Limitations of the various functions
The valuation functions are derived from choice experiments § in which people expressed a willingness to pay for specific scenarios. Projects for which you as a user make calculations will rarely correspond 100% to those scenarios. The characteristics of those scenarios and the factors that are important to people for their appreciation of nature have consequences for the application of the valuation function. Here we discuss the various elements that are important:
Characteristics of the area being converted​
The valuation function calculates the willingness to pay for a change in land use. The starting situation for this change in function 1 and function 2 was an agricultural area with few natural and/or landscape values, a low species diversity without walking or cycling paths through the area and adjacent to other agricultural areas. For function 3 this was a coniferous forest with few natural values that do have walking, cycling or horse riding paths and for function 4 it was a watercourse with poor water quality, low species diversity and paved banks.
If the current situation differs from these characteristics, you must take this into account when completing the valuation function. If there are already constructed walking and cycling paths in the current area, or there is a high species diversity, you must set these parameters to 0. If accessibility or species diversity does not improve, no additional willingness to pay for this can be expected.
If the current area has a landscape value (historical, cultural value), the function probably overestimates the additional amenity and transfer value of the new area. Because there is no data available on willingness to pay for the historical value of landscapes, we cannot provide a correction for this.
The bandwidth in the survey (function 1 and 2) included areas from 10 to 200 ha. In the section "Substantiation of the function" we indicate how we have further developed the valuation formula in this manual so that it can also be applied to areas smaller than 10 ha and larger than 200 ha, even though the uncertainty regarding these results will be greater.
Applicability for Flanders and neighboring regions and countries​
The functions described are applicable throughout Flanders.
The survey for function 1 was conducted exclusively for households from the provinces of East Flanders, West Flanders, Flemish Brabant and the western half of the province of Antwerp. It cannot therefore be determined for the Kempen and the province of Limburg whether the willingness to pay is lower or higher there. Because these regions have more green space available than the other provinces, one can expect that the willingness to pay is lower here, which could cause the valuation function to overestimate the willingness to pay in these regions. Some literature indicates that people who live in a green environment have a higher willingness to pay for more greenery because they find this very important and that is precisely why they started living in that location. The other functions are derived from queries for specific locations. People from all over Flanders were asked here. The analysis found no provincial differences in willingness to pay, not even for the provinces of Limburg and Antwerp.
The choice experiments are solely based on a survey of residents in Flanders. We do not know to what extent people in neighboring regions are willing to pay for the availability of more nature reserves in Flanders. We do note that there are areas in the border regions that receive visitors from these regions. We therefore think that not including the value of people from neighboring regions would distort the total economic value of border areas too much. We take the willingness to pay of Flemish people as an approximation for households from other regions (Wallonia, the Netherlands, Germany and France). The uncertainty in this value is therefore great, but less great than if we did not include the willingness to pay of non-Flemish households for border areas.
§ For more information about this method see e.g. LNE, 2008.
Stated preferences as an indicator​
As an indicator on the dashboard, we use the average willingness to pay per household per year for the planned interventions. To do this, we calculate one of the above formulas for all statistical sectors within the relevant distance and take the average.