A Bayesian mixed logit-probit model for multinomial choice

Author

BURDA, Martin¹ ; HARDING, Matthew² ; HAUSMAN, Jerry³
[1] Department of Economics. University of Toronto, Sidney Smith Hall, 100 St. George Street, Toronto, ON M5S 3G7, Canada
[2] Department of Economics, Stanford University, 579 Serra Mall, Stanford, CA 94305, United States
[3] Department of Economics, MIT, 50 Memorial Drive, Cambridge, MA 02142, United States

Issue title

Estimating demand systems and measuring consumer preferences

Author (monograph)

SLOTTJE, Daniel (Editor)¹
[1] FTI Consulting and Department of Economics, SMU, Dallas, TX 75275, United States

Source

Journal of econometrics. 2008, Vol 147, Num 2, pp 232-246, 15 p ; ref : 3/4 p

CODEN

JECMB6

ISSN

0304-4076

Scientific domain

Control theory, operational research; Mathematics

Publisher

Elsevier, Amsterdam

Publication country

Netherlands

Document type

Article

Language

English

Author keyword

C11 C13 C14 C15 C23 C25 Dirichlet process prior Hierarchical latent class models Multinomial discrete choice model Non-conjugate priors

Keyword (fr)

Algorithme Analyse donnée Analyse multivariable Analyse numérique Chaîne Markov Choix discret Distribution statistique Donnée économique Echantillonnage Econométrie Estimation Bayes Estimation densité Estimation non paramétrique Estimation statistique Fonction répartition Indépendance Loi a priori Loi multinomiale Loi n variables Loi normale Modèle Markov Modèle logit Modèle mixte Modèle probit Ménage Méthode Monte Carlo Méthode statistique Méthode stochastique Prix Processus multivarié Sciences économiques Spécification modèle Structure donnée Test hypothèse Théorie approximation Théorie préférence 60E05 60J10 62E17 62H10 62P20 65C05 65C40 Modèle classe latente Modèle discret Modèle hiérarchique Processus Dirichlet

Keyword (en)

Algorithm Data analysis Multivariate analysis Numerical analysis Markov chain Discrete choice Statistical distribution Economic data Sampling Econometrics Bayes estimation Density estimation Non parametric estimation Statistical estimation Distribution function Independence Prior distribution Multinomial distribution Multivariate distribution Gaussian distribution Markov model Logit model Mixed model Probit model Household Monte Carlo method Statistical method Stochastic method Price Multivariate process Economic sciences Model specification Data structure Hypothesis test Approximation theory Preference theory Latent class model Hierarchical model Dirichlet process

Keyword (es)

Algoritmo Análisis datos Análisis multivariable Análisis numérico Cadena Markov Selección discreta Distribución estadística Dato económico Muestreo Econometría Estimación Bayes Estimación densidad Estimación no paramétrica Estimación estadística Función distribución Independencia Ley a priori Ley multinomial Ley n variables Curva Gauss Modelo Markov Modelo logit Modelo mixto Modelo probit Familia Método Monte Carlo Método estadístico Método estocástico Precio Proceso multivariable Ciencias económicas Especificación modelo Estructura datos Test hipótesis Teoría preferencia

Classification

Pascal

001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H01 Probability theory and stochastic processes / 001A02H01F Distribution theory

Pascal

001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H01 Probability theory and stochastic processes / 001A02H01J Markov processes

Pascal

001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02I Multivariate analysis

Pascal

001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02N Applications / 001A02H02N2 Insurance, economics, finance

Discipline

Mathematics

Origin

Inist-CNRS

Database

PASCAL

INIST identifier

21019599

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