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• Maximum Likelihood under Mis-specification
  1. Poisson MLE
  2. The Kullback-Leibler Divergence
  3. Asymptotics for Mis-specified MLE
  4. Asymptotic Variance Calculations for Poisson MLE
  5. The Information Matrix Equality
• Poisson Regression
  1. Review: Minimum MSE Prediction
  2. Predicting Count Data
  3. Asymptotics for Conditional MLE
  4. The Pseudo-True Parameter Value for Poisson Regression
  5. Partial Effects
  6. Asymptotic Variance Calculations for Poisson Regression
• Binary Outcome Models
  1. Binary Outcomes & the Linear Probability Model
  2. Index Models: Logit & Probit
  3. Asymptotic Variance Calculations for Index Models
  4. Pseudo R-squared
• Random Utility Models
  1. Overview of Random Utility Models
  2. Identification of Choice Models
  3. Index Models as a Special Case
  4. The Logit Family of Choice Models
  5. The Independence of Irrelevant Alternatives
• The Heckman Selection Model
  1. Sample Selection
  2. The Heckman Selection Model
  3. A Proof of Lemma 1
  4. A Proof of Lemma 2
  5. The Mean of a Truncated Normal
• Applied Examples in R
  1. Installing R and RStudio
  2. Count Data - Wooldridge (2010) Example 18.1
  3. Binary Outcomes - Wooldridge (2010) Example 15.1

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