Each for equal: Bridging the gender gap and the data revolution
In 2018, ahead of International Women’s Day, the International Growth Centre (IGC) convened a high-level discussion exploring how we can address the biggest challenges that stop women all around the world from being able to access secure jobs in safe working environments, free from all forms of discrimination and violence.
In 2019, we discussed the importance of increasing women’s political leadership, the barriers women face in aspiring to become political leaders, and the benefits of more inclusive political systems.
This year, we turned to data and its role in informing policies that empower women and address systemic societal issues, such as the gender pay gap, women’s unpaid labour, digital inequality, and the digital gender divide.
What is gender data?
‘Gender data’ is commonly referred to as data disaggregated by sex, which reflects gender issues, questions and concerns related to all aspects of women’s and men’s lives, including their specific needs, opportunities, and contributions to society.
In, Invisible Women: Exposing Data Bias in a World Designed for Men, Caroline Criado Perez reveals that we live in world that is (more often than not) biased towards men. Although women make up around half of the global consumer market, medical research, technology, government policy, and workplace culture has been shown to target and accommodate the average male.
One of the most striking statistics shared by the author is that women are 47 percent more likely to be seriously injured in a car crash than men. They are also 17 percent more likely to die and the explanation is plain and simple. Since the 1950s, car crash test dummies have been modelled on a 76kg, 1.77m male. That means seatbelts are not designed for the female form, and women have to sit further forward because the pedals are too far away.
The gender data gap doesn’t just affect women’s experiences with most products, such as pain medications, cars, phones, city streets, and public transport (Samuel, 2019), it affects policy. Household surveys, for example, focus on the ‘head of the household’. This is traditionally thought of as the senior male, so female respondents are often overlooked.
Female labour is another area of interest. Statistics fail to reflect the amount of work women perform for no wages at all. Worldwide, women work much longer hours than men when work at home is added. And even though women carry out manual labour tasks, they are less likely to do so in institutionalised environments or within a formal timeframe. As a result the work is rarely recorded, leading to the assumption that women perform less manual work.
Why is the gender data gap important?
“What is the alternative to data? Opinions. And we know that opinions tend to reward the ones that scream the loudest”, remarked Oriana Bandiera at the beginning of her presentation before reflecting briefly on the gender diversity in her own sector. Academic economists are overwhelmingly male.
In Europe, around 20 percent of the senior economists are women. In America, 15 percent of professors are women. At Harvard, the faculty photos of the Economics Department feature 43 senior members of the Department and only three are women (The Economist, 2017).
In a recent IGC blog, Nidhi Parekh asked: Where are all the female economists?. I also wonder where the collective voice of underrepresented women around the world has been lost to and what is needed to scream the loudest and be heard.
Data for gender parity: Dismantling stereotypes
As Oriana Bandiera put it, it shouldn’t just be a women’s problem when the resources and talent of half of the population are undervalued. As a first step, we should distance ourselves from preconceptions and stereotypes and shift our attention to data.
To demonstrate this, Bandiera tested the views of the audience on the male and female levels of confidence. As expected, most of the attendees thought of men as being overconfident and women as underconfident. Although it is true that a number of experiments show men to be more confident than women, women are also likely to be more “overconfident” than “underconfident”.
Tonsuree Basu complemented the argument by referring to the relationship between gender and corruption. Although anti-corruption policies are thought to be gender neutral by many, evidence shows that women and men are affected differently as corruption hinders progress towards gender equality and presents a barrier for women to gain full access to their civic, social, and economic rights (Transparency International, 2016). Hence, more data is needed to understand the complex relationship between gender and corruption and look at policy measures to address the issue.
Women are not only victims of corruption, they are also part of the solution (see Jha et al). An early cross-country study found that a higher share of women in the labour force is associated with lower levels of corruption perception in a country (Swamy et al., 2001). The results indicated that firms with female owners or managers were less likely to offer bribes and also less likely to tolerate corrupt activities. Similarly, researchers reported a negative relationship between the share of women in parliament in a country and corruption (Dollar et al., 2001).
Gender-specific challenges and the impact of gendered policies
Gender data helps us understand how various issues and policies impact women differently. This should be considered not only when informing policy but also when assessing policy impacts. Moreover, Tonusree Basu asserted that policy and comprehensive data on everyone should be inseparable.
At a country level, we see various positive measures to bridge the gender data gap across multiple sectors. For instance, Germany assessed the extent of the gender gap in leadership positions in private and public sectors as part of their policy reform commitment (Bdkdemir, 2015). To inform their employment policies, Argentina collected data on workforce participation. After analysing and opening procurement data, Kenya expanded procurement opportunities for youth, women, and people with disabilities in 2013.
