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Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods

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Abstract

Using mixed logit models to analyse choice data is common but requires ex ante specification of the functional forms of preference distributions. We make the case for greater use of bounded functional forms and propose the use of the Marginal Likelihood, calculated using Bayesian techniques, as a single measure of model performance across non nested mixed logit specifications. Using this measure leads to very different rankings of model specifications compared to alternative rule of thumb measures. The approach is illustrated using data from a choice experiment regarding GM food types which provides insights regarding the recent WTO dispute between the EU and the US, Canada and Argentina and whether labelling and trade regimes should be based on the production process or product composition.

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Correspondence to Dan Rigby.

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This paper draws work commissioned by UK Department of Environment Food and Rural Affairs (DEFRA). The views presented in this paper are those of the authors alone and should not be regarded as those of DEFRA or of individuals within DEFRA.

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Rigby, D., Balcombe, K. & Burton, M. Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods. Environ Resource Econ 42, 279–295 (2009). https://doi.org/10.1007/s10640-008-9227-7

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  • DOI: https://doi.org/10.1007/s10640-008-9227-7

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