Global Gender Gap Report

The Global Gender Gap Report was first published in 2006 by the World Economic Forum. The Global Gender Gap Index is an index designed to measure gender equality.[1]

Cover of the 2008 report

The index is designed to "measure gender-based gaps in access to resources and opportunities in countries rather than the actual level of the available resources and opportunities in those countries."[2] It is not necessarily true that highly developed countries should have higher scores.

The methodology used to determine index scores is designed in such a way as to count situations in which men are disadvantaged relative to women as "equal".[3]

Methodology

The report's Gender Gap Index ranks countries according to calculated gender gap between women and men in four key areas: health, education, economy and politics to gauge the state of gender equality in a country. The report measures women's disadvantage compared to men, and is not a measure of equality of the gender gap. Gender imbalances to the advantage of women do not affect the score.[3] So, for example, the indicator "number of years of a female head of state (last 50 years) over male value" would score 1 if the number of years was 25, but would still score 1 if the number of years was 50. Due to this methodology, gender gaps that favor women over men are reported as equality and would not cause deficits of equality in other areas to become less visible in the score, excepted for life expectancy. To put it more simply: women could be better off in all areas and still the index would deem that country perfectly equal.

The three highest-ranking countries have closed over 84% of their gender gaps, while the lowest-ranking country has closed only a little over 50% of its gender gap. It "assesses countries on how well they are dividing their resources and opportunities among their male and female populations, regardless of the overall levels of these resources and opportunities," the Report says.[4] "By providing a comprehensible framework for assessing and comparing global gender gaps and by revealing those countries that are role models in dividing these resources equitably between women and men, the Report serves as a catalyst for greater awareness as well as greater exchange between policymakers."[4]

The report examines four overall areas of inequality between men and women in 130 economies around the globe, over 93% of the world's population:

  • Economic participation and opportunity – outcomes on salaries, participation levels and access to high-skilled employment
  • Educational attainment – outcomes on access to basic and higher level education
  • Political empowerment – outcomes on representation in decision-making structures
  • Health and survival – outcomes on life expectancy and sex ratio. In this case parity is not assumed, there are assumed to be fewer female births than male (944 female for every 1,000 males), and men are assumed to die younger. Provided that women live at least six percent longer than men, parity is assumed. But if it is less than six percent it counts as a gender gap.[5]

Thirteen out of the fourteen variables used to create the index are from publicly available "hard data" indicators from international organizations, such as the International Labour Organization, the United Nations Development Programme and the World Health Organization.[6]

Upper limiting value of the Gender Gap Index

1. Economic participation and opportunity
 ratiolimit[7]weight[8]value
* Labour force participation1.00.1990.199
* Wage equality for similar work1.00.3100.310
* Estimated earned income1.00.2210.221
* Legislators, senior officials and managers1.00.1490.149
* Professional and technical workers1.00.1210.121
 sum1.01.0
2. Educational attainment
 ratiolimit[7]weight[8]value
* Literacy rate1.00.1910.191
* Enrolment in primary education1.00.4590.459
* Enrolment in secondary education1.00.2290.229
* Enrolment in tertiary education1.00.1210.121
 sum1.01.0
3. Health and survival
 ratiolimit[7]weight[8]value
* Sex ratio at birth0.944[9]0.6930.654
* Healthy life expectancy1.060[10]0.3070.325
 sum1.00.980
4. Political empowerment
 ratiolimit[7]weight[8]value
* Women in parliament1.00.3100.310
* Women in ministerial positions1.00.2470.247
* Years with female head of state1.00.4430.443
 sum1.01.0
Compilation
1. Economic participation and opportunity1.000
2. Educational attainment1.000
3. Health and survival0.980
4. Political empowerment1.000
sum  3.980

Gender Gap Index: 3.98 / 4 = 0.9949

This is the upper limiting value of the Gender Gap Index (limes superior) for the female-to-male ratio and for the male-to-female ratio.

