A Multivariate Hurdle Count Data Model with an Endogenous Multiple Discrete- Continuous Selection System
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This paper proposes a new econometric formulation and an associated estimation method for multivariate count data that are themselves observed conditional on a participation selection system that takes a multiple discrete-continuous model structure. This leads to a joint model system of a multivariate count and a multiple discrete-continuous selection system in a hurdletype model. The model is applied to analyze the participation and time investment of households in out-of-home activities by activity purpose, along with the frequency of participation in each selected activity. The results suggests that the number of episodes of activities as well as the time investment in those activities may be more of a lifestyle- and lifecycle-driven choice than one related to the availability of opportunities for activity participation.
At the time of publication Chandra R. Bhat, Subodh K. Dubey, and Raghuprasad Sidharthan were at the University of Texas at Austin, and Prerna C. Bhat was at Harvard University.