Credits: 3 (3-0-0)

Prerequisites: For UG students: HUL315 / HUL215

Description

  1. Review of Classical Linear Regression Model: Gauss-Markov assumptions, finite sample properties, large sample properties.
  2. Instrumental Variable Estimation: Motivation for instrumentation, Simultaneity Bias, Endogeneity and Measurement Error; IV Estimation; 2SLS Estimation.
  3. Generalized Method of Moments: Single equation linear GMM.
  4. Systems of Equations: Seemingly unrelated Regressions (SUR) model; Simultaneous Equations Models: Identification.
  5. Panel Data models: Pooled Estimation; unobserved Heterogeneity: Fixed vs. Random Effects; ML vs. GMM estimation.
  6. Discrete Choice Models: Binary response models, Multinomial Response Models, ordered Response Models.
  7. Censored Regression Models: Estimation and Inference with Censored Tobit.
  8. Estimating Average Treatment Effects: Regression Methods, Methods Based on the Propensity Score, Estimating the ATE using IV.