Monte Carlo simulation and Social Cost Benefit Analysis

Overview

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. 

Type: Method
Project Phase: Planning & Design, Initiation
Type of assessment: Environmental Economics
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)

Monte Carlo simulation of an alternative, resulting in (social) cost and benifit.