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Monte Carlo simulation and Social Cost Benefit Analysis

Type: Method

Project Phase: Initiation, Planning and Design

Purpose: Integrating cumulative uncertainties of nature values in a socio-economic cost benefit analysis

Requirements: Statistical skills, knowledge on cost-benefit analyses

Relevant Software: Excel, mathematical software packages (eg. MATLAB)

 

 

About

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.

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How to Use

SCBA’s are to be made by trained specialists, as they are susceptible to mistakes. Although most people understand the concept of costs and benefits, carrying out a thorough SCBA for a large project is not a simple task. SCBA in combination with Monte Carlo simulation makes the analysis even more complex, because it also requires statistical expertise. This tool may be used by SCBA-specialists with statistical skills or an SCBA-specialist and a statistician working together.

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Practical Applications

In this section we present a case-study in which we have applied a Monte Carlo simulation in combination with a socio-economic cost-benefit analysis to new developments around Lake Grevelingen in the Netherlands (Witteveen+Bos 2011).

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References

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