Retrospective Benefit-Cost Analysis of Security-Enhancing and Cost-Saving Technologies

Abstract

Research and development (R&D) planners in homeland security agencies would like to be able to prioritize investments in projects based on costs versus future safety and security benefits. While costs are often readily available, estimates of safety and security benefits are fraught with uncertainty. To address these challenges, a benefit–cost model of technological change is adapted to the homeland security context. Data are sparse; therefore, estimation is facilitated by developing a familiar linear welfare model using derivatives of cost and risk reduction functions to estimate areas of costs and benefits. The theoretical model is applied to two homeland security projects involving airport patrols and the assignment of U.S. federal air marshals to international flights. Retrospective data are available for most periods. Welfare-based rates of return are reported for the two cases, each of which is estimated to return large present value net benefits. Extensive sensitivity and Monte Carlo simulation explores uncertainties. Two important findings are that (i) given the rationality assumption, relative increases in security levels can be valued, even if the absolute level of security is not known; and (ii) large uncertainties about risk reduction exist but can be bounded by parametric sensitivity and uncertainty analysis.