24.73743520226114 | 25.88813202741613 | 26.12884559557805 | 24.81082267320824 | 23.0785309721395 | 21.71018064687006 | 21.02562192961517 | 20.5312834130194 | 20.2721139639796 | 21.48903561317118 | 23.44234783361782 | 23.66874018266333
Montenegro | MNE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34 | 34.5 | 33.4000015258789 | 39.5999984741211 | 52.7999992370605 | 54 | 40.7000007629395 | 39.5999984741211 | 39.5999984741211 | 56 | 40.9000015258789 | 40.0999984741211 | 39.5999984741211 | 54.5 | 56.5999984741211 | 46.4000015258789 | 32.7999992370605 | 32.4000015258789 | 35.7000007629395 | 45 | 35.5 | 42.4000015258789
Mongolia | MNG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3999996185303 | 11.3999996185303 | 10.8999996185303 | 12.6999998092651 | 16.1000003814697 | 12.6999998092651 | 14 | 13.6000003814697 | 13.3999996185303 | 12 | 13.3000001907349 | 14.6999998092651 | 11.8999996185303 | 11.6000003814697 | 15.1999998092651 | 10.6999998092651 | 10.6000003814697 | 10.3999996185303 | 9.39999961853027 | 14.6999998092651 | 10.1999998092651 | 11.1999998092651
Northern Mariana Islands | MNP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Mozambique | MOZ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3000001907349 | 12.5 | 12.5 | 12.3999996185303 | 12.6000003814697 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.6000003814697 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5
Mauritania | MRT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 48.5 | 48.5999984741211 | 48.7000007629395 | 48.4000015258789 | 48.7999992370605 | 48.7000007629395 | 48.4000015258789 | 48.5999984741211 | 48.7000007629395 | 48.5 | 48.5999984741211 | 48.5 | 48.5999984741211 | 49.5999984741211 | 49.0999984741211 | 48.5999984741211 | 48 | 47.9000015258789 | 47.7999992370605 | 47.9000015258789 | 47.9000015258789 | 48
[NAME] | MUS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.6000003814697 | 18.7000007629395 | 18.8999996185303 | 19 | 20.1000003814697 | 18.2999992370605 | 16.5 | 18.2000007629395 | 20 | 17.2000007629395 | 14.6999998092651 | 15.8999996185303 | 17.2999992370605 | 21.6000003814697 | 20.6000003814697 | 17.8999996185303 | 19.5 | 14.8000001907349 | 17.6000003814697 | 19 | 17.2000007629395 | 18.5
[NAME] | MWI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3999996185303 | 12.6000003814697 | 12.3999996185303 | 12.6000003814697 | 12.6000003814697 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.6000003814697 | 12.6000003814697 | 12.6000003814697 | 12.5 | 12.6000003814697 | 12.6000003814697 | 12.6000003814697 | 12.6000003814697 | 12.5 | 12.5
Malaysia | MYS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.10000038146973 | 10.1000003814697 | 11.3000001907349 | 10.5 | 8.69999980926514 | 7 | 6.80000019073486 | 8.89999961853027 | 10.1999998092651 | 8.5 | 10.1000003814697 | 10.1999998092651 | 10.6000003814697 | 10.3999996185303 | 10.3999996185303 | 9.89999961853027 | 10.3000001907349 | 10 | 11.1999998092651 | 10.6000003814697 | 9.80000019073486 | 9.80000019073486
North America | NAC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.0759625842205 | 16.09426607785861 | 15.19167107174668 | 13.93166167403483 | 13.05176435683702 | 13.38012984335101 | 12.58557629811607 | 11.89253622881694 | 11.05112101499713 | 10.36270434792336 | 11.87572080963699 | 13.31760078180402 | 13.76033469989199 | 13.08820228159499 | 12.7505110931723 | 11.54111256016349 | 11.8472098324053 | 14.44818730924557 | 20.07137161002077 | 20.62830551725459 | 18.61520653202925 | 17.71121261536153
Namibia | NAM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31.1000003814697 | 31.2999992370605 | 31.3999996185303 | 30 | 30.7999992370605 | 31.6000003814697 | 32.7000007629395 | 35 | 37.2000007629395 | 42.0999984741211 | 39.9000015258789 | 30.8999996185303 | 39.5999984741211 | 37.2999992370605 | 35.4000015258789 | 38.5 | 32.7000007629395 | 55.4000015258789 | 47.7000007629395 | 40.7999992370605 | 35.7999992370605 | 29.2999992370605
New Caledonia | NCL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
[NAME] | NER | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743
