Lectures:Fridays, 12:30-3:00 pm, McClelland 401KK
Office Hours: Tuesdays, 2-3:30 pm, or by appointment
Course Description:
This topics course in econometrics covers a number of techniques useful for analysis of microeconomic data. The methods discussed here would also be useful in other fields that use observational or experimental data. The course focuses on methods that do not require strict parametric assumptions, such as M-estimators, nonparametric regression estimators, and bootstrapping. We will also consider simulation-based methods for estimating parametric models. The course will discuss both asymptotic theory and practical implementation of the methods.
Final Exam:
The final exam will be a take-home final, handed out on Monday, May 1 at
4 pm and due Wednesday May 3, by
5 pm. I will make copies of the exam available outside my office and on this web page.
The exam will not require you use a computer to analyze data, but may ask you to provide "pseudo-code" to implement various estimators.
Handouts:
Syllabus
Lecture Note 1
Lecture Note 2 (note: corrected on 1/20)
Lecture Note 3
Homework 2
Lecture Note 4 (corrected on 2/3)
Lecture Note 5
Homework 3
Lecture Note 6
Lecture Note 7
Homework 4
hw4.dat
Lecture Note 8
hw4.m - sample program to solve HW4
logit_mle.m - Logit MLE routine
logit_weighted.m - weighted logit routine
Lecture Note 9
Lecture Note 10
Homework 5
hw5.dat - data file
Lecture Note 11
Lecture Note 12
Homework 6
Homework 5 Solutions
hw5a.m
hw5b.m
stdn_cdf.m
Lecture Note 13
Lecture Note 14
Final Review Questions
HW6 Solutions
Final Exam (Take-Home)