Syllabus

Title
5793 Microeconometrics (Applied Track)
Instructors
PD Dr. Simon Heß
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/17/25 to 02/23/25
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Wednesday 03/05/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 03/12/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 03/19/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 03/26/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 04/02/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 04/09/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 04/23/25 12:00 PM - 02:00 PM D5.0.001
Wednesday 05/07/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 05/14/25 12:00 PM - 02:00 PM D4.0.133
Wednesday 05/21/25 12:00 PM - 02:00 PM D4.0.144
Wednesday 05/28/25 12:00 PM - 02:00 PM D4.0.019
Wednesday 06/04/25 12:30 PM - 02:30 PM TC.0.02
Contents

This course introduces and discusses the tools to answer causal questions across all not only in economics (from labor and health to development and finance) but also in the social sciences more broadly. Students will gain hands-on experience with key causal inference concepts and tools

  • Intro: Causality and correlation -- reatment effects, selection bias, and regression
  • Randomized control trials
  • Regression discontinuity designs
  • Difference-in-differences estimation
  • Instrumental variables
  • Extra: Power analysis and estimation uncertainty: bootstrap and randomization inference
Learning outcomes

By the end of this course, students will be equipped to apply key causal inference methods for their research interests.

They will gain familiarity with the most important microeconometric evaluation techniques used in academic literature, with a particular emphasis on recent advancements. Students will develop the ability to understand contemporary research papers employing these methods and critically assess their strengths and limitations across diverse evaluation contexts.

Attendance requirements

Classroom attendance is mandatory, as active participation is essential for mastering the material and engaging with the course content.

Up to three absences will be tolerated, but students are expected to independently review and catch up on any material covered during missed sessions. 

Teaching/learning method(s)

The course combines lectures and tutorials into a unified format. Key microeconometric evaluation techniques will be presented and practiced. Students will apply these methods through coding exercises and group assignments to reinforce their understanding and develop practical skills.

Assessment

The course assessment is based on three components:

  • Midterm Exam: 35%
  • Homework (4 Assignments): 25%
  • Final Exam: 40%

 

Each component must be passed independently. The final grade will be determined by the weighted average of the three scores, based on the following grade scale:

Letter GradeRange
1100% to 90%
2< 90% to 80%
3< 80% to 70%
4< 70% to 60%
5< 60% to 0%
Readings

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Last edited: 2024-11-25



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