Discrete Choice Models with Multiple Unobserved Choice Characteristics

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Counterfactual inference for consumer choice across many product categories (2019, background): “5In data from a single cross-section of consumers, Athey and Imbens (2007) show that only a single latent variable can be identified (or two if utility is restricted to be monotone in each) without functional form restrictions, arguing that panel data is critical to uncover common latent characteris”
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content (2012, methodology): “20 With regard to the unobserved characteristics required for out-of-sample prediction using the hybrid, BLP and PCM models, we applied the same method as suggested in Athey and Imbens (2007). We drew the unobserved characteristics for the ―holdout sample‖ randomly from the marginal distribution of ”
A Structural Model of Segregation in Social Networks (2010, methodology): “A more feasible strategy is to use data augmentation and Markov Chain Monte Carlo methods as in the discrete choice literature (Rossi et al. (1996), Athey and Imbens (2007)).”
A Bayesian mixed logit-probit model for multinomial choice (2008, methodology): “A multinomial discrete choice model with Bayesian estimation strategy has been analyzed recently by Athey and Imbens (2007).”