WEF Global Gender Gap Index rankings

The highest possible score is 1.0 (equality or better for women, except for lifespan (106% or better for women) and gender parity at birth (94.4% or better for women[11]) and the lowest possible score is 0. Data for some countries are unavailable.[12][13][14]

Global Gender Gap Report 2020
Location Year [note 1]
Country Region 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015[15] 2016[2] 2017 2018 2020[16] 2021[17]
 AfghanistanSouth AsiaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.444
 AlbaniaEurope0.66070.66850.65910.66010.67260.67480.66550.64120.68690.7010.704 0.728 0.734 0.769 0.770
 AlgeriaAfrica0.60180.60680.61110.61190.60520.59910.61120.59660.61820.6320.642 0.629 0.629 0.634 0.633
 AngolaAfrica0.60390.60340.60320.63530.67120.6624N/A0.66590.63110.6370.643 0.640 0.633 0.660 0.657
 ArgentinaSouth America0.68290.69820.72090.72110.71870.72360.72120.71950.73170.7340.735 0.732 0.733 0.746 0.752
 ArmeniaWest AsiaN/A0.66510.66770.66190.66690.66540.66360.66340.66220.6680.669 0.677 0.678 0.684 0.673
 AustraliaOceania0.71630.72040.72410.72820.72710.72910.72940.73900.74090.7330.721 0.731 0.730 0.731 0.731
 AustriaEurope0.69860.70600.71530.70310.70910.71650.73910.74370.72660.7330.716 0.709 0.718 0.744 0.777
 AzerbaijanWest AsiaN/A0.67810.68560.66260.64460.65770.65460.65820.67530.6750.684 0.676 0.680 0.687 0.688
 BahamasCentral AmericaN/AN/AN/A0.71790.71280.73400.71560.71280.72690.7280.729 0.743 0.741 0.720 0.725
 BahrainWest Asia0.58940.59310.59270.61360.62170.62320.62980.63340.62610.6440.615 0.632 0.627 0.629 0.632
 BangladeshSouth Asia0.62700.63140.65310.65260.67020.68120.66840.68480.69730.7040.698 0.719 0.721 0.726 0.719
 BarbadosCentral AmericaN/AN/A0.71880.72360.71760.71700.72320.73010.72890.7440.739 0.750 0.753 0.749 0.769
 BelarusEuropeN/AN/AN/AN/AN/AN/AN/AN/AN/A0.7340.737 0.744 0.747 0.746 0.758
 BelgiumEurope0.70780.71980.71630.71650.75090.75310.76520.76840.78090.7530.745 0.739 0.738 0.750 0.789
 BelizeCentral AmericaN/A0.64260.66100.66360.65360.64890.64650.64490.67010.6680.676 0.692 0.662 0.671 0.699
 BeninAfrica0.57800.56560.55820.56430.57190.58320.62580.5885N/A0.6250.636 0.652 0.654 0.658 0.653
 BhutanSouth AsiaN/AN/AN/AN/AN/AN/AN/A0.66510.63640.6460.642 0.638 0.638 0.635 0.639
 BoliviaSouth America0.63350.65740.66670.66930.67510.68620.72220.73400.70490.7490.746 0.758 0.748 0.734 0.722
 Bosnia and HerzegovinaEuropeN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.713
 BotswanaAfrica0.68970.67970.68390.70710.68760.68320.67440.67520.71290.7100.715 0.720 0.715 0.709 0.716
 BrazilSouth America0.65430.66370.67370.66950.66550.66790.69090.69490.69410.6860.687 0.684 0.681 0.691 0.695
 Brunei DarussalamSoutheast AsiaN/AN/A0.63920.65240.67480.67870.67500.67300.67190.6840.669 0.671 0.686 0.686 0.678
