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Gender Development Index

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The Gender Related Development Index (GDI) is an index designed to measure gender equality.

GDI together with the Gender Empowerment Measure (GEM) were introduced in 1995 in the Human Development Report written by the United Nations Development Program. The aim of these measurements was to add a gender-sensitive dimension to the Human Development Index (HDI). The first measurement that they created as a result was the Gender-related Development Index (GDI). The GDI is defined as a "distribution-sensitive measure that accounts for the human development impact of existing gender gaps in the three components of the HDI" (Klasen 243). Distribution sensitive means that the GDI takes into account not only the averaged or general level of well-being and wealth within a given country, but focuses also on how this wealth and well-being is distributed between different groups within society. The HDI and the GDI (as well as the GEM) were created to rival the more traditional general income-based measures of development such as gross domestic product (GDP) and gross national product (GNP).[1]

Definition and calculation

The GDI is often considered a "gender-sensitive extension of the HDI" (Klasen 245). It addresses gender-gaps in life expectancy, education, and incomes. It uses an "inequality aversion" penalty, which creates a development score penalty for gender gaps in any of the categories of the Human Development Index which include life expectancy, adult literacy, school enrollment, and logarithmic transformations of per-capita income. In terms of life expectancy, the GDI assumes that women will live an average of five years longer than men. Additionally, in terms of income, the GDI considers income-gaps in terms of actual earned income.[1] The GDI cannot be used independently from the Human Development Index (HDI) score and so, it cannot be used on its own as an indicator of gender-gaps. Only the gap between the HDI and the GDI can actually be accurately considered; the GDI on its own is not an independent measure of gender-gaps.[2]

Gender Development Index (2018)

Below is a list of countries by their Gender Development Index, based on data collected in 2018, and published in 2019.[3] Countries are grouped into five groups based on the absolute deviation from gender parity in HDI values, from 1 (most gender parity) to 5 (least gender parity). This means that grouping takes equally into consideration gender gaps favoring males, as well as those favoring females.

