Applied Econometrics II

Objective

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.

> See also the detailed course outline
> Time and Place

Exam

• Final Exam: June 16, 15-17pm at CEI

Project

• 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

• Handout Multinomial Choice
• Data on example in class: travelmode.dta

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

• Article by Baum and Schaffer (2003), Stata Journal, 3/1, 1-31
• Home Assignment GMM 2
• Data

Week 18 (31.03.2004): Introduction to GMM

• Handout GMM
• Home Assignment GMM 1
• Data

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

• A Quick Guide to Stata 8 for Windows
• Take home exercise: Application 1
• Data for application 1 (xls 760 kb)
• Command log file for application 1