Background
The BIGI scale provides an indication of the level of gender inequality in different countries. Indicators of gender inequality are useful for a variety of reasons:
-
They highlight policy-relevant sources of inequality.
-
They highlight how well specific countries are achieving equality relative to their neighbors and other countries around the world.
-
They help individuals to better understand the country they live in.
There have been various attempts to rank countries in regard to gender inequality. Each of the currently available approaches (such as the Global Gender Gap Index, GGGI) has its shortcomings (more below).
For example, the GGGI calculates gender ratios in a way that does not fully capture instances when men fall behind women (e.g., in healthy lifespan). Further, it relies heavily on issues that are often highlighted in women’s rights movements. While those issues are important, they are not the only factors that influence gender inequality. Issues that negatively affect more men than women are not fully considered (see FAQ for more discussion about this). While the GGGI can be useful as a measure of women’s advancement in the areas of politics and employment, it is too biased to one specific gender to consider it a true measure of gender equality (see the original PLOS ONE article for more discussion on this).
In contrast, the BIGI aims to provide a simplified and unbiased measure by focusing on key indicators that are relevant to all men and women in any society. BIGI focuses on key ingredients of a good life:
-
Healthy Life Expectancy (years expected to live in good health)
-
Basic education (literacy, and years of primary, and secondary education)
-
Life satisfaction
These three factors are the minimal ingredients of a good life. Ignoring even one of them leaves out an important aspect of what it takes to have a good life. For example, you may have a long life and be quite satisfied with your life situation, but if you haven’t had a basic education, you likely have missed important opportunities. Equally, you may be very well educated and be satisfied with your life situation, but that is all less meaningful if your healthy lifespan is too short.
In short, the combination of the three factors above are key ingredients of a good life. Remove just one of them, and you miss something fundamentally important. That is exactly why BIGI has these 3 factors!
The website provides average scores for many countries throughout the world. National averages (i.e., of the average Joe and Jane) are useful, but there are of course always individuals who are very different from the average. Keep this in mind when reading! |
Calculation
A simple formula
A nation’s BIGI score is simply
the average of the gender ratios for the three key ingredients of the
BIGI.
-
Healthy Life Expectancy
-
Basic education
-
Life satisfaction
Each of these three elements weighs equally in the calculation. For the sources of these three factors and more information about the methodology, read the original article in PLOS ONE.
A gender ratio is the score of one gender divided by the score of the other gender (typically score of women divided by score of men). We use the gender ratio minus 1.0, such that BIGI scores below zero mean than women are better off; scores higher than zero mean that men are better off (example below).
Please also note that the division of two values can lead to an
asymmetry of scores. For example, 80/78=1.02564, whereas
78/80=0.975. In other words, the ratio 80/78 leads to a slightly larger
deviation from 1.0 than the ratio 78/80. To resolve this asymmetry, BIGI always divides the smaller value by the larger value and then subtracts 1.0 (or subtracts the value from 1). In the social sciences, this is a commonly used way of resolving the asymmetry in gender ratios. Without it, the results would be biased. |
The BIGI can be calculated for each year. In the main paper, a 5-year BIGI is used, that is, the BIGI scores of 5 consecutive years averaged. This reduces the likelihood that values are influenced by small random year-to-year fluctuations. |
Complete calculation example for the USA
The BIGI as reported here is the
average of the BIGI of the years 2012, 2013, 2014, 2015, and
2016. That is, it is a 5-year BIGI. The calculation of each year uses
exactly the same methodology. Below are the details for the 2016 data.
-
In the USA, the healthy life span in 2016 was 71 years for women and 68 years for men. Normally, we divide the female/male value (i.e., 1.044118), but because the male value is smaller and in order to keep symmetry, we calculate the ratio as 2 - 68/71 = 1.042254.
-
For 2016, boys and girls are equally often enrolled in primary education and have the same level of literacy (2016 GGGI report, p.50-51). In secondary education, however, fewer boys (89%) than girls (92%) were enrolled (2016 GGGI report, p.52). This gives a ratio of 2 - 89/92 = 1.032609. For BIGI’s basic education value, we take the value that deviates most from parity, which is the secondary education ratio.
-
We took the life satisfaction information from the Gallup World Poll data 2016 (these data are available via Gallup Analytics, which is a paid service). In the USA, women’s 2016 life satisfaction score was 6.90940845881857 and that of men was 6.69475363004137 on a 0 to 10 scale. The ratio was 1.0311.
-
The average of the three ratios above (healthy life span ratio, 1.0423, education score, 1.0326, and the life satisfaction score, 1.0311) is 1.0353.
-
In order to have 0 as representing parity, we subtracted the results from 1, that is 1 – 1.0353 = -0.0353. In other words, in the US in 2016, the BIGI deviation from parity was 3.5% (in favor of women, because the value is below zero).
-
The US’s BIGI scores for the years 2012-2015 were calculated in the same way as the 2016 BIGI. The mean of -0.0357, -0.0419, -0.0246, -0.0271, and -0.0353 provide a 5-year average of -0.0329.
How to rank BIGI scores
The BIGI is the average of the
three ratios is education, healthy life span, and life
satisfaction. Importantly, a value of 0 means that there is a good
balance between these three, but it does not necessarily mean that the
society is doing well for its citizens (as noted before).
For example, women might fall behind in education while men fall behind in healthy life expectancy. In that way, everybody suffers, but on average, the suffering is canceled out in the overall BIGI score (leading to a good BIGI ranking).
The main conclusion is therefore that even when BIGI is zero, a country may still need to address several gender-specific inequalities.
To deal with this issue, we also calculated a the Average Absolute Deviation from gender Parity (AADP). This AADP score ignores whether it is men or women falling behind, and just takes the average of the three domains (health, education, and healthy life expectancy) irrespective of which gender is doing better. It is called an absolute value because the sign (positive or negative) is ignored.
Data
The table below includes data from 134 nations. First, the meaning of each of the columns is explained here. Note that all data are downloadable as spreadsheet in the original paper (see below).
