Spreadsheet: 55cd7b42-22ec-4032-88d1-214e9ae504d8
Sheet: Sheet1

Data Source | World Development Indicators | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18 | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Unnamed: 22 | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Unnamed: 30 | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Unnamed: 34 | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Unnamed: 38 | Unnamed: 39 | Unnamed: 40 | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Unnamed: 44 | Unnamed: 45 | Unnamed: 46 | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Unnamed: 50 | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Unnamed: 56 | Unnamed: 57
Country Name | Country Code | Indicator Name | Indicator Code | 1960 | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013
Aruba | ABW | Unemployment, youth 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
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 | 23.94652636911865 | 24.43665796236977 | 24.91536236598557 | 23.96305922767316 | 23.60115175790588 | 23.44589718319501 | 22.88170392652192 | 24.80400412873674 | 24.79672374572496 | 25.71579592622895 | 26.25510103599409 | 25.66947489977366 | 23.27607675699545 | 22.24631902800181 | 21.30794116450893 | 20.56385901661865 | 19.61718622360807 | 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
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 | 28.9929218564887 | 26.34418711141305 | 25.70055882416021 | 26.01946156699773 | 24.93066090261625 | 23.35105949907426 | 24.46100816514721 | 23.72630212254487 | 20.94590018303641 | 22.02482010737358 | 21.02198432445666 | 18.40336122842891 | 17.29456566204368 | 18.39091419926258 | 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 | 9.733759512243768 | 10.01209083363098 | 10.02651997706408 | 10.29410407117676 | 10.64021052006317 | 11.679134028912 | 11.79595493262077 | 11.87048589819094 | 12.13645937528274 | 12.41548660737659 | 12.01893704525116 | 12.19329594606832 | 12.01803345528167 | 11.68352455735298 | 10.83424974868077 | 11.58764703673878 | 11.754173850778 | 11.21159851967194 | 11.25349111547294 | 11.70017891543114
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 | 9.5859753813951 | 9.794946868961292 | 9.78957673612577 | 10.08390614138281 | 10.43371094527435 | 11.73559022309541 | 11.87831909485306 | 11.84515885246432 | 12.10014625552721 | 12.35148468424063 | 12.01644868426903 | 12.12716247585123 | 11.92920934686046 | 11.56184790222686 | 10.73471294164437 | 11.42635219450491 | 11.71955951673314 | 11.19925638394354 | 11.19685307937692 | 11.56305184604936
Europe & Central Asia (developing only) | ECA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.30902916198755 | 19.46299315213875 | 20.99125284437907 | 19.29159097189805 | 18.18829547725521 | 18.19693725888041 | 18.32794552723173 | 19.51113317922506 | 20.13956163091252 | 19.38197198739078 | 20.21538886362286 | 21.11939954707366 | 20.73854198893933 | 20.63728048794553 | 19.93840744597954 | 19.28705821934288 | 19.23854489564625 | 18.8937833391756 | 21.43146100424647 | 20.62816107514399 | 19.57755066847789 | 19.1956864004704
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.97547838927267 | 17.25940208827435 | 19.71579583384876 | 20.08091647636084 | 19.44212082390207 | 19.59189667270489 | 20.05308893678444 | 20.52582132717212 | 20.15484883726099 | 18.9054215609604 | 18.52596187486933 | 18.79166305985258 | 19.13884225930834 | 19.03147805194477 | 18.47228771977143 | 17.71017132169479 | 16.53268425002245 | 16.29467451230377 | 20.68156600680225 | 20.57487206452115 | 20.12300024669999 | 21.13114504659883
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 | 16.48576839018899 | 20.7414981056062 | 22.51629302259945 | 21.23780856537762 | 21.77444931068599 | 21.55396188376785 | 20.09917347531967 | 19.17753635437919 | 17.13867395417124 | 15.42863126927868 | 16.45701906644462 | 16.80521147932609 | 17.46131974856481 | 17.5524663407044 | 16.25982159732741 | 14.87300773995561 | 15.84213971038888 | 21.42070439712483 | 22.29846520069902 | 22.67684758359287 | 25.86585570566806
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.62296915860786 | 17.99486066611223 | 21.71158174350493 | 22.83025345131455 | 21.27541385421816 | 21.21422057040795 | 20.28515174659193 | 19.19572643240184 | 19.59261767486396 | 18.82429524566177 | 18.40252203885868 | 19.41682134544625 | 19.26216649089922 | 19.57955048101354 | 19.43148625964047 | 17.82253212769415 | 15.75983858885616 | 15.881030663632 | 21.47560191739716 | 22.46408730636298 | 22.9102215829225 | 25.33209229212445
