Gender Inequality Index

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Countries by Gender Inequality Index (Data from 2019, published in 2020).
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Red denotes more gender inequality, and
green more equality. Gender Inequality Index 2019.svg
Countries by Gender Inequality Index (Data from 2019, published in 2020). Red denotes more gender inequality, and green more equality.

The Gender Inequality Index (GII) is an index for the measurement of gender disparity that was introduced in the 2010 Human Development Report 20th anniversary edition by the United Nations Development Programme (UNDP). According to the UNDP, this index is a composite measure to quantify the loss of achievement within a country due to gender inequality. It uses three dimensions to measure opportunity cost: reproductive health, empowerment, and labor market participation. The new index was introduced as an experimental measure to remedy the shortcomings of the previous indicators, the Gender Development Index (GDI) and the Gender Empowerment Measure (GEM), both of which were introduced in the 1995 Human Development Report.

Contents

Origins

As international recognition of the importance of eliminating gender inequality was growing, the Gender Development Index (GDI) and the Gender Empowerment Measure (GEM) were introduced in the 1995 Human Development Report. The GDI and GEM became the primary indices for measuring global gender inequality for the United Nations Human Development Reports. The GDI and GEM faced criticism for their methodological and conceptual limitations. [2] [3]

Beneria and Permanyer have explained that the GDI and GEM are not measurements of gender inequality in and of themselves. The GDI is a composite index which measures development within a country and then negatively corrects for gender inequality; and the GEM measures the access women have to attaining means of power in economics, politics, and making decisions. Both of which Beneria and Permanyer claim are inaccurate in clearly capturing gender inequality. [4] The GDI fails to include measuring the position of women as compared to men in society, even if it shows the human development costs of gender inequalities in basic human development. [5] Schüler also notes that both the GEM and GDI failed to create any recognition for gender inequality, and the continuance of gender disparities kept going internationally. [6] According to the UNDP, the GDI was criticized for its inability to accurately measure gender inequality for its components being too closely related to the Human Development Index (HDI), a composite measure of human development used by the UNDP. [7]

Thus, the differences between the HDI and GDI were small leading to the implication that gender disparities were irrelevant to human development. The UNDP also claims that both the GDI and GEM were criticized because income levels tended to dominate the earned income component, which resulted in countries with low income levels not being able to get high scores, even in cases where their levels of gender inequality may have been low. The GEM indicators proved to be more relevant to developed countries than less-developed countries. With international growing concern for gender equality, the participants of the World Economic Forum in 2007, among others, recognized that the advancement of women was a significant issue that impacted the growth of nations. [8]

As of 2006, the World Economic Forum has been using the Gender Gap Index (GGI) in its Global Gender Gap Reports, which ranks countries according to their gender gaps, in an attempt to better capture gender disparities. [9] Beneria and Permanyer criticize the GGI for only capturing inequality in certain aspects of women's lives therefore making it an incomplete measure of gender inequality. [4]

Given the amount of criticism the GDI and GEM were facing, the UNDP felt that these indices did not fully capture the differences between gender. In an attempt to reform the GDI and GEM, the UNDP introduced the Gender Inequality Index (GII) in the 2010 Human Development Report. [7] The new index is a composite measure which, according to the UNDP, captures the loss of achievement due to gender inequality using three dimensions: reproductive health, empowerment, and labor market participation. The GII does not include income levels as a component, which was one of the most controversial components of the GDI and GEM. It also does not allow for high achievements in one dimension to compensate for low achievement in another. [7]

Dimensions

There are three critical dimensions to the GII: reproductive health, empowerment, and labor market participation. The dimensions are captured in one synthetic index, as to account for joint significance. According to the UNDP, none of the measures in the dimensions pertain to the country's development and therefore a less-developed country can perform well if gender inequality is low. The UNDP considers the dimensions complementary in that inequality in one dimension tends to affect inequality in another. Therefore, the GII captures association across dimensions, making the index association-sensitive, and ensuring that high achievement in one dimension does not compensate for low achievement in another dimension. [10]

