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ECON 460

ECONOMIC FORECASTING

3-4 credits.

Introduction to econometric time series analysis, forecasting methods, and forecast evaluation. Covers theoretical, methodological, and applied topics, and much of the work will be hands-on data analysis.

Prerequisites & course information

Requisites: ECON 400 , 410 , or graduate/professional standing Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Level - Advanced L&S Credit - L&S Liberal Arts and Science Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. explain and use linear time-series econometric models Audience: Both Grad & Undergrad 2. describe and use economic time-series data and data sources Audience: Both Grad & Undergrad 3. formulate, estimate, and evaluate models for economic forecasting Audience: Both Grad & Undergrad 4. make point forecasts, interval forecasts and fan charts Audience: Both Grad & Undergrad 5. select and use conditioning information Audience: Both Grad & Undergrad 6. use model selection and combination methods Audience: Both Grad & Undergrad 7. be a "fox" rather than a "hedgehog" Audience: Both Grad & Undergrad 8. explain, formulate, and use Vector Autoregressive time-series models Audience: Graduate 9. explain, formulate, and use multivariate time-series forecasting models Audience: Graduate Learning Outcomes: 1. explain and use linear time-series econometric models Audience: Both Grad & Undergrad 2. describe and use economic time-series data and data sources Audience: Both Grad & Undergrad 3. formulate, estimate, and evaluate models for economic forecasting Audience: Both Grad & Undergrad 4. make point forecasts, interval forecasts and fan charts Audience: Both Grad & Undergrad 5. select and use conditioning information Audience: Both Grad & Undergrad 6. use model selection and combination methods Audience: Both Grad & Undergrad 7. be a "fox" rather than a "hedgehog" Audience: Both Grad & Undergrad 8. explain, formulate, and use Vector Autoregressive time-series models Audience: Graduate 9. explain, formulate, and use multivariate time-series forecasting models Audience: Graduate

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