A New Econometric Approach to Multivariate Count Data Modeling




Bhat, Chandra R.
Paleti, Rajesh
Castro, Marisol

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In the current paper, we propose a 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 several 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 for analyzing out-of-home non-work episodes pursued by workers, using data from the National Household Travel Survey.


At the time of publication Chandra R. Bhat and Marisol Castro were at the University of Texas at Austin, and Rajesh Paleti was at Parsons Brinckerhoff.

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