 BulgariaEurope0.68700.70850.70770.70720.69830.69870.70210.70970.74440.7220.726 0.756 0.756 0.727 0.746
 Burkina FasoAfrica0.58540.59120.60290.60810.61620.61530.64550.65130.65000.6510.64 0.646 0.629 0.635 0.651
 BurundiAfricaN/AN/AN/AN/AN/A0.72700.73380.73970.75650.7480.768 0.755 0.741 0.745 0.769
 CambodiaSoutheast Asia0.62910.63530.64690.64100.64820.64640.64570.65090.65200.6620.658 0.676 0.683 0.694 0.685
 CameroonAfrica0.58650.59190.60170.61080.61100.60730.62910.6560N/A0.6820.684 0.689 0.714 0.686 0.692
 CanadaNorth America0.71650.71980.71360.71960.73720.74070.73810.74250.74640.7400.731 0.769 0.771 0.772 0.772
 Cape VerdeAfricaN/AN/AN/AN/AN/AN/A0.71800.71220.71330.7170.729 0.686 0.702 0.725 0.716
 ChadAfrica0.52470.53810.52900.54170.53300.53340.55940.55880.57640.5800.587 0.575 0.580 0.596 0.593
 ChileSouth America0.64550.64820.68180.68840.70130.70300.66760.66700.69750.6980.699 0.704 0.717 0.723 0.716
 ChinaEast Asia0.65610.66430.68780.69070.68810.68660.68530.69080.68300.6820.676 0.674 0.673 0.676 0.682
 ColombiaSouth America0.70490.70900.69440.69390.69270.67140.69010.71710.71220.7250.727 0.731 0.729 0.758 0.725
 Costa RicaCentral America0.69360.70140.71110.71800.71940.72660.72250.72410.71650.7320.736 0.727 0.749 0.782 0.786
 Côte d'IvoireAfricaN/AN/AN/AN/A0.56910.57730.57850.58140.58740.6060.597 0.611 0.627 0.606 0.637
 CroatiaEurope0.71450.72100.69670.69440.69390.70060.70530.70690.70750.7080.7 0.711 0.712 0.720 0.733
 CubaCentral AmericaN/A0.71690.71950.71760.72530.73940.74170.75400.73170.7400.74 0.745 0.749 0.746 0.746
 CyprusWest Asia0.64300.65220.66940.67060.66420.65670.67320.68010.67410.6710.684 0.684 0.684 0.692 0.707
 Czech RepublicEurope0.67120.67180.67700.67890.68500.67890.67670.67700.67370.6870.69 0.688 0.693 0.706 0.711
 Democratic Republic of the CongoAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.576
 DenmarkEurope0.74620.75190.75380.76280.77190.77780.77770.77790.80250.7670.754 0.776 0.778 0.782 0.768
 Dominican RepublicCentral America0.66390.67050.67440.68590.67740.66820.66590.68670.69060.6860.676 0.697 0.701 0.700 0.699
 EcuadorSouth America0.64330.68810.70910.72200.70720.70350.72060.73890.74550.7380.726 0.724 0.729 0.729 0.739
 EgyptAfrica0.57860.58090.58320.58620.58990.59330.59750.59350.60640.5990.614 0.608 0.614 0.629 0.639
 El SalvadorCentral America0.68370.68530.68750.69390.65960.65670.66300.66090.68630.7060.702 0.705 0.690 0.706 0.738
 EstoniaEurope0.69440.70080.70760.70940.70180.69830.69770.69970.70170.7490.747 0.731 0.734 0.751 0.733
 EthiopiaAfrica0.59460.59910.58670.59480.60190.61360.62000.61980.61440.6400.662 0.656 0.656 0.705 0.691
 FijiOceaniaN/AN/AN/A0.64140.62560.62550.62850.62860.62860.645N/A N/A 0.669 0.678 0.674
