Progress 05/01/03 to 09/30/07
Outputs
OUTPUTS: Project activities consisted in: (a) formulating models of a university agricultural bioscientist's choice of general research orientation (basicness of program, private excludability of findings) and funding sources; (b) developing data sets from on-campus interviews with academic scientists and administrators, and from a national survey of academic bioscientists; and (c) using these data in conjunction with the bioscientist choice models to test hypotheses about the impact of research funding amounts and sources, human capital, university culture, and scientists' professional norms on university agricultural research orientation and direction. Results have been disseminated through article submissions to professional journals, workshops, and presentations at professional meetings.
PARTICIPANTS: Steve Buccola, Oregon State University David Erven, Portland State University Hui Yang, Bank of America (who obtained her PhD at Oregon State University on this project) Rick Welch, Clarkson University Leland Glenna, Pennsylvania State University
TARGET AUDIENCES: Research policy makers in federal and state government and in universities
PROJECT MODIFICATIONS: No Project Modifications information reported.
Impacts
We find that a scientist's funding portfolio substantially influences the basicness and excludability of her research. In particular industry financing induces, at the margin, much more applied and excludable investigation than do other money sources. Yet donors' in-kind contributions, the scientist's human capital, the university's culture, and especially the scientist's professional norms, are important as well. Estimated impacts are large considering that that a scientist's latitude, and hence potential responsiveness, in selecting specific research topics generally is greater than his broad orientation toward invention excludability or position on the basic-to-applied discovery continuum. Taking their sample variability into account, scientists' professional norms are about as important as funding sources in affecting the overall direction of laboratory research. Finance, however, has the greater influence over program basicness, and scientific norms the greater
influence over excludability. Such differentiation is understandable because a project's basicness is readily discoverable at the proposal stage, while the expected excludability of its findings depends on research decisions and outcomes occurring later. Government sponsors in particular have little immediate interest in whether property rights are achieved directly from the investigations they fund. And although industry sponsors do seek patenting and licensing opportunities, they regard early access to new ideas as more important than enhanced access to intellectual property.
Publications
- Buccola, S., D. Ervin, and H. Yang. Research Choice and Finance in University Bioscience. Department of Agricultural and Resource Economics, Oregon State University, 2007.
- Ervin, D., S. Buccola, and H. Yang. Academic bioscience, Money Sources, and Professional Norms. Department of Agricultural and Resource Economics, Oregon State University, 2007.
- Buccola, S.T., and Y. Xia. The Strength and Structure of Intellectual Bio-Property Markets. In J. Kesan, ed., Agricultural Biotechnology and Intellectual Property: Seeds of Change, pp. 204-215. Oxfordshire, UK: CAB International, 2007.
- Buccola, S.T., D. Ervin, and H. Yang. Orientation, Funding Source, and Professional Norms in University Agricultural Biotechnology. Presented at Third Meeting of the University-Industry Demonstration Partnership. GUIRR Program, The National Academies, Irvine, CA, July 24, 2007.
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Progress 01/01/06 to 12/31/06
Outputs
We have specified and estimated a dynamic model of public investment in life-science research, distinguishing among the three principal life-science fields: agriculture, pharmaceuticals, and basic biology. The dynamic model was employed to account for research adjustment costs potentially incurred when public and private investment levels are changed, and to permit separate examination of the wage effect and spillover effect of public life-science research. We find that, in both agriculture and pharmaceuticals, public expenditures' positive spillover effect (that is, the private-sector knowledge gleaned from public research) dominates these expenditures' negative wage effect (that is, the higher salaries which private research firms must pay because of scientist hiring in the public sector), so that government- sponsored and -conducted research is strongly complementary with that in the private sector. Positive spillovers are especially high in agriculture. However,
the supply of scientific labor in agricultural research is found to be much more inelastic than in pharmaceutical research, implying a stronger wage effect in the former than in the latter. This strong wage effect partly counterbalances the strong spillover effect, so that private R&D investment in agriculture has been less responsive to exogenous factors than it has been in pharmaceuticals. We will now turn our attention to the second-tier problem: assessing research investments' spillover and productivity effects in individual agricultural sub-fields, particularly in plants, animals, and natural resources.
Impacts
Evidence of public investment's predominant role in creating incentives for industrial investment in life-science research has important implications for government science and technology policy. During the past two decades, the federal government has greatly expanded life-science research investment in response to rising public demands surrounding health and food issues. We have shown this investment strategy to be successful in creating technological opportunities for life-science firms. Simulation results indicate public investment in the life sciences will continue to be highly valuable for the private sector. R&D tax credits may have exerted similar knowledge spillover effects, and represent alternative policy instruments for stimulating industry R&D investment.
Publications
- Wang, C., Y. Xia, and S. Buccola. Public Investment Policy in Life-Science Research. Selected paper delivered at the American Agricultural Economics Association Annual Meetings, Long Beach, CA, July 24, 2006.
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Progress 01/01/05 to 12/31/05
Outputs
A stratified random national survey was conducted of university life scientists engaged in molecular-level research with implications for agriculture, forestry, and aquaculture. The survey obtained data on the nature of the scientists' research; sources, amounts, and types of support; laboratory inputs; academic rank and other demographics; publication and patent outputs; professional networks; university policies and assistance; and aspects of the scientists' professional values. The survey was sent to 1441 scientists, 63.8% of whom provided usable responses. An econometric model was developed in which the basicness and excludability of a scientist's research program are determined simultaneously with publication output and with funding from federal, industry, and other sources. Although basicness and excludability are positively correlated, they have asymmetric effects on one another. Controlling for other factors, federal funding encourages research that is more
basic but more excludable, while industry funding encourages research that is more applied. Only state and foundation funding lead, ceteris paribus, to more applied and less excludable research. The nature and productivity of bioscientific research are, in addition, heavily influenced by the professors' rank, career goals, and attitudes. While industry funding has no effect on federal funding, federal and state/foundation funding do crowd out industry funding.
