Firm R&D units and outsourcing partners: A matching story

We present a theory that examines the optimal match between firm R&D units and external partners for projects that involve problem solving. We have a firm selecting an external partner conditional on the learning costs of its internal R&D unit. We show that there exists a matching equilibrium with property that external partners with low learning costs for a project work with R\&D units that also have low learning costs for the same project. Empirically, we use a dataset of Spanish R\&D firms and relate their share of R&D outsourcing to universities to the composition of their R&D units, described by the presence of staff with a PhD. Our main finding is that, controlling for endogeneity, firms that employ R\&D staff with a PhD outsource relatively more to universities than to firms. We interpret this result as evidence that R&D units with relatively low learning costs for basic projects tend to match with external partners, universities, with relatively low learning costs for the same projects.

Is the US Outperforming Europe in University Technology Licensing? A New Perspective on the European Paradox

Europe is perceived to be lagging behind the US in converting its academic results into economic outcomes. Using new survey data on European and US Technology Transfer Offices (TTOs), we find that differences in academic research, TTO staff and experience explain to a great extent the gap between the US and Europe in terms of the number of license agreements concluded. However, these factors account for only part of the difference in license income. We relate the difference in licensing income to differences in the organization and staffing of TTOs. Our analysis reveals that US TTOs do not attach more importance to generating revenue as an objective than their European counterparts. However, they employ more staff with experience in industry which explains some of the remaining differential in license income performance.

Managing innovations resulting from university-industry collaborations

We consider a policy regime allowing academic institutions to grant industry the intellectual property rights (IPRs) over invention resulting from collaborations. If a firm plays an important role in generating an invention, the researcher offers the IPRs to the firm, as an incentive to collaborate. However, he retains certain domains where he can exploit an invention without having to apply for a license. The choice of these domains involves a tradeoff. In fact, the researcher either induces the firm's effort, by assigning a broad field of use, or he ensures that he can use an invention in other applications, by granting a narrow field of use. The reverse occurs if it is the researcher who plays an important role in generating an invention. The main difference, however, is that if effort were contractible, the firm could reward the researcher for supplying the first best level of effort, because, unlike the researcher, it is not cash constrained. An empirical analysis, based on École Polytechnique Fédérale de Lausanne research contracts, supports the role of broad fields in bolstering a firm's effort, when the latter is important for generating an invention

Micro venture capital

Recently, the venture capital (VC) industry has experienced the entry of several new capital providers. Using US data on investors and their portfolio startups from 2000 to 2022, we document the emergence of a new type of investors: the micro VC. Our analysis reveals that micro Vencture Capitalists (VCs) have an idiosyncratic investment strategy, which differs from traditional VCs. Compared with these investors, micro VCs invest in riskier startups, that is, early-stage ventures initiated by less experienced founders; yet, micro VCs are less likely to syndicate, stage their investments, and replace the startup founders. Additionally, startups funded by micro VCs are less likely to experience successful exits than those backed by traditional VCs. These results can be traced to a mix of smaller capital endowments, less sophisticated limited partners, and lesser human capital of which micro VCs dispose, and that may induce them to spread their thin capital across many investments to maximize returns. Our analysis also uncovers important differences in the strategies pursued by micro VCs and business angels.Managerial SummaryThe VC industry is increasingly populated by a variety of investors with disparate characteristics and objectives. One such type of investors is represented by the so-called micro VC firms. These are VC firms that manage funds typically below $50 million and focused primarily on investing in founder-led startups. We leverage comprehensive VC data in the United States to answer three questions: (1) Who leads micro VC firms? (2) How do micro VC firms invest? (3) How do startups backed by micro VC perform? We find that micro VC firms are often led by relatively inexperienced entrepreneurs with little VC experience, and these firms are supported by less sophisticated limited partners. Although micro VC firms invest in riskier startups, they are less engaged in syndication and investment staging than traditional VC firms. Finally, micro VC-backed startups have a lower probability of successful exit as compared with those backed by traditional VC firms. Collectively, our results suggest that micro VCs differ from traditional VCs beyond being "micro.

Are the US outperforming Europe in university technology licensing? A new perspective on the European paradox

Europe is perceived to lag behind the US in converting its academic results into economic outcomes. Using new survey data and controlling for standard factors affecting the productivity of Technology Transfer Offices (TTOs), we find that European TTOs do not execute less licenses than US TTOs. However, they earn significantly less revenue from licenses. We relate the difference in licensing income to differences in the organization and staffing of TTOs. Specifically, US TTOs employ more staff with experience in industry and appear to have greater flexibility in managing their budget

Universities and access to medicines: What is the optimal ‘humanitarian license’?

This paper seeks to add an economic contribution to the current debate on using university licensing contracts to improve access to medicines in developing countries. We build a simple model in which we have a university licensing out an academic invention to a profit-maximizing pharmaceutical company. We compare three different types of licensing contracts that the university might use to enhance access to pharmaceuticals in the South: (1) an exclusive license limited to the North; (2) an exclusive license worldwide with a price cap in the South; and (3) an exclusive license worldwide with a price cap in the South and a clause specifying that the licensee would lose its exclusivity in the South if it does not supply the Southern market. We show that in a simple model with asymmetric information on production costs the latter type of contract dominates the two others

Firm R&D units and outsourcing partners: A matching story

We present a theory that examines the optimal match between firm R&D units and external partners for projects that involve problem solving. We have a firm selecting an external partner conditional on the learning costs of its internal R&D unit. We show that there exists a matching equilibrium with property that external partners with low learning costs for a project work with R\&D units that also have low learning costs for the same project. Empirically, we use a dataset of Spanish R\&D firms and relate their share of R&D outsourcing to universities to the composition of their R&D units, described by the presence of staff with a PhD. Our main finding is that, controlling for endogeneity, firms that employ R\&D staff with a PhD outsource relatively more to universities than to firms. We interpret this result as evidence that R&D units with relatively low learning costs for basic projects tend to match with external partners, universities, with relatively low learning costs for the same projects