Spreadsheet: 9e60d283-0dcf-4080-ab87-fead9d4566e5
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, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Andorra | AND | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Afghanistan | AFG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.80000019073486 | 6.90000009536743 | 6.69999980926514 | 6.69999980926514 | 6.80000019073486 | 6.80000019073486 | 6.69999980926514 | 7.80000019073486 | 7.69999980926514 | 7.90000009536743 | 7.69999980926514 | 8 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486
Angola | AGO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.09999990463257 | 7 | 7.19999980926514 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.19999980926514 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486
Albania | ALB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.69999980926514 | 11.6000003814697 | 15.3999996185303 | 14.8999996185303 | 13.8999996185303 | 12.1000003814697 | 13 | 12 | 12.3999996185303 | 12.8999996185303 | 18.2999992370605 | 11.5 | 13 | 12.8000001907349 | 12.8000001907349 | 12 | 14 | 12.3999996185303 | 12 | 12.1999998092651 | 12.1999998092651 | 12.6000003814697
Andean Region | ANR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Arab World | ARB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.36136778032902 | 10.68411287810652 | 10.68347225886451 | 10.79531277617748 | 11.08715893042361 | 10.96914717913812 | 10.63973753908718 | 10.56534826333607 | 10.64697828070645 | 11.39670034784943 | 11.14200597208982 | 11.15253084223187 | 11.7485252946354 | 11.19981676669407 | 9.711207567534304 | 9.070147975514292 | 8.847068387138163 | 8.380164605317239 | 7.987530819068541 | 7.990462659210641 | 8.313482078821577 | 8.355532021424937
United Arab Emirates | ARE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.09999990463257 | 2.09999990463257 | 2.09999990463257 | 1.70000004768372 | 1.70000004768372 | 2 | 2.5 | 2.20000004768372 | 2 | 1.79999995231628 | 1.89999997615814 | 2 | 2.09999990463257 | 2.29999995231628 | 2.5 | 2.5 | 2.59999990463257 | 2.40000009536743 | 2.5 | 2.5 | 2.40000009536743 | 2.40000009536743
Argentina | ARG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 6.80000019073486 | 8.30000019073486 | 10.6999998092651 | 16.7999992370605 | 15.5 | 13 | 11.5 | 13.1000003814697 | 13.6999998092651 | 18.7999992370605 | 17.2999992370605 | 14.3000001907349 | 11.1999998092651 | 9.19999980926514 | 8.39999961853027 | 6.80000019073486 | 6.40000009536743 | 7.69999980926514 | 6.69999980926514 | 6.30000019073486 | 6.40000009536743
Armenia | ARM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.7999992370605 | 18.7999992370605 | 18.7999992370605 | 19 | 25.5 | 18.5 | 18.8999996185303 | 21.2999992370605 | 19 | 20.6000003814697 | 31.8999996185303 | 22.3999996185303 | 22.7000007629395 | 28.8999996185303 | 22.1000003814697 | 22.2000007629395 | 22.5 | 26.1000003814697 | 17.8999996185303 | 17.2999992370605 | 17.2000007629395 | 17
American Samoa | ASM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
[NAME] and [NAME] | ATG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Australia | AUS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.89999961853027 | 11.3999996185303 | 11.5 | 10 | 8.80000019073486 | 8.80000019073486 | 8.69999980926514 | 8 | 7.09999990463257 | 6.5 | 7 | 6.5 | 5.90000009536743 | 5.30000019073486 | 4.90000009536743 | 4.69999980926514 | 4.09999990463257 | 4 | 5.69999980926514 | 5.09999990463257 | 4.90000009536743 | 5.19999980926514
Austria | AUT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.29999995231628 | 3.5 | 4.09999990463257 | 3.20000004768372 | 3.09999990463257 | 3.90000009536743 | 3.90000009536743 | 3.90000009536743 | 3.59999990463257 | 3.29999995231628 | 3.40000009536743 | 4.09999990463257 | 4.30000019073486 | 4.5 | 4.90000009536743 | 4.30000019073486 | 3.90000009536743 | 3.59999990463257 | 5 | 4.59999990463257 | 4 | 4.30000019073486
Azerbaijan | AZE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 5.40000009536743 | 5.30000019073486 | 5.09999990463257 | 5.40000009536743 | 5.09999990463257 | 5.09999990463257 | 5.19999980926514 | 7.09999990463257 | 5.09999990463257 | 5 | 4.90000009536743 | 6.30000019073486 | 5.90000009536743 | 7.40000009536743 | 6.40000009536743 | 7.80000019073486 | 7.09999990463257 | 4.90000009536743 | 4.40000009536743 | 4.19999980926514 | 4.40000009536743
Burundi | BDI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.5 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.5 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.19999980926514
Belgium | BEL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.59999990463257 | 4.80000019073486 | 6.19999980926514 | 7.69999980926514 | 7.30000019073486 | 7.40000009536743 | 7.09999990463257 | 7.59999990463257 | 7.5 | 5.30000019073486 | 5.59999990463257 | 6.69999980926514 | 7.59999990463257 | 7.5 | 7.59999990463257 | 7.40000009536743 | 6.69999980926514 | 6.5 | 7.69999980926514 | 8.10000038146973 | 7.09999990463257 | 7.69999980926514
Benin | [NAME] | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.899999976158142 | 2.20000004768372 | 1.79999995231628 | 1.39999997615814 | 1.10000002384186 | 0.899999976158142 | 0.899999976158142 | 1 | 0.899999976158142 | 0.899999976158142 | 0.899999976158142 | 0.899999976158142 | 1 | 1.89999997615814 | 1.79999995231628 | 1 | 1.10000002384186 | 1.10000002384186 | 1.20000004768372 | 0.899999976158142 | 0.899999976158142 | 1
[NAME] | BFA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.40000009536743 | 3 | 4 | 3.29999995231628 | 3.09999990463257 | 3.09999990463257 | 2.90000009536743 | 3 | 2.90000009536743 | 3.79999995231628 | 2.90000009536743 | 3.70000004768372 | 3.5 | 3.5 | 3.40000009536743 | 2.90000009536743 | 4.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257
Bangladesh | BGD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 3.40000009536743 | 3.29999995231628 | 3.09999990463257 | 3 | 2.70000004768372 | 3.09999990463257 | 2.70000004768372 | 3.20000004768372 | 3.29999995231628 | 3.29999995231628 | 3.40000009536743 | 4.09999990463257 | 3.90000009536743 | 3 | 3.40000009536743 | 3.5 | 3.59999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4
Bulgaria | BGR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 19.1000003814697 | 14 | 21.7000007629395 | 20.2999992370605 | 16 | 13.8000001907349 | 14 | 12.5 | 14.5 | 16.6000003814697 | 21 | 18.7999992370605 | 14.1999998092651 | 12.3999996185303 | 10.3000001907349 | 8.69999980926514 | 6.5 | 5.5 | 7 | 10.8000001907349 | 12.3000001907349 | 13.5
Bahrain | BHR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19999980926514 | 5.30000019073486 | 5.09999990463257 | 4.80000019073486 | 4.30000019073486 | 4.19999980926514 | 4.5 | 4.30000019073486 | 4.09999990463257 | 4.59999990463257 | 4.19999980926514 | 4.90000009536743 | 5.5 | 6.30000019073486 | 6.19999980926514 | 5.90000009536743 | 5.59999990463257 | 5.19999980926514 | 5 | 4.80000019073486 | 4.69999980926514 | 4.80000019073486
Bahamas, The | BHS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 13.8999996185303 | 12.8000001907349 | 12.1999998092651 | 10 | 8.80000019073486 | 8.5 | 5.59999990463257 | 5.5 | 5.69999980926514 | 6.5 | 8.69999980926514 | 9.89999961853027 | 9.5 | 9.19999980926514 | 6.69999980926514 | 6.69999980926514 | 7.80000019073486 | 12.8000001907349 | 12.6999998092651 | 12.3000001907349 | 12.1000003814697
Bosnia and Herzegovina | BIH | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.7000007629395 | 21.5 | 23.7000007629395 | 25.3999996185303 | 23.7000007629395 | 24 | 26.2000007629395 | 24.6000003814697 | 24.2000007629395 | 23.7999992370605 | 25.3999996185303 | 23.3999996185303 | 24.2999992370605 | 26.6000003814697 | 24.2999992370605 | 29.5 | 27.3999996185303 | 21.7999992370605 | 23.1000003814697 | 25.6000003814697 | 26 | 26.7000007629395
Belarus | BLR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.80000019073486 | 9.60000038146973 | 9.69999980926514 | 9.60000038146973 | 9.60000038146973 | 10 | 10.3000001907349 | 10.1999998092651 | 10 | 10.1000003814697 | 10.1000003814697 | 10.1000003814697 | 10.1000003814697 | 10.3000001907349 | 10.1999998092651 | 10.1999998092651 | 10.1000003814697 | 10.1000003814697 | 9.69999980926514 | 10 | 9.80000019073486 | 9.69999980926514
Belize | BLZ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 8.10000038146973 | 7.30000019073486 | 8.89999961853027 | 10.1000003814697 | 11.6999998092651 | 9.10000038146973 | 10.8999996185303 | 9.19999980926514 | 8.30000019073486 | 6.80000019073486 | 7.5 | 7.59999990463257 | 7.80000019073486 | 7.5 | 6.90000009536743 | 6.19999980926514 | 6 | 6.5 | 6.09999990463257 | 6.19999980926514 | 5.80000019073486
Bermuda | BMU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Bolivia | BOL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.59999990463257 | 4.5 | 3.90000009536743 | 4.40000009536743 | 4.40000009536743 | 4.30000019073486 | 4.09999990463257 | 4 | 3.59999990463257 | 4 | 4.59999990463257 | 4.30000019073486 | 4.19999980926514 | 3.59999990463257 | 4.5 | 4.40000009536743 | 4.30000019073486 | 2.40000009536743 | 2.79999995231628 | 2.70000004768372 | 2.59999990463257 | 2.70000004768372
Brazil | BRA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 5.40000009536743 | 5.19999980926514 | 5.09999990463257 | 5.09999990463257 | 5.5 | 6.19999980926514 | 7.09999990463257 | 7.80000019073486 | 7.69999980926514 | 7.5 | 7.30000019073486 | 7.80000019073486 | 6.80000019073486 | 7.09999990463257 | 6.40000009536743 | 6 | 5.09999990463257 | 6.09999990463257 | 5.80000019073486 | 4.90000009536743 | 5.19999980926514
Barbados | BRB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 20.1000003814697 | 22.2999992370605 | 18.2000007629395 | 16.7000007629395 | 11.8000001907349 | 11.3999996185303 | 8.69999980926514 | 7.80000019073486 | 7.30000019073486 | 8 | 8.60000038146973 | 9.5 | 8.10000038146973 | 7.5 | 7.09999990463257 | 6.09999990463257 | 6.59999990463257 | 8.19999980926514 | 8.80000019073486 | 9.19999980926514 | 9.60000038146973
[NAME] | BRN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.5 | 3.90000009536743 | 3.40000009536743 | 4.40000009536743 | 4.09999990463257 | 3.90000009536743 | 3.20000004768372 | 3.29999995231628 | 4.09999990463257 | 3.79999995231628 | 3.59999990463257 | 3.59999990463257 | 3.70000004768372 | 3.09999990463257 | 3.09999990463257 | 3.09999990463257 | 3.09999990463257 | 3.09999990463257 | 3.29999995231628 | 3.5 | 3.59999990463257 | 3.59999990463257
Bhutan | BTN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.60000002384186 | 1.70000004768372 | 1.79999995231628 | 2 | 2.59999990463257 | 1.29999995231628 | 1.29999995231628 | 1.20000004768372 | 1.20000004768372 | 1.39999997615814 | 1.60000002384186 | 1.5 | 1.5 | 2.09999990463257 | 2.90000009536743 | 2.79999995231628 | 3.09999990463257 | 2.90000009536743 | 2.70000004768372 | 2.59999990463257 | 1.89999997615814 | 1.89999997615814
