A pdf version of this file can be found at README.pdf
The final exam will be “take-home”, and be made available by 6pm on Monday, May 11. It will be due 24 hours later, by 6pm Tuesday May 12.
- “Hansen” refers to Gary Hansen’s Econometrics Textbook.
- Unresolved references of the form “cite:foo84” or similar are keys with values that can be looked up in are212.bib. This last is a bibtex database which you’re free to use. The bibtex file includes some links to pdf files which you may find useful.
Benjamin Krause’s Personal Meeting Room
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- Section Notes on R can be found on bcourses
- Zoom recording on March 20, 2020 (first remote section)
- Section Notes on Python can be found in the folder above
- Python 01.ipynb and the zoom recording on April 03, 2020
- Python 02.ipynb and the zoom recording on April 10, 2020
- Python 03.ipynb and the zoom recording on April 17, 2020
- Build off of skills we developed with R to provide a basic familiarity of coding in Python (and deepen your overall understanding of coding for econometrics in the process)
- Move from (potentially) no previous Python experience to being able to follow lecture applications and engage in bcourses discussions via Python
- See the Discussion Section Syllabus for general information.
- Office Hours are going to continue to be by appointment, and primarily via email.
- UC Berkeley Covid-19 News and Information
- Covid-19 info for UC Berkeley Grad Students
- Counseling and Psychological Services: These services continue to be available for all of us. If you’re struggling, they’re here to help.
- Phone: (510) 642-9494
- Counseling after-hours support line: (855) 817-5667
- Crisis Text Line: (Not affiliated with the University) For 24/7 support for those in crisis, text HOME to 741741 anywhere in the United States. “Social distancing may be lonely, but you’re not alone.“
See ARE212 Youtube Channel for videos of lectures, etc.
- GitHub
- How to view, files, fork, edit, and issue pull requests (PRs). https://youtu.be/krDQk5ZzP8U
- GitHub to DataHub
- How to use datahub to run & edit code from github: https://youtu.be/lY4D-Li3UgY
- Notes on Multiple Linear Equation Models
- Reading
- Hansen Ch. 11. General contemporary reference on systems of linear regressions.
- fullcite:haavelmo44. Classic discussion of the “probability approach” to estimating economic models; one of the key documents distinguishing econometrics from statistics; one of the key
- fullcite:christ94. Discussion of the birth of econometrics at the Cowles Commission; beyond its historical importance, worth reading to understand the source of much of the jargon we now use.
- cite:stock-trebbi03,wright1921,wright1928 (Appendix B). On the origins of instrumental variables. The Wright papers are some of the earliest and clearest discussions of identification.
- Jupyter notebooks
- Notes on Causality & Correlation
- Reading
- fullcite:frisch30. Highly insightful and only recently published lectures Frisch gave at Yale in 1930.
- fullcite:haavelmo43. A founding document of the structural (Cowles Commission) approach to economics.
- fullcite:haavelmo44. Classic statement regarding the “probability approach” to economics.
- fullcite:goldberger72. Insightful, historically informed reflections on identification of structural models in economics.
- fullcite:pearl15,heckman-pinto15,pearl13. Back and forth between Pearl & Heckman/Pinto. They agree on one thing: Frisch & Haavelmo were right.
- fullcite:pearl09. Pearl’s textbook on causality.
- fullcite:friedman53. Classic essay on the usefulness of “falsifying” economic models and the role of assumptions.
- Stanford Encyclopedia of Philosophy, “The Problem of Induction”
- Hume, An enquiry concerning human understanding
- Sewell Wright https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1200501/pdf/111.pdf
- fullcite:imbens-rubin15. Up-to-date statement and discussion of the Neyman-Rubin potential outcomes model, with focus on the assignment model.
- fullcite:heckman10. Contemporary survey comparing “reduced form” and “structural” approaches to causal inference.
- fullcite:heckman97. Critique of potential outcome approach in program evaluation.
- Jupyter notebooks
- Notes on Identification and Instrumental Variables
- Reading
- Hansen Chapter 12
- fullcite:angrist-krueger01
- fullcite:conley-etal12
- fullcite:chernozhukov-hansen08
- Data
- Notes on GMM
- Reading
- Hansen Chapter 13
- Review normal linear regression model (E.g., Hansen Chapter 5)
- fullcite:chamberlain87
- fullcite:newey-west87a
- Further notes on GMM Estimation
- Jupyter notebook exploring GMM in finite samples (github/datahub)
- Notes on Data Generating Processes and the Bootstrap
- Reading
- Hansen Chapter 10