We compare two approaches for estimating the distribution of consumers' willingness to pay (WTP) in discrete choice models. The usual procedure is to estimate the distribution of the utility coefficients and then derive the distribution of WTP, which is the ratio of coefficients. The alternative is to estimate the distribution of WTP directly. We apply both approaches to data on site choice in the Alps. We find that the alternative approach fits the data better, reduces the incidence of exceedingly large estimated WTP values, and provides the analyst with greater control in specifying and testing the distribution of WTP. Copyright 2008, Oxford University Press.

Rock climbers are likely to exhibit preference heterogeneity dictating the way with which such sport is practiced. This has a reflection on the population's structure of recreational values of rock-climbing destinations, their attributes, and to land management policies. We test this hypothesis on a panel of destination choices by a sample of members of the Italian Alpine Club. Using a latent-class, random utility approach we find evidence in support of the hypothesis that there are at least four classes in the sample, thereby revealing a considerable richness in the structure of preference, which would otherwise be unobservable with more conventional approaches. (JEL Q26, C25) II. FINITE-MIXING IN RANDOM UTILITY MODELSTravel Cost Applications

Land management in Alpine Parks provides multifunctional services to separate groups of users. Choice experiments can be used to derive estimates of value for different management attributes. However, little research has been conducted on how frequently respondents ignore attributes used to describe policy management scenarios. We fill this gap using an approach that identifies and compares both serial and choice-task attribute non-attendance addressing five different visitor types. Our results indicate that accounting for choice-task non-attendance significantly improves model fit and yield estimates of marginal WTP with a more plausible pattern of signs and greater efficiency.

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Estimation of welfare measures is often a dominant driver in the empirical literature on nonmarket valuation. To this end, qualitative choice models based on random utility theory have been widely employed in outdoor recreation studies. A requent goal of applied studies has been the estimation of welfare changes associated with site attribute changes at\ud recreation sites in order to inform regulatory policy and resource management. We review the evolution of the methodology of random utility theory in this field with a focus on taste heterogeneity models and then focus on the recent proposal of specifying utility in theWTP-space (Train K, Weeks M (2005) Discrete choice models in preference space and illing-to-pay space. In: Scarpa R, Alberini A (eds) Applications of simulation methods in environmental and resource economics, chapter 1. Springer, Dordrecht, pp 1–16). Our empirical application is on outdoor alpine recreation data.We emphasize the efficiency and direct testing that using\ud the maximum simulated likelihood estimator affords to practitioners using the WTP-space approach, and illustrate these with examples

The European COST Action E45 on European Forest Externalities (EUROFOREX) participants developed a set of good practice guidelines for the non-market valuation of forests, elaborating on stated and revealed preference methodologies, as well as benefit transfer and meta-analytical procedures. This article presents a summary of the guidelines