Nigeria | NGA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.6999998092651 | 13.6999998092651 | 13.8000001907349 | 13.8000001907349 | 13.6999998092651 | 14 | 13.8999996185303 | 13.8999996185303 | 13.8000001907349 | 14 | 14.1999998092651 | 15 | 14.3000001907349 | 14.3000001907349 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1000003814697 | 14.1999998092651 | 14.1000003814697 | 14.1000003814697
Nicaragua | NIC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.59999990463257 | 4.40000009536743 | 4.69999980926514 | 3.29999995231628 | 3.5 | 3.70000004768372 | 3.90000009536743 | 6.80000019073486 | 4.69999980926514 | 3.29999995231628 | 3.79999995231628 | 4.19999980926514 | 11 | 9.30000019073486 | 7.90000009536743 | 8.10000038146973 | 6.09999990463257 | 7.59999990463257 | 8.19999980926514 | 9.89999961853027 | 9.69999980926514 | 9.39999961853027
Netherlands | NLD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1999998092651 | 7.69999980926514 | 11.3000001907349 | 13.5 | 11.5 | 11.1999998092651 | 9.19999980926514 | 8.19999980926514 | 6.59999990463257 | 4.69999980926514 | 4.19999980926514 | 4.30000019073486 | 6.69999980926514 | 7.90000009536743 | 8 | 6.09999990463257 | 5.59999990463257 | 5.40000009536743 | 7.09999990463257 | 8.80000019073486 | 7.5 | 8.89999961853027
High income: nonOECD | NOC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.20055939426891 | 14.60290448757007 | 15.10636675808267 | 16.6190974173812 | 18.2421122669486 | 18.42312204045083 | 21.75556864256879 | 24.71110030883391 | 21.74332628734832 | 19.47972727279096 | 18.17512753833457 | 16.25346470930882 | 17.54895140354365 | 16.78940707158697 | 15.91019079883953 | 17.25325033577848 | 15.53969425635138 | 14.56748193746576 | 18.36023927293144 | 17.54810021359647 | 15.75454012087301 | 15.90346333641789
Norway | NOR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3000001907349 | 14.8000001907349 | 14.3000001907349 | 12.8999996185303 | 11.6999998092651 | 11.8000001907349 | 10 | 8.69999980926514 | 9.39999961853027 | 9.30000019073486 | 10.3999996185303 | 12.1000003814697 | 12.3999996185303 | 12.3000001907349 | 12.3000001907349 | 8.60000038146973 | 7.90000009536743 | 8.19999980926514 | 10.3000001907349 | 10.8999996185303 | 9.30000019073486 | 10
Nepal | NPL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 3.79999995231628 | 4.30000019073486 | 4.69999980926514 | 5.09999990463257 | 9.30000019073486 | 7.80000019073486 | 6.30000019073486 | 3.79999995231628 | 5.69999980926514 | 8 | 6.09999990463257 | 4.59999990463257 | 4.59999990463257 | 5.5 | 5.80000019073486 | 5.69999980926514 | 5.90000009536743 | 5.90000009536743 | 5.90000009536743 | 5.90000009536743 | 5.90000009536743
New Zealand | NZL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.2999992370605 | 21.1000003814697 | 19.2000007629395 | 16.1000003814697 | 12.3000001907349 | 12.8999996185303 | 13.6999998092651 | 16.1000003814697 | 15.1999998092651 | 14.6000003814697 | 12.3999996185303 | 11.8999996185303 | 10.3999996185303 | 9 | 9.39999961853027 | 9.60000038146973 | 10 | 11.6999998092651 | 15.8999996185303 | 16.7999992370605 | 18.2999992370605 | 17.3999996185303
High income: OECD | OEC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.52117820024738 | 14.68475337632593 | 16.23488242289327 | 16.24936381097642 | 15.27271544288711 | 15.53300037648898 | 15.00714283683121 | 15.06574675983483 | 15.07414731926768 | 14.16417310135588 | 14.43044568983255 | 15.41903476009342 | 15.74366259403564 | 15.39329720345633 | 15.16136569835375 | 13.84946805250361 | 12.9694556009841 | 13.97086104882291 | 18.76534556342156 | 19.1829647992511 | 18.44932647224116 | 19.03323457810707
OECD members | OED | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.92641846184375 | 13.85373721589496 | 15.16367281602326 | 15.25072003953719 | 14.69438326624849 | 14.54380369960447 | 13.80372071155276 | 13.83590881574132 | 13.60843029189139 | 12.91578109146857 | 13.29847556775497 | 14.44226585735575 | 14.82393866940236 | 14.60750204625884 | 14.4031071837105 | 13.16862703112336 | 12.63809349059299 | 13.47134740885656 | 18.16022714580959 | 18.05918762162063 | 17.23148647559449 | 17.56493652728353
