fbpx Judging Foreign Startups - Tarun Khanna | Harvard Kennedy School

Additional Authors:

  • Tarun Khanna


March 12, 2021, Paper: "Accelerators and investors evaluate entrepreneurial ideas in an increasingly global context. Can they pick the most promising startup ideas no matter their provenance? Discerning the potential of early-stage ideas is challenging and may be particularly so when evaluating foreign ideas, for which judges lack contextual expertise. Furthermore, biases may interfere, leading judges to systematically boost or discount foreign startup ideas. We investigate this question using unique data from the global round of a large accelerator in which multiple judges from different regions are randomly assigned to evaluate startups from across the globe. Our analysis of this natural experiment shows that judges are informed about the quality of both foreign and local startups, though they are biased against foreign startup ideas. Judges are less likely to recommend startups headquartered outside their home region by 4 percentage points. Additional information about a startup does not appear to attenuate this bias. Back-of-the-envelope calculations suggest that judges pass over 1 in 10 high-potential foreign startups. Together, our results reveal that judges are able to discern high from low quality startups regardless of their geographic provenance, but they systematically discount foreign ideas relative to local ones."

Non-HKS Harvard Author - Tarun Khanna