Allocation of public funds to R&D: a portfolio choice-styled decision model and a biotechnology case study

Abstract

A decision problem—allocating public research and development (R&D) funding—is faced by a planner who has ambiguous knowledge of welfare effects of the various research areas. We model this as a reverse portfolio choice problem faced by a Bayesian decision-maker. Two elements of the planner’s inferential system are developed: a conditional distribution of welfare ‘returns’ on an allocation, given stated preferences of citizens for the different areas, and a minimum risk criterion for re-allocating these funds, given the performance of a status quo level of funding. A case study of Canadian public research funds expended on various applications of agricultural biotechnology is provided. The decision-making methodology can accommodate a variety of collective expenditure and resource allocation problems.