Working Paper: NBER ID: w28882
Authors: Ruiqing Cao; Rembrand M. Koning; Ramana Nanda
Abstract: Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and persistent impact on the venture’s success. Specifically, we show that products with a female-focused target market launching on a typical day, when nine in ten users on this platform are men, experience 45% less growth a year after launch than those for whom the target market is more male-focused. By isolating exogenous variation in the composition of beta testers unrelated to the characteristics of launched products on that day, we find that on days when there are unexpectedly more women beta testers on the platform—reducing the amount of sampling bias for female-focused products—the gender-performance gap shrinks towards zero. Our results highlight how sampling bias can lead to fewer successfully commercialized innovations for consumers who are underrepresented among early users.
Keywords: sampling bias; entrepreneurship; startup innovation; gender dynamics
JEL Codes: L1; M13; O3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| sampling bias (C83) | growth of female-focused startups (M13) |
| gender representation among early users (J16) | growth of female-focused startups (M13) |
| gender representation among early users (J16) | growth gap between female-focused and male-focused products (J16) |
| launch timing and product characteristics (L15) | sampling bias (C83) |