2020•RePEc: Research Papers in EconomicsRequires access

MIXMIXLOGIT: Stata module to estimate mixed-mixed multinomial logit model

Timothy L. Neal

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Abstract

mixmixlogit is a Stata command that implements the mixed-mixed multinomial logit model (MM-MNL) for binary dependent variable data. It was first proposed in Keane and Wasi (2013) and Greene and Hensher (2013), and applied recently in Keane et al. (2020). It generalises both 'mixed logit' and 'latent class logit' by allowing for multiple latent types in the underlying data that are each characterised by a distribution of random parameters (as opposed to latent class logit, which assumes a homogeneous coefficient vector for each latent type, and mixed logit that allows for a distribution of random parameters for a single type of consumer or agent).

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What this paper is about

mixmixlogit is a Stata command that implements the mixed-mixed multinomial logit model (MM-MNL) for binary dependent variable data. It was first proposed in Keane and Wasi (2013) and Greene and Hensher (2013), and applied recently in Keane et al. (2020). It generalises both 'mixed logit' and 'latent class logit' by allowing for multiple latent types in the underlying data that are each characterised by a distribution of random parameters (as opposed to latent class logit, which assumes a homogeneous coefficient vector for each latent type, and mixed logit that allows for a distribution of random parameters for a single type of consumer or agent).

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Available abstract

mixmixlogit is a Stata command that implements the mixed-mixed multinomial logit model (MM-MNL) for binary dependent variable data. It was first proposed in Keane and Wasi (2013) and Greene and Hensher (2013), and applied recently in Keane et al. (2020). It generalises both 'mixed logit' and 'latent class logit' by allowing for multiple latent types in the underlying data that are each characterised by a distribution of random parameters (as opposed to latent class logit, which assumes a homogeneous coefficient vector for each latent type, and mixed logit that allows for a distribution of random parameters for a single type of consumer or agent).

Key concepts: Mixed logit, Multinomial logistic regression, Latent class model, Logit, Latent variable, Multinomial distribution, Econometrics, Statistics

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