Column |
Meaning |
AADP rank |
This Average Deviation from gender Parity ranking is based on the AADP score (explained above). This ranking gives a sense of how close a country is to achieving gender equality (remember, equality does not necessarily mean that men and women are doing well, on average, just that they are more or less equal within their life circumstances). |
BIGI rank |
This ranking is based on the absolute BIGI score (i.e., the closer BIGI is to zero, the better the rank). Note that BIGI averages out advantages and disadvantages in the individual components. The idea is that falling behind in one component can be balanced out by leading in another component. |
Country |
Name of the country |
Better off? |
A female icon () indicates that women are better off, on average (BIGI < 0). |
BIGI |
The Basic Index of Gender Inequality score |
AADP |
Average Absolute Deviation from Parity score. The average of how far the absolute scores of components are from parity. |
Education |
The education component of BIGI |
Healthy Life Expectation |
The healthy life expectation component of BIGI |
Life Satisfaction |
The life satisfaction component of BIGI |
HDI |
Human Development Index. This is not a component of the BIGI but shown for comparison only. The human development index provides an indication of how well a country does in terms of economic prosperity, expected years of education, and health in the period 2012-2015. Values of 0.80 and greater indicate very highly developed (e.g., USA, UK, Australia, Russia, Saudi Arabia). Values between 0.70 and 0.79 are highly developed (e.g., China, Brazil, Turkey). Values between 0.55 and 0.69 were medium developed (e.g., India, Egypt, South Africa, Guatemala). Values below 0.55 indicate low development (e.g., Chad, Pakistan). |
Click on the headers of the table below to sort differently. Pink values indicate women are better off, blue values indicate men are better off. Hover over numbers to see their column meaning. |
AADP rank | BIGI rank | Country | Better off? | BIGI | AADP | Education | Healthy Life Span | Overall life sastisfaction | HDI |
---|---|---|---|---|---|---|---|---|---|
1 |
12 |
Bahrain |
-0.007938 |
0.007938 |
-0.01264 |
0 |
-0.011173 |
0.8205 |
|
2 |
24 |
Great Britain |
-0.014545 |
0.015671 |
-0.012144 |
-0.033181 |
0.001689 |
0.905 |
|
3 |
27 |
Netherlands |
-0.01585 |
0.01585 |
-0.011092 |
-0.027477 |
-0.008982 |
0.923 |
|
4 |
35 |
Iceland |
-0.017683 |
0.016813 |
-0.011009 |
-0.024365 |
-0.015064 |
0.9155 |
|
5 |
32 |
New Zealand |
-0.017086 |
0.017086 |
-0.010333 |
-0.027249 |
-0.013675 |
0.9115 |
|
6 |
30 |
Serbia |
-0.016696 |
0.018513 |
-0.004871 |
-0.047942 |
0.002726 |
0.772 |
|
7 |
39 |
Norway |
-0.019498 |
0.01865 |
-0.004167 |
-0.033033 |
-0.01875 |
0.946 |
|
8 |
34 |
Ireland |
-0.017437 |
0.020111 |
0.00401 |
-0.046353 |
-0.009969 |
0.91375 |
|
9 |
40 |
Ecuador |
-0.020118 |
0.020118 |
-0.006632 |
-0.053476 |
-0.000245 |
0.735 |
|
10 |
31 |
Lebanon |
-0.016971 |
0.020164 |
0.004789 |
-0.044718 |
-0.010983 |
0.76375 |
|
11 |
10 |
Malta |
-0.007316 |
0.021697 |
-0.010637 |
-0.032883 |
0.021571 |
0.846 |
|
12 |
16 |
Belgium |
-0.011181 |
0.021904 |
0.016085 |
-0.049247 |
-0.000381 |
0.8925 |
|
13 |
2 |
Israel |
0.000626 |
0.022297 |
0.021106 |
-0.032506 |
0.013278 |
0.89575 |
|
14 |
45 |
United Arab Emirates |
-0.022441 |
0.022441 |
-0.03587 |
0 |
-0.031452 |
0.83425 |
|
15 |
26 |
Sweden |
-0.015749 |
0.022527 |
0.010167 |
-0.037918 |
-0.019497 |
0.908 |
|
16 |
46 |
Denmark |
-0.023474 |
0.023474 |
-0.03058 |
-0.036039 |
-0.003803 |
0.9245 |
|
17 |
23 |
Canada |
-0.014173 |
0.023803 |
0.014445 |
-0.037772 |
-0.019194 |
0.915 |
|
18 |
11 |
Switzerland |
-0.007938 |
0.023909 |
0.024043 |
-0.040114 |
-0.007569 |
0.93675 |
|
19 |
49 |
Australia |
-0.024204 |
0.024204 |
-0.013848 |
-0.040324 |
-0.018441 |
0.93625 |
|
20 |
36 |
Czech Rep. |
-0.018326 |
0.024658 |
0.003245 |
-0.064476 |
0.006253 |
0.87225 |
|
21 |
52 |
Cyprus |
-0.025501 |
0.025501 |
-0.013173 |
-0.034952 |
-0.028379 |
0.85225 |
|
22 |
43 |
France |
-0.021771 |
0.025667 |
-0.0043 |
-0.066856 |
0.005844 |
0.892 |
|
23 |
4 |
Azerbaijan |
-0.002668 |
0.026392 |
0.027811 |
-0.04359 |
0.007774 |
0.7535 |
|
24 |
1 |
Italy |
0.00021 |
0.026953 |
0.001775 |
-0.040114 |
0.03897 |
0.88025 |
|
25 |
87 |
Belize |
-0.047942 |
0.029393 |
0.003228 |
-0.08355 |
-0.001401 |
0.70575 |
|
26 |
20 |
Germany |
-0.012993 |
0.029448 |
0.024682 |
-0.05147 |
-0.012191 |
0.92225 |
|
27 |
58 |
Spain |
-0.029903 |
0.029903 |
-0.004376 |
-0.058316 |
-0.027016 |
0.87925 |
|
28 |
21 |
Montenegro |
-0.013121 |
0.030233 |
0.032375 |
-0.039801 |
-0.018523 |
0.80325 |
|
29 |
33 |
Austria |
-0.017387 |
0.030574 |
0.01978 |
-0.059978 |
-0.011964 |
0.891 |
|
30 |
42 |
Luxembourg |
-0.021134 |
0.030914 |
-0.032081 |
-0.045991 |
0.014671 |
