The field of econometrics largely started with time series analysis because many early datasets were time-series macroeconomic data. As the field developed, more cross-sectional and longitudinal datasets were collected, which today dominate the majority of academic empirical research. In nonacademic (private sector, central bank, and governmental) applications, time-series data is still important. Consequently, undergraduate courses must still teach time-series econometric tools if educators are to best serve students. This article reviews the key models that the author believes are most critical for economics students: (1) autoregressive models; (2) distributed lag models; and (3) autoregressive distributed lag models.