 FinlandEurope0.79580.80440.81950.82520.82600.83830.84510.84210.84530.8500.845 0.823 0.821 0.832 0.861
 FranceEurope0.65200.68240.73410.73310.70250.70180.69840.70890.75880.7610.755 0.778 0.779 0.781 0.784
 Gambia, TheAfrica0.64480.64210.66220.67520.67620.67630.6630N/AN/A0.6740.667 0.649 0.642 0.628 0.644
 GeorgiaWest Asia0.67000.66650.66540.66800.65980.66240.66910.67500.68550.6870.681 0.679 0.677 0.708 0.732
 GermanyEurope0.75240.76180.73940.74490.75300.75900.76290.75830.77800.7790.766 0.778 0.776 0.787 0.796
 GhanaAfrica0.66530.67250.66790.67040.67820.68110.67780.68110.66610.7040.705 0.695 0.688 0.673 0.666
 GreeceEurope0.65400.66480.67270.66620.69080.69160.67160.67820.67840.6850.68 0.692 0.696 0.701 0.689
 GuatemalaCentral America0.60670.61440.60720.62090.62380.62290.62600.63040.68210.6670.666 0.667 0.668 0.666 0.655
 GuineaAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/A0.6180.64 0.659 0.656 0.642 0.660
 GuyanaSouth AmericaN/AN/AN/A0.71080.70900.70840.71190.70850.70100.702N/A N/A N/A N/A 0.728
 HondurasCentral America0.64830.66610.69600.68930.69270.69450.67630.67730.69350.6880.69 0.711 0.706 0.722 0.716
 HungaryEurope0.66980.67310.68670.68790.67200.66420.67180.67420.67590.6720.669 0.670 0.674 0.677 0.688
 IcelandEurope0.78130.78360.79990.82760.84960.85300.86400.87310.85940.8810.874 0.878 0.858 0.877 0.892
 IndiaSouth Asia0.60110.59360.60600.61510.61550.61900.64420.65510.64550.6640.683 0.669 0.665 0.668 0.625
 IndonesiaSoutheast Asia0.65410.65500.64730.65800.66150.65940.65910.66130.67250.6810.682 0.691 0.691 0.700 0.688
 IranWest Asia0.58030.59030.60210.58390.59330.58940.59270.58420.58110.5800.587 0.583 0.589 0.584 0.582
 IraqWest AsiaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.535
 IrelandEurope0.73350.74570.75180.75970.77730.78300.78390.78230.78500.8070.797 0.794 0.796 0.798 0.800
 IsraelWest Asia0.68890.69650.69000.70190.69570.69260.69890.70320.70050.7120.719 0.721 0.722 0.718 0.724
 ItalyEurope0.64560.64980.67880.67980.67650.67960.67290.68850.69730.7260.719 0.692 0.706 0.707 0.721
 JamaicaCentral America0.70140.69250.69800.70130.70370.70280.70350.70850.71280.7030.724 0.717 0.724 0.735 0.741
 JapanEast Asia0.64470.64550.64340.64470.65240.65140.65300.64980.65840.6700.66 0.657 0.662 0.652 0.656
 JordanWest Asia0.61090.62030.62750.61820.60480.61170.61030.60930.59680.5930.603 0.604 0.605 0.623 0.683
 KazakhstanCentral Asia0.69280.69830.69760.70130.70550.70100.72130.72180.72100.7190.718 0.713 0.712 0.710 0.710
 KenyaAfrica0.64860.65080.65470.65120.64990.64930.67680.68030.72580.7190.702 0.694 0.700 0.671 0.692
 Korea, Rep.East Asia0.61570.64090.61540.61460.63420.62810.63560.63510.64030.6510.649 0.650 0.657 0.672 0.687
