Venture Studio Characteristics Associated with New Venture Equity Exits
Startups → Investing → Research
The venture studio literature is growing quickly.
Qualitative evidence is rich. Quantitative evidence is almost nonexistent.
BVSR24
Voluntary survey of active studios. Survivorship bias and self-selection bias acknowledged.
What the dataset captures
Why equity exits?
I needed an outcome variable. Not "success," which means different things to different studios. Something operationalisable.
The BVSR24 dataset contains information about venture studios, the people who run them, and the ventures they build. Where in that stack are the associations with equity exits?
The bivariate picture
Every variable tested against exit status. No controls. What shows up on its own?
Age and portfolio size dominate. Most raw variables show no association.
Two dominant variables. Which one is the control?
Age and portfolio size both associate with exits at p < .001. With 38 events, we can afford one control. Which one?
Age wins on every criterion: better fit, stronger confounder, and it's the upstream variable. Portfolio size is partly a consequence of age, not an alternative explanation.
Age captures everything
Age is the obvious confounder. Before we can see whether anything else is associated with exits, we need to account for it.
Controlling for age
I had 38 exits, 15+ variables, and a methodology question.
Every variable against the age baseline
Twenty-three tests. One crosses the threshold: TotalStages (p = .044). Roughly what you'd expect by chance. But the one that crosses is deployment breadth, and it only appears once age is accounted for.
Breadth, not any single stage
Each individual stage was also tested separately alongside studio age.
The association is with the pattern of deployment across stages, not with deployment at any particular stage.
What else improves the model?
TotalStages entered the model. Following Hosmer & Lemeshow: test every remaining variable against the updated baseline (StudioAge + TotalStages). Does anything else add?
Forward selection stops here. But the pattern raised a question: these variables describe different types of information about studios. Does any type, taken as a group, add to the age baseline?
Four questions about studios
How big is it? How is it focused? How does it deploy talent? What does it build? Four questions. Do any of them, taken as a group, add to the age baseline?
One domain adds to the picture
One domain is associated with exits after controlling for age: how broadly the studio deploys entrepreneurial talent and whether the deployer has done this before.
Three domains that showed nothing
Three entire domains show no association. The pattern concentrates in entrepreneurial talent deployment: breadth and experience.
What this suggests
Associations, not causes. Cross-sectional design. Exploratory analysis.
Limitations
- Cross-sectional: associations, not effects.
- TotalStages not significant bivariately; emerges only after controlling for age.
- Within the entrepreneurial talent deployment cluster, neither variable is individually significant. The domain-level association should be interpreted as a joint association.
- 23 individual screening tests, 1 crossing the conventional threshold. Roughly what you'd expect by chance at α = .05.
- Voluntary survey, active studios only, survivorship and self-selection bias.
- Survey instrument captures a broad construct ("founders or operators").
- Exploratory: data not designed to test specific theoretical frameworks.