2018
Rank 		Country Gender Development Index Group Human Development Index
(Women) 		Human Development Index
(Men)
1 Kuwait 0.999271313598908 1 0.802241545091312 0.802826553883562
2 Kazakhstan 0.998616111258415 1 0.814121946939387 0.815250162460792
3 Trinidad and Tobago 1.00211774602851 1 0.797989701033099 0.796303332812547
4 Slovenia 1.00257442927832 1 0.901787072451453 0.899471446823739
5 Vietnam 1.00272297523169 1 0.693389879484458 0.691506923259876
6 Burundi 1.00324890931813 1 0.421654103634997 0.420288624008154
7 Dominican Republic 1.00339001174288 1 0.744042111285307 0.741528321567516
8 Philippines 1.00369597615498 1 0.712223593546365 0.709600925446362
9 Thailand 0.995480861692473 1 0.762715746885023 0.766178212194142
10 Panama 1.00461251995559 1 0.793862458409325 0.790217564125534
11 Ukraine 0.995122669191676 1 0.745224174704749 0.748876694076404
12 Brazil 0.995109362655928 1 0.757109191363106 0.760830135636948
13 Moldova 1.00705674095832 1 0.713558080174709 0.70855797012558
14 Bulgaria 0.992621622836447 1 0.811903568014688 0.817938627706547
15 Slovakia 0.992371676979385 1 0.852080306845641 0.858630215484618
16 Poland 1.00854973881397 1 0.874194924380356 0.86678414632122
17 United States 0.99144743381844 1 0.914844606387427 0.922736370262227
18 Namibia 1.0094706476123 1 0.647427874518634 0.641353838321097
19 Norway 0.990437581014824 1 0.94564679665501 0.954776772187986
20 Finland 0.989817373600636 1 0.919751993696064 0.929213830982077
21 Barbados 1.01032361432783 1 0.816388101546477 0.808046144788592
22 Belarus 1.010339927488 1 0.819686875325532 0.811298111679611
23 Botswana 0.989531869461814 1 0.723041706146159 0.730690671478228
24 Canada 0.989058149729888 1 0.915888363975847 0.926020744307072
25 Croatia 0.98859213038971 1 0.832316431348996 0.841920955835336
26 Singapore 0.98814794506132 1 0.929356109430028 0.940503002687878
27 Argentina 0.987919014775328 1 0.817640023795134 0.827638714880978
28 Venezuela 1.01272311153934 1 0.728475070383083 0.719323043073244
29 Brunei 0.986891147195856 1 0.836720430865344 0.847834569438376
30 Nicaragua 1.01321583363332 1 0.654849103183038 0.646307609342023
31 Colombia 0.986296673191879 1 0.754714364824177 0.765200152588724
32 Romania 0.986261546538915 1 0.809420161886165 0.820695245319724
33 Jamaica 0.986030910048998 1 0.718965693897112 0.729151273626285
34 Russia 1.01499805083001 1 0.828317933961805 0.816078349396287
35 France 0.98439750467821 1 0.883037148032378 0.897033102822659
36 Estonia 1.01574985871536 1 0.885869263158098 0.872133287105225
37 South Africa 0.984153359434317 1 0.698296318804934 0.709540146473014
38 Portugal 0.984006569463407 1 0.842559344988258 0.856253780345916
39 Uruguay 1.01607193850868 1 0.809691228698831 0.79688376187934
40 Hungary 0.983855072217788 1 0.836374771060734 0.850099567180554
41 Cape Verde 0.98384439453558 1 0.644164225448235 0.654741978534431
42 Cyprus 0.983090727880394 1 0.864740933228215 0.879614575444782
43 Czech Republic 0.983021479607738 1 0.881578351276749 0.896804769340881
44 Belize 0.982811514946144 1 0.712983445231243 0.725452881237674
45 Sweden 0.981817713523961 1 0.927549412691099 0.944726704269694
46 Spain 0.98068365758681 1 0.881897607495364 0.899268179573288
47 Denmark 0.980461996197969 1 0.920118047343707 0.938453556498605
48 Ecuador 0.979876022499264 1 0.747701339556282 0.763057083128946
49 Georgia 0.978843828928938 1 0.774556381501532 0.791297200442139
50 Costa Rica 0.977136852016496 1 0.781504112645575 0.799789825788274
51 Japan 0.976487130681848 1 0.901210670433948 0.92291095511383
52 Serbia 0.976372480770375 1 0.789117394155053 0.808213473542829
53 Australia 0.975113503181452 1 0.925664958786577 0.949289447604262
54 Ireland 0.974930720274505 2 0.928842297989999 0.9527264642235
55 Saint Lucia 0.974776845288729 2 0.734104181262105 0.753099732323518
