Essays on Discrete Choice Models
Essays on Discrete Choice Models

Author: Wei Song

Publisher:

Published: 2017

Total Pages: 162

ISBN-13:

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This dissertation focuses on the identification and estimation of discrete choice models. In practice, if the error term is independent of the covariates and follows some known distribu- tion, the discrete choice model is usually estimated using some parametric estimator, such as Probit and Logit. However, when the distribution of the error is unknown, misspecification would in general cause the estimators inconsistent even if the independence between the covariates and the error still holds. The two chapters relax the assumptions on the error distribution in the discrete choice models and propose semiparametric estimators.

Three Essays on Discrete Choice Modeling with Latent Constructs
Three Essays on Discrete Choice Modeling with Latent Constructs

Author: Yutaka Motoaki

Publisher:

Published: 2016

Total Pages: 246

ISBN-13:

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This dissertation consists of three individual studies that are concerned with discrete choice models with latent variables. In all three studies, a special attention is paid to specification and estimation of latent constructs. The first study aims to extends the methodological framework for latent class model by incorporating latent variables in the class assignment rule. The second study focuses on goodness of fit of discrete choice models with latent variables. The last study is concerned with discrete choice models with latent variables applied in the context of hurricane evacuation. The work presented here aims to explore the complexity and challenges of modeling latent constructs that are often overlooked.

Three Essays on the Application of Discrete Choice Models with Discrete-continuous Heterogeneity Distributions
Three Essays on the Application of Discrete Choice Models with Discrete-continuous Heterogeneity Distributions

Author: Chen Wang

Publisher:

Published: 2016

Total Pages: 226

ISBN-13:

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Unobserved heterogeneity is comprehensively acknowledged as an important feature to be considered in discrete choice modeling. Over the last decade, there were abundant studies showing the great outperformance of capturing unobserved heterogeneity of Mixed-Mixed Logit(MM-MNL) models. However, most empirical researches still use mixed logit(MIXL) models or latent class(LC) models which introduced strong assumptions on distributions of marginal utility. In this dissertation, a Mixed-Mixed Logit model(MM-MNL) that assumes a non-parametric mixing distribution for marginal utility is discussed. Consequently, three empirical studies solving different transportation problems are introduced.