Abstract
The allocation of venture capital is one of the primary factors determining who takes products to market, which startups succeed or fail, and as such who gets to participate in the shaping of our collective economy. While gender diversity contributes to startup success, most funding is allocated to male-only entrepreneurial teams. In the wake of COVID-19, 2020 is seeing a notable decline in funding to female and mixed-gender teams, giving raise to an urgent need to study and correct the longstanding gender bias in startup funding allocation.
We conduct an in-depth data analysis of over 48,000 companies on Crunchbase, comparing funding allocation based on the gender composition of founding teams. Detailed findings across diverse industries and geographies are presented. Further, we construct machine learning models to predict whether startups will reach an equity round, revealing the surprising finding that the CEO’s gender is the primary determining factor for attaining funding. Policy implications for this pressing issue are discussed.
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Notes
- 1.
Raising a priced round is a major milestone that offers startups the means to succeed.
- 2.
In startups, the role of CEO is most often taken by one of the founders. This is nearly ubiquitous at early stages.
- 3.
The pipeline problem is often perceived as the primary cause of the gender gap in startup funding allocation, suggesting that the gap would be eliminated if women were as interested as men in pursuing entrepreneurship. We devise and apply analysis methods that shed light into these issues in a manner that cannot be reduced to the pipeline problem.
- 4.
- 5.
We utilized the following name-based gender classifier: https://github.com/clintval/gender-predictor. We retrained the model, achieving an accuracy of 97.10%.
- 6.
Further, many venture capital firms built their own custom models which they do not make public in order to maintain a competitive advantage.
- 7.
As mention above, while a gender gap exits at all startup stages, investors are most reluctant to invest in women in the early stages, where female ventures are 65% less likely to receive funding [4].
- 8.
We report feature importance for the interpretable tree-based models, emphasizing that all models obtained comparable accuracy. Importance analysis for other models are left for future work.
- 9.
Gender information has been incorporated into previous ML models for startup success, see, for example [11].
- 10.
There is a prevalent notion that the key to eradicating gender bias in startup investing lies in increasing the number of female investors. This view is oversimplified and potentially misleading. Both men and women are highly prone to bias against women [15]. While increasing gender diversity amongst investors is important for a variety of reasons, tackling gender bias against female founders calls for more comprehensive solutions.
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A Appendix
A Appendix
This appendix includes additional information on the data used in our analysis (Tables 5, 6 and 7).
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Cassion, C., Qian, Y., Bossou, C., Ackerman, M. (2021). Investors Embrace Gender Diversity, Not Female CEOs: The Role of Gender in Startup Fundraising. In: Shaghaghi, N., Lamberti, F., Beams, B., Shariatmadari, R., Amer, A. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 377. Springer, Cham. https://doi.org/10.1007/978-3-030-76426-5_10
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