Using estimation of demand for the George Washington/Jefferson NationalForest as a case study, it is shown that in a stratified/clustered on-sitesample, latent heterogeneity needs to be accounted for twice: first to accountfor dispersion in the data caused by unobservability of the process that...

Estimating regional demand models by pooling different samples without correcting for such differences causes model misspecification as each sample belongs to a different population. Weighted regression using Pseudolikelihood to account for differences in sample population with adjustment for...

Spatial differences in site characteristics and user populations may result in heterogeneity of recreation preferences and values across geographic regions. Non-linear mixed effects models provide a potential means of accounting for this heterogeneity. This approach was tested by estimating a...

Estimating regional demand models by pooling different samples without correcting for such differences causes model misspecification as each sample belongs to a different population. Weighted regression using Pseudolikelihood to account for differences in sample population with adjustment for...

Using estimation of demand for the George Washington/Jefferson National Forest as a case study, it is shown that in a stratified/clustered on-site sample, latent heterogeneity needs to be accounted for twice: first to account for dispersion in the data caused by unobservability of the process...