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 | 16.06691826292293 | 16.27758054044646 | 16.91733920024644 | 16.37844389083052 | 15.22722048510476 | 15.18874785432674 | 15.59080691256722 | 16.1186472501001 | 15.68602501836978 | 15.32083674356279 | 14.56908353692309 | 13.51620424394677 | 14.10031629441039 | 18.68272284840158 | 18.84649852344392 | 17.90068630355422 | 18.40009847368322
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 | 10.63377554201248 | 10.4340131928344 | 10.35973977835457 | 10.19013810789383 | 10.32624434980966 | 10.52712634355528 | 10.16553867318551 | 10.24142960795559 | 9.927911361684895 | 9.471757197152442 | 9.615563832876092 | 9.373845028890807 | 9.525386809740624 | 9.682612185302759 | 9.788792146150936 | 9.78349658464023 | 9.738727298515341
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 | 10.71882843785876 | 12.23937980810006 | 12.31044013475983 | 11.7861107550514 | 12.41900738736863 | 12.6857412693947 | 13.18948121698384 | 13.03148776510863 | 13.79463495508839 | 13.97942842530421 | 13.17289176193413 | 13.00909858705055 | 11.85501122541235 | 11.35891663480708 | 11.08113998651395 | 12.57154753274109 | 12.16243830265549 | 11.56835931158904 | 11.39973949032365
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 | 12.95549394861514 | 12.44305291603414 | 11.81373163634901 | 11.62144711450605
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 | 10.26569889643404 | 10.24216261440843 | 10.07096358062649 | 10.31755910493649 | 10.02368460157618 | 10.01661966501812 | 10.37111380565002 | 10.39709861142564 | 10.10871392553264 | 9.620643086776035 | 9.50494180089849 | 9.419438955970573 | 9.898346470060856 | 9.764498403543769 | 10.00402019388994 | 10.33265821670606 | 10.18926013194095 | 10.19096346539564 | 10.31270755154308
Low income | LIC | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.067952071799326 | 9.229438743884666 | 9.185648309376505 | 9.07243337536762 | 9.157344917590834 | 9.335046524992727 | 9.6108580866582 | 9.371315047003446 | 9.364669394403107 | 9.562248188690447 | 9.63353796715417 | 9.311423458500153 | 8.691433929588214 | 8.514218506979118 | 8.354734616047713 | 8.847994238251534 | 8.735773903892532 | 8.997195225493613 | 9.362366764127371 | 8.99823063760238 | 8.981281523158817 | 9.117504321079174
[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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.65399446482896 | 10.66677809412627 | 11.49685230927757 | 10.92883893180752 | 10.86901369424174 | 10.98801525982616 | 11.77020985687712 | 11.41612490712715 | 11.62357836642603 | 12.72148779124372 | 12.58298409173812 | 13.51636650057607 | 13.09838678730276 | 12.92513300691244 | 13.28339484373644 | 12.95037497448099 | 11.98769859328926 | 12.14450120681384 | 12.01087771829268 | 11.9442830010717 | 12.06264267274894 | 11.9300237877448
Low & middle income | LMY | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.0271177158693 | 11.16698489212675 | 11.63001002115463 | 11.36126104709226 | 11.62014192846638 | 11.80656106378608 | 12.18941654045754 | 12.26974310867614 | 12.47732129934258 | 13.05453812287107 | 13.02145271960618 | 13.44510606368164 | 13.17425127963615 | 12.84851247044986 | 12.68586982063294 | 12.28877886064223 | 11.67799880836235 | 12.05540342775369 | 12.34866559713535 | 12.14089311139485 | 12.14086410931294 | 12.19233841068361
[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
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 | 23.78360432917026 | 24.10066343900381 | 23.2314233172259 | 22.90241133517751 | 22.8298612205363 | 22.30287783247009 | 24.67002836139096 | 24.18378116297368 | 25.35820153631557 | 25.53568657763335 | 24.16512110052998 | 22.73414338656697 | 21.80129757672983 | 20.78607793993537 | 20.16632735002218 | 19.87503275112659 | 20.87500580515622 | 22.1920241235645 | 22.55644402374851
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.4262668305533 | 11.43431637996107 | 11.97535414902398 | 11.69226107578728 | 11.9841995832766 | 12.17939073754949 | 12.5856851578571 | 12.72249109913879 | 12.97004846020169 | 13.61290159363216 | 13.56675936036767 | 14.11299000446765 | 13.90034390921847 | 13.55263857439103 | 13.39289010659649 | 12.85430631803771 | 12.16589496246241 | 12.5685404995417 | 12.857708807274 | 12.68765382909009 | 12.70476976252781 | 12.7578834320203
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 23.25590429654293 | 23.69298733822453 | 23.90184597818831 | 24.19884873582209 | 24.6671753982978 | 23.82078755265307 | 23.39110376055557 | 23.26365404064837 | 22.78684606755308 | 25.38451286280241 | 24.73743520226114 | 25.88813202741614 | 26.12884559557805 | 24.81082267320825 | 23.0785309721395 | 21.71018064687006 | 21.02562192961517 | 20.5312834130194 | 20.2721139639796 | 21.48903561317118 | 23.44234783361781 | 23.66874019492073
