In the case of fixed-effects models, random-effects models, between estimators, and dynamic panel estimators, the PANEL procedure can process data with different numbers of time series observations across different cross sections. The Parks and Da Silva methods cannot be used with unbalanced data. The missing time series observations are recognized by the absence of time series ID variable values in some of the cross sections in the input data set. Moreover, if an observation with a particular time series ID value and cross-sectional ID value is present in the input data set, but one or more of the model variables are missing, that time series point is treated as missing for that cross section.