0.8945 |
|
31 |
18 |
Albania |
-0.012889 |
0.032231 |
0.029013 |
-0.018182 |
-0.049498 |
0.7615 |
|
32 |
66 |
Malaysia |
-0.035954 |
0.032424 |
-0.005047 |
-0.051515 |
-0.04071 |
0.7845 |
|
33 |
9 |
Macedonia |
0.006834 |
0.032443 |
0.028064 |
-0.038414 |
0.030851 |
0.7445 |
|
34 |
61 |
United States of America |
-0.032937 |
0.032937 |
-0.020057 |
-0.047574 |
-0.03118 |
0.91725 |
|
35 |
62 |
Jordan |
-0.03303 |
0.03303 |
-0.004681 |
-0.021731 |
-0.072677 |
0.739 |
|
36 |
8 |
China |
0.00626 |
0.03352 |
0.059671 |
-0.035038 |
-0.005851 |
0.727 |
|
37 |
63 |
Chile |
-0.033213 |
0.03356 |
-0.039049 |
-0.061111 |
0.00052 |
0.841 |
|
38 |
38 |
Greece |
-0.019161 |
0.034141 |
0.022471 |
-0.049093 |
-0.030861 |
0.86325 |
|
39 |
37 |
Peru |
0.018633 |
0.034378 |
0.075095 |
-0.023617 |
0.004421 |
0.73575 |
|
40 |
60 |
Moldova (Republic of) |
-0.032404 |
0.034522 |
0.003177 |
-0.095382 |
-0.005008 |
0.6955 |
|
41 |
65 |
Mexico |
-0.035445 |
0.035445 |
-0.042414 |
-0.057971 |
-0.00595 |
0.75675 |
|
42 |
13 |
Madagascar |
0.009967 |
0.035804 |
0.068657 |
-0.036523 |
-0.002231 |
0.51 |
|
43 |
68 |
Paraguay |
-0.035997 |
0.035997 |
-0.052707 |
-0.054003 |
-0.001281 |
0.688 |
|
44 |
44 |
Slovenia |
-0.02206 |
0.036205 |
-0.010598 |
-0.076799 |
0.021218 |
0.886 |
|
45 |
70 |
Brazil |
-0.036775 |
0.036775 |
-0.03711 |
-0.06858 |
-0.004635 |
0.74725 |
|
46 |
50 |
Romania |
-0.024549 |
0.036919 |
-0.010617 |
-0.081586 |
0.018555 |
0.79775 |
|
47 |
59 |
Kuwait |
-0.031057 |
0.036939 |
-0.04861 |
0.008824 |
-0.053385 |
0.7955 |
|
48 |
6 |
Singapore |
0.003147 |
0.037008 |
0.057096 |
-0.04451 |
-0.009419 |
0.92275 |
|
49 |
5 |
Indonesia |
-0.003089 |
0.037768 |
0.052019 |
-0.034682 |
-0.026604 |
0.6835 |
|
50 |
72 |
Finland |
-0.038021 |
0.038021 |
-0.006278 |
-0.065023 |
-0.042763 |
0.89125 |
|
51 |
25 |
Kyrgyz Republic |
-0.015089 |
0.038572 |
0.022181 |
-0.080492 |
0.013044 |
0.65725 |
|
52 |
29 |
Georgia |
-0.016536 |
0.038659 |
0.03072 |
-0.082792 |
0.002464 |
0.76275 |
|
53 |
73 |
Bangladesh |
-0.038924 |
0.038924 |
-0.035228 |
-0.009039 |
-0.072505 |
0.57225 |
|
54 |
41 |
Slovak Republic |
-0.021043 |
0.039909 |
0.003137 |
-0.091429 |
0.025162 |
0.8415 |
|
55 |
76 |
Tajikistan |
0.039583 |
0.041579 |
0.105564 |
-0.002994 |
0.01618 |
0.62275 |
|
56 |
22 |
Bosnia and Herzegovina |
-0.013867 |
0.042154 |
0.039216 |
-0.057143 |
-0.030102 |
0.7435 |
|
57 |
47 |
Hungary |
-0.023612 |
0.042487 |
0.013021 |
-0.099147 |
0.015292 |
0.832 |
|
58 |
80 |
Japan |
-0.042856 |
0.042856 |
-0.01 |
-0.069397 |
-0.049169 |
0.8995 |
|
59 |
19 |
Bulgaria |
-0.012899 |
0.043623 |
0.025411 |
-0.084783 |
0.020675 |
0.7885 |
|
60 |
81 |
Costa Rica |
-0.043729 |
0.043729 |
-0.049209 |
-0.042254 |
-0.039723 |
0.77025 |
|
61 |
67 |
Kazakhstan |
-0.035984 |
0.045128 |
0.000416 |
-0.121667 |
0.0133 |
0.7895 |
|
62 |
56 |
Croatia |
-0.028319 |
0.045189 |
-0.044546 |
-0.065714 |
0.025305 |
0.82175 |
|
63 |
85 |
Honduras |
-0.046228 |
0.046228 |
-0.085932 |
-0.046442 |
-0.006311 |
0.62 |
|
64 |
78 |
Korea (Republic of) |
-0.041126 |
0.046639 |
0.008269 |
-0.072432 |
-0.059215 |
0.89675 |
|
65 |
82 |
Latvia |
-0.045333 |
0.047585 |
-0.01947 |
-0.119906 |
0.003378 |
0.8235 |
|
66 |
86 |
Estonia |
-0.046312 |
0.047914 |
-0.017395 |
-0.123944 |
0.002404 |
0.861 |
|
67 |
54 |
El Salvador |
-0.026453 |
0.04903 |
0.033866 |
-0.089322 |
-0.023903 |
0.67725 |
|
68 |
89 |
Panama |
-0.049067 |
0.049067 |
-0.073699 |
-0.057813 |
-0.01569 |
0.7815 |
|
69 |
28 |
Bolivia (Plurinational State of) |
0.016475 |
0.049558 |
0.06422 |
-0.049625 |
0.034829 |
0.668 |
|
70 |
14 |
Zimbabwe |
-0.010275 |
0.049958 |
0.060266 |
-0.07089 |
-0.018719 |
0.50225 |
|
71 |
91 |
Poland |
-0.050899 |
0.050899 |
-0.017345 |
-0.099074 |
-0.036278 |
0.84875 |
|
72 |
3 |
Saudi Arabia |
-0.001554 |
0.051442 |
0.074832 |
-0.030871 |
-0.048622 |
0.84075 |
|
73 |
53 |
Viet Nam |
-0.025981 |
0.052506 |
0.039788 |
-0.090247 |
-0.027483 |
0.676 |
|
74 |
75 |
Botswana |
-0.039531 |
0.054675 |
-0.131153 |
-0.010156 |
0.022717 |
0.6965 |
|
75 |
77 |
Lithuania |
-0.039616 |
0.054838 |
0.010665 |
-0.141681 |
0.012169 |
0.84225 |
|
76 |
69 |
Rwanda |
0.036707 |
0.055362 |
0.096196 |
-0.029344 |
0.040548 |
0.491 |
|
77 |
97 |
Colombia |
-0.055583 |
0.055583 |
-0.07398 |
-0.063602 |
-0.029166 |
0.72075 |
|
78 |
48 |
Mauritius |
-0.023808 |
0.055652 |
0.052155 |
-0.077557 |
-0.037246 |
0.7735 |
|
79 |
55 |
Burundi |
0.027321 |
0.056461 |
0.124697 |
-0.037874 |
-0.006813 |
0.403 |
|
80 |
15 |
Kenya |
0.011129 |
0.056487 |
0.101425 |
-0.030556 |
-0.03748 |
0.548 |
|
81 |
100 |
Sri Lanka |
-0.057614 |
0.056499 |
-0.05267 |
-0.068733 |
-0.048093 |
0.76175 |
|
82 |
98 |
South Africa |
-0.055597 |
0.056538 |
-0.107737 |
-0.060465 |
0.001411 |
0.66075 |
|
83 |
7 |
Turkey |
-0.006155 |
0.056725 |
0.075854 |
-0.053731 |
-0.040588 |
0.761 |
