Discrete Choice Analysis 2019 

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Introduction. Choice behavior and discrete choice models (Ben-Akiva)
Specification and estimation of choice models (Ben-Akiva)
Specification testing (Ben-Akiva)
Computer Lab I: Introduction; Logit estimation and testing
Nested Logit Models (Ben-Akiva)
Multivariate Extreme Value Models - Aggregate Forecasting and Microsimulation (Ben-Akiva)
Stated preferences methods (McFadden)
Computer Lab II: Nested logit; Aggregate forecasting
Mixture Models (Bierlaire)
Simulation-based estimation (Bierlaire)
Combining RP and SP (Ben-Akiva)
Computer Lab III: Logit mixtures; Combining data
Sampling and estimation; Endogeneity (Ben-Akiva)
Discrete Panel data (Bierlaire)
Bayesian estimation (McFadden)
Computer Lab IV: Hierarchical Bayesian Estimation; Individual Prediction
Behavioral Foundations (McFadden)
Models with latent variables (Ben-Akiva)
Questions and answers
Computer Lab V: Hybrid Choice Models [OPTIONAL]

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