Econometrics
Advanced Econometrics
Lecturer (assistant) | |
---|---|
Number | 0000002980 |
Type | Seminar |
Duration | 2 SWS |
Term | Sommersemester 2019 |
Language of instruction | English |
Position within curricula | See TUMonline |
Dates | See TUMonline |
Dates
(No dates found)
Admission information
See TUMonline
Note: Until May 5, 2019, via Moodle.
Note: Until May 5, 2019, via Moodle.
Objectives
Participants shall be able to select the appropriate econometric method given a certain problem and data set; to apply this method proficiently using STATA and/or R; to know the advantages and pitfalls of each method; and to judge if the econometric approach in published studies is correctly chosen and well executed.
Description
Econometric methods are important in many fields of management research. In order to derive meaningful and robust results, one has to know these methods and understand them well. This course shall convey advanced econometric methods, with a focus on approaches to address issues of selection and causality such as instrumental variables and propensity score matching. Depending on the participants’ needs, the emphasis can be shifted to some extent; we will discuss the selection of topics at the kick-off session. The focus will be on applicable knowledge, not so much on details of the theory.
Topics comprise various methods to address selection issues and come close to causality:
o Heckman selection models
o Instrumental variables
o Differences-in-Differences
o Regression discontinuity design
o Matching (e.g. propensity score matching, exact matching)
o Randomized controlled trials
Prerequisites
Participants need to have econometrics knowledge corresponding to an introductory Ph.D. level course in econometrics. Ideally, they should have participated in such a course, e.g. in “Applied Econometrics: An Introduction” by Professor Hottenrott.
Basic knowledge of econometrics. Ideally, participation in “Applied Econometrics: an introduction” taught by Prof. Alexy each winter term.
Teaching and learning methods
Learning methods are a mix of seminar presentations by the participants and lectures. For each seminar session, a group of two participants will prepare a presentation on a specific topic (e.g., Heckman regression) and suggest an article in which this method is applied. The lecturer will meet with each group beforehand to aid in the preparation. The group will bring a dataset with which participants will apply the respective method during the course (please bring laptops). We will use STATA. Participants shall prepare each session and in particular read the suggested paper such that we can have a discussion in class.
Examination
Participants will be assessed based on their seminar presentation (70%) and oral contributions to the course (30%).
Recommended literature
For a selection of suggested readings please see below. Further readings will be announced during the course. • Cameron/Trivedi (2008): Microeconometrics – Methods and Applications (Theory) • Cameron/Trivedi (2008): Microeconometrics in Stata (applications in Stata) • Wooldridge (2003): Introductory Econometrics (2nd ed.) • Stock / Watson (Time series)