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Bite me! ABC’s Shark Tank as a path to entrepreneurship


Business pitch competitions provide early-stage finance and mentoring for entrepreneurs. In this paper, we analyze data from the most public, high-stakes pitch competition in the USA: ABC’s Shark Tank. We construct a dataset comprising all entrepreneurs/firms that have aired between August 2009 and May 2016. Our findings: (1) funding on the show seems to relax an internal financial constraint, rather than signal the quality of the venture to potential outside investors; (2) to the extent that the latter is occurring, there is plausible evidence that the signaling effect works in an unexpected direction for women entrepreneurs—it may crowd out attention from potential investors; (3) while it is fairly clear that this pitch competition is associated with longer-run existence of firms, it has no significant impacts on innovation; (4) there are no consistent differential impacts on racial/ethnic minorities. These findings complement the literature on the impact of pitch competitions and (early) access to finance.

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Fig. 1


  1. 1.

    An exception is Hurst and Lusardi (2004) who find entry into entrepreneurship to be unrelated to wealth over most of the wealth distribution.

  2. 2.

    A related strand of literature explores determinants of successful pitches (e.g., Milovac and Sanchez-Burks 2014; Wood Brooks et al. 2014; Poczter and Shapsis 2016).

  3. 3.

    For related literature on minority entrepreneurship more broadly, see for example Fairlie and Robb (2007), Bates and Bradford (2008), Chatterji and Seamans (2012), and the references within.

  4. 4.

    The show is currently airing Season 8 and holding auditions for Season 9.

  5. 5.

    The show’s media impacts on entrepreneurship/innovation is the topic of a different paper by Robinson and Viceisza (2017), along the lines of the literature reviewed by DellaVigna and La Ferrara (2015).

  6. 6.

    At the entrepreneur-contestant/firm level, this number is calculated by dividing the final amount offered/agreed to by the percent stake in the business. If no offer was made, this number takes the value zero. There are a few instances where the sharks ask for something different from a percent stake, e.g., $1 per unit sold. In such instances, we guesstimate the typical/average price for the unit of product under consideration and calculate the percent stake as the per unit amount requested divided by the per unit average price. Additional details are available in the Stata do file upon request.

  7. 7.

    This variable was coded manually by research assistants instructed to carefully watch the episode/pitch and identify ridiculous ideas. Given such ideas were unlikely to be funded, they first filtered through the pitches that had not received an intention-to-fund. They subsequently worked their way through the remaining pitches. Their coding was further corroborated with keywords/phrases expressed on the Shark Tank blog, which typically summarizes highlights and public opinion regarding each episode/pitch.

  8. 8.

    This approach is analogous to balancing (baseline equivalence) tests conducted in experimental contexts.

  9. 9.

    While the pitches are mixed/matched across episodes during editing, we use this unit/level of clustering regardless, as we have no better information on cohort effects due to lack of internal show data. In addition, this should help take care of any effects post-airing as a result of viewership.

  10. 10.

    We also find that an intention-to-fund is significantly correlated with being registered in Delaware; however, since we do not have accurate data on the time stamp of the registration, we do not exploit this further in the analysis.

  11. 11.

    Using publicly available data from EDGAR, we also tracked whether the firm in question filed with the SEC. It turns out that 5.82% of the firms in our sample (i.e., 34 firms) appear in EDGAR; however, only 1 of these 34 firms (i.e., 0.17% of the sample) underwent a true initial public offering. The remainder filed for so-called form D, which privately held companies raising capital are required to file with the SEC to declare exempt offering of securities. Moreover, form D filings tend to be for investments in small, growing companies by venture capital and angel investors. Since we see this as an automatic by-product of appearing on/getting funding from the sharks, we did not use the data from SEC/EDGAR to construct an initial public offering dummy. Accordingly, we also end up not using this as an outcome, since it has too little variation to be meaningful.

  12. 12.

    This variable was coded manually by research assistants who were instructed to carefully watch the episode/pitch and identify keywords/phrases as explained next. The variable is constructed by summing the following across all sharks on the panel: For any given shark, the sub-variable takes the value 1 if a shark uses terms such as “I get a good vibe from you”, −1 if s/he says “I get a bad vibe from you”, and 0 if s/he express no vibes verbally (i.e., indifference). The sub-variables were further corroborated with keywords/phrases expressed on the Shark Tank blog, which typically summarizes highlights from each episode/pitch.

  13. 13.

    Anecdotally, we note that entrepreneur-contestants who get an intention-to-fund are not significantly different from those who do not on education and industry. In addition, firms who have more educated entrepreneur-contestants are no more likely to exist, be it in the short or the longer run.

  14. 14.

    The latter variable is the difference between (1) the entrepreneur’s (perceived) valuation based on the initial ask during the episode and (2) the shark’s (perceived) valuation based on the final intention-to-fund amount and stake, divided by $1,000,000. The shark’s valuation is assumed to be 0 when the intention-to-fund itself (and thus the associated amount) is 0. The scaling is necessary to interpret the magnitude (economic significance) of the coefficient on this variable.


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We thank audiences at the 2017 American Economic Association Meetings, Duke I&E (Fuqua), GA Tech (Scheller), and the Kauffman Foundation Workshop “Seeking New Insights and Potential Sources of New Entrepreneurial Growth: Minority Entrepreneurship” for useful comments. We also thank Peter Arcidiacono, Tim Bates, William Bradford, Aaron Chatterji, Andrew Dillon, Eric Edmonds, Erica Field, Fred Finan, Robert Garlick, Ruth Vargas Hill, Yael Hochberg, Joe Hotz, Sari Kerr, Eduardo Maruyama, Manju Puri, EJ Reedy, Howie Rhee, Alicia Robb, David Robinson, Rodney Sampson, Rob Seamans, Juan Carlos Suárez Serrato, Joel Sobel, Wilbert van der Klaauw, and two anonymous referees for meaningful suggestions. Viceisza is particularly grateful to the Economics Department at Duke University where much of this work was completed. We also thank Abiana Adamson, Kendyl Curry, Easlynn Lee, Rayna Thornton, and Kadija Yilla for assistance with collecting the data and Camille Black and MoNeka Young for reviewing last-minute drafts of the manuscript. Any errors are those of the authors.

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Correspondence to Angelino Viceisza.

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Smith, B., Viceisza, A. Bite me! ABC’s Shark Tank as a path to entrepreneurship. Small Bus Econ 50, 463–479 (2018).

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  • Entrepreneurship
  • Pitch competition
  • Angel-to-venture capital financing
  • Shark Tank

JEL Classification

  • L26
  • O12
  • G30