 KuwaitWest Asia0.63410.64090.63580.63560.63180.63220.63200.62920.64570.6460.624 0.679 0.630 0.650 0.621
 Kyrgyz RepublicCentral Asia0.67420.66530.70450.70580.69730.70360.70130.69480.69740.6930.687 0.691 0.691 0.689 0.681
 LaosSoutheast AsiaN/AN/AN/AN/AN/AN/AN/A0.69930.70440.713N/A 0.703 0.748 0.731 0.750
 LatviaEurope0.70910.73330.73970.74160.74290.73990.75720.76100.76910.7520.755 0.756 0.758 0.785 0.778
 LebanonWest AsiaN/AN/AN/AN/A0.60840.60830.60300.60280.59230.5980.598 0.596 0.595 0.599 0.638
 LesothoAfrica0.68070.70780.73200.74950.76780.76660.76080.75300.72550.7060.706 0.695 0.693 0.695 0.698
 LiberiaAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/A0.6520.652 0.669 0.681 0.685 0.693
 LithuaniaEurope0.70770.72340.72220.71750.71320.71310.71910.73080.72080.7400.744 0.742 0.749 0.745 0.804
 LuxembourgEurope0.66710.67860.68020.68890.72310.72160.74390.74100.73330.7380.734 0.706 0.712 0.725 0.726
 North MacedoniaEurope0.69830.69670.69140.69500.69960.69660.69680.70130.69430.7010.696 0.702 0.707 0.711 0.715
 MadagascarAfrica0.63850.64610.67360.67320.67130.67970.69820.70160.72140.6980.704 0.692 0.691 0.719 0.725
 MalawiAfrica0.64370.64800.66640.67380.68240.68500.71660.71390.72810.7010.7 0.672 0.662 0.664 0.671
 MalaysiaSoutheast Asia0.65090.64440.64420.64670.64790.65250.65390.65180.65200.6550.666 0.670 0.676 0.677 0.676
 MaldivesSouth AsiaN/A0.63500.65010.64820.64520.64800.66160.66040.65570.652.65 0.669 0.662 0.646 0.642
 MaliAfrica0.59960.60190.61170.58600.56800.57520.58420.58720.57790.5990.591 0.583 0.582 0.621 0.591
 MaltaEurope0.65180.66150.66340.66350.66950.66580.66660.67610.67070.6680.664 0.682 0.686 0.693 0.703
 MauritaniaAfrica0.58350.60220.61170.61030.61520.61640.61290.58100.60290.6130.624 0.614 0.607 0.614 0.606
 MauritiusAfrica0.63280.64870.64660.65130.65200.65290.65470.65990.65410.6460.652 0.664 0.663 0.665 0.679
 MexicoNorth America0.64620.64410.64410.65030.65770.66040.67120.69170.69000.6990.7 0.692 0.721 0.754 0.757
 MoldovaEurope0.71280.71720.72440.71040.71600.70830.71010.70370.74050.7420.741 0.740 0.733 0.757 0.768
 MongoliaEast Asia0.68210.67310.70490.72210.71940.71400.71110.72040.72120.7090.705 0.713 0.714 0.706 0.716
 MontenegroEuropeN/AN/AN/AN/AN/AN/AN/AN/AN/A0.6890.681 0.693 0.706 0.710 0.732
 MoroccoAfrica0.58270.56760.57570.59260.57670.58040.58330.58450.59880.5930.597 0.598 0.607 0.605 0.612
 MozambiqueAfricaN/A0.68830.72660.71950.73290.72510.73500.73490.73700.7410.75 0.741 0.721 0.723 0.758
 MyanmarSoutheast AsiaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A0.691 0.690 0.665 0.681
 NamibiaAfrica0.68640.70120.71410.71670.72380.71770.71210.70940.72190.7600.765 0.777 0.789 0.784 0.809
   NepalSouth Asia0.54780.55750.59420.62130.60840.58880.60260.60530.64580.6580.661 0.664 0.671 0.680 0.683
