Aarhus Universitets segl

No. 486: Socio-economic benefits of improved water quality. Development and use of meta-analysis function for benefit transfer

Zandersen, M., Olsen, S.B., Martinsen, L., Panduro, T.E., Zemo, K.H. & Hasler B. 2022. Samfundsøkonomiske gevinster ved forbedret vandkvalitet. Udvikling og anvendelse af metaanalysefunktion til benefit transfer. Aarhus Universitet, DCE – Nationalt Center for Miljø og Energi, 63 s. - Videnskabelig rapport nr. 486. http://dce2.au.dk/pub/SR486.pdf


The report presents an improved basis for assessment of the benefits asso-ciated with water quality improvements. The developed meta-regression function serves to transfer results from original, primary valuation studies to a Water Framework Directive (WFD) context, where it can be used to assess the benefits of fulfilling WFD requirements. The meta-analysis is based on original studies related to water quality conducted in the Nordic countries. The report describes the meta-analysis method, and how it has been tailored for valuation of improvements in the ecological status of Danish water bodies, which are characterized according to the WFD quality classes of high, good, moderate, poor and bad state.

The method has been developed to enable the estimation of willingness to pay for water quality improvements, and it includes variables which serve to explain variations in willingness to pay, e.g. demographic, geographic and methodology related variables. The underlying dataset encompasses original studies conducted in the Nordic countries during the past 25 years. Data is used to construct an econometric meta-analysis function, which can be used to estimate the value of similar water quality improvements at locations where no primary valuation studies have been conducted. The function has been tested, and results show that the transfer-errors are within the bounds of what is considered acceptable for this type of benefit transfer. The average transfer error is 13.7 % with a median of 0.7 %, and in almost three out of four cases the transfer error will at most be 50 %.

Results show significant variations across catchments; accordingly, willing-ness to pay for good water quality varies across households, as there are differences across catchments in terms of how large improvements are required to reach good status. Variations in aggregate willingness to pay across catchments can also be attributed to the fact that the number of households varies across catchments.

The meta-analysis function is applied as an example of how to calculate willingness to pay for obtaining good ecological status by 2027 for those catchments that have not yet achieved the targets under the EU WFD. The results shows a large variation in the average household willingness to pay across catchments. This is partly due to geographic and demographic differences in the catchments. The variation in the total willingness to pay to obtain good ecological status in each of the catchments is further explained by the significant differences in number of households in the different catchments. The meta-analysis function is also applicable for valuing water quality improvements in lakes and streams. This is, however, not included in the example in this report. It would be relevant to include both lakes, rivers, coastal waters and groundwater in a full cost-benefit analysis of improving water quality to good ecological status.

The meta-analysis function will be useful in relation to future calculations and assessments of the benefits associated with improvements in the quality of Danish coastal waters following implementation of the WFD. The use of the function is demonstrated in the report by applying it in the estimation of the benefits associated with meeting the WFD target of ‘good ecological status’ by 2027 in 108 coastal catchments, which drain into 109 coastal areas.