A combinatorial optimization approach to nonmarket environmental benefit aggregation via simulated populations

This paper considers the use of a "combinatorial optimization" technique in the aggregation of environmental benefit values. Combinatorial optimization is used to statistically match population census data to a contingent valuation survey. The matched survey and census information is then used to produce regional and national total willingness-to-pay figures. These figures are then compared to figures derived using more standard approaches to calculating aggregate environment benefit values. The choice of aggregation approach is shown to have a major impact upon estimates of total benefits at a regional level, especially when the target population displays considerable heterogeneity across space.