Advanced Study of Econometrics 2

Announcements | Syllabus | Schedule | Problem Sets | Homework | Links

Announcements

(9/25/14) My office hours this semester are MR 12:10-12:55.

Syllabus

Objective

Learning the correct use of econometrics.

Textbook

Greene, William H., Econometric Analysis, 7th ed., Pearson Education, 2011

Related Courses

Advanced Study of Econometrics 1

Grading

There will be three mid-term exams and a final exam. It is necessary to submit all homeworks (answer ALL questions). Students can work together on homeworks, but must turn them in separately.

Schedule

You must download and install Adobe Acrobat Reader to view the course materials.

Abbreviations used in my lecture notes: iff (if and only if), s.t. (subject to), s.th. (such that), w.l.o.g. (without loss of generality), w.r.t. (with respect to), WTS (want to show).

  1. (9/26)Course guidance, Linear Algebra #1 (A.1-A.3) (slides)
  2. (9/29)Linear Algebra #2 (A.4-A.7) (slides)
  3. (10/3)Vector Differentiation (A.8) (slides)
  4. (10/6)Probability (B.1-B.8, B.10) (slides)
  5. (10/10)Normal Distributions (B.9, B.11) (slides)
  6. (10/17)Point Estimation (C.1-C.5) (slides)
  7. (10/20)Hypothesis Testing (C.6-C.7) (slides)
  8. (10/24)Asymptotic Theory (D) (slides)
  9. (10/27)Midterm 1
  10. (11/6)MM and ML Estimators (13.1-13.2, 14.1-14.5) (slides)
  11. (11/7)Regression Models and OLS (2, 3) (slides)
  12. (11/10)Finite-Sample Properties of OLS Estimators (4.1-4.3) (slides)
  13. (11/14)Asymptotic Properties of OLS Estimators (4.4) (slides)
  14. (11/17)Classical Asymptotic Tests (14.6) (slides)
  15. (11/21)Classical Asymptotic Tests in CLRMs (5.1-5.7) (slides)
  16. (11/26)Midterm 2
  17. (11/28)IV Estimation (8.1-8.5) (slides)
  18. (12/1)Generalized Linear Regression Models (9.1-9.4, 9.6) (slides)
  19. (12/5)GMM Estimation (13) (slides)
  20. (12/8)Testing for Heteroskedasticity (9.5) (slides)
  21. (12/12)Multivariate LRMs (10.1-10.2) (slides)
  22. (12/15)Panel Data (11.1-11.5) (slides)
  23. (12/19)Midterm 3
  24. (12/22) Nonlinear Regression Models (7.1-7.2.3, 7.2.6, 12.5, E.3) (slides)
  25. (12/26) Hypothesis Testing in NRMs (7.2.4-7.2.5) (slides)
  26. (1/9) Specification (3.5.1, 4.3.2-4.3.3, 4.7.2, 5.10, 6.2) (slides)
  27. (1/15) Time Series (20.1-20.5) (slides)
  28. (1/19) Testing for Serial Correlation (20.7) (slides)
  29. (1/23) Estimation of Models with AR(1) Errors (20.8-20.9) (slides)
  30. (1/26) Simultaneous Equations Models (10.6.1-10.6.5) (slides)
  31. (1/30) Qualitative Response Models (17.1-17.3, 18.1-18.3.1) (slides)
  32. (2/2) Limited Dependent Variables (19.1-19.3, 19.5) (slides)
  33. (2/6) Count Data (18.4) (slides)
  34. (2/9) Duration Data (19.4) (slides)

Problem Sets

  1. (9/26) Problem Set 1
  2. (9/29) Problem Set 2
  3. (10/3) Problem Set 3
  4. (10/6) Problem Set 4
  5. (10/10) Problem Set 5
  6. (10/17) Problem Set 6
  7. (10/20) Problem Set 7
  8. (10/24) Problem Set 8
  9. (11/6) Problem Set 9
  10. (11/7) Problem Set 10
  11. (11/10) Problem Set 11
  12. (11/14) Problem Set 12
  13. (11/17) Problem Set 13
  14. (11/21) Problem Set 14
  15. (11/28) Problem Set 15
  16. (12/1) Problem Set 16
  17. (12/5) Problem Set 17
  18. (12/8) Problem Set 18
  19. (12/12) Problem Set 19
  20. (12/15) Problem Set 20
  21. (12/22) Problem Set 21
  22. (12/26) Problem Set 22
  23. (1/9) Problem Set 23
  24. (1/15) Problem Set 24
  25. (1/19) Problem Set 25
  26. (1/23) Problem Set 26
  27. (1/26) Problem Set 27
  28. (1/30) Problem Set 28
  29. (2/2) Problem Set 29
  30. (2/6) Problem Set 30
  31. (2/9) Problem Set 31

Homework

  1. (Due on 10/6) Homework 1
  2. (Due on 10/20) Homework 2
  3. (Due on 11/6) Homework 3
  4. (Due on 11/17) Homework 4
  5. (Due on 11/28) Homework 5
  6. (Due on 12/12) Homework 6
  7. (Due on 1/9) Homework 7
  8. (Due on 1/30) Homework 8
  9. (Due on 2/6) Homework 9

Links

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