Oman | OMN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697 | 18.1000003814697
Other small states | OSS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.91690551108356 | 24.96028040773988 | 25.87373581663696 | 26.13665078015665 | 25.99994957314596 | 24.8475573861595 | 25.08736882942841 | 22.95403600186052 | 25.49652255429345 | 27.73843737914691 | 26.78432351642677 | 24.72231203134061 | 26.9333072830186 | 26.79612323707172 | 26.31460598426392 | 24.96267413517928 | 22.50747132032394 | 26.81520585624008 | 24.17932463714541 | 23.80064661601901 | 22.87844572547773 | 22.6824301111219
Pakistan | PAK | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 7.40000009536743 | 6.5 | 7 | 7.59999990463257 | 7.59999990463257 | 7.90000009536743 | 8.80000019073486 | 9.39999961853027 | 11.1999998092651 | 11.3999996185303 | 12.1000003814697 | 11.8000001907349 | 11.1000003814697 | 10.5 | 8.5 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.30000019073486
Panama | PAN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.5 | 23.8999996185303 | 22.3999996185303 | 22.8999996185303 | 22.7000007629395 | 25.5 | 22.7999992370605 | 23.1000003814697 | 19.6000003814697 | 24.8999996185303 | 25 | 23.2999992370605 | 23 | 21 | 17.5 | 15.1000003814697 | 12.1000003814697 | 11.3000001907349 | 12 | 11.8999996185303 | 10.8000001907349 | 10.6999998092651
Peru | PER | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8 | 9.19999980926514 | 10.6000003814697 | 7.09999990463257 | 6.59999990463257 | 8.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7 | 8.69999980926514 | 6.5 | 8.10000038146973 | 9.89999961853027 | 8 | 8 | 7.09999990463257 | 6.90000009536743 | 6.90000009536743 | 6.80000019073486 | 6.19999980926514 | 6 | 6.09999990463257
Philippines | PHL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.8999996185303 | 14.8000001907349 | 14.8999996185303 | 14.3999996185303 | 14.1000003814697 | 12.3999996185303 | 13.8000001907349 | 17.1000003814697 | 18 | 21.3999996185303 | 18.2999992370605 | 22 | 19.8999996185303 | 20.5 | 15.3000001907349 | 17.1000003814697 | 16.2999992370605 | 16 | 16.2000007629395 | 14.1999998092651 | 13.6000003814697 | 13.6000003814697
Palau | PLW | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
[NAME] | PNG | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 4 | 3.59999990463257 | 4.5 | 5.30000019073486 | 4.5 | 5.59999990463257 | 4.59999990463257 | 4.80000019073486 | 5.19999980926514 | 5 | 4.80000019073486 | 4.59999990463257 | 4.90000009536743 | 4.59999990463257 | 4.80000019073486 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.30000019073486 | 4.09999990463257 | 4.19999980926514
Poland | POL | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.6000003814697 | 25.5 | 27.6000003814697 | 30.2000007629395 | 28.5 | 25.8999996185303 | 21.7000007629395 | 21.2999992370605 | 27.8999996185303 | 32.9000015258789 | 39.5 | 42.9000015258789 | 41.5 | 38.5999984741211 | 36.2999992370605 | 28.1000003814697 | 19.7999992370605 | 15.1000003814697 | 20 | 22.2999992370605 | 23.5 | 24
Puerto Rico | PRI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 35.4000015258789 | 36.5 | 34.5 | 29.8999996185303 | 28.7999992370605 | 29.7999992370605 | 29.5 | 26.2999992370605 | 25.6000003814697 | 24.1000003814697 | 24.8999996185303 | 24 | 24.7999992370605 | 22.3999996185303 | 25.2000007629395 | 23 | 24.5 | 28.2000007629395 | 33.5999984741211 | 35.5 | 33.4000015258789 | 33.9000015258789
Korea, Dem. Rep. | PRK | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 7 | 6.80000019073486 | 6.5 | 6.59999990463257 | 11.1999998092651 | 11.1999998092651 | 12.1000003814697 | 11.1999998092651 | 11.1000003814697 | 11.6999998092651 | 11.1999998092651 | 11.3000001907349 | 10.8000001907349 | 11 | 10.8999996185303 | 10.8000001907349 | 11.3999996185303 | 12.1000003814697 | 10.8000001907349 | 10.8000001907349 | 11.3999996185303
Portugal | PRT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 8.39999961853027 | 10.5 | 12.8000001907349 | 14.5 | 14 | 11.6000003814697 | 8.19999980926514 | 7.19999980926514 | 6.19999980926514 | 7.19999980926514 | 9.80000019073486 | 12.3000001907349 | 13.5 | 13.6999998092651 | 14.5 | 13.5 | 13.3999996185303 | 18.6000003814697 | 21.1000003814697 | 28.7000007629395 | 36.4000015258789
