Abstract
AbstractThis paper focuses on a particular aspect of the R&D decision process, i.e. the screening of alternative projects at the firm level. A review of the traditional methods of risk analysis, based on two‐parameter measures of risk and return, strongly suggests that they are unable to capture the essential skewed nature of R&D decisions due to the underlying assumption of normal distributions. Fortunately, the availability of alternative models based on ‘distribution free’ methods has significantly increased our ability to evaluate highly skewed returns. This paper sets out, in some detail, the case of using one such model, the stochastic dominance paradigm, to screen R&D proposals.
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