Reproductive health

Permanyer notes that the GII is a pioneering index, in that it is the first index to include reproductive health indicators as a measurement for gender inequality. [3] The GII's dimension of reproductive health have two indicators: the Maternal Mortality Ratio (MMR), the data for which come UNICEF's State of the World's Children, and the adolescent fertility rate (AFR), the data for which is obtained through the UN Department of Economic and Social Affairs, respectively. With a low MMR, it is implied that pregnant women have access to adequate health needs, therefore the MMR is a good measure of women's access to health care. The UNDP expresses that women's health during pregnancy and childbearing is a clear sign of women's status in society. [10]

A high AFR, which measures early childbearing, results in health risks for mothers and infants as well as a lack of higher education attainment. According to the UNDP data, reproductive health accounts for the largest loss due to gender inequality, among all regions. [10]

Empowerment

The empowerment dimension is measured by two indicators: the share of parliamentary seats held by each sex, which is obtained from the International Parliamentary Union, and higher education attainment levels, which is obtained through United Nations Educational, Scientific and Cultural Organization (UNESCO) and Barro-Lee data sets. [11] The GII index of higher education evaluates women's attainment to secondary education and above. Access to higher education expands women's freedom by increasing their ability to question and increases their access to information which expands their public involvement. [10]

There is much literature that finds women's access to education may reduce the AFR and child mortality rates within a country. [8] [12] Due to data limitations the parliament representation indicator is limited to national parliament and excludes local government or other community involvement. Although women's representation in parliament has been increasing women have been disadvantaged in representation of parliament with a global average of only 16%. [10]

Labor market participation

The labor market dimension is measured by women's participation in the workforce. This dimension accounts for paid work, unpaid work, and actively looking for work. The data for this dimension is obtained through the International Labour Organization databases. Due to data limitations women's income and unpaid work are not represented in the labor market dimension of GII. [11] In the absence of reliable earned income data across countries, the UNDP considers labor market participation a suitable substitute for economic aspects of gender inequality. [2]

Calculations

The metrics of the GII are similar in calculations to the Inequality-adjusted Human Development Index (IHDI), which was also introduced in the 2010 Human Development Report, and can be interpreted as a percentage loss of human development due to shortcomings in the included dimensions. The value of GII range between 0 and 1, with 0 being 0% inequality, indicating women fare equally in comparison to men and 1 being 100% inequality, indicating women fare poorly in comparison to men. There is a correlation between GII ranks and human development distribution, according to the UNDP countries that exhibit high gender inequality also show inequality in distribution of development, and vice versa. [10]

The GII is an association-sensitive, responsive to distributional changes across dimension, [3] composite index used to rank the loss of development through gender inequality within a country. [10] The GII measures inequalities by addressing the shortcomings of other measures through aggregate strategy using multiple correspondence analysis (MCA) in order to avoid aggregation problems. [8] There are five steps to computing the gender inequality Index. [10]

Step 1: Treating zeros and extreme values: The maternal mortality rate is truncated systematically at minimum of 10 and maximum of 1,000. The maximum and minimum is based on the normative assumption that all countries with maternal mortality ratios above 1,000 do not differ in their ability to support for maternal health as well as the assumption that all countries below 10 do not differ in their abilities. Countries with parliamentary representation reporting at 0 are counted as 0.1 because of the assumption that women have some level of political influence and that the geometric mean can not have a 0 value.

Step 2: Aggregating across dimensions within each gender group, using geometric means: Aggregating across dimensions for each gender group by the geometric mean makes the GII association-sensitive. [10] The maternal mortality rate and the adolescent fertility rate are only relevant for females the males are only aggregated with the other two dimensions.

Step 3: Aggregating across gender groups, using a harmonic mean: To compute the equally distributed gender index the female and male indices are aggregated by the harmonic mean of the geometric means to capture the inequality between females and males and adjust for association between dimensions.

Step 4: Calculating the geometric mean of the arithmetic means for each indicator: Obtain the reference standard by aggregating female and male indices with equal weight, and then aggregating indices across dimensions.

Reproductive health is not an average of female and male indices but half the distance from the norms established

Step 5: Calculating the Gender Inequality Index: To compute the GII compare the equally distributed gender index from Step 3 to the reference standard from Step 4.

Changes in 2011 calculations

According to the UNDP there was a minor calculation change to the 2011 Gender Inequality Index from the 2010 index used. The maternal mortality ratio was calculated in the Gender Inequality Index at 10 even though the range of GII values should be between 0 and 1. To correct this the maternal mortality ratio is normalized by 10, which generally reduced the values of the GII.

