Materials for TA session (update: March 15, 2021)

Github: github

Basic & Econometrics

• Computational Efficiency
• Cross Validation
• Feature Engineering
• OLS via Stochastic Gradient Descent
• Misspecified Model
• ARCH and GARCH Model
• Spatial data - Visualization

Causal Inference

• Instrumental Variables & Regression Discontinuity
• Differences in Differences

• Blocking estimator & Matching estimator
  • Pre-processing phase:
  • Assess covariate balance
  • Estimate propensity score
  • Trim sample
  • Stratify sample

Exmerimental Design

• A/B Testing
• Randomized Experiments

Machine Learning

• Principan Component Analysis (PCA)
• Regularized Regression
• Double LASSO
• Manifold Learning