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This course is an introduction to practical empirical economic modeling and forecasting. It focuses on the methodology, practice, and implementation of econometric modeling and forecasting with macroeconomic time series. The course's first part (empirical model building) considers data properties, including integration and cointegration; dynamic specification, including error correction models; and model evaluation and design, including computer-automated model selection algorithms and impulse indicator saturation. The course's second part (empirical economic forecasting) focuses on the roles of forecasting, including in policymaking; the generation and evaluation of forecasts; sources of forecast error; and robustification and improvement of forecasts. Throughout, the course includes discussion of the underlying theory, live data-based presentations of substantive empirical analyses, and hands-on learning in class. The latter two aspects help demonstrate the approach to econometric modeling and forecasting and address empirical questions as they arise. Examples with single-equation and multiple-equation models using different countries' data motivate and illustrate the concepts involved. This course is open to enrollment by only MIEF students.