Impacts
An important issue in science policy is the proper role of the private and public sectors in academic life science research. Many argue that industry financing skews research in an applied direction toward studies favoring private over public interests, and toward technologies that will be inaccessible to most university researchers. Industry influence in the university laboratory should therefore be reduced. Our results confirm that industry funding leads to more applied research than does federal funding, but does not indicate that federal support is more effective than industry support in maintaining research in the public sector. A second major issue is the potential complementarity of non-government with government finance. If federal funding of university agricultural research encourages non-government funding, the productivity impact of another federal dollar is accentuated. In regard to industry funding, our results instead support the substitutability
hypothesis: for every additional dollar of federal finance, industry supplies $0.06 less on university agricultural biotechology researchers than they otherwise would. However, in regard to state and foundation funding, our results support the complementarity hypothesis: for every additional dollar of federal finance, states and foundations respond by supplying $0.21 more than they otherwise would.
Publications
- No publications reported this period
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Progress 01/01/04 to 12/31/04
Outputs
Using results from our survey of approximately 80 universities and 700 university agricultural scientists, we employ econometric methods to assess the factors influencing scientists' and funding agents' research program choices. Higher funding encourages scientists to prefer more basic research but also to focus on more excludable (patentable) innovations. More junior professors also prefer more basic yet more excludable research. Controlling for other factors, scientists at Land Grant universities seek to do much more applied bioresearch, but not more excludable research, than do those in other universities. Funding agent preferences are quite different from scientist preferences. For example, the more basic the research promised in a proposal, the less willing is the average funding agent to finance it. But such willingness differs greatly among funding agents, for example between industry and government funding sources.
Impacts
These results constitute the first rigorous empirical examination, at the scientist level, of the factors influencing the types of research pursued in university agricultural biotechnology labs. They will guide a number of policy decisions at the federal and university level. For example, while the typical Land Grant bioscientist does conduct more applied work than does the typical non-Land Grant professor, the claim that Land Grant research is oriented toward financially more capturable results -- as opposed to public or non-market benefits -- is not supported. We also identify a range of policy initiatives that would influence research toward or away from immediate applicability, patentability, and particular crops and organisms.
Publications
- Yang, H., S.T. Buccola, D. Ervin, K. Kim, and E. Minor. University-Industry Relationships and the Biotechnology Research Agenda. Presentation delivered at the Conference on Innovation and Dynamic Efficiency in Agricultural Biotechnology, Economic Research Service and CSREES, USDA, Washington, D.C., October 14 - 15, 2004.
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Progress 01/01/03 to 12/31/03
Outputs
Three activities were undertaken in 2003: (a) continued development of a conceptual model to explain the factors affecting an academic bioscientist's research program and objectives, including any industry relationships in which the scientist is involved; (b) developed a national sample of university bioscientists, together with a survey instrument for testing hypotheses developed from the conceptual model, and (c) began receiving and tabulating the survey responses. A brief review of each follows. (a) We are using a market model to understand the formulation of a university bioscientist's research program. In this model, a scientist and a (government, industry, or other) funding agency each expresses its own preferences for the scientist's research program and funding level. Discrepancies between the two preferences are resolved by assuming competition among scientists and among funding agents, so that research programs which researchers offer are equilibrated with
those which funding agents seek. A research program is represented by how basic it is, by its disciplinary focus, field, and topic, and by the expected market excludability of its expected findings. (b) The national survey instrument contains approximately 50 questions designed to elicit information on (i) the scientist's research program, (ii) sources and amounts of funding, (iii) sources and types of in-kind support for the research program, (iv) the scientist's background and human capital, (v) the scientist's publication and patent outputs, and (vi) the scientist's ethical and other attitudes toward bioscientific research. It was sent in web form to 1067 bioscientists employed at 30 randomly selected U.S. research universities. The random selection was stratified to include 10 land-grant, 10 public non-land-grant, and 10 private universities. (c) A usable response rate of 60% has been achieved to date. In most questions, respondents' answers are distributed broadly across the
possible answers, suggesting adequate sample variation will be available for statistical tests of the study hypotheses. Preliminary regression of research basicness and market excludability suggests these program characteristics are reasonably related to the scientist's orientation toward patenting and to the sources of her laboratory funding.
Impacts
Conceptual model and research design have been reported at three professional conferences (indicated below).
Publications
- Yang, H. and S.T. Buccola. University-industry relationships and the design of biotechnology research. Selected paper delivered at the American Agricultural Economics Association Annual Meetings, Montreal, Quebec, July 27-30, 2003.
- Buccola, S.T. University-industry relationships in agricultural biotechnology: research insights from four cases. Panelist, Rural Sociological Association Annual Meetings, Montreal, Quebec, July 27-30, 2003.
- Xia, Y. and S.T. Buccola. The rate of progress in agricultural biotechnology. Paper delivered at Regional Research Conference NC 1003, New Brunswick, NJ, February 28-March 1, 2003.
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