Abstract

When decision-makers consider pure and applied research infrastructures, such as genomics platforms, astronomic observatories, nanoelectronic laboratories, oceanographic vessels, or particle accelerator facilities (just to mention some examples) are faced by this question: what is the net social benefit of these costly scientific ventures and of the public goods they produce? The answer is often given qualitatively, or even rhetorically, by scientists and other stakeholders in these projects. But can we go beyond anecdotal evidence, narratives and ad hoc studies and try a structured ex-ante and ex-post evaluation of the socio-economic impact of research infrastructures? This paper explores some of the methodological issues involved in a CBA framework for capital-intensive scientific projects. The paper proposes a conceptual model based on the estimation of quantities and shadow prices of cost aggregates, and of six main categories of economic benefits (pure value of discovery, knowledge outputs, technological spillovers, human capital formation, cultural effects and services to third parties). Empirical approaches are suggested for further applied research, including the use of probability distribution functions to generate expected net present values of research infrastructures by Monte Carlo methods.

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