A nonparametric random effects model for the valuation of forest recreation services: An application to forest sites in Tuscany, Italy

This study assesses individuals' preferences for the use of forest sites for recreational purposes by means of the logit-mixed logit (LML) model. The appeal of the LML is that the analyst does not need to assume any specific functional form for the mixing distributions of random preferences. The empirical analysis generates a data-driven nonparametric representation of individuals' preference heterogeneity. We apply this approach to data collected using an unlabelled discrete choice experiment (DCE), consisting of three recreational options, two of which are in two hypothetical forest sites. Forest destinations are described by means of six attributes: forest type, signposting, hiking time, access to rivers or lakes, wildlife watch hides for visitors and cost of access. The empirical findings reveal that the signpost for each trail is the attribute for which respondents are on average willing to pay the most (6.565€). Further evidence suggests that respondents have strong positive preferences for those forest sites that offer amenities such as wildlife watching hides and access to rivers or lakes. Finally, the histograms derived from the semi-parametric LML estimation reveal multimodality of random taste amongst respondents for different hypothetical forest sites.