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A Multivariate Model for Multinomial Choices

By K. (Koen) Bel and R. (Richard) Paap


__Abstract__\ud \ud Multinomial choices of individuals are likely to be correlated. Nonetheless, econometric models for this phenomenon are scarce. A problem of multivariate multinomial choice models is that the number of potential outcomes can become very large which makes parameter interpretation and inference difficult. We propose a novel Multivariate Multinomial Logit specification, where (i) the number of parameters stays limited; (ii) there is a clear interpretation of the parameters in terms of odds ratios; (iii) zero restrictions on parameters result in independence between the multinomial choices and; (iv) parameter inference is feasible using a composite likelihood approach even if the multivariate dimension is large. Finally, these nice properties are also valid in a fixed-effects panel version of the model

Topics: Discrete Choices, Multivariate analysis, Multinomial Logit, Composite Likelihood
Year: 2014
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