Publication: A Bayesian Mixed Logit-probit Model for Multinomial Choice
All || By Area || By Year| Title | A Bayesian Mixed Logit-probit Model for Multinomial Choice | Authors/Editors* | M Burda, M Harding, J Hausman |
|---|---|
| Where published* | Journal of Econometrics |
| How published* | Journal |
| Year* | 2008 |
| Volume | 147 |
| Number | 2 |
| Pages | 232-246 |
| Publisher | Elsevier |
| Keywords | Multinomial discrete choice model, Dirichlet Process prior, non-conjugate priors, hierarchical latent class models |
| Link | http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6VC0-4THSX80-2-15&_cdi=5940&_user=994540&_orig=browse&_coverDate=12%2F31%2F2008&_sk=998529997&view=c&wchp=dGLbVzW-zSkWb&md5=b2d2ba3083fbd4c5b651d43557013af2&ie=/sdarticle.pdf |
| Abstract |
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 assumption-free 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. |
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