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

Author

Listed:
  • Esther Bailey
  • Daniel Fehder
  • Eric Floyd
  • Yael Hochberg
  • Daniel J. Lee

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.

Suggested Citation

  • Esther Bailey & Daniel Fehder & Eric Floyd & Yael Hochberg & Daniel J. Lee, 2026. "Learning to Quit? A Multi-Year, Multi-Site Field Experiment with Innovation-Driven Entrepreneurs," NBER Working Papers 34755, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:34755
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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • M53 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Training
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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