Premium
A New Utility‐Consistent Econometric Approach to Multivariate Count Data Modeling
Author(s) -
Bhat Chandra R.,
Paleti Rajesh,
Castro Marisol
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2405
Subject(s) - multinomial probit , count data , multivariate statistics , econometrics , multinomial distribution , multivariate probit model , discrete choice , probit model , econometric model , multinomial logistic regression , probit , computer science , event (particle physics) , statistics , economics , mathematics , poisson distribution , physics , quantum mechanics
Summary In the current paper, we propose a new utility‐consistent modeling framework to explicitly link a count data model with an event‐type multinomial‐choice model. The proposed framework uses a multinomial probit kernel for the event‐type choice model and introduces unobserved heterogeneity in both the count and discrete‐choice components. Additionally, this paper establishes important new results regarding the distribution of the maximum of multivariate normally distributed variables, which form the basis to embed the multinomial probit model within a joint modeling system for multivariate count data. The model is applied to analyzing out‐of‐home non‐work episodes pursued by workers, using data from the National Household Travel Survey. Copyright © 2014 John Wiley & Sons, Ltd.