56 Lesotho 1.02554956311433 2 0.522151801801454 0.50914341011059
57 Mauritius 0.973598560971563 2 0.781958849986583 0.803163522762666
58 Guyana 0.973439493655793 2 0.655984723050024 0.673883407572098
59 Armenia 0.972097105538784 2 0.745713315885668 0.767118132166803
60 Lithuania 1.02801557456846 2 0.880350319739633 0.856358932216745
61 Belgium 0.971637285832976 2 0.904498199776896 0.93090108105668
62 Suriname 0.971619589838185 2 0.710079630808469 0.730820619751736
63 Israel 0.971565636624078 2 0.89085212219952 0.916924280375936
64 Malaysia 0.971535181068249 2 0.791500865872141 0.814690894674394
65 Albania 0.971302380112087 2 0.778864159321813 0.801876094684266
66 Honduras 0.970407383075693 2 0.611426703399936 0.630072188303048
67 Luxembourg 0.970263947573514 2 0.893206480322808 0.920580922909261
68 Latvia 1.03040141727652 2 0.86528356437401 0.839753856959034
69 Mongolia 1.03051247212425 2 0.745684609993285 0.723605613871095
70 El Salvador 0.969303900072772 2 0.65414310778579 0.67485863591045
71 Germany 0.968046731183915 2 0.922788125514936 0.953247499102003
72 Paraguay 0.968014313475195 2 0.710081665159304 0.733544592548527
73 Italy 0.967274986133354 2 0.865859235918938 0.895153134663575
74 United Kingdom 0.96671693364499 2 0.903526469774669 0.934633953672392
75 Netherlands 0.966586563190941 2 0.915682504422063 0.94733626484437
76 Iceland 0.966035360302579 2 0.921422694662473 0.953818806771077
77 Montenegro 0.965505839872185 2 0.800863981950797 0.829476062057601
78 United Arab Emirates 0.965148016786254 2 0.831679159131191 0.861711514364929
79 Malta 0.964573668396 2 0.867003905508653 0.898846748481537
80 New Zealand 0.963450079812055 2 0.901877659315533 0.936091737613916
81  Switzerland 0.963384994370094 2 0.924302891740428 0.959432518818482
82 Hong Kong 0.96331458591632 2 0.91883629861405 0.953827868951074
83 Austria 0.962992625875126 2 0.894949094941461 0.929341586731435
84 Greece 0.96272210220035 2 0.854140900297802 0.887214387563783
85 Swaziland 0.962280698092814 2 0.594969468404531 0.618290972253447
86 Chile 0.961896022109213 2 0.827637034592205 0.860422556668226
87 China 0.960737178700119 2 0.7411723134053 0.771462091649362
88 Kyrgyzstan 0.959354156976191 2 0.655758696158308 0.683541830084114
89 Mexico 0.957251775460597 2 0.747167434728433 0.780533871947035
90 Qatar 1.04338023447896 2 0.87328373892252 0.836975543588494
91 Myanmar 0.953281245175706 2 0.566167394183869 0.593914332259327
92 Peru 0.951068629111926 2 0.73835574021778 0.776343281249042
93 Zambia 0.949346763894446 3 0.575199531528163 0.60588981118823
94 Cuba 0.94847909440168 3 0.752740766990656 0.793629265456294
95 North Macedonia 0.946858477421388 3 0.736774749145141 0.778125524261687
96 Madagascar 0.946436637249011 3 0.504225253132795 0.532761764800671
97 Tonga 0.944301733548051 3 0.691914784976437 0.732726373779583
98 Guatemala 0.943001743676744 3 0.628457412659945 0.666443531917134
99 Rwanda 0.942983702163843 3 0.519691032216798 0.551113482687214
100 Oman 0.942644918586126 3 0.792879654368817 0.841122291899752
– World average 0.941430799701876 – 0.706980962068851 0.750964343096414
101 Azerbaijan 0.94043401604125 3 0.728006586417231 0.774117666948894
102 Maldives 0.938974186367784 3 0.689217295551526 0.734010908454909
103 Uzbekistan 0.938530667537194 3 0.685437015702195 0.730329907599989
104 Sri Lanka 0.937501402709405 3 0.749425007262443 0.799385478354042
105 Indonesia 0.937278216882204 3 0.681319036769408 0.726912270548411
106 Bahrain 0.936580181665306 3 0.799753662146286 0.853908376242029
107 Bolivia 0.936071128421922 3 0.677681643411889 0.723963834408994
108 Tanzania 0.93556520183438 3 0.509116716427692 0.54418090308346
109 South Korea 0.933514804909621 3 0.869859990274136 0.931811671008637
110 Kenya 0.93334124890745 3 0.553446092043308 0.592972926773739
111 Libya 0.930834633256552 3 0.670350699455828 0.720160891640427