 NetherlandsEurope0.72500.73830.73990.74900.74440.74700.76590.76080.77300.7760.756 0.737 0.747 0.736 0.762
 New ZealandOceania0.75090.76490.78590.78800.78080.78100.78050.77990.77720.7820.781 0.791 0.801 0.799 0.840
 NicaraguaCentral America0.65660.64580.67470.70020.71760.72450.76970.77150.78940.7760.78 0.814 0.809 0.804 0.796
 NigerAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.629
 NigeriaAfrica0.61040.61220.63390.62800.60550.60110.63150.64690.63910.6380.643 0.641 0.621 0.635 0.627
 NorwayEurope0.79940.80590.82390.82270.84040.84040.84030.84170.83740.8500.842 0.830 0.835 0.842 0.849
 OmanWest AsiaN/A0.59030.59600.59380.59500.58730.59860.60530.60910.6040.612 N/A 0.605 0.602 0.608
 PakistanSouth Asia0.54340.55090.55490.54580.54650.55830.54780.54590.55220.5590.556 0.546 0.550 0.564 0.556
 PanamaCentral America0.69350.69540.70950.70240.70720.70420.71220.71640.71950.7720.721 0.722 0.722 0.730 0.737
 Papua New GuineaOceaniaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.635
 ParaguaySouth America0.65560.66590.63790.68680.68040.68180.67140.67240.68900.6660.676 0.678 0.672 0.683 0.702
 PeruSouth America0.66190.66240.69590.70240.68950.67960.67420.67870.71980.6830.687 0.719 0.720 0.714 0.721
 PhilippinesSoutheast Asia0.75160.76290.75680.75790.76540.76850.77570.78320.78140.7900.786 0.790 0.799 0.781 0.784
 PolandEurope0.68020.67560.69510.69980.70370.70380.70150.70310.70510.7150.727 0.728 0.728 0.736 0.713
 PortugalEurope0.69220.69590.70510.70130.71710.71440.70710.70560.72430.7310.737 0.734 0.732 0.744 0.775
 QatarWest AsiaN/A0.60410.59480.59070.60590.62300.62640.62990.64030.6450.643 0.626 0.629 0.629 0.624
 RomaniaEurope0.67970.68590.67630.68050.68260.68120.68590.69080.69360.6930.69 0.708 0.711 0.724 0.700
 RussiaEurope0.67700.68660.69940.69870.70360.70370.69800.69830.69270.6940.691 0.696 0.701 0.706 0.708
 RwandaAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/A0.7940.8 0.822 0.804 0.791 0.805
 Saudi ArabiaWest Asia0.52420.56470.55370.56510.57130.57530.57310.58790.60590.6050.583 0.584 0.590 0.599 0.603
 SenegalAfricaN/AN/AN/A0.64270.64140.65730.66570.69230.69120.6980.685 0.684 0.682 0.684 0.684
 SerbiaEuropeN/AN/AN/AN/AN/AN/A0.70370.71160.70860.7200.72 0.727 0.730 0.736 0.780
 Sierra LeoneAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.655
 SingaporeSoutheast Asia0.65500.66090.66250.66640.69140.69140.69890.70000.70460.7110.712 0.702 0.707 0.724 0.727
 SlovakiaEurope0.67570.67970.68240.68450.67780.67970.68240.68570.68060.6750.679 0.694 0.693 0.718 0.712
 SloveniaEurope0.67450.68420.69370.69820.70470.70410.71320.71550.74430.7840.786 0.805 0.784 0.743 0.741
 South AfricaAfrica0.71250.71940.72320.77090.75350.74780.74960.75100.75270.7590.764 0.756 0.755 0.780 0.781
