This post was written by Carlos Iglesias, Senior Research Manager.
The Internet has the power to drive economic growth and expand social opportunities. It has empowered people and changed the way we communicate with each other, opening up new worlds and new ways of thinking.
However, almost half the world is still offline — and the majority of those offline are women in developing countries, reinforcing gender inequalities. According to our own calculations — based on the Economist Intelligence Unit country-disaggregated data— men remain 21% more likely to be online than women, rising to 52% in the world’s least developed countries (LDCs). Until we manage to close this significant gap, we cannot meet the Sustainable Development Goal target for universal internet access.
To be offline today means to miss out on learning and earning, accessing valuable services, and participating in the democratic public debate. The digital divide between people who have internet access and those who do not could be deepening existing gender inequalities, pushing women further to the margins of society.
What’s the current gender gap in access?
There are different ways to calculate the gender digital divide, depending on the particular lens through which each person sees the world and which group you choose as the reference. We always calculate the gap as the difference between how many men and how many women are online, as a proportion of how many women are online. The lower the percentage of women online, the larger the digital gender gap will be. We use women as the reference group in order to put the focus on the disparity and disadvantages faced by women (1).
More specifically, our approach explains how many more women need to come online in order to reach gender parity using the following formula:
[(% of men using the internet – % of women using the internet) / % of women using the internet]
However, others have decided to take men as the reference group instead of women, leading to different results. In the table below we include the gender access gap figures from three recent reports released by the Economist Intelligence Unit (EUI), the International Telecommunications Union (ITU) and the GSM Alliance (GSMA) — and how they compare with our women-centred approach using the same data:
| Report | Women’s Internet Use | Men’s Internet Use | Use Gap (men’s reference) | Use Gap (alt.)(women’s reference) |
| EIU Inclusive Internet Index | 59% | 65% | 13% | 21% |
| ITU Facts and Figures | 48% | 58% | 17% | 21% |
| GSMA (mobile internet only) Mobile Gender Gap | 54% | 68% | 20% | 25% |
As you can see by looking at the value in the last column (where we recalculate the gap using our women-centred approach), not only are the differences quite significant, but a women-centred approach could also help us in directly understanding how many more women need to come online in order to reach gender parity.
Finally, it is also interesting to have a look at the regional variance of the gender gap in order to have a better idea of where men are more likely to be online than women.
| Region | Women’s Internet Use | Men’s Internet Use | Use Gap countries average (women’s reference) (2) |
| North America | 94% | 95% | 1% |
| Latin America | 60% | 64% | 12% |
| Europe | 77% | 81% | 5% |
| Middle-East and North Africa | 77% | 79% | 9% |
| Sub-Saharan Africa | 28% | 38% | 43% |
| Central Asia | 57% | 64% | 15% |
| East Asia | 83% | 86% | 2% |
| SouthEast Asia-Pacific | 60% | 67% | 11% |
| South Asia | 18% | 37% | 137% |
Your contribution to a women-centered perspective
You can contribute to increasing the focus on the disadvantages faced by women using your data:
- Start by gathering and publishing sex-disaggregated data.
- Always use women as the reference group for women’s issues.
- Document your data decisions and your methodology, including any changes to your approach and your rationale.
- Share the complete underlying raw data, ideally in an open and reusable format. So, if you are not using women as the reference yet, others can do so using your data.
Notes:
(1) This approach takes a binary view of gender (i.e., male and female) and therefore overlooks other gender identities. There are several underlying reasons for the gender gap — including affordability, education and digital skills, income levels, or living in rural areas — which are not covered in this analysis.
(2) We found the average of the gaps of every single country to be more representative of the variance among different countries than the gap of the regional internet use averages by gender.
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