Rankings

As there is no country with perfect gender equality, all countries suffer some loss of human development due to gender inequality. The difference in dimensions used in the GII and HDI means that the GII is not interpreted as a loss of HDI, but has its own rank and value separate from the HDI. [7] The GII is interpreted as a percentage and indicates the percentage of potential human development lost due to gender inequality. The world average GII score in 2011 was 0.492, which indicates a 49.2% loss in potential human development due to gender inequality. [11] Due to the limitations of data and data quality, the 2010 Human Development Report calculated GII rankings of 138 countries for the year 2008. The 2011 Human Development Report was able to calculate the GII rankings of 146 countries for the reporting year 2011. [13]

The 2019 rankings for all scored countries based on UNDP GII data are:

GII RankHDI RankCountryGII Value
12 Switzerland 0.025
21 Norway 0.038
311 Finland 0.039
48 Netherlands 0.043
410 Denmark 0.043
67 Sweden 0.045
614 Belgium 0.045
723 South Korea 0.047
826 France 0.049
94 Iceland 0.058
1022 Slovenia 0.063
1123 Taiwan 0.064
1223 Luxembourg 0.065
1211 Singapore 0.065
1418 Austria 0.069
1429 Italy 0.069
1625 Spain 0.070
1719 Japan 0.075
1838 Portugal 0.079
1919 Canada 0.080
206 Germany 0.084
2133 Cyprus 0.086
2129 Estonia 0.086
232 Ireland 0.093
2416 New Zealand 0.094
258 Australia 0.097
2615 United Kingdom 0.109
2648 Montenegro 0.109
2835 Poland 0.115
2932 Greece 0.116
2943 Croatia 0.116
3131 United Arab Emirates 0.118
3153 Belarus 0.118
3314 Israel 0.123
3434 Lithuania 0.124
3564 Serbia 0.132
3627 Czech Republic 0.136
3782 North Macedonia 0.143
3873 Bosnia and Herzegovina 0.149
3985 China 0.168
4028 Malta 0.175
4137 Latvia 0.176
4269 Albania 0.181
4345 Qatar 0.185
4451 Kazakhstan 0.190
4539 Slovakia 0.191
4617 United States 0.204
4690 Moldova 0.204
4856 Bulgaria 0.206
4942 Bahrain 0.212
5052 Russia 0.225
5140 Hungary 0.233
5274 Ukraine 0.234
5364 Kuwait 0.242
5481 Armenia 0.245
5543 Chile 0.247
56105 Libya 0.252
5640 Saudi Arabia 0.252
5658 Barbados 0.252
5962 Malaysia 0.253
6047 Brunei 0.255
6149 Romania 0.276
6255 Uruguay 0.288
62106 Uzbekistan 0.288
6262 Costa Rica 0.288
6595 Tunisia 0.296
65117 Vietnam 0.296
6770 Cuba 0.304
6860 Oman 0.306
6854 Turkey 0.306
70125 Tajikistan 0.314
7199 Mongolia 0.322
7174 Mexico 0.322
7388 Azerbaijan 0.323
7367 Trinidad and Tobago 0.323
7546 Argentina 0.328
7661 Georgia 0.331
7758 Bahamas 0.341
7866 Mauritius 0.347
79104 Tonga 0.354
8079 Thailand 0.359
81111 Samoa 0.360
8295 Maldives 0.369
82120 Kyrgyzstan 0.369
8493 Fiji 0.370
85124 El Salvador 0.383
8686 Ecuador 0.384
8779 Peru 0.395
88101 Jamaica 0.396
89126 Cape Verde 0.397
9086 Saint Lucia 0.401
9072 Sri Lanka 0.401
92160 Rwanda 0.402
93114 South Africa 0.406
9457 Panama 0.407
9584 Brazil 0.408
9692 Lebanon 0.411
97110 Belize 0.415
98107 Bolivia 0.417
99129 Bhutan 0.421
100132 Honduras 0.423
10183 Colombia 0.428
101128 Nicaragua 0.428
10391 Algeria 0.429
104107 Philippines 0.430
10597 Suriname 0.436
106130 Namibia 0.440
107103 Paraguay 0.446
108116 Egypt 0.449
109102 Jordan 0.450
110142 Nepal 0.452
111121 Morocco 0.454
11288 Dominican Republic 0.455
113137 Laos 0.459
11370 Iran 0.459
115122 Guyana 0.462
116100 Botswana 0.465
117144 Cambodia 0.474
118147 Myanmar 0.478
119113 Venezuela 0.479
119127 Guatemala 0.479
121107 Indonesia 0.480
122151 Syria 0.482
123131 India 0.488
124185 Burundi 0.504
125173 Ethiopia 0.517
126143 Kenya 0.518
127181 Mozambique 0.523
128119 Gabon 0.525
129150 Zimbabwe 0.527
130168 Senegal 0.533
131159 Uganda 0.535
132148 Angola 0.536
133135 Sao Tome and Principe 0.537
133133 Bangladesh 0.537
135138 Ghana 0.538
135154 Pakistan 0.538
137146 Zambia 0.539
138170 Sudan 0.545
139165 Lesotho 0.553
140163 Tanzania 0.556
141153 Cameroon 0.560
142174 Malawi 0.565
143138 Eswatini 0.567
144149 Republic of the Congo 0.570
145167 Togo 0.573
146123 Iraq 0.577
147182 Burkina Faso 0.594
148158 Benin 0.612
148172 Gambia 0.612
150175 Democratic Republic of the Congo 0.617
151157 Mauritania 0.634
152170 Haiti 0.636
153162 Ivory Coast 0.638
154189 Niger 0.642
155182 Sierra Leone 0.644
156175 Liberia 0.650
157169 Afghanistan 0.655
158184 Mali 0.671
159188 Central African Republic 0.680
160187 Chad 0.710
161155 Papua New Guinea 0.725
162179 Yemen 0.795

