Capturing Preference Heterogeneity in Stated Choice Models: A Random Parameter Logit Model of the Demand for GM Food
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Analyses of data from random utility models of choice data have typically used fixed
parameter representations, with consumer heterogeneity introduced by including factors
such as the age, gender etc of the respondent. However, there is a class of models that
assume that the underlying parameters of the estimated model (and hence preferences)
are different for each individual within the sample, and that choices can be explained by
identifying the parameters of the distribution from which they are drawn. Such a
random parameter model is applied to stated choice data from the UK, and the results
compared with standard fixed parameter models. The results provide new evidence of
preferences for various aspects of the UK food system, particularly in relation to GM
food but other environmental and technical aspects also. Indications of how random
parameter models might be developed further are discussed on the basis of these results.