|
Instructors: Dr. Deniz Dilan Karaman Örsal
Event type:
Interactive class
Displayed in timetable as:
Hours per week:
3
Credits:
6,0
Language of instruction:
English
Min. | Max. participants:
- | 45
Comments/contents:
The aim of the course is to train students in applied econometrics. In the first part of the course, the students will learn how to apply some widely used econometric tools (regression models, hypothesis testing, time series models etc). With the help of real world data and the open-source statistical software R the topics of the course will be covered.
The students will formulate a research question, prepare their own data and apply the methods that they have learned. Students are supposed to hand in their ideas by mid-November 2021 by mail to deniz.oersal@uni-hamburg.de
In the second part of the course, the students will present their research. Based on the feedback they will receive within the course, the students will write their final scientific paper.
As the course is fully digitized, access to the video conference software Zoom is necessary. All the material as well as the Zoom login information will be uploaded to OpenOlat. Please register to the OpenOlat portal. Students registered via STiNE are automatically added to the course on OpenOlat.
Learning objectives:
The main goal of this course is to provide the students with the necessary competencies and skills to do their own econometric research.
Didactic concept:
Organization of the course:
First part of the course
Day 1: 15.10.2022, 09:00 - 13:00 (Online)
Organizational Issues, Introduction to Econometric Analysis and Introduction to R
Day 2: 29.10.2021, 10:15 - 14:15 (Online)
Econometric Analysis with R - I
Day 3: 12.11.2021, 09:00 - 13:00 (Online)
Econometric Analysis with R - II
Day 4: 26.11.2021, 09:00 - 13:00 (Online)
Econometric Analysis with R - III
Second Part of the Course
Day 5: 21.01.2022, 10:00 - 15:00 (Online)
Day 6: 22.01.2022, 10:00 - 15:00 (Online)
Day 7: 28.01.2022, 10:00 - 15:00 (Online)
From Day 5 to Day 7 the students will present their scientific work in ten-minute short presentations.
This will also include the presentation of initial results as well as the addressing of outstanding issues.
Deadline to submit the final scientific paper: Friday, 18. February 2022, 11:00 a.m.
Prerequisites: Basic knowledge in inferential statistics and econometrics is necessary. Competencies in R are not required.
|
