Modelling preference heterogeneity using a Bayesian finite mixture of Almost Ideal Demand Systems

Ariane Kehlbacher, Chittur Srinivasan, Rachel McCloy and Richard Tiffin

European Review of Agricultural Economics, 2020, vol. 47, issue 3, 933-970

Abstract: Demand studies often use observable characteristics to proxy preference heterogeneity. It is likely, however, that some households with the same observable characteristics have quite different preferences. An alternative approach is to use a Gaussian mixture of Almost Ideal Demand Systems to capture the heterogeneity. We show how to estimate this with censored purchase data for 5 food categories using Bayesian inference. Using model outputs we infer four different preference classes; how distinct these classes are from one another and which food categories are driving the segmentation process.

Keywords: food preferences; heterogeneity; finite mixture; Bayesian inference; Almost Ideal Demand System (search for similar items in EconPapers)
Date: 2020
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European Review of Agricultural Economics is currently edited by Timothy Richards, Salvatore Di Falco, Céline Nauges and Vincenzina Caputo

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