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ECON5121A: Econometric Theory and Applications

Chinese University of Hong Kong, Fall 2020

CC BY-NC-SA 4.0

Reading and Assignment will be updated each week as the class progresses.

Reading

  • Week 0: [IE] Ch.1--Ch.6
  • Week 1: [E] Ch.1, Ch.2.1--17; Ch.2.31
  • Week 2: [E] Ch.2.18--21; Ch.2.24--30
  • Week 3: [E] Ch.3.1-18, 3.24; Appendix A.1-13, 20, 22
  • Week 4: [IE] Ch.10.1--6, 16; [E] Ch.4.1--4, 7, 11, 14, 16, 20, 21; Ch.5.1--12
  • Week 5: [IE] Ch. 7.1--9; [E] Ch.4.8--10
  • Week 6: [IE] Ch. 7.10--12; Ch. 8.1--14; Ch. 9.1; [E] Ch.6; Ch 7.1-4, 10, 12--14
  • Week 7: [IE] Ch. 10.7, 8, 12, 13, 17, 18; [E] Ch. 7.13
  • Week 8: [IE] Ch.13; [E] 9.1--8, 19--21
  • Week 9: [IE] Ch.14; [E] Ch.9.9--10, 16--18
  • Week 10: [E] Ch.17. 1--12, 15--17, 20, 21, 24, 25, 36, 37; Ch.12.1, 2, 4-6, 40, 41
  • Week 11: [E] Ch.12.7--10, 12, 15--18; Ch.13.1--12
  • Week 12: [E] Ch.13.19--22, 25

Assignment

  • Week 1: [IE] Ex1.5, 9; Ex.2.8, 11, 16; Ex 4.7, 12; Ex 5.5, 6, 15; [E] Ex 2.1, 2, 6, 10--14
  • Week 2: [E] Ex 2.4, 7, 18, 21; lecture notes Ex 2.3
  • Week 3: [E] Ex 3.2, 3-9, 11, 21
  • Week 4: [IE] Ex 10.1, 3; [E] Ex 4.3--5, 12, 13, 15, 16, 23, Ex 5.1--3, 8
  • Week 5: [IE] Ex 7.1, 3, 4, 5(a)--(d); [E] Ex 4.18, 20
  • Week 6: [IE] Ex 7.7, 12; Ex 8.1, 7, 8; [E] Ex 7.1, 2, 3, 6, 14, 20
  • Week 7: [IE] Ex 10.6, 13, 16; [E] Ex 7.11, 15, 19, 23
  • Week 8: [IE] Ex 13.1, 2, 5; [E] Ex 9.2, 3, 9, 13
  • Week 9: [IE] Ex 14.1, 4, 7; [E] Ex 9.4, 5, 7, 17, 19
  • Week 10: [E] Ex 17.1(a), 2, 6, 13; Ex 12.5
  • Week 11: [E] Ex 12.3, 4, 7, 8, 11, 20; Ex 13.2, 3
  • Week 12: No assignment

online_teaching

“All theory is gray, my friend. But forever green is the tree of life.” ---Johann Wolfgang von Goethe: Faust: Part I

Description

This is an entry-level Ph.D. econometrics course. Under the asymptotic framework, it covers estimation and inference of the regression models and the instrumental variable models. It focuses on theory --- applying statistical theory to econometric models. It is NOT about how to apply econometric methods to empirical data.

Textbooks

The lectures are based primarily on Bruce Hansen's textbooks:

Both are downloadable for free.

Lecture Notes

My lecture notes and code demonstrations can be found at

Caveat: This is an ongoing writing project. The text is incomplete, and may contain errors. Use them at your own risk!

I encourage anyone, in particular students taking my class, to contribute or improve the notes. Send me pull requests.

Lecture Hours

Friday 8:30—11:15 am.

The course will be taught online until further notice.

Dates: September 11, 18, 25; October 9, 16, 23, 30; November 6, 13, 20, 27; Dec 4 (12 lectures)

Assessment

  • Attendance (15%): open webcam in each class
  • Assignment (35%): hand in one week after assignment
  • Final (50%): open-book, but no electric devices are allowed

Prerequisites

Undergraduate level multivariate calculus (two semesters), linear algebra (one semester), and probability and statistics (one semester). Undergraduate econometrics is a plus, though not necessary.

Computing Environment

Options:

  • SCRP. Each CU student has an account. Copy and paste the lines in the Rscript when logging into RStudio.
  • Local RStudio. Use the Rscript for git repo and package. May have conflict with pre-existing installation.
  • Local Docker. Use Docker image built from Dockerfile. Clean environment. Need to install Docker.

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0