A Bayesian mixed logit-probit model for multinomial choice

Arbeitspapier

In this paper we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumptionfree nonparametric density specification while other alternative-specific coefficients are assumed to be drawn from a multivariate normal distribution which eliminates the independence of irrelevant alternatives assumption at the individual level. A hierarchical specification of our model allows us to break down a complex data structure into a set of submodels with the desired features that are naturally assembled in the original system. We estimate the model using a Bayesian Markov Chain Monte Carlo technique with a multivariate Dirichlet Process (DP) prior on the coefficients with nonparametrically estimated density. We employ a 'latent class' sampling algorithm which is applicable to a general class of models including non-conjugate DP base priors. The model is applied to supermarket choices of a panel of Houston households whose shopping behavior was observed over a 24-month period in years 2004-2005. We estimate the nonparametric density of two key variables of interest: the price of a basket of goods based on scanner data, and driving distance to the supermarket based on their respective locations. Our semi-parametric approach allows us to identify a complex multi-modal preference distribution which distinguishes between inframarginal consumers and consumers who strongly value either lower prices or shopping convenience.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: cemmap working paper ; No. CWP23/08

Classification and Topics

• Classification: Wirtschaft ; Bayesian Analysis: General ; Estimation: General ; Semiparametric and Nonparametric Methods: General ; Statistical Simulation Methods: General ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
• Subject: multinomial discrete choice model ; Dirichlet Process prior ; non-conjugate priors ; hierarchical ; latent class models ; Probit-Modell ; Bayes-Statistik ; Markovscher Prozess ; Diskrete Entscheidung ; Konsumentenverhalten ; SB-Lebensmittelgeschäft ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Burda, Martin ; Harding, Matthew ; Hausman, Jerry
• Event: Veröffentlichung
• (who): Centre for Microdata Methods and Practice (cemmap)
• (where): London
• (when): 2008

Further information

• DOI: doi:10.1920/wp.cem.2008.2308
• Handle: http://hdl.handle.net/10419/64751
• Last update: 10.03.2025, 11:42 AM CET