Time series models�models which take advantage of variation over time in a single unit�and pooled time series (sometimes called cross-sectional time series or time series cross-sectional) models�which utilize variation across both time and spatial units�are very common in political science. While these models offer substantial leverage over important social science problems that use purely cross-sectional data, there are a number of pitfalls that are necessary to avoid during estimation. Recommended prerequisite: students should have a background in advanced regression statistics (such as PSCI 7085, PSCI 7095 and PSCI 7155).
