This paper evaluates the ability of the maximum approximate composite marginal likelihood (MACML) estimation approach to recover parameters from finite samples in mixed cross-sectional and panel multinomial probit models. Comparisons with the maximum simulated likelihood (MSL) estimation...

In the context of panel ordered-response structures, the current paper compares the performance of the maximum-simulated likelihood (MSL) inference approach and the composite marginal likelihood (CML) inference approach. The panel structures considered include the pure random coefficients (RC)...

The current study contributes to the existing injury severity modeling literature by developing a multivariate probit model of injury severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the injury severity of...

The increasing diversity of vehicle type holdings and the growing usage of vehicles by households have serious policy implications for traffic congestion and air pollution. Consequently, it is important to accurately predict the vehicle holdings of households as well as the vehicle miles of...

Auto ownership modeling plays an important role in travel demand analysis because it is a key determinant of the travel behavior of individuals and households. Discrete-choice auto ownership models use either an ordered-response choice mechanism or an unordered-response choice mechanism. The...