Aim and contents of the course

The aim of Applied Microeconometrics is to analyze individual behavior based on micro data (cross-section and panel data of individuals, households, and firms) and evaluate the effects of economic policies and interventions at the micro level. The course focuses on program evaluation methods aimed at causal identification of treatment effects and panel data models, but introduces students also to discrete-choice and limited-dependent models. Several applications in empirical microeconomics and the evaluation of the effects of economic policies are presented. Students learn how to apply these methods using real-world micro data and the software package Stata.

 

Topics

1. Causal inference – Potential Outcomes Framework
2. OLS and Causality
3. Randomized Control Trials
4. Instrumental Variable Estimation
5. Regression Discontinuity Design
6. Difference-in-Difference
7. Panel Data
8. Limited Dependent Variables (binary choice)

 

Requirements and Grading

• The course is appropriate for master students specializing in empirical microeconomics.
• Knowledge of basic estimation methods, such as the linear regression model and the maximum likelihood method is required.
• Grading will be based on the final exam (2h) which may be written in English or German.

 

Main Text Books

• Angrist, J.D. & J.-S. Pischke (2015). Mastering `metrics: The path from cause to effect. Princeton: Princeton University Press.
• Angrist, J.D. & J.-S. Pischke (2009). Mostly harmless econometrics: In empiricist’s companion. Princeton. Princeton University Press.
• Cunningham, S. (2021). Causal inference: The mixtape. Yale university press.
• Wooldridge, J.M. (2013). Introductory Econometrics. 5^th Edition. Mason (OH): south-Western Cengage learning.

 

Lecture slides and references to selected journal articles on empirical applications will be made available via Moodle.