Gender and beneficial ownership transparency

Using sex-disaggregated data to understand women’s position in society

The use and collection of high-quality and reliable sex-disaggregated data on beneficial owners of companies may be directly useful for gender equality purposes. Data generated through BO disclosures must be reliable and well structured to maximise its utility for potential users.[25] The need for high-quality, reliable data is echoed in gender equality policies.

For gender equality, the availability of data disaggregated by sex is regarded as an essential measure for achieving gender equality goals. To illustrate, the UN Women 2022-2025 strategic plan explicitly identifies the production, analysis, and use of gender statics and sex-disaggregated data as an area of focus in addressing global structures that exacerbate gender inequality.[26] Furthermore, SDG 5 defines gender equality and women’s and girls’ empowerment through equal participation and gender parity in decision-making processes, including women’s representation in business, finance, and managerial positions.[27]

BOT is a relatively new policy area, and examples of its application and use for gender equality are still limited (for an example, see Box 1). Furthermore, with some key exceptions, very few countries that have implemented BOT explicitly collect sex data in their BO declaration forms, and the research for this report found none that include gender equality among their primary BOT policy aims.

Women’s enterprise

Sex-disaggregated data is more widely used in other areas closely related to company ownership, such as women’s enterprise. Women’s enterprise is a dynamic concept and consists of the many ways women participate in business. This includes women’s sole proprietorship, business ownership, and business management. This, therefore, covers BO held by women where it is held directly, but not where it is held indirectly.

Examining the collection and use of sex-disaggregated data in these areas can provide lessons to help determine the potential value and risks for the collection and use of BO sex data to advance gender equality. A review of the research shows the following trends (see Annex 1):

• Sex-disaggregated data is available in some areas that impact women’s company ownership, for example, on women’s access to finance. However, because structures of inequality impact all aspects of women’s public and private lives, gender-based analyses of more areas are required to understand when, where, and how women become owners, such as access to social protection and safety nets.
• Sex-disaggregated data is often acquired through a combination of methods. For example, some approaches cross-reference databases specifically created for monitoring entrepreneurship, such as the Global Entrepreneurship Monitor or the World Bank Enterprise database. Others create their databases using sex-disaggregated data collected from various datasets available to the public, such as national statistics, business sales, and tax files.
• The number of formalised businesses is too small in some contexts to accurately reflect women’s economic participation or to conduct an in-depth analysis on women’s economic empowerment, for example, because many women work in the informal rather than the formal sector.
• Gender affects different women differently. In addition to disaggregating data by sex, there is a need for further disaggregation to account for other variables, for example, according to topic, industry, and geographic location.

Sex-disaggregated data on ownership and control of limited liability companies (LLCs), business management, and use of sole proprietorships are valuable for gender-responsive policy making because, together, they offer a picture of women’s enterprise. Nevertheless, research to date suggests there are significant limitations on this data. For one, the motivation behind women’s enterprise is influenced by many factors beyond gender or sex, for which data is limited, including women’s need for striking a balance between work and home life, their parental and marital status, and their access to social security and safety nets.

Furthermore, much of women’s business activity globally takes place in the informal sector, so where sex-disaggregated data on women’s formal company ownership is used as a sole measure of advancements in women’s enterprise, the economic role of women may be underrepresented. This is a barrier to meaningful, in-depth analysis on women’s enterprise and to understanding women’s true contributions to the economy. Women are also more likely to operate as a sole proprietorship than by incorporating an LLC, so it is important that both are covered by BO disclosures.

Notes

[25] “Open Ownership Principles”, Open Ownership, updated July 2021, https://www.openownership.org/en/principles/.

[26] “Strategic Plan 2022–2025”, UN Women Executive Board, United Nations Entity for Gender Equality and the Empowerment of Women (UN-Women), 12 July 2021. See point 5. https://www.unwomen.org/en/digital-library/publications/2021/09/un-women-strategic-plan-2022-2025#:~:text=governance%20and%20participation%20in%20public,action%2C%20and%20disaster%20risk%20reduction.

[27] “Goal 5: Achieve gender equality and empower all women and girls”, United Nations, n.d., https://sdgs.un.org/goals/goal5.

[28] “ Broad-Based Black Economic Empowerment”, Department of Trade, Industry and Competition, Republic of South Africa, n.d., http://www.thedtic.gov.za/financial-and-non-financial-support/b-bbee/broad-based-black-economic-empowerment/.

[29] Simone Liedtke, “Fronting still a major issue in delivering on economic transformation, says commission”, Engineering News, 22 October 2020, https://www.engineeringnews.co.za/article/fronting-still-a-major-issue-in-delivering-on-economic-transformation-says-commission-2020-10-22.

Next page: Sources of sex-disaggregated data about beneficial owners