What weight should be assigned to future environmental impacts? A probabilistic cost benefit analysis using recent advances on discounting.
Cost-benefit analysis is a standard methodological platform for public investment evaluation. In high environmental impact projects, with a long-term effect on future generations, the choice of discount rate and time horizon is of particular relevance, because it can lead to very different profitability assessments. This paper describes some recent approaches to environmental discounting and applies them, together with a number of classical procedures, to the economic evaluation of a plant for the desalination of irrigation return water from intensive farming, aimed at halting the degradation of an area of great ecological value, the Mar Menor, in South Eastern Spain. A Monte Carlo procedure is used in four CBA approaches and three time horizons to carry out a probabilistic sensitivity analysis designed to integrate the views of an international panel of experts in environmental discounting with the uncertainty affecting the market price of the project's main output, i.e., irrigation water for a water-deprived area. The results show which discounting scenarios most accurately estimate the socio-environmental profitability of the project while also considering the risk associated with these two key parameters. The analysis also provides some methodological findings regarding ways of assessing financial and environmental profitability in decisions concerning public investment in the environment.
Department of Business Management, Public University of Navarra, Spain. carmen.almansa@unavarra.es
Carmen
C
Almansa
José M
JM
Martínez-Paz
D057914:Agricultural Irrigation / Q000191:economics / Q000706:statistics & numerical data; D003247:Conservation of Natural Resources / Q000191:economics / Q000379:methods; D003362:Cost-Benefit Analysis / Q000379:methods; D004777:Environment; D004784:Environmental Monitoring / Q000379:methods*; D004787:Environmental Pollution / Q000191:economics / Q000706:statistics & numerical data*; D015233:Models, Statistical; D009010:Monte Carlo Method; D018570:Risk Assessment / Q000379:methods; D018508:Water Purification / Q000191:economics / Q000706:statistics & numerical data