Intra-respondent Heterogeneity in a Stated Choice Survey on Wetland Conservation in Belarus: First Steps Towards Creating a Link with Uncertainty in Contingent Valuation

Abstract

Applications of discrete choice models in environmental valuation increasingly use a random coefficient specification, such as mixed logit, to represent taste heterogeneity. The majority of applications rely on data containing multiple observations for each respondent, where a common assumption is that tastes stay constant across choices for the same respondent.We question this assumption and make use of a model developed in the transport field which allows tastes to vary over choices for each consumer in addition to variation acrossconsumers. An empirical analysis making use of a stated choice dataset for wetland conservation in Belarus shows that superior performance is obtained by allowing jointly for the two types of heterogeneity and that recovery of these intra-respondent variations is not possible using standard approaches, such as allowing for scale heterogeneity across tasks.We show also that intra-respondent heterogeneity can be especially high for attributes which respondents are unfamiliar with, and that a failure to account for it can substantially 2 affect welfare estimates. We interpret this as an indication that this heterogeneity relates primarily to uncertainty. Finally, we offer initial insights into the relationship between intrarespondent heterogeneity and findings on uncertainty in a contingent valuation context.

Stated preferences: a unique database composed of 1657 recent published articles in journals related to agriculture, environment, or health

“…A combination of several factors may explain the increasing popularity of CE in agriculture, environment, and health: (a) Leading researchers in transportation or marketing have made many methodological contributions over the last decades in CE, including the generalized multinomial Logit model (Fiebig et al 2010), individual modelling approaches (Louviere et al 2008), discrete choice model in WTP space (Train and Weeks 2005), or the experimental designs for mixed Logit models (Bliemer and Rose 2010), which have been used by researchers in other fields. These leading researchers have collaborated with researchers from other fields and published articles in agricultural, environmental, and health journals (Hess and Giergiczny 2015;Scarpa and Rose 2008). They have also edited manuals describing state-of-the-art practices or econometric procedures (Hensher et al 2005;Hess and Daly 2014;Louviere et al 2000) which have been used by many practitioners in agricultural, environmental, and health economics to design questionnaires and estimate welfare estimates.…”

Variational Bayesian Inference for Mixed Logit Models with Unobserved Inter- and Intra-Individual Heterogeneity

“…From the perspective of discrete choice analysis, these alternative views of preference formation justify accounting for both inter-and intra-individual heterogeneity (also see Hess and Giergiczny, 2015). A straightforward way to accommodate unobserved inter-and intra-individual heterogeneity in mixed random utility models is to augment a mixed logit model with a multivariate normal mixing distribution in a hierarchical fashion such that case-specific parameters are generated as normal perturbations around the individual-specific parameters (Hess and Rose, 2009;Hess and Train, 2011).…”

Combining driving simulator and physiological sensor data in a latent variable model to incorporate the effect of stress in car-following behaviour

“…It may be noted that although the benefits of accounting for unobserved inter-intra heterogeneity have been demonstrated in other contexts using mixed logit (e.g. Hess and Train, 2011;Hess and Giergiczny, 2015) and hybrid choice models (e.g. Calastri et al, 2018), these efforts have often only led to minor changes in results.…”