Botswana | BWA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2000007629395 | 20.1000003814697 | 20.3999996185303 | 19.8999996185303 | 20 | 19.6000003814697 | 19 | 18.3999996185303 | 20.5 | 21.7000007629395 | 21 | 20.2999992370605 | 21.1000003814697 | 20.2999992370605 | 19.5 | 15.5 | 15.5 | 19.5 | 15.6999998092651 | 14.3999996185303 | 14.3000001907349 | 14.8000001907349
Sub-Saharan Africa (IFC classification) | CAA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Central African Republic | CAF | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486
Canada | CAN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8000001907349 | 12 | 11.8999996185303 | 10.8999996185303 | 9.80000019073486 | 9.89999961853027 | 9.19999980926514 | 8.5 | 7.80000019073486 | 6.90000009536743 | 7.5 | 8.10000038146973 | 7.90000009536743 | 7.5 | 7 | 6.5 | 6.40000009536743 | 6.5 | 9.39999961853027 | 8.69999980926514 | 7.80000019073486 | 7.59999990463257
East Asia and the Pacific (IFC classification) | CEA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Central Europe and the Baltics | CEB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.746209325864982 | 10.1010455386669 | 11.25388575867754 | 11.43797856675837 | 10.47779502572972 | 9.374491757099717 | 8.596275666040047 | 8.742504781299177 | 10.38433318293442 | 11.90441158451512 | 13.08231595858585 | 13.46061239569672 | 12.67914328129491 | 12.64589514009537 | 11.45964509072428 | 9.689068618715025 | 7.446972077955482 | 6.31527367744478 | 8.521439189736956 | 10.01527181938461 | 9.71359529335793 | 9.85324720631978
Europe and Central Asia (IFC classification) | CEU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Switzerland | CHE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.20000004768372 | 2.29999995231628 | 3 | 3.5 | 2.90000009536743 | 3.40000009536743 | 4.30000019073486 | 3.20000004768372 | 2.59999990463257 | 2.29999995231628 | 1.70000004768372 | 2.79999995231628 | 3.79999995231628 | 3.90000009536743 | 3.90000009536743 | 3.40000009536743 | 2.90000009536743 | 2.79999995231628 | 3.79999995231628 | 4.19999980926514 | 3.70000004768372 | 3.90000009536743
Channel Islands | CHI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Chile | CHL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.30000019073486 | 7.90000009536743 | 7.59999990463257 | 7 | 6.30000019073486 | 5.59999990463257 | 5.40000009536743 | 5.69999980926514 | 9.39999961853027 | 8.69999980926514 | 8.80000019073486 | 8.60000038146973 | 7.90000009536743 | 7.90000009536743 | 7 | 6.69999980926514 | 6.30000019073486 | 6.69999980926514 | 9 | 7.09999990463257 | 6 | 5.40000009536743
China | CHN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.5 | 5 | 4.90000009536743 | 4.90000009536743 | 5.09999990463257 | 5.19999980926514 | 5.19999980926514 | 5.30000019073486 | 5.30000019073486 | 5.09999990463257 | 5.09999990463257 | 5 | 4.90000009536743 | 4.90000009536743 | 4.69999980926514 | 4.5 | 4.30000019073486 | 5 | 5 | 4.80000019073486 | 4.90000009536743 | 5.09999990463257
Cote d'Ivoire | CIV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 7.19999980926514 | 6.5 | 5.80000019073486 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.5
Latin America and the Caribbean (IFC classification) | CLA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Middle East and North Africa (IFC classification) | CME | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Cameroon | CMR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.90000009536743 | 4.90000009536743 | 4.90000009536743 | 4.90000009536743 | 3.09999990463257 | 7.30000019073486 | 7 | 6.69999980926514 | 6.30000019073486 | 5.40000009536743 | 6.80000019073486 | 5 | 5 | 4.09999990463257 | 4 | 3.40000009536743 | 3.70000004768372 | 4.09999990463257 | 4.30000019073486 | 3.40000009536743 | 3.40000009536743 | 3.40000009536743
Congo, Rep. | COG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 7 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486
Colombia | COL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.6999998092651 | 9 | 9.39999961853027 | 9.69999980926514 | 9.80000019073486 | 11.3999996185303 | 10.1999998092651 | 11 | 11.8999996185303 | 12.8000001907349 | 11.5 | 11.5 | 9.5 | 9.5 | 8.89999961853027 | 8.39999961853027 | 10 | 10.1999998092651 | 9.39999961853027 | 9.10000038146973 | 8.39999961853027 | 8
Comoros | COM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.09999990463257 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7 | 7 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743 | 6.80000019073486
Cabo Verde | CPV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.5 | 7.5 | 7.40000009536743
Costa Rica | CRI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.80000019073486 | 3.5 | 3.59999990463257 | 3.5 | 4.5 | 5.19999980926514 | 4.80000019073486 | 4.30000019073486 | 4.90000009536743 | 4.40000009536743 | 5.19999980926514 | 5.5 | 5.80000019073486 | 5.40000009536743 | 5 | 4.40000009536743 | 3.20000004768372 | 4.09999990463257 | 6.40000009536743 | 5.90000009536743 | 6.09999990463257 | 5.90000009536743
South Asia (IFC classification) | CSA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Caribbean small states | CSS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.98210230271575 | 11.90793168466113 | 13.13104368648987 | 12.96551901131717 | 14.09073684883317 | 12.616990967939 | 11.87282725145445 | 11.56939422111381 | 11.22563374161474 | 10.37065751166116 | 11.25952629013444 | 10.66732721791242 | 9.765166539240578 | 9.629407931767267 | 9.294688674161812 | 8.629198831261565 | 7.324149568824682 | 7.686455743839826 | 8.876877026038125 | 9.492441686297802 | 9.574409897769373 | 9.92384093188225
Cuba | CUB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.29999995231628 | 3.5 | 3.70000004768372 | 3.09999990463257 | 7.5 | 6.90000009536743 | 6.40000009536743 | 5.59999990463257 | 5.69999980926514 | 4.80000019073486 | 3.70000004768372 | 3 | 2.09999990463257 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 1.39999997615814 | 1.5 | 2.20000004768372 | 2.09999990463257 | 2.20000004768372
[NAME] | CUW | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Cayman Islands | CYM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Cyprus | CYP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.30000019073486 | 1.89999997615814 | 8.39999961853027 | 3 | 3.29999995231628 | 3.59999990463257 | 2.79999995231628 | 3.40000009536743 | 5 | 3.29999995231628 | 2.70000004768372 | 2.70000004768372 | 3.79999995231628 | 3.59999990463257 | 4.5 | 3.90000009536743 | 3.5 | 3.20000004768372 | 5.30000019073486 | 6.09999990463257 | 8.10000038146973 | 12.3999996185303
Czech Republic | CZE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.5 | 3 | 3.40000009536743 | 3.59999990463257 | 3.40000009536743 | 3.29999995231628 | 3.90000009536743 | 5 | 7.30000019073486 | 7.30000019073486 | 6.80000019073486 | 5.90000009536743 | 6.09999990463257 | 7 | 6.40000009536743 | 5.80000019073486 | 4.19999980926514 | 3.5 | 5.80000019073486 | 6.40000009536743 | 5.80000019073486 | 6
Germany | DEU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.5 | 5.40000009536743 | 6.59999990463257 | 7.19999980926514 | 7.19999980926514 | 8.30000019073486 | 9.19999980926514 | 8.69999980926514 | 8.10000038146973 | 7.5 | 7.80000019073486 | 8.69999980926514 | 9.60000038146973 | 10.5 | 11.3000001907349 | 10.3000001907349 | 8.5 | 7.40000009536743 | 8.10000038146973 | 7.5 | 6.19999980926514 | 5.59999990463257
Djibouti | DJI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Dominica | DMA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Denmark | DNK | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.30000019073486 | 8.30000019073486 | 10.3999996185303 | 7.19999980926514 | 5.59999990463257 | 5.5 | 4.5 | 3.90000009536743 | 4.5 | 4.09999990463257 | 3.59999990463257 | 4.30000019073486 | 4.80000019073486 | 5.09999990463257 | 4.40000009536743 | 3.29999995231628 | 3.5 | 3.20000004768372 | 6.59999990463257 | 8.39999961853027 | 7.69999980926514 | 7.5
Dominican Republic | DOM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8999996185303 | 12.6000003814697 | 12.3000001907349 | 10.3999996185303 | 10.5 | 10.8000001907349 | 9.89999961853027 | 9.19999980926514 | 8.80000019073486 | 8.80000019073486 | 11.8999996185303 | 14.5 | 10.6999998092651 | 11.8000001907349 | 11.5 | 10.3999996185303 | 9.39999961853027 | 8.80000019073486 | 9.60000038146973 | 8.39999961853027 | 8.89999961853027 | 8.80000019073486
Algeria | DZA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.2999992370605 | 20.3999996185303 | 20.6000003814697 | 21.6000003814697 | 24.5 | 25.2000007629395 | 22.3999996185303 | 22.7000007629395 | 22.3999996185303 | 26.1000003814697 | 23.7999992370605 | 22.7999992370605 | 21.1000003814697 | 19.7000007629395 | 13.3999996185303 | 10.8000001907349 | 12.1000003814697 | 10 | 8.60000038146973 | 8.10000038146973 | 8 | 8
East Asia & Pacific (developing only) | EAP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.284249024519474 | 4.559590398792722 | 4.613411773764033 | 4.631632602923085 | 4.678561859234217 | 4.778038858479709 | 4.876267425553141 | 5.175849564605151 | 5.244850226085556 | 5.117996144478267 | 5.217725089176979 | 5.249940383538824 | 5.148537411488678 | 5.20182858025625 | 5.060480618094761 | 4.837087613823987 | 4.597743248791305 | 5.066139718524611 | 5.065828771554429 | 4.715617250413169 | 4.6972978264393 | 4.841775767026248
East Asia & Pacific (all income levels) | EAS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.025198052804166 | 4.406567108189814 | 4.487878884521725 | 4.505949766908313 | 4.548274359868126 | 4.65737116398161 | 4.753429334425705 | 5.18897576834897 | 5.282690180127426 | 5.120443552466601 | 5.218530735467874 | 5.257187720213476 | 5.15835602394691 | 5.160887627817992 | 5.009906903274517 | 4.780833647364568 | 4.53252248795858 | 4.959016564617269 | 5.066244862511971 | 4.741279801180798 | 4.679209671749444 | 4.794868214106711
Europe & Central Asia (developing only) | ECA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.584840133202768 | 9.767800480975469 | 10.43729662333727 | 9.69607837499453 | 9.205487196099005 | 9.153566345120455 | 9.279699631160955 | 9.837875907821386 | 10.36722160533499 | 9.953568333232845 | 10.52603302029573 | 10.75032225541774 | 10.4894023665806 | 10.71449004149055 | 10.17638701757518 | 9.963201881698167 | 9.65559836286076 | 9.612836284948104 | 11.07826563751353 | 10.50204247677993 | 9.757176988551441 | 9.586362919225685
Europe & Central Asia (all income levels) | ECS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.763730413647838 | 8.090285794271002 | 9.21151565875575 | 9.709005844243888 | 9.469599809781029 | 9.539731053243958 | 9.760415877500972 | 9.775390739672378 | 9.796826810967362 | 9.015126347146515 | 8.686852488939184 | 8.80090881348269 | 8.905490119832736 | 8.947838123797604 | 8.595805480259989 | 8.139483017739744 | 7.345810063176469 | 7.333326395297044 | 9.517215469692506 | 9.527229042764564 | 9.082558821698242 | 9.35578798980276