 SpainEurope0.73190.74440.72810.73450.75540.75800.72660.72660.73250.7420.738 0.746 0.746 0.795 0.788
 Sri LankaSouth Asia0.71990.72300.73710.74020.74580.72120.71220.70190.69030.6860.673 0.669 0.676 0.680 0.670
 SurinameSouth AmericaN/A0.67940.66740.67260.64070.63950.64090.63690.65040.6700.679 0.689 0.695 0.707 0.729
 EswatiniAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/A0.6700.665 0.670 N/A N/A 0.729
 SwedenEurope0.81330.81460.81390.81390.80240.80440.81590.81290.81650.8230.815 0.816 0.822 0.820 0.823
  SwitzerlandEurope0.69970.69240.73600.74260.75620.76270.76720.77360.77980.7850.776 0.755 0.755 0.779 0.798
 SyriaWest AsiaN/A0.62160.61810.60720.59260.58960.56260.56610.57750.5680.567 0.568 0.568 0.567 0.568
 TajikistanCentral AsiaN/A0.65780.65410.66610.65980.65260.66080.66820.66540.6750.679 0.678 0.638 0.626 0.650
 TanzaniaAfrica0.70380.69690.70680.67970.68290.69040.70910.69280.71820.7180.716 0.700 0.704 0.713 0.707
 ThailandSoutheast Asia0.68310.68150.69170.69070.69100.68920.68930.69280.70270.7060.699 0.694 0.702 0.708 0.710
 Timor-LesteSoutheast AsiaN/AN/AN/AN/AN/AN/A0.6855N/AN/AN/A0.637 0.628 0.638 0.662 0.720
 TogoAfricaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.683
 Trinidad and TobagoCentral America0.67970.68590.72450.72980.73530.73720.71160.71660.71540.7200.723 N/A N/A 0.756 0.749
 TunisiaAfrica0.62880.62830.62950.62330.62660.6255N/AN/A0.62720.6340.636 0.651 0.648 0.644 0.649
 TurkeyWest Asia0.58500.57680.58530.58280.58760.59540.60150.60810.61830.6240.623 0.625 0.628 0.635 0.638
 UgandaAfrica0.67970.68330.69810.70670.71690.72200.72280.70860.68210.7080.704 0.721 0.724 0.717 0.717
 UkraineEurope0.67970.67900.68560.68960.68690.68610.68940.69350.70560.7020.7 0.705 0.708 0.721 0.714
 United Arab EmiratesWest Asia0.59190.61840.62200.61980.63970.64540.63920.63720.64360.6460.639 0.649 0.642 0.655 0.716
 United KingdomEurope0.73650.74410.73660.74020.74600.74620.74330.74400.73830.7580.752 0.770 0.744 0.767 0.775
 United StatesNorth America0.70420.70020.71790.71730.74110.74120.73730.73920.74630.7400.722 0.718 0.720 0.724 0.763
 UruguaySouth America0.65490.66080.69070.69360.68970.69070.67450.68030.68710.6790.681 0.710 0.715 0.737 0.702
 VanuatuOceaniaN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A N/A N/A N/A 0.625
 VenezuelaSouth America0.66640.67970.68750.68390.68630.68610.70600.70600.68510.6910.694 0.706 0.709 0.713 0.699
 VietnamSoutheast AsiaN/A0.68890.67780.68020.67760.67320.68670.68630.69150.6870.7 0.698 0.698 0.700 0.701
 YemenWest Asia0.45950.45100.46640.46090.46030.48730.50540.51280.51450.4840.516 0.516 0.499 0.494 0.492
 ZambiaAfrica0.63600.62880.62050.63100.62930.63000.62790.63120.63640.650N/A N/A N/A 0.731 0.726
 ZimbabweAfrica0.64610.64640.64850.65180.65740.6607N/AN/A0.70130.7090.71 0.717 0.721 0.730 0.732

