Survey of Econometric Methods
Fall 2017
Jeffrey Parker
Course Outline and Reading List
Note: Dates shown below are tentative. Depending on our actual progress, the dates of reading assignments may change.
Readings with authors listed in bold face are required. Those in regular type are optional readings that may be read by those with strong interests in the subject. Additional readings maybe added as the course progresses. Be sure to check the Web site regularly in order to keep up with any changes; don't just print this page at the beginning of the course and rely on that for the entire semester.
Useful Resources
- There are useful free downloads on the support site for the Studenmund text, including data sets that we will use in class and an extensive introduction to Stata using examples from the text.
- UCLA has a very useful site introducing Stata and its various capabilities.
- The Economics Department has adopted a preferred method for citations. The definitive sources is the Chicago Manual of Style, 16th edition. Some (slightly dated) examples are in the Economics Department Citation Guide.
- The Reed Library (and economics librarian Joe Marquez) has an excellent collection of resources for economics students.
- I also have posted a brief guide with suggestions on how to approach reading economics journal articles.
- Urdan, Timothy C. 2010. Statistics in Plain English. New York: Routledge. Available on print reserves and also as an ebook through the library Web site
1. Introduction to Econometrics
- Introduction to Econ 311 (August 28)
- No reading required
- Introduction to regression models (August 30)
- Studenmund, 7th edition, Chapter 1
- Data visualization and presentation (September 1)
- Schwabish, Jonathan A. 2014. "An Economist's Guide to Visualizing Data." Journal of Economic Perspectives 28 (1):209-34.
- Tufte, Edward, Data Visualization, Chapter 2 and other chapters.
- Sources of economic data (September 6)
- Griliches, Zvi. 1986. "Chapter 25 Economic Data Issues." Handbook of Econometrics 3:1465-1514. This book is on reserve (but only one copy). Here is an annotated collection of key quotations that you should read for class.
2. Ordinary Least Squares
- Basics of OLS regression (September 8 and 11)
- Studenmund, Chapter 2
- Using OLS regression (September 13)
- Studenmund, Chapter 3
3. Probability and Statistics
- Basic introduction to probability and statistics (September 15, 18, and 20)
4. The Classical Regression Model and Statistical Inference
- Assumptions of classical OLS regression (September 22 and 25)
- Studenmund, Chapter 4
- Statistical inference under classical assumptions (September 27, 29, and October 2)
- Studenmund, Chapter 5
First mid-term exam (October 6)
5. Choosing Regression Models
- Alternative specifications and non-linear models (October 9, 11, and 13)
- Studenmund, Chapters 6 and 7
6. Regression Pathologies
- Collinearity and multicollinearity (October 23)
- Studenmund, Chapter 8
- Serial correlation (October 25 and 27)
- Studenmund, Chapter 9
- Heteroskedasticity (October 30)
- Studenmund, Chapter 10
Second mid-term exam (November 1)
7. Time-Series Models
- Basic time series (November 3 and 6)
- Studenmund, Sections 12.1 through 12.3
- Vector autoregressions and Granger causality (November 8 and 10)
- Studenmund, Section 12.4
- VAR reading packet
- Non-stationary time series (November 13)
- Studenmund, Section 12.5
8. Models with Limited Dependent Variables
- Dummy dependent variables (November 15)
- Studenmund, Chapter 13
- Ordinal and bounded dependent variables (November 17)
9. Instrumental Variables and Simultaneous Equations
- Simultaneous equations, identification, and 2SLS (November 20, 22, and 27)
- Studenmund, Chapter 14
10. Models for Panel Data
- Experimental data, fixed- and random-effects models (November 29 and December 1)
- Studenmund, Chapter 16
11. The Practice of Econometrics
- How to design and execute a research project (December 4 and 6)
- Studenmund, Chapter 11
- Instructor's notes on empirical research (from 312 class notes)
- Stock and Watson, Introduction to Econometrics, 3rd ed., Chapter 9