Econometrics
Advanced Econometrics
| Lecturer (assistant) | |
|---|---|
| Number | 0000002980 |
| Type | seminar |
| Duration | 2 SWS |
| Term | Summer semester 2021 |
| Language of instruction | English,Deutsch |
| Position within curricula | See TUMonline |
| Dates | See TUMonline |
Dates
Admission information
See TUMonline
Note: Registration until April 9, 2021, via Moodle.
Note: Registration until April 9, 2021, via Moodle.
Description
Econometric analysis aims at uncovering economic mechanisms, their causes and effects. Understanding the mechanisms behind a phenomenon is indispensable if one is to give advice to managers or policy makers, or to build theory. Simple regressions on cross-sectional data show associations, but not causality, so we need more sophisticated methods. This course shall convey econometric methods that allow causal inference, or at least to come closer to uncovering causal effects. The focus will be on applicable knowledge, less on details of the theory. Topics comprise various methods to address selection issues and come close to causality:
1. Randomized controlled trials and natural experiments
2. Matching
3. Regression discontinuity design
4. Instrumental variables
5. Panel data
6. Differences-in-Differences
7. Heckman selection models
1. Randomized controlled trials and natural experiments
2. Matching
3. Regression discontinuity design
4. Instrumental variables
5. Panel data
6. Differences-in-Differences
7. Heckman selection models
Prerequisites
Doctoral students only. Basic knowledge of econometrics. Ideally, participation in an introductory course on econometrics.
Teaching and learning methods
Learning methods are a mix of seminar presentations by the participants, group discussions, application of econometrics software, and lectures. We will use STATA, though if you prefer you may use R instead. Participants are expected to prepare each session and in particular read the assigned material and run the regression examples provided by Cunnningham such that we can have a discussion in class.