教學大綱 Syllabus

每周課程進度與作業要求 Course Schedule & Requirements

• The tentative course schedule is outlined as follows. The weekly coverage might change as it depends on the progress of the class.

• Expected hours of study are 7.5 hours per week (including 3-hour lectures).

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Week 1 (9/11) - Course Introduction, Overview & Regression Fundamentals

Week 2 (9/18) - Review of Linear Regression, Least Squares and Instrumental Variables

Week 3 (9/25) - Review of Linear Regression, Least Squares and Instrumental Variables (cont'd)

Week 4 (10/2) - Robust and Clustered Standard Errors

Week 5 (10/9) - Robust and Clustered Standard Errors (cont'd); Empirical Research Proposal Due

Week 6 (10/16) - Simulation and Bootstrap Methods 

Week 7 (10/23) - Resampling-Based Inference

Week 8 (10/30) - Student Midterm Presentations (for Proposal & Replication Results)

Week 9 (11/6) - Discrete Choice Analysis

Week 10 (11/13) - Basic Panel Data Models

Week 11 (11/20) - Basic Panel Data Models

Week 12 (11/27) - Difference in Differences

Week 13 (12/4) - Nonparametric Regression

Week 14 (12/11) - Regression Discontinuity Design

Week 15 (12/18) - Production Function Estimation

Week 16 (12/25) - Quantile Regression Models

Week 17 (1/1) - Working on Empirical Research Project (No Class)

Week 18 (1/8) - Working on Empirical Research Project (No Class); Empirical Research Paper Due

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• Problem sets

• The problem sets will include both problem solving and computer tasks. The assignments will be reviewed in class if necessary.

• You are encouraged to form a study group with your classmates, but you must write up your own answers. Problem sets with identical answers will NOT be accepted.

• Group empirical research project (with 4-5 students per group)

• There will be a group project on empirical research, aiming to provide students with experience in applying the statistical and econometric methods examined in the course.

• The task is to take a published article of interest, replicate its numerical results, and then extend the analysis in some way. Possible extensions include different data and modifications of model specification.

• The empirical research paper will be evaluated with respect to clarity of exposition, thoroughness of description of the data and methods, competence in using the methods, and thoughtfulness in interpreting results. Complexity of economic theory and econometric methods does not carry weight in the evaluation.