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Econometric models of duration data in entrepreneurship with an application to start-ups' time-to-funding by venture capitalists (VCs)

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  • Paul P. Momtaz

Abstract

Because time is a key determinant of entrepreneurial decision making, time-to-event models are ubiquitous in entrepreneurship. Widespread econometric misconception, however, may cause complicated biases in existing studies. The reason is spurious duration dependency, a complicated form of endogeneity caused by unobserved heterogeneity, which is particularly pronounced in entrepreneurship data. This article discusses the endogeneity problem and methods to ‘debias’ time-to-event models in entrepreneurship. Simulations and empirical evidence indicate that only the frailty approach yields consistently unbiased parameter estimates. An application to start-up firms' time-to-funding shows that other methods lead to dramatic biases. Therefore, this article advocates a paradigm shift in the modeling of time variables in entrepreneurship.

Suggested Citation

  • Paul P. Momtaz, 2021. "Econometric models of duration data in entrepreneurship with an application to start-ups' time-to-funding by venture capitalists (VCs)," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(13-15), pages 2673-2694, November.
  • Handle: RePEc:taf:japsta:v:48:y:2021:i:13-15:p:2673-2694
    DOI: 10.1080/02664763.2021.1896686
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    Cited by:

    1. Barg, Johannes A. & Drobetz, Wolfgang & Momtaz, Paul P., 2021. "Valuing start-up firms: A reverse-engineering approach for fair-value multiples from venture capital transactions," Finance Research Letters, Elsevier, vol. 43(C).
    2. Shahid, Pirzada Syed Rizwan, 2023. "Founder's Human Capital and the Entrepreneurial Process Duration," OSF Preprints yf6mg, Center for Open Science.
    3. Niclas Dombrowski & Wolfgang Drobetz & Lars Hornuf & Paul P. Momtaz, 2023. "The Financial and Non-Financial Performance of Token-Based Crowdfunding: Certification Arbitrage, Investor Choice, and the Optimal Timing of ICOs," CESifo Working Paper Series 10393, CESifo.

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