Notes

1. Chapter 1
• Regression Model
• Expectations Review
• Model Specification
• Matrix Review
• Gretl script
2. Chapter 2:
•  Geometry of Least Squares
• FWL
• gretl script to do HW exercises in chapter 2.
3. Chapter 3
• CNLRM
• Statistical Properties of LS
• Model Specification
4. Chapters 4, 5, and 6
   
• Exact Tests
• Large Sample Tests
• Delta Theorem
• CES example, dataset, and gretl program
• gretl examples
  
5. GLS
• GLS-FGLS
• Heteroskedasticity
• SUR
6. ML Estimation
• ML 1
• ML 2
• ML 3
• ML 4
• Heteroskedasticity