|
84 |
99 |
Portugal |
-0.056756 |
0.056756 |
-0.082452 |
-0.060274 |
-0.027541 |
0.837 |
|
85 |
101 |
Jamaica |
-0.058214 |
0.059079 |
-0.099794 |
-0.066667 |
-0.010776 |
0.72825 |
|
86 |
104 |
Argentina |
-0.059598 |
0.059598 |
-0.083079 |
-0.072464 |
-0.023252 |
0.82525 |
|
87 |
105 |
Thailand |
-0.061156 |
0.061156 |
-0.070612 |
-0.086412 |
-0.026445 |
0.737 |
|
88 |
83 |
Belarus |
-0.045669 |
0.062607 |
-0.010564 |
-0.151961 |
0.025296 |
0.7965 |
|
89 |
74 |
Russia |
-0.039489 |
0.064163 |
0.017385 |
-0.155478 |
0.019626 |
0.80275 |
|
90 |
88 |
Trinidad and Tobago |
-0.048587 |
0.064625 |
-0.050298 |
-0.037996 |
-0.105582 |
0.7775 |
|
91 |
106 |
Armenia |
-0.065226 |
0.065226 |
-0.10006 |
-0.086003 |
-0.009615 |
0.73975 |
|
92 |
107 |
Dominican Rep. |
-0.066269 |
0.066269 |
-0.12793 |
-0.03097 |
-0.039908 |
0.71525 |
|
93 |
103 |
Qatar |
-0.059365 |
0.066284 |
-0.104212 |
0.023529 |
-0.07111 |
0.852 |
|
94 |
108 |
Venezuela (Bolivarian Republic of) |
-0.066533 |
0.066533 |
-0.095418 |
-0.075703 |
-0.028479 |
0.76925 |
|
95 |
109 |
Nicaragua |
-0.06813 |
0.06813 |
-0.136311 |
-0.057576 |
-0.010502 |
0.63825 |
|
96 |
71 |
Syria |
0.036803 |
0.069869 |
0.129755 |
-0.061171 |
0.018682 |
0.57475 |
|
97 |
51 |
Ukraine |
-0.024807 |
0.070172 |
-0.014577 |
-0.127892 |
0.068048 |
0.74525 |
|
98 |
92 |
Tanzania (United Republic of) |
0.05197 |
0.071546 |
0.15517 |
-0.029365 |
0.030104 |
0.51875 |
|
99 |
96 |
Ghana |
0.054422 |
0.071921 |
0.153202 |
-0.026249 |
0.036312 |
0.575 |
|
100 |
111 |
Uruguay |
-0.073659 |
0.073659 |
-0.100057 |
-0.077143 |
-0.043778 |
0.792 |
|
101 |
17 |
Guatemala |
0.012198 |
0.076875 |
0.13361 |
-0.07196 |
-0.025054 |
0.6255 |
|
102 |
112 |
Mongolia |
-0.076926 |
0.076926 |
-0.066316 |
-0.111134 |
-0.053327 |
0.72925 |
|
103 |
93 |
Tunisia |
0.053817 |
0.077012 |
0.182828 |
-0.039362 |
0.008847 |
0.7225 |
|
104 |
79 |
Algeria |
0.042841 |
0.083375 |
0.188342 |
-0.015873 |
-0.04591 |
0.7415 |
|
105 |
116 |
Suriname |
-0.084422 |
0.085518 |
-0.170814 |
-0.081618 |
0.004121 |
0.72225 |
|
106 |
84 |
Uganda |
0.045679 |
0.086074 |
0.19763 |
-0.05435 |
-0.006244 |
0.4855 |
|
107 |
110 |
Malawi |
0.071353 |
0.090285 |
0.225478 |
-0.028397 |
0.016979 |
0.4685 |
|
108 |
90 |
Cambodia |
0.049407 |
0.093933 |
0.184432 |
-0.066789 |
0.030578 |
0.555 |
|
109 |
57 |
Iran (Islamic Republic of) |
-0.028983 |
0.096784 |
0.101701 |
-0.031365 |
-0.157286 |
0.77175 |
|
110 |
94 |
Cameroon |
0.053832 |
0.098092 |
0.226852 |
-0.010204 |
-0.05722 |
0.51 |
|
111 |
64 |
Egypt |
0.033329 |
0.098409 |
0.197607 |
-0.041577 |
-0.056043 |
0.6865 |
|
112 |
121 |
Philippines |
-0.09874 |
0.09874 |
-0.159511 |
-0.088393 |
-0.048317 |
0.677 |
|
113 |
115 |
Zambia |
0.082919 |
0.104692 |
0.250348 |
-0.032304 |
0.031423 |
0.5725 |
|
114 |
117 |
India |
0.084774 |
0.10761 |
0.285827 |
-0.034253 |
0.002749 |
0.61125 |
|
115 |
120 |
Nigeria |
0.090757 |
0.110142 |
0.302404 |
-0.004255 |
-0.023766 |
0.52175 |
|
116 |
113 |
Angola |
0.077184 |
0.112975 |
0.27046 |
-0.059677 |
-0.008789 |
0.5285 |
|
117 |
122 |
Bhutan |
0.109755 |
0.114332 |
0.317982 |
-0.021499 |
0.003516 |
0.599 |
|
118 |
119 |
Mauritania |
0.090505 |
0.120525 |
0.293603 |
-0.04503 |
0.022941 |
0.509 |
|
119 |
102 |
Namibia |
-0.058658 |
0.122555 |
-0.217544 |
-0.047773 |
0.102348 |
0.6335 |
|
120 |
95 |
Morocco |
0.053859 |
0.123884 |
0.266614 |
-0.02888 |
-0.076156 |
0.6415 |
|
121 |
114 |
Nepal |
0.081468 |
0.131528 |
0.319494 |
-0.02 |
-0.055089 |
0.55225 |
|
122 |
123 |
Senegal |
0.110049 |
0.132269 |
0.363477 |
-0.02967 |
-0.00366 |
0.4855 |
|
123 |
127 |
Burkina Faso |
0.12362 |
0.137665 |
0.391693 |
-0.021067 |
0.000236 |
0.3975 |
|
124 |
124 |
Pakistan |
0.116173 |
0.142799 |
0.388457 |
-0.003383 |
-0.036556 |
0.5445 |
|
125 |
125 |
Ethiopia |
0.116469 |
0.145724 |
0.378816 |
-0.043882 |
0.014474 |
0.43775 |
|
126 |
128 |
Mozambique |
0.128963 |
0.150699 |
0.414633 |
-0.012858 |
0.024605 |
0.4115 |
|
127 |
129 |
Lesotho |
-0.152642 |
0.155204 |
-0.367379 |
-0.065632 |
-0.032602 |
0.49175 |
|
128 |
126 |
Cote d’Ivoire |
0.119953 |
0.156626 |
0.414943 |
-0.038043 |
-0.016892 |
0.46275 |
|
129 |
132 |
Mali |
0.160473 |
0.160473 |
0.455807 |
0.001477 |
0.024135 |
0.43275 |
|
130 |
118 |
Yemen |
0.090227 |
0.166528 |
0.385133 |
-0.025455 |
-0.088998 |
0.49475 |
|
131 |
130 |
Guinea |
0.153464 |
0.171233 |
0.488383 |
-0.02 |
-0.005316 |
0.4115 |
|
132 |
131 |
Liberia |
0.157644 |
0.174103 |
0.49762 |
-0.018868 |
-0.00582 |
0.4245 |
|
133 |
133 |
Benin |
0.187256 |
0.189611 |
0.499874 |
-0.009804 |
0.059154 |
0.47675 |
|
134 |
134 |
Chad |
0.231138 |
0.240094 |
0.660145 |
-0.013434 |
0.046703 |
0.39175 |
Interesting facts
-
In the most developed countries, men fall slightly behind women. You can easily see this if you sort the table above by the Human Development Index (HDI).
