How Venture Capitalists and Startups Bet on Each Other: Evidence From an Experimental System
85 Pages Posted: 20 Nov 2020 Last revised: 16 Nov 2022
Date Written: October 31, 2020
The entrepreneurial financing process is essentially a two-sided matching process between investors and startups. This paper implements two symmetric incentivized resume rating (IRR) experiments with real US venture capitalists and US startup founders to elicit their preferences for potential collaborators. Experimental subjects evaluate randomized profiles of potential collaborators and these evaluation results are incentivized by real opportunities of being matched with their dream cooperation partners. On the investor side, we find both startups' human assets (i.e., educational background, entrepreneurial experiences) and non-human assets (i.e., traction, business model, location, comparative advantages) affect investors' contact interest and investment interest through influencing their evaluations of startups' potential financial returns, risk, and availability. On the startup side, we find both investors' human capital (i.e., entrepreneurial experiences, years of investment experiences) and funds' organizational capital (i.e., previous financial performance, fund size) affect startups' collaboration interest and fundraising plans through influencing startups' judgements on the investor's quality, potential investment interest, and the investor profiles' informativeness. To assess the equilibrium payoffs of VCs and startups, we estimate a search-and-matching model with bargaining between VCs and startups using the experimental results. We find that an average VC gets 80% more value than an average startup because of better outside options. A substantial heterogeneity in equilibrium payoffs, explained by both human and organizational characteristics, exists across both startups and VCs.
Keywords: Human Capital, Non-human Capital, Venture Capital, Entrepreneurship, Portfolio Selection Criteria, Fundraising Behaviors, Field Experiments, Matching, Preference
JEL Classification: C78, C93, D83, G24, G40, J71
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