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University of Montana
ECONOMICS 560: ADVANCED ECONOMETRICS
Section 1
Contact Information:
Douglas Dalenberg |
Spring 2008 |
Office: LA 408 phone: 243-4406 |
MTWF 12:10- 1:00 |
Office hours: MTWF 1:00-2:00 |
Classroom: LA 401 |
or by appointment or discovery |
4 Credits |
Email: doug.dalenberg@mso.umt.edu |
CRN: 30966 |
Text: Kennedy, Peter, A Guide to Econometrics, Cambridge, Mass: The MIT Press, 5th edition, 2003.
In addition you will need access to Wooldridge’s Introductory Econometrics.
Prerequisite: Econ 460 or consent of the instructor.
Description and Objectives: This course is designed to expose students to econometric techniques that move beyond standard ordinary least squares regression analysis. This applied course will use examples to help students understand the various techniques, when to apply them, why we use them, how to test and interpret the results, and how to present the results. The course uses the statistical software Stata and students will become proficient at getting data into Stata, cleaning up the data, examining the data with graphs and tables, and estimating models using the appropriate technique. In addition students will be exposed to some programming tricks to help with data management and presentation of results.
The course has three objectives:
1. Familiarize students with the standard techniques used by economists that move beyond OLS regression analysis.
2. Expand students’ knowledge and techniques for presenting estimation results.
3. Increase students’ proficiency with data management, estimation and presentation.
Grading:
Assignment |
Percent of Grade |
Due date |
Attendance / Participation |
15% |
Every meeting |
Homework Assignments |
60% |
Various |
Empirical Paper |
25% |
Draft due 4/18, Final version due 5/2 |
I will use plus/minus grading with 100-92=A, 91-90=A-, 89-88=B+, 87-82=B, 81-80=B-, 79-78=C+, 77-72=C, 71-70=C- 69-68=D+, 67-62=D, 61-60=D-, 59 and below=F.
Fridays: Fridays will be used for discussion of “Friday Readings”, answering questions, expanding on explanations, going over homework, dealing with your empirical paper and getting more out of Stata. Monday through Wednesdays will be a mix of lecture and computer applications; however, much of the computer work is reserved as homework.
Policies:
1. We will meet Tuesday, May 6 from 10:10-12:10 even though there is no final exam. There will be a homework assignment due that day.
2. Academic dishonesty will result in a score of zero for the assignment or exam in question. University policy states: “All students must practice academic honesty. Academic misconduct is subject to an academic penalty by the course instructor and/or a disciplinary sanction by the University. All students need to be familiar with the Student Conduct Code. The Code is available for review online at http://www.umt.edu/SA/VPSA/index.cfm/page/1321.”
3. The last day to add or drop classes or change the grade option is March 4. From March 5 through May 2 students must petition to drop or change grade options. No petitions are allowed after May 2. To petition to drop a course you will need a Dean’s signature in addition to your advisor’s and instructor’s signature. My understanding is that the Dean of the College of Arts and Sciences accepts only four reasons for a drop (medical, change in work, emergency, no evaluation) and requires written verification.
4. University policy requires that you cannot change to audit status after February 11.
5. University policy now states “A CR is given for work deserving credit (A through D-) and an NCR for work of failing quality (F). CR and NCR grades do not affect grade point average.”
6. Please set your cell phones on vibrate rather than ring and please leave the classroom to talk on a phone.
7. Late work is penalized according to the cost it imposes on me. Work is considered late if I receive it after I have finished grading those assignments handed in on time.
Advice:
1. If my office hours conflict with your schedule, see me for an appointment.
2. Be active. This is a graduate level course and like most upper level courses what you put into the course will determine what you get out of the course. Unfortunately it is difficult to learn econometrics by just listening and taking notes; one must do econometrics in order to learn econometrics.
3. Do the reading and do the homework.
Schedule of Topics
Week 1: Introduction and Review of OLS
Week 2: Standard Cross Section
Week 3: Standard Time Series
Week 4: Maximum Likelihood – Theory and Testing; Review of Logit
Week 5: Logit and Probit
Week 6: Introduction to Multinomial and Count Models
Week 7: Introduction to Multinomial and Count Models
Week 8: Introduction to Instrumental Variables and Simultaneous Equations
Week 9: Introduction to Instrumental Variables and Simultaneous Equations
Spring Break
Week 10: Advanced Time Series
Week 11: Advanced Time Series
Week 12: Panel Data Methods
Draft version of paper due.
Week 13: Panel Data Methods
Week 14: Matrix Representation of OLS
Week 15: Finals week. Wrap-up
Last homework due. Final version of paper due.