Learning to Quit? A Multi-Year, Multi-Site Field Experiment with Innovation-Driven Entrepreneurs

Esther Bailey, Daniel Fehder, Eric Floyd, Yael Hochberg and Daniel J. Lee

No 34755, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We use a randomized experiment with 553 science- and technology-based startups in 12 co-working spaces across the US to evaluate the effects of intensive, short-term entrepreneurial training programs on survival and performance for innovation-driven startups. Treated startups are more likely to shut down their businesses and do so sooner than control startups. Conditional on survival, however, treated startups are more likely to raise external funding for their ventures, raise funding faster, and raise more funding than the control group; they also exhibit higher employment and revenue. Treated founders are less likely to found a new startup after shutdown. Our findings are consistent with practitioner arguments that early entrepreneurship training interventions can help entrepreneurs with less viable ventures “rationally quit” (“fail fast”). We use machine learning techniques (causal random forest) to provide exploratory insights on the most impacted subgroups.

JEL-codes: C93 D22 M13 M53 O32 (search for similar items in EconPapers)
Date: 2026-01
Note: CF PR
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