Ecuador | ECU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.5 | 5.30000019073486 | 4.40000009536743 | 6 | 4.40000009536743 | 4.69999980926514 | 5.5 | 4 | 4.80000019073486 | 5.69999980926514 | 6.5 | 6.59999990463257 | 7.40000009536743 | 5.30000019073486 | 5.19999980926514 | 5 | 4 | 4.80000019073486 | 5.19999980926514 | 4 | 3.29999995231628 | 3.59999990463257
Egypt, Arab Rep. | EGY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 5.19999980926514 | 6.40000009536743 | 6.40000009536743 | 6.69999980926514 | 5.40000009536743 | 5.09999990463257 | 5 | 5 | 5.5 | 5.59999990463257 | 6.30000019073486 | 6.40000009536743 | 6.69999980926514 | 6.90000009536743 | 6.5 | 5.59999990463257 | 4.90000009536743 | 5 | 4.80000019073486 | 7.09999990463257 | 7
Euro area | EMU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.66823431744252 | 7.381872978144295 | 9.08147906639167 | 9.933873177488108 | 9.509393453883964 | 9.820120434656815 | 9.861093337786045 | 9.24419474125287 | 8.640340499382743 | 7.764239553204122 | 7.044746339595296 | 7.536619678108273 | 7.836064819037308 | 8.143974185499609 | 8.112859330457773 | 7.419313828809949 | 6.615976434046243 | 6.849330681701534 | 9.344706547811862 | 9.948198233296178 | 9.937398087188791 | 11.24902062462862
Eritrea | ERI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 7.69999980926514 | 7.80000019073486 | 7.90000009536743 | 7.80000019073486 | 7.90000009536743 | 8 | 7.90000009536743 | 8 | 7.90000009536743 | 8.10000038146973 | 8 | 8 | 8 | 8 | 7.90000009536743 | 7.90000009536743 | 7.69999980926514 | 7.80000019073486 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514
Spain | ESP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12 | 14.1999998092651 | 18.7999992370605 | 19.7000007629395 | 18.1000003814697 | 17.6000003814697 | 16.1000003814697 | 13.8999996185303 | 11.1999998092651 | 9.80000019073486 | 7.59999990463257 | 8.19999980926514 | 8.30000019073486 | 8.30000019073486 | 7.19999980926514 | 6.40000009536743 | 6.5 | 10.1999998092651 | 17.7999992370605 | 19.8999996185303 | 21.2999992370605 | 24.8999996185303
Estonia | EST | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.60000002384186 | 4 | 7.19999980926514 | 8.30000019073486 | 10.5 | 10.6999998092651 | 11.1999998092651 | 10.5 | 12.8999996185303 | 14.6000003814697 | 11.6999998092651 | 10.3000001907349 | 11 | 11.3000001907349 | 8.80000019073486 | 6.19999980926514 | 5.40000009536743 | 5.80000019073486 | 16.8999996185303 | 19.5 | 13.1000003814697 | 11
Ethiopia | ETH | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 3.5 | 3.59999990463257 | 3.5 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 3.90000009536743 | 3.59999990463257 | 3.29999995231628 | 3 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.70000004768372 | 2.79999995231628
European Union | EUU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.598082376702137 | 8.489074159719793 | 10.0015730723909 | 10.40608528625702 | 9.721932841222914 | 9.66990305477717 | 9.297598676967477 | 8.71673011190512 | 8.60027595003052 | 8.21324502380039 | 7.857579411022954 | 8.305591594321418 | 8.358156431464764 | 8.508436967573624 | 8.288013214022385 | 7.589514899611158 | 6.599607458522617 | 6.538954861801016 | 8.988064962996027 | 9.650197087859052 | 9.563768863068228 | 10.45448523471289
Fragile and conflict affected situations | FCS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.855051014956146 | 7.902159244356424 | 7.603279190234665 | 7.721621052832617 | 7.546504262844972 | 7.665683913068536 | 7.807408485270293 | 7.710704734998143 | 7.345693824689067 | 7.506080964815621 | 7.753587865600013 | 7.798454258525473 | 8.590917932957437 | 8.324863690274595 | 7.538141846007382 | 7.483721787193248 | 7.470144608433206 | 7.604178036546686 | 7.391956319701486 | 7.536173564356185 | 7.452408966954881 | 7.510361236757127
Finland | FIN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 13.3000001907349 | 17.7999992370605 | 17.7999992370605 | 15.3999996185303 | 14 | 12.1999998092651 | 10.8000001907349 | 9.69999980926514 | 9 | 8.5 | 8.89999961853027 | 9 | 8.60000038146973 | 8.10000038146973 | 7.30000019073486 | 6.40000009536743 | 5.90000009536743 | 8.89999961853027 | 9 | 8.30000019073486 | 8.10000038146973
Fiji | FJI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.90000009536743 | 4.5 | 4.90000009536743 | 4.69999980926514 | 4.40000009536743 | 4.80000019073486 | 5.40000009536743 | 6.80000019073486 | 6.5 | 6.19999980926514 | 4.90000009536743 | 4.69999980926514 | 6.80000019073486 | 3.79999995231628 | 3.70000004768372 | 5.19999980926514 | 6.80000019073486 | 7.19999980926514 | 6.90000009536743 | 6.80000019073486 | 6.69999980926514 | 6.59999990463257
France | FRA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.30000019073486 | 8.19999980926514 | 9.69999980926514 | 11.1000003814697 | 10.1000003814697 | 10.6999998092651 | 11.1000003814697 | 10.3999996185303 | 10.3999996185303 | 8.60000038146973 | 7 | 7.80000019073486 | 7.69999980926514 | 8.19999980926514 | 8 | 8.10000038146973 | 7.5 | 6.90000009536743 | 8.89999961853027 | 9 | 8.80000019073486 | 9.80000019073486
Faeroe Islands | FRO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Micronesia, Fed. [NAME]. | FSM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Gabon | GAB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 16.3999996185303 | 18 | 19.6000003814697 | 18.7999992370605 | 18 | 17.3999996185303 | 16.7999992370605 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 16.8999996185303 | 17 | 17 | 17 | 17 | 17.1000003814697 | 16.3999996185303 | 15.6999998092651 | 14.1999998092651 | 14.1999998092651 | 15.3000001907349
United Kingdom | GBR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.39999961853027 | 11.6999998092651 | 12.6000003814697 | 11.6000003814697 | 10.1999998092651 | 9.80000019073486 | 8.19999980926514 | 6.90000009536743 | 6.80000019073486 | 6.19999980926514 | 5.30000019073486 | 5.69999980926514 | 5.5 | 5 | 5.09999990463257 | 5.90000009536743 | 5.69999980926514 | 5.80000019073486 | 8.80000019073486 | 8.69999980926514 | 8.5 | 8.39999961853027
Georgia | GEO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.3000001907349 | 12.3000001907349 | 12.8000001907349 | 13.3999996185303 | 15.3000001907349 | 12.8000001907349 | 12.6999998092651 | 12.8999996185303 | 15.1999998092651 | 11.1000003814697 | 11.6000003814697 | 14 | 11.5 | 13.3000001907349 | 14.8000001907349 | 15.3000001907349 | 14 | 16.8999996185303 | 18 | 17.3999996185303 | 16.1000003814697 | 16
Ghana | GHA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.69999980926514 | 3.5 | 8.60000038146973 | 5 | 2.90000009536743 | 8.89999961853027 | 5 | 5.59999990463257 | 9.30000019073486 | 10.1000003814697 | 9.39999961853027 | 9.10000038146973 | 5.80000019073486 | 4.80000019073486 | 3.09999990463257 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5
Guinea | GIN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5 | 3.5
Gambia, The | GMB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743 | 7.5 | 7.5 | 7.5 | 7.40000009536743 | 7.5 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486
Guinea-Bissau | GNB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 7.09999990463257 | 7.19999980926514 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.09999990463257
Equatorial Guinea | GNQ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.40000009536743 | 7.09999990463257 | 7.09999990463257 | 7 | 7.40000009536743 | 8 | 7 | 7.09999990463257 | 7.09999990463257 | 7.5 | 7.19999980926514 | 7.30000019073486 | 7.5 | 7.40000009536743 | 7.30000019073486 | 7.5 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743
Greece | GRC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.90000009536743 | 5.09999990463257 | 6 | 6.19999980926514 | 6.40000009536743 | 6.30000019073486 | 6.5 | 7.19999980926514 | 7.80000019073486 | 7.5 | 6.90000009536743 | 6.90000009536743 | 6.30000019073486 | 6.69999980926514 | 6.19999980926514 | 5.69999980926514 | 5.19999980926514 | 5.09999990463257 | 6.90000009536743 | 10 | 15 | 21.3999996185303
Grenada | GRD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Greenland | GRL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Guatemala | GTM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.09999990463257 | 3.40000009536743 | 2.20000004768372 | 2 | 3.70000004768372 | 2.79999995231628 | 4 | 3.5 | 1.70000004768372 | 1.20000004768372 | 1.20000004768372 | 2.79999995231628 | 2.5 | 2.79999995231628 | 2.59999990463257 | 2.5 | 2.20000004768372 | 2.5 | 2.70000004768372 | 3.09999990463257 | 3.59999990463257 | 3.59999990463257
Guam | GUM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Guyana | GUY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.5 | 8.5 | 12.6999998092651 | 19.1000003814697 | 28.6000003814697 | 24.1000003814697 | 20.2000007629395 | 22.5 | 20.7999992370605 | 15.8000001907349 | 25.8999996185303 | 21.7000007629395 | 22.5 | 23.8999996185303 | 23.8999996185303 | 25.8999996185303 | 17.5 | 17.2000007629395 | 16.8999996185303 | 18.7999992370605 | 18.7999992370605 | 19.3999996185303
High income | HIC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.154949103057421 | 6.861084573722222 | 7.388135417652125 | 7.57026500933856 | 7.286359776528006 | 7.312248190271812 | 7.294204027783123 | 7.369087934891264 | 7.290735288756085 | 6.657051306109429 | 6.573644959892702 | 6.921446800558945 | 7.103853010352419 | 6.802712237993579 | 6.476240296113595 | 6.015811004936519 | 5.473313470593365 | 5.795542138342509 | 8.307698983363865 | 8.390337891301469 | 7.774119675316023 | 7.686235620830948
Hong Kong SAR, China | HKG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.89999997615814 | 2.09999990463257 | 2 | 2 | 3.40000009536743 | 3.09999990463257 | 2.29999995231628 | 5 | 6.90000009536743 | 5.59999990463257 | 6 | 8.39999961853027 | 9.19999980926514 | 7.69999980926514 | 6.59999990463257 | 5.69999980926514 | 4.59999990463257 | 4.09999990463257 | 6 | 5 | 4 | 3.79999995231628
Honduras | HND | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.09999990463257 | 2.79999995231628 | 2.79999995231628 | 2.79999995231628 | 2.79999995231628 | 3.79999995231628 | 2.79999995231628 | 3.40000009536743 | 3.79999995231628 | 3.79999995231628 | 3.90000009536743 | 3.5 | 4.59999990463257 | 4.80000019073486 | 3.20000004768372 | 2.70000004768372 | 2.5 | 2.70000004768372 | 2.79999995231628 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257
Heavily indebted poor countries (HIPC) | HPC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.956135568678992 | 5.882830340003107 | 6.09063760244563 | 5.920771054101325 | 5.793191046727041 | 6.096009658531969 | 5.862936076411311 | 5.827291675051502 | 5.917256442993365 | 5.993744792441841 | 6.125103720991566 | 5.938891905692849 | 5.818155570700118 | 5.616683663419679 | 5.422648444245874 | 5.478651867737273 | 5.418011654517082 | 5.462234961788758 | 5.519377490399785 | 5.474269550460658 | 5.453572730493546 | 5.481896842251507
