NCHU Course Outline

Course Name	(中) 經濟預測方法(3096)
	(Eng.) Economic Forecasting Methods
Offering Dept	Department of Finance
Course Type	Elective			Credits	3	Teacher	Tsung-Chih Lai
Department	Department of Finance / Undergraduate			Language	Chinese	Semester	2026-SPRING
Course Description	This course provides a practical introduction to economic forecasting, focusing on data-driven methodologies rather than formal time series theory. Students will learn how to explore time series data, construct benchmark forecasts, and implement widely used models to evaluate predictive performance. Using real-world datasets and R programming, students will develop the analytical skills necessary to interpret forecasts and support evidence-based decision-making in financial and economic contexts.
Prerequisites

Relevance of Course Objectives and Core Learning Outcomes(%)			Teaching and Assessment Methods for Course Objectives
Course Objectives	Competency Indicators	Ratio(%)	Teaching Methods	Assessment Methods
1. Identify key time series features such as trend and seasonality. 2. Build and evaluate benchmark and standard forecasting models. 3. Compare methods and communicate findings effectively.			Exercises Lecturing Discussion	Written Presentation Oral Presentation Assignment
Course Content and Homework/Schedule/Tests Schedule
Week Course Content Week 1  No class (Holiday, 2/27) Week 2  Getting started Week 3  Time series graphics Week 4  Time series decomposition Week 5  Time series features Week 6  No class (Holiday, 4/3) Week 7  The forecaster’s toolbox (I) Week 8  The forecaster’s toolbox (II) Week 9  Midterm proposal (4/24) Week 10  No class (Holiday, 5/1) Week 11  Time series regression models Week 12  Exponential smoothing Week 13  ARIMA models Week 14  Dynamic regression models Week 15  Some practical forecasting issues Week 16  Final presentation (6/12) self-directed learning    03.Preparing presentations or reports related to industry and academia.
Evaluation
Assessment: 1. Midterm proposal (30%) 2. Final presentation (30%) 3. Homework assignments (30%) 4. Class participation (10%) Course Policies: 1. Students are required to bring their own laptops for in-class exercises. 2. Lecture materials will be posted on the course website; please check regularly. 3. Homework and projects are group-based (max 6 groups); late submissions require prior approval. 4. Within-group and between-group peer evaluations are required and will affect individual grades. 5. Active engagement in discussions and workshops contributes to the final grade.
Textbook & other References
Hyndman, R. J. and Athanasopoulos, G. (2021), Forecasting: Principles and Practice. 3rd Edition. OTexts.
Teaching Aids & Teacher's Website
https://otexts.com/fpp3/
Office Hours
Friday, 14:10–15:00
Sustainable Development Goals, SDGs(Link URL)
04.Quality Education   08.Decent Work and Economic Growth include experience courses：N

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