Correlation and scale in mixed logit models

By Stephane Hess, Kenneth Train. 2017

303 citations recorded by the source corpus.

This paper examines sources of correlation among utility coefficients in models allowing for random heterogeneity, including correlation that is induced by random scale heterogeneity. We distinguish the capabilities and limitations of various models, including mixed logit, generalized multinomial logit (G-MNL), latent class, and scale-adjusted latent class. We demonstrate that (i) mixed logit allows for all forms of correlation, including scale heterogeneity, (ii) G-MNL is a restricted form of mixed logit that, with an appropriate implementation, can allow for scale heterogeneity but (in its typical form) not other sources of correlation, (iii) none of the models disentangles scale heterogeneity from other sources of correlation, and (iv) models that assume that the only source of correlation is scale heterogeneity necessarily capture, in the estimated scale parameter, whatever other sources of correlation exist.

Subfields: Economics and Econometrics, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/f99c804899fbe74d1307610ca73ce11c5fb709be

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Citations in the corpus

A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings (2019, background): “Sillano and Ortúzar, 2005; Train and Weeks, 2005; Train, 2009), mainly to estimate the distribution of 18 WTPs directly11 and to avoid the ex-post division by a distributed cost coefficient (Hess and Train, 2017), 19 often leading to more unreasonable WTP distributions (Daly et al.”