A dynamic analysis of motorcycle ownership and usage: A panel data modeling approach

This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models – ordinary, fixed, and random effects – are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled.

► This study develops motorcycle ownership and usage models based on a large-scale, nationwide two-wave panel survey in Taiwan. ► Three types of discrete choice models − multinomial, nested, and mixed logit − are developed for motorcycle ownership. ► Three types of panel data regression models − ordinary, fixed, and random effects − are developed for motorcycle usage. ► The state dependence effect and heterogeneity do exist in motorcycle ownership and usage decisions, respectively. ► The management strategies of increasing gas prices and parking fees will lead to larger reductions in total motorcycle kilometers traveled and total motorcycle crashes.