Paraguay | PRY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.60000038146973 | 7.69999980926514 | 10.3999996185303 | 9.19999980926514 | 5.30000019073486 | 7.19999980926514 | 9 | 9.10000038146973 | 10.5 | 11.6999998092651 | 11.6999998092651 | 15 | 12 | 11.3000001907349 | 8.89999961853027 | 10.3999996185303 | 8.5 | 8.60000038146973 | 10.1999998092651 | 9.5 | 9 | 10.3000001907349
Pacific island small states | PSS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
French Polynesia | PYF | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Qatar | QAT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.600000023841858 | 0.800000011920929 | 0.899999976158142 | 0.899999976158142 | 1 | 1 | 1 | 0.5 | 0.300000011920929 | 0.200000002980232 | 0.400000005960464 | 0.600000023841858 | 0.899999976158142 | 1.29999995231628 | 1.10000002384186 | 0.800000011920929 | 0.699999988079071 | 0.400000005960464 | 0.300000011920929 | 0.5 | 0.5 | 0.5
Romania | [NAME] | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.6000003814697 | 22.5 | 21.7999992370605 | 21.1000003814697 | 18.8999996185303 | 17.7999992370605 | 16 | 16.8999996185303 | 18.7000007629395 | 19.2000007629395 | 17.8999996185303 | 22.2999992370605 | 19.1000003814697 | 25.2000007629395 | 21.6000003814697 | 22.2999992370605 | 21.1000003814697 | 18.8999996185303 | 21.2999992370605 | 22.3999996185303 | 23.7999992370605 | 22.5
Russian Federation | RUS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.8999996185303 | 12.8999996185303 | 13.5 | 15.3000001907349 | 17.7000007629395 | 18.2999992370605 | 23.1000003814697 | 26.7000007629395 | 22.5 | 19.5 | 17 | 14.3999996185303 | 16.5 | 16.1000003814697 | 14.3999996185303 | 15.6999998092651 | 14.5 | 13.1999998092651 | 18.1000003814697 | 16.7000007629395 | 15.1000003814697 | 14.6000003814697
Rwanda | RWA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1 | 1 | 0.899999976158142 | 0.899999976158142 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
South Asia | SAS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.224356859432698 | 9.306136856634293 | 9.491455868699207 | 8.517518520999227 | 9.070406683798817 | 9.023069701881656 | 9.987065611916742 | 8.71664250451913 | 9.086560194979807 | 10.1603876881999 | 9.583459144796626 | 10.07398572430272 | 9.569052199660138 | 9.224597978194902 | 9.769148086285492 | 9.647651850824884 | 9.062209356176965 | 9.638646976103765 | 9.566931122652274 | 9.43915543026126 | 9.439734115821285 | 9.235747747711644
Saudi Arabia | SAU | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.3999996185303 | 21.7000007629395 | 22.7000007629395 | 24.2000007629395 | 24.2000007629395 | 22.2999992370605 | 23.1000003814697 | 23.2999992370605 | 21.7999992370605 | 21.8999996185303 | 23 | 24.2999992370605 | 23 | 20.3999996185303 | 24.1000003814697 | 30.3999996185303 | 25.7000007629395 | 24.5 | 23.7000007629395 | 23.7999992370605 | 18.7999992370605 | 21.2000007629395
[NAME] | SCE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Sudan | SDN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.8999996185303 | 21.7999992370605 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 22 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 21.8999996185303 | 22.1000003814697
Senegal | SEN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1000003814697 | 11 | 11 | 11 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697
Singapore | SGP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.5 | 6 | 5.90000009536743 | 6.40000009536743 | 6.5 | 6.80000019073486 | 6.30000019073486 | 11.3999996185303 | 12.1999998092651 | 11.5 | 12 | 15.8999996185303 | 17.1000003814697 | 14.5 | 13.5 | 11.8000001907349 | 10 | 10.6999998092651 | 14.6000003814697 | 10.3000001907349 | 9.80000019073486 | 9.39999961853027