Croatia | HRV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11 | 9.30000019073486 | 8.30000019073486 | 8.60000038146973 | 8.89999961853027 | 9.10000038146973 | 9 | 10.6000003814697 | 13 | 15.5 | 19.7999992370605 | 13.1999998092651 | 12.5 | 12.3000001907349 | 11.5 | 9.80000019073486 | 8.30000019073486 | 6.90000009536743 | 7.90000009536743 | 11.3000001907349 | 13.6000003814697 | 15.8999996185303
Haiti | HTI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.10000038146973 | 9.60000038146973 | 10 | 11.1999998092651 | 7.69999980926514 | 8.5 | 8.69999980926514 | 8.69999980926514 | 6.19999980926514 | 6.5 | 6.80000019073486 | 6.69999980926514 | 6.69999980926514 | 7.30000019073486 | 6.5 | 6.40000009536743 | 6.19999980926514 | 6.5 | 6.19999980926514 | 7.5 | 5.69999980926514 | 6.09999990463257
Hungary | HUN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.5 | 11 | 13.6000003814697 | 12.1000003814697 | 11.3000001907349 | 10.6999998092651 | 9.5 | 8.5 | 7.5 | 7 | 6.30000019073486 | 6.09999990463257 | 6.09999990463257 | 6.09999990463257 | 7 | 7.19999980926514 | 7.09999990463257 | 7.59999990463257 | 10.3000001907349 | 11.6000003814697 | 11 | 11.1999998092651
Indonesia | IDN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.69999980926514 | 2.70000004768372 | 3.70000004768372 | 4.40000009536743 | 3.5 | 3.79999995231628 | 4.19999980926514 | 5 | 6 | 5.80000019073486 | 6.80000019073486 | 7.90000009536743 | 7.69999980926514 | 8.19999980926514 | 9.5 | 8.60000038146973 | 8 | 7.59999990463257 | 7.5 | 6 | 5.59999990463257 | 5.59999990463257
Isle of Man | IMN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
India | IND | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4 | 4 | 4.19999980926514 | 3.59999990463257 | 3.90000009536743 | 3.90000009536743 | 4.40000009536743 | 3.70000004768372 | 3.79999995231628 | 4.30000019073486 | 3.90000009536743 | 4.19999980926514 | 4.09999990463257 | 3.90000009536743 | 4.09999990463257 | 4.09999990463257 | 3.79999995231628 | 4.09999990463257 | 4 | 3.29999995231628 | 3.20000004768372 | 3.09999990463257
Not classified | INX | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Ireland | IRL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.3000001907349 | 14.8999996185303 | 15.3999996185303 | 14.5 | 11.8999996185303 | 11.6999998092651 | 10.1999998092651 | 7.90000009536743 | 5.90000009536743 | 4.40000009536743 | 3.79999995231628 | 4.5 | 4.80000019073486 | 5 | 4.59999990463257 | 4.59999990463257 | 4.80000019073486 | 7.09999990463257 | 15 | 17 | 17.7000007629395 | 17.6000003814697
Iran, Islamic Rep. | IRN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.1000003814697 | 11 | 10.6000003814697 | 10.3000001907349 | 9.89999961853027 | 9.89999961853027 | 10.1000003814697 | 10.1000003814697 | 10.1000003814697 | 11.6000003814697 | 10.8999996185303 | 11.3000001907349 | 10.6999998092651 | 9 | 10.5 | 10.1000003814697 | 9.30000019073486 | 9.10000038146973 | 10.8000001907349 | 11.8999996185303 | 11.6999998092651 | 11.6000003814697
Iraq | IRQ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.8999996185303 | 17.6000003814697 | 15.1999998092651 | 16 | 16.7000007629395 | 17.5 | 17.3999996185303 | 17.2000007629395 | 16.2999992370605 | 16.3999996185303 | 16.6000003814697 | 16.3999996185303 | 29.1000003814697 | 27.3999996185303 | 16.1000003814697 | 15.6999998092651 | 15.1000003814697 | 13.6999998092651 | 13.6000003814697 | 13.6000003814697 | 13.6000003814697 | 13.6000003814697
Iceland | ISL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.29999995231628 | 3.79999995231628 | 5 | 5.09999990463257 | 4.80000019073486 | 3.40000009536743 | 3.29999995231628 | 2.29999995231628 | 1.39999997615814 | 1.79999995231628 | 2 | 3.59999990463257 | 3.59999990463257 | 3.20000004768372 | 2.59999990463257 | 2.90000009536743 | 2.29999995231628 | 3.29999995231628 | 8.60000038146973 | 8.30000019073486 | 7.80000019073486 | 6.30000019073486
Israel | ISR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.60000038146973 | 9.19999980926514 | 8.5 | 6.19999980926514 | 5.59999990463257 | 5.80000019073486 | 6.80000019073486 | 8 | 8.5 | 8.5 | 9 | 10.1000003814697 | 10.1999998092651 | 9.5 | 8.5 | 7.90000009536743 | 6.80000019073486 | 5.80000019073486 | 7.5 | 6.80000019073486 | 5.59999990463257 | 6.80000019073486
Italy | ITA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.80000019073486 | 6.80000019073486 | 7.69999980926514 | 8.69999980926514 | 9.10000038146973 | 9.39999961853027 | 9.39999961853027 | 9.5 | 8.89999961853027 | 8.39999961853027 | 7.40000009536743 | 7 | 6.90000009536743 | 6.40000009536743 | 6.19999980926514 | 5.40000009536743 | 4.90000009536743 | 5.5 | 6.80000019073486 | 7.59999990463257 | 7.59999990463257 | 9.89999961853027
Jamaica | JAM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.69999980926514 | 9.30000019073486 | 10.8000001907349 | 9.5 | 10.8000001907349 | 10.1000003814697 | 10.5 | 10 | 10 | 10 | 10.1000003814697 | 10 | 7.5 | 8 | 7.5 | 6.59999990463257 | 6.5 | 7.40000009536743 | 8.69999980926514 | 9.39999961853027 | 9.39999961853027 | 10.3999996185303
Jordan | JOR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.6000003814697 | 15.8999996185303 | 17.2999992370605 | 16 | 12.6999998092651 | 11.8999996185303 | 11.1999998092651 | 11.6999998092651 | 11.1000003814697 | 12.3000001907349 | 14.6000003814697 | 14.6999998092651 | 14.1000003814697 | 11.6999998092651 | 12.8000001907349 | 11.8999996185303 | 10.1999998092651 | 10 | 10.1999998092651 | 10.1999998092651 | 10.8999996185303 | 10.3000001907349
Japan | JPN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.89999997615814 | 2.09999990463257 | 2.40000009536743 | 2.79999995231628 | 3.09999990463257 | 3.40000009536743 | 3.40000009536743 | 4.09999990463257 | 4.80000019073486 | 5 | 5.19999980926514 | 5.59999990463257 | 5.5 | 4.90000009536743 | 4.59999990463257 | 4.30000019073486 | 4 | 4.09999990463257 | 5.30000019073486 | 5.40000009536743 | 4.80000019073486 | 4.59999990463257
Kazakhstan | KAZ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 9.30000019073486 | 8.19999980926514 | 6 | 8.89999961853027 | 10.5 | 10.3999996185303 | 10.5 | 10.8000001907349 | 10.1999998092651 | 8.30000019073486 | 7.59999990463257 | 7.19999980926514 | 7.09999990463257 | 6.5 | 6.19999980926514 | 5.80000019073486 | 5.30000019073486 | 5.59999990463257 | 4.69999980926514 | 4.30000019073486 | 4.30000019073486
Kenya | [NAME] | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.89999961853027 | 8.89999961853027 | 8.89999961853027 | 8.80000019073486 | 8.80000019073486 | 8.80000019073486 | 8.69999980926514 | 8.69999980926514 | 8.69999980926514 | 8.60000038146973 | 8.60000038146973 | 8.60000038146973 | 8.60000038146973 | 8.5 | 8.5 | 8.5 | 8.39999961853027 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486 | 8.19999980926514 | 8.10000038146973
Kyrgyz Republic | KGZ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 7.30000019073486 | 7.40000009536743 | 7 | 7.59999990463257 | 7.59999990463257 | 7.40000009536743 | 8.69999980926514 | 7.40000009536743 | 6.80000019073486 | 7.09999990463257 | 11.1999998092651 | 9 | 7.90000009536743 | 7.40000009536743 | 7.80000019073486 | 7.59999990463257 | 7.5 | 7.40000009536743 | 7.69999980926514 | 7.5 | 7.40000009536743
Cambodia | KHM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.79999995231628 | 1.79999995231628 | 1.79999995231628 | 1.39999997615814 | 1.5 | 1.60000002384186 | 1.70000004768372 | 1.89999997615814 | 2.09999990463257 | 2.29999995231628 | 1.60000002384186 | 1.70000004768372 | 1.79999995231628 | 1.79999995231628 | 1.60000002384186 | 1.70000004768372 | 1.60000002384186 | 1.60000002384186 | 1.79999995231628 | 1.5 | 1.5 | 1.5
Kiribati | KIR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
St. Kitts and Nevis | KNA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Korea, Rep. | KOR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.79999995231628 | 2.79999995231628 | 3.40000009536743 | 2.90000009536743 | 2.40000009536743 | 2.40000009536743 | 2.90000009536743 | 7.90000009536743 | 7.30000019073486 | 5 | 4.59999990463257 | 3.70000004768372 | 3.79999995231628 | 4 | 4.09999990463257 | 3.90000009536743 | 3.70000004768372 | 3.59999990463257 | 4.09999990463257 | 4 | 3.70000004768372 | 3.40000009536743
Kosovo | KSV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Kuwait | KWT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.10000002384186 | 1 | 0.800000011920929 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.699999988079071 | 0.800000011920929 | 0.800000011920929 | 1.20000004768372 | 1.39999997615814 | 1.79999995231628 | 2 | 1.60000002384186 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 1.70000004768372 | 1.60000002384186
Latin America & Caribbean (developing only) | LAC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.611694161944902 | 5.493397705718224 | 5.588011084915852 | 5.937903825263055 | 6.886655653806994 | 6.894367596436226 | 6.479922534133787 | 6.682406943339979 | 7.092540075944488 | 7.249135902314973 | 7.394477709744702 | 7.542684227598134 | 7.364509904098271 | 6.678017987031299 | 6.43710769992903 | 5.822456739862799 | 5.539374935231676 | 5.201070556424047 | 6.148142461931865 | 5.929415502693329 | 5.468137729268852 | 5.455771043986509
Lao PDR | LAO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 2.79999995231628 | 2.90000009536743 | 2.90000009536743 | 3 | 2.20000004768372 | 2.29999995231628 | 2.29999995231628 | 2.20000004768372 | 2.20000004768372 | 2.20000004768372 | 2.09999990463257 | 2.5 | 2.79999995231628 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186 | 1.60000002384186
Lebanon | LBN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8 | 7.90000009536743 | 7.80000019073486 | 8.5 | 7.80000019073486 | 7.90000009536743 | 7.90000009536743 | 7.90000009536743 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257 | 7.30000019073486 | 7.40000009536743 | 7.5 | 8.39999961853027 | 8.39999961853027 | 8.39999961853027 | 8.30000019073486 | 8.30000019073486 | 8.30000019073486
Liberia | LBR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.19999980926514 | 5.40000009536743 | 3.70000004768372 | 6.30000019073486 | 6.90000009536743 | 6 | 5.09999990463257 | 3.40000009536743 | 3.40000009536743 | 3.70000004768372
Libya | LBY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.09999990463257 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7 | 7 | 6.90000009536743 | 6.80000019073486 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.30000019073486
St. Lucia | LCA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Latin America & Caribbean (all income levels) | LCN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.790593494598013 | 5.699494970612191 | 5.784615745153971 | 6.080255279437989 | 6.96168173097182 | 6.946211089770998 | 6.521226158940178 | 6.725019739210452 | 7.211664595858077 | 7.324964083880886 | 7.465506683271708 | 7.597992672224152 | 7.403571529902983 | 6.740252645119912 | 6.486652415924961 | 5.888348414345156 | 5.598762649044351 | 5.283673669995289 | 6.279948837373118 | 6.020814253113344 | 5.539836558361046 | 5.50647426816273