112 Republic of the Congo 0.930508381323755 3 0.590608226344738 0.63471564383389
113 Malawi 0.929979500928547 3 0.466256425669024 0.501362046371437
114 Laos 0.929388949637999 3 0.580896379268115 0.625030434775856
115 Zimbabwe 0.924865126473049 4 0.540217146902477 0.584103704896499
116 Turkey 0.923845887665176 4 0.770530112179602 0.834046156904971
117 Bosnia and Herzegovina 0.92376150833791 4 0.735305564655512 0.795990694587958
118 Cambodia 0.919132552991075 4 0.556669111249323 0.605646170879042
119 Gabon 0.917044836281997 4 0.668897563298245 0.72940551741197
120 Ghana 0.912066262295093 4 0.567120060412223 0.621796994206474
121 Angola 0.901852522177659 4 0.545524138209497 0.60489284533157
122 Mozambique 0.901399241057088 4 0.42171001631638 0.467839329243092
123 São Tomé and Príncipe 0.899721720272795 5 0.571432940029916 0.635121868411333
124 East Timor 0.899338643290567 5 0.589475390655512 0.655454310846352
125 Liberia 0.898619930984625 5 0.437938141035413 0.487345234548226
126 Tunisia 0.898516211947261 5 0.68930089658175 0.767154657218593
129   Nepal 0.897374748629354 5 0.548886325033576 0.611657867431575
130 Bangladesh 0.895463713494037 5 0.574538067712771 0.64160954715961
131 Bhutan 0.893345815434905 5 0.580503137357053 0.649807865361129
132 Lebanon 0.890577064263023 5 0.678454800871403 0.761814814344947
133 Haiti 0.890365827551326 5 0.477397671690552 0.536181485090781
134 Comoros 0.888069540927266 5 0.504017390629825 0.567542706288025
135 Benin 0.883486835760026 5 0.485715005319931 0.549770506656267
136 Sierra Leone 0.882483208929897 5 0.410599830153055 0.465277782056556
137 Saudi Arabia 0.879136805709795 5 0.784333088515893 0.892162725325372
138 Egypt 0.878316588012583 5 0.64266778257163 0.731704024884503
139 Burkina Faso 0.874690316250611 5 0.403149171515835 0.460905035789063
140 Iran 0.873999741121421 5 0.726849370286313 0.831635681440477
141 Senegal 0.87347139391351 5 0.475960252557682 0.544906514253643
142 Palestine 0.871346924588787 5 0.623519218495938 0.71558090227976
143 Cameroon 0.86892158600649 5 0.522007757584777 0.600753584663367
144 Jordan 0.868301159101109 5 0.654288917853024 0.753527633811249
145 Nigeria 0.867675972564795 5 0.491676192340555 0.566658761896094
146 Algeria 0.864588565403417 5 0.684971930096163 0.792251895879002
147 Uganda 0.86268775649487 5 0.48376445336274 0.56076425070444
148 Mauritania 0.852934961025278 5 0.479113168207732 0.561722980181056
149 Democratic Republic of the Congo 0.844045244422387 5 0.418857464866842 0.496250014599019
150 Ethiopia 0.843899175273984 5 0.42770052294657 0.506814718485429
151 South Sudan 0.838915228792041 5 0.368735499184939 0.439538449809623
152 Sudan 0.836500123073206 5 0.456500034277483 0.545726200972158
153 Morocco 0.832807050749792 5 0.602993983556629 0.724050046182658
154 Gambia 0.832110339375305 5 0.415697194375194 0.499569798264101
155 India 0.828659271423645 5 0.573650381208353 0.692263275136976
156 Togo 0.817890855118709 5 0.458991965749326 0.561189751513615
157 Mali 0.807099598839839 5 0.380140424771307 0.470995680480746
158 Guinea 0.80606657004618 5 0.41342656240414 0.512893820147453
159 Tajikistan 0.798555909314393 5 0.561341006774011 0.702945154154523
160 Ivory Coast 0.796251100904936 5 0.445376820642565 0.559342172508641
161 Central African Republic 0.795444752528615 5 0.335149259100481 0.421335684263534
162 Syria 0.79532319946114 5 0.457372222910504 0.57507718022106
163 Iraq 0.789324230426714 5 0.587352897134761 0.744121204561571
164 Chad 0.774452360811538 5 0.347398235861034 0.448572763723
165 Pakistan 0.746878273640409 5 0.464284284133844 0.621633136911112
166 Afghanistan 0.722861973965333 5 0.410756365978411 0.568236234263597
167 Yemen 0.457536126892644 5 0.244873082377673 0.5351994476168
168 Niger 0.298179843688684 5 0.129771161871938 0.435211046684383

