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

Kehlbacher, A., Srinivasan, C. ORCID: https://orcid.org/0000-0003-2537-7675, McCloy, R. ORCID: https://orcid.org/0000-0003-2333-9640 and Tiffin, R. (2020) Modelling preference heterogeneity using a Bayesian finite mixture of Almost Ideal Demand Systems. European Review of Agricultural Economics, 47 (3). pp. 933-970. ISSN 0165-1587 doi: 10.1093/erae/jbz002

Abstract/Summary

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 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.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/82857
Identification Number/DOI	10.1093/erae/jbz002
Refereed	Yes
Divisions	Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology Life Sciences > School of Agriculture, Policy and Development > Department of Agri-Food Economics & Marketing
Publisher	Oxford University Press
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