Syllabus

Title
2153 Topics in Macroeconometrics
Instructors
Univ.Prof. Dr. Jesus Crespo Cuaresma
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
10/11/22 to 11/06/22
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Wednesday 11/16/22 09:00 AM - 12:00 PM D4.2.008
Wednesday 11/30/22 09:00 AM - 12:00 PM D4.0.047
Wednesday 12/07/22 09:00 AM - 12:00 PM D4.0.047
Wednesday 12/14/22 09:00 AM - 12:00 PM D2.0.334 Teacher Training Lab
Wednesday 12/21/22 09:00 AM - 12:00 PM D4.0.047
Wednesday 01/11/23 09:00 AM - 12:00 PM D4.0.047
Wednesday 01/18/23 09:00 AM - 12:00 PM D4.0.047
Wednesday 01/25/23 09:00 AM - 12:00 PM D4.0.047
Wednesday 02/01/23 09:00 AM - 12:00 PM D4.0.047
Contents

This course offers a self-contained presentation of modern methods aimed at assessing specification uncertainty in econometrics, with a particular focus on applications to economic growth. The focus is on model averaging methods and, in particular, on Bayesian approaches to model uncertainty.

Learning outcomes

Students will be able to rigorously address model uncertainty in their inference using modern econometric methods.

Attendance requirements

Attendance is required throughout the course.

Teaching/learning method(s)

Frontal teaching in the first units, coupled with empirical exercises and group work, which will be presented by the students by the end of the course.

Assessment

Assessment is based on class participation (10%), presentation of preliminary results of an empirical assessment (40%) and a paper to be handed in by the end of the course (50%).

Recommended previous knowledge and skills

Proficiency in econometrics (graduate level) is required. Knowledge in Bayesian statistics is an advantage, but not a necessity.

Last edited: 2022-04-25



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