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Modelling heterogeneity in response behaviour towards a sequence of discrete choice questions: a latent class approach

Author

Listed:
  • McNair, Ben J.
  • Hensher, David A.
  • Bennett, Jeff

Abstract

There is a growing body of evidence in the non-market valuation literature suggesting that responses to a sequence of discrete choice questions tend to violate the assumptions typically made by analysts regarding independence of responses and stability of preferences. Heuristics such as value learning and strategic misrepresentation have been offered as explanations for these results. While a few studies have tested these heuristics as competing hypotheses, none have investigated the possibility that each explains the response behaviour of a subgroup of the population. In this paper, we make a contribution towards addressing this research gap by presenting an equality-constrained latent class model designed to estimate the proportion of respondents employing each of the proposed heuristics. We demonstrate the model on binary and multinomial choice data sources and find three distinct types of response behaviour. The results suggest that accounting for heterogeneity in response behaviour may be a better way forward than attempting to identify a single heuristic to explain the behaviour of all respondents.

Suggested Citation

  • McNair, Ben J. & Hensher, David A. & Bennett, Jeff, 2010. "Modelling heterogeneity in response behaviour towards a sequence of discrete choice questions: a latent class approach," MPRA Paper 23427, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:23427
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    References listed on IDEAS

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    More about this item

    Keywords

    Choice experiment; latent class; ordering effects; strategic response; willingness-to-pay;
    All these keywords.

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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