Abstract: I investigate the reputation effects of active involvement, specifically examining how venture capitalists’ (VCs’) on-site meetings with portfolio companies affect VCs’ reputations and future deal flow. By analyzing cell phone signals collected around VC and startup office buildings from 2018 to 2023, I measure VCs’ involvement intensity and deal flow quality. Using exogenous variation in travel ease, I show that increased VC involvement leads them to receive better online reviews from entrepreneurs, attracting more and higher-quality new entrepreneurs to pitch, ultimately improving future investment outcomes. Furthermore, I document six stylized facts about VC involvement: (1) VCs visit underperforming portfolio companies more frequently; (2) the frequency of visits increases when portfolio companies are closer; (3) early-stage investments receive more frequent visits; (4) VCs and nontraditional investors (CVCs, PEs, hedge funds) visit at similar frequencies, while accelerators and incubators visit more often; (5) deals with more co-investors involve more overall visits, but each investor visits less frequently; and (6) larger VCs visit less frequently per deal.
Abstract: Venture capitalists have been criticized for underinvesting in nascent technologies that build on basic science, also known as deep-tech. However, deep-tech startups typically face high technical risks not amenable to the VC model. We study whether public funding of academic research aimed at filling gaps in basic science, thereby reducing technical risk, can foster VC investment. Exploiting the BRAIN Initiative (BI), a focused government program with the goal of mapping the human brain, we find an increase in VC investments in neurotech startups accompanied by higher valuations and more successful VC exits. The channels driving these results are in line with reduced technical risk: 1) a higher supply of technical labor reflected in more STEM academics as employees; 2) more innovation, as measured by the quantity and quality of patents, including breakthrough patents; 3) enhanced integration of neurotechnologies with complementary technologies, especially AI and machine learning, which aligns with the BI's data-driven mission. Our results indicate that by supplying basic science and skilled labor, mission-oriented public funding crowds in private investments in emerging technologies.