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 | 20.62830543987165 | 18.61521087678136 | 17.71123459959816
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 | 18.4233695478009 | 21.75164582649349 | 24.70378534368092 | 21.74006239410151 | 19.47969894521708 | 18.17527565898995 | 16.25442208761781 | 17.54929609706237 | 16.78931189039832 | 15.90993105936288 | 17.25315745717415 | 15.53976540056302 | 14.56751389761617 | 18.36023708130492 | 17.54808866710761 | 15.75512537171346 | 15.90291257169435
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 | 15.53300037648899 | 15.00714283683121 | 15.06574675983483 | 15.07414731926768 | 14.16862767657694 | 14.4304382873249 | 15.41976100813913 | 15.74557102993794 | 15.39553809255393 | 15.16455198655482 | 13.85271800244834 | 12.97326154745262 | 13.97468191288006 | 18.76911444923752 | 19.19089623590248 | 18.45835074568343 | 19.03289683698181
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 | 15.16367281602325 | 15.25072003953719 | 14.69438326624849 | 14.54380369960447 | 13.80372071155276 | 13.83590881574132 | 13.60843029189139 | 12.91955341456171 | 13.29844603721756 | 14.44289436206949 | 14.82562163627047 | 14.60952504199065 | 14.40594398184401 | 13.17154992511301 | 12.64131354400189 | 13.47469485190458 | 18.1636411388378 | 18.06636934130958 | 17.23963546407099 | 17.56465176131589
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 | 24.96028040773989 | 25.87373581663697 | 26.13665078015665 | 25.99994957314596 | 24.84755738615949 | 25.08736882942841 | 22.95403600186053 | 25.49652255429345 | 27.73843737914691 | 26.78432351642677 | 24.72231203134061 | 26.93330728301861 | 26.79612323707171 | 26.3144399340079 | 24.95230557700007 | 22.49290049523891 | 26.7792006172463 | 24.13634268362797 | 23.73680780286328 | 22.83373571486873 | 22.63401342581366
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.2243568594327 | 9.306136856634293 | 9.491455868699209 | 8.517518520999227 | 9.07040668379882 | 9.023069701881658 | 9.987065611916742 | 8.716642504519127 | 9.086560194979807 | 10.1603876881999 | 9.583459144796624 | 10.07398572430272 | 9.56905219966014 | 9.2245979781949 | 9.769148086285492 | 9.647651850824884 | 9.062209356176965 | 9.638646976103763 | 9.566931122652274 | 9.43915543026126 | 9.439734115821286 | 9.23574773583452
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
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 | 14.07891622291755 | 14.31067223105588 | 13.41399105865933 | 12.93283907156306 | 13.83025639983491 | 14.00954937743831 | 13.71456407559963 | 13.83402575077177 | 14.06587123563583 | 14.5045901187471 | 14.37287407624853 | 14.37422113107482 | 13.63568747104734 | 12.98859069805334 | 12.95335440122463 | 12.69133247000806 | 12.86710679175778 | 13.0549657690799 | 13.17964007915557 | 13.00168539738796 | 12.97663849898495
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 | 12.97625540307875
Small states | SST | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24.26664331243679 | 23.62501613810834 | 24.8028280375485 | 24.8807230414843 | 25.85387344147699 | 24.42532999056824 | 24.45332137748485 | 23.17515721150651 | 24.62831149984977 | 25.83008762192802 | 25.33555465735744 | 23.70428078003618 | 24.80164695619919 | 24.74623388145687 | 24.18789095983391 | 22.78475267914202 | 20.87450774956899 | 24.30297728747177 | 22.87934701571898 | 22.96853497187602 | 22.36318549289356 | 22.51707396170446
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.09921908975043 | 12.12289422505309 | 12.41870390763228 | 12.42298232435672 | 13.08501229994843 | 13.38987116491954 | 13.43665782174262 | 14.11655995562741 | 14.42922999419945 | 14.58553816686429 | 14.63767316023805 | 14.75627035803772 | 14.75402023572733 | 14.21323007189533 | 13.50746138787232 | 12.75382266399943 | 12.35316206266868 | 13.01866320141997 | 13.77081544298725 | 13.50680893593833 | 13.43270785140917 | 13.72914575001197
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 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.53055154818164 | 11.75062223123922 | 12.35705086690489 | 12.17021238720918 | 12.29871037416353 | 12.48937134160799 | 12.83801948114382 | 12.99921551331398 | 13.08260765645315 | 13.3875757002939 | 13.34924637165966 | 13.76498123212499 | 13.60675859353285 | 13.25954376090792 | 13.06275759251205 | 12.61135811008766 | 11.93558277456201 | 12.33965446328826 | 13.22217999910849 | 13.05880504707109 | 12.9239751107693 | 13.02923027026929
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