Does accounting for preference heterogeneity improve the forecasting of a random utility model? A case study

By B. Provencher, R. Bishop. 2004

149 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/b01e6c1368a5f17b45ec6838676c6ac963a02e26

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Citations in the corpus

Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture (2009, methodology): “…Boxall and Adamowicz (2002) estimated a LC model to describe recreational choices of wilderness parks; Green and Hensher (2003) used a LC approach to model choice of long distance travel mode; Provencher and Bishop (2004) applied a LC model to the choice of recreational fishing sites, Birol el al.”
Latent class structures: taste heterogeneity and beyond (2014, methodology): “2 Decision rule heterogeneity and other mixtures of models Although structures belonging to the family of random utility models have come to dominate, it is important to recognise that alternative paradigms for decision making have been proposed, for example the elimination by aspects model of Tvers”
Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models (2008, unknown): “In contrast to the approach taken by Provencher and Bishop (2004), we focus on the implications of the choice between LCM and RPL for the estimation of welfare impacts, in terms of per choice occasion consumers’ surplus from changes in environmental quality and site-access conditions.”
Latent class model or mixed logit model? A comparison by transport mode choice data (2009, background): “( 2000 ), McFadden and Train ( 2000 ), Bhat and Gossen ( 2004 ), Bishop and Provencher ( 2004 ), Greene ( 2003 ), Hensher et al .”
Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach (2010, methodology): “modelling literature (Train, 1998; Provencher et al., 2002; Shonkwiler and Shaw, 2003; Provencher and Bishop, 2004; Morey et al., 2006).”
Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences (2005, background): “The modelling of random taste distributions within the framework of site selection random utility logit models has relied on either continuous distributions (Train 1998; Chen and Cosslett 1998; Breffle and Morey 2000) or finite ones (Provencher, Barenklau, and Bishop 2002; Shonkwiler and Land Econom”