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Stated choice models based on the random utility framework are becoming increasingly popular in the applied economics literature. The need to account for respondents' preference heterogeneity in such models has motivated researchers in agricultural, environmental, health, and transport economics to apply random parameter logit and latent class models. In most of the published literature these models incorporate heterogeneity in preferences through the systematic component of utility. An alternative approach is to investigate heterogeneity through the random component of utility, and covariance heterogeneity models are one means of doing this. In this article we compare these alternative ways of incorporating preference heterogeneity in stated choice models and evaluate the sensitivity of estimated welfare measures to which approach is selected. We find that a latent class approach fits our data best, but all the models perform well in terms of out-of-sample predictions. Finally, we discuss what criteria a researcher can use to decide which approach is most appropriate for a given data set

Soil erosion produces both on‐site private costs and off‐site social costs, such as desertification, rural depopulation, siltation of waterways and reductions in biodiversity. To design efficient policies, land use planners and decision makers need information on the relative weights of changes in these consequences, since policy alternatives, such as different management restrictions, will have varying impacts on these consequences of erosion. The research presented here uses the choice experiment method to evaluate these relative weights, using a case study in the Alto Genil and Guadajoz watersheds in southern Spain. We find that reductions in desertification, protection of water quality, protection of biodiversity, the area covered by the scheme, and the number of rural jobs safeguarded are all significant determinants of preferences over alternative policy designs.