Joint Estimation of Process and Outcome in Choice Experiments and Implications for Willingness to Pay

By David A. Hensher. Journal of Transport Economics and Policy, 2008

116 citations recorded by the source corpus.

There is a growing recognition that the study of discrete choice outcomes should take into account the process rules that are used to establish eligibility of each attribute. This paper proposes a joint process–outcome model in which the choices made are conditioned on the rules adopted by each respondent in assessing the attributes packaged in the definition of each alternative. We set out a joint model and estimate two sets of panel-based mixed logit models — one set in which we ignore the attribute processing rules and one set in which we explicitly account for the rules. Using data from a commuter car trip study of unlabelled packages of times and cost attributes, we identify willingness to pay distributions for travel time savings under the various process rules. The main finding is that failing to account for the process rules tends to result in statistically higher mean estimates of values of travel time savings.

Subfields: Economics and Econometrics, Organizational Behavior and Human Resource Management, Transportation

View Paper: https://www.semanticscholar.org/paper/1bf713939516caaead497dde6e2ddb42a95bafea

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Citations in the corpus

Handling respondent uncertainty in Choice Experiments: Evaluating recoding approaches against explicit modelling of uncertainty (2009, background): “Recent studies have investigated biases in respondents’ processing of the different attributes in CE studies and their use of heuristics in response making as an underlying cause of uncertainty d heterogeneity (Campbell, 2008; Hensher, 2008), and found that such biases can be severe.”
Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently? (2009, background): “In this context, increases and decreases (gains and losses) may be evaluated asymmetrically, as discussed in detail by Hess et al. (2007) and also applied by Hensher (2007).”
The state of the art of environmental valuation with discrete choice experiments (2010, background): “As a consequence, there is a recent trend aiming to accommodate both the processing of attributes and the choice outcome under the same framework (Hensher, 2008).”
Attribute Processing, Heuristics, and Preference Construction in Choice Analysis (2009, methodology): “…by Hensher (2006, 2008), Greene and Hensher (2008), Layton and Hensher (2008), Hensher and Rose (in press), Hensher and Layton (2008), Hess and Hensher (2008), Puckett and Hensher (2008), Swait (2001), Cantillo et al. (2006), Cameron (2008), Scarpa et al. (2009,2009a), Beharry and Scarpa…”
Non-attendance to attributes in environmental choice analysis: a latent class specification (2011, background): “…specific category of processing strategies or heuristics, namely attribute non-attendance, where a given attribute and its associated level are ignored by a respondent when evaluating alternative attribute packages (see Hensher et al. 2005a, Campbell et al. 2008, Hensher 2008, Scarpa et al. 2009).”
Non-trading, lexicographic and inconsistent behaviour in stated choice data (2010, background): “One interesting recent body of work in this context looks at how respondents process the information presented to them, for example allowing for the fact that some of the respondents may ignore some of the attributes that they are faced with (cf. Hensher, 2007; Puckett and Hensher, 2007).”