Solomon Islands | SLB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1000003814697 | 9.19999980926514 | 10.3999996185303 | 9.80000019073486 | 9.5 | 10.6999998092651 | 11.1000003814697 | 10.6999998092651 | 11 | 13.1999998092651 | 12.1000003814697 | 11.3000001907349 | 10 | 9.80000019073486 | 9.19999980926514 | 10.3999996185303 | 10 | 9.89999961853027 | 11.6000003814697 | 9.80000019073486 | 9.5 | 10.1000003814697
Sierra Leone | SLE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 7 | 7.09999990463257 | 7.09999990463257 | 7 | 6.90000009536743 | 7 | 7.09999990463257 | 7 | 7.09999990463257 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257
El Salvador | SLV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 15.1999998092651 | 18.5 | 14.6000003814697 | 14.3000001907349 | 13.1999998092651 | 14.8999996185303 | 12.8000001907349 | 14.5 | 14.6000003814697 | 14.6000003814697 | 13 | 13.3000001907349 | 12.5 | 13.8999996185303 | 13.3999996185303 | 12.3999996185303 | 11.8000001907349 | 14.6000003814697 | 14.1000003814697 | 14 | 14
[NAME] | SMR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Somalia | SOM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.5
Serbia | SRB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 26.3999996185303 | 29.3999996185303 | 35.9000015258789 | 31.7000007629395 | 28 | 27.5 | 28.7000007629395 | 28.5 | 28.5 | 26.2000007629395 | 26.7000007629395 | 28.8999996185303 | 31.8999996185303 | 39 | 44 | 42 | 39.5999984741211 | 30.1000003814697 | 37.7999992370605 | 41.0999984741211 | 41.0999984741211 | 41.9000015258789
Sub-Saharan Africa (developing only) | SSA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.09311051184236 | 14.07891622291756 | 14.31067223105588 | 13.41399105865933 | 12.93283907156306 | 13.83025639983491 | 14.00954937743831 | 13.71456407559963 | 13.83402575077176 | 14.06587123563583 | 14.5045901187471 | 14.37287407624853 | 14.37422113107482 | 13.63568747104735 | 12.98859069805334 | 12.95335440122463 | 12.69133247000806 | 12.86710679175778 | 13.0549657690799 | 13.17964007915557 | 13.00168539738796 | 12.97663717752929
South Sudan | SSD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Sub-Saharan Africa (all income levels) | SSF | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.09191925980317 | 14.07814369089048 | 14.3095627092747 | 13.41352017637963 | 12.93265467505181 | 13.82997045975372 | 14.00981109063292 | 13.7140193913519 | 13.83340365120842 | 14.06503879382401 | 14.50387370882481 | 14.37176160972913 | 14.37304480249352 | 13.63517475265684 | 12.9882357688666 | 12.95293889747249 | 12.69126207680197 | 12.8668968678669 | 13.05436436875628 | 13.1790139547589 | 13.0012008152534 | 12.97625408258893
Small states | SST | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.26664331243679 | 23.62501613810833 | 24.80282803754851 | 24.88072304148431 | 25.85387344147699 | 24.42532999056823 | 24.45332137748485 | 23.17515721150651 | 24.62831149984976 | 25.83008762192802 | 25.33555465735744 | 23.70428078003619 | 24.80164695619919 | 24.74623388145687 | 24.18798905141702 | 22.79082592888649 | 20.88299006870266 | 24.3244460421397 | 22.90754211895035 | 23.01284463735181 | 22.394934048476 | 22.5524398185748
Sao Tome and Principe | STP | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Suriname | SUR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.3999996185303 | 36.7000007629395 | 28.7999992370605 | 26.5 | 26.7000007629395 | 24.1000003814697 | 23.6000003814697 | 24.1000003814697 | 24.6000003814697 | 24.2999992370605 | 22.2999992370605 | 22.7000007629395 | 21.7999992370605 | 21.2999992370605 | 22.2999992370605 | 21.8999996185303 | 22.2000007629395 | 22.6000003814697 | 23 | 22.6000003814697 | 22.3999996185303 | 23.1000003814697
Slovak Republic | SVK | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19 | 19.6000003814697 | 23.7999992370605 | 27.8999996185303 | 26 | 20.6000003814697 | 22.6000003814697 | 26.5 | 35.0999984741211 | 39.5 | 41.5999984741211 | 38.9000015258789 | 34.5 | 34.2999992370605 | 30.7999992370605 | 26.3999996185303 | 20.2999992370605 | 18.2000007629395 | 27.8999996185303 | 34.7999992370605 | 33 | 35
