On the asymptotic variance of latent class logit models for discrete choice applications

Journal of Choice Modelling 2026 Open access

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Authors: Peio Alcorta, Petr Mariel
DOI: 10.1016/j.jocm.2025.100586
Cited by: 1
References: 31

Abstract

We derive the Hessian matrix and asymptotic variance of linear-in-parameters latent class logit models. These analytical solutions enable precise estimation of standard errors, significantly improve post-estimation computational efficiency, and may offer deeper theoretical insights into model behaviour and stability.

Fields of Study & Subjects

Economic and Environmental Valuation Consumer Market Behavior and Pricing Auction Theory and Applications

Publication details

Journal / source
Journal of Choice Modelling
Publisher
Elsevier BV
Volume
58
Pages
100586–100586
Publication date
9 January 2026
Language
EN