-
In the least developed nations, which are mostly in Africa, girls fall behind, in particular in education.
-
Countries with a poor reputation for gender equality can have a surprisingly good BIGI score. Importantly, such an overall balance often (but certainly not always) means that while women fall considerably behind in one domain, men fall considerably behind in another domain — thus, two sub-scores are canceled out. Hence, it is important to also look at the AADP score
-
The countries where the gap in healthy life expectancy is particularly large in favor of women are all countries with a high level of alcohol consumption. At the other end of the scale are 5 countries where alcohol is taboo (sort the table by healthy life span to see this).
-
Men consume more alcohol than women in all nations, and alcohol consumption does often not decline with increasing age (see Wilsnack and colleagues, 2009).
Policy implications
The overall quality of life
can be improved by policies that target specific gender
disparities. It is important to realize that gender equality is not a
zero-sum game. Instead,
improving the position of one gender will likely positively influence
the other gender as well.
For example, improving educational opportunities for girls in Africa will benefit the families they will later form. Improving men’s health benefits the families in which they live. Ultimately, we all win by increasing gender equality.
Men’s disadvantages are particularly related to health factors, especially in the developed world. Investment in prevention programs and a more coherent approach to male health is key to improving this situation. For example, there are various national and international strategies for women’s health, but few for men’s health. Creating a national and international strategy for men’s health is a first step to reduce gender inequality in this area.
The first country to introduce a national health plan for men was Ireland (in 2009). Read more. |
"There remains a strong rationale for maintaining a specific focus on men’s health. This is grounded in: continued sex differences in life expectancy and mortality; health inequalities between different sub- populations of men; a substantial body of evidence supporting a gender-specific approach; and the imperative to build on the momentum and key milestones achieved in men’s health over the past ten years. The New Public Sector Equality and Human Rights Duty provides a mandate for maintaining a policy focus on men affected by marginalisation (e.g. Traveller men, ethnic minority men and gay men)." From the National Men’s Health Action Plan Healty Ireland
"More males die at every stage of life. Males have more accidents, are more likely to take their own lives and are more prone to lifestyle-related chronic health conditions than women and girls at the same age." From the announcement of Austrlia’s National Male Health Strategy to support the health of men and boy on 13th of June 2018.
Part of improving men’s health is to better inform the public about the risks of alcohol and to prevent the starting of alcohol consumption in young people. Given that alcohol consumption patterns differ so much between men and women in many countries, men and women would possibly benefit from different types of prevention strategies. A national health strategy for men should take that into account.
Women’s disadvantages are particularly strong in Africa. Investment in education is the key to improving this situation (see also this World Economic Forum, this UNESCO fact sheet and this UNESCO document). Not only do developing countries need to more strongly focus on education, international aid should also focus on it. The problem is that this has been on the agenda for a long time already (e.g., see this document from 1993), but not enough has been accomplished. New programs, such as the Global Partnership for Girls' and Women’s Education "Better Life, Better Future" might change this. Obviously, improving education benefits many other aspects of life as well, including health.
"Girls face a distinctive set of barriers to learning, especially when they reach post-primary levels of education. At that age, girls drop out of school for many reasons: early marriage and pregnancy, violence in and around schools, poverty, household chores, lack of gender-responsive learning contents and environments, among others. Targeted measures are needed to get girls to school, and keep them in school, until they complete the full course of education." From the UNESCO Better Life, Better Future programme.
Further, maternal death during life births also appears to play a role in why poorly developed nations score lower in terms of gender equality, indicating another area for specific intervention.
"Despite progress in some countries, many women and babies still die during childbirth in Africa" From the UN AfricaRenewal program website.
At the same time, we should consider that high levels of economic development are associated with negative side effects on health (e.g., obesity) that have not yet translated in gender-specific health initiatives (e.g., to reduce unhealthy food intake, alcohol and drug consumption). Such initiatives might work better than generic initiatives, given that men and women respond differently to social and cultural factors (e.g., in the case of alcohol, Wilsnack and colleagues, 2009).
One of the risks of general low levels of human development is that gender equality will not be a national priority. Some of the case studies below may illustrate this. And yet, reducing gender equality might boost human development — for example, educating girls in the poorest African nations will help them to deal with the challenges of daily life, including managing fertility and looking after the health of their children. Equally, better support and education of boys and young men in countries such as Brazil and South Africa might well reduce the crime rates and gang violence.
Finally, it is generally the case that countries with a strong social safety net can help people to better access health care or education. It is not, however, the case that men and women would benefit equally from such spending. For instance, the North-Western European countries have a good social safety net, but is still a gender gap in healthy lifespan. The latter indicates the opportunity for extending preventative health services for men.
Download data
You can download the table from the following link:
Case studies
Below, the gender inequality situation is described in more detail for a number of specific countries (albeit still very short). The specific countries were chosen because of the personal connection to the authors of the scale (UK, US, The Netherlands, Germany), the special position in the BIGI ranking, their position in other gender equality rank lists (e.g., Norway, Sweden), or other special features (e.g., large countries).
The ranking after the country names below indicates the Absolute Average Deviation from gender Parity (AADP) score; this shows how much a country deviates from parity (irrespective of which gender is better off). |
BIGI shows whether, on the whole, men or women are better off (as indicated by the male/female icon). Even when there is overall parity, it might simply mean that men and women face equally high levels of difficulties in different domains. The AADP provides an indication of how big the actual difficulties are (irrespective of gender). |
When health life span in years is provided, it is rounded to a whole number. |
Bahrain (#1)
About: Bahrain scores best in the BIGI. Bahrain is an island in the Persian Gulf with fewer than a million citizens, an unusually large number of foreign workers, and it is therefore not truly comparable to the other economically and geographically diverse nations listed.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
1 |
12 |
Bahrain |
-0.007938 |
0.007938 |
-0.01264 |
0 |
-0.011173 |
0.8205 |
Gender inequality: Bahrain’s men and women have an equal life expectancy. Possibly, the taboo on alcohol in Islamic countries protects men’s health. Men fall slightly behind in basic education and life satisfaction.
