Nonmarket valuation of water quality: Addressing spatially heterogeneous preferences using GIS and a random parameter logit model

The spatial distribution of agri-environmental policy benefits has important implications for the efficient allocation of management effort. The practical convenience of relying on sample mean values of individual benefits for aggregation can come at the cost of biased aggregate estimates. The main objective of this paper is to test spatial hypotheses regarding respondents' local water quality and quantity, and their willingness-to-pay for improvements in water quality attributes. This paper combines choice experiment and spatially related water quality data via a Geographical Information System (GIS) to develop a method that evaluates the influence of respondents' local water quality on willingness-to-pay for river and stream conservation programmes in Canterbury, New Zealand. Results showed that those respondents who live in the vicinity of low quality waterways are willing to pay more for improvements relative to those who live near to high quality waterways. The study also found that disregarding the influence of respondents' local water quality data has a significant impact on the magnitude of welfare estimates and causes substantial underestimation of aggregated benefits.

► We consider the influence of local water quality on preferences for water resource attributes in a Choice Experiment. ► We find that welfare values for water quality attributes are spatially sensitive. ► People living near low quality waterways are WTP more for improvements relative to those living near higher quality waterways. ► We find that disregarding the influence of local water quality leads to underestimation of aggregated benefits. ► Integrating biophysical and economic data analysis improves welfare estimates of policy outcomes.