Latin America and the Caribbean | LCR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Least developed countries: UN classification | LDC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.19456749027871 | 5.138149831289515 | 5.145033830547988 | 5.142656013070804 | 5.144497604823056 | 5.08820840448973 | 5.163068839761704 | 5.034231941385912 | 4.967675893949894 | 5.121246295591359 | 5.195391875156346 | 5.110929839594752 | 5.255334442105516 | 5.118130193667513 | 4.879431405963496 | 5.019813860506321 | 4.998775675307423 | 5.103618767102768 | 5.232245267505269 | 5.253933826936811 | 5.241809965433011 | 5.249340748166427
Low income | LIC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.446117120652027 | 4.385206376294156 | 4.396501156475243 | 4.326184132478147 | 4.37740431848931 | 4.53930732723994 | 4.610093392742721 | 4.521323840687376 | 4.449642812376097 | 4.530851453332014 | 4.615904043515211 | 4.514637164030057 | 4.603953630525842 | 4.431463772408775 | 4.158576484461522 | 4.314754368040647 | 4.301856508637395 | 4.417539325219147 | 4.568070224737743 | 4.553559722381404 | 4.535410946867056 | 4.536904500661917
[NAME] | LIE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
[NAME] | LKA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.8000001907349 | 10.5 | 9.69999980926514 | 9.39999961853027 | 8.60000038146973 | 8.10000038146973 | 7.69999980926514 | 6.59999990463257 | 6.59999990463257 | 5.80000019073486 | 5.90000009536743 | 6.5 | 5.90000009536743 | 6.09999990463257 | 5.69999980926514 | 4.80000019073486 | 4.40000009536743 | 3.70000004768372 | 4.5 | 3.59999990463257 | 3.5 | 3.5
Lower middle income | LMC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.214301443133824 | 4.861239168177132 | 5.154198449396409 | 4.787248316162781 | 4.803017163909056 | 4.853182983694729 | 5.246195166538291 | 5.012498017140767 | 5.262202250143059 | 5.67066693178241 | 5.568704599051141 | 5.877353344762959 | 5.749073475500452 | 5.667160978361699 | 5.719695549397809 | 5.534065185864625 | 5.163664852721106 | 5.272316318366626 | 5.241721320961414 | 4.689659749415478 | 4.62083418203465 | 4.577748271647868
Low & middle income | LMY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.770631348607377 | 5.365472911422581 | 5.486428201140829 | 5.311668535863641 | 5.456705504962467 | 5.539449691549493 | 5.648807146446427 | 5.651622196420669 | 5.800793406388802 | 5.973584662846383 | 5.953634915956101 | 6.06240177912166 | 5.990777468355959 | 5.82209692353918 | 5.656370386673535 | 5.437229751488289 | 5.184470203987082 | 5.397384957317088 | 5.567668998366192 | 5.235246726732242 | 5.147157056320843 | 5.176411146572806
[NAME] | LSO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 27.7000007629395 | 29.2000007629395 | 30.7000007629395 | 30 | 25.7999992370605 | 22.7999992370605 | 31.2000007629395 | 26.3999996185303 | 21.5 | 29.5 | 29.2000007629395 | 26.1000003814697 | 30.7000007629395 | 28.6000003814697 | 29 | 26 | 21.2000007629395 | 23.1000003814697 | 23.5 | 21.7000007629395 | 22.2999992370605 | 23.7000007629395
Lithuania | LTU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17.6000003814697 | 9.89999961853027 | 12.5 | 19.1000003814697 | 18.7000007629395 | 17.1000003814697 | 14.3000001907349 | 15.3999996185303 | 14.6999998092651 | 18.2000007629395 | 19.5 | 13.1999998092651 | 12.6000003814697 | 11.1000003814697 | 8.19999980926514 | 5.80000019073486 | 4.30000019073486 | 6 | 17.1000003814697 | 21.2000007629395 | 17.7000007629395 | 15
Luxembourg | LUX | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1.10000002384186 | 1.60000002384186 | 1.89999997615814 | 3 | 2.09999990463257 | 2.5 | 1.79999995231628 | 1.89999997615814 | 1.70000004768372 | 1.79999995231628 | 1.60000002384186 | 1.89999997615814 | 3 | 3.70000004768372 | 3.5 | 3.59999990463257 | 3.59999990463257 | 4.30000019073486 | 4.40000009536743 | 3.79999995231628 | 3.79999995231628 | 4.5
Latvia | LVA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.5 | 13.8999996185303 | 13.3999996185303 | 15 | 13.6000003814697 | 12.8000001907349 | 14.8000001907349 | 15.3999996185303 | 14.1999998092651 | 15 | 14.6000003814697 | 14.8000001907349 | 10.3999996185303 | 9.5 | 9.10000038146973 | 7.5 | 6.40000009536743 | 8 | 20.3999996185303 | 21.7000007629395 | 18.6000003814697 | 16
Macao SAR, China | MAC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.29999995231628 | 2.09999990463257 | 2.20000004768372 | 2.40000009536743 | 3.79999995231628 | 4.40000009536743 | 3.5 | 5.30000019073486 | 7.80000019073486 | 8.60000038146973 | 8.19999980926514 | 8 | 7.19999980926514 | 5.59999990463257 | 4.40000009536743 | 3.59999990463257 | 3.29999995231628 | 3.29999995231628 | 4.09999990463257 | 3.5 | 3 | 2.29999995231628
St. Martin (French part) | MAF | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Morocco | MAR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3000001907349 | 12 | 11.8000001907349 | 11.6000003814697 | 11.3999996185303 | 11.1999998092651 | 11 | 10.8000001907349 | 14.1000003814697 | 13.6999998092651 | 12.5 | 11.3000001907349 | 11.5 | 10.6000003814697 | 10.8000001907349 | 9.69999980926514 | 10.1000003814697 | 9.5 | 8.89999961853027 | 8.89999961853027 | 8.39999961853027 | 8.69999980926514
Mexico and Central America | MCA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Monaco | MCO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Moldova | MDA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.69999980926514 | 8 | 7.5 | 7.5 | 7.59999990463257 | 7.59999990463257 | 9.60000038146973 | 6.80000019073486 | 13.1999998092651 | 9.80000019073486 | 8.60000038146973 | 8.10000038146973 | 9.5 | 9.89999961853027 | 8.60000038146973 | 8.89999961853027 | 6.30000019073486 | 4.59999990463257 | 7.80000019073486 | 9 | 7.69999980926514 | 6.90000009536743
Madagascar | MDG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2 | 2.29999995231628 | 2 | 2.70000004768372 | 2.09999990463257 | 2 | 1.79999995231628 | 1.79999995231628 | 1.79999995231628 | 1.70000004768372 | 3 | 3.40000009536743 | 3.90000009536743 | 2.79999995231628 | 1.79999995231628 | 2.09999990463257 | 3.09999990463257 | 3.29999995231628 | 2.90000009536743 | 2.59999990463257 | 2.59999990463257 | 2.70000004768372
Maldives | MDV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.09999990463257 | 7 | 6.90000009536743 | 6.69999980926514 | 6.5 | 6.59999990463257 | 6.59999990463257 | 6.59999990463257 | 6.40000009536743 | 6.5 | 6.69999980926514 | 7 | 7.19999980926514 | 7.19999980926514 | 7.59999990463257 | 7.90000009536743 | 7.30000019073486 | 7.30000019073486 | 7.09999990463257 | 6.80000019073486 | 6.69999980926514 | 6.5
Middle East & North Africa (all income levels) | MEA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.92983550644053 | 10.40120916830423 | 10.30522584538547 | 10.30904756591837 | 10.48634615208491 | 10.4005742940182 | 10.183369554261 | 10.12679462034012 | 10.20864600942392 | 11.18319960099826 | 10.81690586176906 | 10.93283237858043 | 11.31651526633796 | 10.44433360584091 | 9.482256600044282 | 8.830973397469476 | 8.44239936511994 | 7.967269483216063 | 7.999727745892065 | 8.20990920433891 | 8.426861472404257 | 8.454668992886388
Mexico | MEX | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 2.70000004768372 | 2.90000009536743 | 4 | 6 | 4.5 | 3 | 2.90000009536743 | 2 | 2.20000004768372 | 2.20000004768372 | 2.5 | 2.59999990463257 | 3.09999990463257 | 3.40000009536743 | 3 | 3.20000004768372 | 3.29999995231628 | 5.40000009536743 | 5.19999980926514 | 5.30000019073486 | 4.80000019073486
Marshall Islands | MHL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Middle income | MIC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.928349580232166 | 5.483435996370749 | 5.619103686398804 | 5.432878259362727 | 5.590742835042522 | 5.664728622106852 | 5.77994721152317 | 5.795587521025199 | 5.973757911854292 | 6.159803384958399 | 6.127856022816936 | 6.265913369747874 | 6.174779872010506 | 6.007952074304045 | 5.857989003555751 | 5.589824498787466 | 5.305754782739623 | 5.53341045947401 | 5.70816735250281 | 5.332295329228235 | 5.235108612614807 | 5.269339201807429
Macedonia, FYR | MKD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 30.1000003814697 | 30 | 30.3999996185303 | 31.2999992370605 | 31.5 | 32.5999984741211 | 35.5999984741211 | 32.4000015258789 | 31.8999996185303 | 30.6000003814697 | 29.5 | 31.5 | 37 | 36.7999992370605 | 36.5 | 35.2999992370605 | 34.5 | 33.5 | 31.7999992370605 | 31.8999996185303 | 31.7999992370605 | 31.3999996185303
[NAME] | MLI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 6.5 | 6.59999990463257 | 6.69999980926514 | 6.90000009536743 | 6.59999990463257 | 6.40000009536743 | 6.5 | 6.30000019073486 | 6.40000009536743 | 6.5 | 6.5 | 6.69999980926514 | 6.80000019073486 | 6.59999990463257 | 6.40000009536743 | 6.59999990463257 | 6.5 | 6.5 | 6.19999980926514 | 6.19999980926514 | 6.09999990463257
Malta | MLT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 6.09999990463257 | 6.19999980926514 | 6.69999980926514 | 7 | 6.69999980926514 | 6.30000019073486 | 5.90000009536743 | 6.69999980926514 | 6.30000019073486 | 6.69999980926514 | 6.19999980926514 | 6.40000009536743 | 6.90000009536743 | 6.59999990463257 | 6.09999990463257 | 5.90000009536743 | 5.59999990463257 | 6.5 | 6.80000019073486 | 6.09999990463257 | 5.80000019073486
Myanmar | MMR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4 | 4.09999990463257 | 4.09999990463257 | 4.19999980926514 | 4.59999990463257 | 3.79999995231628 | 3.59999990463257 | 3.70000004768372 | 3.70000004768372 | 3.59999990463257 | 3.5 | 3.5 | 3.5 | 3.5 | 4 | 3.79999995231628 | 3.79999995231628 | 3.70000004768372 | 3.70000004768372
Middle East & North Africa (developing only) | MNA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.72913080570299 | 11.2186371501511 | 11.1452089650377 | 11.2426406191799 | 11.58838999167366 | 11.47074068514059 | 11.1541834691203 | 11.03631989978848 | 11.1486375658297 | 12.2711588809267 | 11.85371411554309 | 11.95492481961092 | 12.4481879310188 | 11.51996655993325 | 10.40104592610029 | 9.654085576943807 | 9.32617921270372 | 8.915809307044148 | 8.969403909647767 | 9.286046029232388 | 9.709324043771105 | 9.705174644572407
Montenegro | MNE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18 | 18.3999996185303 | 18.7000007629395 | 20.5 | 27.7000007629395 | 28.1000003814697 | 19.8999996185303 | 20.1000003814697 | 20.2999992370605 | 29.2000007629395 | 19.8999996185303 | 20.1000003814697 | 20.1000003814697 | 28.1000003814697 | 29.1000003814697 | 23.6000003814697 | 18.2999992370605 | 15.8999996185303 | 18 | 18.8999996185303 | 19.5 | 18.8999996185303
Mongolia | MNG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 6.59999990463257 | 6.69999980926514 | 7.40000009536743 | 8.5 | 7.30000019073486 | 7.69999980926514 | 7.5 | 7.40000009536743 | 6.90000009536743 | 7.40000009536743 | 7.80000019073486 | 7.09999990463257 | 7.5 | 7.90000009536743 | 6.40000009536743 | 7.19999980926514 | 5.90000009536743 | 5.59999990463257 | 7.09999990463257 | 5 | 5.59999990463257
