Modeling Discrete Choices in the Presence of Inertia and Serial Correlation

T concept of habit or inertia in the context of (reluctance to) change in travel behavior has an important bearing on transport policy (e.g., how to break car use habits) and has remained an unresolved issue in demand modeling. Another major problem in modeling the response to policy measures is the potential correlation or dependence between the choices made by a given individual over time (i.e., serial correlation). The two phenomena are closely related. This paper discusses the effects of considering inertia and serial correlation on travel choices. We formulate a fairly general discrete choice model that incorporates randomly distributed inertia thresholds and allow for serial correlation. The inertia thresholds may also be a function of an individual’s socioeconomic characteristics and choice conditions. The model can be applied with panel data as well as with mixed revealed and stated preference data. We applied it to real and simulated data, confirming that if these phenomena exist in the population but are not considered, serious errors in model estimation and prediction may arise, especially in the case of large policy impacts.