Applied Econometrics 41903-01

SPRING 2008

Course information

· Instructor

· Course Syllabus

Course material

1. Statistical inference: a brief review

Likelihood principle

2. Large sample theory: a brief review

Convergence in probability and almost surely convergence

3. Linear models

More on classical linear regression

4. General linear models + GMM

5. MCMC: a brief review

6. Hierarchical linear models

7. Spatial hierarchical models

8. Mixture models

EM algorithm for mixtures

9. Limited dependent variable models

10. Factor models

Annotated bibliography

11. Normal dynamic linear models (DLMs)

Stochastic volatility: normal errors

Stochastic volatility: non-normal errors

12. Sequential Monte Carlo (SMC)

1^st order DLM: SIS filter

1^st order DLM: SIR filter

1^st order DLM: Auxiliary particle filter

Problem set

· HW1.PDF

· HW2.PDF

· HW3.PDF

Midterm exam: April 29^th 2008

Final Project: Due Monday June 23^rd 2008

Miscellaneous

· The R project

· Useful R tips (by Peter Rossi)

· WinBUGS project