Northern Mariana Islands | MNP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Mozambique | MOZ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 7.5 | 7.59999990463257 | 7.5 | 7.5 | 7.5 | 7.5 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486
Mauritania | MRT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 33.7000007629395 | 33.7000007629395 | 33.7999992370605 | 33.5999984741211 | 33.7999992370605 | 33.7000007629395 | 33.5 | 33.5999984741211 | 33.5999984741211 | 33.5 | 33.5 | 33.4000015258789 | 33.4000015258789 | 34.0999984741211 | 33.7000007629395 | 33.2999992370605 | 32.9000015258789 | 32.7000007629395 | 32.5999984741211 | 32.7000007629395 | 32.5999984741211 | 32.7000007629395
[NAME] | MUS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.90000009536743 | 6.69999980926514 | 6.59999990463257 | 6.5 | 7.40000009536743 | 6.59999990463257 | 5.90000009536743 | 6.40000009536743 | 6.90000009536743 | 5.59999990463257 | 4.5 | 4.69999980926514 | 5 | 5.80000019073486 | 5.80000019073486 | 5.5 | 5.30000019073486 | 4.09999990463257 | 4.40000009536743 | 4.59999990463257 | 5.19999980926514 | 5.19999980926514
[NAME] | MWI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6 | 5.90000009536743 | 6 | 5.90000009536743 | 6.09999990463257 | 6 | 6 | 6 | 6.19999980926514 | 6.30000019073486 | 6.30000019073486 | 6.5 | 6.59999990463257 | 6.69999980926514 | 6.80000019073486 | 6.59999990463257 | 6.40000009536743 | 6.19999980926514 | 6.19999980926514 | 6.30000019073486 | 6.30000019073486 | 6.30000019073486
Malaysia | MYS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.20000004768372 | 3.5 | 3.90000009536743 | 3.59999990463257 | 2.90000009536743 | 2.40000009536743 | 2.29999995231628 | 3.09999990463257 | 3.5 | 2.90000009536743 | 3.29999995231628 | 3.29999995231628 | 3.40000009536743 | 3.29999995231628 | 3.29999995231628 | 3.09999990463257 | 3.09999990463257 | 3.09999990463257 | 3.59999990463257 | 3.29999995231628 | 3 | 3
North America | NAC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.663056023664669 | 8.407813010637254 | 7.767326556009085 | 6.766159514900449 | 6.110657120257678 | 5.938972541173219 | 5.418324518779647 | 4.897770132998393 | 4.55872848800399 | 4.289094195746879 | 5.160492251234433 | 6.214005511161016 | 6.555326800561796 | 5.886762800513449 | 5.386434813154837 | 4.885043434041372 | 4.965780811862111 | 6.231355316821754 | 10.29499531837125 | 10.39839697966407 | 9.229246467960488 | 8.225162155358838
Namibia | NAM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 17 | 17.1000003814697 | 17.1000003814697 | 18 | 18.1000003814697 | 18.2000007629395 | 18.2999992370605 | 18.5 | 18.7000007629395 | 19.2000007629395 | 19.7999992370605 | 17.7000007629395 | 19.2000007629395 | 19.5 | 19.1000003814697 | 19.7999992370605 | 17.5 | 32.4000015258789 | 26.2999992370605 | 20.5 | 18 | 14.6999998092651
New Caledonia | NCL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
[NAME] | NER | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.5 | 5.40000009536743 | 5.5 | 5.5 | 5.5 | 5.5 | 5.5 | 5.5 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.40000009536743 | 5.5 | 5.40000009536743 | 5.5 | 5.5 | 5.5 | 5.5 | 5.5 | 5.59999990463257 | 5.5 | 5.59999990463257
Nigeria | NGA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.40000009536743 | 7.5 | 7.5 | 7.5 | 7.5 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.69999980926514 | 7.69999980926514 | 8 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514
Nicaragua | NIC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 6.5 | 5.69999980926514 | 2.70000004768372 | 3.59999990463257 | 4.69999980926514 | 6.19999980926514 | 5.19999980926514 | 5.80000019073486 | 7.40000009536743 | 7.09999990463257 | 6.80000019073486 | 7.90000009536743 | 6.59999990463257 | 5.59999990463257 | 5.40000009536743 | 5.19999980926514 | 6.5 | 7 | 8.39999961853027 | 8.10000038146973 | 8.10000038146973
Netherlands | NLD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.59999990463257 | 4.09999990463257 | 5.30000019073486 | 6.59999990463257 | 6.09999990463257 | 5.19999980926514 | 4.30000019073486 | 3.40000009536743 | 2.70000004768372 | 2.20000004768372 | 1.79999995231628 | 2.29999995231628 | 3.40000009536743 | 4.30000019073486 | 4.40000009536743 | 3.5 | 2.79999995231628 | 2.5 | 3.40000009536743 | 4.40000009536743 | 4.5 | 5.30000019073486
High income: nonOECD | NOC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.94604240527561 | 5.519236036724231 | 6.044736582929561 | 7.757694344037438 | 8.635472476430051 | 8.758976931067913 | 10.1267221725929 | 11.19616528746506 | 11.08345949113856 | 9.414902710149821 | 8.449007922434099 | 7.519087018722639 | 7.689873982605941 | 7.141988571588169 | 6.609707564099399 | 6.556721978223241 | 5.687106318707911 | 5.595478581057065 | 7.421033573826814 | 6.818373230614554 | 5.978633582647022 | 5.339203859155388
Norway | NOR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.80000019073486 | 6.59999990463257 | 6.59999990463257 | 5.90000009536743 | 5.09999990463257 | 4.80000019073486 | 3.79999995231628 | 3.09999990463257 | 3.40000009536743 | 3.59999990463257 | 3.5 | 4.09999990463257 | 4.90000009536743 | 4.80000019073486 | 4.80000019073486 | 3.5 | 2.59999990463257 | 2.79999995231628 | 3.59999990463257 | 4.09999990463257 | 3.40000009536743 | 3.59999990463257
Nepal | NPL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.29999995231628 | 2.09999990463257 | 2.29999995231628 | 2.5 | 2.70000004768372 | 5 | 4.19999980926514 | 3.29999995231628 | 2 | 3 | 4.19999980926514 | 3.09999990463257 | 2.40000009536743 | 2.29999995231628 | 2.79999995231628 | 2.90000009536743 | 2.90000009536743 | 3 | 3 | 3 | 3 | 3
New Zealand | NZL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.3000001907349 | 11.3999996185303 | 10.3999996185303 | 8.80000019073486 | 6.40000009536743 | 6.30000019073486 | 6.80000019073486 | 7.80000019073486 | 7.30000019073486 | 6.30000019073486 | 5.5 | 5.09999990463257 | 4.5 | 3.59999990463257 | 3.5 | 3.59999990463257 | 3.40000009536743 | 4.09999990463257 | 6.09999990463257 | 6.19999980926514 | 6.30000019073486 | 6.5
High income: OECD | OEC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.351229034297035 | 7.141616449908785 | 7.664629873030365 | 7.532434195417391 | 7.011498871159104 | 7.021768995005643 | 6.738371119931985 | 6.628738124448809 | 6.531059166895517 | 6.104279900324562 | 6.199914206322579 | 6.801377599379133 | 6.984248814202019 | 6.732715442432665 | 6.448427853802631 | 5.902141697882078 | 5.427323493624825 | 5.839360254840799 | 8.505287618908662 | 8.746562727533854 | 8.187376563437226 | 8.23128295091816
OECD members | OED | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.223957884658307 | 6.912660445741253 | 7.393251821199938 | 7.352859974883779 | 7.007206914958018 | 6.845485646003592 | 6.439675143748168 | 6.349644398810407 | 6.220632424184552 | 5.805783162406665 | 5.987892617990141 | 6.623377065040093 | 6.786844561570467 | 6.620064061943829 | 6.391453453459713 | 5.860850186184267 | 5.477525625119419 | 5.878428464694775 | 8.527218286566281 | 8.585379487960568 | 7.994430990242529 | 7.946765500484583
Oman | OMN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.30000019073486 | 6.09999990463257 | 6 | 5.90000009536743 | 5.90000009536743 | 6.09999990463257 | 6.30000019073486 | 6.5 | 6.80000019073486 | 6.90000009536743 | 6.90000009536743 | 6.80000019073486 | 6.69999980926514 | 6.59999990463257 | 6.59999990463257 | 6.59999990463257 | 6.69999980926514 | 6.69999980926514 | 6.80000019073486 | 6.90000009536743 | 6.90000009536743 | 6.90000009536743
Other small states | OSS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.94383159498937 | 14.07017479251989 | 14.43931695097383 | 14.43198511021196 | 14.33835263256878 | 13.78795034541844 | 14.34731408248925 | 13.74595176688862 | 13.4714256534834 | 14.86597007120828 | 14.44521023825136 | 13.70200048503997 | 14.4633090140328 | 14.4966312457662 | 14.40900940491058 | 13.33884389109497 | 12.38037978934802 | 14.39560130350194 | 13.28792965975867 | 12.18721414911814 | 11.95085040596151 | 11.86789781814007
Pakistan | PAK | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.30000019073486 | 3.79999995231628 | 3.40000009536743 | 3.5 | 3.70000004768372 | 3.79999995231628 | 3.90000009536743 | 4.09999990463257 | 4.5 | 5.59999990463257 | 5.80000019073486 | 6.19999980926514 | 6.19999980926514 | 6.19999980926514 | 6 | 5.19999980926514 | 4.19999980926514 | 4 | 4 | 4 | 4 | 4
Panama | PAN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.8000001907349 | 11.3000001907349 | 9.80000019073486 | 10.6999998092651 | 10.8000001907349 | 11.5 | 10.8000001907349 | 10.3000001907349 | 9 | 11.1000003814697 | 11.3000001907349 | 10.6999998092651 | 10.1000003814697 | 9 | 7.69999980926514 | 6.90000009536743 | 5 | 4.40000009536743 | 5.19999980926514 | 5.30000019073486 | 4.19999980926514 | 4.09999990463257
Peru | PER | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 6.09999990463257 | 7.09999990463257 | 4.80000019073486 | 4.40000009536743 | 5.59999990463257 | 4.90000009536743 | 4.80000019073486 | 4.69999980926514 | 5.80000019073486 | 4.40000009536743 | 5.30000019073486 | 6.40000009536743 | 5.19999980926514 | 5.19999980926514 | 4.69999980926514 | 4.5 | 4.59999990463257 | 4.5 | 4.09999990463257 | 4 | 4.09999990463257
Philippines | PHL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.10000038146973 | 7.80000019073486 | 8.19999980926514 | 7.69999980926514 | 7.69999980926514 | 6.90000009536743 | 7.5 | 9.19999980926514 | 9.39999961853027 | 11.1999998092651 | 10.5 | 11.3000001907349 | 11.1000003814697 | 11.3999996185303 | 7.69999980926514 | 8.30000019073486 | 7.59999990463257 | 7.5 | 7.5 | 7.30000019073486 | 7 | 6.90000009536743
Palau | PLW | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
[NAME] | PNG | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2 | 1.89999997615814 | 1.70000004768372 | 2.09999990463257 | 2.5 | 2.09999990463257 | 2.59999990463257 | 2.09999990463257 | 2.20000004768372 | 2.40000009536743 | 2.29999995231628 | 2.20000004768372 | 2.09999990463257 | 2.20000004768372 | 2.09999990463257 | 2.09999990463257 | 1.89999997615814 | 1.89999997615814 | 2 | 1.89999997615814 | 1.79999995231628 | 1.79999995231628
Poland | POL | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.80000019073486 | 12.1999998092651 | 12.6999998092651 | 13.1999998092651 | 12.3000001907349 | 11.1000003814697 | 9.60000038146973 | 9.39999961853027 | 11.8000001907349 | 14.5 | 17 | 19.2000007629395 | 19 | 18.2000007629395 | 16.6000003814697 | 13 | 9 | 6.5 | 7.80000019073486 | 9.30000019073486 | 9 | 9.39999961853027
Puerto Rico | PRI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18.8999996185303 | 19.2999992370605 | 19.6000003814697 | 16.8999996185303 | 16.2000007629395 | 15.1999998092651 | 15.1999998092651 | 14.8000001907349 | 13.6999998092651 | 12.1000003814697 | 13 | 13 | 12.6000003814697 | 11.5 | 12.3000001907349 | 11.6000003814697 | 12.1000003814697 | 13.1000003814697 | 16.8999996185303 | 18.7999992370605 | 18.1000003814697 | 18.1000003814697