How to improve: There is very little Bahrain can do in regard to gender inequality. Strengthening policies to ensure all children attend school will likely help to make gains in basic education.
Great Britain (#2)
About: Great Britain (aka UK) is a very highly developed nation with a well-developed social safety net. For example, it has a national health service freely accessible for all residents.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
2 |
24 |
Great Britain |
-0.014545 |
0.015671 |
-0.012144 |
-0.033181 |
0.001689 |
0.905 |
Gender inequality: Great Britain has a relatively low level of gender inequality. Gender differences in life satisfaction are negligible. Men fall somewhat behind in years of secondary education, while they fall more than 3.3% behind in healthy life expectancy (70 years for men and 72 years for women in the 2012-2016 period).
How to improve: Most potential for improvement lies in the area of healthy life expectancy. Currently, Great Britain has a national health strategy for women, but not for men. Creating a national health strategy for men has the potential to make a real difference. The knowledge and skills needed to run a gender-specific health strategy are available in Great Britain. Further, a greater focus on the education gap is needed. The BIGI only looks at years of education, but the reality is that boys do not achieve as well as girls in the time they attend school (this starts already in pre-school).
The Netherlands (#3)
About: The Netherlands is a densely populated Western European nation with relatively high taxes (as is the case in many North-Western European nations). The Netherlands has a strong social safety net.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
3 |
27 |
Netherlands |
-0.01585 |
0.01585 |
-0.011092 |
-0.027477 |
-0.008982 |
0.923 |
Gender inequality: The Netherlands rank highly, although women are overall somewhat better off, which is mostly due to the gap in healthy life expectancy. Differences in overall life satisfaction and opportunitiies in basic education are minimal.
How to improve: Given that the largest gap is in healthy life expectation, this is where the most gains in gender equality can be made; this is the case in the other North-Western European nations too. While these countries provide good access to health care, there is typically no systematic strategy for engaging men in preventative health care (but see Ireland).
Norway (#7)
About: Norway is a small Scandinavian country in terms of population (just over 5 million), but has a relatively large land size. After Iceland, it is the least densely populated Western-European nation. It has the world-highest level of human development score and is ranked the most gender-equal country in the World Economic Forum’s Global Gender Gap Report. It has a strong social safety net.
Short video about why Norway is so wealthy (note, this is just one perspective) |
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
7 |
39 |
Norway |
-0.019498 |
0.01865 |
-0.004167 |
-0.033033 |
-0.01875 |
0.946 |
Gender inequality: Norway scores well, although it is not the highest ranking country. Women do slightly better in each of the BIGI dimensions, mostly so in regard to health. This is similar to the other very highly developed Western nations listed here.
How to improve: As is the case for other very highly developed nations, focusing on men’s health would make the biggest difference.
Israel (#13)
About: Of the countries where men have it, on average, better than women (according to the BIGI score), Israel is the highest ranking country. Israel has a unique history of high levels of immigration from around the world, and has a unique history in regard to gender equality as well (e.g., in the Kibbutz system and military service). At the same time, it is a country that sees large socioeconomic differences along ethnic lines.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
13 |
2 |
Israel |
0.000626 |
0.022297 |
0.021106 |
-0.032506 |
0.013278 |
0.89575 |
Gender inequality: On the whole, Israel does very well (BIGI rank #2), but there are gaps in the individual domains (hence AADP rank #13). Men’s healthy life expectancy is shorter (71 years) than that of women (74 years), while women are disadvantaged in educational opportunities (in secondary education) and life satisfaction. As for countries that have good overall gender parity (i.e., BIGI), the short healthy life expectancy is traded off against education and life satisfaction.
Israel is the highest ranking country in which men have it better than women, although this difference is negligibly small. In fact, Israel is after Italy the country with most balance gender equality (BIGI), although there are some larger differences in the individual domains (hence the lower AADP score of 13).
How to improve: The largest gap is in regard to men’s healthy life expectancy (in favor of women) and the second largest gap in regard to girls' educational opportunities in secondary education. Focusing on men’s health while encouraging families to ensure that their daughters benefit from secondary education will make most gains.
Sweden (#15)
About: Norway’s eastern neighbor has a large geographical area with a relatively small population (10 million), most of which live in the south. It is listed here as a case study because the Swedes are proud of their gender equality. Similar to other North-Western European nations, it has a strong social safety net.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
15 |
26 |
Sweden |
-0.015749 |
0.022527 |
0.010167 |
-0.037918 |
-0.019497 |
0.908 |
Gender inequality: In BIGI, Sweden is not one of the top nations in regard to gender equality, although their score is still good. The overlooked problem in Sweden is that the gender gap in healthy life expectancy is more than 3%. This is similar to that in Great Britain or The Netherlands.
How to improve: As for many other highly developed Western nations, men’s health needs more attention. Sweden spends considerably more on women’s health than men’s health, even after taking into account reproductive health. Information campaigns to better engage men in preventative health care might help to address this issue.
Australia (#19)
About: Australia’s culture is still strongly influenced by its British heritage. Australia’s social safety net is comparable to that of Western European nations. It has a diverse population (of around 25 million).
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
19 |
49 |
Australia |
-0.024204 |
0.024204 |
-0.013848 |
-0.040324 |
-0.018441 |
0.93625 |
Gender inequality: Australia is a good example of a very highly developed country with women doing somewhat better than men, in particular in regard to healthy life expectancy (71 years for men and 74 years for women in the 2012-2016 period).
How to improve: The biggest gain can come from an improved healthy life expectancy of men. A national health strategy for men, including a focus on prevention, might help. Australia’s government has announced such a plan in 2018, and is thus a vanguard in this regard.
Germany (#26)
About: Germany is the most populous country of the European Union (population 82 million), and it is its economic powerhouse. Germany reunited in 1990, after the cold war ended, and dealt with the large cost of helping the underdeveloped former East Germany. Today, Germany is a prosperous country with a strong social safety network.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
26 |
20 |
Germany |
-0.012993 |
0.029448 |
0.024682 |
-0.05147 |
-0.012191 |
0.92225 |
Gender inequality: Germany is certainly not among the top nations in gender equality. Given its high level of development and its reputation of a country that is good at dealing with great challenges, Germany has some real surprises: Germany is the only wealthy European country where girls fall behind in basic education (it is similar to Albania and Bulgaria). Further, the healthy life expectancy gap in favor of women is more than 5% (70 years for men and 74 for women in the 2012-2016 period).
Germany’s reported educational data (as taken from the Global Gender Gap Report) are somewhat odd. Germany reported enrollment in secondary education for the first time in 2016, and it was 47% for girls and 53% for boys. Given that this number is very different from surrounding countries, it is difficult to know why exactly this is, and may have to do with the educational differences in various of its federal states (Bundesländer) as well as the way different educational tracks (including vocational tracks) are counted. Fact is that there are more German women than men at university level, which suggests that girls are better prepared than boys in secondary education for university education. |
How to improve: Germany has done much over the past 20 years to monitor its education gaps and in some ways does more than other countries (see note below). And yet, it urgently needs to address the question why far fewer girls than boys seem to participate in secondary education (although it is currently unclear why this might be). Further, similar to other Western-European nations, it needs to rethink its approach to preventative health care for men, whose healthy life expectancy is almost 4 years shorter than that of women.
