Final answer:
The cross-sectional model cannot include variables that do not change over time, unlike the fixed effects and random effects models which are designed to handle panel data that includes such variables.
Step-by-step explanation:
The model that cannot include variables that do not change over time is the cross-sectional model. In econometrics and statistics, different panel models are used to analyze data that tracks the same subjects over a period of time. A cross-sectional model, however, is characterized by data that is observed at a single point in time. Therefore, it is not designed to handle variables that are constant over time because it does not involve a time dimension.
The fixed effects model and the random effects model both deal with panel data, which means they can integrate variables that are constant over time by accounting for individual-specific effects. The pooled model assumes that the individual observations are independent across time, which can allow for analysis with or without time-invariant variables, depending on the specification.