Korea, Dem. Rep. | PRK | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.70000004768372 | 3.59999990463257 | 3.40000009536743 | 3.20000004768372 | 3.20000004768372 | 5.5 | 5.40000009536743 | 5.80000019073486 | 5.30000019073486 | 5.19999980926514 | 5.5 | 5.30000019073486 | 5.30000019073486 | 5.09999990463257 | 5.19999980926514 | 5.09999990463257 | 5 | 5.30000019073486 | 5.59999990463257 | 5 | 5 | 5.19999980926514
Portugal | PRT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.59999990463257 | 3.29999995231628 | 4.40000009536743 | 5.69999980926514 | 6 | 6 | 5.59999990463257 | 3.90000009536743 | 3.90000009536743 | 3.09999990463257 | 3.20000004768372 | 4.09999990463257 | 5.5 | 5.80000019073486 | 6.69999980926514 | 6.5 | 6.59999990463257 | 6.5 | 8.89999961853027 | 9.80000019073486 | 12.3999996185303 | 15.6999998092651
Paraguay | PRY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 4.09999990463257 | 5.69999980926514 | 5.09999990463257 | 3.09999990463257 | 3.79999995231628 | 4.5 | 4.5 | 6.09999990463257 | 6.69999980926514 | 6.59999990463257 | 8.89999961853027 | 6.59999990463257 | 6.19999980926514 | 4.90000009536743 | 5.59999990463257 | 4.19999980926514 | 4.40000009536743 | 5.40000009536743 | 4.80000019073486 | 4.59999990463257 | 5.19999980926514
Pacific island small states | PSS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
French Polynesia | PYF | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Qatar | QAT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.200000002980232 | 0.200000002980232 | 0.200000002980232 | 0.300000011920929 | 0.300000011920929 | 0.300000011920929 | 0.300000011920929 | 0.100000001490116 | 0.100000001490116 | 0.100000001490116 | 0.100000001490116 | 0.200000002980232 | 0.200000002980232 | 0.400000005960464 | 0.300000011920929 | 0.200000002980232 | 0.200000002980232 | 0.100000001490116 | 0.100000001490116 | 0.100000001490116 | 0.200000002980232 | 0.200000002980232
Romania | [NAME] | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.80000019073486 | 9 | 8.5 | 8.10000038146973 | 7.40000009536743 | 6.19999980926514 | 5.30000019073486 | 5.80000019073486 | 6.90000009536743 | 7.5 | 7.09999990463257 | 8.60000038146973 | 7.5 | 9.10000038146973 | 7.80000019073486 | 8.19999980926514 | 7.19999980926514 | 6.69999980926514 | 7.69999980926514 | 7.90000009536743 | 7.90000009536743 | 7.59999990463257
Russian Federation | RUS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.3999996185303 | 5.19999980926514 | 5.90000009536743 | 8.30000019073486 | 9.69999980926514 | 10 | 12.1999998092651 | 13.5 | 13.1999998092651 | 10.8000001907349 | 9.30000019073486 | 8.10000038146973 | 8.5 | 8 | 7.30000019073486 | 7.40000009536743 | 6.40000009536743 | 6.5 | 8.89999961853027 | 7.90000009536743 | 6.90000009536743 | 5.80000019073486
Rwanda | RWA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.899999976158142 | 0.800000011920929 | 0.899999976158142 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929 | 0.800000011920929
South Asia | SAS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.07700644869932 | 4.014515275861942 | 4.117882729757414 | 3.642764457242638 | 3.874195854706494 | 3.88601996602028 | 4.299339371224121 | 3.709197105272212 | 3.852731620214338 | 4.352590469124292 | 4.086006453101273 | 4.356620556755619 | 4.331046020099189 | 4.160233264982053 | 4.226746679350365 | 4.177905733158376 | 3.856323999718997 | 4.065309216588964 | 4.051241368117315 | 3.505829011425164 | 3.42937198803449 | 3.345029016960925
Saudi Arabia | SAU | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.30000019073486 | 4.90000009536743 | 4.69999980926514 | 4.30000019073486 | 4 | 3.90000009536743 | 4 | 4.19999980926514 | 3.59999990463257 | 3.90000009536743 | 3.90000009536743 | 4.19999980926514 | 3.90000009536743 | 3.40000009536743 | 4 | 4.69999980926514 | 4.19999980926514 | 3.59999990463257 | 3.59999990463257 | 3.59999990463257 | 2.70000004768372 | 3.09999990463257
[NAME] | SCE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Sudan | SDN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.5 | 13.6000003814697 | 13.5 | 13.3000001907349 | 13.1000003814697 | 12.8999996185303 | 12.6999998092651 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.8000001907349 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651 | 12.6999998092651
Senegal | SEN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.80000019073486 | 7.80000019073486 | 7.69999980926514 | 7.80000019073486 | 7.69999980926514 | 7.80000019073486 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.69999980926514 | 7.59999990463257 | 7.59999990463257
Singapore | SGP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 2 | 1.89999997615814 | 2 | 2 | 2.09999990463257 | 1.89999997615814 | 3.29999995231628 | 3.59999990463257 | 3.40000009536743 | 3.5 | 4.5 | 4.90000009536743 | 4.19999980926514 | 3.90000009536743 | 3.40000009536743 | 2.90000009536743 | 3 | 4.09999990463257 | 3 | 2.79999995231628 | 2.70000004768372
Solomon Islands | SLB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 4 | 4.59999990463257 | 4.40000009536743 | 4.19999980926514 | 4.80000019073486 | 4.90000009536743 | 4.80000019073486 | 4.80000019073486 | 5.90000009536743 | 5.30000019073486 | 4.90000009536743 | 4.19999980926514 | 4.09999990463257 | 3.79999995231628 | 4.30000019073486 | 4.09999990463257 | 4 | 4.80000019073486 | 4 | 3.79999995231628 | 4.09999990463257
Sierra Leone | SLE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.5 | 4.40000009536743 | 4.40000009536743 | 4.40000009536743 | 4.5 | 4.5 | 4.5 | 4.59999990463257 | 4.59999990463257 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5 | 4.5 | 4.59999990463257
El Salvador | SLV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.39999961853027 | 10 | 11.8999996185303 | 9.30000019073486 | 8.60000038146973 | 8.39999961853027 | 9.5 | 8.19999980926514 | 8.5 | 8.60000038146973 | 8.80000019073486 | 8 | 9.19999980926514 | 8.69999980926514 | 9.19999980926514 | 8.39999961853027 | 8.10000038146973 | 7.5 | 9.30000019073486 | 9 | 8.89999961853027 | 8.89999961853027
[NAME] | SMR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Somalia | SOM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.40000009536743
Serbia | SRB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11 | 12.1999998092651 | 14.6999998092651 | 13.3000001907349 | 11.6999998092651 | 11.6000003814697 | 12.1000003814697 | 12 | 12 | 11 | 11.1999998092651 | 12.1000003814697 | 13.3000001907349 | 16.2000007629395 | 18.2000007629395 | 17.8999996185303 | 15.6999998092651 | 11.8999996185303 | 14.3000001907349 | 16.7000007629395 | 16.6000003814697 | 17.2000007629395
Sub-Saharan Africa (developing only) | SSA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.515756034738502 | 7.527153991272726 | 7.794312443956526 | 7.277535066575499 | 7.031540746272802 | 7.483679689194642 | 7.469187875800168 | 7.505962701859599 | 7.570337344594692 | 7.88588326149007 | 7.850093173521332 | 7.748966878012838 | 7.57015933194343 | 7.204369487601514 | 6.955257605313951 | 6.891940143676268 | 6.822687405311089 | 6.980383450259914 | 7.063679802253673 | 6.981570123476295 | 6.936024298019575 | 6.968896614323333
South Sudan | SSD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Sub-Saharan Africa (all income levels) | SSF | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.515434008831465 | 7.5270247712775 | 7.793608641393167 | 7.277355799056827 | 7.031508946668877 | 7.483595329965879 | 7.469724754751471 | 7.505449070806237 | 7.569856543459791 | 7.885074769034753 | 7.849729068319656 | 7.748389707569313 | 7.569870927058165 | 7.204689470918313 | 6.9557423335872 | 6.892387263717956 | 6.823432765387571 | 6.980955977956321 | 7.064051760427093 | 6.982034066548687 | 6.936539596290859 | 6.969375100830969
Small states | SST | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13.10973691205654 | 12.8415674096673 | 13.48094411508484 | 13.41757390858997 | 13.68513626949262 | 12.91637338274003 | 13.08200736440476 | 12.66354163454526 | 12.37835091950577 | 13.0443733390355 | 12.981984385161 | 12.31810532099743 | 12.63421881541209 | 12.51192492943602 | 12.35949746546124 | 11.54169525630706 | 10.60360000749564 | 12.07205369735156 | 11.68179436754467 | 11.09927003635115 | 10.95944749017037 | 11.00474038882088
Sao Tome and Principe | STP | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Suriname | SUR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11.8000001907349 | 14 | 11.1000003814697 | 11.3000001907349 | 7 | 8.69999980926514 | 8.5 | 8.60000038146973 | 10.1999998092651 | 10 | 9.10000038146973 | 9.30000019073486 | 8.89999961853027 | 8.69999980926514 | 9.10000038146973 | 8.89999961853027 | 9 | 9.10000038146973 | 9.30000019073486 | 9 | 8.80000019073486 | 8.80000019073486
Slovak Republic | SVK | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.89999961853027 | 9.80000019073486 | 11.8000001907349 | 13.3000001907349 | 12.6000003814697 | 10.1999998092651 | 11.1999998092651 | 12.1999998092651 | 16.3999996185303 | 19 | 19.8999996185303 | 18.6000003814697 | 17.2999992370605 | 17.2999992370605 | 15.3999996185303 | 12.1999998092651 | 9.80000019073486 | 8.39999961853027 | 11.3999996185303 | 14.1999998092651 | 13.5 | 13.5
Slovenia | SVN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.59999990463257 | 3.90000009536743 | 10.5 | 9.30000019073486 | 7.5 | 7.19999980926514 | 6.40000009536743 | 7.30000019073486 | 7.30000019073486 | 6.80000019073486 | 5.40000009536743 | 5.90000009536743 | 6.30000019073486 | 5.80000019073486 | 6 | 4.90000009536743 | 3.90000009536743 | 4 | 5.90000009536743 | 7.40000009536743 | 8.10000038146973 | 8.30000019073486
Sweden | SWE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.59999990463257 | 6.80000019073486 | 11 | 11 | 10 | 10.5 | 10.6000003814697 | 8.89999961853027 | 7.59999990463257 | 6.30000019073486 | 5.40000009536743 | 5.69999980926514 | 6.40000009536743 | 7 | 7.90000009536743 | 6.90000009536743 | 6 | 6 | 8.69999980926514 | 8.69999980926514 | 7.90000009536743 | 8.19999980926514
Swaziland | SWZ | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21 | 20.8999996185303 | 20.7999992370605 | 20.7000007629395 | 20.8999996185303 | 20.7999992370605 | 20.2999992370605 | 20.3999996185303 | 20.5 | 20.5 | 20.6000003814697 | 20.6000003814697 | 20.7000007629395 | 20.7000007629395 | 20.7999992370605 | 20.7999992370605 | 20.8999996185303 | 20.8999996185303 | 20.7999992370605 | 20.7999992370605 | 20.6000003814697 | 20.3999996185303
Sint Maarten (Dutch part) | SXM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Seychelles | SYC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Syrian Arab Republic | SYR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.19999980926514 | 6.19999980926514 | 4.90000009536743 | 4.80000019073486 | 4.69999980926514 | 5.90000009536743 | 6.90000009536743 | 4.69999980926514 | 5 | 6.40000009536743 | 7.80000019073486 | 8.80000019073486 | 7.80000019073486 | 7.09999990463257 | 6.40000009536743 | 5.19999980926514 | 5.09999990463257 | 8.39999961853027 | 5.69999980926514 | 5.90000009536743 | 5.80000019073486 | 5.80000019073486
