In this course, students learn about and apply:

• Concept and application of correlations (using OLS)
• Methods of causal inference (IV, DiD, RDD)
• Formulating and designing their own research project
• Finding and Analyzing data to answer their research question
• Presenting and Writing down the results

The course is split into two parts:

1. Learning about the methods
2. Applying the methods

The first part will be an in-class lecture. The second part is students' own work, with frequent consultations.

• Differentiate between correlation and causality
• Read and interpret modern applied economics (finance) research
  • Interpret regression outputs
  • Evaluate and criticize
• Asking an empirical research question
• Finding and Analyzing data to answer said question

Students collect (bonus) points for class participation in various ways, which will be part of the final grade. Attendance is not strictly mandatory, but due to the tight schedule of the course, it’s highly encouraged to attend each class.

1. Lecture content
   1. 4-hour lecture sessions (28.11.,05.12,12.12, 19.12. if needed)
   2. Lecture exam (75 minutes); December 20^th or January 9^th
2. Research Project
   1. Research topic selection (29.11.)
   2. Topic assignment (30.11.)
   3. First meeting session about empirical projects (19.12.) (rest of lecture if needed)
   4. Status update presentations (10-15 Minutes) and discussions about ongoing research projects (09.01.)
   5. Group meetings (January + February as needed)
   6. Final project meetings (individual): Last week of February
   7. Turn in Research Paper: March 14^th, 8 pm

• Class Participation: 15 points
  • In lecture
  • During Research Project meetings
• Exam: 40 points
• Research Paper: 50 points
• Status update presentation: 5 points
• Total: 110/100

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