Applied Econometrics II
This course gives students hands-on experience in the application of common econometric techniques, as a preparation for empirical postgraduate work or for applied economic research in a professional environment.
- Final Exam: June 16, 15-17pm at CEI
- Presentations: May 26, June 2, and 9, 15-17pm at BFSH1, Salle 252
- Submission of the raw dataset: February 4, 2004.
- Submission of topic and proposal of data: December 17, 2003.
Resources (password protected):
Weeks 22 & 23: Multinomial Choice
Week 21: The Bootstrap
- Handout Bootstrap
- Article by Brownstone and Valletta, J. Appl. Econ. 16, 129-141(2001)
- Take home exercise: Application 13, Stata do-file for application 13
Week 20 (21.04.2004): How to write a applied econometrics paper
- We will discuss the structure of the following article as an example (print it and bring it to class)
Article by Kenkel and Terza, J. Appl. Econ. 16, 165-184 (2001)
- How do I write a scientific paper (by the SciDevNet)
- Slides on "How to write an Applied Econometrics Paper"
Week 19 (07.04.2004): Instrumental Variables and GMM
Week 18 (31.03.2004): Introduction to GMM
Week 17 (24.03.2004): Sample Selection
- Handout see week 16
- Article by Francis Vella (1998), Journal of Human Resources, 33, 127-169.
- Take home exercise: Application 12
- Data for application 12: sevs.dta
- Stata log file for application 12
Week 16 (17.03.2004): Truncation and Censoring
- Handout Limited Dependent Variable Models
- Article by Chay and Powell (2001), Journal of Economics Perspectives, 15/4, 29-42
- Take home exercise: Application 11
- Data for application 11: fair_pt.dta
- Article by Fair (1978), JPE, 86/1, 45-61
- Stata log file for application 11
Week 15 (10.03.2004): Binary Response
- Handout Binary Response
- Article by Mike Gerfin, J. Appl. Econ. 11, 321-339 (1996)
- Take home exercise: Application 10
- Data for application 10: gerfin_jae_1996.dta
- Stata log file for application 10
- Matlab implementation of application 10
Week 14: Refresh of Maximum Likelihood Estimation
- You have to make sure that you revise maximum likelihood estimation for the next term. Here are just a few hints of the type of knowledge I call for: Notes on MLE.
Weeks 12 & 13: Panel Data Model
- Slides Panel Data Models
- Take home exercise: Application 9
- Data for application 9: wagepan.dta
- Stata log file for application 9
- Article by Vella and Verbeek, J. Appl. Econ. 13, 163-183 (1998)
Week 11: Simultaneous Equation Models
- Slides Simultaneous Equation Models
- Take home exercise: Application 8
- Stata log file for application 8
Week 10: Instrumental Variables I
- Handout IV
- Instrumental Variables are hot, hot, hot: Economist 1/8/2004
- Additional introductory readings:
- Angrist and Krueger (2001), Journal of Economics Perspectives, 15/4, 69-85.
- Hausman (2001), Journal of Economics Perspectives, 15/4, 57-67.
- Take home exercise: Application 7
- Data for application 7: klein.dta
- Stata log file for application 7
Week 9: Mulitcollinearity
- Introductory readings:
- Greene (2003), section 4.9.1.
- Kennedy (2003), chapter 13.
- Advanced readings:
- Judge, Griffiths, Hill, Lütkepohl and Lee (1985), The Theory and Practice of Econometrics, 2nd ed., chapter 22, New York: John Wiley.
Week 8: Autocorrelation
- Handout Autocorrelation
- Data Greene (2003), chapter 12
- Replication of example in Greene (2003), chapter 12
- Take home exercise: none, remember the project deadline
Week 7: Heteroskedasticity
- Handout Heteroskedasticity
- Data Greene (2003), chapter 11
- Replication of example in Greene (2003), chapter 11
- Take home exercise: Application 6
- Stata log file for application 6
Week 6: Introduction to Monte Carlo Experiments
- Handout Monte Carlo
- Take home exercise: Application 5
- Stata do-file for application 5
- Results for application 5
Week 4 & 5: Specification and Functional Form in OLS
- Readings on specification and model selection:
- Greene (2003), chapter 8.1, 8.2 and 8.4.
- Kennedy (2003), chapter 5 and 6 (without notes).
- Handout Functional Form
- Take home exercise: Application 4
- Data for application 4
- Stata log for application 4
- Take home exercise: Application 3
- Data for application 3: anscombe1, anscombe2, anscombe3, anscombe4
- Stata log for application 3
Week 3: Refresher on OLS
- Handout OLS Regression
- Application 2
- Data for application 2 (xls 14 kb)
- Take home exercise: finish application 2
- Stata log for application 2
Week 2: Introduction and Data Handling
- Article by Peter Kennedy (2002)
- No take home exercise
Week 1: Introduction and Stata