Turks and Caicos Islands | TCA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Chad | TCD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.19999980926514 | 7.09999990463257 | 7.09999990463257 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.19999980926514 | 7.30000019073486 | 7.19999980926514 | 7.19999980926514 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.5 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.30000019073486 | 7.40000009536743 | 7.30000019073486 | 7.30000019073486
Togo | TGO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.59999990463257 | 7.5 | 7.59999990463257 | 7.5 | 7.5 | 7.5 | 7.5 | 7.5 | 7.5 | 7.5 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.40000009536743 | 7.30000019073486
Thailand | THA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.70000004768372 | 1.39999997615814 | 1.5 | 1.10000002384186 | 1 | 1.10000002384186 | 0.899999976158142 | 3.40000009536743 | 3 | 2.5 | 2.70000004768372 | 1.89999997615814 | 1.60000002384186 | 1.60000002384186 | 1.39999997615814 | 1.29999995231628 | 1.29999995231628 | 1.29999995231628 | 1.5 | 1 | 0.699999988079071 | 0.699999988079071
Tajikistan | TJK | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11 | 10.3000001907349 | 10.8000001907349 | 10.5 | 10.8000001907349 | 10.8999996185303 | 11.1999998092651 | 11.3000001907349 | 11.1999998092651 | 11.3999996185303 | 11.5 | 11.5 | 11.6000003814697 | 11.6000003814697 | 11.5 | 11.5 | 11.6000003814697 | 11.6000003814697 | 11.3999996185303 | 11.3999996185303 | 11.3999996185303 | 11.3000001907349
Turkmenistan | TKM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11 | 10.8999996185303 | 10.8000001907349 | 10.5 | 10.8000001907349 | 10.6999998092651 | 10.5 | 11.1999998092651 | 11.5 | 11.6000003814697 | 11.6999998092651 | 11.5 | 11.6000003814697 | 11.5 | 11.3999996185303 | 11.3000001907349 | 11.3000001907349 | 11.5 | 11.1000003814697 | 11.1999998092651 | 11.3999996185303 | 11.3000001907349
Timor-Leste | TLS | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5.90000009536743 | 5.69999980926514 | 5.59999990463257 | 5.40000009536743 | 5.30000019073486 | 5.30000019073486 | 5.40000009536743 | 6.09999990463257 | 5.30000019073486 | 5.09999990463257 | 8.60000038146973 | 8 | 7.40000009536743 | 6.90000009536743 | 6.30000019073486 | 5.69999980926514 | 5.80000019073486 | 5.09999990463257 | 4.30000019073486 | 3.09999990463257 | 3 | 3.20000004768372
Tonga | TON | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Trinidad and Tobago | TTO | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15.6999998092651 | 17.1000003814697 | 17.6000003814697 | 16.2999992370605 | 15.1999998092651 | 13.3000001907349 | 12.1000003814697 | 11.3000001907349 | 10.8000001907349 | 10.1999998092651 | 8.60000038146973 | 7.80000019073486 | 7.80000019073486 | 6.09999990463257 | 5.80000019073486 | 4.5 | 3.79999995231628 | 3.5 | 4.59999990463257 | 5.09999990463257 | 5.5 | 5
Tunisia | TUN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 14.1999998092651 | 14.6000003814697 | 15.1000003814697 | 13.6000003814697 | 14.6999998092651 | 15.1000003814697 | 15.5 | 16.2000007629395 | 15.1000003814697 | 14.8999996185303 | 14.3000001907349 | 14.5 | 13.8000001907349 | 13.3000001907349 | 11.8999996185303 | 11.8999996185303 | 11.8999996185303 | 11.8999996185303 | 12.6999998092651 | 12.3999996185303 | 12.3999996185303 | 12.3000001907349
Turkey | TUR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.80000019073486 | 8.89999961853027 | 8.89999961853027 | 8.89999961853027 | 7.90000009536743 | 7 | 6.5 | 7 | 7.80000019073486 | 6.59999990463257 | 8.80000019073486 | 10.8000001907349 | 10.8000001907349 | 10.8999996185303 | 10.5 | 10 | 10.1000003814697 | 10.8000001907349 | 14 | 11.5 | 9.19999980926514 | 8.60000038146973
Tuvalu | TUV | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Tanzania | TZA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3 | 2.59999990463257 | 2.70000004768372 | 2.79999995231628 | 3.29999995231628 | 3.5 | 3.29999995231628 | 3.40000009536743 | 3.29999995231628 | 3.59999990463257 | 3.70000004768372 | 2.59999990463257 | 2.59999990463257 | 2.20000004768372 | 1.79999995231628 | 3 | 1.39999997615814 | 1.79999995231628 | 1.79999995231628 | 2.20000004768372 | 2.5 | 2.5
Uganda | UGA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.09999990463257 | 2.09999990463257 | 1.89999997615814 | 2 | 2 | 2 | 2 | 2 | 2.09999990463257 | 2.40000009536743 | 2.79999995231628 | 3 | 2.70000004768372 | 2.20000004768372 | 1.70000004768372 | 1.70000004768372 | 1.79999995231628 | 2.5 | 3.59999990463257 | 3.59999990463257 | 3.59999990463257 | 3.5
Ukraine | UKR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7 | 7.80000019073486 | 9 | 7.19999980926514 | 5.80000019073486 | 7.80000019073486 | 9.19999980926514 | 11.6999998092651 | 12 | 12 | 11.3000001907349 | 10 | 9.5 | 8.89999961853027 | 7.59999990463257 | 7.09999990463257 | 6.69999980926514 | 6.69999980926514 | 9.19999980926514 | 8.5 | 8.19999980926514 | 8.10000038146973
Upper middle income | UMC | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.51253269381757 | 5.995271858355714 | 6.004500447636245 | 5.971530503577832 | 6.253340883136665 | 6.353544191682126 | 6.233918869992977 | 6.463622346174593 | 6.587449026876561 | 6.583979969793147 | 6.616300920772964 | 6.607746270047556 | 6.553209733980148 | 6.312855142683741 | 5.982909176746694 | 5.640442948831435 | 5.435450324381914 | 5.77308965040022 | 6.140458319554808 | 5.932305110846631 | 5.813728750994586 | 5.925623415486792
Uruguay | URY | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 9.19999980926514 | 6 | 5.80000019073486 | 6.5 | 7.80000019073486 | 9.5 | 6.5 | 8 | 7.5 | 7 | 6.59999990463257 | 6.19999980926514 | 5.69999980926514 | 6.5 | 6.40000009536743 | 7.69999980926514 | 6.59999990463257 | 5.40000009536743 | 5.19999980926514 | 5 | 4.59999990463257 | 4.40000009536743
United States | USA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 7.30000019073486 | 8 | 7.30000019073486 | 6.30000019073486 | 5.69999980926514 | 5.5 | 5 | 4.5 | 4.19999980926514 | 4 | 4.90000009536743 | 6 | 6.40000009536743 | 5.69999980926514 | 5.19999980926514 | 4.69999980926514 | 4.80000019073486 | 6.19999980926514 | 10.3999996185303 | 10.6000003814697 | 9.39999961853027 | 8.30000019073486
Uzbekistan | UZB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 11 | 10.6999998092651 | 11 | 10.8999996185303 | 11 | 11.1000003814697 | 11.1999998092651 | 11.1999998092651 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1000003814697 | 11.1999998092651 | 11.1999998092651 | 11.3000001907349 | 11.3000001907349 | 11.3000001907349 | 11.3000001907349 | 11.3000001907349 | 11.1999998092651 | 11.1000003814697
St. Vincent and the Grenadines | VCT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Venezuela, RB | VEN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8.80000019073486 | 7.19999980926514 | 6.19999980926514 | 8.60000038146973 | 9.30000019073486 | 10.3999996185303 | 9 | 10 | 13.6000003814697 | 12.6000003814697 | 11.6000003814697 | 14.5 | 14.5 | 13 | 9.89999961853027 | 8.19999980926514 | 7.09999990463257 | 6.59999990463257 | 7.40000009536743 | 8.19999980926514 | 7.69999980926514 | 7.19999980926514
Virgin Islands (U.S.) | VIR | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Vietnam | VNM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.20000004768372 | 2.20000004768372 | 2.5 | 2.09999990463257 | 2.09999990463257 | 2.09999990463257 | 3.20000004768372 | 2.5 | 2.20000004768372 | 2.40000009536743 | 2.29999995231628 | 1.89999997615814 | 2 | 1.79999995231628 | 1.89999997615814 | 2.09999990463257 | 2.09999990463257 | 2.20000004768372 | 2.09999990463257 | 2.09999990463257 | 1.79999995231628 | 1.89999997615814
[NAME] | VUT | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
West Bank and Gaza | PSE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 22.2999992370605 | 27.5 | 25.6000003814697 | 24.7999992370605 | 24.7999992370605 | 24.6000003814697 | 21 | 14.8999996185303 | 12.3000001907349 | 14.6000003814697 | 26.6000003814697 | 32.9000015258789 | 31.7000007629395 | 28.1000003814697 | 27.2000007629395 | 24.2999992370605 | 22 | 26.5 | 25.5 | 24.6000003814697 | 21.8999996185303 | 24.1000003814697
World | WLD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.072041209437311 | 5.68658957617339 | 5.889119252344293 | 5.783266418581864 | 5.83507259319184 | 5.902096544087224 | 5.981520706524602 | 5.995205361466708 | 6.096576037652652 | 6.10811688460341 | 6.074067989840556 | 6.227807340820264 | 6.203124022265602 | 6.007739654702254 | 5.810591176441746 | 5.54570790333395 | 5.238536440176776 | 5.471709078090481 | 6.074425949827721 | 5.81380577422373 | 5.624428312262422 | 5.628261237782168
Samoa | WSM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS
Yemen, Rep. | YEM | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12.5 | 11.3000001907349 | 10.3000001907349 | 12.1999998092651 | 11.6000003814697 | 10.8999996185303 | 11.6999998092651 | 12.6000003814697 | 11.3000001907349 | 13.1999998092651 | 11.5 | 11.5 | 11.6999998092651 | 11.5 | 12.8999996185303 | 12.6000003814697 | 12.3000001907349 | 12 | 11.6999998092651 | 14.3000001907349 | 14.1999998092651 | 14.3000001907349
South Africa | ZAF | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 20.7000007629395 | 21.2999992370605 | 22.8999996185303 | 17.5 | 14.8000001907349 | 18.3999996185303 | 20.1000003814697 | 21.5 | 21.3999996185303 | 24.7999992370605 | 23.2999992370605 | 23.7000007629395 | 23.7999992370605 | 21.3999996185303 | 20.2000007629395 | 18.7000007629395 | 18.7999992370605 | 19.7000007629395 | 21.7000007629395 | 22.6000003814697 | 22.2000007629395 | 22.7000007629395
Congo, Dem. Rep. | COD | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.59999990463257 | 6.59999990463257 | 6.59999990463257 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.69999980926514 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486 | 6.80000019073486
Zambia | ZMB | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 21.5 | 21.7999992370605 | 22.3999996185303 | 21.7000007629395 | 21.1000003814697 | 17.3999996185303 | 16.5 | 13.6999998092651 | 13.8999996185303 | 14.6999998092651 | 17.1000003814697 | 16.3999996185303 | 17.2999992370605 | 17.3999996185303 | 17.7999992370605 | 17.7000007629395 | 17.7000007629395 | 17.7000007629395 | 17.6000003814697 | 14.5 | 14.5 | 14.6999998092651
Zimbabwe | ZWE | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.80000019073486 | 6.90000009536743 | 7.09999990463257 | 6 | 6.69999980926514 | 7.30000019073486 | 8.60000038146973 | 8 | 7.19999980926514 | 7.59999990463257 | 7.69999980926514 | 6.30000019073486 | 5.19999980926514 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4.09999990463257 | 4 | 4.19999980926514 | 4.19999980926514 | 4.09999990463257 | 4.30000019073486