Using Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferences

In this paper, we investigate the use of geographically weighted choice models for modelling spatially clustered preferences. We argue that this is a useful way of generating highly‐detailed spatial maps of willingness to pay for environmental conservation, given the costs of collecting data. The data used in this study come from a discrete choice experiment survey of public preferences for the implementation of a new national forest management and protection programme in Poland. We combine these with high‐resolution spatial data related to local forest characteristics. Using locally estimated discrete choice models we obtain location‐specific estimates of willingness to pay (WTP). Variation in these estimates is explained by characteristics of the forests close to where respondents live. These results are compared with those obtained from a more typical, two stage procedure which uses Bayesian posterior means of the mixed logit model random parameters to calculate location‐specific estimates of WTP. We find that there are indeed strong spatial patterns to the benefits of changes to the management to national forests. People living in areas with more species‐rich forests and those living nearer bigger areas of mixed forests have significantly different WTP values than those living in other locations. This kind of information potentially enables a better distributional analysis of the gains and losses from changes to natural resource management, and better targeting of investments in forest quality.     

Cattle Farmers’ Preferences for Disease‐Free Zones in Kenya: An application of the Choice Experiment Method

Management of livestock diseases is important in ensuring food safety to consumers in both domestic and export markets. Various measures are prescribed under the Sanitary and Phytosanitary Standards (SPS) agreement of the World Trade Organization. In order to prevent the spread of trans‐boundary cattle diseases, the SPS agreement recommends the establishment of Disease‐Free Zones (DFZs). These have been implemented successfully in some major beef‐exporting countries, but in Kenya are still at a pilot stage. To understand Kenyan farmers’ preferences on the type of DFZ that would be readily acceptable to them, a choice experiment was conducted using a D‐optimal design. Results show that farmers would be willing to pay to participate in a DFZ where: adequate training is provided on pasture development, record keeping and disease monitoring; market information is provided and sales contract opportunities are guaranteed; cattle are properly labelled for ease of identification; and some monetary compensation is provided in the event that cattle die due to severe disease outbreaks. Preferences for the DFZ attributes are shown to be heterogeneous across three cattle production systems. We also derive farmers’ preferences for various DFZ policy scenarios. The findings have important implications for policy on the design of DFZ programmes in Kenya and other countries that face similar cattle disease challenges.