Slovenia | SVN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.1999998092651 | 9.69999980926514 | 36.4000015258789 | 21.2000007629395 | 18.7000007629395 | 16.8999996185303 | 14.3999996185303 | 17.2000007629395 | 17.2000007629395 | 14.8000001907349 | 15 | 15.1000003814697 | 15.6999998092651 | 13.8999996185303 | 14.6000003814697 | 11.6000003814697 | 9.39999961853027 | 9.89999961853027 | 13.8000001907349 | 15.3000001907349 | 15.1000003814697 | 20.3999996185303
Sweden | SWE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.69999980926514 | 16.6000003814697 | 26.7000007629395 | 25.8999996185303 | 21.2999992370605 | 22.6000003814697 | 22.7999992370605 | 18.1000003814697 | 15.3999996185303 | 12.3000001907349 | 12.8999996185303 | 13.6000003814697 | 14.6000003814697 | 17.7999992370605 | 22.7999992370605 | 21 | 19.2000007629395 | 20.1000003814697 | 26.3999996185303 | 26.2999992370605 | 23.6000003814697 | 25.5
Swaziland | SWZ | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 40.9000015258789 | 41 | 40.9000015258789 | 40.9000015258789 | 42 | 41.5 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.4000015258789 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2999992370605 | 39.2000007629395 | 39.2000007629395
Sint Maarten (Dutch part) | SXM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Seychelles | SYC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Syrian Arab Republic | SYR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.6000003814697 | 12.6999998092651 | 9.80000019073486 | 9.60000038146973 | 9.30000019073486 | 12.3000001907349 | 13.3000001907349 | 9.60000038146973 | 10.3000001907349 | 13.3999996185303 | 16.2999992370605 | 23.7000007629395 | 15.3999996185303 | 14.6999998092651 | 14 | 12.3999996185303 | 12.8000001907349 | 16.8999996185303 | 11.6999998092651 | 15.5 | 15.5 | 15.3999996185303
Turks and Caicos Islands | TCA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Chad | TCD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.6000003814697 | 12.8000001907349 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.6000003814697 | 12.3999996185303 | 12.3000001907349
Togo | TGO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 12.3000001907349 | 12.1999998092651 | 12.6000003814697 | 12.5 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.3999996185303
Thailand | THA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 3.5 | 3.79999995231628 | 2.5 | 2.5 | 2.70000004768372 | 2.59999990463257 | 8.30000019073486 | 8.60000038146973 | 7.40000009536743 | 8.30000019073486 | 5.80000019073486 | 5 | 4.80000019073486 | 4.80000019073486 | 4.5 | 4.80000019073486 | 5.09999990463257 | 5.30000019073486 | 3.79999995231628 | 2.59999990463257 | 2.70000004768372
Tajikistan | TJK | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19 | 18.3999996185303 | 18.8999996185303 | 18.6000003814697 | 18.7999992370605 | 19.3999996185303 | 19.7000007629395 | 19.7999992370605 | 19.7999992370605 | 20 | 20.1000003814697 | 20 | 20.1000003814697 | 20.1000003814697 | 19.8999996185303 | 19.8999996185303 | 20 | 20 | 19.7999992370605 | 19.8999996185303 | 19.8999996185303 | 20
Turkmenistan | TKM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.1000003814697 | 19.1000003814697 | 18.8999996185303 | 18.7000007629395 | 19 | 19.2000007629395 | 19 | 19.8999996185303 | 20.3999996185303 | 20.5 | 20.6000003814697 | 20.3999996185303 | 20.3999996185303 | 20.2999992370605 | 20.2000007629395 | 20.1000003814697 | 20.1000003814697 | 20.2999992370605 | 19.8999996185303 | 20 | 20.2999992370605 | 20.1000003814697
Timor-Leste | TLS | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 12.3000001907349 | 12.3000001907349 | 12 | 12 | 12.1000003814697 | 12.5 | 13.8000001907349 | 12.3000001907349 | 12 | 18.5 | 17.3999996185303 | 16.3999996185303 | 15.3999996185303 | 14.3999996185303 | 13.5 | 14.3000001907349 | 13.1000003814697 | 11.8000001907349 | 9.10000038146973 | 8.89999961853027 | 9.19999980926514
Tonga | TON | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Trinidad and Tobago | TTO | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 28.6000003814697 | 29.7999992370605 | 29.3999996185303 | 28.6000003814697 | 28 | 23.5 | 22.8999996185303 | 23.1000003814697 | 21.7000007629395 | 20.2999992370605 | 17.8999996185303 | 17 | 17 | 13.3999996185303 | 12.8000001907349 | 10 | 9.19999980926514 | 8.69999980926514 | 9.89999961853027 | 12 | 12.6999998092651 | 11.8999996185303
