Week 1: Introduction. OLS Recap.
Week 2: OLS in Matrix Form.
Week 3: OLS in Matrix Form and Probability Theory
Week 4: A first peek at Maximum Likelihood
Week 5: Maximum Likelihood Estimation and Heteroskedastic Regression
Week 6: Models for Binary Dependent Variables & Model Fit
Week 7: Interpretation and Simulation
Week 8: Ordered Choice Models & How to write a publishable Paper
Week 9: Multinomial Choice Models
Week 10: Conditional Logit Model
Week 11: Selection Bias and Multi-Equation Models
Week 12: Multi-level Models
Week 13: Baby Bayes – a primer
Week 14: Student Presentations
Last updated on 8 Feb 2022