Economic Policy Visualization

Introduction

Dr. Matthias Schnetzer

March 6, 2023

Course info


About this course

“A picture is worth a thousand words”

This course approaches contemporary issues of economic policy by analyzing innovative or iconic data visualizations. We analyse selected illustrations, discuss the underlying data, the theoretical background and policy implications. We will assemble plots in class and study the basics of data visualization.

You will gain:

  • an overview of contemporary debates in economic policy
  • a basic understanding of principles of data visualization
  • knowledge how to enrich academic publications with informative graphs

Who are you?

What do you expect of this course? Do you already have some coding experience in R?

Schedule

Date Time Room Content Assignment
Mar 06, 2023 10:00-12:00 TC.4.15 Introduction
Mar 13, 2023 10:00-12:00 TC.4.15 Data
Mar 20, 2023 10:00-12:00 TC.4.15 Visualization
Mar 27, 2023 10:00-12:00 D4.0.022 Growth · Geometries
Apr 17, 2023 10:00-12:00 TC.3.07 Inflation · Colors
Apr 24, 2023 10:00-12:00 TC.3.06 Labour · Labels
May 08, 2023 10:00-12:00 TC.3.11 Income · Scales
May 15, 2023 10:00-12:00 D4.0.127 Wealth · Themes
Jun 05, 2023 10:00-12:00 D4.0.127 Mobility · Maps
Jun 12, 2023 10:00-12:00 TC.3.07 Climate · Facets
Jun 19, 2023 10:00-12:00 D4.0.127 Student presentations
Jun 26, 2023 10:00-12:00 D4.0.127 Student presentations

Assignments

Assignment 1 provides the setup of the R infrastructure that is required in this course. There are no points for this assignment.

Assignments 2 to 4 are recreations of examplary figures. These examples are related to figures that are discussed in class. Students should then try to reproduce the plots at home and improve their individual coding skills.

The raw data for the figures are available as CSV files. The charts should then be uploaded to the learning platform before 9 a.m. on the day of the deadline.

Chart & Report

Chart presentation

  • Research question Which economic policy question do you want to answer with your chart?
  • Data
  • Chart
  • Conclusion What can we learn from the data visualization for economic policy?

Deadline: Date of the presentation

RMarkdown (or Quarto) Report

  • Title
  • Author
  • Introduction
  • Research question
  • Data
  • Result
  • Conclusion
  • Code

Deadline: June 30, 2023

Grading


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)

Feedback, cooperation and help

Let me know your feedback on the course anytime. If possible, I will try to incorporate your feedback immediately. At least, I will consider it for future courses.

As some of you might already have advanced coding skills in R, please support each other and collaborate. This does not mean that one person does all the coding and shares with all colleagues. Students should have an intrinsic motivation to improve their coding skills but cooperate to learn from each other.

There is a forum on the learning platform for exchange among students. Please also consult support platforms like Stack Overflow or take a look at the cheatsheets: