Gender Development Index

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).

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. 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.

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

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).

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. 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.

See also

Indices

• American Human Development Report
• Bhutan GNH Index
• Broad measures of economic progress
• Disability-adjusted life year
• Economics
• Full cost accounting
• Gender Parity Index
• Genuine Progress Indicator (GPI)
• Global Peace Index
• Green gross domestic product (Green GDP)
• Green national product
• Gross National Happiness
• Gross National Well-being (GNW)
• Happiness economics
• Happy Planet Index (HPI)
• Human Development Index (HDI)
• Human Poverty Index
• ISEW (Index of sustainable economic welfare)
• Law of Social Cycle
• Legatum Prosperity Index
• Leisure satisfaction
• Living planet index
• Millennium Development Goals (MDGs)
• Money-rich, time-poor
• National Human Development Report
• OECD Better Life Index BLI
• Post-materialism
• Progress (history)
• Progressive utilization theory
• Psychometrics
• Subjective life satisfaction
• Where-to-be-born Index
• Wikiprogress
• World Happiness Report (WHR)
• World Values Survey (WVS)