Monte Carlo simulation is a method based on repeated random sampling of inputs to a deterministic model or calculation procedure. With Monte Carlo simulation, cumulative uncertainties of nature values can be integrated in a socio-economic cost benefit analysis. In the Netherlands, an uncertainty analysis is mandatory in every socio-economic cost-benefit analysis (SCBA), according to the EMVI-guideline. This also applies to other countries that have SCBA guidelines. The purpose of such an analysis is to determine the influence of uncertain assumptions on the balance (net present value) and ranking of the alternatives. In many SCBA's, the uncertainty analysis is executed in a rather informal way. With the tool presented here, a more formal probabilistic sensitivity analysis can be carried out, based on the Monte Carlo simulation. The advantage of this method is that it provides insight in the cumulative effect of multiple uncertainties, including possible interactions between them. The cumulative effect is especially important for valuation of nature, because these values tend to have rather large uncertainty margins in the balance sheet. The formal sensitivity analysis yields information on which effects contribute most to total uncertainty. This insight can help decision makers in focusing efforts on issues producing the highest uncertainty.
This tool is a framework that helps to identify important risks and opportunities (e.g. for co-financing) and ways to integrate them in the cost-estimates of a project. Cost-effectiveness and cost-efficiency are important criteria that often govern decision-making. Usually the costs are calculated after the design alternatives have become available. However, costs are also an important design criterion, so interaction between designing and costing is important. Yet, this interaction is often not included in the design-process. This tool contributes to the assessment of the financial implications of different design alternatives, by taking different possible scenarios and related risks into account. This framework requires only limited background knowledge in costing and designing. Essential is that different disciplines (especially finance and design) work together in order to make more integrated assessments.