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).^[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 (2017)

List of countries by their Gender Development Index 2017.^[3]

2017 Rank	Country	Gender Development Index	Human Development Index (Women)	Human Development Index (Men)
1	Qatar	1.031	0.870	0.843
2	Latvia	1.030	0.858	0.834
3	Lithuania	1.026	0.868	0.846
4	Mongolia	1.023	0.750	0.733
5	Belarus	1.020	0.814	0.799
6	Estonia	1.019	0.876	0.860
6	Russia	1.019	0.823	0.808
8	Barbados	1.015	0.805	0.792
9	Namibia	1.014	0.651	0.642
9	Uruguay	1.014	0.807	0.794
11	Trinidad and Tobago	1.013	0.794	0.784
12	Venezuela	1.011	0.762	0.754
13	Kazakhstan	1.007	0.801	0.795
14	Poland	1.006	0.866	0.861
15	Moldova	1.005	0.701	0.698
15	Vietnam	1.005	0.696	0.692
17	Lesotho	1.004	0.519	0.516
18	Slovenia	1.003	0.898	0.895
19	Burundi	1.002	0.419	0.418
20	Finland	1.000	0.917	0.917
20	Philippines	1.000	0.699	0.698
22	Argentina	0.997	0.816	0.819
22	Colombia	0.997	0.747	0.749
24	Thailand	0.996	0.753	0.756
25	Saint Lucia	0.993	0.744	0.749
25	Ukraine	0.993	0.746	0.751
27	Brazil	0.992	0.755	0.761
27	Sweden	0.992	0.927	0.934
27	United States	0.992	0.919	0.926
30	Norway	0.991	0.945	0.953
30	Croatia	0.991	0.828	0.835
30	Slovakia	0.991	0.850	0.858
33	Brunei	0.990	0.846	0.854
33	Bulgaria	0.990	0.808	0.816
33	Kuwait	0.990	0.791	0.799
36	Dominican Republic	0.989	0.728	0.736
37	Jamaica	0.988	0.731	0.739
37	Panama	0.988	0.782	0.791
39	Switzerland	0.987	0.937	0.949
39	France	0.987	0.894	0.906
41	Canada	0.986	0.916	0.930
41	Czech Republic	0.986	0.881	0.894
43	Romania	0.985	0.804	0.817
44	Hungary	0.985	0.830	0.843
45	South Africa	0.984	0.692	0.704
45	Cyprus	0.984	0.853	0.875
47	Portugal	0.983	0.839	0.853
48	Singapore	0.982	0.922	0.939
49	Denmark	0.980	0.919	0.938
51	Belize	0.979	0.699	0.714
51	Ireland	0.979	0.926	0.946
51	Spain	0.979	0.879	0.898
54	Ecuador	0.978	0.741	0.769
54	Honduras	0.978	0.608	0.622
56	Botswana	0.976	0.707	0.725
56	Malaysia	0.976	0.791	0.810
56	Serbia	0.976	0.777	0.796
59	Australia	0.975	0.926	0.950
59	Japan	0.975	0.894	0.917
59	Israel	0.975	0.890	0.913
59	Georgia	0.975	0.766	0.786
59	Suriname	0.975	0.705	0.723
64	Costa Rica	0.974	0.779	0.800
65	Paraguay	0.972	0.690	0.710
66	Belgium	0.971	0.901	0.928
66	Austria	0.971	0.893	0.920
68	Albania	0.970	0.772	0.796
69	Armenia	0.969	0.740	0.764
69	El Salvador	0.969	0.663	0.684
69	Luxembourg	0.969	0.888	0.916
72	Mauritius	0.968	0.773	0.799
72	United Arab Emirates	0.968	0.832	0.859
74	Germany	0.967	0.919	0.951
74	Italy	0.967	0.863	0.893
76	Iceland	0.966	0.920	0.952
76	Nicaragua	0.966	0.642	0.665
76	Netherlands	0.966	0.913	0.944
76	New Zealand	0.966	0.900	0.932
80	Hong Kong	0.965	0.916	0.949
81	Greece	0.964	0.853	0.885
