Analysis of urban travel time and travel distance: A fully parametric bivariate hazard-based duration modelling approach with correlated grouped random parameters

Hazard-based duration models have been successfully implemented to study event durations across many dis-ciplines. This paper focuses on integrating - for the first time, to the authors' knowledge - the hazard-based duration modelling method into a novel bivariate framework while accounting for the cross-equation error correlation, endogeneity, unobserved heterogeneity, and unbalanced panel effects, by employing correlated grouped random parameters. The developed framework provides the flexibility of using appropriate, case -specific distribution of the hazard function for each duration. Greater explanatory power is achieved through estimation of panel specific correlated random parameters, which can account for the interaction between the captured unobserved effects and their impact on durations. For demonstrative purposes, travel time and travel distance for trips in the year 2017 and made by household members from the Miami metropolitan area, FL, are modelled using the proposed method. The results show that using different distributions significantly affects the overall statistical fit, forecasting accuracy, and the interaction of error terms within the models.

Automated summary

This paper integrates hazard-based duration modeling method into a novel bivariate framework, accounting for cross-equation error correlation, endogeneity, unobserved heterogeneity, and unbalanced panel effects. The developed framework allows for flexibility in using appropriate distribution of hazard function for each duration. The estimation of panel specific correlated random parameters improves explanatory power by capturing the interaction between unobserved effects and durations.