Globally, women-owned suppliers receive less than 1 percent of public contracts, which could change if governments around the world collected and shared gender-disaggregated data on procurement bids, and looked for opportunities to expand the public procurement market to women-owned companies (Open Government Partnerships, 2020).
In Uruguay, the government looked at the areas where gender violence took place in order to address the challenges around gender impact norms. The Canadian government has introduced a new analysis of its proposed budget that focuses on how government spending will impact women, and people of different ages, income, ethnicity, and sexual orientation (Gender Report, 2019).
These and many other positive examples introduced by national governments pave the way towards gender parity, but more consistent efforts at the global level are needed to bridge the data gap and meet the Sustainable Development Goal (SDG) on gender equality by 2030.
Conclusion: Data helps crystalise issues
Reflecting on her experience working with researchers and policymakers, Twivwe Siwale said there is a growing appetite for gender information and a need for improved data. In Zambia, the education of boys is valued above the education of girls, and girls in their early teens drop out of school in Zambia at a rate three times higher than boys.
To address this issue, IGC researchers evaluated a programme aimed at teaching negotiation skills to secondary school girls in Zambia (Ashraf et al., 2013). The study found that equipping girls with negotiation skills improved their educational outcomes over the next three years by allowing daughters to cooperate more effectively with their parents (Little Book of Growth Ideas, 2020).
As Twivwe said, data helps to crystalise issues and solutions and this is why we need more access to data, more qualified statisticians to interpret it, and more inclusive conversations on gender data, policy development and impact.
Editor’s note: You can listen to the full audio recording from the event here.
Ashraf, N., Low, C. and McGinn, K. (2013). The Impact of Teaching Negotiation on Girls’ Education and Health Outcomes, Innovations for Poverty Action – Zambia, Working Paper, the International Growth Centre. Accessible: https://www.theigc.org/wp-content/uploads/2014/09/Ashraf-Et-Al-2013-Working-Paper.pdf
Bdkdemir, I., Ackermann, M., Beil, L., Croger, N. and Mujtaba, B. G. (2015). “Gender Gap in German Management Positions and Recommendations for Equality”, Advances in Social Sciences Research Journal. Accessible: https://journals.scholarpublishing.org/index.php/ASSRJ/article/view/1206/pdf_162
Dollar, D., Fisman, R. and Gatti, R. (2001). “Are women really the “fairer” sex? Corruption and women in government”, Journal of Economic Behavior & Organization, Volume 46, Issue 4, Pages 423-429. Accessible: https://doi.org/10.1016/S0167-2681(01)00169-X
Her Majesty the Queen in Right of Canada (2019). Gender Report: Budget 2019. Accessible: https://www.budget.gc.ca/2019/docs/gba-acs/gbs-acs-en.pdf
Jha, C. and Sarangi, S. (2015). “Do women in power have an impact on corruption?”, the International Growth Centre Blog. Accessible: https://www.theigc.org/blog/do-women-in-power-have-an-impact-on-corruption/
Open Government Partnership (2020). Open Contracting and Procurement. Accessible: https://www.opengovpartnership.org/policy-area/open-contracting-procurement/
Parekh, N. (2019). “IGC Quick Clicks: Where are all the female economists?”, the International Growth Centre Blog. Accessible: https://www.theigc.org/blog/igc-quick-clicks-where-are-all-the-female-economists/
Perez, C. (2020). Invisible Women: Exposing Data Bias in a World Designed for Men, Penguin Books. Accessible: https://www.penguin.co.uk/books/111/1113605/invisible-women/9781784706289.html
Samuel, S. (2019). “Women suffer needless pain because almost everything is designed for men”, Vox. Accessible: https://www.vox.com/future-perfect/2019/4/17/18308466/invisible-women-pain-gender-data-gap-caroline-criado-perez
Sili, L. (2020). “Balance for better: Advancing women’s political leadership”, the International Growth Centre Blog. Accessible: https://www.theigc.org/blog/balance-for-better-advancing-womens-political-leadership/
Swamy, A., Knack, S., Lee, Y. and Azfar, O. (2001). “Gender and corruption”, Journal of Development Economics. Accessible: https://econpapers.repec.org/article/eeedeveco/v_3a64_3ay_3a2001_3ai_3a1_3ap_3a25-55.htm
The Economist (2017). Inefficient equilibrium: Women and economics. Accessible: https://www.economist.com/christmas-specials/2017/12/19/women-and-economics
Transparency International (2016). Gender and Corruption Topic Guide. Accessible: https://www.transparency.org/files/content/corruptionqas/Topic_guide_gender_corruption_Final_2016.pdf