This paper presents simple formulae for the utility covariances of the nested logit (NL) model, and based on these defines a “scaled tree” that can be used as an aid for the interpretation of estimation results. The paper also shows that the full information log-likelihood function of linear-in-the-parameters NL models is concave in the utility parameters. Thus, conditional on the scaling parameters, full information maximum likelihood (FIML) searches cannot get trapped in local maxima.
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Daganzo et al. (1993) studied this question.
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