Grading
Critiques 10%
Replications 30%
Midterm 20%
Final 40%
You get graded based directly on your replications, and also indirectly through the exams, which will have code- and paper-based questions based directly on the replications that you have undertaken. As you can see, the purpose of this course is to get you to do econometrics, via the replications.
Assignments
A Replication is an exercise in which you attempt to repeat the empirical exercise undertaken by the author of the paper. Typically, you will only replicate a small number of lines in a table of results. A good start is to do the stata tutorials linked below. All requests for Stata help should be preceded by you googling "help stata whatever" and typing "help whatever" in Stata. In Stata, the help menus have examples at the bottom. Good starts here "help use", "help recode", "help keep" and "help regress".
Reading
1. Green, William, Econometric Analysis, Prentice Hall, 5th/6th Edition, 2008.
2. Kennedy, Peter, A Guide to Econometrics, 5th or 6th Edition (Paperback).
3. Angrist, Joshua and Jorn-Steffen Pischke, Mostly Harmless Econometrics: An Empiricist's Companion (Paperback).
I will try to let you know where to look for relevant supporting material in these textbooks. In addition, I will post links to other material you may find helpful.
Lecture Notes to Introduce Ordinary Least Squares.
Useful links for learning Stata are at UCLA economics Stata Tutorials .
Benjamin Philips' Tips for Using Stata.
A nice introduction to quantile regression is in Koenker and Hallock.
Assignment 1a is due in-class Wednesday 13 Jan
Write a 2-page critical review of the paper, focusing on empirical strengths, shortcomings and improvements. Do the authors try to do something interesting? Do they succeed? What would you have done?
For this assignment use the 2006 Census Public Use individual-level microdata, and its documentation. Replicate, as best as you can, the rightmost columns of Table 2 of the paper. Note that you do not have all of the variables and observations in the confidential main base used by the authors, so you will have to do your best with the data at hand. Please include your stata code and relevant output (not all the output, just what is important) and your table of results. Please note that you will not get exactly the same numbers because you don't have exactly the same data. Also your data are coded a bit differently and so you will have to use your judgment as to how to replicate that Table to the best of your ability. Hints: 1) try to get the right sample; 2) try to get the right covariates; 3) try to code each variable correctly.
Here is some sample code.
Lecture Notes on Panels.
Lecture Notes on Non-Spherical Errors.
Assignment 2a due in-class Wednesday 27 Jan
Assignment 2b due in-class Wednesday 3 Feb
These data are given at the state-year level. "nf1" gives the basic no-fault indicator. This replication will use the regress command in Stata, with weights a nd robust standard errors. Consider whether or not the authors should have clustered their standard errors and respond accordingly. "Count" gives the number of observations used to compute each datum in each state-year, and so should be used to weight all regressions (we'll learn about this later). Use hetero-robust standard errors with the ",r" subcommand (we'll learn about this later). Other variables give statistics about the distribution of the age at first marriage, computed at the state-year level. "p_**" gives the ** percentile of age at first marriage.
More on Venn Diagrams for Regression, Peter Kennedy, 2002. This paper presents the Ballentine Diagrams discussed in class, relating to Multicollinearity and Endogeneity.
Assignment 3a due in-class Monday 15 Feb
Lecture Notes on Seemingly Unrelated Regression.
Midterm
Useful Reading:
Sources for OLS: Greene, 5th Ed, Chapters 1-3; Kennedy, 5th Ed, Chapters 1-3; Angrist-Pischke Ch 1-3.
Sources for GLS, Heteroskedasticity, Panel Methods: Greene, Chapters 10-13: Kennedy, 5th Ed, Chapters 8, 14, 17, Appendix B; Angrist-Pischke Ch5 (for panel s tuff)
Sources for Endogeneity (and also SUR): Green, Chapters 14-15; Kennedy, 5th Ed, Chapters 9, 10; Angrist-Pischke Ch4.
Midterm, and Suggested Responses.
Survey Paper on Identification: The Identification Zoo.
Assignment 4a due in-class Wednesday 9 March
Replication, due at the beginning of class Thursday 28 March
Assignment 4b due in-class Wednesday 23 March
Your estimation and testing exercise is to:
1. Estimate a 5 good demand system (with 4 equations) using the EASI demand system, some demographics z, and price and budget variation using the GMM command in Stata. Write the full code yourself; do not use code from the web (though you may use this to help). Hand in the code with your assignment.
2. How important is unobserved preference heterogeneity compared to observed preference heterogeneity? Use graphs or tables to show this to the reader.
3. Is Slutsky symmetry true? Formally test the hypothesis of symmetry.
Lecture Notes on Demand Estimation.
Lecture Notes on OLS approaches to time-series econometrics.
Lecture Notes on Confidence Intervals and Testing.
Sources for Endogeneity (and also SUR): Green, Chapters 14-15; Kennedy, 5th Ed, Chapters 9, 10; Angrist-Pischke Ch4.
Sources for Testing: Greene, 5th Ed, Chapters 5,6,4; Kennedy, 5th Ed, Chapter 4.
Sources for SUR: Greene, Chapter 14; Kennedy, 5th Ed, Chapter 10.
Sources for Selection Correction (Heckman Two-Step): Green Chapter 19.5 "Sample Selection".
A bit of Stata code to show how sampling distributions work.
Lecture Notes on Limited Dependent Variables.
Maximum Likelihood Notes are now found in Lecture Notes to Introduce Ordinary Least Squares (end of the doc, where ML is introdu ced) and Lecture Notes on Endogeneity (end of the doc, with application to endogeneity and selection correction), both above.
Assignment 5a, due in-class 11 April
Assignment 5b, due in-class, at the final exam, 21 April, 10am
The Final Exam, 21 April 10am-1pm
Here is the final exam from 3 years ago (last time I taught this), and here is a set of suggested responses.