82	Madagascar	0.962	0.511	0.531
83	Chile	0.961	0.823	0.856
84	Kyrgyzstan	0.960	0.654	0.681
84	Malta	0.960	0.858	0.893
84	Tonga	0.960	0.707	0.736
84	United Kingdom	0.960	0.903	0.941
88	Myanmar	0.959	0.563	0.586
89	Montenegro	0.956	0.794	0.831
90	China	0.955	0.735	0.769
91	Mexico	0.954	0.752	0.789
92	Peru	0.950	0.728	0.766
93	Azerbaijan	0.949	0.734	0.773
93	Cape Verde	0.949	0.632	0.666
95	Guyana	0.948	0.631	0.666
95	Guatemala	0.948	0.630	0.665
97	North Macedonia	0.946	0.731	0.773
98	Uzbekistan	0.945	0.687	0.726
99	Eswatini	0.943	0.568	0.603
100	Oman	0.942	0.781	0.829
100	Cuba	0.942	0.751	0.797
	⌀ average	0.941	0.705	0.749
102	Rwanda	0.941	0.508	0.540
102	Zambia	0.941	0.569	0.605
104	Malawi	0.936	0.460	0.492
105	Sri Lanka	0.935	0.738	0.789
106	Republic of the Congo	0.934	0.583	0.624
106	Laos	0.934	0.579	0.621
108	Tajikistan	0.933	0.624	0.669
109	Indonesia	0.932	0.666	0.715
109	South Korea	0.932	0.866	0.929
110	Bahrain	0.931	0.805	0.865
110	Kenya	0.931	0.568	0.610
112	Bolivia	0.929	0.665	0.716
112	Libya	0.929	0.668	0.719
114	Tanzania	0.928	0.517	0.557
115	Nepal	0.925	0.552	0.598
116	Bosnia and Herzegovina	0.924	0.739	0.800
116	Zimbabwe	0.924	0.513	0.555
118	Turkey	0.922	0.755	0.819
119	Maldives	0.919	0.679	0.739
120	Cambodia	0.914	0.553	0.605
121	Gabon	0.911	0.670	0.735
121	Senegal	0.911	0.481	0.528
123	Ghana	0.910	0.563	0.619
124	Mozambique	0.904	0.414	0.458
125	Tunisia	0.897	0.684	0.762
126	Bhutan	0.893	0.576	0.645
127	São Tomé and Príncipe	0.892	0.550	0.617
128	Gambia	0.890	0.434	0.487
129	Lebanon	0.889	0.701	0.788
130	Bangladesh	0.881	0.567	0.644
131	Palestine	0.877	0.623	0.710
131	Saudi Arabia	0.877	0.782	0.892
133	Comoros	0.876	0.465	0.531
134	Benin	0.875	0.479	0.547
135	Egypt	0.872	0.636	0.729
135	Sierra Leone	0.872	0.389	0.446
137	Iran	0.871	0.726	0.834
138	Burkina Faso	0.870	0.393	0.452
139	Nigeria	0.868	0.494	0.569
140	Cameroon	0.866	0.513	0.593
141	Uganda	0.865	0.475	0.550
142	Algeria	0.861	0.680	0.791
143	Jordan	0.857	0.658	0.767
144	Timor-Leste	0.855	0.567	0.663
145	Democratic Republic of the Congo	0.852	0.420	0.493
146	Ethiopia	0.846	0.424	0.501
146	Liberia	0.846	0.398	0.470
148	Mauritania	0.845	0.470	0.556
149	Ivory Coast	0.841	0.446	0.531
149	India	0.841	0.575	0.683
151	Morocco	0.838	0.598	0.713
152	Sudan	0.831	0.446	0.537
153	South Sudan	0.826	0.348	0.422
154	Iraq	0.823	0.603	0.733
155	Togo	0.822	0.446	0.542
156	Niger	0.812	0.317	0.391
157	Mali	0.811	0.380	0.469
158	Guinea	0.810	0.411	0.507
159	Syria	0.788	0.443	0.563
160	Central African Republic	0.780	0.319	0.409
161	Chad	0.775	0.350	0.452
162	Pakistan	0.750	0.465	0.620
163	Afghanistan	0.625	0.364	0.583
164	Yemen	0.425	0.223	0.524

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