Chris Conlon

PhD Econometrics - Fall 2025

Syllabus

Github Page (for .tex files)

Bruce Hansen's Econometrics (Textbook)

Lecture Notes

• Lecture 1: Review and Simulation Methods (Hansen Ch 2, 6)
  
  • Course Introduction [Notes]
  • Review of Probability Theory [Notes]
  • Review of Statistics [Notes]
• Lecture 2+3: Linear Regression (Hansen Ch 3, 4, 7)
  
  • Linear Regression [Notes]
• Lecture 4: Statistical Inference and Testing
  
  • Variance of OLS [Notes] [Code]
  • Hypothesis Testing [Notes]
• Lecture 5: Wage Equation and R Tutorial
  
  • Wage Equation Example [Notes] [Code] [Data]
• Lecture 6: Maximum Likelihood Estimation
  
  • Intro to MLE [Notes]
  • Logit and Probit [Notes] [Notebook] [Code]
  • Count Data / Poisson Regression [Notes]
• Lecture 7: Program Evaluation, Experiments, and Selection
  
  • Program Evaluation and Randomized Experiments [Notes] [Power Calculation Code]
  • Selection Corrections [Notes] [Code]
• Lecture 8: Instrumental Variables
  
  • Instrumental Variables and 2SLS [Notes] [Code]
• Lecture 9: Quasi Experiments
  
  • Event Study Designs [Notes]
  • Matching Designs [Notes]
  • Difference in Difference [Notes]
• Lecture 10: Quasi Experiments (Continued)
  
  • Synthetic Control [Notes]
  • Regression Discontinuity [Notes]
  • Two Way Fixed Effects [Notes]
• Lecture 11: Model Selection
  
  • Classic Model Selection: AIC and BIC [Notes]
  • Penalized Approaches: Lasso and Ridge [Notes]
  • Bonus: Workflow [Notes]

Assignments

• [PS1] Due 9/25 [Data]
• [PS2] Due 10/9 [Gas Data] [Cornwell Rupert Data]
• [PS3] Due 11/6 [Hogwarts Data] [AK1 Data]
• [PS4] Due 11/26 [Datasets]