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Revealing the extent of process heterogeneity in choice analysis: An empirical assessment


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  • Puckett, Sean M.
  • Hensher, David A.
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    Choice analysts increasingly use a mix of revealed preference and stated choice data paradigms to identify preferences of samples of individuals that are used to infer behavioural response and willingness to pay for specific attributes. These data are in a sense artificial constructs that are developed to approximate real choice settings of the way that individuals process relevant information in making choices. As such, all data designs formalized through a survey instrument seek information through questions that become descriptions of events and as such the probabilities of choice that are of interest are strictly probabilities attached to event descriptions and not choice probabilities of events per se. The recognition of this distinction, initially noted by Kahneman et al. [Kahneman, D., Slovic, P., Tversky, A., 1982. Judgement under uncertainty: Heuristics and biases. Cambridge University Press, New York], can be captured, at least in part, through the idea of process heterogeneity, as a way of recognizing and accounting for the many ways in which individuals process information, and in part is influenced by the way the analyst describes the context in which preference data is sought. Building on previous contributions on attribute processing, this paper draws on recent empirical evidence to further reinforce the importance of joint modelling of process and outcome in choice analysis. This study adds to the evidence of a trend emerging on the upward bias of mean estimates of marginal willingness to pay when ignoring process heterogeneity.

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    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 43 (2009)
    Issue (Month): 2 (February)
    Pages: 117-126

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    Handle: RePEc:eee:transa:v:43:y:2009:i:2:p:117-126

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    Keywords: Process heterogeneity Event description Stated choice Design complexity Relevance Subadditivity Packaging;


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    1. Rabin, Matthew, 1997. "Psychology and Economics," Department of Economics, Working Paper Series, Department of Economics, Institute for Business and Economic Research, UC Berkeley qt8jd5z5j2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    3. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, SUNY-Oswego, Department of Economics, number emetr2, Spring.
    4. David A. Hensher, 2008. "Joint Estimation of Process and Outcome in Choice Experiments and Implications for Willingness to Pay," Journal of Transport Economics and Policy, London School of Economics and University of Bath, London School of Economics and University of Bath, vol. 42(2), pages 297-322, May.
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    Cited by:
    1. Balcombe, Kelvin & Bitzios, Michael & Fraser, Iain & Haddock-Fraser, Janet, 2013. "Using Attribute Importance Rankings within Discrete Choice Experiments: An Application to Valuing Bread Attributes," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia, Australian Agricultural and Resource Economics Society 152151, Australian Agricultural and Resource Economics Society.
    2. Sanko, Nobuhiro & Yamamoto, Toshiyuki, 2013. "Estimation efficiency of RP/SP models considering SP design and error structures," Journal of choice modelling, Elsevier, Elsevier, vol. 6(C), pages 60-73.
    3. Alessandro Innocenti & Patrizia Latturolo & Maria Grazia Pazienza, 2009. "Heuristics and Biases in Travel Mode Choice," Working Papers 0905, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    4. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 45(1), pages 63-79, January.
    5. David Hensher & John Rose & William Greene, 2012. "Inferring attribute non-attendance from stated choice data: implications for willingness to pay estimates and a warning for stated choice experiment design," Transportation, Springer, Springer, vol. 39(2), pages 235-245, March.
    6. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.


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