Avoided cost

The avoided cost analysis tool assesses the costs that individual and society saved because of services and benefits from the green infrastructure.

The scale level and phase to be applied

The target group: Based on observation and input behaviours from GI visitors, the tool is informing regional stakeholders to enable them to make better informed decisions on GI.

The application in the planning process
The avoided cost method was used as a tool to foster the awareness and understanding of existing and potential GI use benefits. This tool expressed the GI use benefits in terms of the health and work commuting costs avoided through the use of GI at the individual and societal level. It assesses the (1) health benefits from physical exercise within the GI as well as (2) the saved expenses by individuals commuting to work by bicycle instead of by car.

The health benefits assessment was partially framed by the TMF calculation toolkit. Because accessible green spaces provide opportunities for exercise, they increase overall level of fitness and reduce obesity of visitors. In addition to accessibility, attractive attributes encourage their use. Thus we hypothesized that actions from GIFT-T! will raise the health benefits from an increase of local stakeholders practicing physical activity in the GI. The rational of the TMF calculation toolkit is the following: If x people cycle/walk y distance on most days, what is the value of the improvements in their overall mortality rate? In other words, this valuation tool estimates the number of lives saved by walking and cycling. The number of lives can also be expressed in monetized units, estimating diverse costs: loss of productivity, medical and ambulance, willingness to avoid, police, insurance administration, property damage. For instance, within the Brussels airport case study, we found that the current frequency of visit of the GI for physical exercise improved the overall fitness of surrounding workers and residents (living within 3000 meters from the center of the GI).We estimated that the visits in the GI reduced the yearly mortality of 8.4 lives, representing total monetary savings of 19,74M€ in health care costs.

We also compared the expenses of individual commuting to work by bicycle with the costs they would inquire if they would travel by car. Analyzing bicycle commuters’ behavior, (distance travelled, frequency of bicycle used), we estimated the money saved by an average commuter in comparison to if he would travel every business day by car to work. We assumed that cycling to work has no direct cost.

Within the Brussels airport case study, we found that the mean annual savings for an average bicycle commuter was 1,380.06€. The annual total mean savings for all bicycle commuters in the case study represented 6 200 000€ in 2013.

Contact persons
Guénaël Devillet, SEGEFA, University of Liège, g.devillet@ulg.ac.be
Evelyne Lord-Tarte, SEGEFA, University of Liège, elordtarte@ulg.ac.be
Tom Bultin, The Mersey Forest, tom.butlin@merseyforest.org.uk

The following contacts are the case study leaders that have applied the tool in practice:

Katia Van Tichelen, VLM, katia.vantichelen@vlm.be
Kees Verdouw, the Province of South of Holland, c.verdouw@pzh.nl
Lieve Janssens, the Province of Antwerp, lieve.janssens@provincieantwerpen.be

More information
The avoid cost method is a widely use method in environmental economics as developed in Hanley and Spash (1993) and explained more recently in Groot et al., (2002). The avoided cost economic valuation method was conducted by the SEGEFA from the University of Liège and partially framed by The Mersey Forest calculation toolkit. The toolkit calculation was used to (1) elicit the GI catchment area, (2) estimate visitors’ frequency increase after a GI improvement, and (3) assess health benefits of physical exercise. Whenever possible, the calculations were filled in by primary data collected by GIFT-T surveys (tools 3.6 and 3.7). When primary data were not sufficient, the calculations were complemented by secondary data (from regional and national official statistics), and from figures suggested by the calculation toolkit (benefit transfer analysis).

Application on case study level: TMF calculation toolkit


  • Hanley, N., Spash, C. (1993) Cost-Benefit Analysis. Edward Elgar Publishers, Aldershot
  • de Groot, R., Wilson, M., Boumans, R., (2002) Typology for the classification, description and valuation of ecosystem functions, goods and services, Ecological Economics, (41) 393–408.