Controversies

General debates

In the years since its creation in 1995, much debate has arisen surrounding the reliability, and usefulness of the Gender Development Index (GDI) in making adequate comparisons between different countries and in promoting gender-sensitive development. The GDI is particularly criticized for being often mistakenly interpreted as an independent measure of gender-gaps when it is not, in fact, intended to be interpreted in that way, because it can only be used in combination with the scores from the Human Development Index, but not on its own. Additionally, the data that is needed in order to calculate the GDI is not always readily available in many countries, making the measure very hard to calculate uniformly and internationally. There is also worry that the combination of so many different developmental influences in one measurement could result in muddled results and that perhaps the GDI (and the GEM) actually hide more than they reveal.[1]

Debates surrounding the life expectancy adjustment

More specifically, there has been a lot of debate over the life-expectancy component of the Gender-related Development Index (GDI). As was mentioned previously, the GDI life expectancy section is adjusted to assume that women will live, normally, five years longer than men. This provision has been debated, and it has been argued that if the GDI was really looking to promote true equality, it would strive to attain the same life-expectancy for women and men, despite what might be considered a biological advantage or not. However, this may seem paradoxical in terms of policy implications, because, theoretically, this could only be achieved through providing preferential treatment to males, effectively discriminating against females. Furthermore, it has been argued that the GDI doesn't account for sex-selective abortion, meaning that the penalty levied against a country for gender inequality is less because it affects less of the population (see Sen, Missing Women).[1]

Debates surrounding income gaps

Another area of debate surrounding the Gender-related Development Index (GDI) is in the area of income gaps. The GDI considers income-gaps in terms of actual earned income. This has been said to be problematic because often, men may make more money than women, but their income is shared. Additionally, the GDI has been criticized because it does not consider the value of care work as well as other work performed in the informal sector (such as cleaning, cooking, housework, and childcare). Another criticism of the GDI is that it only takes gender into account as a factor for inequality, it does not, however, consider inequality among class, region or race, which could be very significant.[1] Another criticism with the income-gap portion of the GDI is that it is heavily dependent on gross domestic product (GDP) and gross national product (GNP). For most countries, the earned-income gap accounts for more than 90% of the gender penalty.

Suggested alternatives

As was suggested by Halis Akder in 1994, one alternative to the Gender-related Development Index would be the calculation of a separate male and female Human Development Index (HDI). Another suggested alternative is the Gender Gap Measure which could be interpreted directly as a measure of gender inequality, instead of having to be compared to the Human Development Index (HDI) as the GDI is. It would average the female-male gaps in human development and use a gender-gap in labor force participation instead of earned income. In the 2010 Human Development Report, another alternative to the Gender-related Development Index (GDI), namely, the Gender Inequality Index (GII) was proposed in order to address some of the shortcomings of the GDI. This new experimental measure contains three dimensions: Reproductive Health, Empowerment, and Labor Market Participation.[2]

See also

Indices

References

  1. ^ a b c d e Klasen S. UNDP's Gender-Related Measures: Some Conceptual Problems and Possible Solutions. Journal of Human Development [serial online]. July 2006;7(2):243-274. Available from: EconLit with Full Text, Ipswich, MA. Accessed September 26, 2011.
  2. ^ a b Klasen, Stephan1; Schuler, Dana. Reforming the Gender-Related Development Index and the Gender Empowerment Measure: Implementing Some Specific Proposals. Feminist Economics. January 2011 (1) 1 - 30
  3. ^ "Gender Development Index (GDI)". United Nations Development Programme - Human Development Reports. Retrieved 12 December 2019.
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