From Connection to Capital: Probability Is Not Amount

For the Indian startups in this study, the funding question has to be split before it can be answered. A broad potential connection may be associated with the chance that a woman-founded firm receives any funding, while the same evidence may say little about how much money the firm raises. The reader’s task here is to separate those margins, then see what direct founder–board and founder–angel relationships add to the picture.

Crossing the funding threshold is one outcome

The broad potential-network models begin with a simple indicator: whether a firm is funded. In the specification that includes a measure for having at least one connection, the connection coefficient is 0.0998. In a linear probability model, that is a conditional association of about 9.98 percentage points. When the number of connections is added, the indicator coefficient becomes 0.0314, while the coefficient on the connection count is 0.000432. The change does not mean that the first estimate was false. It means that the indicator and the count answer overlapping but different questions: whether any link is present and how the number of links varies among firms.

The interaction with woman founder is positive and statistically significant in both specifications: 0.0679 without the count and 0.0567 with it. In the language of the model, the association between the broad connection measure and funding status is larger for women-founded firms than for firms without an identified woman founder. That is an important result, but it is not a causal return to networking. It does not show that adding a contact would raise a particular firm’s probability by the same amount, nor does it tell us which person or interaction produced the association.

The general funding regressions show a related pattern. After the reported controls and fixed effects, the woman-founder coefficient is 0.101 for whether the firm is funded—about 10.1 percentage points in the linear probability specification—and 0.0823 for having an angel investor. The study’s abstract interprets this as women being more likely to receive funding and early investment from angels after overcoming entry and social-capital barriers. The table supports a positive association on these status outcomes in the observed sample.

That finding can sound surprising after the earlier result that women founders have fewer measured founder–angel and founder–board relationships. But there is no logical contradiction. The network relationship model and the funding-status model do not use the same outcome, and the latter may reflect selection into firms that have already cleared other barriers. The funded status may also capture early or smaller investments that are not equivalent to a later institutional round. A positive probability coefficient tells us that more firms crossed a threshold; it does not tell us that the same firms accumulated more capital or faced the same route to get there.

flowchart LR A["Broad potential connection"] --> B["Funding probability"] A --> C["Total or round funding amount"] A --> D["Investor type"] A --> E["Funding timing"] B --> F["Connection by woman founder interaction"] C --> G["Smaller amount-observed sample"] D --> H["Angel or institutional path"] E --> I["Next funding round"] F --> J["Different margins; no single verdict"] G --> J H --> J I --> J

The funding funnel has several exits because capital is not one variable. A firm can receive some funding but not attract an institutional investor. It can attract an angel but take a long time to reach another round.