Top ten countries

The ten highest-ranked countries in terms of gender equality according to the GII for 2008, [10] 2011, [13] and 2012. [14]

2018 rank and value, source: http://hdr.undp.org/en/content/table-5-gender-inequality-index-gii.

2018: 9th is Iceland, 10th is Republic of Korea.

CountryGII Rank

(GII value) 2018

GII Rank 2012GII Value 2012HDI Rank 2012GII Rank 2011GII Value 2011GII Rank 2008GII Value 2008
Netherlands 4 (0.041)10.045420.05210.174
Sweden 2 (0.040)20.055710.04930.212
Denmark 2 (0.040)30.0571530.06020.209
Switzerland 1 (0.037)40.057940.06740.228
Norway 5 (0.044)50.065160.07550.234
Finland 7 (0.050)60.0752150.07580.248
Germany 19 (0.084)70.075570.08570.240
South Korea 7 (0.048)80.08780.07880.198
France 8 (0.051)100.08320100.106110.260
Belgium 6 (0.045)90.068****GHS

Countries not included

Country [15] [16] GII Rank 2012GII Value 2012HDI Rank 2012GII Rank 2011GII Value 2011GII Rank 2008GII Value 2008
Republic of China (Taiwan) 20.0532340.06140.223

Bottom ten countries

The ten lowest ranked countries in terms of gender equality according to the GII for 2008, [10] 2011, [13] and 2012. [14]

2018 rank and value, source: http://hdr.undp.org/en/content/table-5-gender-inequality-index-gii.

CountryGII Rank

(GII value) 2018

GII Value 2012HDI Rank 2012GII Rank 2011GII Value 2011GII Rank 2008GII Value 2008
Yemen 162 (0.834)0.747160--------
Afghanistan 143 (0.575)0.7121751410.7171340.797
Niger 154 (0.647)0.7071861440.7241360.807
Congo 156 (0.655)0.6811861420.7101690.814
Liberia 155 (0.651)0.6581741390.6711310.766
Central African Republic 159 (0.682)0.6541801380.6691320.768
Mali 158 (0.676)0.6491821430.7121350.799
Sierra Leone 153 (0.644)0.6431771370.6621250.756
Mauritania 150 (0.620)0.643155--------

Criticisms

The GII is a relatively new index that has only been in use since 2010. Criticisms of the GII as a global measurement of gender inequality include that the GII may inadequately capture gender inequality, leave out important aspects, or include unnecessary dimensions, and the complexity of GII causes difficulty for some to interpret or calculate.