Tunisia | TUN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.8999996185303 | 31.8999996185303 | 32.9000015258789 | 29.7999992370605 | 32.4000015258789 | 32.9000015258789 | 33.4000015258789 | 36.0999984741211 | 33.9000015258789 | 33.5 | 32.4000015258789 | 33 | 31.5 | 30.3999996185303 | 28.2999992370605 | 27.8999996185303 | 27.8999996185303 | 28.2000007629395 | 30.6000003814697 | 30.2999992370605 | 30.2999992370605 | 30.2000007629395
Turkey | TUR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.2999992370605 | 17.7000007629395 | 18.3999996185303 | 17.2999992370605 | 16.7000007629395 | 14.6000003814697 | 13.6999998092651 | 14.6000003814697 | 15.3000001907349 | 13.3000001907349 | 16.7000007629395 | 19.7999992370605 | 20.7999992370605 | 19.8999996185303 | 19 | 17.7999992370605 | 19 | 19.5 | 24.7999992370605 | 20.5 | 16.7000007629395 | 15.8999996185303
Tuvalu | TUV | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Tanzania | TZA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.80000019073486 | 5.59999990463257 | 5.90000009536743 | 6.09999990463257 | 7.19999980926514 | 7.59999990463257 | 7.19999980926514 | 7.30000019073486 | 7.19999980926514 | 7.69999980926514 | 7.80000019073486 | 5.69999980926514 | 5.80000019073486 | 4.90000009536743 | 4 | 6.5 | 2.79999995231628 | 3.79999995231628 | 4.09999990463257 | 4.80000019073486 | 5.59999990463257 | 5.5
Uganda | UGA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 4.09999990463257 | 3.70000004768372 | 3.70000004768372 | 3.79999995231628 | 3.79999995231628 | 3.79999995231628 | 3.90000009536743 | 3.90000009536743 | 4.5 | 5.30000019073486 | 5.59999990463257 | 5.09999990463257 | 4 | 3.20000004768372 | 3.29999995231628 | 3.29999995231628 | 4.69999980926514 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486
Ukraine | UKR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.3999996185303 | 16.2000007629395 | 18.5 | 14.8000001907349 | 11.8000001907349 | 15.8999996185303 | 18.7000007629395 | 23.7000007629395 | 24.2999992370605 | 24.2999992370605 | 22.8999996185303 | 20.1000003814697 | 19.1000003814697 | 15.8999996185303 | 15.3000001907349 | 14.1999998092651 | 13.3999996185303 | 13.3999996185303 | 18.5 | 17.2000007629395 | 18.2000007629395 | 17.5
Upper middle income | UMC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.09886309491494 | 12.12190827716569 | 12.4169705242324 | 12.42153672409163 | 13.0839509094918 | 13.38898332611477 | 13.43573061978089 | 14.11557085885591 | 14.42804118736921 | 14.58443987415463 | 14.63496447417293 | 14.75550550980338 | 14.75329349555946 | 14.21249980182536 | 13.50666963618652 | 12.75297083265662 | 12.35197581648576 | 13.01724361461348 | 13.76957852550115 | 13.50508001863951 | 13.43051927933598 | 13.72664555239003
Uruguay | URY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.1000003814697 | 16.5 | 16.3999996185303 | 17.2000007629395 | 17.7000007629395 | 18.2000007629395 | 17.2999992370605 | 21.7999992370605 | 20.7000007629395 | 19.7000007629395 | 18.7000007629395 | 17.7000007629395 | 16.7999992370605 | 19.7999992370605 | 19.2000007629395 | 22.8999996185303 | 20.3999996185303 | 15.8000001907349 | 15.5 | 16 | 14.3000001907349 | 13
United States | USA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.6999998092651 | 15.6999998092651 | 14.6999998092651 | 13.5 | 12.6999998092651 | 13 | 12.1000003814697 | 11.3999996185303 | 10.6000003814697 | 10 | 11.6000003814697 | 13.1000003814697 | 13.6000003814697 | 12.8999996185303 | 12.6000003814697 | 11.3999996185303 | 11.8000001907349 | 14.6000003814697 | 20.2999992370605 | 21 | 18.8999996185303 | 17.8999996185303
Uzbekistan | UZB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.2000007629395 | 18.8999996185303 | 19.2000007629395 | 19.1000003814697 | 19.2000007629395 | 19.7000007629395 | 19.7999992370605 | 19.7999992370605 | 19.7999992370605 | 19.7999992370605 | 19.7999992370605 | 19.7999992370605 | 19.7999992370605 | 19.8999996185303 | 19.8999996185303 | 20 | 20.1000003814697 | 20 | 20 | 20 | 20 | 20