Many European nations have a Girls' day for Science, Technology, Engineering, and Mathematics. Germany is the only nation that also has a Boys' day to inform boys about non-stereotypical career opportunities. In this regard, Germany takes informing all children about non-stereotypical careers (not just girls, as is often the case) seriously. |
United States (#34)
About: The US is the largest and the most powerful Western nation. Its economy is the world’s most influential. Compared to other Western nations, taxes are low and, as a consequence, the social safety net is comparatively weak. That possibly also explains why the overall healthy life expectancy (just under 70 years in the 2012-2016 period) was lower than that of any nation in Western Europe.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
34 |
61 |
United States of America |
-0.032937 |
0.032937 |
-0.020057 |
-0.047574 |
-0.03118 |
0.91725 |
Gender inequality: Given its wealth and very high level of human development, its BIGI score is surprisingly low. Men fall behind in all three BIGI indicators. In regard to healthy life expectancy, the gap is nearly 5% (68 years for men and 71 years for women in the 2012-2016 period).
How to improve: Initiatives focusing on men’s access to (or use of) health care, as well as those focusing on boys' education and health might help to address the current inequalities.
China (#36)
About: China is the world’s most populous nation. It has seen and is still seeing rapid changes in economic and human development. In the last decade, it has moved from medium to high human development.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
36 |
8 |
China |
0.00626 |
0.03352 |
0.059671 |
-0.035038 |
-0.005851 |
0.727 |
Gender inequality: China does well in terms of overall gender parity (BIGI rank #8), and scores medium in terms of AADP (#38). Nevertheless, on average, girls fall behind considerably in basic education. This is likely due to the situation in rural areas — it is well known that China has a considerable rural/urban gap, and this particularly affects girls over 14 years old (e.g., Song et al., 2006 and ChinaDaily). At the same time, men’s healthy life expectancy (66 years) is shorter than that of women (69 years).
How to improve: Although Chinese boys and girls in urban areas achieve very similarly in the tri-annual PISA tests, there is a great need to improve access to basic secondary education in rural areas, with a focus on girls (there are initiatives, although we do not have much details). A secondary issue is in regard to men’s healthy life span, which needs a more targetted approach (as is the case in much of the rest of the industrialized world).
Brazil (#45)
About: Brazil is the largest nation in South America and the 5th largest in the world. It has a high level of human development and has seen fast economic growth in the first decade of this century. It is one of the BRIC countries. Brazil has a high degree of income inequality; despite wealth among some sections of the population, large sections of the population live in poverty.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
45 |
70 |
Brazil |
-0.036775 |
0.036775 |
-0.03711 |
-0.06858 |
-0.004635 |
0.74725 |
Gender inequality: Men fall behind in all 3 BIGI components, mostly in healthy life expectancy (62 years for men and 67 years for women in the 2012-2016 period), and second most in basic education.
How to improve: The gender gap in healthy life expectancy is large and needs to be improved. The Brazilian government has set positive steps with the creation of a national health plan for men (2008), and if developed further, this may well help to close this gap in the longer term. Further, improvements in safety (including interventions in regard to criminal gangs), which affects more men than women, will not only help to reduce the healthy life expectancy gap, but likely also reduces the gap in education.
Japan (#58)
About: Japan is a very highly developed, large, and influential Asian nation. Japan faced enormous economic growth in the second half of the 20th century, which has now slowed down and Japan faces new challenges with an ageing population. Nonetheless, Japan is a country with a strong social safety network and very low levels of crime. Japan has the world highest healthy life expectancy. At the same time, Japan has unique sociocultural problems, such as overworking.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
58 |
80 |
Japan |
-0.042856 |
0.042856 |
-0.01 |
-0.069397 |
-0.049169 |
0.8995 |
Gender inequality: Men fall considerably behind women in healthy life expectancy (72 years for men and 78 years for women in the period 2012-2016) and in life satisfaction.
How to improve: It is possible that Japan’s work culture contributes to both to men’s considerably shorter healthy life expectancy and lower life satisfaction. Japanese policy makers and business leaders need to create a national plan for a better work-life balance to reduce the large cost of overworking, which seems to be a heavier burden for men than women.
Estonia (#66)
About: Estonia is one of the small Baltic states (population: 1.3 million) that became independent from the Soviet Union in 1991. Although all previous Eastern-Block nations still have much to do to catch up with their Western-European neighbors, Estonia is in many ways a success story and has a relatively good social safety net.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
66 |
86 |
Estonia |
-0.046312 |
0.047914 |
-0.017395 |
-0.123944 |
0.002404 |
0.861 |
Gender inequality: Estonia scores poorly, because of the huge gender gap in healthy life expectancy (62 years for men and 71 years for women in the 2012-2016 period). Alcohol seems to play a big role in this.
How to improve: Estonia can close the gender gap by focusing on men’s health, especially by tackling alcohol consumption and by promoting a healthy life style. Estonia is taking active steps to reduce alcohol consumption, which may well pay off if successful.
Saudi Arabia (#72)
About: Saudi Arabia is a very highly developed nation that acquires most of its wealth from oil revenue. Known for its strict and traditional approach to gender roles, men and women shop and work typically in completely separate spaces.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
72 |
3 |
Saudi Arabia |
-0.001554 |
0.051442 |
0.074832 |
-0.030871 |
-0.048622 |
0.84075 |
Gender inequality: It may surprise many, but Saudi Arabia has a high level of overall gender parity (BIGI). While women’s basic education falls behind that of men considerably, men score lower on healthy life expectancy and life satisfaction. In other words, the issues men and women suffer from cancel each other out, resulting in parity (good BIGI). While men and women both face difficulties in life (as reflected in a low AADP rank), on the whole their issues are comparable in magnitude (i.e., high BIGI rank).
How to improve: The country has to do much in regard to reducing gender inequality in each of the specific domains (education, health, life satisfaction). Policies (and their implementation) to ensure that girls get basic education are urgently needed. Further, men’s physical and mental well-being clearly requires attention. More research is needed to better understand what can be done, especially because there is little accessible research on Saudi’s men’s health and well-being.
South Africa (#82)
About: South Africa is a medium developed nation. Despite the transition from apartheid, the country has enormous socioeconomic inequality and more than half the population lives below the poverty line.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
82 |
98 |
South Africa |
-0.055597 |
0.056538 |
-0.107737 |
-0.060465 |
0.001411 |
0.66075 |
Gender inequality: Men fall behind considerably in education. In this regard, South Africa deviates much from many other sub-Saharan nations (where often girls fall behind). Further, men have a shorter healthy life expectancy (48 years for men and 51 years for women in the 2012-2016 period).
