Discrete Choice Models in Preference Space and Willingness-to Pay Space

By Kenneth Train, M. Weeks. 2005

926 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/e39d0db7422852e466340a0eb51ed919775485a9

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Citations in the corpus

Transportation service bundling – For whose benefit? Consumer valuation of pure bundling in the passenger transportation market (2018, background): “The concept was first introduced by Cameron and James (1987) and11 Cameron (1988) and was investigated in Train and Weeks (2005).”
Correlation and scale in mixed logit models (2017, background): “Models in WTP-space reparameterize utility such that the distribution of WTP is estimated directly (e.g. Scarpa et al., 2008; Train and Weeks, 2005).”
Consumers’ Willingness to Pay for Renewable Energy: A Meta-Regression Analysis (2015, background): “Large WTP variances can translate into an untenable implication that people are willing to pay a large sum of money for RE (Train and Weeks, 2005).”
Using revealed preferences to estimate the Value of Travel Time to recreation sites (2014, positive): “If violated, this latter assumption will induce biased inference by erroneously attributing variation in scale to variation in WTP. Train and Weeks (2005) resolve this issue by re-writing the model in what they define as being the WTP representation, which, in our context, we refer to as VTT space.”
We want to sort! – assessing households’ preferences for sorting waste (2014, methodology): “…in modelling respondents preference heterogeneity, if no correlations between random variables are allowed, all respondents are assumed to have the same scale coefficient used for normalizing their utility function, i.e. their choices demonstrate the same extent of randomness (Train & Weeks 2005).”
Estimation on stated-preference experiments constructed from revealed-preference choices (2008, background): “Train and Weeks (2005) discuss reasons for and against holding the price coefficient fixed and compare estimation methods when the price coefficient is random.”
Discrete choice models with multiplicative error terms (2009, background): “These issues may be addressed by explicitly specifying a distribution for µ (Bhat, 1997; Swait and Adamowicz, 2001; De Shazo and Fermo, 2002; Caussade et al., 2005; Koppelman and Sethi, 2005; Train and Weeks, 2005).”
Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture (2009, background): “These assumptions implicitly constrain the scale parameter to be constant across respondents, as noted by Train and Weeks (2005) 9 .”
Assuring finite moments for willingness to pay in random coefficient models (2009, positive): “• Finally, the model can be re-parameterised in WTP space, as suggested by Train and Weeks (2005).”