Gender and beneficial ownership transparency
Annex 1: Research on women’s enterprise
The table below details a selection of the research used to determine the trends in how researchers make use of sex-disaggregated data for analyses on women’s enterprise. It is based on theme, method of collecting sex-disaggregated data, and key findings for further exploration.
Table 1. Review of the use of sex-disaggregated data to understand women’s enterprise
| Themes | Author(s) |
Method of collecting sex-disaggregated data |
Findings |
|---|---|---|---|
|
Self-employment as a financial strategy for women in Australia |
Hutchinson, Redmond, and Walker [87] |
Researchers created their database using contacts in their network, with a total sample of 201 small businesses |
Data disaggregated by sex and age shows that middle and older-aged women are most affected by houselessness in Australia. |
|
Access to finance for women-owned small and medium-sized enterprises (SMEs) in developing countries |
Ahmad and Arif[88] |
A database built by International Financial Corporation and McKinsey using data derived from publicly available datasets, such as national statistics |
Using a global definition of women’s enterprise makes it challenging to capture women-owned SMEs in developing countries. |
|
Social protection and safety nets for women in Central, West, Southeast, South, and East Asia |
Jalal[89] |
Addresses the lack of sex-disaggregated data on social protection and safety nets |
The collection of sex-disaggregated data about certain aspects of women’s lives is vital and in the public’s interest. |
|
Gender inequality in business start-ups, ownership, and growth orientation; business as a fallback option to employment for women |
Thébaud[90] |
Individual-level data from the Global Entrepreneurship Monitor database |
Data disaggregated by sex, time, and process has some limitations, for instance, from a lack of data for variables like women’s parental status, and how these influence women’s motivation to start a business. |
|
The survival rate of women-led businesses compared to male-led businesses |
Kalnins and Williams[91] |
Compares data of one million Texan proprietorships downloaded from the Texas Sales and Use Tax Permit Holder File |
Data are disaggregated by sex, industry, and geographic area, and debunk myths about women-led business. |
| Asset ownership for women in Ghana | Baah-Boateng, Boakye-Yiadom, and Oduro[92] |
Household data collected through the Department of Economics at the University of Ghana |
Data are disaggregated by sex, region, ethnicity, (urban or rural) area, class, age, and marital status, and show the importance of intra-household differences in asset ownership. |
|
Gendered dimensions of anti-competitiveness, corruption, access to finance, labour regulations, and tax administration in strategies to improve Africa’s competitiveness globally and promote private sector development |
Bardasi et al.[93] | Data collected from the World Bank Enterprise Survey |
Data are disaggregated by sex, and show the constraints and opportunities for women’s enterprise. In most cases, the samples of women-owned businesses were too small to conduct an in-depth analysis. |
|
Gaps between instances of new female and male entrepreneurship |
Krylova, Meunier, and Ramalho[94] |
Data collected from the World Bank Group’s Entrepreneurship Database; 44 out of 143 economies provided sex-disaggregated data |
Gender gaps remain high: e.g. less than one-third of LLCs are owned by women, and women are more likely to use sole proprietorships. |
Notes
[87] Jacquie Hutchinson, Janice Redmond, and Elizabeth Anne Walker, “Self-employment: Is it a long-term financial strategy for women?”, Equality, Diversity, and Inclusion: An International Journal 36, no. 4 (15 May 2017): 362-375, https://doi.org/10.1108/EDI-10-2016-0078.
[88] Syed Zamberi Ahmad and Afida Mastura Muhammad Arif, “Strengthening access to finance for women-owned SMEs in developing countries”, Equality, Diversity, and Inclusion: An International Journal 34, no. 7 (21 September 2015): 634-639, https://doi.org/10.1108/EDI-11-2012-0104.
[89] Imrana Jalal, “Tracking progress on gender equality by 2030: The importance of sex-disaggregated data in gender equality and social protection indicators for monitoring sustainable development goals”, Social Protection Indicators in Monitoring the Sustainable Development Goals (SDGs), Asian Development Bank event, Manila, Philippines, 14-15 March 2017, https://events.development.asia/system/files/materials/2017/03/201703-importance-sex-disaggregated-data-tracking-gender-equality.pdf.
[90] Sarah Thébaud, “Business as Plan B: Institutional Foundations of Gender Inequality in Entrepreneurship across 24 Industrialized Countries”, Administrative Science Quarterly 60, no. 4 (5 June 2015): 671–711, https://doi.org/10.1177/0001839215591627.
[91]Arturs Kalnins and Michele Williams, “When do female-owned businesses out-survive male-owned businesses? A disaggregated approach by industry and geography”, Journal of Business Venturing 29, no. 6, (November 2014): 822-835, https://doi.org/10.1016/j.jbusvent.2013.12.001.
[92] William Baah-Boateng, Louis Boakye-Yiadom, and Abena Oduro, Measuring the Gender Asset Gap in Ghana (Accra: Woeli Publishing Services, 2011).
[93] Bardasi, Blackden, and Guzman, Gender, Entrepreneurship, and Competitiveness in Africa.
[94] Yulia Krylova, Frederic Meunier, and Rita Ramalho, “Women’s entrepreneurship: How to Measure the Gap between New Female and Male Entrepreneurs?” (Washington DC: World Bank, 2017), https://openknowledge.worldbank.org/handle/10986/28902.