How to improve: Both boys' and men’s education and health need urgent attention. As for Brazil, a reduction in violence will support this in addition to preventative health care and investment in educational resources.
India (#114)
About: India has a population nearly as large as that of China. Like China, India has seen and is still seeing rapid changes in economic and human development (although India is still medium developed). Major equality issues in India are child labor and religious social stratification of society.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
114 |
117 |
India |
0.084774 |
0.10761 |
0.285827 |
-0.034253 |
0.002749 |
0.61125 |
Gender inequality: India scores poorly on the BIGI. The major problem is that girls fall behind enormously in regard to education. There is no other country with a comparable level of human development in which girls fall behind so much in terms of illiteracy. To see this in the table, sort countries by "Education" and note that all the countries with a larger gender gap in education also have a lower Human Development Index (HDI) score.
How to improve: The high level of illiteracy among girls (and women) is caused by various underlying factors (for example, read this). A larger investment in basic education (i.e., increase percentage of GDP spent on basic education) would likely be a good first step. But given the large gender gap and generally high level of illiteracy (among both genders), enormous changes in educational policy and expenditure will be necessary to reduce India’s gender inequality.
Chad (#134)
About: Chad scores lowest in the BIGI. Given Chad’s large size (4th largest land size in Africa), it has a relatively small population (currently around 16 million). That said, the population is ethinically diverse, young, and fast growing. Many people live a traditional nomadic life style. It belongs to the world least developed nations and suffers from continued conflicts in the Lake Chad basin.
AADP rank |
BIGI rank |
Country |
Better off? |
BIGI |
AADP |
Education |
Healthy Life Span |
Overall life sastisfaction |
HDI |
134 |
134 |
Chad |
0.231138 |
0.240094 |
0.660145 |
-0.013434 |
0.046703 |
0.39175 |
Gender inequality: Chad has a very large gender gap in education, with only one third of women being literate compared to half of men. The other gaps pale in comparison to this gap, although Chad’s gender gap in life satisfaction (also in favor of men) is one of the largest as well.
How to improve: Similar to many other African nations, women fall behind enormously in literacy and life satisfaction. The traditional nomadic life style and the lack of infrastructure in a very large country with vast expanses of wild nature will make it difficult to change this rapidly. On top of this, parts of Chad continue to see conflict interfering with education. Solving the ongoing conflicts, abolishing school fees, the creation of new schools, investing in teacher training, and ensuring healthy nutrition are all factors that can, in the long run, contribute to higher levels of literacy (for an expert viewpoint on some of these factors, read this).
Click here to watch this short impression of Chad by French film maker Jean-Thomas Renaud (note, this is just one perspective) |
Alternatives to BIGI
The BIGI was inspired by the Global Gender Gap Index (GGGI) and uses some of its data. There are some important differences between the BIGI and the GGGI, most notably:
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By definition, the GGGI excludes the possibility that men can be less well off than women — this is because the GGGI focuses on women’s advancement
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The GGGI uses indicators that are only relevant to very few people, such as the percentage of top-level female politicians.
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The GGGI includes indicators that may be more reflective of choice than of discrimination, such as number of people choosing tertiary education.
Common Questions about BIGI
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Why is income not included in the BIGI? After all, the total income of all women is lower than the total income of men, should that not matter?
This is explained in detail in the PloS One article about BIGI, please read it here.
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There are far fewer women than men in high-level politics (e.g., national parliament, heads of government, etc) and company boards. Why is this not considered in the BIGI?
There are different reasons for not including this variable (see paper). One of the main arguments is that the number of people in high level politics (or on company boards) is extremely small, and thus, irrelevant to the majority of men and women in a society.
Once you start including issues that affect a small group, you are faced with a selection problem. For example, if you include the gender gap in regard to politics, why not also include the gender gap in imprisonment?
After all, the number of prisoners is much larger than the number of politicians (and hence more relevant). Note, that roughly 95% of the prison population is male. A similar factor is the gender gap in occupational injuries/deaths and in regard to the most dangerous jobs, such as being mineworker or working in the construction sector.
To the best of our knowledge, no gender inequality scale takes these latter variables into account, which suggests a selection bias: Issues that are relevant to women ('s power and influence) take precedent over those that are relevant to men.
That makes of course absolutely no sense for a scale that is about gender equality — after all, both genders should be get equal consideration! In our opinion, most gender inequality scales have a biased selection. There are different ways of solving the selection problem. The way BIGI has solved the selection problem is by not including variables that only affect a small portion of the population. -
How come that the BIGI score in Saudi Arabia is not showing a great disadvantage for women, given the restrictions for women that have been widely reported in the media?
This is explained in detail in the PloS One article about BIGI, please read it here.
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Why do women fall so much behind in terms of education in the poorest countries?
This is explained in detail in the PloS One article about BIGI, please read it here.
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Are you saying that given that gender inequality is not as one-sided in favor of men as the Global Gender Gap Report suggests?
Indeed, we show that there are many countries with a relatively small deviation from gender parity. We believe that the Global Gender Gap Report is biased by ignoring societal problems that affect more men than women, which results in an unrealistically negative outlook for women. The reality is that both men and women are affected by societal issues, and that issues men and women face differently can cancel one another out.
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Given that the situation is not as grim as the Global Gender Gap Report suggests, should we stop caring about gender inequality?
No, because gender equality means that the situation for men and women is comparable, not that it is ideal. These are countries in which there are considerable problems in regard to gender inequality, but the problems of men and women cancel each other out (e.g., women falling behind in education while men falling behind in life expectancy and life satisfaction). Ideally, countries score well in all three subdomains. Bahrain comes close, although it is an unusual nation with a very small population, and thus difficult to compare to more diverse larger societies such as Great Britain.
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Why does there seem to be a discrepancy in the case studies when reporting the actual healthy life expectancy and the percentage?
At first sight, it seems there is a discrepancy, for example, we report for Britain that the healthy life expectancy for men is 70 and for women 72. Given that 70/72=0.972, followed by 0.972-1.0, you get -2.8%, and not the reported -3.3%. This happens because the reported -3.3% is the average of five divisions of each of the five years (71/73,71/73,70/72,69/72,69/72), and not the division of the averaged ages. Because of this you get different values.
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Where did you get the data used to calculate BIGI?
Data are taken from two sources for the 2012-2016 period. 1) The Global Gender Gap Reports published by the World Economic Forum. 2) Gallup World Poll data.
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Who created the BIGI?
The scale was developed by Professor Stoet (UK) and Professor Geary (US).
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Can you come and give a talk about this?
Possibly yes, please send an inquiry to this contact address.
BIGI in the news
Check BIGI and Gender Equality Information via Twitter: https://twitter.com/GenderEqualinfo
References — the original paper
Stoet, G. & Geary, D.C. (2019). A simplified approach to measuring
national gender inequality. Plos One.
Note that this paper can be downloaded for free from the PloS One website.