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The estimation of choice models that explicitly incorporate economic agents' goal-related information has yet to receive focused attention from practitioners. Despite recent advances on spatial analysis in stated preference studies, there is still no evidence on how spatial effects interact with goal pursuit. In this study we propose a modelling framework to analyse how goal pursuit influences choices and query whether pursuit of important goals makes individuals less distance-sensitive. We estimate a hybrid choice model with latent variables to investigate the role of goals and distance on preferences for recreational site attributes. We use data from a choice experiment involving selection among different sites in Dolomiti Bellunesi National Park (Italy). Our results show that goal pursuit has a significant effect on site choice probability and that distance disutility is decreased when individuals visit recreational sites due to pursuit of important goals. This result indicates that willingness to pay inferences concerning spatially distributed activities depend crucially on the spatial distribution of motivations for participation. [ABSTRACT FROM AUTHOR]

Unobserved heterogeneity of error scale in choice models is a recent extension of the better investigated issue of heterogeneity of taste intensity. It is achieved by fitting choice panel data with specifications that simultaneously handle inter-personal variation in scale and taste. The aim is to separate differences in preference intensities across respondents from differences in the degree of consistency in choice behaviour, or 'preference discrimination', while accounting for correlation between the two. Another recent substantive issue in choice data analysis is attribute non-attendance. We develop a finite mixing model to address simultaneously the three issues above. We empirically prove the concept on stated preference data related to tap water attributes in a study for industry regulation. [ABSTRACT FROM AUTHOR]

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications. [ABSTRACT FROM AUTHOR]

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 frequent goal of applied studies has been the estimation of welfare changes associated with site attribute changes at 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 the WTP-space (Train K, Weeks M (2005) Discrete choice models in preference space and willing-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 the maximum simulated likelihood estimator affords to practitioners using the WTP-space approach, and illustrate these with examples. [ABSTRACT FROM AUTHOR]

We report preliminary results on the investigation of the hypothesis of the existence of latent classes in the total demand for days out in a vast section of the Italian Eastern Alps. Finite mixing is informed by socioeconomic variables and it is limited to the demand portion of a hurdle model of visitation. Gradually more flexible count models are estimated moving from the Poisson to the Negative Binomial -1 and -2, to the generalized negative binomial. The implications for expected consumers surplus, predicted visitation and choke prices are discussed for a plausible 2 class model where years of experience play an important role in class membership. [ABSTRACT FROM AUTHOR]