Criticisms

In an academic publication from 2010, Beneria and Permanyer criticized the Global Gender Gap Index for only capturing inequality in certain aspects of women's lives therefore making it an incomplete measure of gender inequality.[18]

In an academic publication from 2019, Stoet and Geary argued that the Global Gender Gap Index has limitations as a measure of gender equality, because of the way it caps scores and because it ignores specific issues on which men are known to fall behind (e.g., risks of working in hazardous jobs).[19] According to the Global Gender Gap Report 2021, the index do not penalize a country where women outperform men in certain aspect and consider that parity is achieved in life expectancy only if women live five years longer than men.[17]

See also

Notes

  1. Years of report publication. Values may reflect data collected the previous year.

References

  1. "Global Gender Gap Report 2017". Archived from the original on 2018-05-12. Retrieved 2018-05-11.
  2. "Global Gender Gap Report 2017 - Rankings". World Economic Forum. Retrieved 17 November 2017.
  3. Ricardo Hausmann, Harvard University, Laura D. Tyson, University of California, Berkeley, Saadia Zahidi, World Economic Forum, Editors (2009). "The Global Gender Gap Report 2009" (PDF). World Economic Forum, Geneva, Switzerland. p. 4. Archived from the original (PDF) on April 5, 2013. Retrieved 2009-11-02. (...) the Index rewards countries that reach the point where outcomes for women equal those for men, but it neither rewards nor penalizes cases in which women are outperforming men in particular variables {{cite web}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  4. 2008 Report, p. 24
  5. 2014 report, page 5
  6. 2008 Report, p. 5
  7. The Global Gender Gap Report 2018 (GGGR), p. 5, Construction of the Index, § 2. Data truncation at equality benchmark: As a second step, these ratios are truncated at the "equality benchmark”. For all indicators, except the two health indicators, this equality benchmark is considered to be 1, meaning equal numbers of women and men.
    GGGR 2018, p. 42, Country Score Card: … To calculate the Index, all ratios were truncated at the parity benchmark of 1 and thus the highest score possible is 1.
  8. GGGR 2018, p. 6; Table 2: Calculation of weights within each subin-dex
  9. GGGR 2018, p. 5, Construction of the Index, § 2. Data truncation at equality benchmark: … In the case of sex ratio at birth, the equality benchmark is set at 0.944,
    GGGR 2018, p. 42, Country Score Card: … except for the sex ratio at birth (0.944)
  10. GGGR 2018, p. 5, Construction of the Index, § 2. Data trun-cation at equality benchmark: … the case of healthy life expectancy the equality benchmark is set at 1.06.
    GGGR 2018, p. 42, Country Score Card: … and the healthy life expectancy (1.06) indicators.
  11. 2016 Report, Page 6
  12. http://www3.weforum.org/docs/WEF_GenderGap_Report_2012.pdf
  13. "The Global Gender Gap Report 2013" (PDF). World Economic Forum. pp. 12–13.
  14. "Global Gender Gap Report 2014 - Reports - World Economic Forum". Global Gender Gap Report 2014.
  15. "Global Gender Gap Report 2015 - Rankings". World Economic Forum. Archived from the original on 17 April 2016. Retrieved 28 April 2016.
  16. "Global Gender Gap Report 2020" (PDF). World Economic Forum. Retrieved 18 December 2019.
  17. "Global Gender Gap Report 2021" (PDF). World Economic Forum. Retrieved 30 March 2021.
  18. Beneria, L., Permanyer, I.,(2010). The Measurement of Socio-economic Gender Inequality Revisited, Development and Change, 41:3, pp.375-399
  19. Stoet, G. & Geary, D.C. (2019). A simplified approach to measuring national gender inequality, PLOS ONE 14(1): e0205349. https://doi.org/10.1371/journal.pone.0205349

Reports

  • Ricardo Hausmann; Laura D. Tyson; Yasmina Bekhouche; Saadia Zahidi (2014). The Global Gender Gap Index 2014 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2014-11-26.
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2013). The Global Gender Gap Report 2013 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2013-10-26. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2012). The Global Gender Gap Report 2012 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2012-10-26. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • The Global Gender Gap Report 2010 (PDF).
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2010). The Global Gender Gap Report 2010 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2010-10-20. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2009). The Global Gender Gap Report 2009 (PDF). World Economic Forum, Geneva, Switzerland. Archived from the original (PDF) on 2013-04-05. Retrieved 2009-11-02. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2008). The Global Gender Gap Report 2008 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2008-11-19. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2007). The Global Gender Gap Report 2007 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2008-11-19. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Ricardo Hausmann, Laura D. Tyson, Saadia Zahidi, Editors (2006). The Global Gender Gap Report 2006 (PDF). World Economic Forum, Geneva, Switzerland. Retrieved 2008-11-19. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
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