St. Vincent and the Grenadines | VCT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Venezuela, RB | VEN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.5 | 12.6999998092651 | 11.1999998092651 | 15.5 | 17.2999992370605 | 20.2000007629395 | 16.2999992370605 | 18.6000003814697 | 22.2000007629395 | 22.2999992370605 | 19.6000003814697 | 24.3999996185303 | 23.8999996185303 | 21.7000007629395 | 16.7999992370605 | 14.3000001907349 | 12.8000001907349 | 12.3000001907349 | 13.6999998092651 | 15.5 | 15 | 14
Virgin Islands (U.S.) | VIR | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Vietnam | VNM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 4.19999980926514 | 4.59999990463257 | 4.09999990463257 | 3.70000004768372 | 3.29999995231628 | 5.09999990463257 | 4.19999980926514 | 4.5 | 4.80000019073486 | 4.59999990463257 | 3.90000009536743 | 4.40000009536743 | 4.19999980926514 | 4 | 4.5 | 4.5 | 4.69999980926514 | 4.59999990463257 | 4.59999990463257 | 4 | 4.09999990463257
[NAME] | VUT | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
West Bank and Gaza | PSE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 32.7999992370605 | 37.4000015258789 | 35.7000007629395 | 34.0999984741211 | 34.5 | 33.5999984741211 | 28.7000007629395 | 20.3999996185303 | 16.7999992370605 | 20.1000003814697 | 35.2999992370605 | 42.5 | 41.5999984741211 | 38.9000015258789 | 37.7999992370605 | 34.4000015258789 | 33.7999992370605 | 38.7000007629395 | 36.4000015258789 | 35.7000007629395 | 30.5 | 33.5
World | WLD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.53039079539568 | 11.75022743397317 | 12.35639038154784 | 12.16966436591703 | 12.2982966470775 | 12.48936883764714 | 12.83856485300377 | 13.00034951835969 | 13.08337906329471 | 13.38684374370316 | 13.34827254472192 | 13.7645912690752 | 13.60621695171501 | 13.25889336604664 | 13.0619765207258 | 12.61059141051784 | 11.93463289887564 | 12.33855966311734 | 13.22079153456172 | 13.05669811078383 | 12.92160403181313 | 13.02833798497909
Samoa | WSM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS
Yemen, Rep. | YEM | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 25.3999996185303 | 23.3999996185303 | 21.5 | 25.7999992370605 | 24.2999992370605 | 22.7000007629395 | 23.7999992370605 | 25.2000007629395 | 22.2000007629395 | 25.7000007629395 | 22.2999992370605 | 22.2000007629395 | 22.5 | 22.2000007629395 | 24.8999996185303 | 24.2999992370605 | 23.7000007629395 | 23.2999992370605 | 22.7000007629395 | 27.8999996185303 | 27.7999992370605 | 28.1000003814697
South Africa | ZAF | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 42.7999992370605 | 42.7999992370605 | 45.9000015258789 | 36.2000007629395 | 30.7000007629395 | 38.2999992370605 | 41.9000015258789 | 40.2000007629395 | 42.5 | 43.2000007629395 | 47.7999992370605 | 49.2999992370605 | 52 | 46 | 43 | 41.7000007629395 | 41.2999992370605 | 41.5 | 44.5999984741211 | 47.4000015258789 | 45.7000007629395 | 47.5
Congo, Dem. Rep. | COD | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 12.1999998092651 | 12.1999998092651 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349 | 12.3999996185303 | 12.3000001907349 | 12.3000001907349 | 12.3999996185303 | 12.3999996185303 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.5 | 12.3999996185303 | 12.5 | 12.5 | 12.5
Zambia | ZMB | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 34.7000007629395 | 35 | 36 | 34.7000007629395 | 33.7000007629395 | 27.8999996185303 | 26.3999996185303 | 21.8999996185303 | 22.2999992370605 | 23.5 | 27.3999996185303 | 26.7000007629395 | 27 | 25.7000007629395 | 26.2999992370605 | 27.6000003814697 | 27.5 | 26.7999992370605 | 27.7999992370605 | 28.5 | 28.5 | 26.8999996185303
Zimbabwe | ZWE | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.2000007629395 | 16.2999992370605 | 16.7999992370605 | 14.1999998092651 | 15.6000003814697 | 16.8999996185303 | 20.2000007629395 | 18.3999996185303 | 16.1000003814697 | 16.3999996185303 | 16.1000003814697 | 12.3999996185303 | 9.39999961853027 | 7 | 7 | 7 | 7 | 6.80000019073486 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.69999980926514