APEC 8213: Econometric Analysis III

This page contains an outline of the topics, content, and assignments for the course. Note that this schedule will be updated as the semester progresses, with all changes documented here.

Week Date Topic Reading Homework Discussion
1 21-Jan I. Estimation Methods: Maximum Likelihood Hansen, Prob. & Stat. for Econ., 10.1-10.19
1 23-Jan I. Estimation Methods: Binary Choice Models Hansen 25.1-25.9
2 26-Jan I. Estimation Methods: Generalized Method of Moments Hansen, 13.1-13.27 Problem Set 1 Assigned
2 28-Jan II. Multinomial and Ordered Logits and Probits Hansen, 26.1-26.10
2 30-Jan Review: MLE; Probit/Logit
Coding: MLE; Probit/Logit
3 2-Feb II. Censoring and Selection Models Hansen, 27.1-27.11 Problem Set 2 Assigned
3 4-Feb III. Nonparametric Density Estimation Hansen, Prob. & Stat. for Econ., 17.1-17.15 Problem Set 1 Due
3 6-Feb Review: GMM; Multinomial
Coding: GMM; Multinomial
4 9-Feb III. Nonparametric Regression Hansen, 19.1-19.25 Problem Set 3 Assigned
4 11-Feb IV. Time Series Econometrics Part 1 Hansen, 14.1-14.9 Problem Set 2 Due
4 13-Feb Review: Censoring/Selection; Nonparametric
Coding: Censoring/Selection; Nonparametric
5 16-Feb IV. Time Series Econometrics Part 2 Hansen, 14.10-14.18 Problem Set 4 Assigned
5 18-Feb IV. Time Series Econometrics Part 3 Hansen, 14.19-12.29 Problem Set 3 Due
5 20-Feb Review: Time Series
Coding: Time Series
6 23-Feb IV. Time Series Econometrics Part 4 Hansen, 14.30-14.43 Problem Set 5 Assigned
6 25-Feb V. Instrumental Variables for Panel Data, Dynamic Panel Models Hansen, 17.28-17.33, 17.36-17.42 Problem Set 4 Assigned Due
6 27-Feb Review: Panel IV
Coding: Panel IV
7 2-Mar VI. Machine Learning: Introduction, Ridge Regression and Lasso Hansen, 29.1-29.11
7 4-Mar VI. Machine Learning: More on Lasso, Regression Trees, Random Forests Hansen, 29.12-29.21 Problem Set 5 Due
7 6-Mar Exam Review
8 9-Mar Spring Break
9 16-Mar Final Exam