Applied Discrete-Choice Modelling
Applied Discrete-Choice Modelling

Author: David A. Hensher

Publisher: Routledge

Published: 2018-04-09

Total Pages: 280

ISBN-13: 1351140744

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Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authorsā€™ own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.

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.

Econometric Models For Industrial Organization
Econometric Models For Industrial Organization

Author: Matthew Shum

Publisher: World Scientific

Published: 2016-12-14

Total Pages: 154

ISBN-13: 981310967X

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Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Interpreting Discrete Choice Models
Interpreting Discrete Choice Models

Author: Garrett Glasgow

Publisher: Cambridge University Press

Published: 2022-05-12

Total Pages: 131

ISBN-13: 1108877184

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In discrete choice models the relationships between the independent variables and the choice probabilities are nonlinear, depending on both the value of the particular independent variable being interpreted and the values of the other independent variables. Thus, interpreting the magnitude of the effects (the ā€œsubstantive effectsā€) of the independent variables on choice behavior requires the use of additional interpretative techniques. Three common techniques for interpretation are described here: first differences, marginal effects and elasticities, and odds ratios. Concepts related to these techniques are also discussed, as well as methods to account for estimation uncertainty. Interpretation of binary logits, ordered logits, multinomial and conditional logits, and mixed discrete choice models such as mixed multinomial logits and random effects logits for panel data are covered in detail. The techniques discussed here are general, and can be applied to other models with discrete dependent variables which are not specifically described here.

Identification and Estimation of Multinomial Choice Models with Latent Special Covariates
Identification and Estimation of Multinomial Choice Models with Latent Special Covariates

Author: Nail Kashaev

Publisher:

Published: 2022

Total Pages:

ISBN-13:

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Identification of multinomial choice models is often established by using special covariates that have full support. This paper shows how these identification results can be extended to a large class of multinomial choice models when all covariates are bounded. I also provide a new āˆšn-consistent asymptotically normal estimator of the finite-dimensional parameters of the model.