Complexity

Klasen and Schüler as well as Permanyer argue that the complexity of the GII will make it difficult to interpret or understand for the professionals who would likely want to make use of it because so many non-linear procedures are applied to the data. [3] [17] Permanyer believes that simplicity is required in order for analysts, policy-makers, or practitioners to convey a clear message to the general public. [3]

Klasen and Schüler claim that the GII is meant to represent a loss of human development, but the standard against which the losses are measured is not stated anywhere, unlike the GDI where the losses were measured against the HDI, making the HDI represent perfect equality. [17] The UNDP explains that the complexity of the calculations are needed in order to maintain an association-sensitive measure, but Permanyer argues that alternative indices that are much less complex have also shown to be association sensitive. [3]

Proposal for a Subnational Index

While Klasen Schuler and Permanyer argue that the GII is too complex, Shmid, Cook and Jones counter that argument with the notion that the current GII is too broad. Shmid, Cook and Jones analyze the GII and how impactful it is for Great Britain and come to the conclusion that there is no measure of gender disparities at the subnational level, leaving the GII being too board overall. [18]

Shmid, Cook and Jones claim that there are difficulties when measuring gender disparities through quantitative data, and that there is a lack of measuring what is important when it comes to gender inequality. [18] These authors state that a proposal for a subnational index including the domains of Paid Work, Money, Power & Participation, Education & Skills, and Unpaid Work will bring a more accurate measurement to gender disparities to Great Britain. [18]

Mix of indices

Both Klasen and Schüler as well as Permanyer argue that the GII mixes indices in a few ways which furthers the complexity and poses other issues. The measurement combines well-being and empowerment which becomes problematic in that it increases the complexity, lacks transparency, and suffers from the problem of using an arithmetic means of ratios. [3] [17] Permanyer argues that it also combines two different, absolute and relative, indicators within the same formula. For example, if the MMR is higher than 10 per 100,000 it is considered inequality. Yet, parliamentary representation is only considered inequality if there is a deviation from 50 percent. Therefore, if women and men fare equally in all dimensions the GII would not equal a zero value as it should. Permanyer gives an example for this problem:

Consider a hypothetical country with PRf = PRm, SEf = SEm, LFPRf = LFPRm and with the lowest MMR and AFR observed in the sample of countries for which data is available (MMR = 10, AFR = 3.8). In that case, that hypothetical country would have a GII value well above 0 (GII approximately 0.15). [3]

Formula Shortcomings

According to both Mcdonald and Koblitz, the GII formula has some issues that could be improved, the major issue being that it is composed of two indicators, maternal mortalities and teen pregnancies. [19] Mcdonald and Koblitz also claim the product of the formula mainly clusters the values towards zero, which for lower-income countries, can make these countries seem to have more issues with gender inequality than reality. [19] The authors claim the formula weighs too heavily on reproductive health causing disproportionate data towards poorer countries. Both Mcdonald and Koblitz believe the GII's formula has a bias towards richer countries and think that the formula should focus on other factors of gender disparity. [19]

Regional relevance

Permanyer also criticizes the GII for whether or not its assessment of gender inequality, and uses of the same set of indicators, are equally relevant or meaningful across all regions of the Globe. For less-developed countries the use of the MMR and AFR in the dimension of reproductive health may be penalizing although the loss may not be entirely explained by gender inequality. [3] Less-developed countries performance in the reproductive health dimension may differ regionally or locally. Access to or use of health services can be influenced by socio-economic levels, public health policies, or social and cultural practices. In developed countries, specifically European countries, gender inequality levels are not very "robust to alternative specifications of gender-related indicators" and analysts and policy makers may choose specific methods to yield desired results. [3]

Choice of variables

Klasen and Schüler briefly criticize the GII for its failure to capture the informal work and unpaid domestic or care work where women are primarily over-represented. In many underdeveloped societies women and girls spend the majority of their time in domestic work whereas men and boys spend far less, if any. [12] Therefore, the if the GII lacks the capturing of the time women spend in unpaid labor, it is insufficient in capturing the true global disparities of women. [17]

See also

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