The close of the 20th century has brought new and daunting challenges to the agricultural and biological sciences. Confronted with population growth and the continual emergence of new diseases, pests, and environmental problems, researchers face pressure to develop improved technologies at an ever-increasing rate. Agricultural researchers are charged with the responsibility of producing more food and fiber, lowering the costs of production, and protecting the natural environment. They are urged to design plant varieties that benefit the poor and remedy social injustice; they are encouraged to create technologies that meet the needs of women; and they are asked to target marginal environments in which producers use few inputs.
For those who manage research organizations or allocate funding for agricultural research, this portfolio of responsibilities can be overwhelming. An increase in funding levels would always help, but the allocation problems remain. Should resources be spread across all the potentially useful subjects? Or should they be concentrated in a few priority areas? If so, which ones? Should they be devoted to long term projects with uncertain payoffs? Or to short term efforts with relatively modest—but predictable—returns? Should "upstream" research be a priority, or should agricultural researchers simply draw on tools and techniques developed in other fields of biological research? Should public money be used to fund research, or will the "right" technology be created in the private sector, where an emergent agro-biotechnology industry is generating new products daily? A host of similar questions can be identified.
Such questions about the efficient and equitable use of resources go to the heart of economics. Although many biological scientists are wary of economic analysis, the real strength of the discipline lies in its ability to shed light on the effective use of resources. Economics is usually defined as the study of how to achieve desired objectives with limited means, and this seems to be an appropriate way of thinking about the problems of research in the years ahead. Moreover, careful economic analysis forces research managers to set out their assumptions. This can occasionally reveal priorities that are "non-obvious" and that have previously been overlooked.
Priority setting for research is complex, however. Research is an inherently uncertain process: We do not know in advance whether or not certain avenues of work will be fruitful, nor how long they may take. The people who are best able to evaluate research - the scientists involved - often differ widely in their views concerning which approaches are best. Furthermore, we typically lack good data on the payoffs associated with research success. Nevertheless, several models and techniques have been developed for attempting to prioritize agricultural research.
This paper will briefly consider the relevant concepts, techniques, and models for ex ante evaluation of agricultural research. A number of examples will be considered. In particular, this paper will focus on an interesting case study: the Rockefeller Foundation's priority setting process for rice biotechnology research. It then asks whether similar priority setting methods are well suited for other decision makers, or whether different tools are appropriate in different settings. Finally, the paper speculates on what issues may emerge as central ones in the decades ahead.
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