We investigate how positive discrimination in accelerator programs impacts the gender finance gap in venture capital (VC) funding. Drawing on insights from the entrepreneurial finance and gender disparity literature, we develop an agent-based model to simulate interactions among male- and female-led startups across self-selection, accelerator selection, and VC funding stages. By integrating individual entrepreneurial attributes, social influences, and gendered selection biases, our model captures the dynamic interplay of these factors in shaping funding outcomes. Our findings reveal a non-linear relationship between the proportion of female-led startups in accelerator programs and the gender finance gap in VC funding. Specifically, as female representation in accelerators increases, the gender finance gap narrows, yet this reduction is accompanied by a decline in the total number of funded startups. This trade-off highlights a critical tension: while positive discrimination fosters equity in accelerator participation, it may inadvertently reduce the overall funding pool, underscoring the complexity of designing interventions to address gender disparities in entrepreneurship. Our study contributes to a deeper understanding of how accelerator programs influence the gender finance gap and provides first insights for crafting inclusive yet effective financing strategies in entrepreneurial ecosystems.
