The Impact of Heterogeneous Preferences in Estimating the value of Lake Urmia Restoration: An Application of Partial Ranking

Willingness to pay (WTP) of environment users, determines the value of those resources. But WTP values for environmental goods tend to display heterogeneity among individuals and spatial heterogeneity. The downward trend in the environmental status of Lake Urmia during last years expresses the fact that its functions will not continue without collective measures and activities. Thus in this paper, partial ranking (best-worst) data analyzed using multilevel latent class model which provides the possibility of classifying individuals based on personal preferences and geographic location. Results showed to better fit the data, a heterogeneous model with three classes and two grand classes is required. Calculating prediction errors for best-worst choices suggests a reduction in the estimated model than the usual homogeneous model. Estimating willingness to pays diagnosed climate regulation and prevention from salt storms as the most important attribute for the respondents.