Research Choice and Finance in University Bioscience

[Author Affiliation]Steven Buccola, 213 Ballard Hall, Oregon State University, Corvallis, OR 97331, USA; E-mail sbuccola@oregonstate.edu; corresponding author.David Ervin, Portland State University, 241M Cramer Hall, Portland, OR 97207, USA; dervin@pdx.edu.Hui Yang, Bank of America, 315 Montgomery St., San Francisco, CA 94104-1866, USA; hui.yang@bankofamerica.com.1. IntroductionMuch of the economics of science is concerned with factors underlying the direction and productivity of laboratory work. The factors are highly varied, including alternative elaborations of the scientist's incentive structure, human capital and training, specialty field and scientific opportunities, laboratory infrastructure and assistance, professional network and culture, and institutional reputation and support. Policy implications include research institution design (Holmstrom 1989), administrative structure (Landry and Amara 1998), reporting protocols (Levitt and Snyder 1997), strength and structure of intellectual property rights (Thursby and Thursby 2003; Dillon 2005), and size and allocation of public funding (Cockburn and Henderson 1998; David, Hall, and Toole 1999; Diamond 1999).The importance of such work lies in the broad social controversy over whether, and if so how, publics ought to intervene in the traditionally autonomous character of scientific communities, for example, by encouraging greater exposure to market forces. Dasgupta and David (1994) argue that economic forces normally conducive to dynamic efficiency are unavailable in the relations between university-based open science and commercial research and development (RD Rosenberg and Nelson 1994; Stephan 1996). Price-mediated supply and demand models are, in particular, largely inappropriate to upstream scientific inquiry. Following Merton (1973), analysis instead has focused on how scientists' choices are influenced by their norms, reward structures, and institutional environments. Much empirical work is confined to subsets of factors for which data are available and which illuminate selected topics (Breschi, Lissoni, and Montobbio 2005; Walsh, Cho, and Cohen 2005; Azoulay, Ding, and Stuart 2007). Cohen, Nelson, and Walsh (2002) trace impacts of public research on industry R&D success. Agrawal and Henderson (2002) and Geuna et al. (2004) examine faculty-industry program and funding relationships in a single university. Others concentrate on generic differences in the way upstream and downstream research is best managed (Aghion, Dewatripont, and Stein 2005).We contribute to this literature by developing and estimating a bench-level model of how a subset of university bioscientists design, finance, and communicate their research. The model enables us to address in a new way some of the fundamental questions in public science policy: Does private support steer university research toward more applied or privately appropriable inventions and thus away from publicly accessible knowledge? In this Bayh-Dole era, is basic research still substantially less excludable than applied research? Does private funding facilitate public funding or vice-versa? How do investigators' professional norms affect what they study? …