SPEPE7033. Seminar on Advanced Quantitative Methods 

中文課名:高等計量方法專題

授課教師:陳釗而

研究室:台大次震宇宙館 223室

Course Description

This course is organized around three major themes in modern econometrics:

  1. Quantile regression and quantile treatment effects
  2. Factor models
  3. Causal machine learning and targeting

Each theme spans five weeks. In the first three weeks of each module, the instructor will introduce the core theory, intuition, and econometric techniques required to understand the topic. In the remaining two weeks, students will present assigned research papers and lead discussions. This structure is designed to balance methodological training with exposure to frontier empirical and methodological research.

Course Objective

By the end of the course, students will be able to:

  • Understand and apply advanced econometric tools related to distributional analysis, factor structures, and causal machine learning.
  • Critically read, interpret, and evaluate contemporary econometric research articles.
  • Implement the covered methods using programming or statistical software and apply them to real empirical problems.
  • Produce a term paper (written individually or in groups of up to three students) that demonstrates mastery of at least one of the methodological frameworks taught in the course.

Course Outline

Theme I: Quantile Regression and Quantile Treatment Effects

Week 1: Instructor-led lecture
Week 2: Instructor-led lecture
Week 3: Instructor-led lecture
Week 4: Student presentations
Week 5: Student presentations

Theme II: Factor Models

Week 6: Instructor-led lecture
Week 7: Instructor-led lecture
Week 8: Instructor-led lecture
Week 9: Student presentations
Week 10: Student presentations

Theme III: Causal Machine Learning and Targeting

Week 11: Instructor-led lecture
Week 12: Instructor-led lecture
Week 13: Instructor-led lecture
Week 14: Student presentations
Week 15: Student presentations

Week 16: Discussion

Readings

To be assigned.
Additional readings will be assigned for presentations.

Grading

Assessment consists of:

  • Two in-class presentations of assigned research papers (50%)
  • A term paper (individual or group work of up to three students), due in Week 18, applying at least one econometric method covered in this course, accompanied by a 15–20 minute recorded presentation explaining the term paper (50%)