Automobiles play a pivotal role in daily life, which makes them a subject of interest in many academic fields. Transportation planners are interested in knowing how many and what types of automobiles are owned by households, how people adjust their fleet, and how they use their vehicles. The primary objective of this study was to develop a comprehensive dynamic model of household automobile transactions at a disaggregate level to be used in a dynamic microsimulation modeling framework that can provide a direct forecast of consumer demand for personal-use vehicles. A market-based decision-making process and a transaction approach were applied for this project because of their consistency with the actual processes followed by decision makers. In the proposed framework, each year a decision maker faces four choices: add a new vehicle to the fleet, dispose of one vehicle, trade one of the vehicles in the fleet, or do nothing. A mixed (random parameters) logit model was used to investigate the effects of heterogeneity in the dynamic transaction model and distinguish between heterogeneity- and state-dependence-based explanations for the observed persistence in choice behavior. In this study, the application of dynamic variables representing the occurrence of changes in household state and their impacts on the observed behavior were also investigated.