Syllabus

Title
5620 Advanced Economic Policy
Instructors
Dr. Matthias Schnetzer
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/15/23 to 02/21/23
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
Day Date Time Room
Monday 03/06/23 10:00 AM - 12:00 PM TC.4.15
Monday 03/13/23 10:00 AM - 12:00 PM TC.4.15
Monday 03/20/23 10:00 AM - 12:00 PM TC.4.15
Monday 03/27/23 10:00 AM - 12:00 PM D4.0.022
Monday 04/17/23 10:00 AM - 12:00 PM TC.3.07
Monday 04/24/23 10:00 AM - 12:00 PM TC.3.06
Monday 05/08/23 10:00 AM - 12:00 PM TC.3.11
Monday 05/15/23 10:00 AM - 12:00 PM D4.0.127
Monday 06/05/23 10:00 AM - 12:00 PM D4.0.127
Monday 06/12/23 10:00 AM - 12:00 PM TC.3.07
Monday 06/19/23 10:00 AM - 12:00 PM D4.0.127
Monday 06/26/23 10:00 AM - 12:00 PM D4.0.127
Contents

Economic Policy Visualization (https://mschnetzer.github.io/adveconpol/)

“A picture is worth a thousand words”. This course approaches contemporary issues of economic policy by analyzing innovative or iconic data visualizations. Based on selected illustrations, we discuss the underlying data, the theoretical background and policy implications in various fields of empirical economics. In a second step, we will assemble plots in class and study the basics of data visualization. Students are required to recreate figures at home to improve their skills in coding. The main task is that students will design a comprehensive data visualization with the ggplot-Package in R and draft a report around that figure in RMarkdown. Student will need to bring their laptop to class and prior knowledge of data handling in R is beneficial.

To sum up, students will gain:

  • an overview of contemporary debates in economic policy based on recent empirical research
  • a basic understanding of principles of data visualization and the use of figures in economic policy debates
  • knowledge how to enrich academic publications with informative graphs
Learning outcomes

After completing this course, students will:

  • know key figures in various fields of economic policy
  • be aware of the potentials and limitations of available data for specific policy discussions
  • show improved programming skills in R and the ability to create a RMarkdown report
  • have basic knowledge of important principles of data visualization
  • be able to create simple charts to enrich their academic articles
Attendance requirements

Attendance and active participation are mandatory. Missing two classes with prior notification is accepted.

Teaching/learning method(s)

The lecturer introduces into various fields of economic policy and provides examples of data visualizations that serve as starting point for discussions. As the graphic illustration of statistical data gains in importance in both the academic and the public discourse, students will learn best practices and gain insights into the visualization of data. Another take-away of the course is to strengthen the knowledge about the power and limitations of the underlying data. A part of each session is dedicated to the work with data. The lecturer provides R-code to produce figures in class. Studens are expected to recreate three charts at home. The main assignment is the production of a comprehensive data visualization on a selected topic of economic policy. Studens will present their chart in class and draft a report with a detailed description of the data, the code and the final visualization in RMarkdown.

The course offers a lot of room for discussion in order to permit students to assess various arguments and perspectives, form their own opinion, and argue in a group setting. The teaching is designed to encourage students to actively participate in the debates, raise questions, and gain experience in visualizing data for academic publications or the general debate.

Assessment
  • Assignments: 30% (0-10 points for each visualization)
  • Chart presentation: 30% (0-20 points for the quality of the presentation, 0-10 for the preliminary chart)
  • Written report: 40% (0-40 points for the report and the final chart)
Readings

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Last edited: 2023-02-09



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